For incident response operations to be appreciated by the general public, it is essential that responsible highway agencies are capable of providing the estimated clearance duration of a detected incident at a 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 detailed incident reports collected by the Maryland-CHART (Coordinated Highway Action Response Team) program between years 2012 and 2016, for such needs. The proposed system features the use of interval-based estimates derived from knowledge of 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. As some key variables associated with incident duration often only become available as the clearance operations progress, the developed system with its sequential nature allows users to dynamically revise the estimated duration when additional data have been reported. The preliminary evaluation results have shown the promise of the developed system which, with its invaluable historical information, can circumvent the many data quality and availability issues which have long plagued the applicability of some state-of-the-art models on this subject.

Most agencies, in response to and management of non-recurrent highway congestion, are requested by the general public to provide the estimated delay and impacts of incidents; this information also allows the agencies to take appropriate control strategies. However, to do so in real time the responsible agencies would need to have a reliable estimate of the incident duration, which although valuable information, is either not available or not acceptably reliable for use in practice. Considering the nature of incident response operations, the difficulty in developing a reliable model may be attributed to both the data quality and, most importantly, the many continuous and discrete variables associated with the incident duration; these include resources and staff level of the incident response team, the nature, onset time, and location of the incident, and other related environmental issues. This study therefore proposes an estimation methodology to circumvent these limitations and take advantage of unique characteristics revealed in incident databases for yielding a robust estimate of incident duration. With well-designed partitioning, clustering, and sequential tests to divide all incidents into several distinct groups, the proposed methodology will yield one primary model using all available data and supplemental models for incidents in each group that are calibrated to best fit their unique characteristics and statistical properties. By using incident data from Maryland-CHART, the evaluation results confirm that the proposed methodology can indeed improve the estimation accuracy if properly integrated in the primary model with each supplemental model.

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