A Review of Traffic Operation Risk Analysis on Highways in a Connected and Automated Environment

ZHANG Mengya; YANG Xiaoguang; MA Chengyuan; YANG Jie

doi:10.3963/j.jssn.1674-4861.2025.02.015

Volume 43 Issue 2

Apr. 2025

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ZHANG Mengya, YANG Xiaoguang, MA Chengyuan, YANG Jie. A Review of Traffic Operation Risk Analysis on Highways in a Connected and Automated Environment[J]. Journal of Transport Information and Safety, 2025, 43(2): 137-153. doi: 10.3963/j.jssn.1674-4861.2025.02.015

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ZHANG Mengya, YANG Xiaoguang, MA Chengyuan, YANG Jie. A Review of Traffic Operation Risk Analysis on Highways in a Connected and Automated Environment[J]. Journal of Transport Information and Safety, 2025, 43(2): 137-153. doi: 10.3963/j.jssn.1674-4861.2025.02.015

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A Review of Traffic Operation Risk Analysis on Highways in a Connected and Automated Environment

doi: 10.3963/j.jssn.1674-4861.2025.02.015

1.
Key Laboratory of Road and Traffic Engineering of the Ministry of Education, Tongji University, Shanghai 201804, China
2.
Department of Civil and Environmental Engineering, University of Wisconsin-Madison, Madison 53706, WI, USA

Received Date: 2024-05-02
Available Online: 2025-09-29

Abstract

Abstract

The analysis of traffic operation risks on expressways holds significant theoretical and practical value for enhancing traffic safety, reliability, and realizing proactive management. The connected environment introduces new methods, theories, and technologies for traffic risk analysis. Focusing on continuous traffic flows on highways and urban expressways, this study systematically reviews the theoretical foundations and key techniques of traffic operation risk analysis under both non-connected and connected environments, and discusses future research directions. In non-connected environments, risk analysis primarily relies on limited unstructured data, emphasizing risk factor identification, accident mechanism analysis, and risk prediction. Challenges remain in achieving high-precision scene modeling, responsive dynamic evolution analysis, and real-time risk perception and forecasting. In connected environments, the integration of multi-source real-time data enables a shift toward proactive risk prediction and localized interaction analysis, with improvements in data support and modeling accuracy. However, in mixed traffic conditions, systematic models for the interaction dynamics of heterogeneous vehicle types have not yet been fully established. The combined effects of diverse driving behaviors, communication delays, and perception deviations require further investigation, and the modeling and interpretation of dynamic factor evolution in complex environments remain incomplete. Future research should advance the modeling of human-vehicle-road collaborative evolution, refine the characterization of risk accumulation and propagation in mixed traffic, enhance multi-source data fusion and dynamic feature extraction, and strengthen the real-time performance and robustness of risk evaluation. Through theoretical innovation, data-driven methods, and integrated technological development, it is expected that an interpretable, predictable, and actionable intelligent traffic risk prevention and control system will be progressively established.
- traffic safety,
- traffic operational risks,
- review,
- connected and automated driving environment,
- highways

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References(56)

References

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A Review of Traffic Operation Risk Analysis on Highways in a Connected and Automated Environment

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