Increase the safety, comfort and sustainability of transportation by means of automated driving.
Conduct problem-driven research within the interdisciplinary spectrum of machine perception, dynamics and control, and human factors.
Focus on complex (urban) traffic scenarios, on challenging vehicle driving maneuvers and on the interaction of self-driving vehicles with humans.
Latest News
“Efficient Deep Learning” proposal granted by Dutch Science Foundation NWO
Our proposal Efficient Deep Learning (EDL) has been granted by the Dutch Science Foundation NWO. EDL brings together leading Dutch universities working on machine learning and efficient computation, and industry that is developing Big Data applications. See NWO press...
Pavlo Bazilinskyy wins prestigious European Young Researchers Award (EYRA)
Pavlo Bazilinskyy, PhD-candidate in the Intelligent Vehicles group at TU Delft, has won the prestigious European Young Researchers Award 2017. Pavlo Bazilinskyy started a PhD programme at Delft University, as a Marie Curie early stage researcher in the Human Factors...
3sat German TV – Special on IAA
The German 3Sat “Nano” science TV program featured a special regarding the IAA 2017 in Frankfurt on September 15-th, also covering the TU Delft IV group. See link.
On road eye tracking in Sweden and the Netherlands
Example publication(s): Cabrall, C.D.D., Petrovych, V., & Happee, R. (2017). Looking at drivers and passengers to inform driver state monitoring of in and out of the loop. In N.A. Stanton (Ed.), Advances in Human Aspects of Transportation, Springer...
Article on the Remaining Challenges of Self-Driving Vehicles: Interview with Dariu Gavrila in the Dutch NRC Newspaper
A two page article titled De grote datarace: een rijbewijs voor de robotauto (the great data race - a driver license for the robot car) appeared in the Dutch national newspaper NRC (2 Sept. 2017) on the remaining challenges of selfdriving vehicles, featuring an...
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