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Robust Adaptive Control of Heterogeneous Vehicle Platoons in the Presence of Network Disconnections With a Novel String Stability Guarantee

Fernando Viadero‐Monasterio, Miguel Meléndez‐Useros, Manuel Jiménez‐Salas, Beatriz L. Boada

2025IEEE Transactions on Intelligent Vehicles13 citationsDOI

Abstract

The objective of this paper is to propose a reliable control solution that addresses the issue of communication disconnections in a heterogeneous vehicle platoon. For each vehicle in the platoon, predecessor-leader following (PLF) communication is selected. In the event of a communication failure, the vehicle transitions to the predecessor-following (PF) topology until communication with the leader is reestablished. To address this issue, a controller has been developed with the objective of adapting to the current communication topology on each vehicle. Event-triggering is implemented to reduce the amount of control orders given to the throttle/brake actuator pedals on each vehicle. Constant time spacing is selected for vehicle separation. A novel method is proposed to ensure string stability of the platoon during the controller design phase. Closed-loop stability of the proposed controlled vehicle platoon is guaranteed under Lyapunov criterion. Robustness against external disturbances and sensor measurement errors is guaranteed under <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\mathscr {H}_\infty$</tex-math></inline-formula> criterion. Simulations demonstrate that the proposed platoon control methodology can enhance road safety in the event of network disconnections. In the most unfavorable circumstances, the separation error is reduced by 40% in comparison to model predictive control techniques and by 73% in comparison to the intelligent driver model.

Topics & Concepts

String (physics)Stability (learning theory)Computer scienceControl theory (sociology)Control (management)Computer networkMathematicsArtificial intelligenceMachine learningMathematical physicsTraffic control and managementVehicular Ad Hoc Networks (VANETs)Vehicle Dynamics and Control Systems
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