cc-by-nc-nd (Frank Fujimoto)

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

11:00 Opening
11:15 Keynote:
Responsibility Sensitive Safety
Jack Weast, Chief Systems Architect for Automated Driving Solutions, Intel (abstract/biography)
12:15Spotlight presentations of extended abstracts in Security

A Cognitive Assistant for Route Selection Using Knowledge Heuristics
Dan Cunnington, Geeth de Mel
(pdf)

Threading frameworks analysis with respect of production requirements, such as FuSa/ISO 26262
Maxym Dmytrychenko, Ilya Burylov
(pdf)

DRiVERSITY – Synthetic Torture Tests to Find Limits of Autonomous Driving Algorithms
Daniel Frassinelli, Alessio Gambi, Stefan Nürnberger, Sohyeon Park
(pdf)
12:45Lunch & Poster
14:15 Oral Session: Security Evaluation of Autonomous Vehicles

Attacker Model for Connected and Autonomous Vehicles
Jean-Philippe Monteuuis, Jonathan Petit, Jun Zhang, Houda Labiod, Stefano Mafrica, Alain Servel
(pdf)

CyberSecurity Evaluation of Automotive E/E Architectures
Martin Ring,  Davor Frkat, Martin Schmiedecker
(pdf)
15:00 Coffee break
15:30Oral Session: Security for CAN

CAN Obfuscation by Randomization (CANORa) – A technology to prevent large scale malware attacks on autonomous vehicles
Tobias Madl, Jasmin Brückmann, Hans-Joachim Hof
(pdf)

Towards Viable Intrusion Detection Methods For The Automotive Controller Area Network
Andrew Tomlinson, Jeremy Bryans, Siraj Shaikh
(pdf)

A Survey on Media Access Solutions for Controller Area Network Penetration Testing
Enrico Pozzobon, Nils H Weiss, Sebastian Renner, Rudolf Hackenberg
(pdf)
16:30Keynote talk: The art of cyber security orchestration (abstract/biography)
Dr. Thomas Wollinger since 2007 Managing Director ESCRYPT GmbH.
17:30Drinks & Reception
All dates are UTC+1 / CET

September 14th: AI

09:00 Keynote:
Responsibility Sensitive Safety
Jack Weast, Chief Systems Architect for Automated Driving Solutions, Intel (abstract/biography)
10:00Oral Session: AI Safety

AutoRVO: Local Navigation with Dynamic Constraints in Dense Heterogeneous Traffic
Yuexin Ma, Dinesh Manocha, Wenping Wang
(pdf)

Sequential Attacks on Agents for Long-Term Adversarial Goals
Edgar Tretschk, Seong Joon Oh, Mario Fritz
(pdf)
10:45Coffee Break
11:15 Oral Session: AI Sensing

Real Time Single Image Dehazing and Soil Removal Using CNNs
Wajahat Akhtar, Sergio Roa Ovalle
(pdf)

Classification of LIDAR Sensor Contaminations with Deep Neural Networks
Jyothish Karakkaparambil James, Vladislav Golyanik, Georg Puhlfürst
(pdf)
12:00 Spotlight presentations of extended abstracts in AI

Taking advantage of sensor modality specific properties in Automated Driving
Christian Haase-Schuetz
(pdf)

Long-Term On-Board Prediction of People in Traffic Scenes under Uncertainty
Apratim Bhattacharyya, Mario Fritz, Bernt Schiele
(pdf)

Long-range obstacle detection from a monocular camera
Muhammad Abdul Haseeb, Danijela Ristic-Durrant, Axel Gräser
(pdf)

Automated Scene Flow Data Generation for Training and Verification
Oliver Wasenmüller, René Schuster, Didier Stricker,  Karl Leiss, Jürgen Pfister, Oleksandra Ganus, Julian Tatsch, Artem Savkin, Nikolas Brasch
(pdf)

Dense Scene Flow from Stereo Disparity and Optical Flow
René Schuster, Oliver Wasenmüller, Didier Stricker
(pdf)

Risk Averse Robust Adversarial Reinforcement Learning
Xinlei Pan, John Canny
(pdf)
12:45Lunch & Posters
14:00Keynote Talk: Learning to Drive by Learning to See
Andreas Geiger, University of Tübingen, Max Planck Institue for Intelligent Systems (abstract/biography)
15:00Keynote Talk (remote): A future with affordable self-driving vehicles
Raquel Urtasun, Uber ATG, Vector Institute, University of Toronto (abstract/biography)
15:45Coffee Break
16:15Panel Discussion
Georg Kuschk, Group Leader Machine Learning, Astyx GmbH
Karl Leiss, CEO, Bit-TS
Christoph Sorge, Professor Legal Informatics, UdS
Christoph Stiller, Professor MRT, KIT
Shervin Raafatnia, AI Validation Engineer, Bosch
Oliver Wasenmüller, Moderator
15:00Closing Remarks
All dates are UTC+1 / CET

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


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