Trajectory Tracking Control for Intelligent Vehicles Based on Cut-In Behavior Prediction
For intelligent vehicles, trajectory tracking control is of vital importance. However, due to the cut-in possibility of adjacent vehicles, trajectory planning of intelligent vehicles is challenging. Therefore, this paper proposes a trajectory tracking control method based on cut-in behavior predicti...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2021-11-01
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| Series: | Electronics |
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| Online Access: | https://www.mdpi.com/2079-9292/10/23/2932 |
| _version_ | 1797507909920227328 |
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| author | Chongpu Chen Jianhua Guo Chong Guo Xiaohan Li Chaoyi Chen |
| author_facet | Chongpu Chen Jianhua Guo Chong Guo Xiaohan Li Chaoyi Chen |
| author_sort | Chongpu Chen |
| collection | DOAJ |
| description | For intelligent vehicles, trajectory tracking control is of vital importance. However, due to the cut-in possibility of adjacent vehicles, trajectory planning of intelligent vehicles is challenging. Therefore, this paper proposes a trajectory tracking control method based on cut-in behavior prediction. A method of cut-in intention recognition is adopted to judge the possibility of adjacent vehicle and the driver preview model is used to predict the trajectory of the cut-in vehicle. The three driving scenarios are divided to manage trajectory planning under different cut-in behaviors. At the same time, the safety distance model is established as the basis for scene conversion. Taking the predicted trajectory of the cut-in vehicle as a reference, the model predictive control (MPC) method is used to plan and control the driving trajectory of the subject vehicle, so as to realize the coordinated control of the subject vehicle and the cut-in vehicle. Finally, the simulation shows that the subject vehicle can effectively recognize the cut-in intention of the adjacent vehicle and predict its trajectory. Facing with the cut-in vehicle, the subject vehicle can take appropriate control actions in advance to ensure the safety. Finally, a smoother coordinate control process is obtained between the subject vehicle and the cut-in vehicle. |
| first_indexed | 2024-03-10T04:55:09Z |
| format | Article |
| id | doaj.art-4f4876233c234545a41a3747b5bafa5b |
| institution | Directory Open Access Journal |
| issn | 2079-9292 |
| language | English |
| last_indexed | 2024-03-10T04:55:09Z |
| publishDate | 2021-11-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Electronics |
| spelling | doaj.art-4f4876233c234545a41a3747b5bafa5b2023-11-23T02:16:17ZengMDPI AGElectronics2079-92922021-11-011023293210.3390/electronics10232932Trajectory Tracking Control for Intelligent Vehicles Based on Cut-In Behavior PredictionChongpu Chen0Jianhua Guo1Chong Guo2Xiaohan Li3Chaoyi Chen4State Key Laboratory of Automotive Dynamic Simulation and Control, Jilin University, Changchun 130012, ChinaState Key Laboratory of Automotive Dynamic Simulation and Control, Jilin University, Changchun 130012, ChinaState Key Laboratory of Automotive Dynamic Simulation and Control, Jilin University, Changchun 130012, ChinaState Key Laboratory of Automotive Dynamic Simulation and Control, Jilin University, Changchun 130012, ChinaState Key Laboratory of Automotive Dynamic Simulation and Control, Jilin University, Changchun 130012, ChinaFor intelligent vehicles, trajectory tracking control is of vital importance. However, due to the cut-in possibility of adjacent vehicles, trajectory planning of intelligent vehicles is challenging. Therefore, this paper proposes a trajectory tracking control method based on cut-in behavior prediction. A method of cut-in intention recognition is adopted to judge the possibility of adjacent vehicle and the driver preview model is used to predict the trajectory of the cut-in vehicle. The three driving scenarios are divided to manage trajectory planning under different cut-in behaviors. At the same time, the safety distance model is established as the basis for scene conversion. Taking the predicted trajectory of the cut-in vehicle as a reference, the model predictive control (MPC) method is used to plan and control the driving trajectory of the subject vehicle, so as to realize the coordinated control of the subject vehicle and the cut-in vehicle. Finally, the simulation shows that the subject vehicle can effectively recognize the cut-in intention of the adjacent vehicle and predict its trajectory. Facing with the cut-in vehicle, the subject vehicle can take appropriate control actions in advance to ensure the safety. Finally, a smoother coordinate control process is obtained between the subject vehicle and the cut-in vehicle.https://www.mdpi.com/2079-9292/10/23/2932trajectory tracking controlcut-in behaviorsafety distance modelmodel predictive control |
| spellingShingle | Chongpu Chen Jianhua Guo Chong Guo Xiaohan Li Chaoyi Chen Trajectory Tracking Control for Intelligent Vehicles Based on Cut-In Behavior Prediction Electronics trajectory tracking control cut-in behavior safety distance model model predictive control |
| title | Trajectory Tracking Control for Intelligent Vehicles Based on Cut-In Behavior Prediction |
| title_full | Trajectory Tracking Control for Intelligent Vehicles Based on Cut-In Behavior Prediction |
| title_fullStr | Trajectory Tracking Control for Intelligent Vehicles Based on Cut-In Behavior Prediction |
| title_full_unstemmed | Trajectory Tracking Control for Intelligent Vehicles Based on Cut-In Behavior Prediction |
| title_short | Trajectory Tracking Control for Intelligent Vehicles Based on Cut-In Behavior Prediction |
| title_sort | trajectory tracking control for intelligent vehicles based on cut in behavior prediction |
| topic | trajectory tracking control cut-in behavior safety distance model model predictive control |
| url | https://www.mdpi.com/2079-9292/10/23/2932 |
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