Modeling and Quantifying Interaction of Information and Capacity in Public Transport Disruptions

Disruption in public transport networks has adverse implications for both passengers and service managers. To evaluate the effects of disruptions on passengers’ behaviour, various methods, simulation modules, mathematical models are widely used. However, such methods included many assumptions sake simplicity. We here use multiagent microsimulation modules to simulate complex real-life scenarios. Aspects that were never explicitly modelled together capacity network effect disruption on-board passengers, who might need alight disrupted services. In addition, our developed module provide a framework can be applied planning real-time management large-scale network. formalize agent-based assignment problem capacitated transit situations, where some information is available about disruption. extend environment quantify precisely impact number agents directly indirectly affected by disruption, respectively, those cannot perform their trip because services (directly passengers), whose not but experience additional crowding (indirectly passengers). The outcomes discussed from perspective extracting more general policy recommendations. modeling solution approaches multimodal system Zürich, Switzerland. Our results show different dissemination strategies have large direct indirect effects. By earlier dissemination, get milder larger space, negative arise. scenarios with least instead very strongly affecting few while less rest