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

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 Inc., pp. 149-177. ISBN 9780443186448

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Abstract

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.

Item Type:	Book Chapter
Additional Information:	Indexed by Scopus
Uncontrolled Keywords:	adaptive system; ADAS; collision avoidance; Motion planning; parameter scheduling; potential field
Subjects:	T Technology > TJ Mechanical engineering and machinery T Technology > TS Manufactures
Faculty/Division:	Faculty of Manufacturing and Mechatronic Engineering Technology
Depositing User:	Miss Amelia Binti Hasan
Date Deposited:	11 Sep 2024 07:43
Last Modified:	11 Sep 2024 07:43
URI:	http://umpir.ump.edu.my/id/eprint/42575
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