Driver-automation shared steering control considering driver neuromuscular delay characteristics based on stackelberg game
Jun Liu, Hongyan Guo, Wanqing Shi, Qikun Dai, Jiaming Zhang
Abstract
To promote the intelligent vehicle safety and reduce the driver steering workload, stackelberg game theory is adopted to design the shared steering control strategy that takes the driver neuromuscular delay characteristics into account. First, a shared steering control framework with adjustable driving weight is proposed, and a coupling interaction model considering the driver neuromuscular delay characteristics is constructed by using the stackelberg game theory. Moreover, the driver-automation optimal control strategy is deduced theoretically when the game equilibrium is reached. Finally, simulation and virtual driving tests are carried out to verify the superiority of the proposed method. The results illustrate that the raised method can enhance the vehicle safety with low driving weight intervention, and it can achieve better auxiliary effect with less control cost. In addition, the driver-in-the-loop test results show that the proposed strategy can achieve better performance in assisting drivers with low driving skills.