This seminar will explore how emerging data sources are enabling more detailed, timely, and context-aware representations of travel demand and network performance. It will examine how advances in computing are making large-scale agent-based models operationally feasible, while also raising questions around model transparency, validation, and governance.
The future of transport modelling is being reshaped by the convergence of unprecedented data availability, rapidly increasing computational power, and a new generation of behavioural modelling approaches. Traditional aggregate models are increasingly complemented - and in some cases challenged - by agent-based and activity-based frameworks that can represent individual decision-making, heterogeneity, and dynamic interactions within the transport system.
Activity-based models allow us to better understand travel behaviour and provide better transport options to users by considering the full integration of public transport services with on-demand mobility solutions. Although these are not new transport models, the data-rich environment and the increased computational power available to modellers open up new challenges and opportunities for the transport community.
This seminar will explore how emerging data sources are enabling more detailed, timely, and context-aware representations of travel demand and network performance. It will examine how advances in computing are making large-scale agent-based models operationally feasible, while also raising questions around model transparency, validation, and governance.
The discussion will extend to transport digital twins as an integrative paradigm that links behavioural models, network dynamics, and real-time data within a continuous decision-support environment. By bridging planning and operations, digital twins offer the potential to move transport modelling from static forecasting towards adaptive, policy-relevant experimentation. The seminar will conclude by reflecting on the implications for practitioners, researchers, and public authorities as transport modelling evolves from predictive tools into living systems that support resilient, inclusive, and data-driven mobility planning.
This webinar is open to anyone working in the Highways and Transport sector, but particularly Practitioners, Researchers, and Public Authorities.
All levels welcome, from apprentices to senior professionals.
Dr Patrizia Franco, Associate Director in Activity and Agent-based Modelling Data, Modelling and Analysis - Digital, Systra UK and Ireland 
Dr. Patrizia Franco is Associate Director of Activity and Agent-based Modelling at Systra (Data, Modelling, and Analytics), with 20 years’ experience in transportation engineering spanning transport planning, modelling, and travel behaviour analysis. Her work integrates emerging data sources with advanced agent- and activity-based methods to inform policy, accelerate decarbonisation, and improve multimodal mobility systems.
At Systra, Dr. Franco leads the development of UK–Ireland capabilities in agent- and activity-based modelling, building a portfolio that translates cutting-edge research into operational decision support. She designs transport digital twins and large-scale demand modelling frameworks that enable robust “what if” testing for urban and rural mobility, shaping interventions for electrification, demand-responsive transport, Mobility as a Service, and last-mile logistics - directly supporting decarbonisation and behavioural change strategies.
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