Journal of Jilin University(Engineering and Technology Edition) ›› 2023, Vol. 53 ›› Issue (3): 693-703.doi: 10.13229/j.cnki.jdxbgxb20220897

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Integrated moving horizon decision⁃making method for lane and speed of intelligent vehicle in complex scenarios

Hong-yan GUO1,2(),Wen-ya YU1,2,Jun LIU1,2(),Qi-kun DAI1,2   

  1. 1.State Key Laboratory of Automotive Simulation and Control，Jilin University，Changchun 130022，China
    2.College of Communication Engineering，Jilin University，Changchun 130022，China
  • Received:2022-07-15 Online:2023-03-01 Published:2023-03-29
  • Contact: Jun LIU E-mail:guohy11@jlu.edu.cn;liujun20@jlu.edu.cn

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Abstract:

Aiming at the problem of intelligent vehicle's driving environment understanding and behavior decision-making in complex scenarios， an integrated moving horizon decision-making method for lane and speed of intelligent vehicle was proposed. To obtain the vehicle positions based on the centerlines of different lanes， the vehicle-road space reconstruction model in complex scenarios and the integrated model of lane and vehicle speed with non-integer longitudinal vehicle speed and integer lane number as control variables was established. The safety of future trajectories of the vehicle and oncoming vehicles from multiple directions was analyzed. The integrated decision-making of lane and speed of intelligent vehicle in complex scenarios was described as a mixed-integer nonlinear programming problem. In order to verify the effectiveness of the integrated moving horizon decision-making method of lane and speed， the joint simulation of the vehicle dynamics simulation software veDYNA and Simulink is carried out in the unprotected intersection scenario. The results show that the decision-making method can change lanes in the face of slow-moving or abruptly cut-in vehicles； for safety, intelligent vehicle can make decisions to slow down and give way, when it and the surrounding vehicles drive to the intersection area at the same time.

Key words: control theory and control engineering, integrated decision-making of lane and speed, moving horizon, complex scenarios, mixed-integer programming

CLC Number: 

  • TP273

Fig.1

Ddiagram of integrated decision-making for lane and speed of intelligent vehicle"

Fig.2

Curves of fitting the lane change"

Fig.3

Vehicle-road space reconstruction model"

Fig.4

Division of driving area"

Fig.5

Simulation results of the condition where the vehicle in front is moving slowly"

Fig.6

Simulation results of the condition where theobstacle vehicles abruptly cut in"

Fig.7

Simulation results of the condition of intelligent vehicle and obstacle vehicles entering the intersection at the same time"

Fig.8

Comparative experiment"

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