Collaborative Multi-Lane on-Ramp Merging Strategy for Connected and Automated Vehicles Using Dynamic Conflict Graph
The on-ramp merging in multi-lane highway scenarios presents challenges due to the complexity of coordinating vehicles’ merging and lane-changing behaviors, while ensuring safety and optimizing traffic flow. However, there are few studies that have addressed the merging problem of ramp vehicles and...
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| Published in | Journal of intelligent and connected vehicles Vol. 7; no. 1; pp. 38 - 51 |
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| Main Authors | , , , , |
| Format | Journal Article |
| Language | English |
| Published |
Tsinghua University Press
01.03.2024
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| Subjects | |
| Online Access | Get full text |
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| Abstract | The on-ramp merging in multi-lane highway scenarios presents challenges due to the complexity of coordinating vehicles’ merging and lane-changing behaviors, while ensuring safety and optimizing traffic flow. However, there are few studies that have addressed the merging problem of ramp vehicles and the cooperative lane-change problem of mainline vehicles within a unified framework and proposed corresponding optimization strategies. To tackle this issue, this study adopts a cyber-physical integration perspective and proposes a graph-based solution approach. First, the information of vehicle groups in the physical plane is mapped to the cyber plane, and a dynamic conflict graph is introduced in the cyber space to describe the conflict relationships among vehicle groups. Subsequently, graph decomposition and search strategies are employed to obtain the optimal solution, including the set of mainline vehicles changing lanes, passing sequences for each route, and corresponding trajectories. Finally, the proposed dynamic conflict graph-based algorithm is validated through simulations in continuous traffic with various densities, and its performance is compared with the default algorithm in SUMO. The results demonstrate the effectiveness of the proposed approach in improving vehicle safety and traffic efficiency, particularly in high traffic density scenarios, providing valuable insights for future research in multi-lane merging strategies. |
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| AbstractList | The on-ramp merging in multi-lane highway scenarios presents challenges due to the complexity of coordinating vehicles’ merging and lane-changing behaviors, while ensuring safety and optimizing traffic flow. However, there are few studies that have addressed the merging problem of ramp vehicles and the cooperative lane-change problem of mainline vehicles within a unified framework and proposed corresponding optimization strategies. To tackle this issue, this study adopts a cyber-physical integration perspective and proposes a graph-based solution approach. First, the information of vehicle groups in the physical plane is mapped to the cyber plane, and a dynamic conflict graph is introduced in the cyber space to describe the conflict relationships among vehicle groups. Subsequently, graph decomposition and search strategies are employed to obtain the optimal solution, including the set of mainline vehicles changing lanes, passing sequences for each route, and corresponding trajectories. Finally, the proposed dynamic conflict graph-based algorithm is validated through simulations in continuous traffic with various densities, and its performance is compared with the default algorithm in SUMO. The results demonstrate the effectiveness of the proposed approach in improving vehicle safety and traffic efficiency, particularly in high traffic density scenarios, providing valuable insights for future research in multi-lane merging strategies. |
| Author | Shi, Jia Luo, Yugong Li, Keqiang Li, Pengfei Wang, Jiawei |
| Author_xml | – sequence: 1 givenname: Jia surname: Shi fullname: Shi, Jia organization: School of Vehicle and Mobility, Tsinghua University,Beijing,China,100084 – sequence: 2 givenname: Yugong surname: Luo fullname: Luo, Yugong organization: School of Vehicle and Mobility, Tsinghua University,Beijing,China,100084 – sequence: 3 givenname: Pengfei surname: Li fullname: Li, Pengfei organization: School of Vehicle and Mobility, Tsinghua University,Beijing,China,100084 – sequence: 4 givenname: Jiawei surname: Wang fullname: Wang, Jiawei organization: University of Michigan,Department of Civil and Environmental Engineering,Ann Arbor,MI,USA,48109 – sequence: 5 givenname: Keqiang surname: Li fullname: Li, Keqiang organization: School of Vehicle and Mobility, Tsinghua University,Beijing,China,100084 |
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| Title | Collaborative Multi-Lane on-Ramp Merging Strategy for Connected and Automated Vehicles Using Dynamic Conflict Graph |
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