Human-Machine Shared Control Approach for the Takeover of Cooperative Adaptive Cruise Control
<|reference_start|>Human-Machine Shared Control Approach for the Takeover of Cooperative Adaptive Cruise Control: Cooperative Adaptive Cruise Control (CACC) often requires human takeover for tasks such as exiting a freeway. Direct human takeover can pose significant risks, especially given the close-following strategy employed by CACC, which might cause drivers to feel unsafe and execute hard braking, potentially leading to collisions. This research aims to develop a CACC takeover controller that ensures a smooth transition from automated to human control. The proposed CACC takeover maneuver employs an indirect human-machine shared control approach, modeled as a Stackelberg competition where the machine acts as the leader and the human as the follower. The machine guides the human to respond in a manner that aligns with the machine's expectations, aiding in maintaining following stability. Additionally, the human reaction function is integrated into the machine's predictive control system, moving beyond a simple "prediction-planning" pipeline to enhance planning optimality. The controller has been verified to i) enable a smooth takeover maneuver of CACC; ii) ensure string stability within a specific Operational Design Domain (ODD) when human control authority is below 32.7%; iii) enhance both perceived and actual safety through machine interventions; and iv) reduce the impact on upstream traffic by up to 60%.<|reference_end|>
@article{wang2024human-machine,
    title={Human-Machine Shared Control Approach for the Takeover of Cooperative
  Adaptive Cruise Control},
    author={Haoran Wang, Zhenning Li, Arno Eichberger, Jia Hu},
    journal={arXiv preprint arXiv:2407.11551},
    year={2024},
    archivePrefix={arXiv},
    eprint={2407.11551},
    primaryClass={cs.RO}
}