Adapting Time Headway in Cooperative Adaptive Cruise Control to Network Reliability

Alsuhaim, Adil; Rayamajhi, Anjan; Westall, James; Martin, Jim

doi:10.1109/tvt.2021.3119620

Cited by 14 publications

(9 citation statements)

References 19 publications

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“…is the position reference input to vehicle k + 1 asymptotically. Applying Theorem 2 again yields that y k+1 (t) → y (k+1) ref (t) as t → ∞, concluding that limits (35) hold for i = k + 1. Hence (i) is proven by the induction process.…”

Section: Control Of Vehicle Platoonmentioning

confidence: 82%

“…(ii) Under the LTI control law, the dynamics of vehicle 1 are described by the same ODE as in (11), and dynamics of other vehicles are described by the same ODE as in (30). Then, given any initial condition satisfying v i (0) > 0 for all i ∈  , the limits in (35) hold.…”

Section: Control Of Vehicle Platoonmentioning

confidence: 99%

“…Since g i is sufficiently high for i ≥ 2, Theorem 2 can be applied to conclude the limits in (35) for the case of i = 2. By induction, assume that the limits in (35)…”

Section: Control Of Vehicle Platoonmentioning

confidence: 99%

“…See the robust approach in References 23 and 24, adaptive optimal method in Reference 25, ecological CACC in Reference 26, predictive control in Reference 27, and Smith predictor in References 28 and 29. See also more recent work in References 30–38 and references therein.…”

Section: Introductionmentioning

confidence: 99%

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Robust adaptive control for a class of autonomous vehicle platoons

Ren,

Chen,

2024

Adaptive Control & Signal

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SummaryThis article studies robust adaptive control for a class of autonomous vehicle platoons. In particular, two innovative adaptive control laws are proposed to address both position and velocity tracking for a vehicle platoon. In addition, it is shown that robust asymptotic string stability can be delivered by the underlying adaptive control laws for the vehicle platoon, in the sense that these adaptive control laws are capable of mitigating parameter uncertainties involved in the nonlinear vehicular dynamics and achieving truly cooperative adaptive cruise control while ensuring the required safety spacing between each neighboring vehicle pair asymptotically. It is also shown that the control performance of the vehicle platoon can be further improved if the operating equilibrium points of all vehicles can be adaptively estimated, leading to two linear time‐invariant control laws for individual vehicles under both position and velocity controls and for the vehicle platoon. Simulation studies illustrate the effectiveness of the proposed control method, validating the results obtained for the class of vehicle platoons.

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Section: Control Of Vehicle Platoonmentioning

confidence: 82%

Section: Control Of Vehicle Platoonmentioning

confidence: 99%

“…Since g i is sufficiently high for i ≥ 2, Theorem 2 can be applied to conclude the limits in (35) for the case of i = 2. By induction, assume that the limits in (35)…”

Section: Control Of Vehicle Platoonmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Robust adaptive control for a class of autonomous vehicle platoons

Ren,

Chen,

2024

Adaptive Control & Signal

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“…Along with the development of intelligent transportation systems(ITS), vehicle platoon has received a wide range of attention from academia and industry [5,6]. Platoon behavior exists widely in nature.…”

Section: Introductionmentioning

confidence: 99%

ELM-Based Non-Singular Fast Terminal Sliding Mode Control Strategy for Vehicle Platoon

Wang

2022

Sustainability

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Vehicle platoon is one of the innovations in the automated highway systems, which has the potential to reduce fuel consumption, alleviate traffic congestion and lighten the driver’s burden. How to control the vehicle effectively to ensure the stability of the queue is a challenge. Aiming to overcome the shortcomings of the platoon control method based on traditional sliding mode control, a non-singular terminal sliding mode control method optimized by the extreme learning machine is proposed in this paper. Firstly, the vehicle longitudinal dynamics are derived from the analysis of the forces acting on the vehicle in the longitudinal direction. A constant time headway policy is taken as the spacing policy. The modified non-singular terminal sliding mode control method has outstanding performance, simulation results demonstrate that the following vehicles can rapidly track the trajectory of the leading vehicle in the platoon with less spacing error and guarantee string stability. In this study, several experiments are set up to consider the disturbance and other uncertain practical factors. The performance of the proposed method is superior to the traditional sliding mode control method. Experimental results show that the proposed method can significantly reduce chattering and has good robustness under the circumstances of the disturbance.

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