Research on the trajectory tracking of a curved road in an active lane change scenario based on model predictive control algorithm
In this paper, a control method for trajectory planning and tracking of an intelligent vehicle is proposed. In terms of trajectory planning, a trajectory planning method for curved lane changes is designed based on conventional lane change trajectory planning and considering the adaptive correction of road curvature. In addition, curve trajectory tracking control strategy based on model predictive control is designed. Model predictive control is suitable for multi-input and multi-output nonlinear models, and it has the advantage of considering model constraints. This type of control makes the model output more in line with vehicle dynamics characteristics and improves the trajectory tracking accuracy. Finally, the simulation shows that the method proposed in this paper can generate a reasonable curved lane-changing trajectory, and under the consideration of the vehicle dynamics constraints, the MPC algorithm is used to effectively follow the expected trajectory, so that the vehicle can change lanes smoothly.
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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:
- © The Author(s) 2023.
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Authors:
- Wang, Wei
- 0009-0002-4426-5169
- Qu, Fufan
- Guo, Chong
- Li, Wenbo
- Publication Date: 2023-9
Language
- English
Media Info
- Media Type: Web
- Features: Figures; References; Tables;
- Pagination: 20p
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Serial:
- Advances in Mechanical Engineering
- Volume: 15
- Issue Number: 9
- 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: Algorithms; Highway curves; Intelligent vehicles; Lane changing; Predictive models; Vehicle trajectories
- Subject Areas: Highways; Vehicles and Equipment;
Filing Info
- Accession Number: 01910146
- Record Type: Publication
- Files: TRIS
- Created Date: Feb 27 2024 4:03PM