A Human-Oriented Cooperative Driving Approach: Integrating Driving Intention, State, and Conflict

• URL: http://arxiv.org/abs/2512.23220v1
• Date: Mon, 29 Dec 2025 05:51:00 GMT
• Title: A Human-Oriented Cooperative Driving Approach: Integrating Driving Intention, State, and Conflict
• Abstract summary: We propose a Human-Oriented Cooperative Driving (HOCD) approach to establish more natural and effective human-vehicle interaction.<n>In implementation, we take both tactical and operational levels into account to ensure seamless human-vehicle cooperation.<n>Compared to other cooperative driving approaches, the proposed HOCD approach significantly enhances driving performance and mitigates human-machine conflict.
• Score: 50.983743505985956
• License: http://creativecommons.org/licenses/by-nc-sa/4.0/
• Abstract: Human-vehicle cooperative driving serves as a vital bridge to fully autonomous driving by improving driving flexibility and gradually building driver trust and acceptance of autonomous technology. To establish more natural and effective human-vehicle interaction, we propose a Human-Oriented Cooperative Driving (HOCD) approach that primarily minimizes human-machine conflict by prioritizing driver intention and state. In implementation, we take both tactical and operational levels into account to ensure seamless human-vehicle cooperation. At the tactical level, we design an intention-aware trajectory planning method, using intention consistency cost as the core metric to evaluate the trajectory and align it with driver intention. At the operational level, we develop a control authority allocation strategy based on reinforcement learning, optimizing the policy through a designed reward function to achieve consistency between driver state and authority allocation. The results of simulation and human-in-the-loop experiments demonstrate that our proposed approach not only aligns with driver intention in trajectory planning but also ensures a reasonable authority allocation. Compared to other cooperative driving approaches, the proposed HOCD approach significantly enhances driving performance and mitigates human-machine conflict.The code is available at https://github.com/i-Qin/HOCD.

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