A Freeway Traffic Incident Management System Needs Reliable Models and Algorithms for Estimating Clearance Times of Detected Incidents, Activating Detour/Diversion Operations, and Producing Reliable Traveler Information.

The Performance of An Incident Response Management Model was Compared with a Traditional Model and Current Practices by the Coordinated Highway Action Response Team in Maryland.

Date Posted
11/30/2022
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Identifier
2022-L01160

Development of a Traffic Management Decision Support Tool (DST) for Freeway Incident Traffic Management Plan Development

Summary Information

Traffic incidents are the main cause of congestion on highway networks. Strategies to mitigate delays related to traffic incidents have been deployed by guiding travelers to different routes. To optimize traffic diversion, it is essential to have reliable measures of incident duration. The proposed system in this study can aid highway agencies in retrieving information on incident duration, the maximum traffic queue, and the need for detour operations. The dataset analyzed was Maryland incident data collected by the Coordinated Highway Action Response Team (CHART), a highway incident management program operated by the Maryland Department of Transportation State Highway Administration (MDOT SHA). The initiative was to decrease congestion related to traffic incidents on freeways by deploying rapid response units, clearance strategies for roadways blocked by a traffic incident, and appropriate traffic management. To validate the proposed model’s performance, the model was applied to segments of I-270, I-70, and US15, managed by Traffic Operation Center-7 in Maryland. These roadways were 63 miles long with 30 distinct exits. The project’s timeframe on assessing the model’s performance was from January 2017 to June 2017.

  • Account for the limited resources for the performance of emergency responses during incident management. Agencies have limited resources such as dedicated staff and tow-trucks, especially during peak periods; therefore, it is essential to utilize a model that optimizes the allocation of resources. This study allocated the available response units to minimize the total incident-induced delay.
  • Develop models or algorithms to estimate reliable measures of clearance times of detected incidents and produce reliable traveler information. The prediction of incident clearance time is essential in understanding the traffic impacts that affect the operational efficiency of a freeway. This study implemented an integrated system to provide a reliable estimate of the clearance duration. Reliable information is crucial to aid agencies in implementing traffic managing strategies to disseminate routing information to travelers and activate detour operations. These types of models are also needed to retrieve reliable traveler information, such as the maximum queue length and total delay.
  • Enhance the reliability of the incident response management strategy. The proposed model in this study only considered one incident to occur at a given time window. However, during congested peak periods, multiple incidents may occur at a given time. The distribution of incident frequency was also considered to be consistent, while in reality it is random. Agencies should employ models that consider historical data of incident frequency, which would produce more reliable results for the responsible agencies. 
  • Develop real-time models to evaluate the integrated incident response and management system. Maintaining the efficiency of the transportation system to prevent congestion would be possible if real-time evaluation was implemented. Agencies can also identify measures of effectiveness, and detect which areas need improvement and/or distribute the available information the other agencies and roadway users.

Development of a Traffic Management Decision Support Tool (DST) for Freeway Incident Traffic Management Plan Development

Development of a Traffic Management Decision Support Tool (DST) for Freeway Incident Traffic Management Plan Development
Source Publication Date
12/01/2017
Author
Kim, Woon; Hyeonmi Kim; Minsu Won; and Gang-Len Chang
Publisher
Prepared by University of Maryland for Maryland State Highway Administration
Other Reference Number
Report No. MD-17- SHA/UM/4-19
System Engineering Elements

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