Decentralized Longitudinal Tracking Control for Cooperative Adaptive Cruise Control Systems in a Platoon

Abstract

Abstract-This paper presents a longitudinal tracking control law for Cooperative Adaptive Cruise Control (CACC) systems in a platoon that can comprehensively enable tracking capability of various spacing policies, designed expected velocity, and designed expected acceleration. Taking into account heterogeneous traffic, i.e., a platoon of vehicles with possibly different characteristics, the longitudinal control problem is formulated as an output tracking control problem with a quadratic function so that the contradictions among the different tracking requirements are realized, which include inter-vehicle spacing, velocity and acceleration. Then, the decentralized longitudinal tracking control law is proposed by using a limited communication structure and maximum principle (in this case, a wireless communication link with the nearest preceding vehicle and designed platoon leader only), in which the feedback items are composed of the states of host vehicles, and additional information of the nearest preceding vehicle and designed platoon leader are used as feedforward items. In addition, the concepts of "expected velocity" and "expected acceleration" are introduced to design the desired velocity and acceleration, realize additional objectives, and improve the predictive abilities. Numerous simulation results show that the proposed tracking controller provides a reliable tool for a systematic and efficient design of a platoon controller within CACC systems.

Lane-Changing Tracking Control of Automated Vehicle Platoon Based on MA-DDPG and Adaptive MPC

“…[54] and [55] combine the MARL algorithm with the CACC control method, but the relationship between different agents is not described in the literature mentioned above, nor is the general structure made evident. A decentralized MARL framework for longitudinal tracking control of CACC platoons is proposed in [56], [57], removing the central controller. The work in [58] proposes a CAV platoon control method based on the distributed DQN algorithm, which contains local training and global consensus, but this method can only produce discrete action spaces with the speed curve fluctuating up and down.…”

Cooperative decentralized decision making for conflict resolution among autonomous agents

“…In the literature, systems that claim to behave in a cooperative way share the ability of working together. Regarding the aspect of cooperation, some do not go more into detail [1,8,10], others include additional aspects: Communication is often required for cooperative behavior in terms of exchanging information [2,3,5,7,13,17] or just receiving information [16], e. g. for collision detection or enhancing ACC capabilities. However, cooperative system behavior based on implicit communication can be found as well [20].…”

Robust optimal control and identification of adaptive cruise control systems in the presence of time delay and parameter uncertainties

“…The communication topology of a vehicular platoon can be either centralized or decentralized. If all vehicles have access to information of lead vehicle, the network is centralized (Chehardoli and Ghasemi, 2018; Di Bernardo et al, 2016), otherwise is decentralized (Claes et al, 2011; Han et al, 2013). Because the stability margin of centralized networks is larger than decentralized networks, the amplitude of spacing error is smaller in centralized networks (Zheng et al, 2016b).…”