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Reframing Decision Support Systems as a Continuum Across Regionwide TSMO and Integrated Corridor Management

• Jul 16, 2020

Research Description

States and regions across the US use elements of down-scaled integrated corridor management (ICM) and decision support systems (DSS) to activate formal intra and inter-agency response plans to various traffic conditions across their urban and rural regions. These elements include shared floor space at regional traffic management centers, formal policy agreements, step-by-step communication protocols, and regional data sharing arrangements across agencies. Even from a single jurisdictional perspective, contributions to incident management response through time-sensitive, and coordinated adjustment of traveler information systems such as dynamic message signs, and ITS equipment such as traffic signal timing lead state DOTs down the path of response profiles and interdepartmental data sharing and protocol establishment. This begs the question of whether DSS as a central part of ICM needs to be redefined or reframed to include smaller scale and incremental approaches that add up to the structure if not the complete body of a fully automated integrated corridor management system.

This research proposes a rethink on what integrated corridor management on a smaller scale with resulting response plans, and DSS elements could mean. Many agencies following a congestion management process to identify corridors with reliability and congestion issues also consider investments in what could be termed ICM-adjacent systems which could benefit from a clear, fiscally-constrained link to ICM methods and the development of DSS response plans. Any research would draw on findings of NCHRP 03-128 (https://apps.trb.org/cmsfeed/TRBNetProjectDisplay.asp?ProjectID=4352), the recent ICM deployments in Dallas, and San Diego (https://ops.fhwa.dot.gov/publications/fhwahop19016/form.htm), and the smaller ICM deployment grant experiences across the U.S. Findings should also be tied to recent innovations and market advances that improve the access of local and state government agencies to suitable business analytics, artificial intelligence solutions, and sensor-driven process automation.

Additional Supporting Information

https://apps.trb.org/cmsfeed/TRBNetProjectDisplay.asp?ProjectID=4352

https://ops.fhwa.dot.gov/publications/fhwahop19016/form.htm

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Submitted By

Matthew Miller

Texas A&M Transportation Institute

703-732-0756

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