The possibility of capturing dynamic and continuous travel time and/or speed data by responsible governing agencies or obtaining it from private sources opens many pragmatic avenues to assess the performance of transportation network and make improved decisions. One such avenue is visualizing the effect of an incident (say, a fatal crash) on travel time variation, within the vicinity of a crash over time, through the use of a decision support tool (DST). This paper outlines the development and implementation of such a DST, which uses historical travel time and crash data to assess the effect. Travel time variations are computed for each link within a chosen radius (proximal area), by comparing the travel time (at 15-minute intervals) during the selected time period on a day with crash, by severity, and the average travel time for the corresponding link (same time-of-the-day and day-of-the-week). The visual output from the DST can help identify links within the chosen radius to divert traffic due to a crash for incident management and re-routing traffic over time (say, up to 2 hours after the fatal crash), and to assist planners and engineers in their day-to-day activities (mobility and safety improvements at link- or corridor-level). It also assists transportation network users make reliable route, mode, and departure time decisions to avoid delay due to a crash.


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    Title :

    Visualizing the Effect of a Crash over Space and Time Using Historical Travel Time and Crash Data



    Conference:

    International Conference on Transportation and Development 2018 ; 2018 ; Pittsburgh, Pennsylvania



    Publication date :

    2018-07-12




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



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