Safety-Based Vulnerability Assessment for Identifying Critical Road Links: A Cooperative Game Theory Approach
Abstract
Road traffic crashes are a major global cause of fatalities and serious injuries. Identifying safety-critical links during transportation planning can help mitigate these risks proactively. While conventional safety approaches rank links based on crash frequency, this study introduces a network vulnerability perspective to assess link importance. This new perspective shifts the focus from evaluating the local impact of crashes on individual links to assessing each link’s contribution to overall network safety. Unlike previous research that evaluates link safety contribution in isolation, this study adopts a cooperative game theory framework to account for cooperative interactions among links. The Shapley value, a solution concept from cooperative game theory, is employed to quantify the importance of each link, treating links as players. To account for the flow-dependent nature of road safety, we utilize a safety evaluation metric that calculates the utility of a cooperative game within a stochastic user equilibrium (SUE) model. This approach calculates the average marginal contribution of links to network safety across all possible link coalitions, accounting for traffic interactions rather than considering only their marginal contribution (MC) to the grand coalition. Numerical experiments highlight the advantages of the proposed approach by comparing Shapley value-based rankings with those derived from MC alone. Results show that the Shapley value more comprehensively captures link-level safety contributions, offering planners a useful framework for identifying critical links and prioritizing interventions to enhance network safety during the planning stage.
Fields of Study & Subjects
Traffic and Road Safety
Transportation Planning and Optimization
Infrastructure Resilience and Vulnerability Analysis
Publication details
- Journal / source
- IEEE Transactions on Intelligent Transportation Systems
- Volume
- 27
- Issue
- 7
- Pages
- 8710–8723
- Publication date
- 16 February 2026
- Language
- EN