Cyclist crash rates;
Age group differences;
Resampling;
XGBoost-Tweedie;
Nonlinear effects;
CRASH-FREQUENCY;
OLDER DRIVERS;
RISK;
VEHICLE;
INJURY;
MODELS;
D O I:
10.1016/j.aap.2024.107872
中图分类号:
TB18 [人体工程学];
学科分类号:
1201 ;
摘要:
In the Netherlands and all over the world, traffic safety problem has been growing particularly for cyclists over the last decades with more people shifting to cycling as a healthy and sustainable mode of transport. Literature shows that age is an important factor in crash involvement and consequences; however, few studies identify the risk factors for cyclists from across different age groups. Therefore, this study aims to identify and understand the effects of traffic, infrastructure, and land use factors on vehicle-to-bike injury and fatal crashes involving cyclists from different age groups. For this purpose, we adopted an approach consisting of resampling and machine learning (XGBoost-Tweedie) techniques to analyse police-reported crashes between the years 2015 and 2019 in the Netherlands. The analysis shows that effects of external variables on crashes widely vary among different age groups and the analysis of total crash rates may not disclose the nature of crashes of cyclist from different age groups. The analysis also shed light on the nonlinear effects of traffic and built environment factors on cyclist crashes, which are usually disregarded in the traffic safety literature. The proposed approach and findings provide a profound understanding of the nature of cyclist crashes and the complex relationships between factors, which can contribute to developing effective crash prevention strategies tailored to different age groups.
机构:
Faculty of Transportation Engineering, Kunming University of Science and Technology, KunmingFaculty of Transportation Engineering, Kunming University of Science and Technology, Kunming
Ji X.-F.
Qiao X.
论文数: 0引用数: 0
h-index: 0
机构:
Faculty of Transportation Engineering, Kunming University of Science and Technology, KunmingFaculty of Transportation Engineering, Kunming University of Science and Technology, Kunming
Qiao X.
Jiaotong Yunshu Xitong Gongcheng Yu Xinxi/Journal of Transportation Systems Engineering and Information Technology,
2023,
23
(01):
: 314
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323
机构:
Guangzhou Univ, Sch Geog & Remote Sensing, Guangzhou 510006, Peoples R ChinaGuangzhou Univ, Sch Geog & Remote Sensing, Guangzhou 510006, Peoples R China
Zhuang, Caigang
Li, Shaoying
论文数: 0引用数: 0
h-index: 0
机构:
Guangzhou Univ, Sch Geog & Remote Sensing, Guangzhou 510006, Peoples R ChinaGuangzhou Univ, Sch Geog & Remote Sensing, Guangzhou 510006, Peoples R China
Li, Shaoying
Tan, Zhangzhi
论文数: 0引用数: 0
h-index: 0
机构:
South China Normal Univ, Beidou Res Inst, Foshan 528200, Peoples R ChinaGuangzhou Univ, Sch Geog & Remote Sensing, Guangzhou 510006, Peoples R China
Tan, Zhangzhi
Feng, Gao
论文数: 0引用数: 0
h-index: 0
机构:
Guangzhou Urban Planning & Design Res Inst, Guangzhou 510060, Peoples R China
Guangdong Enterprise Key Lab Urban Sensing Monito, Guangzhou 510060, Peoples R ChinaGuangzhou Univ, Sch Geog & Remote Sensing, Guangzhou 510006, Peoples R China
Feng, Gao
Wu, Zhifeng
论文数: 0引用数: 0
h-index: 0
机构:
Guangzhou Univ, Sch Geog & Remote Sensing, Guangzhou 510006, Peoples R ChinaGuangzhou Univ, Sch Geog & Remote Sensing, Guangzhou 510006, Peoples R China