What will we learn?

By the end of Lesson 1, you should be able to:

• characterize the relationship between GIS and transportation and explain why GIS-T is such an active field;
• discuss some of the challenges and opportunities for GIS-T in the 21^st century;
• list some modes of transportation and discuss the meaning and significance of modal competition, modal shift, and containerization;
• state the mission and describe some of the current initiatives of the U.S. Department of Transportation (USDOT);
• describe some of the geographic areas the Census Bureau uses to aggregate and disseminate data.

Among the many areas and disciplines to which GIS has been applied, transportation has been particularly fertile ground, and the development of specialized GIS applications has been an area which has seen a lot of activity. This important interdisciplinary field is commonly referred to as GIS-T. The significance of this field is evidenced by the fact that there are two conferences devoted to it, one annual and one biennial. Each year the American Association of State Highway and Transportation Officials (AASHTO) sponsors the annual GIS for Transportation Symposium [1]. The symposium draws over 400 registrants from federal, state, and local government and the private sector. The Urban and Regional Information Systems Association (URISA) sponsors a conference called GIS in Transit [2]which is held every other year. The 10th GIS in Transit conference was held last year.

A key reason that GIS-T is so important is that transportation is a huge industry upon which many other industries depend. In 2015, the federal government spent 85 billion dollars on transportation-related initiatives. That represented 2.22% of our total federal budget for 2015. The National Priority Project (NPP) website [3] presents some interesting charts which put federal transportation spending in perspective.

In addition to federal dollars, there are many billions of state and local dollars spent on transportation. If you want to see how states are using transportation dollars, the Track State Dollars website [5] gives you access to data for each state.

In the U.S., federal agencies have helped to promote GIS use for transportation analysis purposes through geospatially-enabled initiatives such as the U.S. Census Bureau’s TIGER program and the Federal Highway Administration’s Highway Performance Monitoring System (HPMS). Software vendors have continually updated and improved their GIS products to include additional GIS-T functionality and tools. Today, GIS-T is an integral part of transportation operations around the world.

The natural synergy between GIS and transportation is at least in part due to the fact that transportation is inherently spatial, and while it’s true that GIS plays an important role in transportation, one can also argue that transportation plays an important role in GIS. Transportation features are frequently included on maps for context and orientation even when the fundamental purpose of the map has little or nothing to do with transportation.  Take a few minutes to review this recent blog [6] from GeoSpatial World which briefly examines some important applications of GIS to transportation.  In this course, we'll cover these application areas as well as many others.

Broadly speaking, the field of transportation is concerned with the transport of people and goods. To appreciate the value that GIS brings to transportation it is necessary to develop an understanding of the various forms of transportation that exist and also the types of activities and problems which those in the field need to address.

Transportation Modes

The different ways that people and freight can be transported are referred to as transportation modes. There are many different modes of transportation, and they can be differentiated and categorized in a number of ways. At a high level, we can divide transportation into the categories of air, land, sea, and space. We could further divide the land-based transportation into road, rail, pedestrian, bike, and pipeline, although one might rightfully argue that pipelines can run under the sea. Transportation modes are not always mutually exclusive and the specific modes we talk about often depend on the situation at hand. There have been many GIS applications which have been designed for a specific mode or for a group of closely related modes.

Transportation Processes and Activities

Just as we can categorize transportation according to the many modes of transportation which exist, we can think about transportation in terms of the many processes and activities which are performed in order to manage transportation infrastructure, vehicles, and operations. Some of these processes cut across modes and others are specific to a single mode or a few modes. These processes and activities include:

• infrastructure monitoring and maintenance;
• transportation planning and transit planning;
• property acquisition and management;
• vehicle tracking and logistics;
• highway safety analysis and improvement;
• traffic monitoring, modeling, and mitigation;
• screening projects for environmental impacts;
• dissemination of travel information to the public;
• reporting data to government agencies to secure funding;
• mobile data collection;
• routing and permitting of oversize overweight vehicles.

GIS-T plays an important role in enhancing the manner in which transportation organizations accomplish these processes and activities and, in some cases, allow organizations to perform functions which would simply not be possible without spatial technologies. GIS-T applications support evaluation of different scenarios, provide objective data for decision-making purposes, and promote the visualization of conditions.

GIS-T Techniques and Tools

GIS-T utilizes many mainstream geospatial tools and methods but it also employs a number of techniques which were borne out of the specialized needs of the transportation industry. These include:

• Conflation
  Conflation is a technique used to bring together adjacent or overlapping datasets which were collected at different times and have different levels of accuracy and precision. While the process of conflation in GIS is frequently applied to transportation networks, conflation can also be used to combine other types of features.
• Network Analysis
  A roadway network is comprised of roads and intersections. In network terminology, the intersections are referred to as nodes, and the streets which connect the nodes are called edges. GIS-T commonly employs network analysis techniques to roadway networks to solve common transportation-related problems such as finding the best route between two points or determining the service area around a specific location (i.e., the area within which someone could reach the location of interest in a defined period of time).
• Linear Referencing Systems
  Linear referencing systems (LRS) are used to spatially reference the location of assets (e.g., bridges), occurrences (e.g., crashes), and roadway characteristics and administrative data (e.g., speed limits) by specifying the distance along a linear feature in a roadway network. Collectively, these attributes of a roadway are referred to as events. In this course we'll only consider the application of an LRS to roadway networks, they can be used in any linear network including pipelines and hydrologic networks.
• Dynamic Segmentation
  Dynamic segmentation is closely linked to LRS. In dynamic segmentation, we take the roadway events which are linearly referenced along roadways and transform them on the fly into spatial features. Taken together, LRS and dynamic segmentation allow us to effectively manage and utilize the myriad of attribute information associated with roadway networks. We will explore these techniques in detail in Lesson 6.

We will learn more about these techniques in upcoming lessons.

This week, you’ll take some time to get to know perhaps the most significant transportation organization in the United States, the U.S. Department of Transportation (USDOT). The USDOT (established in 1966) is a cabinet-level department within the U.S. government which employs about 55,000 people and is responsible for maintaining and advancing the nation’s transportation systems and infrastructure.

A key function of the USDOT is to develop programs which implement transportation-related statutes. One of the most important statutes the USDOT is tasked with implementing relates to the funding of surface transportation. The latest surface transportation statute is known as the Fixing America’s Surface Transportation (FAST) Act, which was signed into law by President Obama in December 2015.

The USDOT is comprised of a number of operating administrations and bureaus, each of which specializes in a specific area of transportation. Some of these divisions, along with the area of transportation they are responsible for, are listed below:

• Federal Highways Administration (FHWA)
  Specializes in highway transportation
• Federal Transit Administration (FTA)
  Provides financial and technical assistance to public transit agencies
• Federal Aviation Administration (FAA)
  Regulates all aspects of civil and commercial aviation and operates a national system of air traffic control and navigation
• Federal Railroad Administration (FRA)
  Enforces rail safety regulations and administers railroad assistance programs
• National Highway Traffic Safety Administration (NHTSA)
  Specializes in reducing vehicle-related crashes

We’ll take a closer look at some of these USDOT divisions in later lessons.

Spend some time looking at the USDOT’s website [7] and try to learn some more about the organization and some of their current initiatives and activities. Also, spend some time learning about the Smart City Challenge which the USDOT kicked off in December 2015. This challenge was designed to promote innovative solutions to some of the biggest challenges our cities face and offered $50 million to the winning city, $40 million of which came from the USDOT and $10 million from a private partner. Here is a video where the USDOT provided information to city mayors across the county. (Note: the presentation doesn't begin until about 10 minutes into the recording and you may want to skip ahead to the 18-minute mark when former Transportation Secretary Anthony Foxx begins to speak).

Video: Smart Cities Webcast (25:14)

Video: #SmartCityPitch: Columbus (2:35) 

The winner, announced in June 2016, was Columbus, Ohio. I think you’ll agree that their winning pitch (see above) exhibited an impressive use of multimedia.

Take a look at these links to see what's happened since the award was made in June 2016:

• The USDOT published a report [11] summarizing the lessons learned thus far.
• The city of Columbus is maintaining a list of the Smart City projects [12] which are planned or underway.
• Learn how Columbus turned the $50 million award into $500 million [13] by leveraging private investment (also check out the video at the top of the page to see some of their innovative ideas).

One of my goals for this course is to promote meaningful interactions between all of us as we cover topics in GIS-T over the next 10 weeks and to lay the framework for building relationships which will extend beyond the end of the course. Throughout the course, you will have the opportunity to get to know your classmates and me a little better. As a first step, you will create a video autobiography so we can begin to get to know you. In later lessons, you will spend time in one-on-one video chats with your classmates getting to know each other better.

Speaker

Our next webinar will be with Mr. Michael Ratcliffe. Michael is Assistant Division Chief for Geographic Standards, Criteria, Research, and Quality in the Census Bureau’s Geography Division, where he is responsible for geographic area concepts and criteria, address and geospatial data quality, and research activities. During his tenure at the Census Bureau, he has worked in both the Geography and Population Divisions, on a variety of geographic area programs, including urban and rural areas, metropolitan and micropolitan statistical areas, and other statistical geographic areas, and has led staff engaged in product development and dissemination. In addition to his work at the Census Bureau, he is an adjunct professor at George Washington University, where he teaches Population Geography. Prior to that appointment, he was an adjunct instructor at the University of Maryland-Baltimore County. Mr. Ratcliffe holds degrees in geography from the University of Oxford and the University of Maryland.

Geographic Areas Used by the Census Bureau

The Census Bureau defines many different geographic areas which can be used to organize and aggregate data. The areas the Census Bureau uses can be divided into those which are legally defined and those which are not. The Census Bureau refers to non-legally defined areas as statistical areas.

Figure 1.1: Standard Hierarchy of Census Geographic Entities

Click for a text description of Standard Hierarchy of Census Geographic Entities.

Standard Hierarchy of Census Geographic Entities

• Nation

  • Metropolitan and Micropolitan Statistical Areas and Related Statistical Areas

  • Urban Areas

  • ZIP Code Tabulation Areas

• Regions

• Divisions

• States

  • School Districts

  • Congressional Districts

  • Consolidated Cities

  • Planning Regions

  • Economic Places

  • Estates

  • Urban Growth Areas

  • State Legislative Districts

  • Public Use Microdata Areas

  • Places

• Counties

  • Voting Districts

  • Traffic Analysis Zones

  • County Subdivisions

    • Subminor Civil Divisions

• Census Tracts

• Block Groups

• Census Blocks

  • AIANNH Areas (American Indian, Alaska Native, Native Hawaiian Areas)

  • Metropolitan and Micropolitan Statistical Areas and Related Statistical Areas

  • Urban Areas

  • ZIP Code Tabulation Areas

  • School Districts

  • Congressional Districts

  • Consolidated Cities

  • Planning Regions

  • Economic Places

  • Estates

  • Urban Growth Areas

  • State Legislative Districts

  • Public Use Microdata Areas

  • Places

  • Voting Districts

  • Traffic Analysis Zones

  • County Subdivisions

    • Subminor Civil Divisions

Source: United States Census Bureau [14]

In this lesson you:

• briefly examined the important role GIS plays in the field of transportation and learned about the manner in which GIS-T is evolving in the 21^st century. \
• learned something about transportation modes and the concepts of mode competition, mode shift, and containerization.
• spent some time learning about the role of the USDOT in the transportation industry. .
• aquainted yourself with the speaker and general topics for next week's webinar.
• took the first step in getting to know each other by creating a video autobiography which will serve to introduce you to the rest of the class.

What will we learn?

By the end of Lesson 2, you should be able to:

• compare and contrast different sources of roadway data which are available;
• compare the ways Google and OSM enlist the help of volunteers to improve their roadway data;
• describe the characteristics of the TIGER/Line shapefiles and OSM data;
• discuss the use of Census data for transportation planning;
• explain the purpose of Section 106 of the National Historic Preservation Act (NHPA) and describe how it impacts transportation projects;
• list some details about your classmates based on your review of their video autobiographies.

Roadway data are fundamental to GIS-T and many of the most important transportation modes (e.g. highway, transit, bike). Many GIS functions and analyses rely on it including geocoding and network analysis, both of which we’ll take a close look at in the next few lessons. Roadway data also play an important role in mapping and visualization for many GIS applications.

There are a number of commercial and public sources of street data and services which are available. Some are public and freely available, and others are commercial. In this lesson, we’ll take a look at some of the most widely used sources of street data.

Public Sources

TIGER Data

TIGER is a data source produced and published by the U.S. Census Bureau. These data include street data which can be used to perform geocoding or to produce a street network. TIGER data were used as a “seed” for many of the other roadway data sources, both public and commercial. We will take a closer look at TIGER data later in this section.

OpenStreetMap (OSM)

OSM is a rapidly growing Volunteered Geographic Information (VGI) project which got its start in 2004 and is sponsored by the OpenStreetMap Foundation. For U.S. roads, OSM initially used TIGER Line files but many updates have since been made based on input from its volunteer community which is now over a million strong. In some parts of the world, OSM data are as good, or nearly as good, as its commercial counterparts.

Agency-Generated

State-level transportation agencies have long maintained road centerline networks as well as additional networks for other modes. They have been improved greatly in accuracy and precision, and agencies are increasingly adding local and private roads and associated data. Much of this latter impetus is due to increased federal requirements for data collection and reporting. In most cases, these networks are the most complete and accurate product for network features and associated attributes for any given state.

Transportation for the Nation (TFTN)

TFTN is an evolving governmental initiative from the National States Geographic Information Council (NSGIC) and USDOT that originated in 2008. TFTN will initially be a road centerline dataset that may replace overlapping federal efforts and products. A set of centerline datasets has been created as part of state DOT submittal requirements for FHWA’s Highway Performance Monitoring System (HPMS). The next step is to try and join these across state lines.

Commercial Sources

TomTom / Tele Atlas

Tele Atlas was founded in 1984 and was acquired by TomTom in 2008. Tele Atlas data was primarily collected from its own mapping vans. The company’s road products are decreasing in importance and usage.

Nokia / NAVTEQ / HERE

Founded in 1985 and acquired by Nokia in 1991, NAVTEQ (now renamed HERE) operates independently and partners with third-party agencies and companies to provide its networks and services for portable GPS devices made by Garmin and others, and Web-based applications including Yahoo! Maps, Bing Maps, Nokia Maps, and MapQuest.

ESRI StreetMap and StreetMap Premium

ESRI does not produce road data directly but instead acquires it from HERE, TomTom, and others and repackages it. ESRI StreetMap covers North America and is part of Data and Maps which is included with ArcGIS. StreetMap premium has more current data than StreetMap and also has coverage for Europe.

Google

Google has become a major provider of mapping services. Google doesn’t make its street data available directly but instead uses it to provide services. These services are provided through products such as Google Maps, Google Earth, and various APIs. In 2008, Google released a tool called Google Map Maker to encourage individuals to submit or correct feature information. This is similar in concept to the manner in which OSM derives much of its data. Google retired Map Maker in 2017 in favor of its "Local Guides [15]" program. As a "Local Guide," you can contribute reviews of businesses or places, upload photos and suggest a new place. Recently, they also began to add capabilities to allow users to report issues with roadway geometry and missing roads. Local Guide contributions are all made directly in the Google Maps interface. Take a look at these comparisons between OSM and Google in regards to the services [16] they provide and their user contributions [17] programs. One should note these comparisons are published on the OSM Wiki site so they may be a bit biased.

Also, check out this map comparison tool [18] made available by Geofabrik, an organization who promotes OSM and provides a portal for downloading OSM data extracts. Select an area you are familiar with, and compare the OSM map, the Google map, and the HERE map.

In this section, we'll take a closer look at two of the most extensive sources of publicly available roadway data: TIGER and OSM.

The TIGER database was first created in preparation for the 1990 decennial census. In creating TIGER, not only did the Census Bureau produce the first nationwide map of roadways, it also incorporated topographical context which defined the relationship between road features as indicated in its name: Topologically Integrated Geographic Encoding and Referencing database.

In addition to the TIGER spatial database, the Census Bureau also created a Master Address File (MAF) which is a database of all known living quarters in the U.S. The MAF contains about 300,000 addresses which are identified as location addresses, mailing addresses or both. In addition, the MAF contains a record for each living unit which can correspond to a separate structure or a residence within a shared structure. There are about 200,000 living units in the MAF some of which have multiple associated addresses. Following the 2000 decennial census, the Census Bureau decided to merge the two databases into a single database known as the MAF/TIGER Database (MTdb).

The Census Bureau is planning a 3-part informational series on TIGER to commemorate its 25^th anniversary. Part 1 will examine the history of TIGER, Part 2 will address efforts to improve its accuracy, and Part 3 will address the tools which provide access to the data. To date, only Part 1 of the series [19] has been made available. Spend a few minutes looking through the document to learn a little about TIGER’s history.

The TIGER data is available in a number of formats [20] including Shapefiles, geodatabases, and KML files. The Census Bureau also provides a tool called TIGERweb [21] which allow online viewing and the ability to incorporate TIGER data directly in GIS applications via web services including an OGC standard Web Mapping Service (WMS). For the exercises in this and the upcoming lesson, we will be working with the TIGER/Line shapefiles [22].

The Tiger/Line shapefiles are available for multiple years. Each year, the Census Bureau provides an updated set of Tiger/Line shapefiles in addition to associated technical documentation. The technical documentation for the 2017 Tiger/Line shapefiles can be found here [23]. It is over 120 pages long and serves as an excellent reference for the Tiger/Line Shapefiles.

With more than 3 million registered users, the OSM project has a huge community behind it. Consequently, there is plenty of documentation available for learning about the project and becoming a member of the community. A few good resources for learning about OSM are the Open Street Map Wiki [24]and the guides on LearnOSM.org [25].

OSM data is natively available in a unique file format (i.e., .osm files). However, many of the sites which provide access to OSM data serve it up in commonly used formats like shapefiles. For example, take a look at Geofabrik’s OSM data download page [26]. Also, take a look at the first few sections of the OSM Data Guide [27] which describe the .osm file format and some options for acquiring OSM data.

We often talk about spatial data in terms of points, lines, polygons, and attributes. OSM, however, uses the terms nodes, ways, relations and tags. In order to develop some understanding of these terms, take a look the descriptions of OSM data’s elements [28]on the OSM Wiki site.

In preparation for this week's webinar, you learned about the geographic areas the Census Bureau uses to tabulate and disseminate data. This week, you’ll explore the Census Bureau in greater detail. The Census Bureau is part of the U.S. Department of Commerce. The mission of the Census Bureau is to “serve as the leading source of quality data about the nation's people and economy.” To fulfill its data gathering objectives, the Bureau conducts both decennial censuses and a continuous survey known as the American Community Survey (ACS). The ACS was born in 2005 out of a need for more up-to-date information than the decennial census provided. Data from both the decennial census and the ACS are made available in a variety of ways, one of the most popular of which is the via the American FactFinder site [29].

Data collected by the Census Bureau serve some critical functions. These data are used to:

• determine the number of seats each state has in the house of representatives;
• distribute over 400 billion dollars in federal funding annually;
• make planning decisions about community services.

Geography and GIS are very important to the Census Bureau.

Census Transportation Planning Products Program

The Census Transportation Planning Products Program (CTPP) [33] is an initiative led by the American Association of State Highway and Transportation Officials (AASHTO). AASHTO is an organization we’ll take a closer look at in an upcoming lesson. The CTPP provides special tabulations of Census data which are of particular interest to transportation planners. These datasets provide insight into how people commute and which modes of transportation they use. They are often used to validate travel demand models which themselves are used to make decisions on what types of transportation projects are needed to support regional needs, including those related to economic growth, public health, transit needs, and highway safety issues (for a quick overview of the Four Step Model (FSM) which commonly used in travel demand modeling, see this 2007 article by Michael McNally at the University of California, Irvine [34]).

To facilitate the use of the CTPP data, AASHTO created a web-based application [35]to examine travel flows. The CTPP even has a YouTube channel devoted to teaching people how to use the software (although the quality of the videos is less than stellar). Take a look at the YouTube video below (5 minutes) which shows how to generate some basic county to county commuter flow data. The CTPP data analysis tool also has the ability to display results in a variety of formats including thematic maps.

Video: CTPP Software - select geography by list and map (5:29)

Another interesting use of the commuter flow data can be seen in an application created by Mark Evans. Mark used the Google Maps API to create a GIS application called Commuter Flows [37] which facilitates the visualization of census tract level commuter flows derived from the ACS data.

This week, you will get to know a little about each other by reviewing the video autobiographies posted by your classmates in Lesson 1. You’ll also have a one-on-one chat with one of your classmates as per the schedule you were provided at the end of Week 1. The discussion should be at least 30 minutes in length. If it’s the first time you’ve chatted with each other, spend the majority of time getting to know each other. Otherwise, focus on discussing the lesson content.

Speaker

Our speaker will be Dr. Ira Beckerman. Ira has been the Cultural Resources Section Chief for the Bureau of Design at PennDOT since 1998. Trained as an archaeologist (Ph.D. Anthropology, Penn State, 1986), he has worked as a field archaeologist in Mexico, Tennessee, North Carolina, and Pennsylvania. His 22 years of transportation experience is split between PennDOT and (previously) the Maryland State Highway Administration. Dr. Beckerman’s research interests include archaeological predictive modeling, pre-contact Eastern North America, and GIS. He is a member of the Society for American Archaeology, Register of Professional Archaeologists, and the Transportation Research Board’s Archaeology and Historic Preservation Committee, and has served on panels for TRB and the American Association of State Highway Transportation Officials (AASHTO). Dr. Beckerman was a 2001 recipient of the PennDOT Star of Excellence. His group also recently led an effort to develop a predictive model for archaeological sites which serves as a valuable tool for screening projects early in the planning process.

Section 106 of the National Historic Preservation Act (NHPA)

The National Historic Preservation Act (NHPA) was passed into law in 1966. The purpose of the law is to protect historic and archaeological sites of significance. One outcome of the NHPA was the creation of the National Register of Historic Places (NRHP), which is a list of districts, sites, and structures deemed worthy of protection. There are more than 1 million properties currently on the list and about 30,000 additional properties are added annually. Section 106 of the NHPA specifically requires historical and archaeological sites to be assessed for impact as part of any federally funded project.

To gain a better understanding of the Section 106 process, take a look at A Citizen’s Guide to Section 106 Review [38], a brief overview put together by the Advisory Council on Historic Preservation. Also, watch the following video which describes the process which agencies need to follow to comply with Section 106 of NHPA.

Cultural Resources GIS

Many states have developed GIS-based systems to help state agencies and other interested parties identify historic properties and known archaeological sites and assess their proximity to planned projects. Spend some time exploring Pennsylvania’s Cultural Resources Geographic Information System (CRGIS) [40]. CRGIS was created and maintained through a collaborative partnership between the Pennsylvania Historical & Museum Commission (PHMC) and PennDOT. (note: CRGIS requires that pop-ups are allowed ... so you'll have to enable them in your browser either in general or for this site specifically. You can disable them again when you're done exploring CRGIS. Instructions for adjusting pop-up settings in Internet Explorer/Edge and Chrome are included in the "Getting Started" link in the upper right portion of the CRGIS website.)

Archaeological Predictive Modeling

A number of efforts have been undertaken in recent years to use predictive modeling to identify locations which are likely archaeological sites. In Pennsylvania, FHWA, PennDOT, the Pennsylvania Historical and Museum Commission (PHMC) and URS Corporation partnered to create such a predictive model which is described in brief here [41]. The model uses data from known archaeological sites together with spatial algorithms to rank areas based on their likelihood of having artifacts. These data are then used in evaluating potential projects and alternatives.

In this lesson, we discussed the importance of roadway centerline data to GIS and explored some of the public and commercial sources for this data. In particular, we took a close look at the Census Bureau’s TIGER data in addition to the data available via Open Street Map (OSM).

Our transportation organization of the week was the Census Bureau. We spent some time learning about the American Community Survey and the role that Census data plays in transportation planning.

In preparation for next week's webinar, we reviewed the role of Section 106 of NHPA in transportation projects and explored a cultural resources GIS application.

Finally, you had the opportunity to learn a little bit about your classmates by reviewing their video autobiographies and by having your first one-on-one conversation.

What will we learn?

By the end of Lesson 3, you should be able to:

• describe the process of geocoding and discuss some of the more common types of geocoding which are used;
• discuss the purpose and characteristics of an address locator;
• create an address locator using TIGER/Line shapefiles and use it to geocode a list of addresses;
• discuss conflation as it applies to GIS-T and use some of the tools in ArcMap to assist in conflation activities;
• define the process of conflation as it applies to roadway data and identify some situations where conflation would be performed;
• list the key functions of an MPO and RPO;
• describe the transportation plans which are created and maintained by MPOs, RPOs, and state Departments of Transportation (DOT).

Geocoding

Geocoding is the process of taking the description of a specific location and converting it into a set of coordinates or a point feature which can then be displayed on a map or used in some type of spatial analysis. A variety of location description types can be geocoded including addresses and place names. There are a number of different approaches which can be used for geocoding, but at a high level they all follow the same process:

• Descriptions of the locations to be geocoded are compiled into a standard format.
• The location descriptions are compared to a reference dataset.
• Candidate locations are established and scored according to a set of rules.
• If the score for a candidate location exceeds a threshold value, it is declared a match.
• If no candidate location score exceeds the established threshold, the location of interest is flagged as unmatched.
• If two or more candidate locations share the same score and that score exceeds the threshold value, a tie is declared.

Geocoding is a widely used geospatial technique that has applications across many industries. It is often a prerequisite process to performing some type of network analysis such as routing. There are a variety of distinct processes which can be used for geocoding. The primary differences lie in the type of reference data which is used. The most common type of geocoding uses roadway centerline data where each street segment has address range attributes for each side of the street. Most online geocoding services, including Google Maps, Yahoo Maps, and MapQuest, rely almost exclusively on this type of geocoding. Other types of geocoding use parcel boundary data or address point data. You’ll read more about the different types of geocoding in Assignment 3-1.

There are many geocoding services which are available, some of which are free and some of which are subscription-based. The free services generally limit the number of locations you can process at one time. Given a suitable reference dataset, it is also possible to create your own geocoding service. You’ll have an opportunity to do just that in Assignment 3-2.

ArcGIS Address Locators

The first step to geocoding in ArcGIS is selecting an address locator which will be used. The address locator defines the reference dataset and the rules which will be used by the geocoding engine in identifying candidates and matches for the location descriptions (typically addresses) you are trying to locate. You can use an existing address locator, which typically requires a subscription, or you can create your own. To create your own address locator, you need to have access to a suitable set of reference data. There are many potential reference datasets available including those which are created by state or county governments. One good source of reference data for geocoding is the TIGER/Line shapefiles we examined in Lesson 2.

To create an address locator, use the “Create Address Locator” tool in ArcToolbox (see Figure 3.1).

Figure 3.1 - Create Address Locator Tool

When you launch the tool, you are presented with the Address Locator dialog (see Figure 3.2).

Figure 3.2 - Address Locator Dialog

The first step in creating an address locator is selecting a locator style. The locator style which is most appropriate depends on the reference data you’re planning to use in addition to the format of the locations you’re trying to geocode. A commonly used address locator style is the U.S. Addresses – Dual Ranges (see Figure 3.3).

Figure 3.3 - Address Locator Styles

Once the locator style has been selected, the Field Map list in the bottom portion of the Address Locator dialog is automatically populated (see Figure 3.4). Fields with an asterisk are required by the locator style, and fields without an asterisk are optional. Once you have loaded a reference dataset, you can map these fields to the corresponding fields in the reference data.

Figure 3.4 - Address Locator Dialog with Field Map List Populated

The second step in creating an address locator is defining the reference dataset or datasets which will be used. As mentioned above, there are many reference data sources which can be used. For example, you can use a linear feature class based on roadway centerlines such as the “Address Range-Feature Shapefile” TIGER/Line shapefiles we reviewed in Lesson 2. Alternatively, you could use a polygon feature class based on parcel boundaries or zip code boundaries. Yet another option would be to use a point feature class based on address points.

Once you have selected the reference data, you can map the fields associated with the address locator style you have selected with the corresponding fields in the reference data (see Figure 3.5).

Figure 3.5 - Mapping Locator Style Fields with Reference Data Fields

The final step is to save the address locator to a location you select. While you can store the locator in either a geodatabase or a file folder, ESRI recommends storing an address locator in a file folder for better performance.

Here is a link to an ESRI webpage where you can download a white paper [42] which tells you everything you’d ever want to know about address locators in ArcGIS.

Geocoding a List of Addresses (or other location descriptions)

To geocode a list of addresses, you should first add the table of addresses data to your map document in ArcGIS. The addresses to be geocoded can be prepared in any number of file formats including xlsx, xls, dbf, csv, and txt. Once the table of addresses has been added, you can right-click on the newly added table and select “Geocode Addresses” from the resulting context menu. At this point, you’ll be asked to select an address locator (see Figure 3.6).

Figure 3.6 - Select an Address Locator

If the address locator you wish to use is not in the list, you can add it. Once you select an address locator and click “ok,” you will be presented with the “Geocode Addresses” dialog (see Figure 3.7).

Figure 3.7 - Geocode Addresses Dialog

In the top portion of the dialog, you can map the fields in the input table to the corresponding fields in the address locator, if it isn’t done automatically, and define the location and name of the shapefile or feature class where the results of the geocoding process should be stored. You can also configure some parameters for the address locator by clicking the “Geocoding Options” button. The “Geocoding Options” dialog is then displayed (see Figure 3.8).

Figure 3.8 - Geocoding Options Dialog

In the top portion of the dialog, you can exercise some control over how matching is performed. The spelling sensitivity level controls the extent to which misspellings will still be considered a match. The lower the score, the more tolerant the geocoding engine is for misspelled words. The minimum candidate score sets the threshold score for identifying candidates. The lower this score, the more candidates an address could have. Finally, the minimum match score establishes the threshold score for declaring a match for the address. Lowering the minimum match score will generally increase the match rate but will also tend to result in a higher rate of false positives.

The dialog can also be used to set other parameters for the geocoding engine such as offset positions for geocoded point features and some output data elements which can optionally be included as attributes in the resultant shapefile or feature class.

Once the geocoding options have been defined, the geocoding process can be initiated by clicking “Ok” on the “Geocode Addresses” dialog (see Figure 3.7). When the geocoding process is complete, a summary of the geocoding results is presented (see Figure 3.9).

Figure 3.9 - Geocoding Results Summary Screen

This summary shows the number of addresses which had candidates above the minimum match score (i.e., matches), the number of addresses which had multiple candidates which were above the minimum match score and had the same score (i.e., ties) and the number of addresses which did not produce any candidates above the minimum candidate score (i.e., unmatched).

From the results summary screen, a manual rematch process can be initiated by clicking the “Rematch” button. This brings up the “Interactive Rematch” screen (see Figure 3.10).

Figure 3.10 - Interactive Rematch Screen

On this screen, unmatched addresses, ties, and matched addresses can be reviewed. Unmatched addresses generally result from either a problem with the address or a problem in the reference data. If a problem is observed with the address, it can be corrected and matched with the correct candidate directly on this screen. Often, however, it is unclear what the problem is with a particular address, and additional research is required to determine where the problem lies before it can be corrected.

Conflation, in the context of GIS, is the process of combining two geospatial datasets so that the resultant dataset is superior to the input datasets. While conflation processes are used throughout GIS, they are of particular importance in GIS-T where roadway datasets of varying spatial quality and attribution are available from many different sources. The act of conflating datasets can often be a complex and time-consuming process. How complex and time-consuming the process is depends on a number of factors including the spatial extent of the datasets, the number of features present and the degree of spatial alignment between corresponding features. In some cases, it may be possible to automate a portion of the process but the success of these types of approaches depends on the quality of the initial datasets and the requirements for the final product.

Reference Dataset

When conflating two datasets, one of the datasets is generally considered to be the reference or target dataset. This is the dataset with the most spatially accurate features. The other dataset is sometimes referred to as the input or source dataset.

Conflation Workflow

While each conflation project can be unique, they all draw from a core set of activities. Some of the more common conflation activities include the following:

1. Feature Matching: The objective here is to match corresponding features in the datasets. This process can be based on the spatial alignment of the features and/or certain attributes of the features.
2. Feature Alignment: Once features are matched, they can be brought into spatial alignment with each other to establish proper topological relationships.
3. Feature Addition: Features in the input dataset which are missing in the reference dataset can be added to the reference dataset.
4. Attribute Transfer: Attributes information from the input dataset is added to the reference dataset.

The characteristics of the activities involved in a conflation project are largely dependent on the nature of the input datasets. There are three potentials scenarios:

1. Vector - Vector
2. Vector - Image/Raster
3. Image/Raster - Image/Raster

In GIS-T, we are most commonly engaged in conflating two vector datasets (i.e., roadway data).

Horizontal Conflation vs. Vertical Conflation

Conflation can also be broadly categorized as horizontal conflation or vertical conflation based on the geographic relationship between the datasets. In horizontal conflation, the objective is to join two datasets which are spatially adjacent to each other. For example, perhaps you want to join roadway datasets from two adjacent counties or two adjacent states. In these cases, there is often some feature overlap near the dataset boundaries. In vertical conflation, the datasets being merged span the same geographic region or at least have substantial overlap. The objective is often to transfer a robust set of attribute data from one dataset, which may be of poor spatial accuracy, to a dataset which is poor in attribution but spatially accurate. Of course, in the real world, you may run across situations where the datasets partially overlap.

Conflation Tools

GIS software often has some built-in tools to at least assist with conflation needs. For example, in ArcMap 10.2.1, ESRI introduced a set of tools to help with conflation. The conflation toolset is found in the Editing Toolbox. ESRI also added a tool called Detect Feature Changes to the Data Comparison toolset in the Data Management Toolbox. Spend some time reviewing the help documentation for these tools.

This week, we’ll take some time to explore Metropolitan Planning Organizations (MPOs) and Rural Planning Organizations (RPOs). MPOs were formed as part of 1962 Federal-Aid Highway Act and are required for any urbanized area with a population of more than 50,000. Congress recognized transportation planning is best done at a regional level since the nature of transportation systems and services often transcends an individual municipality, city, or county.

Watch the short video (11 minutes) below which discusses the purpose and structure of MPOs. There are more than 300 MPOs across the U.S., a listing of which is provided here [43].

Video: MPO Planning Process (11:27)

Rural areas often have transportation needs that are very different from metropolitan areas. In rural regions, either the State DOT, a Rural Planning Organization (RPO), or a local government conducts transportation planning. While RPOs are not federally required, it is a requirement that if the state performs the planning function for rural regions, they need to coordinate with local officials.

In Pennsylvania, there are 15 MPOs and 8 RPOs. MPOs and RPOs often have strong GIS capabilities to support various planning studies.

This week you’ll have a one-on-one chat with one of your classmates as per the schedule you were provided in Week 1. The discussion should be at least 30 minutes in length. If it’s the first time you’ve chatted with each other, spend the majority of time getting to know each other. Otherwise, focus on discussing the lesson content.

Speaker

Next week, our speaker will be Mr. Glenn McNichol. Glenn is a Senior GIS Specialist with the Delaware Valley Regional Planning Commission (DVRPC). He has been with the Commission for 23 years. As a member of DVRPC’s GIS unit, he supports the activities of the Commission’s planning staff through map production, data development, and GIS analysis. He also manages the Commission’s orthoimagery program.

Glenn holds a BA in Geography from Montclair State University. He also received a Professional Certificate in Geomatics from Cook College, Rutgers University.

The August 2016 edition of DVRPC News [45] featured a profile of Glenn (note: scroll to the bottom of the page to see the profile).

The Delaware Valley Regional Planning Commission (DVRPC)

DVRPC is a Municipal Planning Organization (MPO) responsible for 9 counties in the Philadelphia area, 6 of which are in Pennsylvania and 3 of which are in New Jersey.

DVRPC's stated vision and mission statements are shown below:

DVRPC’s vision for the Greater Philadelphia Region is a prosperous, innovative, equitable, resilient, and sustainable region that increases mobility choices by investing in a safe and modern transportation system; that protects and preserves our natural resources while creating healthy communities, and that fosters greater opportunities for all.

DVRPC’s mission is to achieve this vision by convening the widest array of partners to inform and facilitate data-driven decision-making. We are engaged across the region, and strive to be leaders and innovators, exploring new ideas and creating best practices.

DVRPC is engaged in many transportation projects [46]. Spend some time looking through a few of them.

In this lesson, we discussed a number of geocoding techniques and considered the pros and cons of each. We also examined the properties of an address locator in ArcGIS and the role it plays in the geocoding process. You had the opportunity to construct your own address locator using TIGER/Line shapefiles and used it to geocode a series of addresses.

We also learned a bit about conflation especially in regards to roadway datasets. You then explored some of the tools in ArcGIS which can be used to conflate multiple datasets.

Our transportation organizations of the week were MPOs and RPOs. We learned about how they are structured and the responsibilities they have in the area of transportation planning.

In our weekly webinar, we had the opportunity to interact with Dr. Ira Beckerman, an archaeologist who leads PennDOT’s cultural resources group which is responsible for the Department’s compliance with Section 106 of the National Historic Preservation Act. We also had the opportunity to hear from Glenn McNichol, a Senior GIS Specialist with the Delaware Valley Regional Planning Commission (DVRPC).

In preparation for next week’s webinar, we took a look at DVRPC, a large MPO which handles the Philadelphia area, and explored the types of transportation projects they conduct.

Finally, you had the opportunity to get to know one of your classmates a little better and share some of your ideas and questions about this week’s lesson materials.

What will we learn?

By the end of Lesson 4, you should be able to:

• describe the importance of a transportation network;
• characterize the data elements which go into a street network and evaluate street data sources to determine their suitability in serving as the basis of a network dataset;
• create a network dataset from street data;
• list the key functions of the Federal Highways Administration (FHWA);
• describe the composition and purpose of the National Highway System (NHS);
• discuss FHWA’s Geospatial Data Collaboration (GDC) initiative; and
• talk about the importance of addressing environmental and community considerations early in the transportation planning process and provide some examples of how GIS can be used to facilitate this process.

People and goods can move from one location to another by traversing a transportation network. There are many types of transportation networks including street networks, railroad networks, pedestrian walkway networks, river networks, utility networks, and pipeline networks. A geospatial model of a transportation network is comprised of linear features and the points of intersection between them. The modeling and analysis of networks has so many applications that there is an entire branch of mathematics devoted to it known as graph theory. In graph theory, linear segments of the network (e.g., road segments) are referred to as edges, and the points where the linear segments connect are called nodes.

Some transportation networks permit travel in both directions such as street networks and are referred to as undirected networks. Other networks generally limit travel to a single direction such as pipeline networks. These networks are referred to as directed networks. In ArcGIS, undirected networks are modeled with network datasets whereas directed networks are modeled as geometric networks. In this course, we will limit our study to street networks and the use of network datasets to model them.

Many transportation problems can be addressed through a network. A few examples are listed below:

• identifying the fastest, shortest, or most scenic path between two points on the network;
• determining the most efficient way for a delivery vehicle to visit a series of stops (also known as the traveling salesman problem);
• defining the service area around a given location;
• identifying an optimal store location.

We will take a detailed look at some of the more common network analyses in the next lesson. In this lesson, we will focus on the components of a transportation network model and the mechanics of creating one.

While a high-quality set of roadway centerline data is certainly a prerequisite to modeling a transportation network, it is by no means sufficient. Other important elements of a network model include the following:

• Topology

  The topology of a street network refers to the spatial arrangement and connectivity of the roads which comprise the network. Understanding how the road features relate and connect is critical to determining which paths or routes through the network are possible. Elevation is an important consideration in establishing network topology. Physical connections between streets require not only that they cross in the x-y plane but also that they cross at the same elevation. The picture below shows a complex interchange where many roads cross, but there are limited points of connectivity.

  

  Figure 4.1: Complex Highway Interchange

  Credit: ESRI 2010 User Conference Technical Workshop

• Cost Attributes

  In order to select the “best” route between two points in a network, you need to define what you are trying to accomplish. Perhaps you’re interested in determining the shortest route. In this case, you would need to know the distance between all adjacent nodes in the network. Consequently, the edges would need to have an attribute which quantifies length. Alternatively, if you want to know the fastest route between two points, you need to know the time it takes to move between any two adjacent nodes. Consequently, to support the fastest route determination, the edges need to have an associated time attribute or a speed limit attribute, since time is a function of length and speed limit. Regardless of how you define “best,” you need to have a corresponding attribute or attributes which allow the cost of potential routes to be quantified and compared. For example, if you want to know the most scenic route between any two points in the network, you would need to have a scenic score attribute associated with each edge which quantifies its scenic value.

• Turns

  Turns also play a key role in modeling a street network. One fundamental consideration in regards to turns is whether they are permitted. Many road intersections do not permit U-turns, for example. A second consideration for turns is the length of time they take. Left turns generally take longer to complete than right turns, since you generally have to contend with oncoming traffic. In order to accurately estimate how long it would take to traverse a network along a specific route, turn delays need to be taken into account.

• One-Way Restrictions

  Another important data element for a street network relates to one-way roads. In order to ensure that only legitimate routes are considered, roads which limit travel to one direction need to be identified.

• Traffic

  We all know that traffic plays an important role in determining how long it takes to traverse a particular route. Consequently, historic traffic data, or better yet, live traffic data, can be extremely useful in a street network model.

• Directions

  Often one of the desired outputs of network analysis is a set of description directions. In order to support the production of meaningful directions, a variety of descriptive roadway attributes needs to be present. Signpost data can also provide a valuable source of information for the creation of meaningful directions.

As you can see, a lot of information is required beyond basic roadway centerline geometry in order to create a street network which can support network analysis and produce high-quality results.

This week, you’ll take some time to get to know the Federal Highways Administration (FHWA), an important agency within the USDOT. The roots of the FHWA trace back to its first predecessor organization known as the Office of Road Inquiry (ORI) which was created by President Grover Cleveland in 1893. In the days before the automobile, interstate travel was dominated by railroad and it was actually a bicycle boom which was largely behind the initial interest in improving America’s roads. An interesting history of the FHWA can be found here [47]. A signature achievement in the advancement of America’s roads was the development of the Interstate system of roadways championed by President Dwight D. Eisenhower. Today, the Interstate system represents about 50,000 miles of highway and is responsible for about one-quarter of the vehicle miles traveled on America’s roadways.

The primary function of the FHWA is to assist states and local governments with the design, construction, and maintenance of roads and bridges and to ensure US roads and highways meet a high standard of safety and quality. The primary mechanism through which the FHWA supports states and local governments is the Federal Aid Program. This program looks to focus federal monies on the nation’s most important roadways.

The Intermodal Surface Transportation Efficiency Act of 1991 introduced the concept of the National Highway System, a system of roads and highways deemed critical to America’s economy, defense, and/or mobility. Through the efforts of FHWA working with other federal, state, and local partners, roughly 160,000 miles of roadway were identified for inclusion in the NHS. The National Highway System Designation Act of 1995 signed into law by President Bill Clinton officially designated these roadways as the NHS.

A brief but informative article on the NHS titled The National Highway System: A Commitment to America's Future [48] appeared in a 1996 edition of Public Roads, a bimonthly magazine published by FHWA.

One of the FHWA’s key objectives is to encourage innovation and to provide states and local governments with needed technical assistance. A recent FHWA initiative known as Geospatial Data Collaboration [49] (GDC) is aimed at promoting the use of GIS tools to facilitate data sharing and increased collaboration between transportation agencies and resource agencies, with the ultimate objective of more timely project delivery.

There are no one-on-ones scheduled for this week.

Next week we'll hear from 2 speakers.

Speaker #1

Our first speaker will be Mr. Frank DeSendi. Frank is the Manager of PennDOT’s Geographic Information Division and is also a former Chair of the American Association of State Highway Transportation Officials’ GIS for Transportation (AASHTO GIS-T) Task Force. He began his career with PennDOT in 1989 and has been working in the geospatial field since 1995. Frank holds a Bachelor of Science in Geography from The Pennsylvania State University.

One interesting use of spatial technology which Frank’s group implemented a few years ago is called LPN which stands for Linking Planning and NEPA. PennDOT and its planning partners (i.e., the MPOs and RPOs) use the application to screen potential projects against more than forty environmental datasets which collectively address most NEPA concerns. Based on the proximity of a proposed transportation project to these resources, the application determines a score which can be used to compare various alternatives for the project. The user’s guide for the application is here [50].

Planning and Environmental Linkages (PEL)

In the past, transportation planning and the development of TIPs and STIPs occurred with little thought given to environmental and cultural resources and community concerns. Later in the project development process, when the design and construction of the project were imminent, the potential impacts to these resources were considered as is required by NEPA. If through this NEPA review process, the project was anticipated to have potential impacts on these resources, it often led to substantial delays in project delivery, unexpected increases in the project budget, and a less than ideal solution for all involved. Consequently, significant efforts have been made in the past 15 years to begin assessing potential impacts to resources early in the planning process and for transportation agencies to work more closely with resources agencies. Spatial technologies have played a large role in facilitating potential impact assessments, identifying alternatives that eliminate or minimize impacts and, when impacts are unavoidable, identifying mitigation strategies which can offset any negative impacts of the project.

In response to the need to more closely integrate transportation planning and environmental review, FHWA created the Planning and Environmental Linkages (PEL) program to help state DOTs, MPOs and RPOs revise their planning processes, improve their coordination with resource agencies and develop tools to streamline the entire process.

Watch the 2011 webinar (72 minutes) jointly sponsored by FHWA and AASHTO titled Linking Transportation and Natural Resource Planning through the use of Environmental GIS Tools [51].

Speaker #2

Our second speaker will be Mr. Greg Ulp. Greg is a Senior Project Manager with GeoDecisions, a division of Gannett Fleming specializing in GIS and IT. He has over 25 years of experience in applying spatial technologies to solve transportation problems and has worked with a number of state DOTs. Greg has worked extensively with the Pennsylvania Department of Transportation’s GIS Division. He was the technical architect for a GIS application called the Multimodal Project Management System Interactive Query (MPMS-IQ) which is used to access and visualize data for the Department’s highway and bridge projects. Greg holds a bachelor’s degree in computer science from The Pennsylvania State University.

Transportation Planning

There are a number of transportation plans that regional planning organizations (MPOs and RPOs) and state DOTs are federally required to prepare and periodically update. These include the following:

• Long Range Transportation Plan (LRTP)
  An LRTP, also known as a Regional Transportation Plan (RTP), is a long-term plan which is prepared by an MPO. It typically has a 20 to 30-year horizon and is updated every 3 to 5 years. The LRTP establishes priorities and long-term objectives for the region.
• Transportation Improvement Program (TIP)
  The TIP is a short-term plan, at least 4 years in length, which aligns with the policies and objectives defined in the LRTP. Each MPO is federally mandated (49 U.S.C. 5303(j)) to develop a TIP which includes all federally funded projects in addition to non-federally funded projects which are consistent with the LRTP. The TIP is required to be in line with available funding (i.e., fiscally constrained).
• Statewide Transportation Improvement Program (STIP)
  The STIP is a statewide roll-up of each of the TIPs across the state and is maintained and updated by the state DOT. The STIP is also federally mandated (23 U.S. Code § 135). Each state’s STIP is subject to approval by both the Federal Highways Administration (FHWA) and the Federal Transit Administration (FTA) (two organizations we’ll take a look at in upcoming lessons).

Project Visualization Tools

In order to solicit feedback from the public on potential projects and to provide legislators and the public access to information on planned and active projects, state DOTs, Municipal Planning Organizations (MPOs) and Rural Planning Organizations (RPOs) sometimes use web-based GIS applications to enable people to visualize projects in a specific geographic area and get detailed information on a project of interest.

Watch this FHWA sponsored webcast on Visualizing TIPs and STIPs Using GIS [52] which was held on April 27, 2016. It is a little rough in spots but is very informative. The presentation doesn’t actually start until about 7 ½ minutes in, due to some technical difficulties. In the webcast, PennDOT discusses three separate GIS-based project visualization applications which are used to provide the public and state legislators access to planned and active projects. All three applications have a consistent user interface and differ only in the types of projects they show. The first application shows active projects under construction, the second shows Act 89 projects which are projects of particular interest to state legislators and the third shows planned projects (i.e., projects on the STIP and TYP). All three applications can be accessed here [53].

Another organization which participated in the webcast was the Delaware Valley Planning Commission (DVRPC). DVRPC is an MPO which spans 9 counties in 3 states (Pennsylvania, New Jersey, and Delaware). In the webcast, DVRPC discusses how they make project information available through a Google Maps-based GIS application. Take some time to explore the 2017 DVPC TIP Visualization tool [54]. In addition to using GIS to facilitate visualization of their transportation program, DVRPC also uses spatial technologies to evaluate potential projects for the TIP based on a variety of criteria they have developed.

MPMS-IQ

MPMS-IQ is a web-based GIS application developed for PennDOT which allows users to visualize projects and access a wide variety of project related information via a map interface. The projects which are available through MPMS-IQ include active construction projects in addition to projects on PennDOT’s Twelve Year Plan (TYP). Unlike the STIP, the TYP is not federally mandated. The STIP corresponds to the first 4 years of the TYP. Take some time to explore MPMS-IQ [55]. In particular, look at the methods by which users can search for projects, the information available for each project, and the additional layers and features the application provides.

In this lesson, we learned about transportation networks. Specifically, we examined the elements which comprise a network and the activities that go into creating one. You then had the opportunity to solidify this knowledge by modeling a transportation network in ArcGIS through the construction of a network dataset from roadway centerlines and other associated data.

Our transportation organization of the week was the FHWA. You learned a little about the history and key roles of the FHWA. We also took a look at NHS, a network of roadways deemed critical to the nation, and FHWA’s geospatial data initiative known as the GDC.

We also had the opportunity to hear from two speakers this week.  Glenn McNichol, a Senior GIS Specialist with the Delaware Valley Regional Planning Commission (DVRPC) and Michael Ratcliffe, the Assistant Division Chief for Geographic Standards, Criteria, Research, and Quality in the Census Bureau’s Geography Division.

In preparation for next week’s webinars, we learned how transportation planning and the NEPA review processes which seek to assess and mitigate environmental impacts related to transportation projects have become more tightly integrated and about the role GIS has played in helping to bring the two together. We also took a look at some GIS applications used to visualize planned and active transportation projects.

What will we learn?

By the end of Lesson 5, you should be able to:

• list the common types of problems that network analysis can be used to solve;
• use ESRI’s Network Analyst extension to perform a variety of network analyses;
• list some of the key functions state DOTs serve and discuss how their roles have changed over time;
• provide an example of how spatial technologies are used within a specific state DOT;
• discuss the nature of a Linear Referencing Systems (LRS) and dynamic segmentation and explain why these techniques are important in managing the geometry and diverse set of attribute information associated with transportation networks;
• share something you learned about one of your classmates and/or some ideas you discussed with a classmate about the content of this week’s lesson.

Network analysis can be used to solve many different transportation problems that would be very challenging to solve otherwise. A prerequisite to performing network analysis is that you have a network model. In ESRI’s terms, this is a network dataset. We walked through an exercise to construct a network dataset in the last lesson. Of course, it is not a requirement of network analysis that you construct your own network model. There are a number of commercially available network models you can use instead.

The types of problems which network analysis can be used to solve are quite varied. One common characteristic of the algorithms that power each is that they involve determining the cost of one or more routes through the network. The cost is most commonly based on time or distance, but you can define a cost attribute any way you want. For example, you might score each edge in the network based on its scenic value. You could then create a cost parameter based on the scenic score and use the solver to find the most scenic route.

ESRI provides 6 out-of-the-box network analyses as a part of Network Analyst. ESRI terms these network analyses “solvers.” The solvers are listed below along with a brief description of each:

Route Solver

The route solver determines the best route between two or more points. Most of us use this network analysis on a regular basis. Whenever you use Google Maps or a comparable service to get directions from one location to another the service is conducting a network analysis to determine the best, typically fastest, route. This solver can route any number of points according to a specified order (i.e., the traveling salesman problem) or the most efficient order.

Figure 5.1 - Route Solver: Time vs. Distance Based Cost

Credit: ESRI [57]

Closest Facility Solver

This solver is used to determine the closest facility to a given location. The term "facility" can be a bit misleading. For example, this solver could be used to determine the closest ambulance to an accident scene. In this case, using ESRI’s terminology, the ambulances would be considered facilities.

Figure 5.2 - Closest Facility Solver

Credit: ESRI [57]

Service Area Solver

The geographic region which can reach a designated facility in a certain period of time (or vice versa) is termed a service area. To determine the bounds of this area, you can use the Service Area Solver.

Figure 5.3 - Service Area Solver

Credit: ESRI [57]

Origin-Destination (OD) Cost Matrix Solver

The OD cost matrix solver is generally used to determine the distances of the fastest routes between a set of origins and a set of destinations. Although the path between each origin and destination is often represented as a straight line, the route which corresponds to the time and distance costs between each pair of locations follows the street network.

Figure 5.4 - OD Cost Matrix Solver

Credit: ESRI [57]

Vehicle Routing Solver

The vehicle routing solver is typically used to determine the most efficient routes for a fleet of vehicles tasked with servicing a series of stops.

Figure 5.5 - Vehicle Routing Solver

Credit: ESRI [57]

Location-Allocation Solver

The location-allocation solver can be used to determine how effectively a facility site is servicing locations which have a need for its services. As such, it can be used to select the best location for a facility from a series of candidate locations.

Figure 5.6 - Location-Allocation Solver

Credit: ESRI [57]

This week, we’ll take some time to explore state Departments of Transportation (DOTs). All 50 states have a department of transportation, and while there are many similarities between them, they can differ in both how they are organized and in the specific functions they perform. A convenient set of links for all 50 state DOTs [58] is maintained by FHWA.

The origins of most state DOTs trace back to the early 1900s. At that time, they were commonly named State Highway Departments and, as the name implies, their focus was almost exclusively on highways. In the 100 or so years since then, their roles have evolved, and the responsibilities have increased dramatically. Today, state DOTs typically operate or oversee all modes of transportation within the state, and the scope of their functional responsibilities have grown from engineering and construction to include planning, safety, assessment, and mitigation of project impacts on the environment and community resources, driver’s licensing and vehicle registration, permitting, and providing technical support and oversight for local roads. A good summary of the roles and responsibilities of a state DOT is provided in Chapter 2 [59] of the National Cooperative Highway Research Program’s (NCHRP) Report No. 750 titled “Strategic Issues Facing Transportation, Volume 5: Preparing State Transportation Agencies for an Uncertain Energy Future [60] (2014).”

Given the extensive number of functions a state DOT is responsible for performing, there are a tremendous number of opportunities for applying spatial technologies, some of which we have looked at already (FHWA maintains a searchable compilation of state GIS-T projects [61]). Consequently, state DOTs have a substantial need for GIS expertise, although the degree to which these needs are outsourced varies. GIS expertise within the DOT is often housed in their planning or information technology organizations. AASHTO maintains a list of GIS-T contacts [62] for each state.

There are no one-on-ones scheduled for this week.

Next week, we'll hear from 2 speakers.

Speaker #1

Our first speaker will be Mr. Bill Schuman. Bill is the Sr. Vice President of Project Delivery for Transcend Spatial Solutions. His responsibilities include project manager oversight; providing subject matter expertise for road inventory, asset management, linear referencing systems (LRS), and road data models; business operations; and guiding the company’s strategic direction. He has over 28 years of transportation and GIS experience. He is a recognized LRS and transportation data expert and has worked with state and local governments on IT strategic plans, spatially enabled database and data warehousing projects, LRS design and implementation projects, and many custom data maintenance and data presentation applications.

Bill holds a B.S. in Civil Engineering from the University of Wyoming and is a GIS Professional.

Linear Referencing Systems (LRSs)

Transportation agencies capture a wide variety of information about their roadways in addition to information about assets or occurrences along their roadways. Some of these attributes relate to a specific location (e.g., crashes) while other attributes relate to a section of roadway (e.g., speed limit). Collectively, these point or linear attributes are referred to as events.

Figure 5.7 - Crash and Speed Limit Events

The large number of events which need to be associated with the geometry of the roadway creates a challenge due to the fact that they often change values at different locations. For example, the locations where speed limit changes occur generally doesn’t correspond to the points where changes in pavement type, the number of lanes, or the condition of the roadway occur.

Figure 5.8 - Route Events

Credit: ESRI [63]

Consequently, if we were to attempt to segment the roadway in such a way to ensure all attributes were constant over the length of each segment, we would wind up with a highly segmented roadway. Alternatively, if we were to create a separate linear feature class for each roadway attribute, we would have a large number of feature classes that would need to be maintained. One solution to this problem is to separate the events data from the route geometry and maintain them in separate tables which relate to the route geometry according to the route name and a linear measure (for point events) or pair of measures (for linear events) which indicate the location of the event along the route.

There are many different ways one can locate an event along a route. For example, an event could be located according to its distance along the route in miles from the county line. Alternatively, the distance could be measured from the beginning of the route or some other established marker or datum. These different approaches are referred to as Linear Referencing Methods (LRMs).

Given the relationship between the events in the events table and the route features, GIS software can dynamically create feature classes for any specific event or combination of events. This process is known as dynamic segmentation. The standard set of geoprocessing tools can then be applied to these dynamically generated features just as they can be applied to a persistent feature class.

The entire system which an organization uses to allow for the separation of event data and dynamic generation of feature classes is known as a Linear Referencing System (LRS). LRSs have been used extensively with road networks, but they are applicable to other types of linear networks as well, including pipelines and hydrologic networks.

Speaker #2

Our second speaker will be Mr. Derald Dudley. Derald is a geographer and computer scientist in the Office of Spatial Analysis and Visualization (OSAV) which is part of the USDOT's Bureau of Transportation Statistics (BTS). He also chairs the Federal Geographic Data Committee (FGDC) Transportation Subcommittee.

BTS and the National Transportation Atlas Database (NTAD)

In April 1994, then-President Bill Clinton signed Executive Order 12906 titled “Coordinating Geographic Data Acquisition and Access: The National Spatial Data Infrastructure.” Since then, the FGDC together with their partner organizations have developed and revised a strategic plan to advance the National Spatial Data Infrastructure (NSDI). The most current version of the plan can be found here. [64] The USDOT’s Bureau of Transportation Statistics (BTS) [65] is responsible for overseeing the transportation components of the NSDI through the National Transportation Atlas Database (NTAD) [66]. Take some time to familiarize yourself with BTS and the NTAD. Also, take a look at the following datasets included in the NTAD: Highway Performance Monitoring System (HPMS) and the National Highway Planning Network (NHPN). Finally, read about the National Transit Map [67] which also generates datasets included in the NTAD.

In this lesson, we learned about network analysis and the broad set of transportation problems it can be used to address. We examined how network analysis is implemented in ESRI's Network Analyst extension to ArcMap and examined the 6 categories of network analysis or solvers which it provides. In addition, you had the chance to get some hands-on experience with a few of the solvers. You will have additional opportunities to apply these tools in upcoming lessons as well.

Our transportation organizations of the week were state DOTs. We reviewed some the key functions these organizations perform and looked at how their roles have changed over the past century. You also explored a state DOT of your choice and became familiar with an example of how they use spatial technologies.

In our weekly webinar, we had the chance to interact with Frank DeSendi, the Manager of PennDOT's Geographic Information Division, and review how PennDOT utilizes spatial technology to help them identify potential impacts a transportation project could have on the environment. We also had the opportunity to interact with Greg Ulp, a senior project manager who was the technical architect for MPMS-IQ, a GIS application used by PennDOT to disseminate project information to the public and other interested parties.

In preparation for next week's webinar, we learned a bit about LRSs and dynamic segmentation, important topics in GIS-T which we will cover in more detail in next week's lesson. We also learned about the National Transit Atlas Database (NTAD) and some of the important datasets it contains.

What will we learn?

By the end of Lesson 6, you should be able to:

• use ArcMap’s Linear Referencing Tools to construct routes from roadway centerline features;
• calibrate the measures along a route based on actual measures made in the field;
• describe the purpose and characteristics of a Straight Line Diagram (SLD);
• create an SLD given event data along a route;
• discuss the key functions of the American Association of State Highway and Transportation Officials (AASHTO);
• discuss some emerging technologies in Intelligent Transportation Systems (ITS) and the objectives and features of traveler information systems;

Last week, we explored the purpose and components of an LRS. This week, you’ll have an opportunity to solidify your understanding by completing some hands-on exercises to create routes, calibrating linear measures along a route, and using dynamic segmentation to convert event tables into event features. You’ll also see how GIS software can be used to reduce the burden associated with the creation and management of an LRS and event data.

In the past few years, ESRI has been promoting their Roads and Highways product which is designed to provide a fuller featured set of tools for transportation organizations to manage their LRS and roadway event data. A 57-minute introduction to this tool [68] was provided at the 2013 ESRI users’ conference.

Straight Line Diagrams

Transportation organizations capture and maintain a large number of linearly referenced roadway events including:

• Intersections
• Bridges
• Rail Crossings Locations
• Legal Boundaries
• Accidents
• Signs
• Speed Limits
• Average Annual Daily Traffic (AADT)
• Width of the Right of Way
• Width of the Roadway Shoulders
• Functional Class
• Curves
• Grades
• Projects

Displaying more than a few of these on a single map can begin to clutter the map and make it difficult for the user to understand.

One tool which transportation organizations have used for many years to visualize road attribute information is a Straight Line Diagram (SLD). In an SLD, a roadway section of interest is presented as a straight line along with various roadway attributes or events. Often, these roadway attributes are maintained by separate groups within the transportation organization, and sometimes they are linearly referenced using different LRMs. An SLD brings many attributes together with a uniform referencing method to facilitate visualization of the data and the potential identification of relationships between different data elements.

The specific layout of SLDs varies from one organization to another. One common layout for an SLD includes three components: a map component, a schematic component, and an attribute component. The map component often appears at the top of the SLD and presents the alignment of the route of interest. The schematic component, sometimes referred to as a stick diagram, presents the route as a straight line and can incorporate roadway features such as intersections, bridges, ramp entrances, and exits and legal boundaries. The attribute component includes roadway event data presented along the same horizontal axis. Linear events such as speed limit are displayed as a series of horizontal bars with the extent of each bar corresponding to the region over which the attribute has a constant value. Point events are displayed as point symbols positioned according to their location along the route.

Figure 6.1 - Example SLD Layout

Historically, SLDs were manually created and assembled into books for reference across the organization. Given the effort required to generate SLDs in this manner, the books often reflected data which was somewhat dated. Today, most SLDs are created dynamically from current event data using sophisticated GIS software applications.

As an example, the Massachusetts Department of Transportation uses a web-based tool called Massachusetts Route Log [69] to generate Straight Line Diagrams (SLDs). Here is an example SLD generated from this application for a portion of State Route 9.

Figure 6.2 - Massachusetts Route Log

Credit: MassDOT

Vermont’s Agency of Transportation (VTrans) has a similar SLD tool called VTrans Routelogs [70].

Figuren 6.3 - VTrans Routelogs SLD

Credit: VTrans

This week, you’ll take some time to get to know the American Association of State Highway and Transportation Officials (AASHTO). AASHTO is an association comprised of representatives from the state transportation agencies in all 50 states, the District of Columbia, and Puerto Rico. AASHTO seeks to promote transportation excellence and integration across the U.S. and to foster effective communication and cooperation between the state DOTs and the federal government. Founded over a century ago, it was originally named the American Association of State Highway Officials (AASHO). As with state DOTs, its focus has broadened over the years, and in 1973, it was renamed the American Association of State Highway and Transportation Officials (AASHTO) to reflect the fact that its scope of activities spans all modes of transportation.

AASHTO administers a variety of technical programs. A few of their more significant areas of activity are briefly discussed below.

Standards and Publications

AASHTO establishes technical standards and guidelines which are generally adhered to by the state DOTs in addition to many organizations outside the U.S. It has published many highly respected and widely used reference documents spanning a variety of transportation disciplines including the following:

• A Policy on Geometric Design of Highways and Streets (also known as “The Green Book”)
• The Highway Safety Manual (HSM)
• Standard Specifications for Transportation Materials and Methods of Sampling and Testing
• AASHTO LRFD Bridge Design Specifications.
• Manual for Assessing Safety Hardware (MASH)

AASHTOWare

AASHTO manages a program aimed at providing exceptional enterprise level software to transportation agencies. These products incorporate the experience and expertise of its member organizations and have been developed using pooled funds from state DOTs and the FHWA. The suite of software developed in this program is collectively known as AASHTOWare and its products span 5 core business areas:

• Project
• Bridge
• Safety
• Pavement
• Right of Way

An overview of the AASHTOWare program is provided in this 7-minute video [71]. AASHTO also publishes a catalog of AASHTOWare products [72]. Many of the AASHTOWare software products incorporate varying levels of spatial technology. For example, the bridge products use the Google Maps API for spatial analysis and visualization.

Research

AASHTO is very active in the area of transportation research. A substantial portion of the research AASHTO promotes is carried out by the National Cooperative Highway Research Program (NCHRP).

AASHTO Materials Reference Laboratory

The AASHTO Materials Reference Laboratory [73] (AMRL) develops protocols for testing construction materials and accredits laboratories who test these materials. Many state DOTs require laboratories to be AMRL accredited before they will do business with them.

Centers of Excellence

AASHTO also operates the following three centers of excellence, each of which is designed to provide information and expertise in a specific area of transportation:

• Center for Environmental Excellence
  This center focuses on environmental considerations associated with transportation.
• National Operations Center of Excellence (NOCoE)
  This center focusing on topics relevant to transportation operations.
• Build America Transportation Investment Center (BATIC) Institute
  This center focuses on funding and financing transportation projects.

There are no one-on-ones scheduled for this week.

Speaker

Next week, we will have a webinar with Doug Tomlinson, Chief of Traffic Operations at the Pennsylvania Department of Transportation. Doug's career has focused on various aspects of traffic engineering including work zone traffic control, traffic signals, traffic calming, incident management, ITS, and Traffic Operations. He is currently a Chief of Traffic Operations for PennDOT's Bureau of Maintenance and Operations with a focus on Planning and Operations.

Doug has worked for PennDOT since 1994. He was named ITS PA person of the year by the Pennsylvania chapter in 2013. Doug was a graduate of PennDOT's first Executive Development Academy, as well as a 2008 Graduate of the Operations Academy. Doug graduated Magna Cum Laude from the University of Pittsburgh at Johnstown in 1993 with a B.S. in Civil Engineering Technology.

Intelligent Transportation Systems

Intelligent Transportation Systems (ITS) is an exciting subfield of transportation which encompasses a broad array of technologies. The unifying goals of ITS technologies and systems are to help us use our transportation network more effectively and to allow us to make more informed decisions. One of the most active areas within ITS is in the area of Connected Vehicles and Autonomous Vehicles (CV/AV). Check out this TED talk [74] (4:06) from 2011 on Google's driverless car:

Traveler Information Systems

An area of ITS which has become very popular in recent years is traveler information systems. These systems disseminate real-time information to travelers in order to allow them to make more informed choices. These systems commonly contain the following types of information:

• Traffic and road conditions
• Construction projects
• Planned events
• Camera video and images
• Incidents
• Weather information

Traveler information can be disseminated by a number of methods including via Highway Advisory Radio stations (HAR), Variable Message Signs (DMS) and 511 websites, mobile applications, and IVR systems. On July 21, 2000, the Federal Communications Commission designated a single 3 digit number (511) which could be used anywhere in the nation to obtain traveler information. Implementation of the services themselves was left to states and local agencies.

The Federal Highways Administration (FHWA) hosts a 511 Travel Information Telephone Services [75] website which shows the locations in the U.S. which provide 511 telephone services. As you can see from this site, most states in the U.S. operate a 511 information service. If you click on any location with 511 telephone services, you'll be given more information about the 511 services of that state/location. You'll notice that there is a “backdoor” number you can use to call 511 in a state even if you are not in that state. The information provided also gives the link to the corresponding 511 website if there is one.

In this lesson, we explored how GIS tools can be used to help maintain an LRS and event data. We also examined dynamic segmentation, a process used to convert event data into event features, and some very useful diagrams known as Straight Line Diagrams (SLDs).

Our transportation organization of the week was AASHTO. We reviewed some of the important roles AASHTO plays in establishing policy, producing important guidance documents, conducting and promoting research, and in creating exceptional software products for a number of functional areas in transportation.

In our weekly webinar, we had the chance to interact with Bill Schuman, Sr. Vice President of Project Delivery for Transcend Spatial Solutions, and benefit from his expertise and many years of experience in the area of LRS.  We also had the opportunity to interact with Derald Dudley, a geographer and computer scientist with the USDOT's Bureau of Transportation Statistics (BTS).

In preparation for next week’s webinar, we also spent some time learning about intelligent transportation systems and, in particular, traveler information systems.

What will we learn?

By the end of Lesson 7, you should be able to:

• explain how traffic safety analysis is moving beyond traditional approaches which have focused solely on historic crash data;
• navigate the Fatality Analysis Reporting System (FARS) and perform ad-hoc queries of the data it contains;
• use crash data extracted from FARS or other state crash data systems to visualize and analyze the data in ArcGIS;
• list some of the uses and benefits spatial technologies offer in the area of highway safety;
• describe some of the goals and objectives of the National Highway Traffic Safety Administration (NHTSA);
• submit a review of Pennsylvania's 511 Traveler Information System;
• discuss the purpose of the Highway Performance Monitoring System (HPMS) and the requirements it imposes on state DOTs;
• share something you learned about one of your classmates and/or some ideas you discussed with a classmate about the content of this week’s lesson.

Highway safety is an important area of focus for state DOTs and the USDOT. There are few groups within the USDOT who are focused on improving highway safety. The first is the Office of Safety. The Office of Safety is comprised of two units. The Technologies Unit deals with safety-related highway design considerations and technologies which can be used to improve highway safety performance. The Programs Unit oversees federal and state safety programs. One of the key programs they administer is the Highway Safety Improvement Programs (HSIP). HSIP is a federal-aid program designed to provide funding to states for projects aimed at reducing fatalities and serious injuries on qualifying roadways. In 2016, the program provided about 2.2 billion dollars to the states for safety projects.

Reference: FHWA Website [76] accessed 12/31/2016

To qualify for HSIP funds, a state is required to develop and maintain a Strategic Highway Safety Plan (SHSP). An SHSP is designed to guide the investment of funds to projects which have the greatest potential to reduce fatalities and serious injuries. To qualify for HSIP funds, states are also required to identify their priorities using a Data-Driven Safety Analysis (DDSA).

The second group within USDOT which is responsible for highway safety is the National Highway Traffic Safety Administration (NHTSA). NHTSA is an administration within USDOT whose mission is to reduce crash fatalities and injuries. We’ll take a close look at NHTSA later in this lesson.

State DOTs commonly collect and use crash data to identify areas of their roadway networks where there are unusually high crash rates. However, looking at crash data alone can be misleading and result in a less than optimal use of available state and federal dollars. To address this problem, AASHTO, in conjunction with the FHWA, developed the Highway Safety Manual (HSM), a document which many consider the definitive reference on highway safety. The HSM offers a comprehensive and balanced approach and set of tools which consider operations, the environment, and the cost of construction alongside safety considerations. A good overview of the HSM can be found here. [77] The approaches provided in the HSM go beyond traditional approaches to identifying priority locations for safety improvements which rely solely on crash history data.

There are two fundamental problems associated with using crash data alone. First, crashes are statistical events and as such don’t occur at regular predictable intervals. Consequently, crash data alone can sometimes lead an agency to falsely identify sections of a roadway as high risk and, conversely, sometimes overlook a risky section. The second problem of looking solely at historic crash data is that it disregards the dependence of crash frequency on traffic. As traffic levels increase on a section of the roadway due to changing travel patterns, crash rates can increase. To overcome these limitations, it is necessary to look not only at historic crash frequencies but also at expected crash frequencies based on roadway characteristics and traffic data.

Tools have been developed which implement the approaches defined in the HSM. These include AASSHTO’s Safety Analyst and FHWA’s Interactive Highway Safety Design Model (IHSDM). However, states often lack much of the data required to effectively use these tools, such as horizontal and vertical curve data. Horizontal curves are roadway curves that turn to the left or right, and vertical curves are roadway peaks/hills and valleys. For my Capstone Project, I used roadway centerline data to extract horizontal curvature data from Pennsylvania’s roadways. I gave a lightning talk on the project at Penn State in November 2016 for GIS day. My presentation was just under 10 minutes in length (embedded video below). 

Two model frameworks have been developed to help states structure the crash and roadway data needed for highway safety analyses in a standard format. The first is the Model Minimum Uniform Crash Criteria (MMUCC [78]). MMUCC is a list of standard crash data elements and associated definitions developed by NHSTA. While the implementation of this model is voluntary, states are encouraged to adhere to the standard in collecting and compiling crash data. Similar in concept to the MMUCC, the Model Inventory of Roadway Elements MIRE [79] is a list of over 200 roadway and traffic data elements critical to safety management developed by the FHWA.

Collecting roadway data according to the MIRE model will not only benefit the state DOT in regards to traffic safety efforts, it will also help other core areas of transportation such as operations, asset management, and maintenance.

Countermeasures

Once a section of roadway has been identified for needed safety improvements, an agency needs to decide which types of countermeasures would be the most effective. There are many types of safety countermeasures that could be implemented. Here’s a list of 20 proven countermeasures [80] published by FHWA’s Office of Safety.

FARS [81] is a system used to collect, store and analyze fatalities on U.S. roadways. The system is administered by the National Center for Statistics and Analysis (NCSA) which is part of the National Highway Traffic Safety Administration (NHTSA). The system includes data from all 50 states, the District of Columbia, and Puerto Rico. The primary purpose of the system is to monitor the effectiveness of vehicle safety standards and highway safety programs which are implemented at the state level. Only crashes which result in at least one fatality and occur on a roadway which is open to the public are included in FARS.

Figure 7.1 - NHTSA's Fatality Analysis Reporting System (FARS)

Credit: NHTSA Website [81] (accessed on 1/1/2017)

Pennsylvania Crash Information Tool (PCIT)

Some states make crash data available to the public and other interested parties via a web portal. As an example, Pennsylvania makes crash information available via the Pennsylvania Crash Information Tool (PCIT) [82].

Figure 7.2 - Pennsylvania Crash Information Tool (PCIT)

Credit: PCIT Website [82](accessed on 1/1/2017)

Many of the reports on this site are similar to those in FARS. PennDOT is in the process of adding mapping capabilities to the next version of PCIT scheduled for release in the spring of 2017. Similar to FARS, PennDOT also makes raw crash data available. The PCIT site simply guides users to the PennDOT’s GIS Data Portal [83] for this data.

Figure 7.3 - PennDOT's GIS Data Portal

Credit: PennDot's Data Portal Website [83] (accessed on 1/1/2017)

Pennsylvania crash data is available from 1997 to 2016. Differences between the FARS crash data and PennDOT’s crash data include:

• crash data from PennDOT include all reportable crashes and not just fatal crashes;
• crash data from PennDOT include many more attributes or “flags” which can be used to filter the crashes;
• PennDOT’s GIS Data Portal provides very limited querying options (year and county only) and, consequently, the burden is on the user to filter the data to meet their needs.

GIS Uses and Benefits in Highway Safety

As we learned in Lesson 6, spatial technologies are used to locate crashes and perform crash analysis to locate crash hotspots, otherwise known as crash clusters. Spatial technologies also play a critical role in expanding network screening to include roadway characteristics and traffic data in addition to historic crash data as called for in the HSM. Spatial analyses not only help in identifying priority sections of the roadway for safety improvements, but they can also be used to determine the countermeasures which are most likely to be effective and to assess their impact once they have been in place for a period of time. Finally, and perhaps most importantly, GIS plays a huge role in vehicle to vehicle communications and autonomous car technologies. These initiatives promise to have revolutionary impacts on highway safety and make the goal of 0 fatalities seem not so far-fetched.

This week, you’ll take some time to get to know the National Highway Traffic Safety Administration (NHTSA - pronounced "NITS-uh”). NHTSA is an agency within the USDOT responsible for reducing deaths, injuries, and economic losses resulting from motor vehicle crashes. The agency was created by the Highway Safety Act of 1970 to administer programs that had previously been the responsibility of the National Highway Safety Bureau.

Dr. Mark Rosekind was the NHTSA Administrator under the Obama administration. Take a look at a 37-minute presentation (below) he gave at the Original Equipment Suppliers Association [85](OESA) 2016 annual meeting. Also, spend some time reviewing NHTSA’s 2016-2020 strategic plan titled “The Road Ahead [86]”.

Video: NHTSA Administrator Dr. Mark Rosekind's presentation at OESA Annual Conference, Nov. 2, 2016 (37:36)

Credit: THE ROAD AHEAD, National Highway Traffic Safety Administration Strategic Plan 2016—2020 (USDOT, NHTSA October 2016)

A few of NHTSA’s areas of focus are briefly described below:

Vehicle Safety Ratings and Recalls

NHTSA plays a large role in accepting and tracking vehicle safety complaints which can ultimately lead to safety recalls. They also administer the New Car Assessment Program (NCAP) which assesses and scores vehicle models using a 5-star safety rating. Safety rating and recall information [88] is compiled and made available to consumers. Using this information, consumers can quickly determine how specific vehicles perform in front-end, side, and rear-end collisions in addition to rollovers. NHTSA also compiles safety information on car seats, tires, and other equipment.

Data-Driven Approaches to Crime and Traffic Safety (DDACTS)

DDACTS is a model which NHTSA developed in association with the Department of Justice (DOJ). It uses the temporal and spatial analysis of crash and crime data to identify the optimal deployment of highly visible law enforcement personnel and vehicles. Detailed information about the model is available in the DDACTS Operational Guidelines [89].

National 911 Program

The purpose of the National 911 Program [90] is to promote and coordinate 911 services across the U.S. NHTSA is currently promoting and rolling out the Next Generation of 911 (NG911) which will modernize 911 systems based on advances in technology which have occurred since 911 was first put in place 50 years ago.

Office of Vehicle Safety Research

The Office of Vehicle Safety Research is a NHTSA Office that develops and implements research programs designed to reduce crashes, fatalities, and injuries. Some of their research activities can be found here [91].

National Center for Statistics and Analysis (NCSA)

The NCSA [92] is an office within NHTSA which provides analytical and statistical support to the agency through data collection, crash investigations, and data analysis. One of NCSA’s responsibilities is to maintain and enhance FARS. They also produce many useful and interesting publications summarizing information gathered by NHTSA [93].

This week, you’ll have a one-on-one chat with one of your classmates (or me) as per the schedule you were provided in Week 1. The discussion should be at least 30 minutes in length. If it’s the first time you’ve chatted with each other, spend the majority of time getting to know each other. Otherwise, focus on discussing the lesson content.

Next week, we'll hear from 2 speakers.

Speaker #1

Our first speaker will be Mr. Jeff Roecker. Jeff graduated from Penn State with a degree in Geography and joined PennDOT in 2008. Jeff plays a lead role in the Department's Crash Data Analysis and Retrieval Tool (CDART), and he is the project manager for PennDOT's Strategic Highway Safety Plan (SHSP).

Crash Data Collection

FHWA requires all states to maintain a database of crashes in order to support the analysis of crash locations. There is variation from state to state on how they define reportable crashes, how they collect the information and how readily they share the information. Many states publish annual summaries of crash data for the prior year and also provide trending information for various crash statistics. The Pennsylvania Department of Transportation (PennDOT) publishes an annual report entitled Crash Facts and Statistics. The 2016 version of this publication can be found here [94].

Crash data is important to state DOTs for a number of reasons. First, without this data, an agency doesn’t know if things are improving. Second, this data can offer clues to where safety improvement or countermeasures are most needed. Crash patterns can also be used to help law enforcement design initiatives associated with seat belt usage and checkpoints for impaired drivers.

Law enforcement officials are generally responsible for reporting crashes. In Pennsylvania, the Commonwealth of Pennsylvania Police Officers Crash Report Manual provides law enforcement agencies instructions on reporting crash data including definitions of which types of crashes are reportable to PennDOT. The police use a multipage form (AA 500 [95]) to report crash data. The form captures extensive information about the crash including the location, all vehicles and individuals involved in the crash, the number and nature of any injuries, weather and road conditions at the time of the crash, a diagram of the crash, and statements from any witnesses. PennDOT also provides a detailed reference document known as Pub 153 [96] to help police officers complete the form correctly.

PennDOT also has a web-based system called the Crash Reporting System (CRS) which provides an electronic alternative to submitting crash data. A user’s guide for the system can be found here [97]. CRS is also used by PennDOT to review and validate all data which is automatically retrieved from paper forms which are received from law enforcement agencies. Any meaningful analysis of crash data requires that the data is accurate and complete.

Crash Analysis

State DOTs use crash data to identify locations where there are unusually high crash rates and also to determine measures which will likely lower these crash rates. One of the most useful types of crash analysis, which is used by many state DOTs, is a spatial technique known as cluster or hot spot determination. This type of determination is done using GIS software by stepping along each route and identifying sections of roadway which meet the definition of a crash cluster based on established parameter settings for the analysis.

In Pennsylvania, crash data submitted by law enforcement agencies electronically via CRS or the AA500 paper form, are processed and stored in a system known as the Crash Data Access and Retrieval Tool (CDART). CDART is a geospatial application which allows PennDOT to perform a variety of crash analyses including crash cluster analyses. It performs two basic types of crash cluster analysis. The first is a standard cluster analysis where each road is considered separately. The second is an intersection-based cluster which examines the number of crashes which occur on all associated roads within a certain distance of the point of intersection. One of the other interesting analyses CDART performs is a “before and after” analysis which compares crash frequencies for a section of roadway before and after a safety improvement was implemented to determine its effectiveness. For each of the analyses CDART performs, the system allows the user to generate tabular or map-based outputs. CDART is an internal tool to PennDOT and is not available for public use.

On May 30, 2013, Sharon Hawkins of the Arkansas DOT gave a 42-minute presentation on some of the GIS tools [98] they use to locate and analyze crashes (located below). The presentation was part of the FHWA GIS in Transportation webinar series. The webinar provides an excellent perspective on the importance of GIS in collecting and analyzing crash data. Many states have gone through a similar evolution and set of problems in their efforts to manage and utilize crash data to improve highway safety.

Video: GIS Tools Used to Locate & Analyze Crashes (42:28)

Speaker #2

Our second speaker will be Mr. Jeremy Freeland. Jeremy is a Transportation Planning Manager in the Transportation Planning Division of PennDOT’s Bureau of Planning and Research. He is responsible for coordinating and overseeing all of PennDOT’s traffic collection efforts, both manual and automated. He is also responsible for assembling PennDOT’s annual Highway Performance Monitoring System (HPMS) submittal to the Federal Highway Administration (FHWA). Jeremy has been with PennDOT for 13 years. He earned a geography degree from Shippensburg University in 2003.

Highway Performance Monitoring System (HPMS)

FHWA is responsible for collecting sufficient highway characteristics and performance data in order to support their own needs as well as those of the USDOT and Congress. HPMS is a national information system which was created to fulfill this need. Initially developed in 1978 as a replacement of biennial roadway condition studies which began in 1965, one of the primary purposes of HPMS is still to provide Congress with a biennial assessment of U.S. roads for use in estimating future highway investment needs. Here is a link to the 2015 Status of the Nation's Highways, Bridges, and Transit: Conditions & Performance [99]. HPMS is also used for a multitude of other purposes, not the least of which is apportioning Federal-aid highway monies to the states.

The specific data collection and reporting requirements state DOTs need to comply with are defined in the HPMS Field Manual [100]. FHWA also provides software to submit, validate, and analyze state HPMS data. This software is web-based and is only available to authorized users (typically those staff at a state DOT with responsibilities for reporting HPMS data). The guide for the latest version of this software (i.e., version 8.0) is provided here. [101]

Traffic Data

One of the most important types of data collected for HPMS is traffic data. Of the 70 or so HPMS data elements states are required to report, about a dozen are traffic elements. FHWA’s 2016 Traffic Monitoring Guide [102] is a document designed to help states put together a traffic monitoring program.

In this lesson, you learned about traffic safety and the efforts of state DOTs to make our highways safer. You also took a close look at federally reported crash data (i.e., FARS) in addition to an example of crash data which is collected at the state level.

Our transportation organization of the week was NHTSA, an administration with USDOT focused on reducing fatalities and serious injuries on America’s roadways. You had the opportunity to explore some of their specific activities and programs.

In our weekly webinar, we had the opportunity to interact with Doug Tomlinson, an expert in ITS. 

In preparation for next week’s webinar, you learned a little about how crash data is collected in the field.  You also took a look at HPMS and about the types of traffic data states need to collect in addition to the methods and tools they use to collect it.

Finally, you had the opportunity to get to know one of your classmates a little better and share some of your ideas and questions about this week’s lesson materials.

What will we learn?

By the end of Lesson 8, you should be able to:

• list the different devices which are used to collect traffic count data;
• describe some of the primary uses of traffic count data;
• use a roadway video log system to monitor roadway assets;
• describe some of the work being done by Volpe, The National Transportation Systems Center;
• discuss some of the congestion pricing strategies that have been implemented around the world and list some of the outcomes which have been observed.

There are two types of traffic data that state DOTs use. The first is live traffic data, and it is generally used to measure and address congestion. Often, live traffic data is measured by monitoring vehicle speeds. There are a number of companies that collect speed data by enlisting fleets of vehicles to share their location data. These companies sell the data to state DOTs and others interested in real-time traffic. One such company is INRIX.

The other type of traffic data that state DOTs use is traffic count data. There are a variety of devices which are commonly employed to obtain traffic counts. A few of the more common devices are described below:

• Automatic Traffic Recorder (ATR)
  ATRs are permanent traffic counting devices which operate 24/7/365 and are installed below the road surface. ATRs capture traffic volume, but do not differentiate between vehicle types.
• Continuous Automatic Vehicle Classification (CAVC) 
  CAVCs are also permanent traffic counting devices which operate 24/7/365 and are installed below the road surface. In addition to counting vehicles, these devices classify vehicles into the 13 categories which FHWA requires (see Figure 1).
• Weigh-in-Motion (WIM)
  Like ATRs and CAVCs, WIMs are also permanent traffic counting devices which operate 24/7/365 and are installed below the road surface. In addition to counting and classifying vehicles, WIMs also capture truck weights.
• Short-Term In-Pavement (STIP)
  STIPs are semi-permanent traffic counting devices much like ATRs. These devices are typically only used to collect counts once a year for a 24-hour period.
• Portable Short-Term Counter
  These are temporary traffic counting devices which make use of pneumatic tubing which is laid across the road. Different configurations can be used to achieve simple traffic counts or vehicle classification counts. The majority of traffic counts are performed using these devices.

The computers which capture, store, and transmit ATR, CAVC and WIM data back to a central location are typically housed in secure enclosures which are positioned alongside the roadway and are equipped with a permanent power source. STIP sites are not equipped with permanent computers and power. Instead, portable units are used to complete the period counts at these locations.

Figure 8.1 - FHWA's 13 Vehicle Classifications

Click for a text description of Figure 8.1

Class 1: Motorcycles

Class 2: Passenger cars

Class 3: Four tire, single unit

Class 4: Buses

Class 5: Two axle, six tire, single unit

Class 6: Three axle, single unit

Class 7: Four or more axle, single unit

Class 8: Four or less axle, single trailer

Class 9: 5-Axle tractor semitrailer

Class 10: Six or more axle, single trailer

Class 11: Five or less axle, multi trailer

Class 12: Six axle, multi-trailler

Class 13: Seven or more axle multi-trailer

Credit: FHWA

The Value of Traffic Data

Traffic data has a wide variety of uses, a few of the most significant of which are listed here:

HPMS Reporting

One of the most significant uses is to comply with federal HPMS reporting requirements. As was covered last week, states need to report HPMS data to the FHWA each year. HPMS reporting is particularly important to state DOTs since the apportionment of federal funding is based on it.

Highway Safety Improvement Programs (HSIP)

HSIP is a federal aid program aimed at reducing traffic fatalities and major injuries. FHWA requires the project selection process to be data-driven. Traffic data is required to determine crash rates and, consequently, it plays an important role in selecting eligible HSIP projects.

Highway Design

Traffic count data is considered in the design of new roads and the rehabilitation and enhancements of existing roads.

Congestion Management

While real-time congestion management approaches typically use live traffic data based on vehicle speeds, traffic count data can be used to assess congestion and the prospective benefits of ITS technologies.

Roadway Video Logging

Many state DOTs acquire roadway video from specially equipped vehicles which drive all the state-owned roadways. The video data is then made available via a software application which allows users to go on a “virtual drive.” A few examples are Oregon Department of Transportation’s (ODOT) Digital Video Log (DVL) [105] system and PennDOT’s Video Log [106] application. There are many uses of roadway video systems, not the least of which is that they can serve as a means to monitor and maintain roadways and roadway assets, which is both safer and less expensive than an actual visit. The traffic group in PennDOT, for example, uses Video Log to scope out new locations for conducting counts.

Figure 8.2 - PennDOT's Video Log Application

Credit: PennDOT [106]

This week, you’ll take some time getting to know Volpe, The National Transportation Systems Center. Volpe, which is part of the USDOT, is located in Cambridge, Massachusetts and was founded in 1970. It provides a variety of engineering and scientific services to the public and private clients it services and is fully funded by the project work it performs. Its mission is to promote innovative ideas in order to improve the US transportation system. An overview of Volpe’s activities is provided here [107].

Congestion Pricing

Congestion pricing represents a variety of approaches which are aimed at shifting traffic away from a congested section of roadway by implementing pricing surcharges during peak periods to shift some traffic to off times, alternate roadways or alternative modes. In 2007 – 2008, the USDOT invested over a billion dollars to implement congestion-reducing strategies in six US cities. For two of the cities, Volpe was asked to conduct surveys to better understand how congestion pricing affects travel choices. A summary of Volpe’s findings is here [108].

To promote the use of congestion pricing, the FHWA published a primer series on the topic [109], the first of which provided a high-level overview of the concept.

There are no one-on-ones scheduled this week.

Speaker

Our speaker will be Mr. Rodney Bunner. Rodney is a Geospatial Technology Specialist who, over the past twenty years, has worked as a consultant to local, regional, state, and federal agencies in developing spatially-enabled and GIS-T applications. He has contributed to the development of a variety of software products and tools within different government sectors including:

• Public Transportation agency support for planning and operations;
• Metropolitan/Regional Planning Organization support for multi-modal transportation planning including travel demand modeling and market assessments;
• State Department of Transportation highway asset management and linear referencing including interactive straight-line diagramming;
• Department of Defense (DOD) facility operations and asset management.

As a public-sector consultant, Rodney’s professional objective has been to develop software applications which streamline the technically challenging and time-consuming data integration, data development, and analytical processes required to fulfill specific government business needs and workflows. To this end, over the past thirteen years, he has been the lead developer for the Florida Department of Transportation’s (FDOT) TBEST Transit Planning software. TBEST provides public transportation agencies with business-specific data, analytics, and reporting tools to address everyday service and strategic planning tasks. Rodney supports numerous agencies throughout the U.S. in implementing and utilizing TBEST.

Rodney is currently the President of ServiceEdge Solutions, a technology company primarily focused on the development of geospatial applications for Transportation. He is a 1991 graduate of West Virginia University with a B.A. in Geography and a 1996 graduate of Shippensburg University of Pennsylvania with a M.S. in Environmental Studies. He currently resides in the Tampa, Florida area with his wife and two children.

Title VI Considerations for Public Transportation Providers

Title VI of the Civil Rights Act of 1964 is intended to ensure people are not discriminated against on the basis of race, color, or national origin in programs which utilize federal funding. Title VI, and the regulations which FTA has put in place to implement it, place specific requirements on transit providers, especially those who provide fixed route services.

Transit Boardings Estimation and Simulation Tool (TBEST)

TBEST is a tool developed by the Florida Department of Transportation (FDOT) to help organizations analyze existing fixed route transit service and potential service changes which are being considered. CUTR has played a big role in the development of the software and also in providing support to agencies who want to use it. A CUTR webinar (57:16) on TBEST can be found here [110]. I provide this link for your reference but watching it is optional. The main speaker in the webinar is Rodney Bunner, next week’s speaker. Consequently, Rodney will likely cover much of the same material in our webinar with him next week. This tool is a very powerful tool and you are able to download and install it for free if you would like. However, you do not need to install it to complete the course requirements.

In this lesson, you learned about the different ways traffic data is collected and used. You also had the opportunity to review PennDOT’s Video Log application and use it to locate some permanent traffic counting devices.

Our transportation organization of the week was Volpe, The National Transportation Systems Center. You learned about some of the initiatives in which Volpe is engaged. In particular, you explored the concept of congestion pricing and reviewed some applications of these strategies including the manner in which they affect driver behavior and their overall effectiveness in mitigating congestion.

In our weekly webinar, you had the chance to interact with two transportation professionals. Mr. Jeff Roecker spoke about some of the tools and approaches PennDOT uses to improve highway safety and Mr. Jeremy Freeland spoke about HPMS reporting and the roles that spatial tools play in the implementation of a statewide traffic count program.

Finally, in preparation for next week’s webinar, you learned about a transit planning tool called TBEST and you reviewed some requirements that transit agencies need to meet which are based on Title VI of the Civil Rights Act of 1964.

What will we learn?

By the end of Lesson 9, you should be able to:

• describe the nature of DRT services and the primary populations they are intended to serve;
• list some of the technologies providers use to help them manage DRT services;
• characterize the most common types of DRT fare structures;
• discuss some of the characteristics of fixed route transit and explain the structure and function of GTFS data;
• describe some of the functions and accomplishments of the Federal Transit Administration (FTA);
• share something you learned about one of your classmates and/or some ideas you discussed with a classmate about the content of this week’s lesson.

Transit organizations typically offer two distinctly different types of service: Demand Responsive Transportation (DRT) and fixed route transportation. Fixed route transportation operates according to prescribed routes and schedules whereas DRT does not. In this lesson, we will look at both of these types of transit.

Demand Responsive Transportation (DRT)

DRT is generally designed to provide curb to curb or door to door service for individuals who have special transportation needs such as seniors and persons with disabilities. The availability of DRT services can vary significantly from state to state and even county to county based on funding availability. DRT differs from taxi service in two fundamental ways:

1. To use DRT, a rider must make an advance reservation (generally, at least 24 hours in advance).
2. DRT is a shared-ride type service where multiple riders can be serviced at the same time, and a rider is generally not taken directly from their point of origin to their point of destination. Consequently, DRT trips can have substantially longer ride time than taxi trips.

DRT services are generally designed to serve rural areas where fixed route transit is not practical due to low ridership and also to complement fixed route services for those who live near a fixed route but are unable to use it due to physical or cognitive limitations.

ADA Complementary Paratransit

The Americans with Disabilities Act (ADA) of 1990 prohibits discrimination against persons with disabilities in a number of areas including public transportation. The FTA has defined a series of requirements public transit providers need to meet to comply with the ADA. These requirements are found in Title 49 Part 37 of the Code of Federal Regulations (CFR). In these regulations, the FTA requires fixed route providers to provide DRT service, comparable to the level of service provided to individuals who are able to utilize fixed route services, to persons with disabilities. DRT services designed to address the needs of persons with disabilities is known as paratransit service. Specifically, bus or rail fixed route providers are required to offer paratransit services to individuals who are unable to use the fixed route service due to physical and/or cognitive limitations, who live within ¾ of a mile of a fixed route and are traveling to a destination which is also within ¾ of a mile of a fixed route. This requirement is challenging and costly for transit providers to fulfill. It applies to all providers, and not just those who are receiving federal funding. It is also an unfunded mandate in that FTA does not provide grant monies to transit agencies to help offset the cost of compliance. You’ll complete an assignment next week to evaluate the eligibility of a series of trips for complementary paratransit service.

Technologies for DRT Services

Providing DRT services in a way which is both cost effective and customer friendly is a very challenging task. The number of riders requesting service can vary substantially from day to day as can the trip origins and destinations. Service requests are initiated by riders through a call to a Customer Service Representative (CSR). Reservations typically need to be made at least 24 hours before service. Generally, the day before services are delivered, schedulers need to determine how to accommodate all of the reservations for the day with a limited number of vehicles and drivers. Further, the schedulers need to ensure a wide variety of constraints are met, including promised pickup time, required drop off times (e.g., for medical appointments) and total ride time. On the day of service, dispatchers work with the drivers to ensure all trips are successfully completed. Drivers follow a trip manifest which defines which stops they will visit and the order in which they will visit them. Drivers also need to track a variety of data elements at each stop including arrival and departure times, the passengers boarding and alighting at each stop, the vehicle odometer reading, and the amount of money collected from each passenger.

Figure 9.1 - DRT Process

Click for a text description of Figure 9.1

Schedule Ride: At least one day in advance of a desired ride, a rider calls the transit agency's reservation center to schedule a paratransit ride. → Dispatch Paratransit Vehicle: The day of the ride, the transit agency's dispatch center creates a schedule for the paratransit vehicles and dispatches a vehicle to the rider's pick-up location. → Pick-Up Rider: The paratransit vehicle arrives at the rider's pick-up location, and the driver assists the rider in boarding the vehicle and securing a mobility device. → Take Rider to Destination: The paratransit vehicle may pick up additional riders, and then drop off the rider at the pre-determined destination.

Credit: US Government Accountability Office

For all but the smallest providers, it would be very difficult to manage DRT service without technology. The most important technology which providers use is DRT software. Most DRT software assists the providers with all of the key tasks associated with delivering and reporting on the service. Many systems incorporate Automatic Vehicle Location (AVL) technology, which allows the dispatcher to monitor the location of all of their vehicles. This can be extremely useful in terms of ensuring drivers stay on task and follow the manifest. Some of the more sophisticated packages can do automated scheduling. These systems determine the best vehicle for a given trip reservation. DRT scheduling is very complex, owing to the large number of variables involved, many of which are related to human behavior, and as a result, even software that can do automated scheduling cannot produce good schedules without significant scheduler oversight.

Interactive Voice Response (IVR) technology is also playing an increasingly important role in DRT operations. Typically, systems which incorporate IVR will configure the system to automatically call riders the night before a scheduled trip to remind them of the trip and give them an opportunity to cancel the trip. Systems will also generally automatically call the riders when the vehicle is approaching their location. These calls, known as imminent arrival calls, are valuable for both the provider and riders. Providers benefit because the calls ensure riders will be ready, and riders benefit since the calls give them a clear idea of when to be ready and eliminate the need for them to wait outside for a prolonged period. IVR plays a significant role in reducing “No-Shows” where the driver gets to a location to pick up a rider and the rider is not there. No-shows add additional costs to a service which is already expensive to provide.

Many providers give their drivers Mobile Digital Computers (MDC) which serve a variety of functions. More and more DRT software vendors are shifting to tablet technology instead of using proprietary hardware. MDCs provide additional communications with dispatch via canned or ad hoc text messages. The MDCs also generally present the trip manifest information to the driver in an electronic form and tell the driver their next stop location, how well they are adhering to the schedule, how many passengers should be boarding and alighting at each stop, and how much money they should collect from each person. The driver also uses the MDC to capture the information they need to collect such as the stop arrival time, the passengers who boarded and who alighted the vehicle at the stop, how much they collected from each rider, and what time they departed from the stop. MDCs can also be configured to provide the driver with turn-by-turn directions and eliminate the need for a separate GPS device.

Fare Structures

Transit agencies use a number of different methodologies to establish a fare structure for their DRT services. The three most common are listed below:

Flat – In a flat fare structure, as the name implies, the cost of the trip is the same regardless of origin and destination, assuming both are within the agency’s service area.

Zone-Based – In a zone-based fare structure, the agency divides its service area into zones. The zones are generally comprised of a series of concentric circles or a rectangular grid which blankets the service area. Fares are then established for each origin and destination zone.

Mileage-Based – In a mileage-based fare structure, the agency develops a series of mileage-based tiers and associates a fare with each. The mileage associated with each trip depends only on the origin and destination and not on other pickups or drop-offs the driver may have performed while the passenger is in the vehicle. Consider the following example:

Ellen makes a reservation to go to the senior center on Monday at 10 am. On Friday afternoon, the agency’s scheduler is working with their paratransit software to finalize the driver manifests (i.e., schedules) for Monday morning. This process involves determining the most efficient way to deliver the service while at the same time observing customer service policies such as ensuring all riders get to their appointments on time and do not exceed the maximum onboard time established by the agency. On Monday morning, the drivers depart the transit agency and begin to execute the manifests (i.e., schedules) that have been prepared for them. The driver assigned to pick up Ellen arrives at her house to pick her up at 8:45 am. The driver then drives to Allen’s house to pick him up and on to Sue’s house to pick her up. He then drives to the VA hospital to drop off Allen and to Walmart to drop off Sue. Finally, he drives to the senior center and drops Ellen off at 9:50 am.

The driver may have visited many stops while Ellen was on the vehicle, but the mileage used for fare determination is based only on the route from her origin to her destination. When an agency uses a mileage-based fare structure, they can base the mileage on the fastest route from the origin to destination or the shortest distance route from the origin to destination.

Fixed route transit services can be defined as services which operate on predefined routes according to a set schedule. The services can be divided into a number of more specific modes including:

• Local Bus
• Commuter Bus
• Express Bus
• Bus Rapid Transit
• Light Rail
• Subway
• Ferry Boat

Figure 9.3 - Examples of Fixed Route Transit

Credit: USDOT

Routes and Patterns

Fixed route buses operate on designated routes according to a published schedule. One can think of routes as generalized paths buses follow. For example, Route 1 may be structured to provide service along Market Street. It may begin at a transit center where riders can transfer from one route to another or even to a different mode such as light rail or subway and travel along Market Street until it reaches some terminal point at which time it returns along Market Street to the transit center. The specific path each route traverses can depend on the time of the day, the day of the week, and even the time of year (e.g., summer service). Each distinct path associated with a route is called a pattern. As an example, Figure 9.2 and Figure 9.3 show two patterns for the same route. The route generally follows Pattern 1, but at times during the day when the YMCA is busiest, it follows a somewhat different pattern.

Figure 9.3 - Route 1 Pattern 1

Credit: JD Kronicz

Figure 9.4 - Route 1 Pattern 2

Credit: JD Kronicz

Trips, Headway, Interlining, and Vehicle Blocks

When one uses the term trip in regards to DRT, it generally refers to the transport of a rider from their point of origin to their desired destination. In fixed route, the term trip has a different meaning. Over the course of a day, service along a route will generally be offered a number of times. For example, service along Market Street, in the above example, may occur at a frequency of twice an hour from 9 am to 4:30 pm, with a bus leaving the transit center every 30 minutes. In the world of fixed route, a trip corresponds to a bus completely traversing the route one time. The period of time between each trip is called the headway. In this example then, there are 16 trips and the headway is 30 minutes. If it takes more than 30 minutes to complete a single trip, then it will take multiple buses to provide service along Market Street. Sometimes a bus will operate a single route the entire day, and sometimes a bus will service multiple routes. When a bus completes a trip on one route and then begins a trip on a second route, it is referred to as interlining. A bus's schedule for an entire day is called a block. For example, Bus 2a may operate on Route 1 from 9 am to 12:30 pm, at which time it is used on Route 2 from 1 pm to 5 pm. The block for Bus 2a would be the sequential set of trips it completes over the course of the day on Routes 1 and 2.

Stops, Time Points, and On-Time Performance

A stop is a designated location along a route where riders can get on or get off the bus. The bus is obligated to stop at certain stops known as time points. These are stops that appear on the bus schedule. Generally, a transit agency will have a policy that a bus should not depart a time point before the scheduled time. How well a transit provider adheres to its published schedule is referred to as its on-time performance. It is important for transit providers to adhere to their schedules since riders depend on transit to get to their destinations on time. There are also stops along a route which are not time points. The bus will only stop at these stops if a rider is waiting at the stop or if a rider wishes to alight the vehicle at the stop. In addition to defined stops, some providers accommodate flag stops. A flag stop is an arbitrary location along the route where a rider wishes to board or alight the bus. The rider needs to flag the bus down in order to board or alert the driver they wish to alight the bus at that location.

Runs and Run Cutting

Sometimes, a single driver will operate on the same bus and route all day long. At others times, the driver may operate on a number of buses and/or routes over the course of the day. The collection of trips a driver performs over the course of their shift is known as a run. Just as a block represents a bus's schedule for the day, a run represents the driver's schedule for the day. Matching drivers with the pieces of work a transit provider needs to staff is known as run cutting. Run cutting can be a complex process at least in part because drivers and other staff often belong to a union, and the labor agreements which have been negotiated can have many different rules which need to be followed.

Fixed Route Technologies

Fixed route providers use a large number of technologies to manage operations and provide good customer service. The most significant of these technologies are described briefly below:

Fare Collection

There are a variety of fare collection technologies which fixed route providers use to collect and securely store fares. Some fare boxes are able to assist the driver in verifying that cash-paying riders provided the correct fare. Registering fare boxes are able to count coins and bills, but they cannot differentiate between different denominations of bills. For example, a registering farebox can’t tell the difference between a one dollar bill and a twenty dollar bill. Validating fare boxes can do everything a registering fare box can do and, in addition, can differentiate between different denominations of bills. Registering and validating fareboxes also generally allow the drivers to keep track of the types of passengers who are boarding (e.g., seniors, persons with disabilities, children, etc.). For providers who have relatively low ridership, it is difficult to justify the cost of registering or validating fare boxes. For these types of providers, a vault style fare box is often the most logical choice. A vault style fare box does not count cash payments. Instead, the upper compartment is generally transparent which allows the driver to confirm the correct fare was provided before it is dropped into the lower compartment. Many providers are moving toward providing more flexible payment options. Touch cards are a convenient type of fare media which are growing in popularity. Riders can generally add additional value to these cards using a ticketing machine or via the web.

Computer Aided Dispatch / Automatic Vehicle Location (CAD/AVL)

Many transit organizations who operate a fixed route bus service use CAD/AVL. CAD/AVL systems consist of onboard hardware to track the buses, and software which helps the dispatchers to manage service as it is occurring and resolve issues as they arise. CAD/AVL allows the dispatcher to see where all the agency's vehicles are on a map and to quickly determine which are on schedule and which are ahead of schedule or behind schedule.

Automatic Passenger Counters (APC)

APCs are simple devices which are mounted by each door and count the number of passengers boarding and alighting the bus. While there are different types of APCs on the market, the most common employ a series of infrared beams. Each time the beams are broken, the system counts it as either a boarding or alighting. During busy times, the devices can miss a passenger here and there. The devices can also have a hard time with children, especially if they are carried onto the bus. The data collected via APCs can be used to determine the current onboard passenger count, a piece of information that is sometimes made available to the riding public along with other real-time bus information. Transit agencies sometimes also use APC data to fulfill part of their reporting NTD requirements to the FTA but, in order to do so, they need to demonstrate that their APCs meet certain accuracy requirements. You'll learn about NTD reporting later in this lesson.

Automated Announcement Systems (AAS)

In order to comply with ADA requirements, fixed route vehicles are generally equipped with an AAS which provides both audible announcements and visual announcements about upcoming stops and points of interest. These systems are generally triggered based on the vehicle's position as it approaches a designated location. Most systems utilize geofences to determine when an onboard announcement should be made.

Vehicle Surveillance

Most fixed route vehicles are equipped with camera systems which record activities on the bus as well as outside the bus. It is common for a bus to have 6 separate audio and video streams with some of the larger articulated buses being equipped with 8 separate streams. The video from these buses is stored in onboard DVRs and can be streamed by dispatch if needed. The DVR capacities are generally sufficient to store a few weeks of video before overwriting. The systems are configured to automatically flag sections of video in the event the system senses any unusual forces due to a collision or abrupt deceleration or turn. The driver can also press a button to manually flag a section of the video. When the system flags a section of the video, it preserves a window of time which brackets the triggering event for later review. Flagged sections of video are often wirelessly downloaded when the bus returns to the depot. Vehicle surveillance systems are extremely useful for identifying undesirable driver behaviors and incidents onboard the bus, as well as helping to determine the cause of any bus-related accidents. Local police are also sometimes interested in this video if they believe it may be of use in solving or prosecuting a case.

Real Time Passenger Information

Real time passenger information systems have become extremely popular in recent years. These systems make real-time bus information available to riders via web applications, smartphone applications, and dynamic message boards which are sometimes located as transit centers or other high traffic stops. In Lessons 8 and 9, we looked at an example of one which CATA uses called MyStop.

Rider Alerts

Transit providers often offer rider alert systems to notify users about disruptions in services or to provide other types of notifications. Riders can typically sign up for alerts related to specific routes and/or system-wide alerts.

Scheduling Software

Developing and adjusting routes, patterns, stops, trips, and blocks can be challenging especially for larger transit providers. Scheduling software is designed to assist agencies in this regard. Scheduling software also often incorporates some functions to assist with run cutting as well.

Vehicle Health Monitoring

Many buses come equipped with vehicle diagnostics that can transmit various vehicle health information back to the transit agency. This technology helps to ensure problems are taken care of before they lead to vehicle breakdown. Some vehicle health systems integrate with maintenance management systems and can automatically schedule vehicles for preventative maintenance.

Trip Planning/Google Transit

Many fixed route providers offer trip planning services to their riders. These services are generally web-based and allow the rider to indicate their origin, destination, and desired date and time of departure or date and time of arrival. The trip planning service then presents options which define a combination of walking and fixed route options that best meet their needs. The options may involve one or more transfers between fixed route vehicles. The most popular fixed route trip planning service is Google Transit. The idea for what has become Google Transit was first spawned by TriMet, a transit agency which services Portland, Oregon. TriMet approached MapQuest, Yahoo, and Google to see if they would be interested in incorporating transit data into their map products, but only Google replied. The Google Transit Trip Planner launched on December 7, 2005. Google transit incorporates stops, routes, schedule, and fare information for a provider’s bus, subway, rail, and/or light rail service. The service is automatically available as a free service via Google Maps in any area where one or more local transit providers publish their data to Google.

For most of the first year, TriMet was the only operator available on Google Maps. In September 2006, five more cities got on board: Eugene, OR; Honolulu, HI; Pittsburgh, PA; Seattle, WA; and Tampa, FL. Today, Google Transit spans many hundreds of cities [111].

Figure 9.5 - Example of Google Transit in Downtown Philadelphia

Credit: Google

In order for transit providers to submit their fixed route information to Google in a consistent way­, a data specification was required. The specification which was developed for this purpose is discussed in the next section. As mentioned above, Google Transit is a free service to transit agencies and to the public who can perform trip planning in Google Maps. However, if you wish to tie into the capabilities programmatically to incorporate the power of Google Transit (or more generally Google Maps) into your own software application, there are often associated fees you need to consider. A popular and robust alternative open source trip planning system is Open Trip Planner [112].

General Transit Feed Specification (GTFS)

The specification which was developed to allow transit agencies to publish their fixed route data to Google Transit is known as GTFS. Originally it stood for the Google Transit Feed Specification, but in 2010, Google changed the name to the General Transit Feed Specification given its growing status as the default specification for transit data. GTFS is an open data standard which represents fixed-route schedule, route, and bus stop data in a series of 13 comma-delimited text files compressed into a ZIP file. Each of the 13 text files contains a series of fields or attributes about a component of the fixed route service. Some of the files and fields are optional (see Table 1).

Click for description of each table [113] along with the meaning of each field.

The primary use of GTFS data is to publish fixed route schedule data to Google Transit so that riders can perform trip planning. However, there are many other potential uses for GTFS data. For example, transit planning software systems such as TBEST commonly allow users to upload route, stop, and schedule data in GTFS format. In the past few years, Google has created a new specification based on GTFS which incorporates real-time information in addition to the static schedule data. The new specification is known as GTFS Real Time [114] and is starting to gain some traction among transit agencies, but is not yet widely used.

In Assignment 9-2 you’ll have a chance to work with GTFS data from a transit agency in Tampa, Florida. Specifically, you’ll use the route geometry contained in the shapes.txt component of the GTFS data to establish the zone for ADA complementary paratransit.

The following assignment is optional. You do not need to complete this assignment to fulfill the requirements of the course. TBEST is a powerful tool for transit planning and is available for free. If you have an interest in the tool, this assignment will help you to get some hands-on experience using it.

This week, you’ll take some time to get to know the Federal Transit Administration (FTA). The FTA is the administration within the USDOT which focuses on providing financial and technical support to public transportation agencies across the United States. The FTA was created in 1970 by President Lyndon Johnson, although, back then, it was known as the Urban Mass Transportation Administration (UMTA).

This week, you’ll have a one-on-one chat with one of your classmates as per the schedule you were provided in Week 1. The discussion should be at least 30 minutes in length. If it’s the first time you’ve chatted with each other, spend the majority of time getting to know each other. Otherwise, focus on discussing the lesson content.

Public transit organizations provide important services which alleviate congestion and which offer mobility to those who have no other transportation options. While they all have some common objectives and challenges, transit organizations are each unique, based largely on differences in the communities they serve and in the political landscape they operate under at both the state and local level. Next week, we'll hear from 2 speakers who represent two separate transit organizations.

Speaker #1

Our first speaker will be Dr. Minhua Wang. Dr. Wang has over 25 years' experience in IT and GIS, has served multiple positions in government agencies, software development companies, and consulting firms. Dr. Wang has developed expertise and reputations in the areas of GIS for transportation or (GIS-T), Public Transit, and transportation software development and implementation. His experiences in the transportation GIS field include data modeling, enterprise architecture design, system integration, application development, asset management, and GIS technology implementation. Dr. Wang currently serves as GIS Manager in the Washington Metropolitan Area Transit Authority (WMATA). He has overall responsibility for administrative, technical and managerial tasks necessary for the development and operation of Metro’s enterprise Geographic Information System. He has involved considerable interaction, cooperation and collaboration with managers throughout Metro, and officials of other public agencies and regional partners in the design, development, and implementation of the geographic information system and related products to meet various needs and functions. Prior to WMATA, Dr. Wang served as Project Manager at DC Department of Transportation (DDOT), Group Leader at CitiLabs (a Transportation Planning Software company), Enterprise Architect at KCI Technology Inc., and Technical Architect/Director of Application Development at Geodecisions. Dr. Wang holds a Ph.D. degree in GIS from the University of Waterloo, Canada, and an MS degree in Remote Sensing and a BS degree in Geography from Peking University, China.

Washington Metropolitan Area Transit Authority (WMATA)

WMATA [119] serves the greater Washington DC area and is one of the largest transit agencies in the United States. 

Speaker #2

Our second speaker will be Ryan Harshbarger, Director of Transportation for the Centre Area Transportation Authority (CATA). Ryan has been with the Authority for eight years, starting his career at CATA as a Transportation Data Analyst, before transitioning to his current role. Previously, he worked in inventory control for several private sector businesses with a focus on Lean/Six Sigma process improvement. Ryan has been heavily involved in the advancement of CATA’s Intelligent Transportation System, serving as the program lead on several projects to enhance both the components on the vehicles and deployment of new software for internal and external consumption.

Centre Area Transportation Authority (CATA)

CATA is a transportation organization which services portions of Centre County, Pennsylvania. One of the factors which differentiates CATA is the presence of Penn State University which lies within its service area.

In this lesson, you learned about DRT services including some of the challenges inherent to DRT and the technologies agencies commonly employ to help them manage and deliver these services. You also learned how DRT software can help transit providers schedule trip requests by completing an exercise on Network Analyst’s vehicle routing solver.  You also learned about fixed route transportation and GTFS, the standard format used by transit agencies to publish their schedule data.

This week, you explored the FTA, an administration within the USDOT.

In our weekly webinar, you had the chance to interact with Mr. Rodney Bunner and learn about TBEST, a powerful Transit Planning Tool.

In preparation for next week’s webinar, you learned about Title VI of the Civil Rights Act of 1964 and how it impacts fixed route providers in particular. You also had a chance to explore TBEST, a tool you’ll have a chance to work with in next week’s lesson.

Finally, you had the opportunity to get to know one of your classmates a little better and share some of your ideas and questions about this week’s lesson materials.

What will we learn?

By the end of Lesson 10, you should be able to:

• construct and use a multimodal network dataset;
• discuss efforts to improve the walkability and bikeability of communities;
• list some ways GIS is being leveraged in aviation and maritime;
• describe some important transportation initiatives being advanced in Europe;
• talk about the operational considerations associated with running a transit agency and describe some of the ways they leverage GIS to manage operations and improve customer service.

Over the past 50 years, walking and biking as modes of transportation have declined dramatically in the United States largely as a result of urban sprawl. However, in the past decade, we have begun to see a resurgence of interest in these modes of travel, driven in large part by millennials. 

The Alliance for Biking and Walking is an association of bicycling and walking advocacy organizations in North America. They currently have more than 220 member organizations across the United States, Canada, and Mexico. In 2016, the Alliance published a report [120] benchmarking the status of bicycling and walking in the United States. The report has been published every two years for about the past decade. Funding for the effort comes in large part from the Centers for Disease Control and Prevention. In March 2016, Christy Kwan, the interim director of the Alliance gave a podcast which touched on some of the highlights of the report [121].

To address the increased interest in walkable and bikeable communities, planners use GIS to assess current conditions and to identify and prioritize needed improvements. Dr. Mike Lowry from the University of Idaho gave a presentation in 2014 [122] where he described the concepts of bicycle level of service and bikeability and reviewed some of the GIS tools he has developed for analysis in this area. 

Walk Score and Bike Score are two GIS applications currently owned by the Seattle based residential real estate company, Redfin. These applications are designed to help people assess the walkability and bikeability of a house they may be considering. They both implement priority algorithms to calculate a score from 0 to 100. Bike Score, for example, takes the following characteristics into account in deriving a score.

• Bike lanes
• Hills
• Destinations and road connectivity
• Bike commuting mode share

GIS is also leveraged by walking and biking enthusiasts, largely through the use of mobile applications such as STRAVA, to track performance and share route information with others.

Watch these two TED talks given by Jeff Speck, a city planner, urban designer and walkability advocate. The first, titled The Walkable City [123], was given in September 2013 and the second, titled 4 Ways to Make a City More Walkable [124], was given in October 2013.

If you would like some more information on this topic, you may want to take a look at a December 2016 report published by the U.S. Department of Housing and Urban Development (HUD) titled Creating Walkable and Bikeable Communities [125].

Aviation

Given the inherently spatial nature of flight data, it is not hard to understand the importance of GIS when it comes to navigation and surveillance in the skies. The International Air Transport Association (IATA) estimates that the number of airline passengers will double in the next 20 years. This will make the already challenging job of managing traffic in the skies and at airports even more challenging.

In recent years, airplanes and airports around the world have been modernizing their flight management systems and air traffic management systems to incorporate GIS and the Global navigation satellite system (GNSS). Due to the increased spatial accuracy that results, this modernization increases the capacity of airports for both departures and arrivals and also allows for the more efficient use of airspace since planes can fly closer together. The modernization effort in the United States is known as known as the Next Generation Air Transportation System (NextGen) and is led by the Federal Aviation Administration (FAA) [126], an administration within the USDOT. A similar initiative in Europe is known as Single European Sky ATM Research (SESAR). The United States and the European Union have worked together to ensure that these initiatives are interoperable (see NextGen - SESAR State of Harmonisation [127]).

The use of GIS in aviation, however, goes well beyond the navigation and surveillance of airplanes. GIS is also used to address many concerns in and around airports, including:

• infrastructure planning
• asset management
• maintenance operations
• the assessment of noise impacts
• the evaluation of vertical obstructions and height clearances
• avoidance of bird strikes

Take a look at this presentation at the 2015 ESRI Users' Conference [128] which looks at some of the ways the Hartsfield-Jackson Atlanta International Airport is leveraging GIS to manage operations and improve their passengers' experience. Then watch this session on Combining GIS and IoT to Create Smart Airports [129] which discusses how they are using IoT to expand the capabilities of spatial technology in ways which benefit both the traveling public and a variety of business units within the airport.

Maritime

Maritime transportation is one of the oldest forms of transportation and remains a vital component of the world's economy. Over 90 percent of the goods traded are transported by ship. The Maritime Administration (MARAD) [130] is the agency within the USDOT which oversees waterborne transportation in the United States. As in aviation, GIS plays an important role in ship navigation and surveillance to help to manage traffic near ports, to keep ships safe from natural and human dangers (i.e., piracy) on the open water, and to aid in response to emergencies when they occur.

GIS is a valuable tool for managing all aspects of port operations. Read the article titled Maritime transport: Shipping undergoes sea change [131] published in the May 2012 issue of GeoWorld and watch this presentation [132] from the 2014 ESRI Users' Conference on the ways GIS is employed at the Port of Rotterdam, Europe's largest port.

This week, you’ll take some time to get to know the European Union (EU). The EU was formed after World War II to prevent future wars between any of its member states. The EU currently has 28 members. The European Commission (EC) serves as the executive branch within the EU and is responsible for proposing legislation and carrying out the daily operations of the EU. The EC has 28 commissioners, one from each member nation. Spend some time browsing the content on the EC's Mobility and Transport [133] website.

Strategic Transport Research and Innovation Agenda (STRIA)

The Strategic Transport Research and Innovation Agenda (STRIA) is a key element of the EU's energy union strategy designed to decarbonize Europe, improve energy security, increase efficiency, and make Europe more competitive in the global market. STRIA is divided into seven transportation themes:

1. Electrification
2. Alternative fuels
3. Vehicle design & manufacturing
4. Connected and automated transport
5. Transport infrastructure
6. Network and traffic management systems
7. Smart transport and mobility services

Roadmaps have been developed for each of these areas. Each roadmap is a detailed document which lays out a strategy for advancing innovative solutions in one of the seven themes.

Transport Research and Innovation Monitoring and Information System (TRIMIS)

In the latter half of 2017, the EC implemented the Transport Research and Innovation Monitoring and Information System (TRIMIS) to monitor and report on the roadmaps for each of the 7 transportation themes defined by STRIA. The TRIMIS database has information on almost 500 programs and 6200 projects in transportation. The EU recently published a report titled EU Transport Research & Innovation Status Assessment Report 2017 [134] which is based on data in the TRIMIS database.

Trans-European Transport Network Policy (TEN-T)

The Trans-European Transport Network Policy (TEN-T) was created by the EU to develop and improve the transportation network throughout Europe including roads, rail, waterways (both inland and maritime), ports, airports, and rail terminals. TEN-T activities are focused on 9 important transportation corridors which connect the EU member counties. Take some time to learn about TEN-T. [135]

There are no one-on-ones scheduled this week.

In our final lesson, you looked at some other modes of transportation (walking, biking, aviation and maritime) and considered some of the ways GIS is being used in these areas. 

You had a chance to work with Network Analyst to construct and use a multimodal network dataset and to consider some interesting perspectives on walkable and bikeable communities.  

You also took a look at some ways GIS is being leveraged at the Hartsfield-Jackson Atlanta International Airport and the Port of Rotterdam.

This week, you explored the European Union and some of the transportation initiatives they are advancing including STRIA and TEN-T.

In our weekly webinar, you had the opportunity to listen to two speakers who each work (or have worked) for a transit agency. Dr. Minhua Wang reviewed GIS applications developed at WMATA, the transit agency serving the greater Washington, D.C. area, and Ryan Harshbarger spoke about some of the operational considerations at CATA, the transit agency servicing State College, Pennsylvania.

Finally, you provided feedback on the various course elements so that the course material can continue to be refined and improved for future students.