The project introduced a novel design method using the Design Science Research (DSR) approach, which integrates technological and human-centric elements to enhance policymaking by considering human behaviour and social contexts. The MOB data collection system, using image-based sensors for autonomous traffic participant behaviour detection, complies with GDPR/NIS2 regulations and supports microscopic transport planning. A “Holistic Big Data Platform” was also established, enabling scalable processing and analysis of diverse mobility datasets to offer insights for urban planning. Additionally, an advanced discrete choice model (the Stated Preference Survey (SP)) was created using survey data to understand travellers’ behaviour in response to factors like travel time, cost, and infrastructure changes, guiding interventions for pilot testing.
Through a newly developed co-creation methodology based on gaming inspirations, workshops have enabled stakeholders, including cities and communities, to engage in solution design, ensuring that proposed urban interventions align with real-world needs.
The UGM has been integrated into the process of creating digital twin models for 3 cities and serves as a framework that bridges data from diverse sources, enabling the development of tailored digital twins for LLs and SIAs. The exploration of interoperability between diverse data models of digital twins will continue to address complex urban scenarios.
The Fotefar application has facilitated high resolution data. This type of collection system is not open-source or commercially available and provides data which was previously unavailable or unmanageable. The data collection may also be able to give a better insight into the travel behaviour in a larger scale study.
The project has actively increased awareness and communication for its objectives, particularly through online channels and events. These initiatives have focused on engaging citizens and policymakers, emphasizing the importance of sustainable mobility solutions. The project has worked to establish synergies with other related initiatives, leveraging existing research to enhance the impact of AMIGOS in advancing sustainable urban mobility.
At the end of the project, the expected results will include a suite of data-driven tools, models, and methodologies that can guide cities in implementing sustainable and inclusive urban mobility solutions. These results are designed to have a lasting impact on urban mobility, helping cities to reduce congestion, promote active and public transport, and enhance safety and accessibility for all citizens.
