Citation

Campisi T, Tesoriere G, Skoufas A, Zeglis D, Andronis C, Basbas S. Transp. Res. Proc. 2022; 60: 124-131.

Copyright

(Copyright © 2022, Elsevier Publications)

DOI

10.1016/j.trpro.2021.12.017

PMID

unavailable

Abstract

Level of Service (LOS) is one of the most crucial components for the assessment of pedestrian facilities by mainly concerning the effective width as well as pedestrians' flows. However, current research reveals that qualitative characteristics can also contribute to LOS estimation as perceived by pedestrians. Specifically, socio-demographic characteristics (i.e., age, gender) as well as characteristics related with perceived comfort and safety can be related with perceived LOS. A Revealed Preference (RP) face to face questionnaire-based survey (including 301 interviewees) was realized during October 2019 at a central pedestrian facility in the city of Thessaloniki, Greece. RP questionnaire survey assisted in gaining valuable knowledge concerning the factors that mainly affect pedestrians' perceived LOS across the pedestrian facility. The examined pedestrian facility is one of the most important in Thessaloniki since it facilitates high pedestrian flows within the city center daily. The present survey considered pedestrians' general mobility characteristics such as walking frequency along the facility and trip purpose. Additionally, the evaluation of the greater facility' area in terms of land use attractiveness, comfort, personal and road safety, public transport, parking conditions and traffic delays, accessibility, pedestrians and bicycles were concerned as well. Ordinal regression was the main tool for the development of the ordinal regression model, and therefore, for the conclusions' drawing of the present research. The findings regarding perceived LOS can pave the way towards the design of sustainable policy concerning pedestrian facilities as well as the encouragement of active transport in urban areas.

Language: en

Keywords

active transport; Level of Service (LOS); ordinal regression model; pedestrian street; pedestrians; sustainable urban mobility; walking