TY - GEN
T1 - Hierarchical Distributed MPC for Longitudinal and Lateral Vehicle Platoon Control with Collision Avoidance
AU - Liu, Hankun
AU - Qiang, Zhiwen
AU - Dai, Li
AU - Chen, Boli
AU - Xia, Yuanqing
N1 - Publisher Copyright:
© 2023 Technical Committee on Control Theory, Chinese Association of Automation.
PY - 2023
Y1 - 2023
N2 - This paper proposes a hierarchical distributed model predictive control (MPC) method for vehicle platoon control in both longitudinal and lateral directions. In the upper layer, a novel path-planning module and a trajectory-fusion module are utilized to compute a smooth reference trajectory for each follower. In the lower layer, the longitudinal and lateral distributed model predictive controllers are decoupled to control the velocity and steering respectively. To ensure safety and reduce the computation burden, the constraints to avoid collision are reformulated by using the strong duality theory. A simulation is conducted to demonstrate the effectiveness of the proposed control algorithm in maintaining platoon formation and ensuring the safety of the platoon.
AB - This paper proposes a hierarchical distributed model predictive control (MPC) method for vehicle platoon control in both longitudinal and lateral directions. In the upper layer, a novel path-planning module and a trajectory-fusion module are utilized to compute a smooth reference trajectory for each follower. In the lower layer, the longitudinal and lateral distributed model predictive controllers are decoupled to control the velocity and steering respectively. To ensure safety and reduce the computation burden, the constraints to avoid collision are reformulated by using the strong duality theory. A simulation is conducted to demonstrate the effectiveness of the proposed control algorithm in maintaining platoon formation and ensuring the safety of the platoon.
KW - Collision avoidance constraints
KW - Distributed model predictive control
KW - Longitudinal and lateral control
KW - Vehicle platoon
UR - http://www.scopus.com/inward/record.url?scp=85175544173&partnerID=8YFLogxK
U2 - 10.23919/CCC58697.2023.10240367
DO - 10.23919/CCC58697.2023.10240367
M3 - Conference contribution
AN - SCOPUS:85175544173
T3 - Chinese Control Conference, CCC
SP - 2676
EP - 2682
BT - 2023 42nd Chinese Control Conference, CCC 2023
PB - IEEE Computer Society
T2 - 42nd Chinese Control Conference, CCC 2023
Y2 - 24 July 2023 through 26 July 2023
ER -