IDEAS home Printed from https://ideas.repec.org/a/rom/mrpase/v5y2013i4p5-18.html
   My bibliography  Save this article

Factors Affecting The Citizen’S Trends To Use The Pedestrian Bridges In Iran

Author

Listed:
  • Ali SOLTANI

    (Department of Urban Planning, Faculty of Art and Architecture, Shiraz University, Iran)

  • Samaneh MOZAYENI

    (Department of Urban Planning, McMaster Univrersity, Canada)

Abstract

Pedestrian bridges eliminate all conflicts with traffic on the road below. They would sound to be the great solution for getting pedestrians across the street. But do they constantly work well? The primary goal of this study was to determine the trends of the pedestrians as they made use of these bridges. Ten pedestrian bridges in Tehran and Shiraz, two major cities of Iran, were chosen for observation of their rate of use by pedestrians. A survey was conducted among 200 pedestrians including those who used the bridges, and those who chose instead to risk traffic and cross the street under the bridge. The respondents’ perception about the safety of crossing the road was inversely related to the respondents’ bridge use. Other factors positively influencing bridge use included time of day, density of people under the bridge, and previous involvement in a traffic accident.

Suggested Citation

  • Ali SOLTANI & Samaneh MOZAYENI, 2013. "Factors Affecting The Citizen’S Trends To Use The Pedestrian Bridges In Iran," Management Research and Practice, Research Centre in Public Administration and Public Services, Bucharest, Romania, vol. 5(4), pages 5-18, December.
  • Handle: RePEc:rom:mrpase:v:5:y:2013:i:4:p:5-18
    as

    Download full text from publisher

    File URL: https://mrp.ase.ro/no54/f1.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Yang, Jianguo & Deng, Wen & Wang, Jinmei & Li, Qingfeng & Wang, Zhaoan, 2006. "Modeling pedestrians' road crossing behavior in traffic system micro-simulation in China," Transportation Research Part A: Policy and Practice, Elsevier, vol. 40(3), pages 280-290, March.
    2. Hoogendoorn, S. P. & Bovy, P. H. L., 2004. "Pedestrian route-choice and activity scheduling theory and models," Transportation Research Part B: Methodological, Elsevier, vol. 38(2), pages 169-190, February.
    3. Keegan, Owen & O'Mahony, Margaret, 2003. "Modifying pedestrian behaviour," Transportation Research Part A: Policy and Practice, Elsevier, vol. 37(10), pages 889-901, December.
    Full references (including those not matched with items on IDEAS)

    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, 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.
    2. Li, Baibing, 2013. "A model of pedestrians’ intended waiting times for street crossings at signalized intersections," Transportation Research Part B: Methodological, Elsevier, vol. 51(C), pages 17-28.
    3. Xianing Wang & Zhan Zhang & Ying Wang & Jun Yang & Linjun Lu, 2022. "A Study on Safety Evaluation of Pedestrian Flows Based on Partial Impact Dynamics by Real-Time Data in Subway Stations," Sustainability, MDPI, vol. 14(16), pages 1-19, August.
    4. Joohyun Lee & Mardelle McCuskey Shepley, 2020. "College Campuses and Student Walkability: Assessing the Impact of Smartphone Use on Student Perception and Evaluation of Urban Campus Routes," Sustainability, MDPI, vol. 12(23), pages 1-18, November.
    5. Jie Xu & Yao Ning & Heng Wei & Wei Xie & Jianyuan Guo & Limin Jia & Yong Qin, 2015. "Route Choice in Subway Station during Morning Peak Hours: A Case of Guangzhou Subway," Discrete Dynamics in Nature and Society, Hindawi, vol. 2015, pages 1-8, March.
    6. Aura-Luciana Istrate & Vojtěch Bosák & Alexandr Nováček & Ondřej Slach, 2020. "How Attractive for Walking Are the Main Streets of a Shrinking City?," Sustainability, MDPI, vol. 12(15), pages 1-20, July.
    7. Jie Yang & Nirajan Shiwakoti & Richard Tay, 2023. "Exploring Melbourne Metro Train Passengers’ Pre-Boarding Behaviors and Perceptions," Sustainability, MDPI, vol. 15(15), pages 1-20, July.
    8. Hoogendoorn, Serge P. & Bovy, Piet H. L., 2004. "Dynamic user-optimal assignment in continuous time and space," Transportation Research Part B: Methodological, Elsevier, vol. 38(7), pages 571-592, August.
    9. Korbmacher, Raphael & Dang, Huu-Tu & Tordeux, Antoine, 2024. "Predicting pedestrian trajectories at different densities: A multi-criteria empirical analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 634(C).
    10. Mohammed Mahmod Shuaib, 2016. "Modeling the Pedestrian Ability of Detecting Lanes and Lane Changing Behavior," Modern Applied Science, Canadian Center of Science and Education, vol. 10(7), pages 1-1, July.
    11. Zhang, Yihao & Chai, Zhaojie & Lykotrafitis, George, 2021. "Deep reinforcement learning with a particle dynamics environment applied to emergency evacuation of a room with obstacles," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 571(C).
    12. Rahul, T.M. & Manoj, M., 2020. "Categorization of pedestrian level of service perceptions and accounting its response heterogeneity and latent correlation on travel decisions," Transportation Research Part A: Policy and Practice, Elsevier, vol. 142(C), pages 40-55.
    13. Marija Nikolić & Michel Bierlaire & Matthieu de Lapparent & Riccardo Scarinci, 2019. "Multiclass Speed-Density Relationship for Pedestrian Traffic," Transportation Science, INFORMS, vol. 53(3), pages 642-664, May.
    14. Xiao, Yao & Yang, Mofeng & Zhu, Zheng & Yang, Hai & Zhang, Lei & Ghader, Sepehr, 2021. "Modeling indoor-level non-pharmaceutical interventions during the COVID-19 pandemic: A pedestrian dynamics-based microscopic simulation approach," Transport Policy, Elsevier, vol. 109(C), pages 12-23.
    15. Xu, Xin-yue & Liu, Jun & Li, Hai-ying & Jiang, Man, 2016. "Capacity-oriented passenger flow control under uncertain demand: Algorithm development and real-world case study," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 87(C), pages 130-148.
    16. Abdelghany, Ahmed & Abdelghany, Khaled & Mahmassani, Hani, 2016. "A hybrid simulation-assignment modeling framework for crowd dynamics in large-scale pedestrian facilities," Transportation Research Part A: Policy and Practice, Elsevier, vol. 86(C), pages 159-176.
    17. Qingyan Ning & Maosheng Li, 2022. "Modeling Pedestrian Detour Behavior By-Passing Conflict Areas," Sustainability, MDPI, vol. 14(24), pages 1-17, December.
    18. Wang, Shuaian & Zhang, Wei & Qu, Xiaobo, 2018. "Trial-and-error train fare design scheme for addressing boarding/alighting congestion at CBD stations," Transportation Research Part B: Methodological, Elsevier, vol. 118(C), pages 318-335.
    19. Lili Lu, A. & Gang Ren, B. & Wei Wang, C. & Ching-Yao Chan, D., 2015. "Application of SFCA pedestrian simulation model to the signalized crosswalk width design," Transportation Research Part A: Policy and Practice, Elsevier, vol. 80(C), pages 76-89.
    20. Haghani, Milad & Sarvi, Majid & Shahhoseini, Zahra, 2019. "When ‘push’ does not come to ‘shove’: Revisiting ‘faster is slower’ in collective egress of human crowds," Transportation Research Part A: Policy and Practice, Elsevier, vol. 122(C), pages 51-69.

    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:rom:mrpase:v:5:y:2013:i:4:p:5-18. 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: Colesca Sofia (email available below). General contact details of provider: https://edirc.repec.org/data/ccasero.html .

    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.