SAFIRA – Safety and distance in public transport through passenger guidance
SAFIRA – Safety and distance in public transport through passenger guidance
Local public transport was particularly affected by the coronavirus pandemic. Passenger numbers decreased sharply during the crisis. People's mobility has changed in terms of time and space since then. At the same time, public transport is a key factor in achieving climate goals and contributing to a sustainable transportation system. This is why public transport must regain trust and reposition itself through data innovations. Data innovations will help to make public transport more resilient and to better manage unexpected events.
Planned passenger routing based on capacity utilisation information.
Real-time capacity utilisation data is developed into reliable forecasts using AI approaches, transferred to the VBB passenger information system and made available to third parties. The increasing availability of precise information on capacity rates of public transport brings the possibility of providing information on alternative, less crowded route options to passengers. A more even utilisation of vehicle capacity also contributes to achieve the goal of a sustainable transport system, as the expected increase in demand is more likely to be met with existing vehicle and infrastructure capacities.
Capacity utilisation forecasts are generated with a short to medium-term time horizon and utilisation and capacity-based routing functions are implemented in journey planner apps of public transport. DLR is responsible for the user research and complements the technical development, as acceptance, trust, and the resulting change in behaviour (switching to a different route) are the key to successful passenger guidance. A number of psychological constructs are being analysed using qualitative and quantitative methods. This makes it possible to investigate how crowded the train is perceived, compare it to the actual utilization rate, and identify the effect of external factors on the perception. When, where and how passenger information needs to be provided and whether and how behavioural changes can be motivated are also analyzed taking into account inter-individual differences (e.g. people with physical or sensory disabilities, older people or migrants).
