YouTube AV 50K: An Annotated Corpus for Comments in Autonomous Vehicles

With one billion monthly viewers, and millions of users discussing and sharing opinions, comments below YouTube videos are rich sources of data for opinion mining and sentiment analysis. We introduce the YouTube AV 50K dataset, a freely-available collections of more than 50,000 YouTube comments and metadata below autonomous vehicle (AV)-related videos. We describe its creation process, its content and data format, and discuss its possible usages. Especially, we do a case study of the first self-driving car fatality to evaluate the dataset, and show how we can use this dataset to better understand public attitudes toward self-driving cars and public reactions to the accident. Future developments of the dataset are also discussed.Comment: in Proceedings of the Thirteenth International Joint Symposium on Artificial Intelligence and Natural Language Processing (iSAI-NLP 2018

Merging self-driving cars with the law

Self-driving cars are gradually being introduced in the United States and in several Member States of the European Union. Policymakers will thus have to make important choices regarding the application of the law. One important aspect relates to the question who should be held liable for the damage caused by such vehicles. Arguably, product liability schemes will gain importance considering that the driver's fault as a cause of damage will become less likely with the increase of autonomous systems. The application of existing product liability legislation, however, is not always straightforward. Without a proper and effective liability framework, other legal or policy initiatives concerning technical and safety matters related to self-driving cars might be in vain. The article illustrates this conclusion by analysing the limitation periods for filing a claim included in the European Union Product Liability Directive, which are inherently incompatible with the concept of autonomous vehicles. On a micro-level, we argue that every aspect of the Directive should be carefully considered in the light of the autonomisation of our society. On the macro-level, we believe that ongoing technological evolutions might be the perfect moment to bring the European Union closer to its citizens. (C) 2018 Jan De Bruyne and Jarich Werbrouck. Published by Elsevier Ltd. All rights reserved

Business Case and Technology Analysis for 5G Low Latency Applications

A large number of new consumer and industrial applications are likely to change the classic operator's business models and provide a wide range of new markets to enter. This article analyses the most relevant 5G use cases that require ultra-low latency, from both technical and business perspectives. Low latency services pose challenging requirements to the network, and to fulfill them operators need to invest in costly changes in their network. In this sense, it is not clear whether such investments are going to be amortized with these new business models. In light of this, specific applications and requirements are described and the potential market benefits for operators are analysed. Conclusions show that operators have clear opportunities to add value and position themselves strongly with the increasing number of services to be provided by 5G.Comment: 18 pages, 5 figure

Neural Networks for Safety-Critical Applications - Challenges, Experiments and Perspectives

We propose a methodology for designing dependable Artificial Neural Networks (ANN) by extending the concepts of understandability, correctness, and validity that are crucial ingredients in existing certification standards. We apply the concept in a concrete case study in designing a high-way ANN-based motion predictor to guarantee safety properties such as impossibility for the ego vehicle to suggest moving to the right lane if there exists another vehicle on its right.Comment: Summary for activities conducted in the fortiss Eigenforschungsprojekt "TdpSW - Towards dependable and predictable SW for ML-based autonomous systems". All ANN-based motion predictors being formally analyzed are available in the source fil