A large-scale controlled experiment on pedestrian walking behavior involving individuals with disabilities. (July 2017)

• Record Type: Journal Article
• Authors: Sharifi, Mohammad Sadra; Christensen, Keith; Chen, Anthony; Stuart, Daniel; Kim, Yong Seog; Chen, YangQuan
• Is Part Of: Travel behaviour and society. Volume 8(2017)
• Page Start: 14
• Page End: 25
• Publication Date: 2017-07
• Subjects: Individuals with disabilities -- Pedestrian -- Behavior -- Crowds -- Research methods; Transportation -- Periodicals; Population geography -- Periodicals; 303.48305
• DOI: 10.1016/j.tbs.2017.03.003
• Languages: English
• ISSNs: 2214-367X

Abstract

Highlights: Complex geometries significantly reduce heterogeneous populations' walking speed. Individuals with disabilities need more space to maintain their preferred speeds. Individuals with disabilities' walking speed is lower than those without disabilities. Greater spacing is maintained within groups including individuals using wheelchairs. The findings will help policy professionals provide better performance measures. Abstract: It is imperative to design walking facility infrastructures to accommodate the needs of all pedestrian, including individuals with disabilities. Unfortunately, individuals with disabilities are often overlooked due to the lack of available data. The purpose of this study was to measure the individual pedestrian walking behaviors of individuals with disabilities through controlled video tracking experiments of heterogeneous crowds in various walking facilities; including passageways, right and oblique corners, doorways, bottlenecks, and stairs. The goal of this paper is to provide an overview of conducting experimental research on pedestrian walking behavior involving individuals with and without disabilities, including automated video tracking methods, data collection, logistical issues, processing methods, and lessons learned from conducting a large-scale study. The findings support future large-scale experiments related to the pedestrian walking behavior of individuals with disabilities. The results can be used to calibrate and validate pedestrian traffic flow models capturing the behaviors and interactions of crowds which include different types of individuals with disabilities.