Examining the characteristics between time and distance gaps of secondary crashes

作     者：Xinyuan Liu Jinjun Tang Chen Yuan Fan Gao Xizhi Ding Xinyuan Liu;Jinjun Tang;Chen Yuan;Fan Gao;Xizhi Ding

作者机构：Smart Transport Key Laboratory of Hunan ProvinceSchool of Transport and Transportation EngineeringCentral South UniversityChangsha 410075China Department of Computer ScienceCity University of Hong Kong999077Kowloon TongHong KongChina Department of Geography and Resource ManagementThe Chinese University of Hong KongShatinNT 999077Hong KongChina 

出 版 物：《Transportation Safety and Environment》 (交通安全与环境（英文）)

年 卷 期：2024年第6卷第1期

页      面：116-131页

核心收录：

学科分类：03[法学] 08[工学] 0838[工学-公安技术] 0306[法学-公安学] 

基　　金：This research was funded in part by Innovation-Driven Project of Central South University(Grant No.2020CX041) the Fundamental Research Funds for the Central Universities of Central South University(Grant No.2022ZZTS0717) 

主　　题：secondary crash(SC) time and distance gaps stacking framework local interpretable model-agnostic explanations(LIME) 

摘      要：Understanding the characteristics of time and distance gaps between the primary(PC)and secondary crashes(SC)is crucial for preventing SC ccurrences and improving road *** previous studies have tried to analyse the variation of gaps,there is limited evidence in quantifying the relationships between different gaps and various influential *** study proposed a two-layer stacking framework to discuss the time and distance ***,the framework took random forests(RF),gradient boosting decision tree(GBDT)and eXtreme gradient boosting as the base classifiers in the first layer and applied logistic regression(LR)as a combiner in the second *** this basis,the local interpretable model-agnostic explanations(LIME)technology was used to interpret the output of the stacking model from both local and global *** SC dentification and feature selection,346 SCs and 22 crash-related factors were collected from California interstate *** results showed that the stacking model outperformed base models evaluated by accuracy,precision,and recall *** explanations based on LIME suggest that collision type,distance,speed and volume are the critical features that affect the time and distance *** volume can prolong queue length and increase the distance gap from the SCs to *** collision types,peak periods,workday,truck involved and tow away likely induce a long-distance ***,there is a shorter distance gap when secondary roads run in the same direction and are close to the primary *** speed is a significant factor resulting in a long-time gap,while the higher speed is correlated with a short-time *** results are expected to provide insights into how contributory features affect the time and distance gaps and help decision-makers develop accurate decisions to prevent SCs.