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 26th 2019
  • Extended abstract submission deadline: August 25th 2019
  • Notification of acceptance (full papers): July 14th 2019
  • Notification of acceptance (extended abstracts): September 8th 2019
  • Camera ready full papers due: August 18th 2019
  • Symposium: October 8th 2019
  • Location:German Research Center for Artificial Intelligence, Kaiserslautern, Germany
  • Organizers: German Chapter of the ACM

Organizing Committee

Cornelia Denk, BMW, ACM SIGGRAPH Munich Germany
Mario Fritz, CISPA, Germany
Oliver Grau, Intel, Germany, ACM Europe Council
Hans-Joachim Hof, Technical University of Ingolstadt, German Chapter of the ACM
Oliver Wasenmüller, DFKI Kaiserslautern, Germany

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.htmlproceedings-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/CSCS2019
  • 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 Abstract:

  • 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/
    Submissions for “significant, already published work” are also acceptable in their original form (not subject to formatting or page constraints).
  • 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