IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v12y2020i19p7863-d417967.html
   My bibliography  Save this article

Exploring Walking Behavior in the Streets of New York City Using Hourly Pedestrian Count Data

Author

Listed:
  • Jae Min Lee

    (School of Architecture, University of Ulsan, Ulsan 44610, Korea)

Abstract

This paper explores hourly automated pedestrian count data of seven locations in New York City to understand pedestrian walking patterns in cities. Due to practical limitations, such patterns have been studied conceptually; few researchers have explored walking as a continuous, long-term activity. Adopting an automated pedestrian counting method, we documented and observed people walking on city streets and found that unique pedestrian traffic patterns reflect land use, development intensity, and neighborhood characteristics. We observed a threshold of thermal comfort in outdoor activities. People tend to seek shade and avoid solar radiation stronger than 1248 Wh/m 2 at an average air temperature of 25 °C. Automated collection of detailed pedestrian count data provides a new opportunity for urban designers and transportation planners to understand how people walk and to improve our cities to be less dependent on the automobile.

Suggested Citation

  • Jae Min Lee, 2020. "Exploring Walking Behavior in the Streets of New York City Using Hourly Pedestrian Count Data," Sustainability, MDPI, vol. 12(19), pages 1-16, September.
  • Handle: RePEc:gam:jsusta:v:12:y:2020:i:19:p:7863-:d:417967
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/12/19/7863/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2071-1050/12/19/7863/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Reid Ewing & Robert Cervero, 2010. "Travel and the Built Environment," Journal of the American Planning Association, Taylor & Francis Journals, vol. 76(3), pages 265-294.
    2. Robin, Th. & Antonini, G. & Bierlaire, M. & Cruz, J., 2009. "Specification, estimation and validation of a pedestrian walking behavior model," Transportation Research Part B: Methodological, Elsevier, vol. 43(1), pages 36-56, January.
    3. 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.
    4. repec:cdl:uctcwp:qt7cn9m1qz is not listed on IDEAS
    5. repec:cdl:uctcwp:qt2z79q67d is not listed on IDEAS
    6. Fukuyo, Kazuhiro, 2006. "Application of computational fluid dynamics and pedestrian-behavior simulations to the design of task-ambient air-conditioning systems of a subway station," Energy, Elsevier, vol. 31(5), pages 706-718.
    7. Serge P. Hoogendoorn & W. Daamen, 2005. "Pedestrian Behavior at Bottlenecks," Transportation Science, INFORMS, vol. 39(2), pages 147-159, May.
    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. Yuanyuan Guo & Linchuan Yang & Wenke Huang & Yi Guo, 2020. "Traffic Safety Perception, Attitude, and Feeder Mode Choice of Metro Commute: Evidence from Shenzhen," IJERPH, MDPI, vol. 17(24), pages 1-20, December.
    2. Hernando José Bolívar-Anillo & Shersy Vega Benites & Giovanna Reyes Almeida & Samuel de Jesús Ortega Llanos & Valentina Taba-Charris & Keyla Andrea Acuña-Ruiz & Byron Standly Reales Vargas & Paula Fer, 2025. "Addressing Increased Temperatures in Cities: Determination of Pedestrian Routes with Thermal Comfort in Barranquilla, Colombia," Sustainability, MDPI, vol. 17(11), pages 1-17, June.
    3. Avital Angel & Achituv Cohen & Sagi Dalyot & Pnina Plaut, 2023. "Impact of COVID-19 policies on pedestrian traffic and walking patterns," Environment and Planning B, , vol. 50(5), pages 1178-1193, June.

    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. 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.
    2. 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.
    3. 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.
    4. 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.
    5. Hänseler, Flurin S. & Bierlaire, Michel & Farooq, Bilal & Mühlematter, Thomas, 2014. "A macroscopic loading model for time-varying pedestrian flows in public walking areas," Transportation Research Part B: Methodological, Elsevier, vol. 69(C), pages 60-80.
    6. He, Mengchen & Wang, Qiao & Chen, Juan & Xu, Shiwei & Ma, Jian, 2023. "Modeling pedestrian walking behavior in the flow field with moving walkways," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 619(C).
    7. Li, Maosheng & Shu, Panpan & Xiao, Yao & Wang, Pu, 2021. "Modeling detour decision combined the tactical and operational layer based on perceived density," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 574(C).
    8. Haghani, Milad, 2021. "The knowledge domain of crowd dynamics: Anatomy of the field, pioneering studies, temporal trends, influential entities and outside-domain impact," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 580(C).
    9. Haghani, Milad & Sarvi, Majid, 2017. "Stated and revealed exit choices of pedestrian crowd evacuees," Transportation Research Part B: Methodological, Elsevier, vol. 95(C), pages 238-259.
    10. Jeongyun Kim & Sehyun Tak & Michel Bierlaire & Hwasoo Yeo, 2020. "Trajectory Data Analysis on the Spatial and Temporal Influence of Pedestrian Flow on Path Planning Decision," Sustainability, MDPI, vol. 12(24), pages 1-16, December.
    11. Sobhana, Karthika P. & Choubey, Nipun & Verma, Ashish, 2023. "Modelling and simulating the leader–follower behaviour of pedestrians in unidirectional flow," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 623(C).
    12. Jiang, Yan-Qun & Zhang, Wei & Zhou, Shu-Guang, 2016. "Comparison study of the reactive and predictive dynamic models for pedestrian flow," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 441(C), pages 51-61.
    13. 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.
    14. 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.
    15. Milad Haghani & Majid Sarvi & Zahra Shahhoseini & Maik Boltes, 2016. "How Simple Hypothetical-Choice Experiments Can Be Utilized to Learn Humans’ Navigational Escape Decisions in Emergencies," PLOS ONE, Public Library of Science, vol. 11(11), pages 1-24, November.
    16. Haghani, Milad & Sarvi, Majid & Shahhoseini, Zahra, 2015. "Accommodating taste heterogeneity and desired substitution pattern in exit choices of pedestrian crowd evacuees using a mixed nested logit model," Journal of choice modelling, Elsevier, vol. 16(C), pages 58-68.
    17. Huang, Rong & Zhao, Xuan & Zhou, Chenyu & Kong, Lingchen & Liu, Chengqing & Yu, Qiang, 2022. "Static floor field construction and fine discrete cellular automaton model: Algorithms, simulations and insights," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 606(C).
    18. Yuki Oyama, 2023. "Global path preference and local response: A reward decomposition approach for network path choice analysis in the presence of locally perceived attributes," Papers 2307.08646, arXiv.org.
    19. Oyama, Yuki, 2024. "Global path preference and local response: A reward decomposition approach for network path choice analysis in the presence of visually perceived attributes," Transportation Research Part A: Policy and Practice, Elsevier, vol. 181(C).
    20. Nicolas, Alexandre & Bouzat, Sebastián & Kuperman, Marcelo N., 2017. "Pedestrian flows through a narrow doorway: Effect of individual behaviours on the global flow and microscopic dynamics," Transportation Research Part B: Methodological, Elsevier, vol. 99(C), pages 30-43.

    More about this item

    Keywords

    ;
    ;
    ;
    ;

    Statistics

    Access and download statistics

    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:gam:jsusta:v:12:y:2020:i:19:p:7863-:d:417967. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    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.