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CSME 2021/04
Volume 42 No.2
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187-196
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Real-Time Heuristic Motion Planning for Autonomous Vehicle Driving
Shyr-Long Jenga, Wei-Hua Chiengb and Yung-Chen Wangc
aDepartment of Mechanical Engineering Lunghwa University of Science and Technology, Taiwan, R.O.C.
bDepartment of Mechanical Engineering National Chiao Tung University, Taiwan, R.O.C
cElectric Propulsion and Control Department, Industrial Technology Research Institute, Taiwan, R.O.C
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Abstract:
This study presents a novel method that can be used to perform dynamic motion planning for a nonholonomic four-wheeler vehicle according to actual dynamic constraints to achieve a rapid response in the driving environment and obtain optimal vehicle performance. The proposed intuitive steering model employs inferential heuristics of driving behavior and relevant two-direction indices obtained from a driver’s-perspective view instead of traditional path planning to quickly and efficiently generate target paths without the requirement of complicated mathematical calculations. In the full model of a nonholonomic vehicle, a chassis with Ackerman steering geometry and double-wishbone suspension, lateral and longitudinal forces from contact strains, and forces due to the suspension system are considered to verify the motion of an autonomous vehicle from its starting position to its destination. Simulations of lane changes and U-turn maneuvers reveal that the proposed method provides a feasible trajectory in real time. The path planning method is effective for many driving scenarios, provides high dynamic performance, and maintains high maneuverability. This method is intuitive and extensible, thus allowing vehicles to navigate in real time and adapt to dynamic environmental conditions.
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Keywords: path planning, autonomous vehicle, heuristic
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*Corresponding author; e-mail:
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©
2021
CSME , ISSN 0257-9731
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