The Model of Severity Prediction of Traffic Crash on the Curve

Author:

Xi Jian-feng12,Liu Hai-zhu2,Cheng Wei3ORCID,Zhao Zhong-hao2,Ding Tong-qiang2

Affiliation:

1. State Key Laboratory of Automotive Simulation and Control, Jilin University, Changchun 130022, China

2. College of Transportation, Jilin University, Changchun 130022, China

3. Faculty of Transportation Engineering, Kunming University of Science and Technology, Kunming 650224, China

Abstract

With the study of traffic crashes on curved road segments as the focus of research, a logistic regression based curve road crash severity prediction model was established based on a sample crash database of 20000 entries collected from 4 regions of China and 15 evaluation indicators involving driver, driving environment, and traffic environment factors. Maximum Likelihood Estimation and step-back technique were deployed for data analysis, the conclusion of which is that the three main contributory factors on curve road crash severity are weather, roadside protection facility, and pavement structure. Hosmer and Lemeshow tests were used to verify the reliability of the model, and the model variables were discussed to a certain degree as well.

Funder

National Natural Science Foundation of China

Publisher

Hindawi Limited

Subject

General Engineering,General Mathematics

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1. Accident Severity Analysis On the North-South Expressway Using Binomial Logistic Regression;International Journal of Integrated Engineering;2023-11-28

2. Reviews and prospects of human factors research on curve driving;Journal of Traffic and Transportation Engineering (English Edition);2023-10

3. The influences of strict and post-strict lockdowns due to the Covid-19 pandemic on crash severity on rural roads: A case study of Khorasan Razavi, Iran;Transportation Research Part F: Traffic Psychology and Behaviour;2023-08

4. Curve Trajectory Prediction through Vehicle Infrastructure Cooperation;2022 IEEE 17th Conference on Industrial Electronics and Applications (ICIEA);2022-12-16

5. Predicting and Analyzing Road Traffic Injury Severity Using Boosting-Based Ensemble Learning Models with SHAPley Additive exPlanations;International Journal of Environmental Research and Public Health;2022-03-02

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