PHYSIOLOGICAL AND PERCEPTUAL EVALUATION OF RIDING COMFORT IN MOUNTAINOUS RAILWAYS
Keywords:
Mountain Railways, Riding Comfort, Physiological Assessment, Subjective Evaluation, Tourism TransportationAbstract
This study investigates riding comfort in mountainous tourism rail transit by integrating subjective passenger feedback with objective physiological and environmental data. Using the Lijiang Yulong Snow Mountain line as a case study, the research identifies key factors influencing passenger comfort and proposes strategies for improvement. Physiological signals, including electrocardiography (ECG), electromyography (EMG), and skin conductance, were recorded alongside environmental parameters such as vibration, noise, and altitude. Factor analysis revealed three significant components: physical comfort, environmental adaptability, and service experience. High-altitude sections above 3000 m led to an 18% reduction in heart rate variability (HRV) (p < 0.01) and were strongly associated with passenger fatigue. Sharp curves with a radius below 150 m increased muscle activity by 22% (p < 0.001). The results suggest that multi-faceted evaluation of ride comfort in mountainous rail should combine passenger perception with environmental and physiological data like HRV, EMG, and skin conductance. Targeted strategies, including adaptive suspension systems and altitude-adjustive seating, are proposed to improve comfort in complex terrains. Beyond the case of Lijiang, the results provide practical insights for the design, operation, and management of tourism rail systems in other Asian mountainous regions, thereby supporting sustainable tourism development and enhancing passenger-centered travel experiences.
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References
Allen, J. (2007). Photoplethysmography and its application in clinical physiological measurement. Physiological Measurement, 28(3), R1–R39.
Boucsein, W. (2012). Electrodermal activity (2nd ed.). New York: Springer.
Buchheit, M. (2014). Monitoring training status with HR measures: do all roads lead to Rome? Frontiers in Physiology, 5, 73.
Choocharukul, K., & Sriroongvikrai, K. (2013). Multivariate analysis of customer satisfaction: A case study of Bangkok’s Mass Rapid Transit (MRT) passengers. Journal of the Eastern Asia Society for Transportation Studies, 10, 1258–1269.
Clancy, E., Morin, E., & Merletti, R. (2002). Sampling, noise-reduction, and amplitude estimation issues in surface electromyography. Journal of Electromyography and Kinesiology, 12(1), 1–16.
Critchley, H. (2002). Electrodermal responses: What happens in the brain. The Neuroscientist, 8(2), 132–142.
Dawson, M., Schell, A., & Filion, D. (2007). The electrodermal system. In J. Cacioppo, L. Tassinary, & G. Berntson (eds.). Handbook of Psychophysiology (3rd ed., pp. 159–181). Cambridge University Press.
De Luca, C. (2006). Electromyography. Encyclopedia of Medical Devices and Instrumentation, 2, 98–109.
Fan, C., Lin, Y., Lin, S., Li, Y., Wu, F., Xiong, X., … & Peng, Y. (2022). Influencing factors and mechanism of high-speed railway passenger overall comfort: Insights from source functional brain network and subjective report. Frontiers in Public Health, 10, 993172.
Frost, J. (n.d.). Shapiro-Wilk normality test. Retrieved from https://statisticsbyjim.com/glossary/shapiro-wilk-normality-test.
Heathers, J. (2014). Everything Hertz: Methodological issues in short-term frequency-domain HRV. Frontiers in Physiology, 5, 177.
Laborde, S., Mosley, E., & Thayer, J. (2017). Heart rate variability and cardiac vagal tone in psychophysiological research Recommendations for experiment planning, data analysis, and data reporting. Frontiers in Psychology, 8, 213.
Lieophairot, C., & Rojniruttikul, N. (2024). Enhancing the Passenger Experience: Investigating Service Quality, Image, and Motivation Factors for Thailand’s Train Transport Sector. Journal of System and Management Sciences, 14(11), 275-294.
Merletti, R., & Farina, D. (2016). Surface electromyography: Physiology, engineering, and applications (2nd ed.). New York: Institute of Electrical and Electronics Engineers.
Peng, Y., Lin, Y., Fan, C., Xu, Q., Xu, D., Yi, S., … & Wang, K. (2022). Passenger overall comfort in high-speed railway environments based on EEG: Assessment and degradation mechanism. Building and Environment, 210, 108711.
Setz, C., Arnrich, B., Schumm, J., Marca, R., Tröster, G., & Ehlert, U. (2010). Discriminating stress from cognitive load using a wearable EDA device. IEEE Transactions on Information Technology in Biomedicine, 14(2), 410–417.
Shaffer, F., & Ginsberg, J. (2017). An overview of heart rate variability metrics and norms. Frontiers in Public Health, 5, 258.
Tandamrong, D., & Laphet, J. (2025). Exploring the influence of green mindset on passengers’ intentions toward sustainable air travel: Evidence from Thailand. Sustainability, 17(16), 7254.
Thayer, F., Ahs, F., Fredrikson, M., Sollers, J., & Wager, T. (2012). A meta-analysis of heart rate variability and neuroimaging studies: Implications for heart rate variability as a marker of stress and health. Neuroscience & Biobehavioral Reviews, 36(2), 747–756.
Tolkach, D., Chon, K., & Xiao, H. (2016). Asia Pacific Tourism Trends: Is the Future Ours to See?. Asia Pacific Journal of Tourism Research, 21(10), 1071-1084.
Ueasangkomsate, P. (2019). Service quality of public road passenger transport in Thailand. Kasetsart Journal of Social Sciences, 40(1), 74–81.
Wawryszczuk, R., & Kardas-Cinal, E. (2025). Impact of environmental factors on passenger ride comfort. Applied Sciences, 15(4), 1986.
Wikipedia. (2025). Kolmogorov–Smirnov test. Retrieved from https://en.wikipedia.org/wiki/Kolmogorov%E2%80%93Smirnov_test
Zou, Q., Xia, Y., Ran, X., Gou, X., & Feng, J. (2025). Classification of mountain-based rail transit stations and analysis of passenger flow influencing mechanisms. PLoS One, 20(5), e0323937.
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