GIS for Transportation: Principles, Data and Applications

7.1 Highway Safety


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.

Figure 1 - Highway Safety Improvement Program Funds
Fiscal Year 2016 2017 2018 2019 2020
Estimated Funding* $2.226 B $2.275 B $2.318 B $2.360 B $2.407 B

Reference: FHWA Website 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. 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. A link to the presentation is here (my presentation was just under 10 minutes in length).

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). 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 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.


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 published by FHWA’s Office of Safety.

Assignment 7-1 (15 points)

My Capstone project gave me an opportunity to complete a project I had been thinking about for a few years. The idea was to use spatial techniques to extract horizontal curvature information from roadway centerline data. Horizontal curvature is an important roadway characteristic which many state DOTs lack. It can provide high value to a number of groups within the agency, not the least of which are those concerned with improving highway safety. Another use for this data is in the area of routing oversize / overweight vehicles. Most state DOTs are responsible for issuing permits to those who wish to travel along state roads with an oversize / overweight vehicle. As part of the permit, the DOT defines the route the vehicle must travel along. 

Take a look at a lightning talk I gave in 2016 at Penn State's GIS Day event. As you're listening to the brief presentation, advance through the Powerpoint slides I was using (unfortunately they were not incorporated into the video). Then watch an interview I recently recorded with Jason Hershock, a highway safety engineer at PennDOT, where Jason discusses a project the Department is conducting to comply with a set of requirements FHWA has imposed on states to ensure curves are properly signed. A recording of the interview can be found in Canvas' Media Gallery.  Finally, take a look at this 2016 cost-benefit analysis PennDOT conducted on a countermeasure involving High-Friction Surface Treatment (HFST).

Submit an M.S. Word document (no more than 500 words) to Assignment 7-1 in Canvas which addresses the following items:

  1. Why is horizontal curvature information often lacking and/or inadequate for highway safety analyses? (3 points)
  2. Why is looking at crash data alone less than ideal for identifying the best places to incorporate safety improvements? (2 points)
  3. Briefly describe how Jason's group used spatial technologies to address the FHWA requirements on curve signage. (5 points)
  4. Using your knowledge of network analyst, how might you incorporate horizontal curvature information to route oversized vehicles? (2 points)
  5. What was the finding of the cost-benefit analysis PennDOT performed on the HFST countermeasure? What are your thoughts about the dollar value assigned to a fatality? (3 points)

The Fatality Analysis Reporting System (FARS)

FARS 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.

The Fatality Analysis Reporting System Encyclopedia. The type of fatality, the amount of fatalities, and and the year from 1994-2014.
Figure 3 - NHTSA's Fatality Analysis Reporting System (FARS)
Credit: NHTSA Website (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).

screen capture of the Pennsylvania Crash Info Tool on the PCIT website
Figure 4 - Pennsylvania Crash Information Tool (PCIT)
Credit: PCIT Website (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 for this data.

 Screen capture of  PennDOT's GIS Data Portal
Figure 5 - PennDOT's GIS Data Portal
Credit: PennDot's Data Portal Website (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 includes 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.

Assignment 7-2 (20 points)

In this assignment, you’ll have an opportunity to work with crash data from FARS and PennDOT’s GIS Data Portal. Submit an M.S. Word document to Assignment 7-2 in Canvas which addresses the following items:

  1. Using the FARS system, create a thematic map (they refer to it as an intensity map) which shows how fatal crashes varied by state in 2015. Include a screenshot of the thematic map you produced in FARS. Which 3 states had the most fatal crashes? (5 points)
  2. Export crash data from FARS in Excel format which includes all 2015 fatal crashes in Pennsylvania. In step 2 of the “Query FARS Data” wizard, you can select any of the 3 options since you only need data from the Crash table. The only attributes which you need to include are the latitude, longitude and the number of fatalities.  You should also select the “Case Listing” to get the unaggregated list of crashes. Import the crash data into ArcMap and create a map of the crashes where the symbology varies by the number of fatalities. The map should include Pennsylvania county boundaries. (Hint: For the Pennsylvania county boundaries you can download the county boundaries for the entire US from TIGER and then do an attribute query on these counties to select PA counties. The ‘StateFP’ = 42 for Pennsylvania counties. Once you have selected only the Pennsylvania counties, export them as a new feature class.) Include a screenshot of your map. (5 points)
  3. Imagine you work for the Pennsylvania State Police and you are trying to identify good locations for DUI checkpoints in Centre County. To do so, you’re going to look at crash data for 2015 to see where alcohol-related crashes occurred. Since you want to consider all crashes which involved alcohol and not just fatal crashes, the FARS database will not be sufficient. Instead, use 2015 Centre County crash data available from PennDOT’s GIS Data Portal.
    1. Create a map which shows the crashes of interest. Include a screenshot of your map. This exercise will require you to convert the crash data to a feature class, join the crash feature class with the crash flags and use an attribute query to create the set of crashes you want. While there are a number of flags which you could use to identify these crashes, use the “alcohol_related” flag for this exercise. (5 points)
    2. Using the crash data, select 3 locations for DUI checkpoints. Create a screenshot of the map with the checkpoints designated on the map. You can either create a feature class for the checkpoints or simply place graphic symbols, available on the draw toolbar in ArcMap, where you want the checkpoints to be. Provide a brief rationale for your choices. (3 points)
    3. What additional information would be useful in helping you to establish good DUI checkpoints? (2 points)

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 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.

Optional Reading

In August 2013, FHWA published a document titled Assessment of the Geographic Information Systems’ (GIS) Needs and Obstacles in Traffic Safety. In the document, FHWA identified some of the challenges states face in collecting and integrating crash data in addition to some of the opportunities GIS offers to address these issues.