Leveraging cooperative connected automated vehicles for mixed traffic safety

Zhao, Chenguang; Molnár, Tamás G.; Yu, Huan · 2025 · Transportation Research Part B Methodological

DOI: 10.1016/j.trb.2025.103352

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Summary

This paper addresses the challenge of ensuring safety and stability in mixed traffic environments containing both connected automated vehicles (CAVs) and human-driven vehicles (HVs). While prior research has focused on controlling pure CAV platoons or single CAVs, there is a lack of study regarding the safety impact of cooperative control strategies for multiple CAVs interacting with HVs, particularly the trade-offs between traffic stability and collision avoidance. The authors investigate how a pair of cooperative CAVs can stabilize mixed traffic and enhance safety under varying levels of connectivity and automation penetration. The study models a mixed vehicle platoon consisting of two CAVs (a head and a tail CAV) separated by $N$ HVs. The authors design nominal cooperative feedback controllers for the CAVs that integrate adaptive cruise control, feedback from connected HVs, and coordination between the two CAVs. To address safety, the paper employs Control Barrier Functions (CBFs) to construct safety constraints. These CBFs act as safety filters that modify the nominal controllers only when necessary to prevent rear-end collisions, thereby guaranteeing safety for the CAVs, the intermediate HVs, and the platoon as a whole. The authors conduct theoretical stability analysis using linearized system dynamics and head-to-tail transfer functions, alongside numerical simulations to validate the controllers' performance against uncertain human driver behaviors and varying connectivity rates. The results demonstrate that cooperative control between CAVs effectively stabilizes mixed traffic dynamics. The integration of CBF-based safety filters ensures that this stability is achieved without compromising safety, successfully preventing collisions for both automated and human-driven vehicles. Furthermore, the study reveals distinct benefits based on the direction of connectivity: when an HV connects to an upstream CAV, the CAV can leverage this information to stabilize upstream traffic; conversely, when an HV connects to a downstream CAV, the safety of that specific connected HV is enhanced. The proposed framework proves robust to unmodeled HV dynamics and varying penetration rates. The significance of this work lies in providing a methodological framework for cooperative CAV control that simultaneously guarantees stability and formal safety in mixed traffic. By leveraging HV connectivity, the approach offers a pathway to improve traffic smoothness and safety during the transitional period before full automation. The findings highlight that connectivity is not merely a tool for efficiency but a critical component for ensuring the safety of surrounding human drivers, offering practical insights for the deployment of CAVs in real-world mixed-autonomy scenarios.

Key finding

Cooperative control of connected and automated vehicles stabilizes mixed traffic, and leveraging connectivity with human-driven vehicles provides additional benefits by enhancing upstream traffic stability or downstream vehicle safety depending on the connection direction.

Methodology

simulation_modeling

Provenance

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Summary generated by qwen3.6-27b-prismaquant on 2026-06-10; verification: verified.

Topics

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• v2x connected vehicle