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<p>HMC is a transitional stage before intelligent vehicles achieve highly automated driving. Because the driver and the ADAS are simultaneously in the loop, there exist conflicts of driving rights. The steering system of intelligent vehicles must be agile in executing steering control commands in real time. This paper researches the coordinated steering control strategy of HMC for SBW system equipped in intelligent vehicles. Firstly, the SBW system is modelled, and the rack displacement tracking controller is designed based on Fuzzy-SMC. Subsequently, the controllers representing human and machine are designed based on the single-point preview driver model and MPC, respectively. In the scenario of HMC, the vehicle’s lateral offset and the human–machine operation difference are considered, and a fuzzy controller is designed to derive the allocation of driving rights. Then, HMC coordination controller is designed based on NCGT, which enables ADAS to take driver’s actions into account when making decisions. Finally, a semi-physical test bench for SBW system is built. The results of the simulation and HIL tests show that both controllers have good trajectory following effects. Steering control rights can be switched promptly during HMC and driver’s inappropriate operation is corrected, which ensures that the vehicle can follow the correct trajectory.</p>

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Coordinated Human–Machine Co-driving Control of a Steer-by-Wire System Based on a Non-cooperative Game Between Driver and ADAS

  • 期刊论文

  • 发表日期：

    2025年4月2日

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  • Yang Kun,
  • Jiang Haobin,
  • Yuan Peichun,
  • Chen Long,
  • Tang Bin,
  • Li Aoxue,
  • Li Chenxu

摘要

HMC is a transitional stage before intelligent vehicles achieve highly automated driving. Because the driver and the ADAS are simultaneously in the loop, there exist conflicts of driving rights. The steering system of intelligent vehicles must be agile in executing steering control commands in real time. This paper researches the coordinated steering control strategy of HMC for SBW system equipped in intelligent vehicles. Firstly, the SBW system is modelled, and the rack displacement tracking controller is designed based on Fuzzy-SMC. Subsequently, the controllers representing human and machine are designed based on the single-point preview driver model and MPC, respectively. In the scenario of HMC, the vehicle’s lateral offset and the human–machine operation difference are considered, and a fuzzy controller is designed to derive the allocation of driving rights. Then, HMC coordination controller is designed based on NCGT, which enables ADAS to take driver’s actions into account when making decisions. Finally, a semi-physical test bench for SBW system is built. The results of the simulation and HIL tests show that both controllers have good trajectory following effects. Steering control rights can be switched promptly during HMC and driver’s inappropriate operation is corrected, which ensures that the vehicle can follow the correct trajectory.