J Shanghai Jiaotong Univ Sci ›› 2021, Vol. 26 ›› Issue (5): 615-625.doi: 10.1007/s12204-021-2351-z

• Intelligent Connected Vehicle • Previous Articles     Next Articles

Intelligent-Assist Algorithm for Remote Shared-Control Driving Based on Game Theory

QIAO Bangjun∗ (乔邦峻), LI Huanghe (李黄河), WU Xiaodong (吴晓东)   

  1. (School of Mechanical Engineering, Shanghai Jiao Tong University, Shanghai 200240, China)
  • Received:2020-11-30 Online:2021-10-28 Published:2021-10-28

Abstract: Contemporary autonomous-driving technology relies on good environmental-perception systems and high-precision maps. For unknown environments or scenarios where perception fails, a human-in-the-loop remote-driving system can effectively complement common solutions, although safety remains an issue for its application. A haptic shared-control algorithm based on non-cooperative game theory is presented in this paper. The algorithm generates collision-free reference paths with model predictive control and predicts the driver’s path using a two-point preview model. Man-machine torque interaction is modeled as a Nash game, and the assist system’s degree of intervention is regulated in real time, according to assessments of collision risk and the driver’s concentration. Simulations of several representative scenarios demonstrate how the proposed method improves driving safety, while respecting driver decisions.

Key words: remote driving, shared control, game theory

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