The Effects of Multiple Factors on Elderly Pedestrians’ Speed Perception and Stopping Distance Estimation of Approaching Vehicles
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Univ Arizona, Dept Syst & Ind EngnIssue Date
2020-06-30
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Shi, J., Wu, C., & Qian, X. (2020). The Effects of Multiple Factors on Elderly Pedestrians’ Speed Perception and Stopping Distance Estimation of Approaching Vehicles. Sustainability, 12(13), 5308.Journal
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© 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).Collection Information
This item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at repository@u.library.arizona.edu.Abstract
To make safe road-crossing decisions, it is necessary for pedestrians to accurately estimate the speed and stopping distance of approaching vehicles. Accordingly, the objective of our study was to examine the effects of multiple factors, such as weather conditions, context time (day or night), and illuminance of the roads, on older pedestrians' (>60 years old) speed perception and stopping distance estimation of approaching vehicles. The participants in this study included 48 older participants who were asked to estimate the speed and stopping distance of approaching vehicles based on 12 s video clips that were selected from natural conditions. The results revealed that actual speeds, weather, context time, and lighting conditions played important roles in the performance of the participants. Compared with young adults, older pedestrians were found to have smaller accurate estimation intervals that varied by multidimensional influencing factors and thus resulted in missing road-crossing opportunities at lower vehicles' speeds and increasing road-crossing dangers at higher speeds. The older pedestrians' performance with respect to speed perception and stopping distance estimation is modeled using a regression model with a complex level of tasks. These models can be used by engineers when establishing speed limits and lighting conditions in the areas with senior residents.Note
Open access journalISSN
2071-1050EISSN
2071-1050Version
Final published versionae974a485f413a2113503eed53cd6c53
10.3390/su12135308
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Except where otherwise noted, this item's license is described as © 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).