Izvorni znanstveni članak
https://doi.org/10.1080/00051144.2022.2055913
A variable weight adaptive cruise control strategy based on lane change recognition of leading vehicle
Xu Li
; School of Transportation, Shandong University of Science and Technology, Qingdao, People’s Republic of China
Ning Xie
; School of Transportation, Shandong University of Science and Technology, Qingdao, People’s Republic of China
Jianchun Wang
; School of Transportation, Shandong University of Science and Technology, Qingdao, People’s Republic of China
Sažetak
The traditional adaptive cruise system is responsible for delay in recognizing the cut-in/cut-out behaviour of front vehicle, and there is significant longitudinal acceleration of the vehicle fluctuation leading to reduced driver’s comfort level and even dangerous situation. In this paper, the next generation simulation data set and back propagation (BP) neural network are used to train the vehicle lane change recognition model to recognize the lane change behaviour of the preceding vehicle. The higher controller adopts variable weight linear quadratic optimal control to adjust the weight parameters according to the recognition results of front vehicle to reduce the fluctuation of vehicle acceleration. The lower layer adopts fuzzy proportional-integral-derivative (PID) control to follow the expected acceleration and builds the vehicle inverse dynamic model. Through CarSim/Simulink co-simulation, the results show that, under the cut-in or cut-out and working conditions, the behaviour of the leading vehicle can be recognized, following target can be switched in advance, weight parameters can be adjusted and the large fluctuation of longitudinal acceleration can be reduced.
Ključne riječi
Adaptive cruise control; lane change intention recognition of leading vehicle; layered control; weight adjustment strategy
Hrčak ID:
287527
URI
Datum izdavanja:
11.4.2022.
Posjeta: 278 *