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Optimization of mid-block pedestrian crossing network with discrete demands

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  • 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
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    References listed on IDEAS

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    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. 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.
    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. 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.
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    Cited by:

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    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.

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