Exploring injury severity of pedestrian-vehicle crashes at intersections: unbalanced panel mixed ordered probit model

被引:0
|
作者
Željko Šarić
Xuecai Xu
Daiquan Xiao
Joso Vrkljan
机构
[1] University of Zagreb,Department of Traffic Accident Expertise, Faculty of Transport and Traffic Sciences
[2] Huazhong University of Science and Technology,School of Civil and Hydraulic Engineering
[3] Polytechnic “Nikola Tesla”,undefined
来源
关键词
Injury severity; Pedestrian-vehicle crash; Unbalanced panel mixed ordered probit model; Random parameter ordered probit model;
D O I
暂无
中图分类号
学科分类号
摘要
Although the pedestrian deaths have been declining in recent years, the pedestrian-vehicle death rate in Croatia is still pretty high. This study intended to explore the injury severity of pedestrian-vehicle crashes with panel mixed ordered probit model and identify the influencing factors at intersections. To achieve this objective, the data were collected from Ministry of the Interior, Republic of Croatia from 2015 to 2018. Compared to the equivalent random-effects and random parameter ordered probit models, the proposed model showed better performance on goodness-of-fit, while capturing the impact of exogenous variables to vary among the intersections, as well as accommodating the heterogeneity issue due to unobserved effects. Results revealed that the proposed model can be considered as an alternative to deal with the heterogeneity issue and to decide the factor determinants. The results may provide beneficial insight for reducing the injury severity of pedestrian-vehicle crashes.
引用
收藏
相关论文
共 50 条
  • [1] Exploring injury severity of pedestrian-vehicle crashes at intersections: unbalanced panel mixed ordered probit model
    Saric, Zeljko
    Xu, Xuecai
    Xiao, Daiquan
    Vrkljan, Joso
    EUROPEAN TRANSPORT RESEARCH REVIEW, 2021, 13 (01)
  • [2] Investigating injury severity of pedestrian-vehicle crashes by integrating latent class cluster analysis and unbalanced panel mixed ordered probit model
    Xiao, Daiquan
    Saric, Zeljko
    Xu, Xuecai
    Yuan, Quan
    JOURNAL OF TRANSPORTATION SAFETY & SECURITY, 2023, 15 (02) : 83 - 102
  • [3] Modeling Pedestrian Injury Severity in Pedestrian-Vehicle Crashes in Rural and Urban Areas: Mixed Logit Model Approach
    Chen, Zhen
    Fan, Wei
    TRANSPORTATION RESEARCH RECORD, 2019, 2673 (04) : 1023 - 1034
  • [4] Factors affecting pedestrian injury severity in pedestrian-vehicle crashes: Insights from a data mining and mixed logit model approach
    Ouyang, Huijie
    Han, Yin
    Liu, Pengfei
    Zhao, Jing
    JOURNAL OF TRANSPORTATION SAFETY & SECURITY, 2024, 16 (09) : 1015 - 1038
  • [5] Pedestrian-injury severity analysis in pedestrian-vehicle crashes with familiar and unfamiliar drivers
    Xue, Gang
    Wen, Huiying
    TRANSPORTMETRICA A-TRANSPORT SCIENCE, 2024, 20 (01) : 36 - 36
  • [6] Exploring Factors Contributing to Pedestrian Injury Severity in Pedestrian-Vehicle Crashes: An Integrated XGBoost-SHAP, Latent Cluster, and Mixed Logit Approach
    Ouyang, Huijie
    Liu, Pengfei
    Han, Yin
    JOURNAL OF TRANSPORTATION ENGINEERING PART A-SYSTEMS, 2025, 151 (02)
  • [7] Evaluation of Injury Severity for Pedestrian-Vehicle Crashes in Jordan Using Extracted Rules
    Mujalli, Randa Oqab
    Garach, Laura
    Lopez, Griselda
    Al-Rousan, Taleb
    JOURNAL OF TRANSPORTATION ENGINEERING PART A-SYSTEMS, 2019, 145 (07)
  • [8] Modeling pedestrian injury severity in pedestrian-vehicle crashes considering different land use patterns: Mixed logit approach
    Yang, Tianjia
    Fan, Wei
    Song, Li
    TRAFFIC INJURY PREVENTION, 2023, 24 (02) : 114 - 120
  • [9] Predicting pedestrian-vehicle interaction severity at unsignalized intersections
    Muduli, Kaliprasana
    Ghosh, Indrajit
    TRAFFIC INJURY PREVENTION, 2025, 26 (02) : 252 - 261
  • [10] Mixed logit approach to modeling the severity of pedestrian-injury in pedestrian-vehicle crashes in North Carolina: Accounting for unobserved heterogeneity
    Li, Yang
    Fan, Wei
    JOURNAL OF TRANSPORTATION SAFETY & SECURITY, 2022, 14 (05) : 796 - 817