Event‐driven intermittent control for vehicle platooning over vehicular ad‐hoc networks

Abstract

This article is concerned with the problem of vehicle platooning control over vehicular ad-hoc networks (VANETs). Compared with the existing platooning control strategies, an event-driven intermittent control method is developed to reduce control costs and extend the operating life of controllers while ensuring the desired platooning performance. By establishing suitable boundary functions and Lyapunov function, the control input is determined according to the relationship among the trajectories of these functions. Thereafter, sufficient conditions for platooning control performance analysis are derived by a set of linear matrix inequalities. Wherein, the vehicle platooning based on intermittent control is obtained to maintain the desired inter-vehicle distance and a uniform speed in the platoon. Furthermore, a simple optimization algorithm is constructed to calculate the smallest upper bound on tracking errors. Finally, several simulations based on different topologies are provided to verify the validity of the proposed method.

A Novel Framed Slotted Aloha Medium Access Control Protocol Based on Capture Effect in Vehicular Ad Hoc Networks

“…In ref. [19], an adaptive and on-demand TDMA-based MAC protocol is proposed to address the challenges of hightransmission collisions and channel resource wastage in the unbalanced traffic conditions of VANETs. In ref.…”

Coalitional Control Strategy for a Heterogeneous Platoon Application

“…It is noteworthy to mention that, to compute the optimal state feedback gain matrix for other possible communication topologies, one must adequately change both the cost index J i from ( 7) and the control action u i from (8). Depending on the topology, one must also incorporate a tracking error term that contains the output signal received via the enabled communication links.…”

“…Two communication topologies are employed in a cooperative adaptive cruise control (CACC) strategy, namely using the information from the preceding vehicle and using the additional information from two vehicles ahead, together with the predecessor data. Several control strategies for vehicle platooning have been recently studied, such as distributed model predictive control (DMPC) [7], eventdriven intermittent control [8], hierarchical fuzzy control logic [9], and deep reinforcement learning [10], among others. In [11], a DMPC strategy for flexible vehicle platooning is proposed.…”

IBLF‐based lanes merging control for vehicle platoon with prescribed performances

“…In light of the advancements of the control strategies and remote communication techniques, the distributed cooperative control has been investigated extensively in various scenarios 1‐5 . As a subfield of distributed control, the intelligent transportation systems attract more and more attentions nowadays.…”

“…In light of the advancements of the control strategies and remote communication techniques, the distributed cooperative control has been investigated extensively in various scenarios. [1][2][3][4][5] As a subfield of distributed control, the intelligent transportation systems attract more and more attentions nowadays. Specifically, the advanced driving assistance system (ADAS) has revealed a great potential for wide applications in intelligent transportation systems.…”