The transport sector and the use of individual cars in particular are sources of negative externalities. Shared mobility could form a solution to this issue. This study contributes to a better understanding of the implementability of such a shared mobility by exploring the potential determinants of the use of carpooling and carsharing for commuting among a comprehensive set of socio-demographic, socio-economic, interpersonal and contextual variables. The analyses are based on a representative sample of 2002 workers living in the Paris region. Fisher's exact and Wilcoxon tests and multivariate logistic models were used to characterize the differences between carpoolers and carsharing users and to identify the correlates of mode use in our sample. We outline that the correlates differ between the two shared modes. Our models first highlight the importance of contextual variables: the use of carpooling mainly concerns people who live in rather deprived neighborhoods, while carsharing is overrepresented in well-to-do and denser neighborhoods. We identify the importance of mobility management policies within the workplace and the positive role of information. Having a carpooling service within the company is positively associated with carpooling for commuting. Regarding carsharing, the awareness of existing services (free-floating and peer-to-peer) is positively associated with carsharing use. Finally, the main originality of this study is the identification of the key role of the entourage (colleagues and/or family members) in both carpooling and carsharing. Public policies should therefore consider these results to exploit several levers to favor the use of shared modes in the Paris region.

Abstract:Innovative solutions have been implemented to promote sustainable mobility in urban areas. In the Nantes area (northwestern part of France), alternatives to single-occupant car use have increased in the past few years. In the urban area, there is an efficient public transport supply, including tramways and a "busway" (Bus Rapid Transit), as well as bike-sharing services. In periurban and rural areas, there are carpool areas, regional buses and the new "tram-train" lines. In this article, we focus on the impact on house prices of these "sustainable" transportation infrastructures and policies, in order to evaluate their values. The implicit price of these sustainable transport offers was estimated through hedonic price functions describing the Nantes urban and periurban/rural housing markets. Spatial regression models (SAR, SEM, SDM and GWR) were carried out to capture the effect of both spatial autocorrelation and spatial heterogeneity. The results show patterns of spatial heterogeneity of transportation offer implicit prices at two scales: (i) between urban and periurban/rural areas, as well as (ii) within each territory. In the urban area, the distance to such offers was significantly associated with house prices. These associations varied by type of transportation system (positive for tramway and railway stations and negative for bike-sharing stations). In periurban and rural areas, having a carpool area in a 1500-m buffer around the home was negatively associated with house prices, while having a regional bus station in a 500-m buffer was non-significant. Distance to the nearest railway station was negatively associated with house prices. These findings provide research avenues to help public policy-makers promote sustainable mobility and pave the way for more locally targeted interventions.

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The project objective is to develop an optimized methodology to assess the environmental impacts of urban mobility plans (UMP, in French PDU), taking into account their social and economic consequences. The main proposed methodology is based on a systemic approach: multi-factor (air quality, noise, energy consumption, greenhouse gas emission) numerical simulations with a chain of physically-based models, based on alternative and comparative scenarios. The social and economic consequences of these alternative simulations are assessed by means of econometric models. Two alternative approaches are explored: (i) the use of composite environmental indicators to correlate the sources to the impacts, especially

In this paper we propose a general algorithm for solving unconstrained optimization problems. The basic step of the algorithm consists in finding a "good" successor point to the current iterate by choosing it along a curvilinear path and within a trust region. This scheme is due to Powell and it has been applied by Sorensen to a particular type of path. We give a series of properties that an arbitrary path should satisfy in order to achieve global convergence and fast asymptotic convergence. We review various paths that have been proposed in the literature and study the extent to which they satisfy our properties.

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