GIS for Transportation: Principles, Data and Applications

8.1 Traffic


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.

13 vehicle classification. Class 1 is motorcycles and class 13 is seven or more axle, multi-trailer.
Figure 1 - FHWA's 13 Vehicle Classifications
Credit: FHWA

Watch This

Watch the first 4 minutes of the Traffic Counting Training Video below which was developed by PennDOT to train traffic count technicians.

Click for a transcript of first four minutes.
Welcome to an overview of PennDOT's traffic counter training. As a traffic field technician, you'll be playing an important role for the Pennsylvania Department of Transportation. PennDOT's traffic monitoring system collects, analyzes, and maintains highway traffic data on over 40,000 miles of roads in Pennsylvania.

Specifically, you will help us collect information on traffic volume and vehicle classification throughout the state. With your assistance, over 10,000 traffic counts are taken annually in Pennsylvania. After all traffic data is collected in the field, it is submitted to PennDOT central office where it is processed and used to make important decisions about highway design; safety and planning; for research to improve congestion management; to help design and install traffic control systems; to track statistics to help make air quality conformity determinations; to provide information for economic development; and for required federal reporting.

To assist with the collection of this data traffic field technicians use five types of counting devices. Of these five types, three of them are permanent traffic sites that record information 24 hours a day, 7 days a week, 365 days a year.

The most sophisticated of these permanent devices are Weigh In Motion sensors or WIMs. These sites collect axle weight information as well as vehicle classification information.

The second type of device is the Continuous Automatic Vehicle Classifier or CAVC. These sites collect vehicle classification information.

The third type is the Automatic Traffic Recorder or ATR which collects traffic volume data. The permanent sites have a power source and collect traffic data through magnetic loops, sensors, piezos, and/or Kistler sensors that are embedded in the road surface. A modem automatically transfers the data directly to the PennDOT central office daily.

The fourth type of counting device is a semi-permanent counting device commonly referred to as a STIP or Short-Term In Pavement site. The STIP is much like the ATR except that there is no counter in the roadside cabinet. A field technician installs the counter on a predetermined schedule, usually one time a year for a 24-hour period. The counter is then retrieved and the data downloaded and processed.

The fifth type of counting device is a Portable Short-Term Counter. A portable short-term counter installation is a count that is set for a 24-hour period. This type of traffic data collection device provides the majority of the traffic counts taken as part of our statewide count program. A portable short-term traffic counting device collects the data using pneumatic rubber tubing laid across a roadway and attached to a portable counter that has been secured along the side of the road. Tires passing over the road tube register axle counts. The installation of one road tube registers volume counts while a 2 road tube installation produces a vehicle classification count.

The following diagram shows typical setup configurations for portable short-term traffic volume and classification counts: center turn lane class count; center turn lane volume count; divided highway class count; divided highway volume count; two-lane class count; two-lane volume count.

The locations of PennDOT’s permanent traffic counters are presented in a series of district and county maps. Below each map is a table identifying the county, route, segment, and offset of each device. You’ll use this information in Assignment 8-1.

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) system and PennDOT’s Video Log 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.

A screenshot of PennDOT's Video Log Application. It shows a point on a map, the street view of that area, and some basic info.
Figure 2 - PennDOT's Video Log Application
Credit: PennDOT

Assignment 8-1 (20 points)

Spend some time exploring PennDOT’s Video Log application and download Pennsylvania 2016 crash data, PA roadway traffic data, and PA county boundaries from PennDOT’s GIS Data Portal. The roadway traffic data is under the category “Roadway” in a dataset identified as “RMSTRAFFIC (Traffic Volumes).” Each feature in this RMSTRAFFIC shapefile corresponds to a continuous section of roadway with uniform traffic. PennDOT performs traffic counts on each of these traffic sections. Once you’re done, complete the following activities and submit your responses in the form of an M.S. Word document to Assignment 8-1 in Canvas.

  1. Using Video Log, locate a CAVC site, a WIM site, and an ATR site. (Note - a link to a document identifying the location of each permanent traffic site in Pennsylvania was provided earlier in the lesson). Grab a screenshot of each. The picture should show above-ground evidence of the traffic counting device. Include each of the three screenshots in the Word document. For each image, identify the device type along with the county, route, segment, and offset for the device. Also, list the most recent AADT listed for that location (hint: look in the reports drop-down in the upper right corner of Video Log). (5 points)
  2. Add two fields to the attribute table called "AVMT" (annual vehicle miles traveled) and "AVMT" (annual vehicle miles traveled for trucks only). Use the field calculator to derive these new parameters for each traffic section (i.e., for each feature in the RMSTRAFFIC shapefile). The fields you should use to calculate these new fields are "CUR_AADT" (the current average annual daily traffic), "ADTT_CUR" (the average daily truck traffic) and "SEG_LNGTH_" (the length of each traffic section in feet). Note that the RMSTRAFFIC shapefile already has attributes for the total daily VMT (i"DLY_VMT") and the daily truck VMT ("DLY_TRK_VM"), but you should not use these to calculate "AVMT" and "AVMT". Instead, use the fields specified. In your submission, define the formulas you used to calculate these new fields. Once you have populated these new fields, create a new table that totals them for each county. Include a table (or a screenshot of a table) showing the annual VMT (all vehicles) and the annual VMT (trucks only) for each county. (3 points)
  3. Create a county-based thematic map for AVMT and AVMT and include a screenshot of each (hint: join the county level AVMT and AVMT to the PA counties feature class). (3 points)
  4. Calculate the total number of crashes and the total number of fatal crashes for each county in 2016. Include a table or a screenshot of a table which summarizes the county level crashes and fatal crashes. (3 points)
  5. Calculate the 2016 crash rate and the 2016 fatal crash rate for each county (Note: crash rate is generally reported as crashes per million vehicle miles traveled). In your submission, define the formula you used for calculating the crash rate. Also, include a screenshot of the table which shows these values for each county. (3 points)
  6. Create a county-based thematic map for both types of crash rates and include a screenshot of each (Hint: Joint the county level crash summaries to the PA Counties feature class). (3 points)

Assignment 8-2 (15 points)

For this assignment, read ESRI's documentation on incorporating historic traffic data into network analysis and complete Exercise 11: Performing network analysis using traffic data. Following the same approach for the Monday 9 am and Monday 10 pm service areas, solve for the Sunday 9 am service area. As you’re completing the exercises, address the following items and submit your responses in the form of an M.S. Word document to Assignment 8-2 in Canvas. Note: We will not complete the portion of the exercise which uses live traffic data since that requires a subscription to a live traffic feed.

  1. Include a screenshot of the Monday 9 am service area. (2 points)
  2. Include a screenshot which compares the Monday 9 am and Monday 10 pm service areas. (2 points)
  3. Include a screenshot which compares the Sunday 9 am and Monday 9 am service areas. (2 points)
  4. Turn on the traffic group layer. There are three layers in this group all identified as Streets_ND. What is the difference between these three layers? (2 points)
  5. Use the Time Slider tool to observe a thematic map of the travel speeds for the three service area analyses you completed (i.e., Monday 9 am, Monday 10 pm, and Sunday 9 am). Include a screenshot of each. (Note: in the time slider properties, you may need to set the "Restrict Full-Time Extent To" setting to "<undefined>" in order to observe the days and times you need. (3 points)
  6. Define "free-flow" speed. (1 point)
  7. Define "traffic profile" in your own words. (1 point)
  8. According to the ESRI documentation, you need a table with traffic profiles and a table which relates streets and traffic profiles in order to create a network dataset with historical traffic data. The network analyst tutorial data includes a geodatabase for San Francisco and a geodatabase for San Diego. Identify the tables in each of these geodatabases which serve these roles and describe some of the differences between the corresponding tables in each geodatabase. (2 points)