Model Predictive Contouring Control for Vehicle Obstacle Avoidance at the Limit of Handling Using Torque Vectoring∗

Alberto Bertipaglia*, Davide Tavernini, Umberto Montanaro, Mohsen Alirezaei, Riender Happee, Aldo Sorniotti, Barys Shyrokau

*Corresponding author for this work

Research output: Chapter in Book/Conference proceedings/Edited volumeConference contributionScientificpeer-review

Abstract

This paper presents an original approach to vehicle obstacle avoidance. It involves the development of a nonlinear Model Predictive Contouring Control, which uses torque vectoring to stabilise and drive the vehicle in evasive manoeuvres at the limit of handling. The proposed algorithm combines motion planning, path tracking and vehicle stability objectives, prioritising collision avoidance in emergencies. The controller's prediction model is a nonlinear double-track vehicle model based on an extended Fiala tyre to capture the nonlinear coupled longitudinal and lateral dynamics. The controller computes the optimal steering angle and the longitudinal forces per each of the four wheels to minimise tracking error in safe situations and maximise the vehicle-to-obstacle distance in emergencies. Thanks to the optimisation of the longitudinal tyre forces, the proposed controller can produce an extra yaw moment, increasing the vehicle's lateral agility to avoid obstacles while keeping the vehicle stable. The optimal forces are constrained in the tyre friction circle not to exceed the tyres and vehicle capabilities. In a high-fidelity simulation environment, we demonstrate the benefits of torque vectoring, showing that our proposed approach is capable of successfully avoiding obstacles and keeping the vehicle stable while driving a double-lane change manoeuvre, in comparison to baselines lacking torque vectoring or collision avoidance prioritisation.

Original languageEnglish
Title of host publicationProceedings of the IEEE International Conference on Advanced Intelligent Mechatronics, AIM 2024
PublisherIEEE
Pages1468-1475
Number of pages8
ISBN (Electronic)979-8-3503-5536-9
DOIs
Publication statusPublished - 2024
Event2024 IEEE/ASME International Conference on Advanced Intelligent Mechatronics, AIM 2024 - Boston, United States
Duration: 15 Jul 202419 Jul 2024

Publication series

NameIEEE/ASME International Conference on Advanced Intelligent Mechatronics, AIM
ISSN (Print)2159-6247
ISSN (Electronic)2159-6255

Conference

Conference2024 IEEE/ASME International Conference on Advanced Intelligent Mechatronics, AIM 2024
Country/TerritoryUnited States
CityBoston
Period15/07/2419/07/24

Bibliographical note

Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care
Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.

Fingerprint

Dive into the research topics of 'Model Predictive Contouring Control for Vehicle Obstacle Avoidance at the Limit of Handling Using Torque Vectoring∗'. Together they form a unique fingerprint.

Cite this