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Evaluation of an Exclusive Spur Dike U-Turn Design with Radar-Collected Data and Simulation

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Hotspot Identification for Shanghai Expressways Using the Quantitative Risk Assessment Method.

Can Chen¹, Tienan Li², Jian Sun^3,4

¹Department of Traffic Engineering and Key Laboratory of Road & Traffic Engineering of the Ministry of Education, Tongji University, 4800 Cao'an Road, Shanghai 201804, China. 1433975@tongji.edu.cn.

International Journal of Environmental Research and Public Health

|December 31, 2016

Summary

This summary is machine-generated.

This study introduces a new quantitative risk assessment (QRA) method for hotspot identification (HSID) on expressways. This approach effectively identifies high-risk locations by considering both crash probability and monetized direct and indirect crash consequences.

Keywords:

crash empirical Bayesian expressway hotspot identification potential crash costs risk assessment

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Area of Science:

Road safety
Transportation engineering
Risk management

Background:

Hotspot identification (HSID) is crucial for effective expressway safety management.
Existing methods may not fully capture the multifaceted costs associated with traffic incidents.

Purpose of the Study:

To develop and present a novel HSID method utilizing quantitative risk assessment (QRA).
To integrate direct and indirect crash losses into a unified risk assessment framework for prioritizing safety interventions.

Main Methods:

Employs the empirical Bayesian method to estimate crash occurrence probability for all exposed vehicles.
Utilizes a deterministic queuing diagram method to calculate indirect losses from traffic delays.
Monetizes both direct (injuries, property damage) and indirect losses to quantify total crash consequences.

Main Results:

The proposed QRA method successfully identifies high-risk expressway sites.
The method provides a clear criterion for ranking sites based on potential crash costs.
A case study on Shanghai's urban expressways validates the effectiveness of the approach.

Conclusions:

The new QRA-based HSID method offers a robust approach to identifying critical safety hotspots.
This method accurately reflects the societal costs of potential crashes, aiding targeted safety improvements.