Déplacements domicile-travail en Île-de-France et choix individuels du mode de transport

Nous étudions dans cet article le choix du mode de transport pour un déplacement domicile-travail au sein de la région Île-de-France dans un ensemble à deux modalités : véhicule particulier ou transports en commun. Nous modélisons la présence d’effets indirects liés aux autres dimensions de la demande de transport et l’existence d’hétérogénéité des goûts dans la population observée. Nous spécifions, identifions et estimons par la méthode du maximum de vraisemblance simulée un modèle Logit à paramètres aléatoires. Les résultats sont nombreux et réalistes : dispersion des goûts concernant les attributs de transports et les variables socio-économiques, corrélation positive entre valeur du temps et niveau de la congestion, rejet de l’axiome IIA.We develop in this paper a dichotomous discrete choice model for the analysis of home to work trips in the French Parisian region. The two modes of transportation are private motorized vehicle and public transportation. We analyse indirect effects coming from the other choices associated with the demand for travel. We also take into account random tastes of travellers. A mixed Logit model is formulated. Identification of the parameters and estimation by maximization of the simulated likelihood function are discussed. The results of the application are realistic and intuitive: tastes for travel attributes are heterogeneous among the population, so are the effects of their socioeconomic variables, the correlation of the value of time with the level of road congestion is positive and the IIA axiom does not hold

Déplacements domicile-travail en Île-de-France et choix individuels du mode de transport

We develop in this paper a dichotomous discrete choice model for the analysis of home to work trips in the French Parisian region. The two modes of transportation are private motorized vehicle and public transportation. We analyse indirect effects coming from the other choices associated with the demand for travel. We also take into account random tastes of travellers. A mixed Logit model is formulated. Identification of the parameters and estimation by maximization of the simulated likelihood function are discussed. The results of the application are realistic and intuitive: tastes for travel attributes are heterogeneous among the population, so are the effects of their socioeconomic variables, the correlation of the value of time with the level of road congestion is positive and the IIA axiom does not hold. Nous étudions dans cet article le choix du mode de transport pour un déplacement domicile-travail au sein de la région Île-de-France dans un ensemble à deux modalités : véhicule particulier ou transports en commun. Nous modélisons la présence d’effets indirects liés aux autres dimensions de la demande de transport et l’existence d’hétérogénéité des goûts dans la population observée. Nous spécifions, identifions et estimons par la méthode du maximum de vraisemblance simulée un modèle Logit à paramètres aléatoires. Les résultats sont nombreux et réalistes : dispersion des goûts concernant les attributs de transports et les variables socio-économiques, corrélation positive entre valeur du temps et niveau de la congestion, rejet de l’axiome IIA.

Long distance mode choice and distributions of values of travel time savings in three European countries

The study presented in this paper uses Stated Preferences (SP) data on mode choice collected as part of a recent survey on long distance travel u n dertaken in three European countries. The purpose of this article is twofold. It aims at exploring the impacts of the choic e of mixing probability distri butions while accounting for unobserved taste heter ogeneity and it aims at focusing on the derived estimation of the distribu tions of values of travel time savings (VTTS). We compare eleven distributions, each having particular properties in terms of domain, location, scale, and shape. Due to the repetiti ve nature of the SP experiments, we estimate mixtures of Multinomial Logit (MNL) models for panel data. The results show that the mixing distributions differ from one country to another, suggesting existence of European disparities as it regards long - dista nce mode choice. The results also show that long - distance travellers pay a lot more attention to access and egress travel times to and from the main mode than to total travel time with the main mode

Travel discomfort-time tradeoffs in Paris subway: an empirical analysis using interval regression models

We analyze individual travel discomfort-time tradeoffs in Paris subway using stated choice experiments. The survey design allows to set up in a willingness-to-pay space to estimate the distributions of elasticities of values of travel time savings to crowd density and time multipliers. Several formulations of a generalized travel cost function are tested. Accounting for heterogeneity in preferences, the econometric models all take the form of an ordered Probit with known bounds. We derive several estimates that could be used for fine-tuning of traffic simulation systems and more general transportation policy analysis

Attitudes to Distance, Time and Cost in Logit Transport Choice Models

During the last 20 years, a distance variable has sometimes been added to specifications of Logit utility functions that already included travel time and cost variables long assumed in theory and practice to embody the impeding effect of distance on transport demand. We briefly recall some milestones of this seemingly superfluous enrichment of modeling practice and propose to understand it as allowing for the expression of an Attitude to Distance (or DA) distinct from the Attitude to Time or Cost level of service outcomes. The framework adopted to document this split role of distance, a duality not entirely absent from common language, is the Multino- mial Box-Cox Logit model where, in the hope of improving estimates of Values of Travel Time Savings, distance raised to a simple power has recently often been introduced in interactions with the time and cost terms. Under the DA interpretation, the new power parameters of distance reveal an optimistic, pessimistic or neutral behavior towards distance distinct from any attitudes to the level of service variables themselves. In alternate specifications of utility functions based from the start on price, speed and distance variables, the self-standing distance term can also be re-interpreted as comprising a Distance Attitude component in addition to an impedance effect

To make LUTI models operationnal tools for planning

International audienceLand Use and Transport Integrated models (LUTIs) are promising tools for urban planning. Although a large literature is dedicated to these models, little attention has been paid to them as operational tool for planners and few efforts have been made by academics to fill the gap between lab application and operational use for planning practice. We shed light on what would make them accepted and more used by planners to evaluate urban and transport policies. In addition to a literature review and reflection on our own experience, we carried out a survey of end users in France to identify their motivations and barriers to using LUTI models. Our analysis shows a need for a far more bottom-up oriented approach. Only a closer collaboration between modelers and end users, and more efforts to integrate modeling into urban planning will make LUTIs considered as relevant approaches

Euclidean distance versus travel time in business location: A probabilistic mixture of hurdle-Poisson models

While the question of the specification of spatial weight matrix is now largely discussed in the spatial econometrics literature, the definition of distance has attracted less attention. The choice of the distance measure is often glossed over, with the ultimate use of the Euclidean distance. This paper investigates this issue in the case of establishments locating in the Paris region. Indeed, numerous works highlight the importance of transport infrastructure in the location model, which challenges the choice of the Euclidean distance in representing spatial effects. To compare the various distance measures, we develop a probabilistic mixture of hurdle-Poisson models for several activity sectors. Each model class uses a different definition of distance to capture spatial spillovers. The following distance measures are considered: Euclidean distance, two road distances (with and without congestion), public transit distance, and the corresponding travel times. Overall, the obtained results are in line with the literature regarding the main determinants of establishments' location. However, we find that for some activity sectors, such as construction, the peak road travel time for private vehicles is the most likely to correctly capture spatial spillovers, whereas for other sectors, such as real estate, the Euclidean distance slightly prevails. This tends to show that spatial spillovers are channeled by different means, depending on the activity sector. In addition, we find that the proposed mixture of hurdle-Poisson models that uses several latent classes performs significantly better than the "pure" hurdle-Poisson models based on a single distance measure, emphasizing the usefulness of our approach

Exploration of the Complex Similarity of Urban System Components

Similar to countless natural phenomena, cities have inherent orders that can be properly captured and expressed through a complex analysis of their components. Using Geographic Information Systems (GIS), this work offers a ring-buffer fractal approach to analyze the spatial characteristics of the components of an urban system. This approach was applied to road length, number of intersections, population+employment, and building gross floor area for the city of Chicago. The complex nature of these four components manifested itself in power-law relationships and represented by their fractal dimensions. Results showed that road length and number of intersections were closely related, albeit their fractal patterns followed slightly different trends. Additionally, population+employment and building gross floor area are significantly similar and one can explain the other. Moreover, the method developed in this study was able to identify the boundary of the old city of Chicago, highlighting its ability to capture hidden characteristics of an urban system. The proposed method could further be used to correlate complex properties of urban transportation systems to other relevant measures, including connectivity, accessibility, and mobility to name a few