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Articles

Cyclists do better. Analyzing urban cycling operating speeds and accessibility

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Pages 448-464 | Received 25 Oct 2017, Accepted 15 Jan 2019, Published online: 01 Mar 2019
 

Abstract

Given the growing interest in promoting more sustainable urban transport, over the past years, many researchers have analyzed cycling mobility from different perspectives. However, some important aspects remain underexplored. One of them is the study of cycling speeds. The first goal of this research is to analyze the impact of a wide range of factor on cyclists’ speeds. Based on the examination of thousands of GPS routes, the investigation conducts diverse OLS regressions in order to analyze cyclists’ speed according to the diverse local factors that affect cyclists along their journey, such as the slope, the existence – and type – of bike infrastructures, the average traffic speed or the density of traffic lights or intersections. Cycling speed is also analyzed according to cyclists’ gender or age, the purpose of the journey, or even the weather conditions. The research includes the analysis of regular cyclists’ trips, as well as the analysis of bike-messengers’ routes. The results obtained shed light on the influence of these factors on cyclists’ speed by quantifying their specific impact, and diverse models predict cyclists’ travel times in the current scenario but also in future ones that may correspond to the implementation of new infrastructure or policies. In addition, the models allowed us to pursue the second goal of this study: to conduct a comparative analysis of accessibility for different transport modes, and then evaluate the competitiveness between them. The results evidence that cycling is not only a sustainable transport mode, but the most competitive for small-medium distances.

Disclosure statement

No potential conflict of interests was reported by the author(s).

Additional information

Funding

The authors gratefully acknowledge funding from Spanish Ministry of Economy and Competitiveness and the European Regional Development Fund (TRA2015-65283-R and FPDI 2013/17001), and the Madrid Regional Government (SOCIALBIGDATA-CM, S2015/HUM-3427).

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