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Solving connected automated vehicle merging problems: A generalized benders decomposition-based approach for mixed-integer nonlinear programming

Author

Listed:
  • Chen, Jieming
  • Wu, Yiwei
  • Zhou, Yue
  • Chung, Edward
  • Wang, Shuaian

Abstract

Intensive interactions among vehicles often lead to congestion and accidents, particularly at freeway merging sections. As connected automated vehicles (CAVs) become a reality, their collaborative driving offers a promising solution. However, the real-time scheduling and trajectory planning for multiple CAV streams remain challenging and are not adequately addressed in the existing literature. To this end, this study formulates an integrated mixed-integer nonlinear programming (MINLP) model to jointly optimize lane change decisions, vehicle sequences, and vehicle trajectories, with the objective of maximizing traffic efficiency and driving comfort at multi-lane freeway merging sections. Existing commercial software struggles to handle such a complicated model. To rapidly obtain solutions, this study designs a Generalized Benders Decomposition (GBD)-based solution algorithm to tackle the problem of multi-vehicle combinatorial optimization and nonlinear trajectory optimization. Meanwhile, the finite convergence property of the GBD approach is proved. Numerical experimental results demonstrate that the proposed model outperforms three benchmark CAV control methods and a two-step method under various traffic demands and mainline-ramp demand ratios, highlighting significant traffic benefits from jointly planning lane changes and driving sequences, as well as utilizing microscopic vehicle information. Furthermore, this study evaluates traffic delay and the number of lane changes under varying road lengths, i.e., the lengths of lane-changing and merging areas, identifying recommended lengths for the maximum traffic efficiency, and analyzing the performance trend under varying traffic demands.

Suggested Citation

  • Chen, Jieming & Wu, Yiwei & Zhou, Yue & Chung, Edward & Wang, Shuaian, 2025. "Solving connected automated vehicle merging problems: A generalized benders decomposition-based approach for mixed-integer nonlinear programming," Transportation Research Part B: Methodological, Elsevier, vol. 200(C).
    • Handle: RePEc:eee:transb:v:200:y:2025:i:c:s0191261525001420
    DOI: 10.1016/j.trb.2025.103293
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    References listed on IDEAS

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    1. Kai Yuan & Victor L. Knoop & Serge P. Hoogendoorn, 2017. "A Microscopic Investigation Into the Capacity Drop: Impacts of Longitudinal Behavior on the Queue Discharge Rate," Transportation Science, INFORMS, vol. 51(3), pages 852-862, August.
    2. 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.
    3. Zhou, Xuesong, 2017. "Recasting and optimizing intersection automation as a connected-and-automated-vehicle (CAV) scheduling problem: A sequential branch-and-bound search approach in phase-time-traffic hypernetworkAuthor-Name: Li, Pengfei (Taylor)," Transportation Research Part B: Methodological, Elsevier, vol. 105(C), pages 479-506.
    4. Zhang, Hanyu & Du, Lili & Shen, Jinglai, 2022. "Hybrid MPC System for Platoon based Cooperative Lane change Control Using Machine Learning Aided Distributed Optimization," Transportation Research Part B: Methodological, Elsevier, vol. 159(C), pages 104-142.
    5. Li, Tienan & Chen, Danjue & Zhou, Hao & Laval, Jorge & Xie, Yuanchang, 2021. "Car-following behavior characteristics of adaptive cruise control vehicles based on empirical experiments," Transportation Research Part B: Methodological, Elsevier, vol. 147(C), pages 67-91.
    6. Xiao, Zhuang & Ye, Hongbo & Chung, Edward, 2025. "New formulations and solution approaches for train eco-driving problems," Transportation Research Part B: Methodological, Elsevier, vol. 195(C).
    7. Yang, Da & Jia, Bingmei & Dai, Liyuan & Jin, Jing Peter & Xu, Lihua & Chen, Fei & Zheng, Shiyu & Ran, Bin, 2022. "Optimization model for the freeway-exiting position decision problem of automated vehicles," Transportation Research Part B: Methodological, Elsevier, vol. 159(C), pages 24-48.
    8. Tian, Junfang & Zhang, H.M. & Treiber, Martin & Jiang, Rui & Gao, Zi-You & Jia, Bin, 2019. "On the role of speed adaptation and spacing indifference in traffic instability: Evidence from car-following experiments and its stochastic model," Transportation Research Part B: Methodological, Elsevier, vol. 129(C), pages 334-350.
    9. Chen, Danjue & Ahn, Soyoung & Hegyi, Andreas, 2014. "Variable speed limit control for steady and oscillatory queues at fixed freeway bottlenecks," Transportation Research Part B: Methodological, Elsevier, vol. 70(C), pages 340-358.
    10. Li, Xiaopeng & Ghiasi, Amir & Xu, Zhigang & Qu, Xiaobo, 2018. "A piecewise trajectory optimization model for connected automated vehicles: Exact optimization algorithm and queue propagation analysis," Transportation Research Part B: Methodological, Elsevier, vol. 118(C), pages 429-456.
    11. Han, Youngjun & Ahn, Soyoung, 2018. "Stochastic modeling of breakdown at freeway merge bottleneck and traffic control method using connected automated vehicle," Transportation Research Part B: Methodological, Elsevier, vol. 107(C), pages 146-166.
    12. Wang, Hua & Meng, Qiang & Chen, Shukai & Zhang, Xiaoning, 2021. "Competitive and cooperative behaviour analysis of connected and autonomous vehicles across unsignalised intersections: A game-theoretic approach," Transportation Research Part B: Methodological, Elsevier, vol. 149(C), pages 322-346.
    13. Daiheng Ni & John D. Leonard & Chaoqun Jia & Jianqiang Wang, 2016. "Vehicle Longitudinal Control and Traffic Stream Modeling," Transportation Science, INFORMS, vol. 50(3), pages 1016-1031, August.
    14. Jinglai Shen & Eswar Kumar H. Kammara & Lili Du, 2022. "Fully Distributed Optimization-Based CAV Platooning Control Under Linear Vehicle Dynamics," Transportation Science, INFORMS, vol. 56(2), pages 381-403, March.
    15. Ximing Cai & Daene C. McKinney & Leon S. Lasdon & David W. Watkins, 2001. "Solving Large Nonconvex Water Resources Management Models Using Generalized Benders Decomposition," Operations Research, INFORMS, vol. 49(2), pages 235-245, April.
    16. Zhou, Yang & Wang, Meng & Ahn, Soyoung, 2019. "Distributed model predictive control approach for cooperative car-following with guaranteed local and string stability," Transportation Research Part B: Methodological, Elsevier, vol. 128(C), pages 69-86.
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