A Knowledge-based System for Estimating Incident Clearance Duration for Maryland : I-95 a Case Study for the Project of MD-17-SHA/UM/4-19 : “Development of a Traffic Management Decision Support Tool for Freeway Incident Traffic Management (FITM) Plan Deployment”
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A Knowledge-based System for Estimating Incident Clearance Duration for Maryland : I-95 a Case Study for the Project of MD-17-SHA/UM/4-19 : “Development of a Traffic Management Decision Support Tool for Freeway Incident Traffic Management (FITM) Plan Deployment”

  • 2017-12-01

Filetype[PDF-656.68 KB]


  • English

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    • Alternative Title:
      Development of a Traffic Management Decision Support Tool for Freeway Incident Traffic Management (FITM) Plan Deployment
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    • Abstract:
      For the incident response operations to be appreciated by the general public, it is essential that responsible highway agencies be capable of providing the estimated clearance duration of a detected incident at the level sufficiently reliable for motorists to make proper decisions such as selecting a detour route. Depending on the estimated clearance duration, the incident response center can then implement proper strategies to interact with motorists, ranging from providing incident information only to executing mandatory detouring operations. This study presents a knowledge-based system, based on the detailed incident reports collected by the Maryland CHART (Coordinated Highway Action Response Team) program between the years 2012 through 2016, for such needs. The proposed system features its use of interval-based estimates, derived from the knowledge of the historical data with different confidence levels for each estimated incident clearance duration, and its rule-based structure for convenient updates with new data and available expertise from field operators. Since some key variables associated with incident duration often only become available as the clearance operations progress, the developed system with its sequential nature allows the users to dynamically revise the estimated duration when additional data have been reported. Our preliminary evaluation results have shown the promise of the developed system which with its invaluable historical information can circumvent many data quality and availability issues which have long plagued the applicability of some state-of-the-art models on this subject.
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