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A multinomial logit model: Safety risk analysis of interchange area based on aggregate driving behavior data.
Xiaohua Zhao1, Yang Ding1, Ying Yao1
1Beijing Key Laboratory of Traffic Engineering, College of Metropolitan Transportation, Beijing University of Technology, 100124, China.
Journal of Safety Research
|March 7, 2022
Summary
Road safety risk at urban expressway interchanges is influenced by factors like day of week and traffic congestion. Understanding these elements can help improve traffic management and road conditions.
Area of Science:
- Traffic Engineering
- Road Safety Analysis
- Urban Planning
Background:
- Urban expressway interchanges are increasingly prone to accidents due to rising vehicle ownership.
- Identifying key factors influencing road safety is crucial for accident prevention.
Purpose of the Study:
- To investigate the impact of various factors on road safety risk levels at urban expressway interchanges.
- To analyze the influence of traffic control devices and road conditions on safety.
Main Methods:
- Utilized aggregate driving behavior data from navigation software.
- Employed the traffic order index (TOI) to assess road safety risk levels.
- Developed a multinomial logit model (MNL) to analyze influencing factors.
Main Results:
- Significant factors for risky roads include day of the week, number of lanes, and congestion.
- Traffic disturbance (merging/diverging within 500m) and specific advance guide sign systems also impact risk.
- Complexity of diagrammatic guide signs (low/medium) was identified as a significant factor.
Conclusions:
- Findings provide actionable insights for traffic management departments.
- Recommendations can guide improvements in road conditions and traffic control devices at interchanges.
- This research contributes to enhancing safety in complex urban road networks.
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