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The relation between urban environment and travel behaviour is not a new problem. Neighbourhood characteristics may affects mobility of dwellers in different ways, such as frequency of trips and structure of the tours. At the same time, qualitative issues related to the individual’s attitude towards specific behaviour have recently taken an important place in transport modelling contributing to a better understanding of travel demand. Following this research line, this paper aims to study the effect of neighbourhood characteristics into the choice of the type of tours performed, but we assume that neighbourhood characteristics can also affect the individual propensity to travel and hence the choice of the tours throughout the propensity to travel. Since the propensity to travel is not observed, we employ hybrid choice models to estimate jointly the discrete choice of tours and the latent variable. The propensity to travel is indicative of the tendency to undertake trips, and it is related to the individual socio-economic characteristics and the neighbourhood characteristic. The discrete choice model simulates the choice among tours characterised by different purpose for the main activity and the number of intermediate stops performed. The data used in this study comes from a survey conducted in 2006 and 2007 in Madrid. A total of 943 individuals were interviewed in 3 different neighbourhoods (CBD, urban and suburban). The results show that neighbourhood attributes have indeed a significant impact on the choice of the type of tours either directly and through the propensity to travel. The propensity to travel has a different impact depending on the structure of each tour and increases the probability of choosing more complex tours, such as tours with many intermediate stops. Finally, as expected, the hybrid models show a major improvement into the goodness of fit of the model, compared to a classical discrete choice model that does not incorporate latent effects.

How urban environment affects travel behaviour: integrated choice and latent variable model for travel schedules