Cyclists' travel behaviour, from theory to reality

Abstract

A lot of cities are experiencing an increase of cycling in their daily urban trips. This produce benefits for all citizens and many decision-makers are designing policies to improve bike use. However, this is not possible without a cycling demand management policy, which should be based on the scientific knowledge of cyclist behaviour key factors. In the scientific literature we can find many references about factors affecting bicycle use. They are oriented either to show qualitative analysis, where bike factors assessment are made; or they present discrete choice models where bike factors are evaluated in order to the final user choice. Both research lines provide important information on cyclist behaviour knowledge. However they are not enough to explain all the explanatory factors to use bikes. Some factors influencing cycling use are of psycho-social type and they are not included in the econometrics models normally used. This paper presents a research done to improve cycling demand forecast. For this research we have made an internet based survey in the Madrid University Campus, where a public bike system is expected to be implemented. In this survey we have collected more than 3,000 responses, including objective and subjective factors for the trip to the University. Based of the outputs of the survey several models have been adjusted for forecasting cycling demand. We have used social science techniques like covariance structural equation modelling. These techniques are based on the use of latent variables and they consider the relationships among them. The results emphasize the importance of experience for using bicycle for daily mobility. The explanatory factors have been ranked in four groups: convenience, pro-bike factors, physical limitations and external limitations. Among these groups, external limitations and convenience are the most relevant, explaining 85% of cyclist travel behaviour. There are also important interactions between pro-bike factors and convenience ones that have to be taken into account because pro-bike factor have an influence of almost 57% of the convenience factors. These results allow explaining the key factors to develop a sound cycling policy.