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Motion planning and control for autonomous vehicle collision avoidance systems using potential field-based parameter scheduling

Establishing an efficient and safe maneuver is an important part toward the successful development of autonomous vehicle collision avoidance systems in encountering the risk of imminent collision. A real driving environment deals with various dynamic conditions such as different vehicle speeds and n...

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Main Authors: Nurbaiti, Wahid, Hairi, Zamzuri, Noor Hafizah, Amer, Dwijotomo, Abdurahman, Sarah ‘Atifah, Saruchi
Format: Book Chapter
Language:English
English
Published: Elsevier 2024
Subjects:
T Technology (General)
TA Engineering (General). Civil engineering (General)
TJ Mechanical engineering and machinery
TK Electrical engineering. Electronics Nuclear engineering
TS Manufactures
Online Access:http://umpir.ump.edu.my/id/eprint/42552/1/Motion%20planning%20and%20control%20for%20autonomous%20vehicle%20collision.pdf
http://umpir.ump.edu.my/id/eprint/42552/2/Motion%20planning%20and%20control%20for%20autonomous%20vehicle%20collision%20avoidance%20systems%20using%20potential%20field-based%20parameter%20scheduling_ABS.pdf
http://umpir.ump.edu.my/id/eprint/42552/
https://doi.org/10.1016/B978-0-443-18644-8.00003-4
https://doi.org/10.1016/B978-0-443-18644-8.00003-4
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spelling my.ump.umpir.425522024-12-02T01:17:58Z http://umpir.ump.edu.my/id/eprint/42552/ Motion planning and control for autonomous vehicle collision avoidance systems using potential field-based parameter scheduling Nurbaiti, Wahid Hairi, Zamzuri Noor Hafizah, Amer Dwijotomo, Abdurahman Sarah ‘Atifah, Saruchi T Technology (General) TA Engineering (General). Civil engineering (General) TJ Mechanical engineering and machinery TK Electrical engineering. Electronics Nuclear engineering TS Manufactures Establishing an efficient and safe maneuver is an important part toward the successful development of autonomous vehicle collision avoidance systems in encountering the risk of imminent collision. A real driving environment deals with various dynamic conditions such as different vehicle speeds and numerous driving situations. Therefore, an adaptive strategy in a collision avoidance system is necessary in providing an appropriate vehicle motion and feasible trajectory of control for collision-free maneuver to guarantee safety. This study proposed a motion planning and control strategy for an autonomous vehicle collision avoidance system based on the potential field (PF) approach with a combination of the parameter scheduling technique. A particle swarm optimization algorithm is used to optimize the knowledge database information that is developed based on the perception of driver toward risk in the driving environment. This is the main component in developing the adaptive mechanism to adapt to numerous vehicle speeds and different obstacle positions during avoidance maneuver. The main contribution of this work is the improvement of a feasible vehicle motion for safe collision avoidance maneuver that is generated based on the reference lateral motion provided by the motion planner. Results demonstrate that the proposed motion planning and control strategy managed to decrease the lateral error with respect to the avoidance trajectory data and maximum reference lateral motion of up to 77% and 73% respectively compared to base-type PF. The proposed strategy is then validated on an actual steering wheel system through the hardware in loop test. Elsevier 2024-01-01 Book Chapter PeerReviewed pdf en http://umpir.ump.edu.my/id/eprint/42552/1/Motion%20planning%20and%20control%20for%20autonomous%20vehicle%20collision.pdf pdf en http://umpir.ump.edu.my/id/eprint/42552/2/Motion%20planning%20and%20control%20for%20autonomous%20vehicle%20collision%20avoidance%20systems%20using%20potential%20field-based%20parameter%20scheduling_ABS.pdf Nurbaiti, Wahid and Hairi, Zamzuri and Noor Hafizah, Amer and Dwijotomo, Abdurahman and Sarah ‘Atifah, Saruchi (2024) Motion planning and control for autonomous vehicle collision avoidance systems using potential field-based parameter scheduling. In: Machine Intelligence in Mechanical Engineering. Elsevier, Amsterdam, Netherlands, pp. 149-177. ISBN 978-044318644-8, 978-044318645-5 https://doi.org/10.1016/B978-0-443-18644-8.00003-4 https://doi.org/10.1016/B978-0-443-18644-8.00003-4
institution Universiti Malaysia Pahang Al-Sultan Abdullah
building UMPSA Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Malaysia Pahang Al-Sultan Abdullah
content_source UMPSA Institutional Repository
url_provider http://umpir.ump.edu.my/
language English
English
topic T Technology (General)
TA Engineering (General). Civil engineering (General)
TJ Mechanical engineering and machinery
TK Electrical engineering. Electronics Nuclear engineering
TS Manufactures
spellingShingle T Technology (General)
TA Engineering (General). Civil engineering (General)
TJ Mechanical engineering and machinery
TK Electrical engineering. Electronics Nuclear engineering
TS Manufactures
Nurbaiti, Wahid
Hairi, Zamzuri
Noor Hafizah, Amer
Dwijotomo, Abdurahman
Sarah ‘Atifah, Saruchi
Motion planning and control for autonomous vehicle collision avoidance systems using potential field-based parameter scheduling
description Establishing an efficient and safe maneuver is an important part toward the successful development of autonomous vehicle collision avoidance systems in encountering the risk of imminent collision. A real driving environment deals with various dynamic conditions such as different vehicle speeds and numerous driving situations. Therefore, an adaptive strategy in a collision avoidance system is necessary in providing an appropriate vehicle motion and feasible trajectory of control for collision-free maneuver to guarantee safety. This study proposed a motion planning and control strategy for an autonomous vehicle collision avoidance system based on the potential field (PF) approach with a combination of the parameter scheduling technique. A particle swarm optimization algorithm is used to optimize the knowledge database information that is developed based on the perception of driver toward risk in the driving environment. This is the main component in developing the adaptive mechanism to adapt to numerous vehicle speeds and different obstacle positions during avoidance maneuver. The main contribution of this work is the improvement of a feasible vehicle motion for safe collision avoidance maneuver that is generated based on the reference lateral motion provided by the motion planner. Results demonstrate that the proposed motion planning and control strategy managed to decrease the lateral error with respect to the avoidance trajectory data and maximum reference lateral motion of up to 77% and 73% respectively compared to base-type PF. The proposed strategy is then validated on an actual steering wheel system through the hardware in loop test.
format Book Chapter
author Nurbaiti, Wahid
Hairi, Zamzuri
Noor Hafizah, Amer
Dwijotomo, Abdurahman
Sarah ‘Atifah, Saruchi
author_facet Nurbaiti, Wahid
Hairi, Zamzuri
Noor Hafizah, Amer
Dwijotomo, Abdurahman
Sarah ‘Atifah, Saruchi
author_sort Nurbaiti, Wahid
title Motion planning and control for autonomous vehicle collision avoidance systems using potential field-based parameter scheduling
title_short Motion planning and control for autonomous vehicle collision avoidance systems using potential field-based parameter scheduling
title_full Motion planning and control for autonomous vehicle collision avoidance systems using potential field-based parameter scheduling
title_fullStr Motion planning and control for autonomous vehicle collision avoidance systems using potential field-based parameter scheduling
title_full_unstemmed Motion planning and control for autonomous vehicle collision avoidance systems using potential field-based parameter scheduling
title_sort motion planning and control for autonomous vehicle collision avoidance systems using potential field-based parameter scheduling
publisher Elsevier
publishDate 2024
url http://umpir.ump.edu.my/id/eprint/42552/1/Motion%20planning%20and%20control%20for%20autonomous%20vehicle%20collision.pdf
http://umpir.ump.edu.my/id/eprint/42552/2/Motion%20planning%20and%20control%20for%20autonomous%20vehicle%20collision%20avoidance%20systems%20using%20potential%20field-based%20parameter%20scheduling_ABS.pdf
http://umpir.ump.edu.my/id/eprint/42552/
https://doi.org/10.1016/B978-0-443-18644-8.00003-4
https://doi.org/10.1016/B978-0-443-18644-8.00003-4
_version_ 1822924762290061312
score 13.235362

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