Abstract
Research in cyclist behavior has until now avoided complex models for cyclist speed, instead preferring simple average speeds aggregated from multiple cyclists travelling on different terrain. This paper applies methods from recent research to create a detailed linear model for cyclist speeds, which varies according to road characteristics. This model is estimated using GPS point data for Toronto bicycle trips, generated by a smartphone app published by the City of Toronto. The model results indicate that the negative effect of cycling uphill on speed is stronger than the positive effect of travelling downhill. Further, the results demonstrate that bicycle infrastructure such as bike paths and bike lanes significantly increases cycling speed. The findings are useful for planners and decision makers who want to propose guidelines to increase cycling speed in order to attract more people toward cycling.
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