Regional Intelligent Transportation Information System (RITIS) Data Driven Screening and Project Selection

Georgia Department of Transportation


  • How GDOT conducted an extensive review of available data sources for prioritization rankings of bottlenecks and determined using RITIS speed data was the best available option to complete the analysis.
  • How RITIS and the Probe Data Analytics (PDA) suite was introduced to support operations, planning, analysis, research, and performance measures.
  • How the dataset that was created by this process was compiled into a spatial dashboard that allows GDOT to review the statewide ranking of intersections.


Georgia DOT setup the Operational Improvement Program (the Program) in 2010. The Program is designed to identify congestion bottlenecks and develop high benefit, low-cost solutions which can be quickly implemented to reduce congestion and increase throughput. Historically, the Program has been fed through public comments, District identified needs, and signal program requests. As requests started to outpace available funding and advancements were made in-roadway congestion data, GDOT wanted to identify a way to both prioritize evaluations of bottleneck locations and be more proactive in identifying potential bottlenecks.

GDOT was already a member of the Eastern Transportation Coalition (ETC) and was starting to utilize the data available through their Regional Intelligent Transportation Information System (RITIS). GDOT conducted an extensive review of available data sources to develop bottleneck rankings, including RITIS data and determined that the speed data available through RITIS was the best available option to complete this analysis.

TSMO Planning, Strategies and Deployment

The RITIS platform had been used by other offices within traffic operations, however the “big data” that is probe data was new to the Program. RITIS and the Probe Data Analytics (PDA) suite was introduced. The PDA Suite allows GDOT to support operations, planning, analysis, research, and performance measures using probe and other agency transportation data through visualization and retrieval tools. After a review of the 10 tools inside the PDA suite, it was determined that the most effective tool for intersection identification and prioritization would be the Bottleneck Ranking tool.

One issue encountered was that the data provided was for a single approach to an intersection, not an entire intersection. While this is useful, the goal of this screening process was to prioritize intersections across the state, not solely make decisions based upon single approach delay information. Additionally, the metrics that are included and calculated by RITIS are not typical traffic engineering metrics.

For bottleneck input data, in order to obtain a large sample size of data for the state, two months of data was utilized for this initial intersection prioritization. Additionally, all roadway types available in RITIS were included in the analysis. For bottleneck outputs the default overall ranking completed by RITIS is based on the Base Impact metric which is calculated as the sum

of the queue lengths over the duration of the bottleneck. The Base Impact metric is valuable, however the metric only uses queue length (derived from spatial located based data) to generate this value. While this is important, the ranking of a single lane road in a rural area could be above a multi- lane road in an urbanized area. Therefore, other metrics provided by RITIS were explored including Total Delay.

Total Delay uses the difference in between free-flow speed and observed speed multiplied by AADT to weight the Base Impact. By using this metric, which included a volume component, the ranking of approaches would be realized based upon the number of vehicles utilizing an approach. Each set of metrics produced by RITIS was exported for each segment across the state and then filtered to remove off-system and buffering the segments, so they match up at the intersection level.

The Probe Data Analytics Suite uses the traffic message channel (TMC) standard to identify each road segment. The bottleneck ranking tool uses the head of the TMC segment as identification of the bottleneck because head of the segment is usually where traffic blockage starts.

The data was then filtered to head locations that are intersections with a state route or US highway. The filtering process left approximately 19,000 segments for further processing. Because RITIS, calculates bottlenecks by approach, the approach data was then aggregated by intersection to calculate the total intersection delay. The aggregation left 4,859 total intersections. The intersections were then ranked at the state and District levels.

Communications, Planning, and Execution

The data driven approach was an iterative process that included many workshops with GDOT and consultants working on the Program. One of the most interesting components of this process was including data scientists and GIS analysts to support the necessary scripting and soft coding needed to analyze these large datasets. The dataset that was created by this process was compiled into a spatial dashboard that allows GDOT to review the statewide ranking of intersections at their leisure. As the dashboard and data was provided to more GDOT

users, both inside the Program and outside the Program, the request to modify the presentation of the data was necessary, as the end user and their needs can be slightly different than those of personnel inside the Program. Overall, the dashboard and dataset have been created and stored in a way to allow for maximum flexibility for future requests of the Program.

Outcome, Benefit and Learnings

GDOT is currently using an annual calculation of the bottleneck rankings to prioritize analysis of locations and to support the Districts in their responses to citizen and stakeholder comments. In Summer 2020, the Program reviewed the Top 200 bottlenecks within the state to determine if a project is programmed at that location, if there are elevated crash trends, and any geometric, ROW, or utility constraints for an improvement. Locations without programmed projects and that appeared to have few constraints to implement an improvement, are currently being evaluated with the highest ranked intersections being evaluated first.

Additionally, Districts have recently started requesting RITIS ranking from Office of Traffic Operations (OTO) to support their responses to citizen or stakeholder requests. The RITIS bottleneck data allows the Districts to let the requester know the ranking of the subject intersection within the County, District, and State. This helps them in explaining funding priorities and to direct the conversations with local agencies to higher ranked intersections.

Other benefits of the new methodology include allowing the Program to be more proactive and justifiable in selecting locations for evaluation rather than reacting to public or stakeholder comments. The RITIS method allows OTO to be more proactive in evaluating and addressing some issues prior to receiving a comment. The other major benefit of the methodology is the ability to use the data to conduct before and after studies and provide key decision makers with a better understanding of the actual benefits of implemented projects.

While this methodology leverages technology to drastically improve the project identification process, there are still areas which the team is working to improve the process including a limitation in the datasets and the second is better incorporation of volume data. The data sets currently include approximately 4,800 of the State’s intersections. While a large majority of major intersections are included, smaller stop-controlled intersections are sometimes omitted. Additionally, volume data is not currently available for all links which does not allow for full calculations for all intersections. The team is currently evaluating new methods and data sources to address these limitations in future iterations of the analysis.

Operations Area of Practice

  • Traffic Signal Timing

Organizational Capability Element

  • Performance Management
  • Programming/Budget/Funding
  • Project Development
  • Performance Measurement

Content Type

  • Case Studies & Lessons Learned

Publishing Organization

  • NOCoE

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Issue Date
April 25th, 2021
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