Godwin Yeboah

Everyday Cycling in Urban Environments: Understanding Behaviors and Constraints in Space-Time

Cycling in British cities is increasing but at a slow rate nationally. The ultimate realizations of cycling benefits in urban areas, such as cities in North East England, are hampered by lack of appropriate data to aid in our understanding of cycling behaviors to inform policy strategies and improve cycling uptake as well as data processing methodologies. Several efforts are being made to enhance data availability to understand cycling behaviors to inform policy strategies for which this research aims to contribute by providing evidence on the use of the area’s cycling infrastructure by utility cyclists. A proposed corridor space analytical approach was used to analyze the newly collected 7-day GPS data from 79 utility cyclists to estimate the extent to which respondents used the area’s cycling infrastructure. The data was used together with the area cycling infrastructure data from Newcastle City Council. Findings from the corridor space analysis suggest that 57.4 % of cyclists from sample prefer cycling on the cycle network, while 33.8 % cycle outside the cycle network with 8.8 % near the cycle network. Also, for all cycle trips, men tend to dominate in cycling on and near the cycle network. Both the males and females tend to use the cycle network more than off the network for utility trips. With 42.6 % of cyclists still cycling outside the designated cycle network, it is imperative that policy initiatives are aimed towards investing in cycling research and infrastructure to further deepen our understanding to encourage cycling around the study area. It was also suggested that the captured detailed actual route choice preferences could serve as input to the development of agent-based models towards understanding cycling behaviors around the study area.

Route Choice Analysis of Urban Cycling Behaviors Using OpenStreetMap: Evidence from a British Urban Environment

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.