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Macro-level traffic safety analysis in Shanghai, China.
Xuesong Wang1, Qingya Zhou1, Junguang Yang1
1School of Transportation Engineering, Tongji University, Shanghai, 201804, China; The Key Laboratory of Road and Traffic Engineering, Ministry of Education, Shanghai, 201804, China.
Accident; Analysis and Prevention
|February 25, 2019
Summary
Traffic safety in Shanghai is crucial due to rapid growth. This study identified key factors like population density and road networks that influence traffic crash frequency, aiding future transport planning.
Area of Science:
- Urban Planning
- Transportation Engineering
- Traffic Safety Analysis
Background:
- Rapid urban growth in Shanghai necessitates proactive traffic safety measures.
- Macro-level traffic safety research is limited in China.
- Understanding factors influencing crash frequency is vital for urban development.
Purpose of the Study:
- To develop a macro-level traffic safety model for Shanghai's urban area.
- To examine the relationship between traffic crash frequency and various urban characteristics.
- To inform transportation planning and safety management strategies.
Main Methods:
- Development of a macro-level safety model for 263 traffic analysis zones (TAZs).
- Utilized a Bayesian conditional autoregressive negative binomial model to account for spatial correlations.
- Analyzed relationships between crash frequency and road network, traffic, socio-economic, and land use variables.
Main Results:
- Higher crash frequencies correlate with increased population, road density, and arterial road lengths.
- Increased trip frequencies and shorter intersection spacing were also linked to higher crash rates.
- Identified specific contributing factors to traffic crashes at a macro-level.
Conclusions:
- The study provides valuable insights for transportation planners and managers in Shanghai.
- Findings can guide the development of targeted safety interventions and improved planning.
- Emphasizes the importance of integrating safety considerations early in transport planning for growing cities.
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