Chapter
Jun 4, 2021

A Dynamic Traffic Assignment Approach to Evaluating Incident-Induced User Delay Costs with Integrated Corridor Management: A Case Study in Austin, Texas

Publication: International Conference on Transportation and Development 2021

ABSTRACT

Traffic incidents often require lane or road closures to facilitate the incident clearance and ensure the safety of first responders. With the integrated corridor management (ICM) strategies, upstream traffic could be diverted to parallel roadways and the incident-induced traffic congestion is managed in an integrated system rather than individual facilities. This study delivers an example of estimating the incident-induced user delay costs with ICM strategies. A dynamic traffic assignment (DTA) tool is used to quantify the travel delays caused by an incident under various ICM strategies. In particular, a case study based on a fatal crash on the Interstate 35 in Austin, Texas, is performed under three types of ICM strategies. The DTA can capture more realistic traffic flow characteristics by considering time-dependent link information, compared to the static traffic assignment (STA) method. DTA parameters are specified to approximate the driver behavior under different ICM strategies. Emerging traffic data were collected to validate the study results. All tested ICM strategies are found to be associated with decreased travel times and user delay costs, but the one that offers both timely detour options and proper adjustments to traffic controls on parallel roads can be more effective in reducing corridor-wide delays. This study contributes by demonstrating the implementation of DTA models to model driver behavior during traffic incidents and the deployment of ICM strategies. DTA models are a valuable tool to evaluate the region-wide effectiveness of traffic management strategies during traffic incidents.

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Go to International Conference on Transportation and Development 2021
International Conference on Transportation and Development 2021
Pages: 168 - 180

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Published online: Jun 4, 2021

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1Cockrell School of Engineering, Dept. of Civil, Architectural and Environmental Engineering, Univ. of Texas at Austin, Austin, TX. Email: [email protected]
Natalia Ruiz Juri [email protected]
2Network Modeling Center, Center for Transportation Research, Univ. of Texas at Austin, Austin, TX. Email: [email protected]
3College of Engineering, Dept. of Civil, Construction and Environmental Engineering, Univ. of Alabama, Tuscaloosa, AL. Email: [email protected]
Heidi W. Ross [email protected]
4Network Modeling Center, Center for Transportation Research, Univ. of Texas at Austin, Austin, TX. Email: [email protected]
Randy B. Machemehl [email protected]
5Cockrell School of Engineering, Dept. of Civil, Architectural and Environmental Engineering, Univ. of Texas at Austin, Austin, TX. Email: [email protected]
John Nevares [email protected]
6Texas Dept. of Transportation, Austin, TX. Email: [email protected]
Adam Kaliszewski [email protected]
7Texas Dept. of Transportation, Austin, TX. Email: [email protected]

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