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Study on the stress response of young passengers in different subway passenger densities

Author

Listed:
  • Xiaofei Lin

    (Anhui University of Technology)

  • Shouxin Song

    (Beijing Jiaotong University)

  • Pengfei Yu

    (Ocean University of China)

  • Pengwei Yuan

    (University of Jinan)

Abstract

In this study, we set up a virtual subway car and analyzed the stress response of young passengers in different compartments. A total of 10 volunteers participated in the experimental study. We measured their diastolic blood pressures, systolic blood pressures, and heart rates, from a car density of one person per square meter to a density of 10 persons per square meter, using 37° sport wristbands. The results show that the participants’ mean, minimum, and maximum heart rates were within the normal range, but the ratio of their mean to their maximum heart rate was 73.69%, a level that would have an impact on human health. Their mean, minimum, and maximum diastolic blood pressures and systolic blood pressures were within the normal range. Passenger density had no significant effect on diastolic blood pressure, systolic blood pressure, or heart rate (p

Suggested Citation

  • Xiaofei Lin & Shouxin Song & Pengfei Yu & Pengwei Yuan, 2020. "Study on the stress response of young passengers in different subway passenger densities," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 11(5), pages 899-908, October.
    • Handle: RePEc:spr:ijsaem:v:11:y:2020:i:5:d:10.1007_s13198-020-01013-7
    DOI: 10.1007/s13198-020-01013-7
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    References listed on IDEAS

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    1. Cox, Tom & Houdmont, Jonathan & Griffiths, Amanda, 2006. "Rail passenger crowding, stress, health and safety in Britain," Transportation Research Part A: Policy and Practice, Elsevier, vol. 40(3), pages 244-258, March.
    2. Lee, Keumsook & Jung, Woo-Sung & Park, Jong Soo & Choi, M.Y., 2008. "Statistical analysis of the Metropolitan Seoul Subway System: Network structure and passenger flows," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(24), pages 6231-6234.
    3. Jie Zhou & Zhong-Ke Shi, 2015. "Lattice hydrodynamic model for bidirectional pedestrian flow with the consideration of pedestrian density difference," International Journal of Modern Physics C (IJMPC), World Scientific Publishing Co. Pte. Ltd., vol. 26(08), pages 1-20.
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