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Stated and revealed exit choices of pedestrian crowd evacuees

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  • Haghani, Milad
  • Sarvi, Majid

Abstract

Understanding fundamental behavioural features regulating the escape wayfinding decisions of pedestrian humans in built environments has major implications for the safety planning and the risk-analysis of crowded public facilities. In contrast to the vast interest invested in modelling the momentary responses of evacuees to their immediate surroundings (i.e. the collision-avoidance models), their global navigation behaviour is poorly understood albeit believed to be a major determinant of the accuracy of the crowd simulation models. The primary challenge arises from the scarcity of reliable data suitable for modelling purposes causing the experimental knowledge in the field lagging substantially behind the corresponding model developments. Observations derived from fully natural emergency contexts (in the form of modelling material) are rare and collecting data in realistic experimental settings poses its own major challenges. Only few experimental modelling attempts have been reported thus far in relation with this problem primarily using the stated-choice (SC) methods. Modelling based on revealed choices (RC), however, has remained absent in this context leaving the findings of the SC experiments mostly unverified. It is still unclear whether we can reliably learn from the wayfinding choices made in virtually visualised environments without the decision-makers interacting with real individuals and the physical elements of the environment as they do in the real-world settings. Furthermore, the extent to which the findings of these experiments are specific to the particular characteristics of the environment visualised in the experiments is also unclear.

Suggested Citation

  • 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.
  • Handle: RePEc:eee:transb:v:95:y:2017:i:c:p:238-259
    DOI: 10.1016/j.trb.2016.10.019
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    Cited by:

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    2. Haghani, Milad & Bliemer, Michiel C.J. & Rose, John M. & Oppewal, Harmen & Lancsar, Emily, 2021. "Hypothetical bias in stated choice experiments: Part II. Conceptualisation of external validity, sources and explanations of bias and effectiveness of mitigation methods," Journal of choice modelling, Elsevier, vol. 41(C).
    3. Haghani, Milad & Bliemer, Michiel C.J. & Rose, John M. & Oppewal, Harmen & Lancsar, Emily, 2021. "Hypothetical bias in stated choice experiments: Part I. Macro-scale analysis of literature and integrative synthesis of empirical evidence from applied economics, experimental psychology and neuroimag," Journal of choice modelling, Elsevier, vol. 41(C).
    4. Haghani, Milad & Bliemer, Michiel C.J. & Hensher, David A., 2021. "The landscape of econometric discrete choice modelling research," Journal of choice modelling, Elsevier, vol. 40(C).
    5. Kinateder, Max & Warren, William H., 2021. "Exit choice during evacuation is influenced by both the size and proportion of the egressing crowd," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 569(C).
    6. Haghani, Milad & Sarvi, Majid, 2018. "Hypothetical bias and decision-rule effect in modelling discrete directional choices," Transportation Research Part A: Policy and Practice, Elsevier, vol. 116(C), pages 361-388.
    7. Gao, Dong Li & Xie, Wei & Ming Lee, Eric Wai, 2022. "Individual-level exit choice behaviour under uncertain risk," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 604(C).
    8. Shahhoseini, Zahra & Sarvi, Majid, 2019. "Pedestrian crowd flows in shared spaces: Investigating the impact of geometry based on micro and macro scale measures," Transportation Research Part B: Methodological, Elsevier, vol. 122(C), pages 57-87.
    9. Shenhao Wang & Qingyi Wang & Jinhua Zhao, 2019. "Multitask Learning Deep Neural Networks to Combine Revealed and Stated Preference Data," Papers 1901.00227, arXiv.org, revised Aug 2019.
    10. Shatu, Farjana & Yigitcanlar, Tan & Bunker, Jonathan, 2019. "Objective vs. subjective measures of street environments in pedestrian route choice behaviour: Discrepancy and correlates of non-concordance," Transportation Research Part A: Policy and Practice, Elsevier, vol. 126(C), pages 1-23.
    11. Milad Haghani & Michiel C. J. Bliemer & John M. Rose & Harmen Oppewal & Emily Lancsar, 2021. "Hypothetical bias in stated choice experiments: Part II. Macro-scale analysis of literature and effectiveness of bias mitigation methods," Papers 2102.02945, arXiv.org.
    12. Can Liao & Kejun Zhu & Haixiang Guo & Jian Tang, 2019. "Simulation Research on Safe Flow Rate of Bidirectional Crowds Using Bayesian-Nash Equilibrium," Complexity, Hindawi, vol. 2019, pages 1-15, January.
    13. Meiying Jiang & Qibing Jin & Lisheng Cheng, 2019. "Effects of Ticket-Checking Failure on Dynamics of Pedestrians at Multi-Exit Inspection Points with Various Layouts," IJERPH, MDPI, vol. 16(5), pages 1-16, March.
    14. Banerjee, Arunabha & Das, Sanhita & Maurya, Akhilesh Kumar, 2024. "Behavioural characteristics influencing walking speed of pedestrians over elevated facilities: A case study of India," Transport Policy, Elsevier, vol. 147(C), pages 169-182.
    15. Arellana, J. & Garzón, L. & Estrada, J. & Cantillo, V., 2020. "On the use of virtual immersive reality for discrete choice experiments to modelling pedestrian behaviour," Journal of choice modelling, Elsevier, vol. 37(C).
    16. Liang, Mengdi & Xu, Jie & Jia, Limin & Qin, Yong, 2020. "An improved model of passenger merging in a Y-shaped passage," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 540(C).
    17. Xu, Chenchen & Luo, Yiyang & Fuellhart, Kurt & Shao, Quan & Witlox, Frank, 2023. "Modeling exit choice behavior in airplane emergency evacuations," Journal of Air Transport Management, Elsevier, vol. 112(C).
    18. 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).
    19. Haghani, Milad & Sarvi, Majid, 2019. "Laboratory experimentation and simulation of discrete direction choices: Investigating hypothetical bias, decision-rule effect and external validity based on aggregate prediction measures," Transportation Research Part A: Policy and Practice, Elsevier, vol. 130(C), pages 134-157.
    20. Haghani, Milad & Sarvi, Majid, 2017. "Social dynamics in emergency evacuations: Disentangling crowd’s attraction and repulsion effects," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 475(C), pages 24-34.
    21. Kayvan Aghabayk & Alireza Soltani & Nirajan Shiwakoti, 2022. "Investigating Pedestrians’ Exit Choice with Incident Location Awareness in an Emergency in a Multi-Level Shopping Complex," Sustainability, MDPI, vol. 14(19), pages 1-21, September.
    22. Vosough, Shaghayegh & Roncoli, Claudio, 2024. "Achieving social routing via navigation apps: User acceptance of travel time sacrifice," Transport Policy, Elsevier, vol. 148(C), pages 246-256.
    23. Haghani, Milad & Sarvi, Majid, 2018. "Crowd behaviour and motion: Empirical methods," Transportation Research Part B: Methodological, Elsevier, vol. 107(C), pages 253-294.
    24. Zhou, Zi-Xuan & Nakanishi, Wataru & Asakura, Yasuo, 2021. "Data-driven framework for the adaptive exit selection problem in pedestrian flow: Visual information based heuristics approach," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 583(C).
    25. Huang, Zhiren & Wang, Pu & Zhang, Fan & Gao, Jianxi & Schich, Maximilian, 2018. "A mobility network approach to identify and anticipate large crowd gatherings," Transportation Research Part B: Methodological, Elsevier, vol. 114(C), pages 147-170.

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