A Novel Path Planning Algorithm for Truck Platooning Using V2V Communication
In truck platooning, the leading vehicle is driven manually, and the following vehicles run by autonomous driving, with the short inter-vehicle distance between trucks. To successfully perform platooning in various situations, each truck must maintain dynamic stability, and furthermore, the whole sy...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2020-12-01
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| Series: | Sensors |
| Subjects: | |
| Online Access: | https://www.mdpi.com/1424-8220/20/24/7022 |
| _version_ | 1797545390836285440 |
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| author | Yongki Lee Taewon Ahn Chanhwa Lee Sangjun Kim Kihong Park |
| author_facet | Yongki Lee Taewon Ahn Chanhwa Lee Sangjun Kim Kihong Park |
| author_sort | Yongki Lee |
| collection | DOAJ |
| description | In truck platooning, the leading vehicle is driven manually, and the following vehicles run by autonomous driving, with the short inter-vehicle distance between trucks. To successfully perform platooning in various situations, each truck must maintain dynamic stability, and furthermore, the whole system must maintain string stability. Due to the short front-view range, however, the following vehicles’ path planning capabilities become significantly impaired. In addition, in platooning with articulated cargo trucks, the off-tracking phenomenon occurring on a curved road makes it hard for the following vehicle to track the trajectory of the preceding truck. In addition, without knowledge of the global coordinate system, it is difficult to correlate the local coordinate systems that each truck relies on for sensing environment and dynamic signals. In this paper, in order to solve these problems, a path planning algorithm for platooning of articulated cargo trucks has been developed. Using the Kalman filter, V2V (Vehicle-to-Vehicle) communication, and a novel update-and-conversion method, each following vehicle can accurately compute the trajectory of the leading vehicle’s front part for using it as a target path. The path planning algorithm of this paper was validated by simulations on severe driving scenarios and by tests on an actual road. The results demonstrated that the algorithm could provide lateral string stability and robustness for truck platooning. |
| first_indexed | 2024-03-10T14:14:53Z |
| format | Article |
| id | doaj.art-b3fe3f1c38794ab4ae7e68d75a8a4050 |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-03-10T14:14:53Z |
| publishDate | 2020-12-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-b3fe3f1c38794ab4ae7e68d75a8a40502023-11-20T23:53:37ZengMDPI AGSensors1424-82202020-12-012024702210.3390/s20247022A Novel Path Planning Algorithm for Truck Platooning Using V2V CommunicationYongki Lee0Taewon Ahn1Chanhwa Lee2Sangjun Kim3Kihong Park4Graduate School of Automotive Engineering, Kookmin University, Seoul 02707, KoreaGraduate School of Automotive Engineering, Kookmin University, Seoul 02707, KoreaResearch and Development Division, Hyundai Motor Company, Gyeonggi-do 18280, KoreaResearch and Development Division, Hyundai Motor Company, Gyeonggi-do 18280, KoreaGraduate School of Automotive Engineering, Kookmin University, Seoul 02707, KoreaIn truck platooning, the leading vehicle is driven manually, and the following vehicles run by autonomous driving, with the short inter-vehicle distance between trucks. To successfully perform platooning in various situations, each truck must maintain dynamic stability, and furthermore, the whole system must maintain string stability. Due to the short front-view range, however, the following vehicles’ path planning capabilities become significantly impaired. In addition, in platooning with articulated cargo trucks, the off-tracking phenomenon occurring on a curved road makes it hard for the following vehicle to track the trajectory of the preceding truck. In addition, without knowledge of the global coordinate system, it is difficult to correlate the local coordinate systems that each truck relies on for sensing environment and dynamic signals. In this paper, in order to solve these problems, a path planning algorithm for platooning of articulated cargo trucks has been developed. Using the Kalman filter, V2V (Vehicle-to-Vehicle) communication, and a novel update-and-conversion method, each following vehicle can accurately compute the trajectory of the leading vehicle’s front part for using it as a target path. The path planning algorithm of this paper was validated by simulations on severe driving scenarios and by tests on an actual road. The results demonstrated that the algorithm could provide lateral string stability and robustness for truck platooning.https://www.mdpi.com/1424-8220/20/24/7022TROOPtruck platooningpath planningkalman filterV2V communicationstring stability |
| spellingShingle | Yongki Lee Taewon Ahn Chanhwa Lee Sangjun Kim Kihong Park A Novel Path Planning Algorithm for Truck Platooning Using V2V Communication Sensors TROOP truck platooning path planning kalman filter V2V communication string stability |
| title | A Novel Path Planning Algorithm for Truck Platooning Using V2V Communication |
| title_full | A Novel Path Planning Algorithm for Truck Platooning Using V2V Communication |
| title_fullStr | A Novel Path Planning Algorithm for Truck Platooning Using V2V Communication |
| title_full_unstemmed | A Novel Path Planning Algorithm for Truck Platooning Using V2V Communication |
| title_short | A Novel Path Planning Algorithm for Truck Platooning Using V2V Communication |
| title_sort | novel path planning algorithm for truck platooning using v2v communication |
| topic | TROOP truck platooning path planning kalman filter V2V communication string stability |
| url | https://www.mdpi.com/1424-8220/20/24/7022 |
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