Towards activity-based exposure measures in spatial analysis of pedestrian–motor vehicle crashesThis article was handled by Associate Editor Chris Lee.

Dong，Ni1,2,3; Meng，Fanyu4,5; Zhang，Jie1,2; Wong，S. C.6; Xu，Pengpeng6

2020-12-01

10.1016/j.aap.2020.105777

ACCIDENT ANALYSIS AND PREVENTION   影响因子和分区

0001-4575

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.

Activity-based exposure measures Crash frequency Pedestrian safety Spatial correlation Spatial heterogeneity

SSCI ; EI

英语

其他

20204009292402

Frequency estimation ; Accidents ; Risk assessment ; Vehicles ; Population statistics ; Surveys

Roads and Streets:406.2 ; Accidents and Accident Prevention:914.1

SOCIAL SCIENCES, GENERAL

2-s2.0-85091803787

Scopus

1.School of Transportation and Logistics,Southwest Jiaotong University,Chengdu,China
2.National United Engineering Laboratory of Integrated and Intelligent Transportation,Southwest Jiaotong University,Chengdu,China
3.Department of Civil and Environmental Engineering,University of Washington,Seattle,United States
4.Academy for Advanced Interdisciplinary Studies,Southern University of Science and Technology,Shenzhen,China
5.Department of Statistics and Data Science,Southern University of Science and Technology,Shenzhen,China
6.Department of Civil Engineering,The University of Hong Kong,Hong Kong

Dong，Ni,Meng，Fanyu,Zhang，Jie,等. Towards activity-based exposure measures in spatial analysis of pedestrian–motor vehicle crashesThis article was handled by Associate Editor Chris Lee.[J]. ACCIDENT ANALYSIS AND PREVENTION,2020,148.

Dong，Ni,Meng，Fanyu,Zhang，Jie,Wong，S. C.,&Xu，Pengpeng.(2020).Towards activity-based exposure measures in spatial analysis of pedestrian–motor vehicle crashesThis article was handled by Associate Editor Chris Lee..ACCIDENT ANALYSIS AND PREVENTION,148.

Dong，Ni,et al."Towards activity-based exposure measures in spatial analysis of pedestrian–motor vehicle crashesThis article was handled by Associate Editor Chris Lee.".ACCIDENT ANALYSIS AND PREVENTION 148(2020).