Urban mobility systems across Europe are facing increasing pressure due to rising traffic volumes, road safety risks, environmental impacts, and the growing complexity of transport networks. Cities are required to balance the efficient movement of people and goods with determined and demanding climate objectives, public health concerns, and societal expectations for safer, cleaner, and liveable urban environments. In the meantime, traffic management authorities normally operate with fragmented information, limited situational awareness, and limited capacity to anticipate risks or respond proactively to rapidly changing traffic conditions.
Although large volumes of transport-related data are generated on a daily basis, existing traffic monitoring and management remains hindered, reactive, while it is also focused on isolated parts of the transport system. This limits the ability of public authorities to form a comprehensive, real-time understanding of traffic systems, and to translate available data into evidence-based decisions. Consequently, opportunities to improve road safety, reduce congestion, and optimise the use of the existing infrastructure are not fully exploited.
These challenges are closely aligned with key European policy priorities, such as road safety, sustainable urban mobility, and the digital transformation of transport systems. In the context of increasing urbanisation and the transition towards greener and more digital mobility, there is a growing need for data-driven solutions to support smarter, resilient, and more adaptive traffic management across European cities.
Against this backdrop, the overall objective of the project is to develop and demonstrate an integrated approach for monitoring, analysing, and managing traffic, to support more informed, timely, and proactive decision-making. By combining advanced sensing technologies, artificial intelligence, and digital modelling within a unified framework, the project aims to enable traffic authorities and decision makers to better understand current conditions, anticipate emerging risks, and assess alternative management strategies.
The project’s pathway to impact is based on transforming heterogeneous traffic and mobility data into actionable insights that can be directly used by decision-makers. By improving situational awareness and enabling predictive and scenario-based analysis, the project is expected to contribute mainly to road safety improvement and reduced congestion, but also to more efficient and sustainable use of urban transport infrastructure. In addition, social and behavioural factors are considered to ensure usability, trust, and long-term adoption of the developed solutions.
