Horizon Mobility: AI for Transport Disruption Resilience

Building and physically proving a resilience system for multimodal passenger transport that uses real-time data analytics and generative and discriminative AI to predict how a disruption will unfold, generate and share a response plan fast, and run predictive maintenance that catches infrastructure and equipment failures before they cause disruptions. The project has to pull in data from multiple sources, build scenario libraries for different disruption types, and deliver guidelines, tools, training and an emergency-simulation programme for transport and infrastructure operators and authorities, who help design the system rather than just receive it. It is proven live across at least three transport modes (e.g. bus, metro, tram, train, coach, trolleybus, ferry, shared mobility) in at least three pilot sites in different Member States, and has to cut passenger delay at corridor level by at least 20% during planned disruptions and cut the time from generating to sharing a response plan by at least 40% during unplanned or critical events, both against a baseline the project sets itself.