Conrad, ChristopherXu, YanPanda, DeepakTsourdos, Antonios2024-06-192024-06-192024-05-13Conrad C, Xu Y, Panda D, Tsourdos A. (2024) Simulating enhanced vertiport management in a multimodal transportation ecosystem. In 2024 IEEE Aerospace Conference, 02-09 March 2024, Big Sky, USA979-8-3503-0463-31095-323Xhttps://doi.org/10.1109/AERO58975.2024.10521373https://dspace.lib.cranfield.ac.uk/handle/1826/22524The advanced air mobility (AAM) industry envisions a transformative transportation ecosystem for passengers and cargo deliveries. Nonetheless, coordinating large volumes of new aerial vehicles necessitates innovative unmanned aircraft system (UAS) traffic management (UTM) solutions, supported by a robust vertiport infrastructure. Moreover, AAM will form part of a broader multimodal ecosystem, posing additional technical, procedural and operational challenges. This work thereby presents a simulation tool in AnyLogic for deploying, training and testing collaborative and intelligent AAM decision-making frameworks within a multimodal transportation system. The platform integrates multiple vertiports with diverse resource constraints, and offers a flexible solution to investigate the impact of different vertiport designs, layouts and procedures. AAM-specific influences are also introduced, including electric vehicle batteries, heterogeneous vehicle specifications, stricter flight envelopes, and hyper-local micro-weather variations. The model further acknowledges the complex inter-dependencies within a multimodal environment to capture fluctuating travel demands and dynamic passenger flows within transportation terminals. This scalable simulation tool thereby enables the development of enhanced vertiport management and AAM traffic coordination solutions, and facilitates exploratory research on multimodal coordination amongst air, ground, rail and sea transportation systems.en-UKAttribution 4.0 InternationalTrainingRailsIndustriesEcosystemsLayoutTransportationElectric vehiclesConference paper979-8-3503-0462-6