<p>Vehicle collision avoidance (CA) has been widely studied to improve road traffic safety. However, most evasion assistance control methods face challenges in effectively coordinating collision avoidance safety and human-machine interaction conflict. This paper introduces a novel multi-mode evasion assistance control (MEAC) method for intelligent distributed-drive electric vehicles. A reference safety area is established considering the vehicle safety and stability requirements, which serves as a guiding principle for evading obstacles. The proposed method includes two control modes: Shared-EAC (S-EAC) and Emergency-EAC (E-EAC). In S-EAC, an integrated human-machine authority allocation mechanism is designed to mitigate conflicts between human drivers and the control system during collision avoidance. The E-EAC mode is tailored for situations where the driver has no collision avoidance behavior and utilizes model predictive control to generate additional yaw moments for collision avoidance. Simulation and experimental results indicate that the proposed method reduces human-machine conflict and assists the driver in safe collision avoidance in the S-EAC mode under various driver conditions. In addition, it enhances the vehicle responsiveness and reduces the extent of emergency steering in the E-EAC mode while improving the safety and stability during the collision avoidance process.</p>

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Multi-mode Evasion Assistance Control Method for Intelligent Distributed-drive Electric Vehicle Considering Human Driver’s Reaction

  • Bo Leng,
  • Zhuoren Li,
  • Ming Liu,
  • Ce Yang,
  • Yi Luo,
  • Amir Khajepour,
  • Lu Xiong

摘要

Vehicle collision avoidance (CA) has been widely studied to improve road traffic safety. However, most evasion assistance control methods face challenges in effectively coordinating collision avoidance safety and human-machine interaction conflict. This paper introduces a novel multi-mode evasion assistance control (MEAC) method for intelligent distributed-drive electric vehicles. A reference safety area is established considering the vehicle safety and stability requirements, which serves as a guiding principle for evading obstacles. The proposed method includes two control modes: Shared-EAC (S-EAC) and Emergency-EAC (E-EAC). In S-EAC, an integrated human-machine authority allocation mechanism is designed to mitigate conflicts between human drivers and the control system during collision avoidance. The E-EAC mode is tailored for situations where the driver has no collision avoidance behavior and utilizes model predictive control to generate additional yaw moments for collision avoidance. Simulation and experimental results indicate that the proposed method reduces human-machine conflict and assists the driver in safe collision avoidance in the S-EAC mode under various driver conditions. In addition, it enhances the vehicle responsiveness and reduces the extent of emergency steering in the E-EAC mode while improving the safety and stability during the collision avoidance process.