When crossing international gateways, commercial vehicles engage in multiple activities—such as approaching on congested roadways, paying tolls, undergoing customs inspections, and waiting in queues—that increase trip times and trip-time variability. Documenting the times incurred in these multiple activities is difficult because the activities are spatially dispersed, temporally variant, and affected by institutional and operational complexities resulting from the multiple organizations operating infrastructure in two countries. An approach is presented to capture the times required to complete various activities at international border crossings, using trucks from a large fleet that regularly crosses international gateways. This approach takes advantage of the telematics systems already in use by the truck fleet and is not dependent on installation of roadside equipment. Geofences are specified at strategic locations that delineate the beginnings and ends of activities of interest and send information electronically to the vehicles' onboard data units. The activity times for an individual truck crossing can be determined from data automatically recorded when trucks enter and exit the specified geofences. The trucks serve as activity time probes, and the activity times of multiple trucks can be aggregated to form activity time distributions. To demonstrate the capabilities and potential of the approach, empirical data from a large fleet of trucks traversing two of the busiest U.S. border crossings are used to produce results on median crossing times, variability in trip times, time-of-day patterns, and excess times (i.e., delays) generated from customs inspections and the queuing that results from the inspections.


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    Title :

    Documenting Truck Activity Times at International Border Crossings Using Redesigned Geofences and Existing Onboard Systems


    Additional title:

    Transportation Research Record: Journal of the Transportation Research Board


    Contributors:


    Publication date :

    2010-01-01




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English




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