Academic journal article Population

Daily Mobility of the Inhabitants of Lille Up to 2030

Academic journal article Population

Daily Mobility of the Inhabitants of Lille Up to 2030

Article excerpt

As society develops, the number of contacts and of economic and cultural exchanges increases, while the reasons for travel and the geographical areas covered become more varied. People make daily trips within a defined territory to carry out extra-domestic activities for either work-related or personal reasons. The massive use of private vehicles has been a key factor in transforming territorial organization, by dispersing both activities, and above all housing, over much larger areas, and the rapid growth in household car ownership in the 1960s and 1970s spawned numerous transport planning studies. Planning at that time focused mainly on the creation of transport infrastructures able to meet a high demand for mobility, chiefly in the large urban areas or agglomerations. P. Merlin (1991) observed that "studies have concentrated on urban transportation systems, which have played a pioneering role in clarifying the issues, concepts and methods of planning".

Of the many factors involved in spatial change, urban policies make a lasting impact on how cities function. Public investment choices in urban transport facilities (subways, trams, expressways) are crucial for a city's development. The public authorities need to possess the right information to make coherent transport policy choices, particularly regarding new infrastructure, whose irreversible character calls for a long-term vision of demand.

In addition, mobility has become a key focus of concern with regard to energy consumption, land use and environmental issues. Public sensitivity over these questions is growing in the developed countries and the public authorities' efforts to mitigate the harmful impacts of the transport sector are under close scrutiny.

Many of the transport models developed to date consider a static and stable environment in which the modelled and observed phenomena remain unchanged over time. Yet this stability is problematical when studies concern mobility behaviour over the long term. Mobility is not independent of the transformations affecting society or of the habits of city-dwellers. Moreover, the intensity of these changes is not constant but varies with socioeconomic trends and local population dynamics.

Overall behaviour in large groups of individuals at the aggregate level often appears difficult to explain. When the population is heterogeneous, projections based on analysis of general trends do not yield a clear picture of potential future developments. Nor does cross-sectional analysis seem appropriate in times of demographic, economic and social change. It transposes into trends the differences observed between individuals at a particular point in time, often leading to biased estimates (Madre and Gardes, 2005). Dynamic approaches to modelling daily mobility are thus needed.

By decomposing a phenomenon into different temporal effects, the factors responsible for its variation over time can be identified. Among several possible approaches, that based on the role of age has long been used in various research fields, notably in economics (Kessler and Masson, 1988). But the age effect is not sufficient to explain the changes observed: the dynamics of behaviour also depend on the cohorts involved. Finally, the analysis must also take into account the time when the events occurred. The approach that incorporates age, period and cohort effects, familiar to demographers, thus offers a pertinent method for identifying long-term changes in behaviour. This approach has already been employed in transport studies to project the size and structure of the vehicle stock, demand for cars (Gallez, 1994), and levels of household car ownership (Bussière et al., 1996).

To evaluate the age, cohort and period effects in mobility and to make long-term projections, we require a model that interprets the effects of the different time factors involved in the dynamics of behaviour, but that also makes use of longitudinal data. In this article we show how cross-sectional surveys repeated at regular intervals can be used to construct a longitudinal observation of daily mobility. …

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