Case Studies
Nov 15, 2022

Effect of Technological Distractions on Pedestrian Safe-Crossing Performance during Mixed Pedestrian–Bicycle Flow Overlapping with Turning Vehicles: A Case Study of Hangzhou, China

Publication: Journal of Transportation Engineering, Part A: Systems
Volume 149, Issue 1

Abstract

Crashes involving pedestrians are most likely to occur when the pedestrian is crossing the road. In the particular context of road traffic systems in China, with frequent on-crosswalk cycling and pedestrian green signals overlapping with vehicle right- and left-turn green signals, walking on a signalized intersection crosswalk seems much more challenging. As such, pedestrians need to be more cautious and perform properly. The present study designed tasks for safe crossing at this form of intersection and, using video cameras, explored the performance of pedestrians. Taking smartphones as source of distraction, comparisons were made between distracted and nondistracted pedestrians. Of the phone use rate of 20.3% while crossing, 13.4% were visual-manual interactions, 3.5% were hand-free phones, and 3.4% were hand-held phones. For both genders, pedestrians who crossed while visually-manually interacting with a mobile or talking/listening on a mobile were less likely to glance before initiating crossing, less likely to look at traffic while crossing, less likely to avoid on-crosswalk opposite pedestrians and bicycles, and less likely to make eye contact with right/left-turning drivers. Surprisingly, female pedestrians who were texting took longer to react to the pedestrian green signal than males who were texting. Findings of this study suggest that distraction while crossing roads exposes pedestrians to a high risk of accident. Hence, to improve pedestrian safety, the authors advise relevant actions such as unsafe-crossing warning technologies; pedestrian, bicyclist, and driver education; and law enforcement. Detailed advice is found in the summary section at the end of the paper.

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Data Availability Statement

Some or all data, models, or code that support the findings of this study are available from the corresponding author upon reasonable request.

Acknowledgments

This study was supported by “Pioneer” and “Leading Goose” R&D Program of Zhejiang (2022C01042), the National Natural Science Foundation of China (Grant No. 92046011), Center for Balance Architecture Zhejiang University, and Alibaba-Zhejiang University Joint Research Institute of Frontier Technologies.

References

Bungum, T. J., C. Day, and L. J. Henry. 2005. “The association of distraction and caution displayed by pedestrians at a lighted crosswalk.” J. Commun. Health 30 (4): 269–279. https://doi.org/10.1007/s10900-005-3705-4.
Chen, S., J. Xing, and Y. Cao. 2017. “The Impact of Waiting Time on Pedestrian Violations at Signalized Intersections.” Civ. Eng. Urban Plann. Int. J. 4 (2): 1–13. https://doi.org/10.5121/civej.2017.4201.
Da Silva, M. P., J. D. Smith, and W. G. Najm. 2003. Analysis of pedestrian crashes. Washington, DC: National Highway Traffic Safety Administration.
FHWA (Federal Highway Administration). 2004. Manual on uniform traffic control devices for streets and highways. 2003 ed. Washington, DC: FHWA.
Gruden, C., I. Ištoka Otković, and M. Šraml. 2021. “Safety analysis of young pedestrian behavior at signalized intersections: An eye-tracking study.” Sustainability 13 (8): 4419. https://doi.org/10.3390/su13084419.
Harbluk, J., and Y. Noy. 2001. The impact of cognitive distraction on driver visual behavior and vehicle control. Washington, DC: National Highway Traffic Safety Administration.
Hatfield, J., and S. Murphy. 2007. “The effects of mobile phone use on pedestrian crossing behaviour at signalized and unsignalised intersections.” Accid. Anal. Prev. 39 (4): 197–205. https://doi.org/10.1016/j.aap.2006.07.001.
Horberry, T., et al. 2019. “Pedestrian smartphone distraction: Prevalence and potential severity.” Transp. Res. Part F: Traffic Psychol. Behav. 60 (Jan): 515–523. https://doi.org/10.1016/j.trf.2018.11.011.
Hu, L., J. Ou, J. Huang, F. Wang, Y. Wang, B. Ren, and L. Zhou. 2021. “Safety evaluation of pedestrian-vehicle interaction at signalized intersections in Changsha, China.” J. Transp. Saf. Secur. 2021 (1): 1–26. https://doi.org/10.1080/19439962.2021.1960662.
Jiang, K., F. Ling, Z. Feng, C. Ma, W. Kumfer, C. Shao, and K. Wang. 2018. “Effects of mobile phone distraction on pedestrians’ crossing behavior and visual attention allocation at a signalized intersection: An outdoor experimental study.” Accid. Anal. Prev. 115 (Mar): 170–177. https://doi.org/10.1016/j.aap.2018.03.019.
Liu, Y., R. Alsaleh, and T. Sayed. 2021. “Modeling the influence of mobile phone use distraction on pedestrian reaction times to green signals: A multilevel mixed-effects parametric survival model.” Transp. Res. Part F: Traffic Psychol. Behav. 81 (54): 115–129. https://doi.org/10.1016/j.trf.2021.05.020.
Lyu, N., et al. 2022. “Using naturalistic driving data to identify driving style based on longitudinal driving operation conditions.” J. Intell. Connected Vehicles 5 (1): 17–35. https://doi.org/10.1108/JICV-07-2021-0008.
Mwakalonge, J., S. Siuhi, and J. White. 2015. “Distracted walking: Examining the extent to pedestrian safety problems.” J. Traffic Transp. Eng. 2 (5): 327–337. https://doi.org/10.1016/j.jtte.2015.08.004.
Neider, M. B., J. S. McCarley, J. A. Crowell, H. Kaczmarski, and A. F. Kramer. 2010. “Pedestrians, vehicles, and cell phones.” Accid. Anal. Prev. 42 (Oct): 589–594. https://doi.org/10.1016/j.aap.2009.10.004.
Osborne, R., et al. 2020. “Pedestrian distraction from smartphones: An end-user perspective on current and future countermeasures.” Transp. Res. Part F: Traffic Psychol. Behav. 73 (1): 348–361. https://doi.org/10.1016/j.trf.2020.07.007.
Pan, C., J. Xu, and J. Fu. 2021. “Effect of gender and personality characteristics on the speed tendency based on advanced driving assistance system (ADAS) evaluation.” J. Intell. Connected Vehicles 4 (1): 28–37. https://doi.org/10.1108/JICV-04-2020-0003.
Pesic, D., B. Antić, D. Glavić, and M. Milenković. 2016. “The effects of mobile phone use on pedestrian crossing behaviour at unsignalized intersections—Models for predicting unsafe pedestrians behavior.” Saf. Sci. 82 (Feb): 1–8. https://doi.org/10.1016/j.ssci.2015.08.016.
Pickrell, T. M., and T. J. Ye. 2010. Driver electronic device use observation protocol. Washington, DC: USDOT.
Ren, G., Z. Zhou, W. Wang, Y. Zhang, and W. Wang. 2011. “Crossing behaviors of pedestrians at signalized intersections: Observational study and survey in China.” Transp. Res. Rec. J. Transp. Res. Board 2264 (1): 65–73. https://doi.org/10.3141/2264-08.
Russo, B. J., E. James, C. Y. Aguilar, and E. J. Smaglik. 2018. “Pedestrian behavior at signalized intersection crosswalks: Observational study of factors associated with distracted walking, pedestrian violations, and walking speed.” Transp. Res. Rec. J. Transp. Res. Board 2672 (35): 1–12. https://doi.org/10.1177/0361198118759949.
Tapiro, H., T. Oron-Gilad, and Y. Parmet. 2020. “Pedestrian distraction: The effects of road environment complexity and age on pedestrian’s visual attention and crossing behavior.” J. Saf. Res. 72 (3): 101–109. https://doi.org/10.1016/j.jsr.2019.12.003.
Thompson, L. L., F. P. Rivara, and R. C. Ayyagari. 2013. “Impact of social and technological distraction on pedestrian crossing behavior: An observational study.” Inj. Prev. 19 (4): 232–237. https://doi.org/10.1136/injuryprev-2012-040601.
Transportation Research Board. 2000. Highway capacity manual. 5th ed. Washington, DC: Transportation Research Board.
Wei, Y., C. Zhang, B. Zhou, F. Chen, and H. Zhang. 2017. “The mobile phone use behavior and its effect on pedestrian safety at signalized intersections in China.” In Proc., 2017 4th Int. Conf. on Transportation Information and Safety (ICTIS), 225–231. New York: IEEE.
Wu, Y., Y. Guo, and W. Yin. 2021. “Real time safety model for pedestrian red-light running at signalized intersections in China.” Sustainability 13 (4): 1695. https://doi.org/10.3390/su13041695.
Zhou, Z., S. Liu, W. Xu, Z. Pu, S. Zhang, and Y. Zhou. 2019. “Impacts of mobile phone distractions on pedestrian crossing behavior at signalized intersections: An observational study in China.” Adv. Mech. Eng. 11 (4): 1687814019841838. https://doi.org/10.1177/1687814019841838.

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Published In

Go to Journal of Transportation Engineering, Part A: Systems
Journal of Transportation Engineering, Part A: Systems
Volume 149Issue 1January 2023

History

Received: Jun 24, 2022
Accepted: Sep 14, 2022
Published online: Nov 15, 2022
Published in print: Jan 1, 2023
Discussion open until: Apr 15, 2023

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Authors

Affiliations

Ph.D. Candidate, Institute of Intelligent Transportation Systems, College of Civil Engineering and Architecture, Zhejiang Univ., 866 Yuhangtang Rd., Hangzhou 310058, China; Center for Balance Architecture, Zhejiang Univ., 148 Tianmushan Rd., Hangzhou 310058, China; Alibaba-Zhejiang Univ. Joint Research Institute of Frontier Technologies, Hangzhou 310058, China. ORCID: https://orcid.org/0000-0002-4968-0057. Email: [email protected]
Haihang Han [email protected]
Professor, Zhejiang Scientific Research Institute of Transport, 705 Dalongjuwu Rd., Hangzhou 310000, China. Email: [email protected]
Professor, Institute of Intelligent Transportation Systems, College of Civil Engineering and Architecture, Zhejiang Univ., 866 Yuhangtang Rd., Hangzhou 310058, China; Zhongyuan Institute, Zhejiang Univ., 6 Changchun Rd., Zhengzhou 450000, China; Pengcheng Laboratory, 2 Xinkeyi Rd., Shenzhen 518000, China (corresponding author). ORCID: https://orcid.org/0000-0001-6110-0783. Email: [email protected]

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