TY - GEN
T1 - Model predictive approach to integrated path planning and tracking for autonomous vehicles
AU - Huang, Chao
AU - Li, Boyuan
AU - Kishida, Masako
N1 - Funding Information:
The authors are supported by ERATO HASUO Metamathematics for Systems Design Project (No. JPMJER1603), JST.
Publisher Copyright:
© 2019 IEEE.
PY - 2019/10
Y1 - 2019/10
N2 - In the field of path planning for autonomous vehicle, the existing studies separately consider the path planning and path tracking problem. To fill in this research gap, this study proposes an integrated path planning and path tracking control method. In addition, this paper studies the collision avoidance problem of autonomous vehicles by considering static and dynamic obstacles. Simulation results show that the proposed method can generate a collision-free path and control the autonomous vehicle to avoid the obstacles simultaneously.
AB - In the field of path planning for autonomous vehicle, the existing studies separately consider the path planning and path tracking problem. To fill in this research gap, this study proposes an integrated path planning and path tracking control method. In addition, this paper studies the collision avoidance problem of autonomous vehicles by considering static and dynamic obstacles. Simulation results show that the proposed method can generate a collision-free path and control the autonomous vehicle to avoid the obstacles simultaneously.
UR - http://www.scopus.com/inward/record.url?scp=85076806055&partnerID=8YFLogxK
U2 - 10.1109/ITSC.2019.8916898
DO - 10.1109/ITSC.2019.8916898
M3 - Conference article published in proceeding or book
AN - SCOPUS:85076806055
T3 - 2019 IEEE Intelligent Transportation Systems Conference, ITSC 2019
SP - 1448
EP - 1453
BT - 2019 IEEE Intelligent Transportation Systems Conference, ITSC 2019
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2019 IEEE Intelligent Transportation Systems Conference, ITSC 2019
Y2 - 27 October 2019 through 30 October 2019
ER -