TY - GEN
T1 - Multi-Segment Polynomial Trajectory Generation of Autonomous Vehicles Based on Quadratic Programming
AU - Wei, Chao
AU - Lv, Mo
AU - Ma, Benshan
AU - Zhang, Zhe
AU - Zhao, Botong
AU - Su, Menglun
N1 - Publisher Copyright:
© 2024 IEEE.
PY - 2024
Y1 - 2024
N2 - Trajectory planning is one of the key technologies of autonomous vehicles. The quality of trajectory will affect the driving safety, but the trajectory planning of autonomous vehicles is still a challenging problem. In this paper, a multi-segment polynomial trajectory planning method based on quadratic programming in the Frenet coordinate system is proposed. The trajectory curve is divided into multiple segments to optimize with different emphasis. Firstly, an objective function is designed to consider the moving targets, trajectory comfort, driving safety and acceleration cost. Also, the trajectory continuity, road boundary limit, and vehicle movement limit are considered in the constraints. Next, the optimization problem is solved to determine the coefficients of the multi-segment polynomial, and then the trajectory is generated. Finally, the Gilbert-Johnson-Keerthi (GJK) algorithm is used to detect the collision, which ensures the safety of the trajectory geometrically. Simulation results show that the proposed method can generate a safe and comfortable trajectory. Besides, the proposed method can effectively improve real-time performance and trajectory quality.
AB - Trajectory planning is one of the key technologies of autonomous vehicles. The quality of trajectory will affect the driving safety, but the trajectory planning of autonomous vehicles is still a challenging problem. In this paper, a multi-segment polynomial trajectory planning method based on quadratic programming in the Frenet coordinate system is proposed. The trajectory curve is divided into multiple segments to optimize with different emphasis. Firstly, an objective function is designed to consider the moving targets, trajectory comfort, driving safety and acceleration cost. Also, the trajectory continuity, road boundary limit, and vehicle movement limit are considered in the constraints. Next, the optimization problem is solved to determine the coefficients of the multi-segment polynomial, and then the trajectory is generated. Finally, the Gilbert-Johnson-Keerthi (GJK) algorithm is used to detect the collision, which ensures the safety of the trajectory geometrically. Simulation results show that the proposed method can generate a safe and comfortable trajectory. Besides, the proposed method can effectively improve real-time performance and trajectory quality.
KW - autonomous vehicles
KW - Frenet coordinate system
KW - multi-segment polynomial
KW - quadratic programming
KW - trajectory planning
UR - http://www.scopus.com/inward/record.url?scp=85199663120&partnerID=8YFLogxK
U2 - 10.1109/ICCCR61138.2024.10585399
DO - 10.1109/ICCCR61138.2024.10585399
M3 - Conference contribution
AN - SCOPUS:85199663120
T3 - 2024 4th International Conference on Computer, Control and Robotics, ICCCR 2024
SP - 171
EP - 177
BT - 2024 4th International Conference on Computer, Control and Robotics, ICCCR 2024
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 4th International Conference on Computer, Control and Robotics, ICCCR 2024
Y2 - 19 April 2024 through 21 April 2024
ER -