The platooning of connected and automated vehicles (CAVs) is expected to have a transformative impact on road transportation, e.g., enhancing highway safety, improving traffic utility, and reducing fuel consumption. Requiring only local information, distributed control schemes are scalable approaches to the coordination of multiple CAVs without using centralized communication and computation. From the perspective of multi-agent consensus control, this paper introduces a decomposition framework to model, analyze, and design the platoon system. In this framework, a platoon is naturally decomposed into four interrelated components, i.e., 1) node dynamics, 2) information flow network, 3) distributed controller, and 4) geometry formation. The classic model of each component is summarized according to the results of the literature survey; four main performance metrics, i.e., internal stability, stability margin, string stability, and coherence behavior, are discussed in the same fashion. Also, the basis of typical distributed control techniques is presented, including linear consensus control, distributed robust control, distributed sliding mode control, and distributed model predictive control.
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Fully Distributed Optimization-Based CAV Platooning Control Under Linear Vehicle Dynamics
This paper develops distributed optimization-based, platoon-centered connected and autonomous vehicle (CAV) car-following schemes, motivated by the recent interest in CAV platooning technologies. Various distributed optimization or control schemes have been developed for CAV platooning. However, most existing distributed schemes for platoon centered CAV control require either centralized data processing or centralized computation in at least one step of their schemes, referred to as partially distributed schemes. In this paper, we develop fully distributed optimization based, platoon centered CAV platooning control under the linear vehicle dynamics via the model predictive control approach with a general prediction horizon. These fully distributed schemes do not require centralized data processing or centralized computation through the entire schemes. To develop these schemes, we propose a new formulation of an objective function and a decomposition method that decomposes a densely coupled central objective function into the sum of multiple locally coupled functions whose coupling satisfies the network topology constraint. We then exploit locally coupled optimization and operator splitting methods to develop fully distributed schemes. Control design and stability analysis is carried out to achieve desired traffic transient performance and asymptotic stability. Numerical tests demonstrate the effectiveness of the proposed fully distributed schemes and CAV platooning control.
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- NSF-PAR ID:
- 10326722
- Date Published:
- Journal Name:
- Transportation Science
- Volume:
- 56
- Issue:
- 2
- ISSN:
- 0041-1655
- Page Range / eLocation ID:
- 381 to 403
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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Abstract Rapid advances in vehicle automation and communication technologies enable connected autonomous vehicles (CAVs) to cross intersections cooperatively, which could significantly improve traffic throughput and safety at intersections. Virtual platooning, designed upon car‐following behavior, is one of the promising control methods to promote cooperative intersection crossing of CAVs. Nevertheless, demand variation raises safety and stability concerns when CAVs adopt a virtual platooning control approach. Along this line, this study proposes an adaptive vehicle control method to facilitate the formation of a virtual platoon and the cooperative crossing of CAVs, factoring demand variations at an isolated intersection. This study derives the stability conditions of virtual CAV platoons depending on the time‐varying traffic demand. Based on the derived stability conditions, an optimization model is proposed to adaptively control CAVs dynamics by balancing approaching traffic mobility and safety to enhance the reliability of cooperative crossing at intersections. The simulation results show that, compared to the nonadaptive control, our proposed method can increase the intersection throughput by 18.2%. Also, time‐to‐collision results highlight the advantages of the proposed adaptive control in securing traffic safety.
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null (Ed.)Connected Autonomous Vehicular (CAV) platoon refers to a group of vehicles that coordinate their movements and operate as a single unit. The vehicle at the head acts as the leader of the platoon and determines the course of the vehicles following it. The follower vehicles utilize Vehicle-to-Vehicle (V2V) communication and automated driving support systems to automatically maintain a small fixed distance between each other. Reliance on V2V communication exposes platoons to several possible malicious attacks which can compromise the safety, stability, and efficiency of the vehicles. We present a novel distributed resiliency architecture, RePLACe for CAV platoon vehicles to defend against adversaries corrupting V2V communication reporting preceding vehicle position. RePLACe is unique in that it can provide real-time defense against a spectrum of communication attacks. RePLACe provides systematic augmentation of a platoon controller architecture with real-time detection and mitigation functionality using machine learning. Unlike computationally intensive cryptographic solutions RePLACe accounts for the limited computation capabilities provided by automotive platforms as well as the real-time requirements of the application. Furthermore, unlike control-theoretic approaches, the same framework works against the broad spectrum of attacks. We also develop a systematic approach for evaluation of resiliency of CAV applications against V2V attacks. We perform extensive experimental evaluation to demonstrate the efficacy of RePLACe.more » « less
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The performance of connected and automated vehicle (CAV) platoons, aimed at improving traffic efficiency and safety, depends on vehicle dynamics and communication reliability. However, CAVs are vulnerable to perturbations in vehicular communication. Such endogenous vulnerability can induce oscillatory dynamics to CAVs, leading to the failure of platooning. Differing from previous work on CA V platoon stability, this research exploits CAV platooning vulnerability under periodic perturbation by formulating the oscillatory dynamics as vibrations in a mechanical system. Akin to other mechanical systems, a CAV platoon has its inherent oscillation frequency, exhibiting unique characteristics in a perturbed travel environment. To this end, this paper proposes an approach to characterize the CAV platooning vulnerability using the mechanical vibration theory. The employed theory reveals that CAV platooning vulnerability mainly associates with its resonance frequency, through which a small periodic perturbation can amplify the platoon oscillation. The analytical formulation and simulation results show that preventing periodic perturbations from a platoon's resonance frequency is crucial to enhance the CAV platooning reliability and suppress large amplitude oscillations, helping to secure the expected benefits of CAV platoons.more » « less
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Connected automated vehicles (CAVs), built upon advanced vehicle control and communication technology, can improve traffic throughput, safety, and energy efficiency. Previous studies on CAVs control focus on instability and stability properties of CAV platoons; however, these analyses cannot reveal the damping platoon oscillation characteristics, which are important for enhancing CAV platoon reliability against variant continuous perturbations. To this end, this research seeks to characterize the damping oscillations of CAVs through exploiting the platoon's unforced oscillatory, i.e., damping behavior. Inspired by the mechanical vibration theory, the proposed approach is applied to a CAV platoon with linear car-following control formulated as Helly's model and the predecessor-following communication topology. The proposed approach is applied to a CAV platoon with the linear car-following control formulated as Helly's model and the predecessor-following communication topology. Numerical analysis results show that a periodic perturbation with the resonance frequency of the CAV platoon will amplify the oscillation and lead to the severest oscillatory traffic. Our analysis highlights the importance of preventing platoon oscillations from resonance in ensuring CAV platooning reliability.more » « less
- Free Publicly Accessible Full Text
-
Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.1287/trsc.2021.1100
