Highlights Different pedestrian crash exposure proxies: population, walking frequency and walking time, were estimated based on the household travel survey data. Three pedestrian crash prediction models were established to measure the association between pedestrian crash, exposure, travel purpose and other possible factors. Model using walking frequency as the exposure proxy was superior to that using population and walking time. Crash risk of back home walking trip was more profounding than that of other travel purposes.

    Abstract Pedestrian are vulnerable to severe injury and mortality in the road crashes. Understanding the essence of the pedestrian crash is important to the development of effective safety countermeasures and improvement of social well-being. It is necessary to measure the exposure for the quantification of pedestrian crash risk. The primary goals of this study are to explore the efficient exposure measure for pedestrian crash, and identify the possible factors contributing to the incidence of pedestrian crash. In this study, amount of travel was estimated based on the Travel Characteristic Survey (TCS) data in 2011, and the crash data were obtained from the Transport Information System (TIS) of the Hong Kong Transport Department during the period from 2011 to 2015. Total population, walking frequency and walking time were adopted to represent the pedestrian exposure to road crash. The effect of trip purpose on pedestrian crash was evaluated by disaggregating the pedestrian exposure proxies by purpose. Three random-parameter negative binomial regression models were developed to compare the performances of the three pedestrian exposure proxies. It was found that the model in which walking frequency was used as the exposure proxy provided the best goodness-of-fit. Frequency of walking back home, among other trip purposes, was the most sensitive to the increase in pedestrian crash risk. Additionally, increase in the frequency of pedestrian crash was correlated to the increases in the proportions of children and elderly people. Furthermore, household size, median household income, road density, number of non-signalized intersection as well as number of zebra crossings also significantly affected the pedestrian crash frequency. Findings of this study should be indicative to the development and implementation of effective traffic control and management measures that can improve the pedestrian safety in the long run.


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    Title :

    Exposure to pedestrian crash based on household survey data: Effect of trip purpose


    Contributors:
    Sze, N.N. (author) / Su, Junbiao (author) / Bai, Lu (author)

    Published in:

    Publication date :

    2019-03-27


    Size :

    8 pages




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English