Enhanced resilience in multimodal passenger transport through digital technologies and generative and discriminative AI

Expected Outcome

Project results are expected to contribute to all the following expected outcomes:

• Development of systems that utilize real-time data analytics to dynamically respond to disruptions, allowing transport and infrastructure operators to adjust operations swiftly and efficiently;
• Development of predictive maintenance strategies applying innovative Generative AI solutions and utilizing other digital technologies to anticipate and prevent infrastructure and equipment failures;
• Development of guidelines and tools to support passenger transport operators and authorities to ensure minimal disruption in unexpected and critical situations and organise real life emergency simulations;
• Deployment of training programme for transport and infrastructure operators on how to handle transport disruption, including tools and catalogue with contingency planning for specific transport disruptions;
• Reduction of average passenger delay at corridor level (at least 20%) during planned disruptions, compared to the baseline and of (at least 40%) time needed from the generation to the dissemination of a response plan to different stakeholders (e.g. transport operators, passengers, citizens) during unplanned and critical events, compared to the baseline.

Scope

Passenger transport systems are a critical component of urban, sub-urban, and long-distance travel, facilitating connectivity, reducing traffic congestion, and supporting environmental sustainability. However, these systems face challenges such as operational disruptions, safety and security risks, and evolving passenger demands.

In the context of passenger transport, resilience refers to the ability of a transport system to absorb disturbances, maintain its basic structure and function, and recover to a required level of service within acceptable time and cost after being affected by disruption. This involves implementing measures that ensure continuous operation, quick recovery from unexpected events, and adaptability to changing circumstances. Enhanced resilience is essential for maintaining public trust and ensuring smooth functioning of transport systems and it is a cornerstone of the EU Sustainable and Smart Mobility Strategy.

Proposed actions are expected to address all of the following aspects:

• Development and implementation of measures to enhance the resilience of urban, sub-urban and long-distance transport systems.
• Leveraging digital technologies (e.g. big data, digital twins) and in particular generative and discriminative AI for anticipating and predicting the evolution of disruptions and their impacts, with real-time planning and information systems for minimizing impact and enabling faster recovery.
• Use of innovative technologies for data acquisition and integrate data from various sources to inform decision-making and optimise strategies, and generate scenario libraries for different disruptive events and monitor the implementation of the response plans
• Involve authorities and operators in the design process to create holistic solutions that are user-friendly and aligned with their needs.
• Conducting safety and security assessments in data interpretation, ensuring decisions are based on objective factors while avoiding biases.
• Test and validate the aspects above in real-life use cases in multimodal transport corridor within urban, sub-urban and long-distance passenger transport with minimum three transport modes per use cases (e.g. buses, metros, trams, trains, coaches, trolleybuses, ferries, share mobility) in at least three pilot sites situated in different Member States and reflecting a diversity of operational, geographic, and technological contexts.

Proposals are encouraged to building on results from previous calls on infrastructure and transport resilience (e.g. HORIZON-CL5-2024-D6-01-11, MG-7-1-2017, HORIZON-CL5-2021-D6-01-09), multimodal traffic management (e.g. HORIZON-CL5-2022-D6-02-05, MG-2-11-2020), shared mobility and public transport (e.g. HORIZON-CL5-2022-D6-02-04, HORIZON-MISS-2021-CIT-02-02). Proposals should also comply with existing EU framework and strategies and building upon the concepts and solutions developed in other Union initiatives aimed to facilitate data sharing in transport, such as the European mobility data space (EMDS). Particular efforts should be made to ensure that the data produced in the context of this topic is FAIR (Findable, Accessible, Interoperable and Re-usable).

Technology Readiness Level - Technology readiness level expected from completed projects

Activities are expected to achieve TRL 6-7 by the end of the project – see General Annex B.