Factors that affect highway-related crash frequency and injury severity vary across observations. Using a methodology that does not account nor correct for heterogeneity in observed and unobserved crash factors across highway segments may lead to biased and inconsistent estimated coefficients, thus resulting in erroneous inferences. The present paper demonstrates the use of random-parameters models to facilitate and enhance how crash factors affect crash frequency and injury severity along a highway segment. The results indicate that a unit increase in the presence of stop sign along a highway segment reduces crash frequency by 2.471 for 87.24% of the roadway segments. For the remaining 12.76% of the roadway segments, crash frequency is increased by the same margin. Using the random-parameters multinomial logit model, the result indicates that, for 90.89% of the observations, the presence of a stop sign on a highway segment increases the probability of the injury outcome. For 9.11% of the observations, the presence of a stop sign on a highway segment reduces the probability of the injury outcome, and the marginal effect value across observations is 0.0017. Vertical grades greater than 5% increase crash frequency for 58.46% of the highway segments, and decrease for 41.54% of the highway segments by 0.121 for one unit increase in vertical grades.


    Access

    Download


    Export, share and cite



    Title :

    Random-parameters analysis of highway characteristics on crash frequency and injury severity


    Contributors:


    Publication date :

    2016




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    Unknown