The demographic and technological changes that we are experiencing will continue and will greatly influence people’s mobility.
Whatever systems are put in place must cover aspects such as, efficiency, affordability, quality, comfort, accessibility, punctuality and reliability, flexibility, information and value for money. These long-term needs and expectations need to be analysed to get a better understanding about them. However, it is equally important to analyse megatrends and future Scenarios regarding mobility.
The railway industry, one of the most long-term oriented industries existing, is now facing the faster and faster life cycles of its most competitive transport mode, the road transport sector and its related technologies. The competitive situation of the rail industry is suffering from its lack of flexibility and from the far better “client orientation” of other modes. To overcome such a backlog the rail industry has to anticipate trends and developments at an earlier stage and has to adjust its system accordingly.
The main objective of the project NEAR2050 is to study the future demand on the railway sector, determining which variables affect railway services the most. To define users’ behaviour and the most important variables, it is necessary to establish what are the customer’s opinions and variables that condition their choices when choosing a transport mode. Thanks to this, future user behaviour can be predicted, and future railways demand can be enhanced.
NEAR2050 combined both qualitative and quantitative analysis to answer the objectives regarding the future challenges of the rail sector until the year 2050. Current user requirements and the technical and societal needs were identified by focus groups and expert interviews all over Europe as well as by online surveys with a lot of participation from all kind of stakeholder of the rail sector.
The future expectations and trends were identified by expert interviews and focus groups again using face to face interviews as well as online surveys, by discrete choice models of modal share and the future preferences of users and by trend analysis with statistical evaluations of consistency and qualitative future projections of these trends and their influence on the rail system.
