TY - GEN
T1 - Parallel Distributed Cooperative Control of Multiple Vehicles with Low Communication Traffic
AU - Jie, Ma
AU - Sichao, Tang
AU - Feng, Gao
AU - Yuan, Liping
N1 - Publisher Copyright:
© 2023 IEEE.
PY - 2023
Y1 - 2023
N2 - This paper presents a parallel distributed framework for cooperative control of of connected and automated vehicles (CAV) with low communication traffic. With this framework, the original centralized cooperative control problem is decomposed to a series of separable sub-optimization ones by introducing a set of consensus variables and linear transformation to fully use the computation resources of CAV. Additionally, to reduce the communication traffic between different computing nodes, a communication filtering strategy is designed by limit the transmission of the consensus variables by considering the fact that the interaction process tends to convergence when the variation among adjacent steps is small. To ensure the converge of numerical optimization process, a non-negative decreasing function is used to evaluate the variation of consensus variables. The effectiveness of the proposed cooperative control system is validated and analyzed by several comparative simulations with the original one by considering several indices including cooperation, optimality and communication efficiency.
AB - This paper presents a parallel distributed framework for cooperative control of of connected and automated vehicles (CAV) with low communication traffic. With this framework, the original centralized cooperative control problem is decomposed to a series of separable sub-optimization ones by introducing a set of consensus variables and linear transformation to fully use the computation resources of CAV. Additionally, to reduce the communication traffic between different computing nodes, a communication filtering strategy is designed by limit the transmission of the consensus variables by considering the fact that the interaction process tends to convergence when the variation among adjacent steps is small. To ensure the converge of numerical optimization process, a non-negative decreasing function is used to evaluate the variation of consensus variables. The effectiveness of the proposed cooperative control system is validated and analyzed by several comparative simulations with the original one by considering several indices including cooperation, optimality and communication efficiency.
KW - Alternating direction method of multipliers
KW - Cooperative control
KW - Distributed computation framework
KW - Intelligent vehicle
UR - https://www.scopus.com/pages/publications/85185385365
U2 - 10.1109/CVCI59596.2023.10397216
DO - 10.1109/CVCI59596.2023.10397216
M3 - 会议稿件
AN - SCOPUS:85185385365
T3 - Proceedings of the 2023 7th CAA International Conference on Vehicular Control and Intelligence, CVCI 2023
BT - Proceedings of the 2023 7th CAA International Conference on Vehicular Control and Intelligence, CVCI 2023
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 7th CAA International Conference on Vehicular Control and Intelligence, CVCI 2023
Y2 - 27 October 2023 through 29 October 2023
ER -