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Safe Adaptive Cruise Control with Road Grade Preview and V2V Communication

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arxiv 1810.09000 v1 pith:ZUL4G43W submitted 2018-10-21 cs.SY cs.ROcs.SY

Roya Firoozi , Shima Nazari , Jacopo Guanetti , Ryan O'Gorman , Francesco Borrelli This is my paper · ORCID
classification cs.SYcs.RO
keywords controlcontrollergradeproposedroadsafeadaptivecruise
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We present the design of a safe Adaptive Cruise Control (ACC) which uses road grade and lead vehicle motion preview. The ACC controller is designed by using a Model Predictive Control (MPC) framework to optimize comfort, safety, energy-efficiency and speed tracking accuracy. Safety is achieved by computing a robust invariant terminal set. The paper presents a novel approach to compute such set which is less conservative than existing methods. The proposed controller ensures safe inter-vehicle spacing at all times despite changes in the road grade and uncertainty in the predicted motion of the lead vehicle. Simulation results compare the proposed controller with a controller that does not incorporate prior grade knowledge on two scenarios including car-following and autonomous intersection crossing. The results demonstrate the effectiveness of the proposed control algorithm.

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Cited by 1 Pith paper

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. Learning Model Predictive Control for Connected Autonomous Vehicles

    math.OC 2019-08 reject novelty 4.0 of 10

    A short-range learning MPC for vehicle platooning is proposed that incorporates wireless channel predictions, but its core equations contain algebraic and logical errors and the optimality claim is unproven.

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