805 research outputs found
Temporal Logic Formalisation of ISO 34502 Critical Scenarios: Modular Construction with the RSS Safety Distance
ISO 34502 の自動運転車危険シナリオを数学的に定式化--安全性保証タスクの自動化・効率化により自動運転の社会受容を促進-- 京都大学プレスリリース. 2024-04-12.SAC '24: 39th ACM/SIGAPP Symposium on Applied Computing, Avila Spain, April 8 - 12, 2024As the development of autonomous vehicles progresses, efficient safety assurance methods become increasingly necessary. Safety assurance methods such as monitoring and scenario-based testing call for formalisation of driving scenarios. In this paper, we develop a temporal-logic formalisation of an important class of critical scenarios in the ISO standard 34502. We use signal temporal logic (STL) as a logical formalism. Our formalisation has two main features: 1) modular composition of logical formulas for systematic and comprehensive formalisation (following the compositional methodology of ISO 34502); 2) use of the RSS distance for defining danger. We find our formalisation comes with few parameters to tune thanks to the RSS distance. We experimentally evaluated our formalisation; using its results, we discuss the validity of our formalisation and its stability with respect to the choice of some parameter values
Risk Management Core -- Towards an Explicit Representation of Risk in Automated Driving
While current automotive safety standards provide implicit guidance on how
unreasonable risk can be avoided, manufacturers are required to specify risk
acceptance criteria for automated driving systems (SAE Level 3+). However, the
'unreasonable' level of risk of automated driving systems (SAE Level 3+) is not
yet concisely defined. Solely applying current safety standards to such novel
systems could potentially not be sufficient for their acceptance. As risk is
managed with implicit knowledge about safety measures in existing automotive
standards, an explicit alignment with risk acceptance criteria is challenging.
Hence, we propose an approach for an explicit representation and management of
risk, which we call the Risk Management Core. The proposal of this process
framework is based on requirements elicited from current safety standards and
apply the Risk Management Core to the task of specifying safe behavior for an
automated driving system in an example scenario.Comment: 16 pages, 6 figure
From Bit To Bedside: A Practical Framework For Artificial Intelligence Product Development In Healthcare
Artificial Intelligence (AI) in healthcare holds great potential to expand
access to high-quality medical care, whilst reducing overall systemic costs.
Despite hitting the headlines regularly and many publications of
proofs-of-concept, certified products are failing to breakthrough to the
clinic. AI in healthcare is a multi-party process with deep knowledge required
in multiple individual domains. The lack of understanding of the specific
challenges in the domain is, therefore, the major contributor to the failure to
deliver on the big promises. Thus, we present a decision perspective framework,
for the development of AI-driven biomedical products, from conception to market
launch. Our framework highlights the risks, objectives and key results which
are typically required to proceed through a three-phase process to the market
launch of a validated medical AI product. We focus on issues related to
Clinical validation, Regulatory affairs, Data strategy and Algorithmic
development. The development process we propose for AI in healthcare software
strongly diverges from modern consumer software development processes. We
highlight the key time points to guide founders, investors and key stakeholders
throughout their relevant part of the process. Our framework should be seen as
a template for innovation frameworks, which can be used to coordinate team
communications and responsibilities towards a reasonable product development
roadmap, thus unlocking the potential of AI in medicine.Comment: 30 pages, 4 figure
08091 Abstracts Collection -- Logic and Probability for Scene Interpretation
From 25.2.2008 to Friday 29.2.2008, the Dagstuhl Seminar 08091 ``Logic and Probability for Scene Interpretation\u27\u27 was held in the International Conference and Research Center (IBFI), Schloss Dagstuhl.
During the seminar, several participants presented their current
research, and ongoing work and open problems were discussed. Abstracts of
the presentations given during the seminar as well as abstracts of
seminar results and ideas are put together in this paper
Description Logic for Scene Understanding at the Example of Urban Road Intersections
Understanding a natural scene on the basis of external sensors is a task yet to be solved by computer algorithms. The present thesis investigates the suitability of a particular family of explicit, formal representation and reasoning formalisms for this task, which are subsumed under the term Description Logic
Computer theorem proving in math
We give an overview of issues surrounding computer-verified theorem proving
in the standard pure-mathematical context. This is based on my talk at the PQR
conference (Brussels, June 2003)
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