Citation

Kim D, Park K. J. Am. Coll. Health 2021; ePub(ePub): ePub.

Copyright

(Copyright © 2021, Informa - Taylor and Francis Group)

DOI

10.1080/07448481.2021.1967358

PMID

unavailable

Abstract

OBJECTIVE: To identify factors that contribute to near-miss collisions between pedestrians and personal transportation devices (PTDs) in a university campus using a novel data collection method, unmanned aerial vehicle (UAV). PARTICIPANTS: A total of 3,349 pedestrians and 173 PTD riders were detected through UAV observations.

METHODS: The researchers employed UAV technology to capture and geocode the interactions and behavior of pedestrians and PTD riders. Then, a multilevel logistic regression model examined factors that contribute to near-miss collisions between pedestrians and PTDs.

RESULTS: The model outputs indicate that higher speed, non-bicycle PTDs (eg, skateboard and scooter), and some preventive actions, like reducing speed, deviating, and weaving, increase the probability of a PTD rider getting involved in a near-miss collision.

CONCLUSIONS: Findings can guide campus planners to redesign the streets as a safe environment for all transportation modes and implement appropriate regulations and education programs, especially for non-bicycle PTD riders.

Language: en

Keywords

Bicycle; pedestrian; near-miss collision; personal transportation devices (PTDs); unmanned aircraft systems (UAS)