Research on Truck Lane Management Strategies for Platooning Speed Optimization and Control on Multi-Lane Highways
Automated truck platooning has become an increasingly popular research subject, and its applicability to highways is considered one of the earliest possible landing scenarios for automated driving. However, there is a lack of research regarding the combination of truck platooning technology and truc...
| Published in: | Applied Sciences |
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| Main Authors: | , , , |
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2023-03-01
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| Subjects: | |
| Online Access: | https://www.mdpi.com/2076-3417/13/6/4072 |
| _version_ | 1849886955982028800 |
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| author | Yikang Rui Shu Wang Renfei Wu Zhe Shen |
| author_facet | Yikang Rui Shu Wang Renfei Wu Zhe Shen |
| author_sort | Yikang Rui |
| collection | DOAJ |
| container_title | Applied Sciences |
| description | Automated truck platooning has become an increasingly popular research subject, and its applicability to highways is considered one of the earliest possible landing scenarios for automated driving. However, there is a lack of research regarding the combination of truck platooning technology and truck lane management strategy on multilane highways in the environment of a cooperative vehicle–infrastructure system (CVIS). For highway weaving sections under the CVIS environment, this paper proposes a truck platooning optimal speed control model based on multi-objective optimization. Through a combination of model predictive control and the cell transmission model, this approach considers the bottleneck cell traffic flow, overall vehicle travel time, and truck platooning fuel consumption as objectives. By conducting experiments on a mixed traffic flow simulation platform, the multi-lane management strategies and optimal speed control effect were evaluated through different scenarios. This study also determined the appropriate proportion of truck platooning for an exclusive lane and to increase truck lanes, thus providing effective lane management decision support for highway managers. |
| format | Article |
| id | doaj-art-e66dfc697f1d479d9db9c6cd9fa2dff1 |
| institution | Directory of Open Access Journals |
| issn | 2076-3417 |
| language | English |
| publishDate | 2023-03-01 |
| publisher | MDPI AG |
| record_format | Article |
| spelling | doaj-art-e66dfc697f1d479d9db9c6cd9fa2dff12025-08-20T01:06:18ZengMDPI AGApplied Sciences2076-34172023-03-01136407210.3390/app13064072Research on Truck Lane Management Strategies for Platooning Speed Optimization and Control on Multi-Lane HighwaysYikang Rui0Shu Wang1Renfei Wu2Zhe Shen3School of Transportation, Southeast University, Nanjing 211189, ChinaPlanning Research Center, Jiangsu Provincial Department of Transportation, Nanjing 210000, ChinaSchool of Transportation, Southeast University, Nanjing 211189, ChinaSchool of Transportation, Southeast University, Nanjing 211189, ChinaAutomated truck platooning has become an increasingly popular research subject, and its applicability to highways is considered one of the earliest possible landing scenarios for automated driving. However, there is a lack of research regarding the combination of truck platooning technology and truck lane management strategy on multilane highways in the environment of a cooperative vehicle–infrastructure system (CVIS). For highway weaving sections under the CVIS environment, this paper proposes a truck platooning optimal speed control model based on multi-objective optimization. Through a combination of model predictive control and the cell transmission model, this approach considers the bottleneck cell traffic flow, overall vehicle travel time, and truck platooning fuel consumption as objectives. By conducting experiments on a mixed traffic flow simulation platform, the multi-lane management strategies and optimal speed control effect were evaluated through different scenarios. This study also determined the appropriate proportion of truck platooning for an exclusive lane and to increase truck lanes, thus providing effective lane management decision support for highway managers.https://www.mdpi.com/2076-3417/13/6/4072truck platooningtruck lane management strategymulti-objective optimizationspeed optimization and control |
| spellingShingle | Yikang Rui Shu Wang Renfei Wu Zhe Shen Research on Truck Lane Management Strategies for Platooning Speed Optimization and Control on Multi-Lane Highways truck platooning truck lane management strategy multi-objective optimization speed optimization and control |
| title | Research on Truck Lane Management Strategies for Platooning Speed Optimization and Control on Multi-Lane Highways |
| title_full | Research on Truck Lane Management Strategies for Platooning Speed Optimization and Control on Multi-Lane Highways |
| title_fullStr | Research on Truck Lane Management Strategies for Platooning Speed Optimization and Control on Multi-Lane Highways |
| title_full_unstemmed | Research on Truck Lane Management Strategies for Platooning Speed Optimization and Control on Multi-Lane Highways |
| title_short | Research on Truck Lane Management Strategies for Platooning Speed Optimization and Control on Multi-Lane Highways |
| title_sort | research on truck lane management strategies for platooning speed optimization and control on multi lane highways |
| topic | truck platooning truck lane management strategy multi-objective optimization speed optimization and control |
| url | https://www.mdpi.com/2076-3417/13/6/4072 |
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