Analyzing pedestrian crash injury severity under different weather conditions

被引:46
|
作者
Li, Duo [1 ]
Ranjitkar, Prakash [2 ]
Zhao, Yifei [1 ]
Yi, Hui [1 ]
Rashidi, Soroush [3 ]
机构
[1] Changan Univ, Highway Sch, Room 208, Xian 710000, Shaanxi, Peoples R China
[2] Univ Auckland, Dept Civil & Environm Engn, Auckland, New Zealand
[3] Opus Int Consultants Ltd, Auckland, New Zealand
关键词
Injury severity; weather; classification and regression trees (CART); random forests; ACCIDENT; RISK;
D O I
10.1080/15389588.2016.1207762
中图分类号
R1 [预防医学、卫生学];
学科分类号
1004 ; 120402 ;
摘要
Objective: Pedestrians are the most vulnerable road users due to the lack of mass, speed, and protection compared to other types of road users. Adverse weather conditions may reduce road friction and visibility and thus increase crash risk. There is limited evidence and considerable discrepancy with regard to impacts of weather conditions on injury severity in the literature. This article investigated factors affecting pedestrian injury severity level under different weather conditions based on a publicly available accident database in Great Britain.Method: Accident data from Great Britain that are publicly available through the STATS19 database were analyzed. Factors associated with pedestrian, driver, and environment were investigated using a novel approach that combines a classification and regression tree with random forest approach.Results: Significant severity predictors under fine weather conditions from the models included speed limits, pedestrian age, light conditions, and vehicle maneuver. Under adverse weather conditions, the significant predictors were pedestrian age, vehicle maneuver, and speed limit.Conclusions: Elderly pedestrians are associated with higher pedestrian injury severities. Higher speed limits increase pedestrian injury severity. Based on the research findings, recommendations are provided to improve pedestrian safety.
引用
收藏
页码:427 / 430
页数:4
相关论文
共 50 条
  • [1] Analyzing Traffic Crash Severity in Work Zones under Different Light Conditions
    Wei, Xinxin
    Shu, Xiang
    Huang, Baoshan
    Taylor, Edward L.
    Chen, Huaxin
    JOURNAL OF ADVANCED TRANSPORTATION, 2017,
  • [2] Analyzing pedestrian crash injury severity at signalized and non-signalized locations
    Haleem, Kirolos
    Alluri, Priyanka
    Gan, Albert
    ACCIDENT ANALYSIS AND PREVENTION, 2015, 81 : 14 - 23
  • [3] Diagnostic analysis of the effects of weather condition on pedestrian crash severity
    Zhai, Xiaoqi
    Huang, Helai
    Sze, N. N.
    Song, Ziqi
    Hon, Kai Kwong
    ACCIDENT ANALYSIS AND PREVENTION, 2019, 122 : 318 - 324
  • [4] Injury Severity of Multivehicle Crash in Rainy Weather
    Jung, Soyoung
    Qin, Xiao
    Noyce, David A.
    JOURNAL OF TRANSPORTATION ENGINEERING, 2012, 138 (01) : 50 - 59
  • [5] Injury severity analysis of truck-involved crashes under different weather conditions
    Uddin, Majbah
    Huynh, Nathan
    ACCIDENT ANALYSIS AND PREVENTION, 2020, 141
  • [6] Applying Association Rules Mining to Investigate Pedestrian Fatal and Injury Crash Patterns Under Different Lighting Conditions
    Hossain, Ahmed
    Sun, Xiaoduan
    Thapa, Raju
    Codjoe, Julius
    TRANSPORTATION RESEARCH RECORD, 2022, 2676 (06) : 659 - 672
  • [7] Analyzing crash injury severity for a mountainous freeway incorporating real-time traffic and weather data
    Yu, Rongjie
    Abdel-Aty, Mohamed
    SAFETY SCIENCE, 2014, 63 : 50 - 56
  • [8] Evaluation of Pedestrian Safety Pedestrian Crash Hot Spots and Risk Factors for Injury Severity
    Jang, Kitae
    Park, Shin Hyoung
    Kang, Sanghyeok
    Song, Ki Han
    Kang, Seungmo
    Chung, Sungbong
    TRANSPORTATION RESEARCH RECORD, 2013, (2393) : 104 - 116
  • [9] Identifying crash-prone traffic conditions under different weather on freeways
    Xu, Chengcheng
    Wang, Wei
    Liu, Pan
    JOURNAL OF SAFETY RESEARCH, 2013, 46 : 135 - 144
  • [10] Critical patterns associated with vehicle-pedestrian hit-and-run casualty injury severity under different weather conditions: An association rule mining approach
    Tamakloe R.
    Adanu E.K.
    IATSS Research, 2024, 48 (03) : 299 - 318