Platoon longitudinal and lateral control and cooperative positioning algorithm based on DMPC and FedKF

• Published in: 2022 6th International Symposium on Computer Science and Intelligent Control (ISCSIC) pp. 216 - 220
• Main Authors: Zhang, Haiqiao, Li, Yinong, Li, Meiyu
• Format: Conference Proceeding
• Language: English
• Published: IEEE 01.11.2022
• Subjects: cooperative positioning; Federated Kalman filtering; Heuristic algorithms; Kalman filters; Longitudinal and lateral platoon control; Predictive models; Radar tracking; Roads; Stability analysis; Topology
• DOI: 10.1109/ISCSIC57216.2022.00053

Platoon control helps to improve road utilization and reduce congestion under existing road conditions, but GPS signal error often affects the stability of platoon system. To solve this problem, this paper considers the longitudinal and lateral control and cooperative positioning of the platoon, establishes the dynamic model of the platoon composed of five vehicles, designs distributed model prediction controllers for the platoon, and uses the Federated Kalman Filter (FedKF) method to realize the fusion of GPS signals and radar signals in the platoon, so as to make sufficient use of the information redundancy of the platoon to improve the positioning accuracy, reduce speed fluctuation and improve system stability. Finally, the simulation experiment compares the platoon based on Extended Kalman Filter (EKF) and the platoon based on FedKF. It is confirmed that the designed controller has a good effect on the platoon control and the platoon using FedKF has more advantages in positioning accuracy and other aspects in the presence of GPS positioning errors, radar detection errors and dynamic process noises.