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

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.

Language

  • English

Media Info

  • Pagination: pp 168 - 180
  • Monograph Title: International Conference on Transportation and Development 2021: Transportation Operations, Technologies, and Safety

Subject/Index Terms

Filing Info

  • Accession Number: 01777542
  • Record Type: Publication
  • ISBN: 9780784483534
  • Files: TRIS, ASCE
  • Created Date: Jul 23 2021 3:26PM