Introduction
The COVID-19 emergency and the cities lockdown have had a strong impact on transport and mobility. In particular, travel demand has registered an unprecedented overall contraction, dramatically dropping down with peaks of - 90%-95% passengers for public transport (PT). During the re-opening phase, demand is gradually resuming the levels before the crisis, although some structural changes are observed in travel behaviour, and containment measures to reduce the risk of contagion are still being applied, affecting transport supply.
Objective
This paper aims at assessing to what extent keeping a one-meter interpersonal distancing on-board trains is sustainable for public transport companies.
Method
The analysis is based on travel demand forecasting models applied to two case-studies in Italy: a suburban railway line and a High-speed Rail (HSR) line, differentiated by demand characteristics (e.g. urban vs. ex-urban) and train access system (free access vs. reservation required).
Results
In the suburban case, the results show the need of new urban policies, not only limited to the transport domain, in order to manage the demand peaks at the stations and on-board vehicles. In the ex-urban case, the outputs suggest the need for public subsidies in order for the railways undertakings to cope with revenue losses and, at the same time, to maintain service quality levels.
Investments in transportation infrastructure have been identified as one of the main factors to promote territorial economic growth. However, appraisal methods currently used in the planning practice do not consider spatial economic distributional effects, ignoring who within a given region would receive greater economic benefits from an investment than others (and eventually who might receive worse). In this paper, a modelling framework is proposed to assess the spatial economic impacts of transportation infrastructure investments; the method combines spatial regressions with transportation accessibility analysis, assuming Gross Domestic Product per Capita variation as a proxy of the economic growth. The application to the case study is related to the Adriatic and Ionian region, which includes both some EU (Italy, Slovenia, Croatia, and Greece) and non-EU countries (Bosnia-Herzegovina, Montenegro, Albania, North Macedonia, and Kosovo) and is characterized by huge disparities in terms of infrastructural assets. The models allow us to both statistically prove the importance of spatial modelling specifications and to forecast economic impacts that would be generated by ongoing infrastructure investment plans for the reconstruction of the road and railway networks in the region; this highlighted where current economic disparities tend to be bridged up, i.e., mainly along the foreseen extensions of the Trans-European Transport Network (TEN-T) corridors, and where not.
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