Citation

Sun X, Hu H, Ma S, Lin K, Wang J, Lu H. Sustainability (Basel) 2022; 14(22): e14982.

Copyright

(Copyright © 2022, MDPI: Multidisciplinary Digital Publishing Institute)

DOI

10.3390/su142214982

PMID

unavailable

Abstract

In this study, factors affecting crash duration and geostatistical analysis were examined using traffic crash data from Houston, USA. Significant factors affecting road crash duration included 14 independent factors related to time, roadway, and environment. Delays caused by traffic crashes were used as an indicator to assess the impact of traffic crashes of different severity on the roadway network. In addition, the spatial distribution characteristics of the different values corresponding to each key impact factor under different scenarios in the region were studied using ArcGIS kernel density analysis techniques. This is because the combination of these two methods is more operational and understandable. The results show that accidents are more likely to occur at night and on holidays, that accidents last longer after they occur in residential areas, and that accident duration varies near different road facilities. This study may provide a reference for targeted management and improvement measures for road safety.

Language: en

Keywords

duration; kernel density analysis; multinomial logit models; traffic crashes