Multi-objective Constrained Lane-changing Decision-making for Autonomous Vehicles
[1]LIN Guoqing,QIN Yu,et al.Multi-objective Constrained Lane-changing Decision-making for Autonomous Vehicles[J].Journal of Zhengzhou University (Engineering Science),2027,48(XX):1-9.[doi:10.13705/j.issn.1671-6833.2027.01.001]
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Journal of Zhengzhou University (Engineering Science)[ISSN
1671-6833/CN
41-1339/T] Volume:
48
Number of periods:
2027 XX
Page number:
1-9
Column:
Public date:
2027-12-10
- Title:
- Multi-objective Constrained Lane-changing Decision-making for Autonomous Vehicles
- Keywords:
- autonomous vehicles; multi-objective constraints; lane-changing decision; trajectory planning; simulation analysis; Vehicle-in-the-Loop experiments
- CLC:
- TP391.9；U463.6
- Abstract:
- To achieve safe and efficient lane-changing of autonomous vehicles in complex traffic environments, a lane-changing strategy based on multi-objective constraints is proposed. Driving dissatisfaction is decomposed into speed dissatisfaction and space dissatisfaction, which are used to evaluate the current lane condition and generate lane-change intentions. A lane evaluation function is established to quantitatively assess candidate lanes and determine the optimal target lane. Within a connected vehicle environment, constraint checks are conducted from the perspectives of legality, safety, and altruism, and lane-changing is executed only when all constraints are satisfied. A quintic polynomial is employed for lane-change trajectory planning, and efficiency and comfort weights are introduced to balance lane-change efficiency and ride comfort. Results from CarSim–Simulink co-simulation and vehicle-in-the-loop experiments demonstrate that the proposed strategy meets multi-objective constraint requirements and achieves stable and reliable lane-change decision-making and execution. Specifically, the maximum yaw angle is 3.45 deg, the maximum lateral acceleration is 1.31 m/s², and the maximum trajectory tracking errors are 0.02 m in the lateral direction and 0.012 m in the longitudinal direction. These results verify that the proposed decision model can achieve precise lane-change control with satisfactory performance.
- References:
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Last Update:
2026-07-24
