Creating a Richer Data Source for 3D Pedestrian Flow Simulations in Public Transport

The distribution of passenger flows in public transport environments can be predicted through simulations of flow characteristics. The flow characteristics are usually based on average values, which do not include behavioural characteristics of people with mobility impairments such as wheelchair users, individuals with prams and small children, elderly people or people with sensory impairments. In the project at hand we gather data on orientation behaviour of these passenger groups through experience and task-related research. In a combination of methods - video and audio recording, user centred scenario and task development, questionnaires, interviews and time-motion-event (TME) recording - qualitative and quantitative data are generated. By linking qualitative information to quantitative measures a multi-dimensional description of the behaviour of individuals and user groups in a transport interchange emerges. It is expected that by comparing and contrasting the resulting behavioural measures to the average values currently used to represent passenger flows, the quality of simulations can be considerably enhanced.