Road deaths, injuries and property damage places a huge burden on the economy of most nations. Wyoming has one of the highest truck-related fatality rates among the states in the US. The high crash rates observed in the state is as a result of many factors mainly related to the challenging mountainous terrain in the state, which places extra burden on truck drivers in terms of requiring higher levels of alertness and driving skills. The difficult geometry of roads characteristic of mountainous terrain in terms of steep grade lengths adds extra risks of fatalities or injuries occurring as a result of a crash. These risks are more pronounced for truck-related crashes due to their weight and sizes. As part of the measures to reduce the incidence of truck-related crashes on mountainous areas, the Wyoming Department of Transportation (WYDOT) initiated a study to investigate causes of truck crashes on downgrade areas of Wyoming. Several studies have investigated the contributory factors to severe injury crashes but the focus has mostly been on level sections. This study analyzed the contributory geometric factors of truck crashes on downgrades by estimating three crash prediction negative binomial models. These models took into account the injury severity of the crashes. The results indicate that downgrade length, shoulder width, horizontal curve length, number of lanes, number of access points and truck traffic on the highway all impact truck-related crashes and injury frequencies on downgrades in Wyoming. The results of this study will be helpful to future downgrade road design policy aimed at reducing downgrade truck related crashes.


    Access

    Download


    Export, share and cite



    Title :

    Predicting injury severity and crash frequency: Insights into the impacts of geometric variables on downgrade crashes in Wyoming


    Contributors:


    Publication date :

    2020




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    Unknown




    An assessment of machine learning and data balancing techniques for evaluating downgrade truck crash severity prediction in Wyoming

    Vincent Michael Ampadu / Muhammad Tahmidul Haq / Khaled Ksaibati | DOAJ | 2022

    Free access

    Predicted Average Annual Cost of Crashes on the US-16 Wyoming Downgrade Using Time Series Analysis and Forecasting

    Ampadu, Vincent-Michael Kwesi / Ker, Andrew John / Wulff, Shaun S. et al. | Springer Verlag | 2024



    Predicted Average Annual Cost of Crashes on the US-16 Wyoming Downgrade Using Time Series Analysis and Forecasting

    Ampadu, Vincent-Michael Kwesi / Ker, Andrew John / Wulff, Shaun S. et al. | Springer Verlag | 2024


    Comparison of Vehicle-Based Crash Severity Metrics for Predicting Occupant Injury in Real-World Oblique Crashes

    Dean, Morgan E. / Gabauer, Douglas J. / Riexinger, Luke E. et al. | Transportation Research Record | 2022