Receptor-Oriented Modelling of Travel Experience: Multimodal Data Integration for Intermodal Public Transport

Kurzfassung

The Erlebensatlas project addresses a core challenge in intermodal public transport: capturing and visualizing the subjective travel experience of passengers in real time. Traditional models of passenger flow and service quality often neglect the receptive dimension of travel—how travelers perceive, process, and are affected by dynamic contextual factors such as delays, crowding, accessibility barriers, or information deficits. Our approach integrates multimodal data sources, including subjective self-reports, physiological indicators, and contextual data streams (e.g., GPS, service information, environmental conditions), to build a receptor-inspired modelling framework for travel experience. This framework treats travelers as active “human receptors” of their mobility environment, whose responses can be measured, aggregated, and visualized to identify spatial and temporal hot spots of positive and negative experiences. We present technical solutions for data acquisition through an intermodal travel app (KeepMoving), synchronization of sensor and survey data, and anonymized storage and sharing via open-source pipelines. To infer requirements for visualization and application, workshops and interviews with transport providers and municipal stakeholders have been conducted. The resulting visualization concepts function as a collective receptor map of intermodal journeys, enabling providers to identify unmet needs, evaluate interventions, and innovate passenger-centered services. By aligning methods of experience sampling and physiological sensing with receptor modelling perspectives, Erlebensatlas offers both a conceptual and a technical bridge: from modelling environmental impacts on individual perception, to developing scalable tools that inform the design of resilient, user-centered mobility systems in Indo-German urban contexts.