Weather impacts on various types of road crashes: a quantitative analysis using generalized additive models

作     者：Becker, Nico Rust, Henning W. Ulbrich, Uwe 

作者机构：Free Univ Berlin Inst Meteorol Carl Heinrich Becker Weg 6-10 D-12165 Berlin Germany Hans Ertel Ctr Weather Res Berlin Germany 

出 版 物：《EUROPEAN TRANSPORT RESEARCH REVIEW》 (欧洲运输研究评论)

年 卷 期：2022年第14卷第1期

页      面：1-18页

核心收录：

学科分类：12[管理学] 0202[经济学-应用经济学] 02[经济学] 1201[管理学-管理科学与工程(可授管理学、工学学位)] 020205[经济学-产业经济学] 08[工学] 082303[工学-交通运输规划与管理] 0823[工学-交通运输工程] 

基　　金：Bundesministerium fur Verkehr und Digitale Infrastruktur [4818DWDP3A] 

主　　题：Road crashes Crash type Traffic volume Weather Precipitation Sun glare Wind speed Generalized Additive Model Relative risk Impact model 

摘      要：Adverse weather conditions can have different effects on different types of road crashes. We quantify the combined effects of traffic volume and meteorological parameters on hourly probabilities of 78 different crash types using generalized additive models. Using tensor product bases, we model non-linear relationships and combined effects of different meteorological parameters. We evaluate the increase in relative risk of different crash types in case of precipitation, sun glare and high wind speeds. The largest effect of snow is found in case of single-truck crashes, while rain has a larger effect on single-car crashes. Sun glare increases the probability of multi-car crashes, in particular at higher speed limits and in case of rear-end crashes. High wind speeds increase the probability of single-truck crashes and, for all vehicle types, the risk of crashes with objects blown on the road. A comparison of the predictive power of models with and without meteorological variables shows an improvement of scores of up to 24%, which makes the models suitable for applications in real-time traffic management or impact-based warning systems. These could be used by authorities to issue weather-dependent driving restrictions or situation-specific on-board warnings to improve road safety.