About the workshop

Autonomous driving has made remarkable progress in recent years. Nevertheless, one unsolved question remains: How can autonomous vehicle (AV) systems generalize to new environments or unseen conditions?
This question can be answered from different angles: (1) Use machine learning-based software architectures, (2) use more data, (3) apply heavy simulation & real-world testing or (4) making code open-source available for joint community development. This workshop will go beyond abstract discussions by confronting participants with the real challenges of generalization in autonomous driving. We will stage a direct dialogue between two competing paradigms: (1) modular, open-source ecosystems that thrive on community-driven collaboration, and (2) data-hungry end-to-end approaches that aim to scale through massive models and datasets. What makes this workshop unique is its hands-on character: participants will experience a live, livestreamed demonstration of the TUM EDGAR autonomous vehicle driving on public roads in Munich, providing a concrete basis for in-depth discussions on robustness, safety, and scalability. Through keynotes, interactive sessions, and real-world experiments on topics like domain adaptation, sim-to-real transfer, self-supervised and continual learning, evaluation benchmarks, and software engineering practices, we will collectively ask: which paradigm — modular, end-to-end, or hybrid — can truly deliver generalization in AVs?

Speakers

Marco Pavone
Associate Professor
Stanford University & NVIDIA
Cristina Olaverri-Monreal
Full Professor
JKU Linz
Felix Fent
Postdoctoral Researcher
TU Munich
Hongyang Li
Assistant Professor
University of Hong Kong
Kashyap Chitta
Co-Founder and CTO
KE:SAI

Program

The workshop featured prominent speakers and contributions from the intelligent vehicles and mobile robotics community at ICRA 2026 in Vienna. We thank all speakers and participants for the insightful talks, lively discussions, and strong engagement throughout the session.

Recordings of the talks are now available in the Recordings section below.

Time Talk Title Speaker
14:00 - 14:15 Opening Remarks Johannes Betz
14:15 - 14:45 Generalized Autonomous Driving at Scale Hongyang Li
14:45 - 15:15 From Benchmarks to Real-World Autonomous Driving Cristina Olaverri-Monreal
15:15 - 15:30 Spotlight Session (5 featured spotlights) Contributed Papers
15:30 - 16:00 Coffee Break + Poster Session (13 accepted papers)  
16:00 - 16:30 Democratizing Autonomous Driving Kashyap Chitta
16:30 - 17:00 Embodied Reasoning for Out-of-Distribution Reliability in Autonomy Marco Pavone / Milan Ganai
17:00 - 17:30 Open-Source: A Catalyst for Solving the Generalization Problem? Felix Fent
17:30 - 17:45 Closing Remarks Johannes Betz

Recordings

Recordings of the workshop talks are available below. Press play to load the video from YouTube.

Cristina Olaverri-Monreal's talk was not recorded, at the speaker's request.

Watch the full playlist on YouTube

Accepted Papers

The submission phase is closed. Decisions have been communicated to authors via OpenReview. All accepted papers are invited to participate in the workshop poster session.

  • 23 Submissions
  • 13 Accepted papers
  • 56.5% Acceptance rate
  • 13 Poster invitations

*Where available, the linked PDFs point to the final submissions. If no final submission was provided, the initial submission remains available instead.

We thank all reviewers for their time, expertise, and constructive feedback to the authors.

FAQ

Organizers

Johannes Betz
Assistant Professor
Professorship Autonomous Vehicle Systems
Technical University of Munich
Ilir Tahiraj
PhD Student
Institute of Automotive Technology
Technical University of Munich
Markus Lienkamp
Full Professor
Institute of Automotive Technology
Technical University of Munich
Korbinian Moller
PhD Student
Professorship Autonomous Vehicle Systems
Technical University of Munich

This workshop is supported by the
IEEE‑RAS Technical Committee on "Autonomous Ground Vehicles and Intelligent Transportation Systems", TIER IV, the Autoware Foundation, MIRMI, and the Robotics Institute Germany.