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Research Article | Open Access

Collaborative multi-lane on-ramp merging strategy for connected and automated vehicles using dynamic conflict graph

Jia Shi1Yugong Luo1Pengfei Li1Jiawei Wang2Keqiang Li1( )
School of Vehicle and Mobility, Tsinghua University, Beijing 100084, China
Department of Civil and Environmental Engineering, University of Michigan, Ann Arbor, MI 48109, USA
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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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Journal of Intelligent and Connected Vehicles
Pages 38-51
Cite this article:
Shi J, Luo Y, Li P, et al. Collaborative multi-lane on-ramp merging strategy for connected and automated vehicles using dynamic conflict graph. Journal of Intelligent and Connected Vehicles, 2024, 7(1): 38-51. https://doi.org/10.26599/JICV.2023.9210032

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Received: 12 December 2023
Revised: 16 January 2024
Accepted: 24 January 2024
Published: 31 March 2024
© The author(s) 2024.

This is an open access article under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/).

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