Past studies have shown that using accident records to estimate vehicle occupancies (i.e., using the observed occupancies of vehicles involved in accidents) results in an overestimation of occupancy. There are a number of possible reasons for this, one of which is that multioccupant accidents are more likely to be reported (i.e., appear in an accident database) because, with more people, the possibility of an injury is greater. The interaction between vehicle occupancy and accident severity is used to develop a method to correct for the occupancy overestimation bias inherent in accident data. A nested logit model of occupancy and severity is estimated, and a correction technique is applied to eliminate biases. The results show that the proposed approach gives accurate predictions of vehicle occupancies using standard accident data.


    Access

    Download

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Predicting Vehicle Occupancies from Accident Data: An Accident Severity Approach


    Additional title:

    Transportation Research Record


    Contributors:


    Publication date :

    1998-01-01




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English




    Prototype Information System for Estimating Average Vehicle Occupancies from Traffic Accident Records

    Gan, Albert / Liu, Kaiyu / Shen, L. David et al. | Transportation Research Record | 2008



    Method for predicting severity of potential collision accident

    REN YUANYUAN / ZHAO LAN / ZHENG XUELIAN et al. | European Patent Office | 2022

    Free access

    Accident severity estimator for a vehicle

    CASTELLANO JAVIER | European Patent Office | 2016

    Free access