Modeling for urban travel demand begins with 20-year forecasts of population, households, vehicle ownership, and employment for a region's individual transportation analysis zones. Yet even though these models rely on socioeconomic forecasts, the long-term accuracy of such models has not received attention, especially for smaller regions with limited planning staff. This paper reports on a case study of the socioeconomic predictions made in 1980 for a horizon year of 2000, by comparing predicted and actual results in Lynchburg, Virginia. The region percentage error reflects the difference between forecast and observed values for the entire region. Although regional forecasts for the number of vehicles and employment showed errors of less than 10%, those forecasts for population and households showed errors of 48% and 14%, respectively. The failure of planned development in two of the region's 68 zones accounted for much of this error, such that removal of these two zones lowered population and household region percentage errors to 10% and 1%, respectively. The zone percentage error is the average of all individual zone percentage errors. Even after removal of the two aforementioned zones, population, households, vehicles, and employment had strikingly large zone percent errors of 39%, 48%, 45%, and 136%, respectively. These results make a compelling case for executing the regional travel demand model twice: once with the given socioeconomic forecasts and once with forecasts modified on the basis of expected errors. For regions that have not conducted an assessment such as that presented here, the expected errors from this paper may be used.


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    Title :

    Accuracy of Zonal Socioeconomic Forecasts for Travel Demand Modeling: Retrospective Case Study


    Additional title:

    Transportation Research Record: Journal of the Transportation Research Board


    Contributors:


    Publication date :

    2012-01-01




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English



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