Lateral Vehicle Trajectory Planning Using a Model Predictive Control Scheme for an Automated Perpendicular Parking System
- Authors
- Kim, Daejung; Jeong, Yongwoo; Chung, Chung Choo
- Issue Date
- Feb-2023
- Publisher
- Institute of Electrical and Electronics Engineers
- Keywords
- Kinematics; Path planning; Planning; Trajectory planning; Approximation algorithms; Trajectory; Predictive models; Automated perpendicular parking system; constrained optimization; model predictive control (MPC); trajectory planning; vehicle lateral control
- Citation
- IEEE Transactions on Industrial Electronics, v.70, no.2, pp 1820 - 1829
- Pages
- 10
- Indexed
- SCIE
SCOPUS
- Journal Title
- IEEE Transactions on Industrial Electronics
- Volume
- 70
- Number
- 2
- Start Page
- 1820
- End Page
- 1829
- URI
- https://scholarworks.bwise.kr/hanyang/handle/2021.sw.hanyang/185417
- DOI
- 10.1109/TIE.2022.3163567
- ISSN
- 0278-0046
1557-9948
- Abstract
- This paper proposes a lateral vehicle trajectory planning and control algorithm using a model predictive control (MPC) scheme for an automated perpendicular parking system. Previous work showed that approximated clothoid-based local path planning using a virtual towing distance provides low computational time and the stability of lateral vehicle motion in a parking system. However, this approach cannot function in certain parking situations and may cause undesirable steering maneuvers due to state-dependent planning. We present a new approximated clothoid path based on lateral vehicle kinematics to cope with these problems. Using the proposed kinematic model, we formulate an MPC problem for path planning. Then, the proposed lateral vehicle trajectory planning becomes an MPC problem under constraints. Besides, we show that lateral vehicle motion for vertical parking can be implemented using simple kinematic lateral motion control. Experimental results show that the vehicle with the proposed method moves smoothly and completes the given parking mission under constraints, even under tight parking space conditions.
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