IDEAS home Printed from https://ideas.repec.org/a/eee/transb/v73y2015icp103-121.html
   My bibliography  Save this article

Optimization of mid-block pedestrian crossing network with discrete demands

Author

Listed:
  • Yu, Chunhui
  • Ma, Wanjing
  • Lo, Hong K.
  • Yang, Xiaoguang

Abstract

In many cases, pedestrian crossing demands are distributed discretely along an arterial segment. Demand origins, destinations and crosswalks comprise a pedestrian crossing network. An integrated model for optimizing the quantity, locations and signal settings of mid-block crosswalks simultaneously is proposed to best trade-off the operational performances between pedestrians and vehicles. Pedestrian behavior of choosing crosswalks is captured under a discrete demand distribution. Detour distance and delay at signalized crosswalks are formulated as a measure of pedestrian crossing cost. Maximum bandwidths are modeled in analytical expressions as a measure of vehicular cost. To solve the proposed model, the Non-dominated Sorting Genetic Algorithm II (NSGA II) based algorithm is designed and employed to obtain the Pareto frontier efficiently. From the numerical study, it is found that there exists an optimal number of mid-block crosswalks. Excess available crosswalks may make no contributions to improvement in pedestrian cost when the constraint of the minimum interval between crosswalks and vehicular cost are taken into account. Two-stage crosswalks are more favorable than one-stage ones for the benefits of both pedestrian and vehicles. The study results show promising properties of the proposed method to assist transportation engineers in properly designing mid-block crosswalks along a road segment.

Suggested Citation

  • Yu, Chunhui & Ma, Wanjing & Lo, Hong K. & Yang, Xiaoguang, 2015. "Optimization of mid-block pedestrian crossing network with discrete demands," Transportation Research Part B: Methodological, Elsevier, vol. 73(C), pages 103-121.
    • Handle: RePEc:eee:transb:v:73:y:2015:i:c:p:103-121
    DOI: 10.1016/j.trb.2014.12.005
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0191261514002227
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.trb.2014.12.005?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. G. Yannis & E. Papadimitriou & A. Theofilatos, 2013. "Pedestrian gap acceptance for mid-block street crossing," Transportation Planning and Technology, Taylor & Francis Journals, vol. 36(5), pages 450-462, July.
    2. Li, Baibing, 2014. "A bilevel model for multivariate risk analysis of pedestrians’ crossing behavior at signalized intersections," Transportation Research Part B: Methodological, Elsevier, vol. 65(C), pages 18-30.
    3. Wong, C. K. & Wong, S. C., 2003. "Lane-based optimization of signal timings for isolated junctions," Transportation Research Part B: Methodological, Elsevier, vol. 37(1), pages 63-84, January.
    4. Pillai, Rekha S. & Rathi*, Ajay K. & L. Cohen, Stephen, 1998. "A restricted branch-and-bound approach for generating maximum bandwidth signal timing plans for traffic networks," Transportation Research Part B: Methodological, Elsevier, vol. 32(8), pages 517-529, November.
    5. Little, John D. C. & Kelson, Mark D. & Gartner, Nathan H., 1981. "MAXBAND : a versatile program for setting signals on arteries and triangular networks," Working papers 1185-81., Massachusetts Institute of Technology (MIT), Sloan School of Management.
    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. Sun, Qipeng & He, Chen & Wang, Yongjie & Liu, Hang & Ma, Fei & Wei, Xiao, 2022. "Reducing violation behaviors of pedestrians considering group interests of travelers at signalized crosswalk," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 594(C).
    2. Yang, Xin & Chen, Anthony & Ning, Bin & Tang, Tao, 2016. "A stochastic model for the integrated optimization on metro timetable and speed profile with uncertain train mass," Transportation Research Part B: Methodological, Elsevier, vol. 91(C), pages 424-445.
    3. Guanghua Han & Xujin Pu & Bo Fan, 2017. "Sustainable Governance of Organic Food Production When Market Forecast Is Imprecise," Sustainability, MDPI, vol. 9(6), pages 1-20, June.
    4. Piotr Szagala & Andrzej Brzezinski & Mariusz Kiec & Marcin Budzynski & Joanna Wachnicka & Sylwia Pazdan, 2022. "Pedestrian Safety at Midblock Crossings on Dual Carriageway Roads in Polish Cities," Sustainability, MDPI, vol. 14(9), pages 1-13, May.
    5. Gang Cheng & Shuzhi Zhao & Tao Zhang, 2019. "A Bi-Level Programming Model for Optimal Bus Stop Spacing of a Bus Rapid Transit System," Mathematics, MDPI, vol. 7(7), pages 1-14, July.
    6. Tang, Liying & Liu, Yugang & Li, JiaLi & Qi, Ruiting & Zheng, Shuai & Chen, Bin & Yang, Hongtai, 2020. "Pedestrian crossing design and analysis for symmetric intersections: Efficiency and safety," Transportation Research Part A: Policy and Practice, Elsevier, vol. 142(C), pages 187-206.
    7. Yang, Songpo & Liao, Feixiong & Wu, Jianjun & Timmermans, Harry J.P. & Sun, Huijun & Gao, Ziyou, 2020. "A bi-objective timetable optimization model incorporating energy allocation and passenger assignment in an energy-regenerative metro system," Transportation Research Part B: Methodological, Elsevier, vol. 133(C), pages 85-113.

    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. Zhao, Jing & Li, Peng, 2016. "An extended car-following model with consideration of speed guidance at intersections," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 461(C), pages 1-8.
    2. Yu, Chunhui & Ma, Wanjing & Yang, Xiaoguang, 2020. "A time-slot based signal scheme model for fixed-time control at isolated intersections," Transportation Research Part B: Methodological, Elsevier, vol. 140(C), pages 176-192.
    3. Yu, Chunhui & Ma, Wanjing & Han, Ke & Yang, Xiaoguang, 2017. "Optimization of vehicle and pedestrian signals at isolated intersections," Transportation Research Part B: Methodological, Elsevier, vol. 98(C), pages 135-153.
    4. D’Acierno, Luca & Gallo, Mariano & Montella, Bruno, 2012. "An Ant Colony Optimisation algorithm for solving the asymmetric traffic assignment problem," European Journal of Operational Research, Elsevier, vol. 217(2), pages 459-469.
    5. Xingmin Wang & Zachary Jerome & Zihao Wang & Chenhao Zhang & Shengyin Shen & Vivek Vijaya Kumar & Fan Bai & Paul Krajewski & Danielle Deneau & Ahmad Jawad & Rachel Jones & Gary Piotrowicz & Henry X. L, 2024. "Traffic light optimization with low penetration rate vehicle trajectory data," Nature Communications, Nature, vol. 15(1), pages 1-14, December.
    6. Lo, Hong K., 1999. "A novel traffic signal control formulation," Transportation Research Part A: Policy and Practice, Elsevier, vol. 33(6), pages 433-448, August.
    7. Wafaa Saleh & Monika Grigorova & Samia Elattar, 2020. "Pedestrian Road Crossing at Uncontrolled Mid-Block Locations: Does the Refuge Island Increase Risk?," Sustainability, MDPI, vol. 12(12), pages 1-16, June.
    8. Giulio Cantarella & Antonino Vitetta, 2006. "The multi-criteria road network design problem in an urban area," Transportation, Springer, vol. 33(6), pages 567-588, November.
    9. Ennio Cascetta & Mariano Gallo & Bruno Montella, 2006. "Models and algorithms for the optimization of signal settings on urban networks with stochastic assignment models," Annals of Operations Research, Springer, vol. 144(1), pages 301-328, April.
    10. Bielli, Maurizio & Reverberi, Pierfrancesco, 1996. "New operations research and artificial intelligence approaches to traffic engineering problems," European Journal of Operational Research, Elsevier, vol. 92(3), pages 550-572, August.
    11. Sadek, Bassel & Doig Godier, Jean & Cassidy, Michael J & Daganzo, Carlos F, 2022. "Traffic signal plans to decongest street grids," Transportation Research Part B: Methodological, Elsevier, vol. 162(C), pages 195-208.
    12. Jiaming Shi & Changxu Wu & Xiuying Qian, 2020. "The Effects of Multiple Factors on Elderly Pedestrians’ Speed Perception and Stopping Distance Estimation of Approaching Vehicles," Sustainability, MDPI, vol. 12(13), pages 1-16, June.
    13. Kun Wang & Liang Xu & Han Jiang, 2022. "Analysis of the Effect of Human-Machine Co-Driving Vehicle on Pedestrian Crossing Speed at Uncontrolled Mid-Block Road Sections: A VR-Based Case Study," IJERPH, MDPI, vol. 19(12), pages 1-12, June.
    14. Ma, Wanjing & Li, Li & Wang, Yinhai, 2016. "A driving force model for non-strict priority crossing behaviors of right-turn driversAuthor-Name: Lin, Dianchao," Transportation Research Part B: Methodological, Elsevier, vol. 83(C), pages 230-244.
    15. Mohebifard, Rasool & Hajbabaie, Ali, 2019. "Optimal network-level traffic signal control: A benders decomposition-based solution algorithm," Transportation Research Part B: Methodological, Elsevier, vol. 121(C), pages 252-274.
    16. Chen, Qun & Wang, Yan, 2015. "Cellular automata (CA) simulation of the interaction of vehicle flows and pedestrian crossings on urban low-grade uncontrolled roads," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 432(C), pages 43-57.
    17. Yuan, Tianchen & Ioannou, Petros A., 2023. "Coordinated Traffic Flow Control in a Connected Environment," Institute of Transportation Studies, Working Paper Series qt6q67f9z4, Institute of Transportation Studies, UC Davis.
    18. Hong K. Lo, 2001. "A Cell-Based Traffic Control Formulation: Strategies and Benefits of Dynamic Timing Plans," Transportation Science, INFORMS, vol. 35(2), pages 148-164, May.
    19. Cantarella, G.E. & Pavone, G. & Vitetta, A., 2006. "Heuristics for urban road network design: Lane layout and signal settings," European Journal of Operational Research, Elsevier, vol. 175(3), pages 1682-1695, December.
    20. Dujardin, Yann & Vanderpooten, Daniel & Boillot, Florence, 2015. "A multi-objective interactive system for adaptive traffic control," European Journal of Operational Research, Elsevier, vol. 244(2), pages 601-610.

    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:73:y:2015:i:c:p:103-121. 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.