Analysis of distracted pedestrians’ waiting time: Head-Mounted Immersive Virtual Reality application
DOI:
https://doi.org/10.17815/CD.2020.32Keywords:
pedestrian, crossing waiting time, proportional hazard model, immersive virtual realityAbstract
This paper analyzes the distracted pedestrians’ waiting time before crossing the road in three conditions: 1) not distracted, 2) distracted with a smartphone and 3) distracted with a smartphone in the presence of virtual flashing LED lights on the crosswalk as a safety measure. For the means of data collection, we adapted an in-house developed virtual immersive reality environment (VIRE). A total of 42 volunteers participated in the experiment. Participants’ positions and head movements were recorded and used to calculate walking speeds, acceleration and deceleration rates, surrogate safety measures, time spent playing smartphone game, etc. After a descriptive analysis on the data, the effects of these variables on pedestrians’ waiting time are analyzed by employing a cox proportional hazard model. Several factors were identified as having impact on waiting time. The results show that an increase in initial walk speed, percentage of time the head was oriented toward smartphone during crossing, bigger minimum missed gaps and unsafe crossings resulted in shorter waiting times. On the other hand, an increase in the percentage of time the head was oriented toward smartphone during waiting time, crossing time and maze solving time, means longer waiting times for participants.References
Transport Canada, “Un bref aperçu des usagers de la route vulnérables qui sont victimes d’accidents
mortels,” 2010.
Transport Canada, “Canadian Motor Vehicle Traffic Collision Statistics: 2005,” 2005.
Transport Canada, “Canadian Motor Vehicle Traffic Collision Statistics: 2015,” 2015.
M. Brosseau, S. Zangenehpour, N. Saunier, and L. Miranda-Moreno, "The impact of waiting time and
other factors on dangerous pedestrian crossings and violations at signalized intersections: A case study in
Montreal," Transportation research part F: traffic psychology and behaviour, vol. 21, pp. 159-172, 2013.
S. E. Banducci, N. Ward, J. G. Gaspar, K. R. Schab, J. A. Crowell, H. Kaczmarski, A. F. Kramer, “The
effects of cell phone and text message conversations on simulated street crossing,” Human factors, vol. 58,
no. 1, pp. 150–162, 2016.
M. I. B. Lin and Y.P. Huang, “The impact of walking while using a smartphone on pedestrians’
awareness of roadside events,” Accident Analysis and Prevention, vol. 101, pp. 87–96, 2017.
B. Farooq, E. Cherchi , A. Sobhani , “Virtual Immersive Reality for Stated Preference Travel Behaviour
Experiments: A Case study of Autonomous Vehicles on Urban Roads,” Transportation Research Record
: Journal of Transportation Research Board, vol. 2672, pp. 35-45, 2018.
M. M. Hamed, “Analysis of Pedestrians’ behavior at pedestrian crossings,” Safety Science, vol. 38(1),
pp. 63-82, 2001.
O. Keegan, M. O’Mahony, “Modifying pedestrian behaviour,” Transportation Research Part A: Policy
and Practice, vol. 37 (10), pp. 889-901, 2003.
B, LI, “A model of pedestrians' intended waiting times for street crossings at signalized intersections,”
Transportation Research Part B: Methodological, vol. 51, pp. 17-28, 2013.
M. J. O’Neill, “Effects of familiarity and plan complexity on wayfinding in simulated buildings,”
Journal of Environmental Psychology, vol. 12, no. 4, pp. 319–327, 1992.
R. A. Ruddle, S. J. Payne, and D. M. Jones, “Navigating buildings in ‘desk-top’ virtual environments:
Experimental investigations using extended navigational experience,” Journal Experimental Psychology:
Applied, vol. 3, no. 2, pp. 143–159, 1997.
A. Sobhani, B. Farooq “Impact of smartphone distraction on pedestrians’ crossing behaviour: An
application of head-mounted immersive virtual reality”, Transportation Research Part F: Psychology and
Behaviour, pp. 228-241, 2018.
T. Therneau, P. Grambsch, “Modeling Survival Data: Extending the Cox Model,” Springer, 2000.
T. Therneau, “A Package for Survival Analysis in S,” version 2.38, Available:
https://CRAN.R-project.org/package=survival, 2015.
M. Zaki H and T. Sayed, “Exploring Walking Gait Features for the Automated Recognition of
Distracted Pedestrians,” IET Intelligent. Transport Systems, vol. 10, no. 2, pp. 106-113, 2016.
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Copyright (c) 2020 Arash Kalatian, Anae Sobhani, Bilal Farooq
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