Preliminary Conference Programme



Thursday 23 May

Morning Session
09:00 - 12:45

09:00

Software library qualification for ASIL D systems

Dr Oscar Slotosch
Board member
Validas AG
GERMANY
According to ISO 26262, software components and libraries have to be classified into 'unchanged' or 'modified/new' components. New/modified libraries have to be developed according to ISO 26262. However, for usually unchanged libraries, like C/C++ standard libraries or C runtime libraries, there is a simplification in ISO 8-12. In the talk we present the testing requirements for software libraries and how they can be qualified. In addition we present the Validas growing qualification kit for C/C++, which already covers about 200 C library functions and can be used to qualify many others.

09:30

Making cameras self-aware for autonomous driving

Moritz Bücker
Business unit manager
Adasens Automotive GmbH
GERMANY
Two fundamental algorithms addressing the issue of making cameras self-aware of their status are proposed: online targetless calibration based on optical flow, and blockage detection based on image quality metrics (e.g. sharpness and saturation). Online calibration is based on the vanishing point theory; soil/blockage detection is based on the extraction of image quality metrics and the identification of discriminative feature vectors by a support-vector machine. The presentation will include videos and real-world examples from the algorithms running in real time.

10:00

An executable requirement model framework for ADAS software development

Alexander Van Bellinghen
Research engineer
Siemens Industry Software NV
BELGIUM
The introduction of automated driving vehicles leads to increased complexity in automotive software. This paper explains how a formal contract-based software design and testing approach based on an executable requirements model front loads the implementation, validation and verification of ADAS/AV software. Requirements are transformed into engineering contracts that are put on top of the software architecture to ensure architecture consistency, drive the software implementation specification (C/Simulink/…) and channel unit or integration testing. This contract-based design methodology considering requirements as engineering contracts will be explained through an adaptive headlight software use case.

10:30 - 11:15

Break

11:15

Coding a dilemma – legal issues on developing AI solutions

Dr Alexander Duisberg
Partner
Bird & Bird LLP
GERMANY
Developing AI solutions poses a multitude of challenges. Starting from the regulatory framework on AV, implementing privacy by design and default, ensuring functional safety, testing the solutions in 'sandbox conditions', addressing contractual and product liability, all the way up to dealing with the critical ethical issues (dilemma situations) requires a conscious, well-prepared approach. Although 'try as you go' has never been the approach of the industry, the legal requirements on process and proper documentation, as well as managing risk, are critical success factors for AV. The presentation sets out the key issues and discusses possible solutions.

11:45

Safety argument structures for autonomous systems that use machine learning

James McCloskey
Group leader - digital assurance
Frazer-Nash Consultancy Ltd
UK
Machine learning (ML) is making rapid progress in a variety of applications. It is highly likely to be used in safety-related and possibly safety-critical systems. There is a need to consider how to make safety arguments for systems that exploit AI techniques; more generally, there is a need to make safety arguments for autonomous systems that make use of them. This paper presents the work undertaken by a consortium led by Frazer-Nash Consultancy in support of Defence Science and Technology Laboratory to determine the types of safety argument.

12:15

Warp 'driving' – approaching AI’s speed of light

Kirk Boydston
Training data specialist
Samasource
NETHERLANDS
Does it really require infinitely more training data to get your model to 100%? Getting an algorithm to 99%+ accuracy often feels like approaching the speed of light. Although some applications of AI are okay with sub-100% thresholds, anything less than 100% just simply won’t cut it for applications where lives are at stake, (e.g. pedestrian detection). This talk will investigate the emerging best practices derived from 75+ autonomous vehicle projects around breaking free of the 'subluminal' data barrier, and address questions such as does a 'warp drive' to 100% accuracy exist or is there a long, incrementalist slog ahead?

12:45 - 14:00

Lunch and Conference Close

Please Note: This conference programme may be subject to change

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