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Journal Articles EPJ Data Science Year : 2015

Understanding the variability of daily travel-time expenditures using GPS trajectory data

Abstract

Transportation planning is strongly influenced by the assumption that every individual has for his daily mobility a constant daily budget of ~1 hour. However, recent experimental results are proving this assumption as wrong. Here, we study the differences in daily travel-time expenditures among 24 Italian cities, extracted from a large set of GPS data on vehicles mobility. To understand these variations at the level of individual behaviour, we introduce a trip duration model that allows for a description of the distribution of travel-time expenditures in a given city using two parameters. The first parameter reflects the accessibility of desired destinations, whereas the second one can be associated to a travel-time budget and represents physiological limits due to stress and fatigue. Within the same city, we observe variations in the distributions according to home position, number of mobility days and a driver's average number of daily trips. These results can be interpreted by a stochastic time-consumption model, where the generalised cost of travel times is given by a logarithmic-like function, in agreement with the Weber-Fechner law. Our experimental results show a significant variability in the travel-time budgets in different cities and for different categories of drivers within the same city. This explicitly clashes with the idea of the existence of a constant travel-time budget and opens new perspectives for the modeling and governance of urban mobility.
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Dates and versions

cea-01334188 , version 1 (20-06-2016)
cea-01334188 , version 2 (17-10-2022)

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Riccardo Gallotti, Armando Bazzani, Sandro Rambaldi. Understanding the variability of daily travel-time expenditures using GPS trajectory data. EPJ Data Science, 2015, 4, pp.18. ⟨10.1140/epjds/s13688-015-0055-z⟩. ⟨cea-01334188v2⟩
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