The symposium took place in Munich, Germany — in proximity to the European Conference on Computer Vision as a satellite event.
2nd ACM COMPUTER SCIENCE IN CARS SYMPOSIUM – (CSCS 2018)
FUTURE CHALLENGES IN ARTIFICIAL INTELLIGENCE & SECURITY FOR AUTONOMOUS VEHICLES
Scope:
Industry, as well as academia, have made great advances working towards an overall vision of fully autonomous driving. Despite the success stories, great challenges still lie ahead of us to make this grand vision come true. On the one hand, future systems have to be yet more capable to perceive, reason and act in complex real-world scenarios. On the other hand, these future systems have to comply with our expectations for robustness, security and safety. ACM, as the world’s largest computing society, addresses these challenges with the ACM Computer Science in Cars Symposium. This conference provides a platform for industry and academia to exchange ideas and meet these future challenges jointly. The focus of the 2018 conference lies on AI & Security for Autonomous Vehicles. Contributions centered on these topics are invited.
Topics:
Submission of contributions are invited in (but not limited to) the following key areas:
- Artificial Intelligence in Autonomous Systems: Sensing, perception & interaction are key challenges — inside and outside the vehicle. Despite the great progress, complex real-world data still poses great challenges towards reliable recognition and analysis in a large range of operation conditions. Latest Machine Learning and in particular Deep Learning techniques have resulted in high performance approaches that have shown impressive results on real-world data. Yet these techniques lack core requirements like interpretability.
- Automotive Security for Autonomous driving: Autonomous cars will increase the attack surface of a car as they not only make decisions based on sensor information but also use information transmitted by other cars and infrastructure. Connected autonomous cars, together with the infrastructure and the backend systems of the OEM, constitute an extremely complex system, a so- called Automotive Cyber System. Ensuring the security of this system poses challenges for automotive software development, secure Car-to-x communication, security testing, as well as system and security engineering. Moreover, security of sensed information becomes another important aspect in a machine learning environment. Privacy enhancing technologies are another issue in automotive security, enforced by legislation, e.g., the EU General Data Protection Regulation. For widespread deployment in real-world conditions, guarantees on robustness and resilience to malicious attacks are key issues.
- Evaluation & Testing: In order to deploy systems for autonomous and/or assisted driving in the real-world, testing and evaluation is key. Giving realistic and sound estimates – even in rare corner cases – is challenging. A combination of analytic as well as empirical methods is required
Program
September 13th: Security
September 14th: AI
General Chair
Oliver Grau, Intel, Germany, ACM Europe Council
Program Chairs
Hans-Joachim Hof, TH Ingolstadt, German Chapter of the ACM
Mario Fritz, CISPA Helmholtz Center i.G.
Organizing Committee
Cornelia Denk, BMW, ACM SIGGRAPH Munich
Oliver Wasenmüller, DFKI Kaiserslautern
Jürgen Pfister, BIT Technology Solutions
Björn Brücher, Intel
Confirmed Program Committee
Ali Al-Bayatti, De Montfort University, Leicester, UK
Björn Andres, Bosch, Germany
Rodrigo Benenson, Google, Switzerland
Chih-Hong Cheng, Fortiss, Germany
Trevor Darrell, UC Berkeley, USA
Gareth Davies, University of South Wales, UK
Lipika Deka, De Montfort University, Leicester, UK
Alexey Dosovitskiy, Intel, Germany
Markus Enzweiler, Daimler, Germany
Uwe Franke, Daimler, Germany
Andreas Geiger, MPI Intelligent Systems, Germany
Rudolf Hackenberg, OTH Regensburg, Germany
Helge Janicke, De Montfort University, Leicester, UK
Christoph Krauß, Fraunhofer SIT
Antonio Lopez, UAB, Spain
Tilo Müller, Friedrich-Alexander Universität Erlangen-Nürnberg, Germany
Andrey Nikishin, Kaspersky Lab, UK
Stefan Nürnberger, CISPA, Germany
Sebastian Renner, OTH Regensburg, Germany
Arvid, Rosinski, Audi, Germany
Bernt Schiele, MPI Informatics, Germany
Vitaly Shmatikov, Cornell, USA
Philipp Slusallek, DFKI, Germany
Didier Sticker, DFKI, Germany
Guangzhi Qu, Oakland University, USA
Armin Wasicek, UC Berkeley, USA
Nils Weiß, OTH Regensburg, Germany
Keynote Speakers
Responsibility Sensitive Safety
Jack Weast, Chief Systems Architect for Automated Driving Solutions, Intel
The art of cyber security orchestration
Dr. Thomas Wollinger since 2007 Managing Director ESCRYPT GmbH.
Learning to Drive by Learning to See
Andreas Geiger, University of Tübingen, Max Planck Institue for Intelligent Systems
A future with affordable self-driving vehicles
Raquel Urtasun, Uber ATG, Vector Institute, University of Toronto
Thank you to our valued
