Route choice analysis of urban cycling behaviours using OpenStreetMap: Evidence from a British Urban Environment

G. Yeboah, S. Alvanides

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review

17 Citations (Scopus)

Abstract

The neglect of non-motorized transportation options in transport planning and demand modelling is gradually being addressed in the United Kingdom. In route choice research there has been, in recent years, a trend away from modelling hypothetical situations towards field testing. This is partly due to the effective use of emerging GPS technologies for gathering travel behavior data in “wild” urban spaces, making it possible to observe realistic situations. Such data on detailed travel behaviors offer possibilities for further research, especially in the non-motorized transportation arena. Globally, there has been progress in the development of cyclists’ route choice models using revealed preference GPS data from various geographical and local contexts. However, we have little evidence on detailed cyclists’ route choices in the UK in a national and local context. This is particularly the case with low cycling participation cities in North England, where there have been various attempts to increase cycling uptake in recent years. This chapter fills this knowledge gap by undertaking a route choice analysis using the cycling-friendly version of OpenStreetMap (OSM) as the transportation network for analysis, alongside GPS tracks (7 days) and travel diary data for 79 Utility Cyclists around Newcastle upon Tyne in North East England. We examined specific variables as proposed in the relevant cycling literature and used these to develop a model testing the null hypothesis that network restrictions (i.e. one way, turn restrictions and access) do not have any significant influence on the movement of commuter cyclists. The findings suggest that OSM can provide a robust transportation network for cycling research, in particular when combined with GPS track data. The observed routes were significantly longer than their shortest path alternatives, the only exception being the straight-line distance between the observed bike routes and the unrestricted network routes, where the difference was not statistically significant. We conclude that network restrictions for both observed and shortest paths are significant, suggesting that route directness is an important factor to be considered for restricted and unrestricted networks.

Original languageEnglish
Title of host publicationOpenStreetMap in GIScience
Place of PublicationLondon
PublisherSpringer
Pages189-210
ISBN (Print)978-3-319-14279-1
DOIs
Publication statusPublished - 2015

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