Investigating the effect of light truck vehicle percentages on rear-end fatal traffic crashes

    Authors

    H. Abdelwahab;M. Abdel-Aty

    Abbreviated Journal Title

    J. Transp. Eng.-ASCE

    Keywords

    traffic management; trucks; vehicles; time series analysis; traffic; accidents; collisions; Engineering, Civil; Transportation Science & Technology

    Abstract

    Millions of Americans buy light truck vehicles (LTVs) each year to meet family, business, and personal travel needs. The main objective of this research is to study the effect of the increased percentage of LTVs in traffic on fatalities by manner of collision (rear-end), and also to address the impact of crash configuration (car-car, car-LTV, LTV-car, and LTV-to-LTV). This paper presents time series models that incorporate the percentage of LTVs in traffic to analyze and forecast future trends of fatality that result from rear-end collisions. A time series model was estimated to predict future LTV percentages. Future forecasts using the calibrated time series model show that the LTV percentage is expected to increase and reach 45% of the traffic stream in the United States by the year 2010. The crash analysis is based on the fatality analysis reporting system crash database covering the period of 1975-2000. A transfer function time series model with the LTV percentage as an input and annual deaths from rear-end crashes as output indicates that the annual deaths in passenger vehicles involved in rear-end collisions will be 1,004 by the year 2010 (a 5% increase compared to that of the year 2000). The analysis also showed an expected increase in the fatalities of certain configurations based on the type of vehicles involved in the crash, and indicating possible problems if the lead vehicle is an LTV and the following vehicle is a regular car.

    Journal Title

    Journal of Transportation Engineering-Asce

    Volume

    130

    Issue/Number

    4

    Publication Date

    1-1-2004

    Document Type

    Article

    Language

    English

    First Page

    419

    Last Page

    428

    WOS Identifier

    WOS:000222249600003

    ISSN

    0733-947X

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