Driving and steering collision avoidance system of autonomous vehicle with model predictive control based on non-convex optimization
A planar motion control system is proposed for autonomous vehicles not only to follow the lanes, but also to avoid collisions by braking, accelerating, and steering. The supervisor is designed first to determine the desired speed and the risk of the maneuvering due to road boundaries and obstacles. In order to allow lane changes on multi-lane roads, the model predictive controller is formulated based on the probabilistic non-convex optimization. The micro-genetic algorithm is applied to calculate the target speed and target steering angle in real time. A software-in-the-loop unit is constructed with the Rapid Control Prototyping device in the vehicle communication environment. The performance of the proposed system is verified for various collision avoidance scenarios and the simulation results demonstrate the safe and effective driving performance of autonomous vehicles with no collision on multi-lane road.
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Availability:
- Find a library where document is available. Order URL: http://worldcat.org/issn/16878132
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Supplemental Notes:
- © 2021 Yuho Song and Kunsoo Huh.
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Authors:
- Song, Yuho
- Huh, Kunsoo
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0000-0002-7179-7841
- Publication Date: 2021-6
Language
- English
Media Info
- Media Type: Digital/other
- Features: Appendices; Figures; References;
- Pagination: 14p
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Serial:
- Advances in Mechanical Engineering
- Volume: 13
- Issue Number: 6
- Publisher: Sage Publications, Incorporated
- ISSN: 1687-8132
- EISSN: 1687-8140
- Serial URL: https://journals.sagepub.com/home/ade
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Publication flags:
Open Access (libre)
Subject/Index Terms
- TRT Terms: Advanced vehicle control systems; Autonomous vehicles; Crash avoidance systems; Lane changing; Vehicle design
- Subject Areas: Design; Highways; Safety and Human Factors; Vehicles and Equipment;
Filing Info
- Accession Number: 01780689
- Record Type: Publication
- Files: TRIS
- Created Date: Aug 30 2021 2:46PM