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A Cooperative Merging Control Method for Freeway Ramps in Connected and Autonomous Driving

Author

Listed:
  • Jiaxin Wu

    (Faculty of Maritime and Transportation, Ningbo University, Ningbo 315832, China
    Collaborative Innovation Center of Modern Urban Traffic Technologies, Southeast University, Nanjing 211189, China
    National Traffic Management Engineering & Technology Research Centre, Ningbo University, Ningbo 315832, China)

  • Yibing Wang

    (Institute of Intelligent Transportation Systems, Zhejiang University, Hangzhou 310058, China)

  • Zhao Zhang

    (School of Transportation Science and Engineering, Beihang University, Beijing 100191, China)

  • Yiqing Wen

    (Faculty of Maritime and Transportation, Ningbo University, Ningbo 315832, China
    Collaborative Innovation Center of Modern Urban Traffic Technologies, Southeast University, Nanjing 211189, China
    National Traffic Management Engineering & Technology Research Centre, Ningbo University, Ningbo 315832, China)

  • Liangxia Zhong

    (Faculty of Maritime and Transportation, Ningbo University, Ningbo 315832, China
    Collaborative Innovation Center of Modern Urban Traffic Technologies, Southeast University, Nanjing 211189, China
    National Traffic Management Engineering & Technology Research Centre, Ningbo University, Ningbo 315832, China)

  • Pengjun Zheng

    (Faculty of Maritime and Transportation, Ningbo University, Ningbo 315832, China
    Collaborative Innovation Center of Modern Urban Traffic Technologies, Southeast University, Nanjing 211189, China
    National Traffic Management Engineering & Technology Research Centre, Ningbo University, Ningbo 315832, China)

Abstract

The highway on-ramp merging area is one of the major sections that form traffic bottlenecks. In a connected vehicle environment, V2V and V2I technologies enable real-time exchange of information, including position, speed, and acceleration. To improve the efficiency of vehicle merging at the on-ramp, this study proposes a cooperative merging control strategy for network-connected autonomous vehicles. First, the central controller designs the merging sequence and safety space for vehicles passing through the confluence point. Then, a trajectory optimization model was constructed based on vehicle longitudinal dynamics, and the PMP algorithm was used to determine the optimal control input. Finally, all vehicles follow the optimal trajectory so that the ramp vehicles merge smoothly into the mainline. Simulations verify that the proposed algorithm performs better than FIFO, with 13.2% energy savings, 41.4% increase in average speed, and 50.4% reduction in travel time over the uncontrolled merging scenario. The method is further applied to different traffic flow conditions and the results show that it can significantly improve traffic safety and mobility, while effectively reducing vehicle energy consumption. However, the traffic operation improvement is not satisfactory under low traffic demand.

Suggested Citation

  • Jiaxin Wu & Yibing Wang & Zhao Zhang & Yiqing Wen & Liangxia Zhong & Pengjun Zheng, 2022. "A Cooperative Merging Control Method for Freeway Ramps in Connected and Autonomous Driving," Sustainability, MDPI, vol. 14(18), pages 1-20, September.
    • Handle: RePEc:gam:jsusta:v:14:y:2022:i:18:p:11120-:d:907624
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    References listed on IDEAS

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    1. Rodrigo C. Carlson & Ioannis Papamichail & Markos Papageorgiou & Albert Messmer, 2010. "Optimal Motorway Traffic Flow Control Involving Variable Speed Limits and Ramp Metering," Transportation Science, INFORMS, vol. 44(2), pages 238-253, May.
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