Control Rights Distribution Weights and Takeover Authority for Human-machine Co-driving based on Fuzzy Control Algorithm

This paper presents driving control rights allocation mechanism and the theory of human-machine co-driving based on fuzzy logic algorithm for solving the issues that the steering wheel angle input by the driver in the distracted and exhausted state causes the vehicle to deviate from the center line of the lane. Based on the establishment of the vehicle kinematics model, aiming at the driving situation of the vehicle deviating from the center line of the lane caused by the steering wheel angle input in the distracted and exhausted state, the weight coefficient of the driving control rights is introduced based on the fuzzy logic control algorithm. The human-machine co-driving model is based on weighting coefficients, weighted fusion of the human driver and the automatic driving system, and finally controls the steering wheel angle of the vehicle to achieve lane keeping. Finally, a Carsim/Matlab joint simulation platform was built to simulate the effect of lane keeping under different vehicle speeds. The results show that the weight coefficient of control weight can be changed in real time according to driver status information and vehicle information, and the human-machine co-driving model can better realize the flexible transfer of Human-machine co-driving control rights and maintain lanes, with high control accuracy and anti-lube good stickiness and good interference.