A new commercial-vehicle trip forecasting model has been developed for the Baltimore Metropolitan Council (BMC). BMC includes trucks in its regional modeling but has previously excluded an important category of nonpersonal travel with passenger cars, light trucks, and other vehicles. These include light-duty delivery vehicles, taxis, government vehicles, service personnel vehicles, craftsmen vehicles, and similar vehicles. The challenge in estimating commercial vehicle trips is to define them and obtain data on observed trip patterns. Traditional surveys were judged unlikely to be useful, so an innovative way was devised to synthesize commercial vehicle counts at those locations where classification count data already existed. BMC staff conducted new counts at locations throughout the region. Commercial vehicles were defined as those bearing any text or logo or carrying equipment of an obviously commercial nature. A database was created and used to calibrate a count model, which was then applied to estimate commercial counts at more than 550 locations. These counts indicated that commercial traffic is almost 8% of the total traffic volume. The researchers synthesized a trip table from these count data and used that table to develop a commercial trip model that would estimate link volumes accurately. The resulting assignment error is -1.9% and the regional percent root-mean-square error is 12.5%. The result is a process that exhibits reasonable sensitivities to the key input variables and matches counts very well. A forecast was made and the results were found to be reasonable. The procedure was implemented within BMC's regional model set.
Modeling Commercial Vehicle Travel
Transportation Research Record
Transportation Research Record: Journal of the Transportation Research Board ; 1895 , 1 ; 31-37
2004-01-01
Aufsatz (Zeitschrift)
Elektronische Ressource
Englisch
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