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Title: Characterizing Connected and Automated Vehicle Platooning Vulnerability under Periodic Perturbation
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.
Authors:
; ;
Award ID(s):
2047793
Publication Date:
NSF-PAR ID:
10318499
Journal Name:
2021 IEEE International Intelligent Transportation Systems Conference (ITSC)
Sponsoring Org:
National Science Foundation
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