The SEGVAUTO-4.0-CM project (2019–2023) was a collaborative scientific research program funded by the Community of Madrid through its call for grants for R&D programs among research groups (TRA2016-78886-C3-1-R), coordinated by the Polytechnic University of Madrid (UPM) in partnership with the UAH and the UCM. The main objective of this public initiative was to lay the technological foundations for an advanced, clean, and accessible transportation ecosystem, promoting knowledge transfer between the academic sector and the region’s automotive industry.

On the technical front, the project deployed artificial intelligence algorithms for decision-making in autonomous driving, cooperative vehicle-to-infrastructure (V2X) communication systems, and high-resolution 3D mapping. It also incorporated advanced computer simulations for the energy optimization of clean vehicles and virtual reality environments designed to study occupant safety and pedestrian interaction with the new automated environments.
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In the area of protecting vulnerable users, pedestrian safety tests focused on characterizing human behavior in the moments leading up to a collision using immersive virtual reality environments. Through simulations involving volunteers equipped with VR headsets and biometric sensors, researchers at INSIA-UPM analyzed critical variables such as reaction times to the unexpected appearance of an autonomous vehicle, people’s intuitive evasion trajectories, and their physiological stress indicators.
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