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Estimating pedestrian speed using aggregated literature data

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  • Bosina, Ernst
  • Weidmann, Ulrich

Abstract

Since about 80 years, human walking speed has been measured for different purposes. The comparability of the results of these measurements is low, as the walking speed is influenced by a vast amount of parameters and no standardised measurement conditions exist. This work describes the most important factors influencing walking speed based on existing literature and estimates their impact. For this purpose, all walking speed measurements available in the literature were collected and reviewed. Using this data, the parameter values for different influences were computed and grouped according to their strength, which enables to determine the most important measurement parameters in future walking speed experiments. In addition, standardised measurement conditions are proposed which would provide a baseline for future studies and thus enhance their scientific value. For each of these conditions average walking speeds are calculated and the significance of the walking speed differences was determined.

Suggested Citation

  • Bosina, Ernst & Weidmann, Ulrich, 2017. "Estimating pedestrian speed using aggregated literature data," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 468(C), pages 1-29.
    • Handle: RePEc:eee:phsmap:v:468:y:2017:i:c:p:1-29
    DOI: 10.1016/j.physa.2016.09.044
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    7. Wang, Xinjian & Liu, Zhengjiang & Wang, Jin & Loughney, Sean & Yang, Zaili & Gao, Xiaowei, 2021. "Experimental study on individual walking speed during emergency evacuation with the influence of ship motion," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 562(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. Dramane Sam Idris Kanté & Aissam Jebrane & Anass Bouchnita & Abdelilah Hakim, 2023. "Estimating the Risk of Contracting COVID-19 in Different Settings Using a Multiscale Transmission Dynamics Model," Mathematics, MDPI, vol. 11(1), pages 1-19, January.
    10. Shuqi Miao & Tinghao Li & Lili Zheng & Bowen Tan & Qianjun Ma, 2023. "Analysis of Factors Affecting Walking Speed Based on Natural Field Data: Considering the Attributes of Travelers and the Travel Environment," Sustainability, MDPI, vol. 15(14), pages 1-21, July.
    11. Huang, Shenshi & Wei, Ruichao & Lo, Siuming & Lu, Shouxiang & Li, Changhai & An, Chao & Liu, Xiaoxia, 2019. "Experimental study on one-dimensional movement of luggage-laden pedestrian," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 516(C), pages 520-528.
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    13. Sihui Long & Lingyun Meng & Jianrui Miao & Xin Hong & Francesco Corman, 2020. "Synchronizing Last Trains of Urban Rail Transit System to Better Serve Passengers from Late Night Trains of High-Speed Railway Lines," Networks and Spatial Economics, Springer, vol. 20(2), pages 599-633, June.
    14. Mondal, Satyajit & Gupta, Ankit, 2021. "Speed distribution for interrupted flow facility under mixed traffic," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 570(C).
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    Keywords

    Pedestrian; Walking speed;

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