Modeling and Optimization of Connected and Automated Vehicle Platooning Cooperative Control with Measurement Errors
This paper presents a cooperative control method for connected and automated vehicle (CAV) platooning, thus specifically addressing the challenge of sensor measurement errors that can disrupt the stability of the CAV platoon. Initially, the state-space equation of the CAV platooning system was formu...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2023-11-01
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| Series: | Sensors |
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| Online Access: | https://www.mdpi.com/1424-8220/23/21/9006 |
| _version_ | 1797631278822981632 |
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| author | Weiming Luo Xu Li Jinchao Hu Weiming Hu |
| author_facet | Weiming Luo Xu Li Jinchao Hu Weiming Hu |
| author_sort | Weiming Luo |
| collection | DOAJ |
| description | This paper presents a cooperative control method for connected and automated vehicle (CAV) platooning, thus specifically addressing the challenge of sensor measurement errors that can disrupt the stability of the CAV platoon. Initially, the state-space equation of the CAV platooning system was formulated, thereby taking into account the measurement error of onboard sensors. The superposition effect of the sensor measurement errors was statistically analyzed, thereby elucidating its impact on cooperative control in CAV platooning. Subsequently, the application of a Kalman filter was proposed as a means to mitigate the adverse effects of measurement errors. Additionally, the CAV formation control problem was transformed into an optimal control decision problem by introducing an optimal control decision strategy that does not impose pure state variable inequality constraints. The proposed method was evaluated through simulation experiments utilizing real vehicle trajectory data from the Next Generation Simulation (NGSIM). The results demonstrate that the method presented in this study effectively mitigates the influence of measurement errors, thereby enabling coordinated vehicle-following behavior, achieving smooth acceleration and deceleration throughout the platoon, and eliminating traffic oscillations. Overall, the proposed method ensures the stability and comfort of the CAV platooning formation. |
| first_indexed | 2024-03-11T11:20:36Z |
| format | Article |
| id | doaj.art-9bd90438c9cf470d99201a0b03119bfe |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-03-11T11:20:36Z |
| publishDate | 2023-11-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-9bd90438c9cf470d99201a0b03119bfe2023-11-10T15:13:09ZengMDPI AGSensors1424-82202023-11-012321900610.3390/s23219006Modeling and Optimization of Connected and Automated Vehicle Platooning Cooperative Control with Measurement ErrorsWeiming Luo0Xu Li1Jinchao Hu2Weiming Hu3School of Instrument Science and Engineering, Southeast University, Nanjing 210096, ChinaSchool of Instrument Science and Engineering, Southeast University, Nanjing 210096, ChinaSchool of Instrument Science and Engineering, Southeast University, Nanjing 210096, ChinaSchool of Instrument Science and Engineering, Southeast University, Nanjing 210096, ChinaThis paper presents a cooperative control method for connected and automated vehicle (CAV) platooning, thus specifically addressing the challenge of sensor measurement errors that can disrupt the stability of the CAV platoon. Initially, the state-space equation of the CAV platooning system was formulated, thereby taking into account the measurement error of onboard sensors. The superposition effect of the sensor measurement errors was statistically analyzed, thereby elucidating its impact on cooperative control in CAV platooning. Subsequently, the application of a Kalman filter was proposed as a means to mitigate the adverse effects of measurement errors. Additionally, the CAV formation control problem was transformed into an optimal control decision problem by introducing an optimal control decision strategy that does not impose pure state variable inequality constraints. The proposed method was evaluated through simulation experiments utilizing real vehicle trajectory data from the Next Generation Simulation (NGSIM). The results demonstrate that the method presented in this study effectively mitigates the influence of measurement errors, thereby enabling coordinated vehicle-following behavior, achieving smooth acceleration and deceleration throughout the platoon, and eliminating traffic oscillations. Overall, the proposed method ensures the stability and comfort of the CAV platooning formation.https://www.mdpi.com/1424-8220/23/21/9006intelligent transportationconnected and automated vehicle (CAV) platoonsensor measurement errorcooperative control |
| spellingShingle | Weiming Luo Xu Li Jinchao Hu Weiming Hu Modeling and Optimization of Connected and Automated Vehicle Platooning Cooperative Control with Measurement Errors Sensors intelligent transportation connected and automated vehicle (CAV) platoon sensor measurement error cooperative control |
| title | Modeling and Optimization of Connected and Automated Vehicle Platooning Cooperative Control with Measurement Errors |
| title_full | Modeling and Optimization of Connected and Automated Vehicle Platooning Cooperative Control with Measurement Errors |
| title_fullStr | Modeling and Optimization of Connected and Automated Vehicle Platooning Cooperative Control with Measurement Errors |
| title_full_unstemmed | Modeling and Optimization of Connected and Automated Vehicle Platooning Cooperative Control with Measurement Errors |
| title_short | Modeling and Optimization of Connected and Automated Vehicle Platooning Cooperative Control with Measurement Errors |
| title_sort | modeling and optimization of connected and automated vehicle platooning cooperative control with measurement errors |
| topic | intelligent transportation connected and automated vehicle (CAV) platoon sensor measurement error cooperative control |
| url | https://www.mdpi.com/1424-8220/23/21/9006 |
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