Autonomous Wary Collision Avoidance
(2021) In IEEE Transactions on Intelligent Vehicles 6(2). p.353-365- Abstract
- Handling of critical situations is an important part in the architecture of an autonomous vehicle. A controller for autonomous collision avoidance is developed based on a wary strategy that assumes the least tireroad friction for which the maneuver is still feasible. Should the friction be greater, the controller makes use of this and performs better. The controller uses an acceleration-vector reference obtained from optimal control of a friction-limited particle, whose applicability is verified by using numerical optimization on a full vehicle model. By employing an analytical tire model of the tireroad friction limit, to determine slip references for steering and body-slip control, the result is a controller where the computation of its... (More)
- Handling of critical situations is an important part in the architecture of an autonomous vehicle. A controller for autonomous collision avoidance is developed based on a wary strategy that assumes the least tireroad friction for which the maneuver is still feasible. Should the friction be greater, the controller makes use of this and performs better. The controller uses an acceleration-vector reference obtained from optimal control of a friction-limited particle, whose applicability is verified by using numerical optimization on a full vehicle model. By employing an analytical tire model of the tireroad friction limit, to determine slip references for steering and body-slip control, the result is a controller where the computation of its output is explicit and independent of the actual tire-road friction. When evaluated in real-time on a high-fidelity simulation model, the developed controller performs close to that achieved by offline numerical optimization. (Less)
Please use this url to cite or link to this publication:
https://lup.lub.lu.se/record/4bdf24ea-e406-487c-a3a0-2c04697fa182
- author
- Fors, Victor ; Olofsson, Björn LU and Nielsen, Lars
- organization
- publishing date
- 2021-06-01
- type
- Contribution to journal
- publication status
- published
- subject
- in
- IEEE Transactions on Intelligent Vehicles
- volume
- 6
- issue
- 2
- pages
- 13 pages
- publisher
- IEEE - Institute of Electrical and Electronics Engineers Inc.
- external identifiers
-
- scopus:85092917025
- ISSN
- 2379-8858
- DOI
- 10.1109/TIV.2020.3029853
- project
- ELLIIT LU P11: Online Optimization and Control towards Autonomous Vehicle Maneuvering
- RobotLab LTH
- language
- English
- LU publication?
- yes
- id
- 4bdf24ea-e406-487c-a3a0-2c04697fa182
- date added to LUP
- 2020-12-27 18:04:56
- date last changed
- 2023-04-24 21:08:07
@article{4bdf24ea-e406-487c-a3a0-2c04697fa182,
abstract = {{Handling of critical situations is an important part in the architecture of an autonomous vehicle. A controller for autonomous collision avoidance is developed based on a wary strategy that assumes the least tireroad friction for which the maneuver is still feasible. Should the friction be greater, the controller makes use of this and performs better. The controller uses an acceleration-vector reference obtained from optimal control of a friction-limited particle, whose applicability is verified by using numerical optimization on a full vehicle model. By employing an analytical tire model of the tireroad friction limit, to determine slip references for steering and body-slip control, the result is a controller where the computation of its output is explicit and independent of the actual tire-road friction. When evaluated in real-time on a high-fidelity simulation model, the developed controller performs close to that achieved by offline numerical optimization.}},
author = {{Fors, Victor and Olofsson, Björn and Nielsen, Lars}},
issn = {{2379-8858}},
language = {{eng}},
month = {{06}},
number = {{2}},
pages = {{353--365}},
publisher = {{IEEE - Institute of Electrical and Electronics Engineers Inc.}},
series = {{IEEE Transactions on Intelligent Vehicles}},
title = {{Autonomous Wary Collision Avoidance}},
url = {{http://dx.doi.org/10.1109/TIV.2020.3029853}},
doi = {{10.1109/TIV.2020.3029853}},
volume = {{6}},
year = {{2021}},
}