2. 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
follow 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.


IMPORTANT DATES & LOGISTICS
Full paper submission deadline: May 6 2018
Extended abstract submission deadline: July 2 2018
Notification of acceptance (full papers): July 2 2018
Notification of acceptance (extended abstracts): July 31 2018
Camera ready full papers due: July 31 2018
Symposium: September 13+14 2018
Location: Munich, Germany
Organizer: German Chapter of the ACM

ORGANIZING COMMITTEE
Cornelia Denk, BMW, ACM SIGGRAPH Munich
Mario Fritz, MPI Informatics
Oliver Grau, Intel, Germany, ACM Europe Council
Hans-Joachim Hof, TH Ingolstadt, German Chapter of the ACM
Oliver Wasenmüller, DFKI Kaiserslautern

CONFIRMED PROGRAM COMMITTEE
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
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
Antonio Lopez, UAB, Spain
Andrey Nikishin, Kaspersky Lab, UK
Stefan Nürnberger, CISPA, Germany
Arvid, Rosinski, Audi, Germany
Bernt Schiele, MPI Informatics, Germany
Vitaly Shmatikov, Cornell, USA
Didier Sticker, DFKI, Germany
Guangzhi Qu, Oakland University, USA
Armin Wasicek, UC Berkeley, USA


FULL PAPERS:
- SUBMISSION: We are inviting industrial and academic participation in the
event. We are looking for high-quality, original contributions to our peer
reviewed “Full Paper” track with oral and poster presentations. The research
papers must be formatted according to the acm-sigconf-authordraft template,
which can be obtained from
http://www.acm.org/publications/article-templates/proceedings-template.html.
Page limit is 8 pages with an additional 9th page only containing references.
Accepted papers will be published as a conference publication in the ACM
Digital Library. Contributions have to be submitted in the “Full Paper” track by
the deadline specified below at https://cmt3.research.microsoft.com/CSCS2018/

- REVIEW PROCESS: The review process is double blind, that is, authors do not
know the names of the reviewers of their papers, and reviewers do not know the
authors' names. Avoid providing information in the submission that may
identify the authors in the acknowledgments where possible (e.g., company,
co-workers and grant IDs). Avoid providing links to websites that identify the
authors.


EXTENDED ABSTRACTS:
- SUBMISSION: We are inviting submissions for the “Extended abstracts” tracks
with poster presentation -- with online publication (this does not count as
references publication) -- in the following 5 categories: demo, exhibitions,
discussion papers, PhD position paper, and significant, already published work.
The extended abstracts must be formatted according to the
acm-sigconf-authordraft template which can be obtained from
http://www.acm.org/publications/article-templates/proceedings-template.html.
Page limit is 2 pages with an additional 3rd page only containing references.
Contributions have to be submitted in the “Extended Abstract” track by the
deadline specified below at https://cmt3.research.microsoft.com/CSCS2018/

- REVIEW PROCESS: The review process is light-weight and single blind, that is,
the authors, do not know the reviewers' names, but the submission does
not have to be anonymized.


For more information - please visit http://cscs.mpi-inf.mpg.de