Highlights Using population as a surrogate of pedestrian exposure leads to biased estimates. Activity-based exposure measures should be used when modeling pedestrian crashes. Travel-diary survey offers a straightforward means to estimate pedestrian activity. Spatial heterogeneity is worthy of note in zonal pedestrian crash-frequency models.

    Abstract Background Although numerous efforts have been devoted to exploring the effects of area-wide factors on the frequency of pedestrian crashes in neighborhoods over the past two decades, existing studies have largely failed to provide a full picture of the factors that contribute to the incidence of zonal pedestrian crashes, due to the unavailability of reliable exposure data and use of less sound analytical methods. Methods Based on a crowdsourced dataset in Hong Kong, we first proposed a procedure to extract pedestrian trajectories from travel-diary survey data. We then aggregated these data to 209 neighborhoods and developed a Bayesian spatially varying coefficients model to investigate the spatially non-stationary relationships between the number of pedestrian–motor vehicle (PMV) crashes and related risk factors. To dissect the role of pedestrian exposure, the estimated coefficients of models with population, walking trips, walking time, and walking distance as the measure of pedestrian exposure were presented and compared. Results Our results indicated substantial inconsistencies in the effects of several risk factors between the models of population and activity-based exposure measures. The model using walking trips as the measure of pedestrian exposure had the best goodness-of-fit. We also provided new insights that in addition to the unstructured variability, heterogeneity in the effects of explanatory variables on the frequency of PMV crashes could also arise from the spatially correlated effects. After adjusting for vehicle volume and pedestrian activity, road density, intersection density, bus stop density, and the number of parking lots were found to be positively associated with PMV crash frequency, whereas the percentage of motorways and median monthly income had negative associations with the risk of PMV crashes. Conclusions The use of population or population density as a surrogate for pedestrian exposure when modeling the frequency of zonal pedestrian crashes is expected to produce biased estimations and invalid inferences. Spatial heterogeneity should also not be negligible when modeling pedestrian crashes involving contiguous spatial units.


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    Title :

    Towards activity-based exposure measures in spatial analysis of pedestrian–motor vehicle crashes


    Contributors:
    Dong, Ni (author) / Meng, Fanyu (author) / Zhang, Jie (author) / Wong, S.C. (author) / Xu, Pengpeng (author)


    Publication date :

    2020-09-09




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English




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