Predictive Force-Centric Emergency Collision Avoidance
(2021) In Journal of Dynamic Systems, Measurement, and Control, ASME 143(8). p.081005-081005- Abstract
- A controller for critical vehicle maneuvering is proposed that avoids obstacles and keeps the vehicle on the road while achieving heavy braking. It operates at the limit of friction and is structured in two main steps: a motion-planning step based on receding-horizon planning to obtain acceleration-vector references, and a low-level controller for following these acceleration references and transforming them into actuator commands. The controller is evaluated in a number of challenging scenarios and results in a well behaved vehicle with respect to, e.g., the steering angle, the body slip, and the path. It is also demonstrated that the controller successfully balances braking and avoidance such that it really takes advantage of the braking... (More)
- A controller for critical vehicle maneuvering is proposed that avoids obstacles and keeps the vehicle on the road while achieving heavy braking. It operates at the limit of friction and is structured in two main steps: a motion-planning step based on receding-horizon planning to obtain acceleration-vector references, and a low-level controller for following these acceleration references and transforming them into actuator commands. The controller is evaluated in a number of challenging scenarios and results in a well behaved vehicle with respect to, e.g., the steering angle, the body slip, and the path. It is also demonstrated that the controller successfully balances braking and avoidance such that it really takes advantage of the braking possibilities. Specifically, for a moving obstacle, it makes use of a widening gap to perform more braking, which is a clear advantage of the online replanning capability if the obstacle should be a moving human or animal. Finally, real-time capabilities are demonstrated. In conclusion, the controller performs well, both from a functional perspective and from a real-time perspective. (Less)
Please use this url to cite or link to this publication:
https://lup.lub.lu.se/record/fe4254a0-adb1-408e-9c8a-e78f245ec66a
- author
- Fors, Victor ; Anistratov, Pavel ; Olofsson, Björn LU and Nielsen, Lars
- organization
- publishing date
- 2021-08-01
- type
- Contribution to journal
- publication status
- published
- subject
- in
- Journal of Dynamic Systems, Measurement, and Control, ASME
- volume
- 143
- issue
- 8
- article number
- DS-20-1471
- pages
- 12 pages
- publisher
- American Society Of Mechanical Engineers (ASME)
- external identifiers
-
- scopus:85107661660
- ISSN
- 0022-0434
- DOI
- 10.1115/1.4050403
- project
- ELLIIT LU P11: Online Optimization and Control towards Autonomous Vehicle Maneuvering
- RobotLab LTH
- language
- English
- LU publication?
- yes
- id
- fe4254a0-adb1-408e-9c8a-e78f245ec66a
- date added to LUP
- 2021-05-06 21:07:11
- date last changed
- 2023-04-24 21:08:25
@article{fe4254a0-adb1-408e-9c8a-e78f245ec66a,
abstract = {{A controller for critical vehicle maneuvering is proposed that avoids obstacles and keeps the vehicle on the road while achieving heavy braking. It operates at the limit of friction and is structured in two main steps: a motion-planning step based on receding-horizon planning to obtain acceleration-vector references, and a low-level controller for following these acceleration references and transforming them into actuator commands. The controller is evaluated in a number of challenging scenarios and results in a well behaved vehicle with respect to, e.g., the steering angle, the body slip, and the path. It is also demonstrated that the controller successfully balances braking and avoidance such that it really takes advantage of the braking possibilities. Specifically, for a moving obstacle, it makes use of a widening gap to perform more braking, which is a clear advantage of the online replanning capability if the obstacle should be a moving human or animal. Finally, real-time capabilities are demonstrated. In conclusion, the controller performs well, both from a functional perspective and from a real-time perspective.}},
author = {{Fors, Victor and Anistratov, Pavel and Olofsson, Björn and Nielsen, Lars}},
issn = {{0022-0434}},
language = {{eng}},
month = {{08}},
number = {{8}},
pages = {{081005--081005}},
publisher = {{American Society Of Mechanical Engineers (ASME)}},
series = {{Journal of Dynamic Systems, Measurement, and Control, ASME}},
title = {{Predictive Force-Centric Emergency Collision Avoidance}},
url = {{http://dx.doi.org/10.1115/1.4050403}},
doi = {{10.1115/1.4050403}},
volume = {{143}},
year = {{2021}},
}