2022 TRAIL International PhD Summer School on Automated Driving

Key information

Date:                     Tuesday 30 August – Thursday 1 September 2022
Location:               Delft University of Technology, Faculty TPM, the Netherlands
Organized by:       Research School for TRansport, Infrastructure and Logistics (TRAIL)
Target group:        International PhD students, both TRAIL and non-TRAIL members
Credits:                 1 ECTS

Organizing committee: Prof. Vincent Marchau (TRAIL/Radboud University), Prof. Bart van Arem (TU Delft), Prof. Bert van Wee (TRAIL/TU Delft), Conchita van der Stelt (TRAIL)

Course manager: Prof. Vincent Marchau

Lecturers: Prof. Bart van Arem (TU Delft), Dr. Niels Agatz (EUR), Dr. Simeon Calvert (TU Delft), Dr. Goncalo Correia (TU Delft), Dr. Haneen Farah(TU Delft), Prof. Vincent Marchau (TRAIL/Radboud University), Prof. Henk Meurs (Radboud University), Prof. Filippo Santoni (TU Delft), Dr. Maaike Snelder (TU Delft), Prof. Bert van Wee (TRAIL/TU Delft)

The 3rd edition of the summer school on Automated Driving (AD) was held at the TU Delft: 27 participants registered, coming from different countries: the Netherlands (10), Belgium (3), Germany, (1), Finland (2), USA (1), Italy (3), Sweden (1), Turkey (1), Australia (2), Portugal (1), United Kingdom (1), China (1). 20 PhD students participated onsite and 7 online.

The program included lectures on an overview of AD and on its societal  impacts on day 1, lectures on possible AD-markets and lectures on AD-impacts on traffic and travel on day 2, and AD-policy lectures on day 3. There was also a three-day assignment in mixed online/onsite groups, culminating in a presentation and discussion. This assignment involved the specification (and motivation) of a major priority for research and development in the next years concerning Automated Driving.

Participants appreciated in particular the variety and quality of the subjects, the lecturers, the mutual possibilities for interaction among participants, and the site-visit at the TU Delft Automated Vehicle Lab.


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