IDEAS home Printed from https://ideas.repec.org/a/eee/transb/v95y2017icp421-441.html
   My bibliography  Save this article

Parsimonious shooting heuristic for trajectory design of connected automated traffic part II: Computational issues and optimization

Author

Listed:
  • Ma, Jiaqi
  • Li, Xiaopeng
  • Zhou, Fang
  • Hu, Jia
  • Park, B. Brian

Abstract

Advanced connected and automated vehicle technologies enable us to modify driving behavior and control vehicle trajectories, which have been greatly constrained by human limits in existing manually-driven highway traffic. In order to maximize benefits from these technologies on highway traffic management, vehicle trajectories need to be not only controlled at the individual level but also coordinated collectively for a stream of traffic. As one of the pioneering attempts to highway traffic trajectory control, Part I of this study (Zhou et al., 2016) proposed a parsimonious shooting heuristic (SH) algorithm for constructing feasible trajectories for a stream of vehicles considering realistic constraints including vehicle kinematic limits, traffic arrival patterns, car-following safety, and signal operations. Based on the algorithmic and theoretical developments in the preceding paper, this paper proposes a holistic optimization framework for identifying a stream of vehicle trajectories that yield the optimum traffic performance measures on mobility, environment and safety. The computational complexity and mobility optimality of SH is theoretically analyzed, and verifies superior computational performance and high solution quality of SH. A numerical sub-gradient-based algorithm with SH as a subroutine (NG-SH) is proposed to simultaneously optimize travel time, a surrogate safety measure, and fuel consumption for a stream of vehicles on a signalized highway section. Numerical examples are conducted to illustrate computational and theoretical findings. They show that vehicle trajectories generated from NG-SH significantly outperform the benchmark case with all human drivers at all measures for all experimental scenarios. This study reveals a great potential of transformative trajectory optimization approaches in transportation engineering applications. It lays a solid foundation for developing holistic cooperative control strategies on a general transportation network with emerging technologies.

Suggested Citation

  • Ma, Jiaqi & Li, Xiaopeng & Zhou, Fang & Hu, Jia & Park, B. Brian, 2017. "Parsimonious shooting heuristic for trajectory design of connected automated traffic part II: Computational issues and optimization," Transportation Research Part B: Methodological, Elsevier, vol. 95(C), pages 421-441.
    • Handle: RePEc:eee:transb:v:95:y:2017:i:c:p:421-441
    DOI: 10.1016/j.trb.2016.06.010
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0191261515302642
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.trb.2016.06.010?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Gipps, P.G., 1981. "A behavioural car-following model for computer simulation," Transportation Research Part B: Methodological, Elsevier, vol. 15(2), pages 105-111, April.
    2. Cassidy, Michael J. & Bertini, Robert L., 1999. "Some traffic features at freeway bottlenecks," Transportation Research Part B: Methodological, Elsevier, vol. 33(1), pages 25-42, February.
    3. Li, Xiaopeng & Cui, Jianxun & An, Shi & Parsafard, Mohsen, 2014. "Stop-and-go traffic analysis: Theoretical properties, environmental impacts and oscillation mitigation," Transportation Research Part B: Methodological, Elsevier, vol. 70(C), pages 319-339.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Gao, Caihong & Wang, Ziyang & Wang, Shupei & Li, Ying, 2024. "Mitigating oscillations of mixed traffic flows at a signalized intersection: A multiagent trajectory optimization approach based on oscillation prediction," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 635(C).
    2. Chen Wang & Yulu Dai & Jingxin Xia, 2020. "A CAV Platoon Control Method for Isolated Intersections: Guaranteed Feasible Multi-Objective Approach with Priority," Energies, MDPI, vol. 13(3), pages 1-16, February.
    3. Huifu Jiang & Shi An & Jian Wang & Jianxun Cui, 2018. "Eco-Approach and Departure System for Left-Turn Vehicles at a Fixed-Time Signalized Intersection," Sustainability, MDPI, vol. 10(1), pages 1-20, January.
    4. 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.
    5. 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.
    6. Lu, Gongyuan & Nie, Yu(Marco) & Liu, Xiaobo & Li, Denghui, 2019. "Trajectory-based traffic management inside an autonomous vehicle zone," Transportation Research Part B: Methodological, Elsevier, vol. 120(C), pages 76-98.
    7. Shi, Xiaoyu & Zhang, Jian & Jiang, Xia & Chen, Juan & Hao, Wei & Wang, Bo, 2024. "Learning eco-driving strategies from human driving trajectories," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 633(C).
    8. Zhao, Shuaidong & Zhang, Kuilin, 2020. "A distributionally robust stochastic optimization-based model predictive control with distributionally robust chance constraints for cooperative adaptive cruise control under uncertain traffic conditi," Transportation Research Part B: Methodological, Elsevier, vol. 138(C), pages 144-178.
    9. Zhou, Yang & Zhong, Xinzhi & Chen, Qian & Ahn, Soyoung & Jiang, Jiwan & Jafarsalehi, Ghazaleh, 2023. "Data-driven analysis for disturbance amplification in car-following behavior of automated vehicles," Transportation Research Part B: Methodological, Elsevier, vol. 174(C).
    10. Zhang, Hanyu & Du, Lili, 2023. "Platoon-centered control for eco-driving at signalized intersection built upon hybrid MPC system, online learning and distributed optimization part II: Theoretical analysis," Transportation Research Part B: Methodological, Elsevier, vol. 172(C), pages 199-216.
    11. Xiao Xiao & Yunlong Zhang & Xiubin Bruce Wang & Shu Yang & Tianyi Chen, 2021. "Hierarchical Longitudinal Control for Connected and Automated Vehicles in Mixed Traffic on a Signalized Arterial," Sustainability, MDPI, vol. 13(16), pages 1-17, August.
    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. Qu, Xiaobo & Yu, Yang & Zhou, Mofan & Lin, Chin-Teng & Wang, Xiangyu, 2020. "Jointly dampening traffic oscillations and improving energy consumption with electric, connected and automated vehicles: A reinforcement learning based approach," Applied Energy, Elsevier, vol. 257(C).
    14. Liu, Qingling & Xu, Xiaowen, 2024. "A platoon-based eco-driving control mechanism for low-density traffic flow," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 637(C).
    15. Liu, Chunyu & Sheng, Zihao & Chen, Sikai & Shi, Haotian & Ran, Bin, 2023. "Longitudinal control of connected and automated vehicles among signalized intersections in mixed traffic flow with deep reinforcement learning approach," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 629(C).
    16. Guan Wang & Jintao Lai & Zhexi Lian & Zhen Zhang, 2023. "An Eco-Driving Strategy Considering Phase-Switch-Based Bus Lane Sharing," Sustainability, MDPI, vol. 15(9), pages 1-20, April.
    17. Qu, Xiaobo & Zhang, Jin & Wang, Shuaian, 2017. "On the stochastic fundamental diagram for freeway traffic: Model development, analytical properties, validation, and extensive applications," Transportation Research Part B: Methodological, Elsevier, vol. 104(C), pages 256-271.
    18. Huifu Jiang & Wei Zhou & Chang Liu & Guosheng Zhang & Meng Hu, 2020. "Safe and Ecological Speed Control for Heavy-Duty Vehicles on Long–Steep Downhill and Sharp-Curved Roads," Sustainability, MDPI, vol. 12(17), pages 1-35, August.
    19. Zhou, Yang & Ahn, Soyoung, 2019. "Robust local and string stability for a decentralized car following control strategy for connected automated vehicles," Transportation Research Part B: Methodological, Elsevier, vol. 125(C), pages 175-196.
    20. Li, Li & Li, Xiaopeng, 2019. "Parsimonious trajectory design of connected automated traffic," Transportation Research Part B: Methodological, Elsevier, vol. 119(C), pages 1-21.
    21. Huifu Jiang & Jia Hu & Byungkyu Brian Park & Meng Wang & Wei Zhou, 2019. "An Extensive Investigation of an Eco-Approach Controller under a Partially Connected and Automated Vehicle Environment," Sustainability, MDPI, vol. 11(22), pages 1-24, November.
    22. Anton Agafonov & Alexander Yumaganov & Vladislav Myasnikov, 2023. "Cooperative Control for Signalized Intersections in Intelligent Connected Vehicle Environments," Mathematics, MDPI, vol. 11(6), pages 1-19, March.
    23. Zhou, Yang & Ahn, Soyoung & Wang, Meng & Hoogendoorn, Serge, 2020. "Stabilizing mixed vehicular platoons with connected automated vehicles: An H-infinity approach," Transportation Research Part B: Methodological, Elsevier, vol. 132(C), pages 152-170.
    24. 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-N," Transportation Research Part B: Methodological, Elsevier, vol. 105(C), pages 479-506.
    25. Wu, Fuliang & Bektaş, Tolga & Dong, Ming & Ye, Hongbo & Zhang, Dali, 2021. "Optimal driving for vehicle fuel economy under traffic speed uncertainty," Transportation Research Part B: Methodological, Elsevier, vol. 154(C), pages 175-206.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Zhou, Fang & Li, Xiaopeng & Ma, Jiaqi, 2017. "Parsimonious shooting heuristic for trajectory design of connected automated traffic part I: Theoretical analysis with generalized time geography," Transportation Research Part B: Methodological, Elsevier, vol. 95(C), pages 394-420.
    2. Yao, Handong & Li, Qianwen & Li, Xiaopeng, 2020. "A study of relationships in traffic oscillation features based on field experiments," Transportation Research Part A: Policy and Practice, Elsevier, vol. 141(C), pages 339-355.
    3. Martínez, Irene & Jin, Wen-Long, 2020. "Optimal location problem for variable speed limit application areas," Transportation Research Part B: Methodological, Elsevier, vol. 138(C), pages 221-246.
    4. Jin, Wen-Long, 2017. "Kinematic wave models of lane-drop bottlenecks," Transportation Research Part B: Methodological, Elsevier, vol. 105(C), pages 507-522.
    5. Jiang, Rui & Hu, Mao-Bin & Zhang, H.M. & Gao, Zi-You & Jia, Bin & Wu, Qing-Song, 2015. "On some experimental features of car-following behavior and how to model them," Transportation Research Part B: Methodological, Elsevier, vol. 80(C), pages 338-354.
    6. Zheng, Zuduo, 2014. "Recent developments and research needs in modeling lane changing," Transportation Research Part B: Methodological, Elsevier, vol. 60(C), pages 16-32.
    7. Yeo, Hwasoo, 2008. "Asymmetric Microscopic Driving Behavior Theory," University of California Transportation Center, Working Papers qt1tn1m968, University of California Transportation Center.
    8. Li, Xiaopeng & Peng, Fan & Ouyang, Yanfeng, 2010. "Measurement and estimation of traffic oscillation properties," Transportation Research Part B: Methodological, Elsevier, vol. 44(1), pages 1-14, January.
    9. Zhang, Xuan & Jia, Bin & Jiang, Rui, 2018. "Impact of safety assistance driving systems on oscillation magnitude, fuel consumption and emission in a car platoon," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 505(C), pages 995-1007.
    10. 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.
    11. Jin, Wen-Long, 2017. "A first-order behavioral model of capacity drop," Transportation Research Part B: Methodological, Elsevier, vol. 105(C), pages 438-457.
    12. Li, Xiaopeng & Ouyang, Yanfeng, 2011. "Characterization of traffic oscillation propagation under nonlinear car-following laws," Transportation Research Part B: Methodological, Elsevier, vol. 45(9), pages 1346-1361.
    13. Zhou, Zhi & Li, Linheng & Qu, Xu & Ran, Bin, 2024. "A self-adaptive IDM car-following strategy considering asymptotic stability and damping characteristics," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 637(C).
    14. Zhao, Jing & Knoop, Victor L. & Wang, Meng, 2020. "Two-dimensional vehicular movement modelling at intersections based on optimal control," Transportation Research Part B: Methodological, Elsevier, vol. 138(C), pages 1-22.
    15. Banks, James H., 2003. "Average time gaps in congested freeway flow," Transportation Research Part A: Policy and Practice, Elsevier, vol. 37(6), pages 539-554, July.
    16. Li, Xiaopeng & Wang, Xin & Ouyang, Yanfeng, 2012. "Prediction and field validation of traffic oscillation propagation under nonlinear car-following laws," Transportation Research Part B: Methodological, Elsevier, vol. 46(3), pages 409-423.
    17. Osorio, Carolina & Punzo, Vincenzo, 2019. "Efficient calibration of microscopic car-following models for large-scale stochastic network simulators," Transportation Research Part B: Methodological, Elsevier, vol. 119(C), pages 156-173.
    18. Bonsall, Peter & Liu, Ronghui & Young, William, 2005. "Modelling safety-related driving behaviour--impact of parameter values," Transportation Research Part A: Policy and Practice, Elsevier, vol. 39(5), pages 425-444, June.
    19. Wang, Tao & Liao, Peng & Tang, Tie-Qiao & Huang, Hai-Jun, 2022. "Deterministic capacity drop and morning commute in traffic corridor with tandem bottlenecks: A new manifestation of capacity expansion paradox," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 168(C).
    20. Cassidy, Michael J. & Jang, Kitae & Daganzo, Carlos F., 2010. "The smoothing effect of carpool lanes on freeway bottlenecks," Transportation Research Part A: Policy and Practice, Elsevier, vol. 44(2), pages 65-75, February.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:transb:v:95:y:2017:i:c:p:421-441. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/wps/find/journaldescription.cws_home/548/description#description .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.