Traction Adaptive Motion Planning and Control at the Limits of Handling

In this article, we address the problem of motion planning and control at the limits of handling, under locally varying traction conditions. We propose a novel solution method where traction variations over the prediction horizon are represented by time-varying tire force constraints, derived from a...

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Bibliographic Details
Published in:IEEE transactions on control systems technology 2022-09, Vol.30 (5), p.1888-1904
Main Authors: Svensson, Lars, Bujarbaruah, Monimoy, Karsolia, Arpit, Berger, Christian, Torngren, Martin
Format: Article
Language:English
Subjects:
Adaptive control
Algorithms
Automation & Control Systems
autonomous vehicles
collision avoidance
Computer and Information Sciences
Constraints
Data- och informationsvetenskap (Datateknik)
Electrical Engineering, Electronic Engineering, Information Engineering
Elektroteknik och elektronik
Engineering
Force
Friction
Heavy vehicles
Motion planning
optimization
optimization-based motion planning
Planning
predictive control
Roads
sampling-based
sampling-based motion planning
Time optimal control
Tire force
Tires
Traction
Trajectory
vehicle control
Vehicle dynamics
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Summary:In this article, we address the problem of motion planning and control at the limits of handling, under locally varying traction conditions. We propose a novel solution method where traction variations over the prediction horizon are represented by time-varying tire force constraints, derived from a predictive friction estimate. A constrained finite time optimal control problem (CFTOC) is solved in a receding horizon fashion, imposing these time-varying constraints. Furthermore, our method features an integrated sampling augmentation procedure that addresses the problems of infeasibility and sensitivity to local minima that arise at abrupt constraint alterations, for example, due to sudden friction changes. We validate the proposed algorithm on a Volvo FH16 heavy-duty vehicle, in a range of critical scenarios. Experimental results indicate that traction adaptive motion planning and control improves the vehicle's capacity to avoid accidents, both when adapting to low local traction, by ensuring dynamic feasibility of the planned motion, and when adapting to high local traction, by realizing high traction utilization.
ISSN:1063-6536
1558-0865
1558-0865
DOI:10.1109/TCST.2021.3129373