IDEAS home Printed from https://ideas.repec.org/a/eee/transb/v119y2019icp1-21.html
   My bibliography  Save this article

Parsimonious trajectory design of connected automated traffic

Author

Listed:
  • Li, Li
  • Li, Xiaopeng

Abstract

One challenging problem about connected automated vehicles is to optimize vehicle trajectories considering realistic constraints (e.g. vehicle kinematic limits and collision avoidance) and objectives (e.g., travel time, fuel consumption). With respect to communication cost and implementation difficulty, parsimonious trajectory planning has attracted continuous interests. In this paper, we first analyze the feasibility conditions for a general continuous-time trajectory planning problem and then propose an analytical solution method for two important boundary trajectory problems. We further propose a discrete-time model with a more general objective function and a certain sparsity requirement that helps parsimonious planned trajectories. This sparsity requirement is implemented with a l1 norm regulatory term appended to the objective function. Numerical examples are conducted on several representative applications and show that the proposed design strategy is effective.

Suggested Citation

  • Li, Li & Li, Xiaopeng, 2019. "Parsimonious trajectory design of connected automated traffic," Transportation Research Part B: Methodological, Elsevier, vol. 119(C), pages 1-21.
    • Handle: RePEc:eee:transb:v:119:y:2019:i:c:p:1-21
    DOI: 10.1016/j.trb.2018.11.006
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0191261517311426
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.trb.2018.11.006?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. 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. D. Helbing & M. Treiber & A. Kesting & M. Schönhof, 2009. "Theoretical vs. empirical classification and prediction of congested traffic states," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 69(4), pages 583-598, June.
    3. Weintraub, Andrés & Ortiz, Carmen & González, Jaime, 1985. "Accelerating convergence of the Frank-Wolfe algorithm," Transportation Research Part B: Methodological, Elsevier, vol. 19(2), pages 113-122, April.
    4. Demir, Emrah & Bektaş, Tolga & Laporte, Gilbert, 2014. "A review of recent research on green road freight transportation," European Journal of Operational Research, Elsevier, vol. 237(3), pages 775-793.
    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. Fukushima, Masao, 1984. "A modified Frank-Wolfe algorithm for solving the traffic assignment problem," Transportation Research Part B: Methodological, Elsevier, vol. 18(2), pages 169-177, April.
    7. Yin, Yafeng, 2008. "Robust optimal traffic signal timing," Transportation Research Part B: Methodological, Elsevier, vol. 42(10), pages 911-924, December.
    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. Cassidy, Michael J. & Windover, John R., 1998. "Driver memory: Motorist selection and retention of individualized headways in highway traffic," Transportation Research Part A: Policy and Practice, Elsevier, vol. 32(2), pages 129-137, February.
    10. Taniguchi, Yohei & Nishi, Ryosuke & Ezaki, Takahiro & Nishinari, Katsuhiro, 2015. "Jam-absorption driving with a car-following model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 433(C), pages 304-315.
    11. Li Li, 2015. "Selected Applications of Convex Optimization," Springer Optimization and Its Applications, Springer, edition 127, number 978-3-662-46356-7, September.
    12. Marguerite Frank & Philip Wolfe, 1956. "An algorithm for quadratic programming," Naval Research Logistics Quarterly, John Wiley & Sons, vol. 3(1‐2), pages 95-110, March.
    13. 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.
    14. 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.
    15. Nishi, Ryosuke & Tomoeda, Akiyasu & Shimura, Kenichiro & Nishinari, Katsuhiro, 2013. "Theory of jam-absorption driving," Transportation Research Part B: Methodological, Elsevier, vol. 50(C), pages 116-129.
    16. Wong, S. C. & Wong, W. T. & Leung, C. M. & Tong, C. O., 2002. "Group-based optimization of a time-dependent TRANSYT traffic model for area traffic control," Transportation Research Part B: Methodological, Elsevier, vol. 36(4), pages 291-312, May.
    17. 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.
    18. Yu, Chunhui & Feng, Yiheng & Liu, Henry X. & Ma, Wanjing & Yang, Xiaoguang, 2018. "Integrated optimization of traffic signals and vehicle trajectories at isolated urban intersections," Transportation Research Part B: Methodological, Elsevier, vol. 112(C), pages 89-112.
    19. 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.
    20. 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.
    21. Wei, Yuguang & Avcı, Cafer & Liu, Jiangtao & Belezamo, Baloka & Aydın, Nizamettin & Li, Pengfei(Taylor) & Zhou, Xuesong, 2017. "Dynamic programming-based multi-vehicle longitudinal trajectory optimization with simplified car following models," Transportation Research Part B: Methodological, Elsevier, vol. 106(C), pages 102-129.
    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. Nishi, Ryosuke, 2020. "Theoretical conditions for restricting secondary jams in jam-absorption driving scenarios," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 542(C).
    2. 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.
    3. 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.
    4. Shi, Xiaowei & Li, Xiaopeng, 2023. "Trajectory Planning for an Autonomous Vehicle with Conflicting Moving Objects Along a Fixed Path – An Exact Solution Method," Transportation Research Part B: Methodological, Elsevier, vol. 173(C), pages 228-246.
    5. Zhang, Jian & Tang, Tie-Qiao & Yan, Yadan & Qu, Xiaobo, 2021. "Eco-driving control for connected and automated electric vehicles at signalized intersections with wireless charging," Applied Energy, Elsevier, vol. 282(PA).
    6. Wang, Tao & Yuan, Zijian & Zhang, Yuanshu & Zhang, Jing & Tian, Junfang, 2023. "A driving guidance strategy with pre-stop line at signalized intersection: Collaborative optimization of capacity and fuel consumption," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 626(C).
    7. Wu, Wei & Zhang, Fangni & Liu, Wei & Lodewijks, Gabriel, 2020. "Modelling the traffic in a mixed network with autonomous-driving expressways and non-autonomous local streets," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 134(C).
    8. Nishi, Ryosuke & Watanabe, Takashi, 2022. "System-size dependence of a jam-absorption driving strategy to remove traffic jam caused by a sag under the presence of traffic instability," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 600(C).
    9. Li, Qianwen & Li, Xiaopeng, 2022. "Trajectory planning for autonomous modular vehicle docking and autonomous vehicle platooning operations," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 166(C).

    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. 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.
    2. 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.
    3. Li, Xiaopeng, 2022. "Trade-off between safety, mobility and stability in automated vehicle following control: An analytical method," Transportation Research Part B: Methodological, Elsevier, vol. 166(C), pages 1-18.
    4. 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.
    5. Yu Wang & Xiaopeng Li & Junfang Tian & Rui Jiang, 2020. "Stability Analysis of Stochastic Linear Car-Following Models," Transportation Science, INFORMS, vol. 54(1), pages 274-297, January.
    6. 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.
    7. 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.
    8. Tian, Junfang & Jiang, Rui & Jia, Bin & Gao, Ziyou & Ma, Shoufeng, 2016. "Empirical analysis and simulation of the concave growth pattern of traffic oscillations," Transportation Research Part B: Methodological, Elsevier, vol. 93(PA), pages 338-354.
    9. 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.
    10. 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.
    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. 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.
    13. 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.
    14. Zhang, Jing & Xu, Keyu & Li, Shubin & Wang, Tao, 2020. "A new two-lane lattice hydrodynamic model with the introduction of driver’s predictive effect," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 551(C).
    15. Zhou, Linjie & Ruan, Tiancheng & Ma, Ke & Dong, Changyin & Wang, Hao, 2021. "Impact of CAV platoon management on traffic flow considering degradation of control mode," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 581(C).
    16. Zhang, Jing & Wang, Bo & Li, Shubin & Sun, Tao & Wang, Tao, 2020. "Modeling and application analysis of car-following model with predictive headway variation," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 540(C).
    17. Taesung Hwang, 2021. "Assignment of Freight Truck Shipment on the U.S. Highway Network," Sustainability, MDPI, vol. 13(11), pages 1-11, June.
    18. 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).
    19. Wang, Zhaodong & Wang, Xin & Ouyang, Yanfeng, 2015. "Bounded growth of the bullwhip effect under a class of nonlinear ordering policies," European Journal of Operational Research, Elsevier, vol. 247(1), pages 72-82.
    20. Nishi, Ryosuke & Watanabe, Takashi, 2022. "System-size dependence of a jam-absorption driving strategy to remove traffic jam caused by a sag under the presence of traffic instability," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 600(C).

    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:119:y:2019:i:c:p:1-21. 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.