A New Framework to Assess Regional and Urban Impacts of Transport Infrastructure: The Case of High-Speed Rail in Portugal

This paper presents a comprehensive framework for modeling the impacts of large-scale transport infrastructure which have the potential to fundamentally alter the spatial interaction properties of regions, producing significant socio-demographic and economic modifications. This model is being developed as part of a broader research project to assess the impacts of the development of a high-speed rail (HSR) network in Portugal and to evaluate the best infrastructure and service configurations of the system. The framework will be applied to study a future HSR line between Lisbon and Oporto, exploring the concept of megalopolis formation for the corridor. The expected impacts of HSR include rearrangements of the socio-economic structure of the region it serves, redefinition of the nature of the economic linkages to neighboring regions and other external regions, and changes to the urban forms of the various urban centers which will experience significant accessibility upgrades. The framework calls for an agent-based formulation, with decision-making agents at various spatial scales and decision making levels interacting both in space and across levels, producing effects on upper and lower levels of spatial resolution and decision making. The model will include three main types of agents, which are linked to different scales of decision-making and spatial resolution, e.g. municipal, regional, and national. This paper presents the framework of the model, characterizes the interactions among the various levels of decision-making and assessment, and describes the methodological formulation of all the sub-models proposed for this comprehensive simulation tool

Investigating the role of High Speed Rail in shaping metro-regions

In the literature many definitions of megacities and mega-regions are proposed (Urena et al., 2009; Pagliara et al., 2011). For example, Hall (2009) defines a mega city region as a ?series of cities physically separated but functionally networked clustered around one or more larger central cities and are connected with dense flows of people and information using important transport infrastructures?. Transport infrastructures and services are fundamental either for the emergence or the proper functioning of mega cities and regions. High Speed Rail systems are definitely today considered as important infrastructures. By impacting strongly on accessibility patterns, they have revolutionized users? life style together with their mobility behavior thanks to their power of shrinking spaces and shaping places. This contribution is based on the recognition that commuting flows are not enough to justify the formation of a megacity or a mega-region. Even if they can contribute to it, they don?t justify the development of a megapolis. A theoretical model should be specified in order to explain the mechanisms through which metro areas integrate into mega-regions and to understand what is the real role of HSR systems as a variable of this model. This paper attempts to fill this gap, present in the literature, and identify some European corridors having high potential for mega-region formation as supported by High Speed Rail. Examples can be found in France, in Spain and in Italy as well. To achieve this objective, this paper will rely on a thorough literature review aimed at the identification of the possible causal relations between changes in accessibility induced by HSR and the emergence of megacities and megaregions. Moreover a first attempt of specifying the model is proposed. Indeed regression models are defined, where the dependent variables are described in terms of commuting flows, travel time and travel cost of the competing transport modes between metro areas, variables connected with HSR, i.e. comfort, speed, low environmental impact, etc. will be considered as well. Other factors influencing the formation of megacities and megaregions will be introduced and tested. Among them economic variables like the number of jobs, the GDP, etc. Further perspectives should consider that this construct should be tested and synthesized in mathematical terms and then calibrated with the collection of real data