Abstract
The opportunities for data collection in smart cities and communities provide new approaches for assessing risk of roadway components. This paper presents and compares two different methodological approaches for cycling safety assessment of objective and perceived risk. Objective risk was derived from speed and direction profiles collected with Global Navigation Satellite System (GNSS) and camera installed on an instrumented bicycle. Safety critical events between cyclists and other road users were identified and linked to five different roadway components. A panel of experts was asked to score the severity of the safety critical events using a Delphi process to reach consensus. To estimate the perceived risk, a web-based survey was provided to the city bicyclist community asking them to score the same five roadway components with a 4-point Likert scale. A comparison between perceived and objective risk classification of the roadway components showed a good agreement when only higher severity conflicts were considered. The research findings support the notion that it is possible to collect information from bicycle probe data that match and user perceptions and thus, utilizing them to take advantage of such data in advancing the goals of in smart cities and communities.
Document Type
Article
Publication Date
10-26-2021
Digital Object Identifier (DOI)
https://doi.org/10.3390/infrastructures6110154
Funding Information
This research has been partially financed by “Astro Database” Project of the University of Catania.
Related Content
The data presented in this study are available on request from the corresponding author. The data are not publicly available due to privacy.
Repository Citation
Cafiso, Salvatore; Pappalardo, Giuseppina; and Stamatiadis, Nikiforos, "Observed Risk and User Perception of Road Infrastructure Safety Assessment for Cycling Mobility" (2021). Civil Engineering Faculty Publications. 25.
https://uknowledge.uky.edu/ce_facpub/25
Notes/Citation Information
Published in Infrastructures, v. 6, issue 11, 154.
© 2021 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 (https://creativecommons.org/licenses/by/4.0/).