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Conference papers

Reference-Free Human-Automation Shared Control for Obstacle Avoidance of Automated Vehicles

Abstract : In this paper, a novel reference-free shared control system is designed for obstacle avoidance for automated vehicles. Rather than using a reference path to guide the driver, the proposed framework constrains the vehicle's status to guarantee the safety without scarifying the driver's freedom. The constrained Delaunay triangle method is introduced to identify the vehicle's position constraints and the constraints of obstacle avoidance, vehicle stability and physical limitations are investigated and unified. A nonlinear predictive control problem, which is constructed accounting nonlinear vehicle dynamics and given driver actions, is designed to optimize the steering and braking actions needed to keep the vehicle safe. The automation is supposed to correct the driver's steering or braking actions to prevent constraint violation and losing the control of vehicle. The simulation results show that the automation can assist the driver to avoid obstacles and guarantee the vehicle's stability with minimal control intervention.
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Contributor : Mylène Delrue Connect in order to contact the contributor
Submitted on : Wednesday, October 27, 2021 - 9:54:32 AM
Last modification on : Wednesday, November 3, 2021 - 10:01:52 AM




Chao Huang, Peng Hang, Jingda Wu, Tran Anh-Tu Nguyen, Chen Lv. Reference-Free Human-Automation Shared Control for Obstacle Avoidance of Automated Vehicles. 2020 IEEE International Conference on Systems, Man, and Cybernetics (SMC), Oct 2020, Toronto, Canada. pp.4398-4403, ⟨10.1109/SMC42975.2020.9283287⟩. ⟨hal-03405164⟩



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