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The public transport sector in all corners of the world has been dramatically affected by the global COVID-19 crisis. In order to support the process of revitalising confidence in public transport, UITP wishes to explore the methods for improving the passenger flow in public transport systems, in particular in urban networks (railway/metro/bus/ tram), to maximise the number of passengers, while offering the most comfortable and safest passenger experience. We will also be looking into methods of monitoring and modelling fluctuations in mobility demand and anticipating the impacts of unexpected events and specific conditions (pandemic outbreaks, strikes, vehicle or system malfunctions, weather conditions, flooding, etc.).
An important objective is to improve the prediction of passenger demand, in order to optimise the resources and adapt the supply of transport services with the support of analytics and algorithms.
Another objective is to provide passengers with reliable information to allow them to choose when and how to travel safely while respecting social distancing, health regulations and recommendations. The integration of such predictive information into the Mobility as a Service (MaaS) ecosystem will allow users to gain greater trust in public transport and will promote sustainable transport.
In addition, it provides an opportunity to explore ways of maximising the value of the passenger dwelling time and improving potential new revenue streams, such as interactive adverts, cafe kiosks and vending areas.