Capturing high-level users decisions

Based on the principles of discrete choice theory, we develop models aiming to replicate current conditions as well as anticipating future user's behavior towards traditional and new mobility services. The models may vary from high-level activity-based and mode choice models to very detailed and disaggregated models capturing decisions like en-route choices.

 

Evaluating policies and operations

Our expertise lies also on multi-scale(macro, meso, micro) and multi-modal simulation. We focus on developing state-of-the-art activity-based models and integrating them with Dynamic Traffic Assignment tools, driving behavior models and multi-modal controllers (PuT and on-demand services). Thus, we are able to test different scenarios, providing insight on daily travel patterns, appraising and optimizing ITS and ATIS systems, fleet operations and strategies as well as evaluating energy and emission policies.

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Integrating passenger and freight models

Urban population growth has a great influence on demand for passenger mobility as well as  on demand for goods and services. In the light of this, we are looking in expanding our research further by developing models that aim to capture the daily freight demand patterns, identify the impacts of commodities movements urban environments and evaluate existing freight management systems and policies.

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For more details on our work, please visit our projects and publications.