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Keynote Lectures

Human Factors and Intelligent Vehicle Technologies
Cristina Olaverri Monreal, University of Applied Sciences Technikum Wien, Austria

Towards Future Mobility with Mesh Connected Vehicles
João Barros, Veniam, Portugal

Autonomy Requirements for Smart Vehicles
Emil Vassev, Lero - The Irish Software Research Centre, UL, Limerick, Ireland


Human Factors and Intelligent Vehicle Technologies

Cristina Olaverri Monreal
University of Applied Sciences Technikum Wien

Brief Bio


Dr. Cristina Olaverri Monreal graduated with a Master’s degree in Computational Linguistics, Computer Science and Phonetics from the Ludwig-Maximilians University (LMU) in Munich 2002 and received her PhD 2006 in cooperation with BMW.
She currently leads the Competence Team “Intelligent Technologies in Smart Cities” at the University of Applied Sciences Technikum Wien, Austria. Her research aims to minimize the barrier between users and systems in complex, dynamic scenarios that are critical to decision making processes, such as driving a vehicle and innovative forms of mobile and ubiquitous interaction approaches to human mobility. Her research interests lie in multi-functional systems for in-vehicle information and entertainment; overall efficiency of user and system utilization; driver behavior; simulation tools and research concerning Intelligent Transportation Systems (ITS). Dr. Olaverri is chair of the Technical Activities Committee on Human Factors in ITS. She is Vice-president of Educational Activities in the IEEE ITS Council Executive Committee and a member of the IEEE ITS Board of Governors (BoG). In addition, she serves as an associate editor and editorial board member of several journals in the field, including the IEEE Intelligent Transportation Systems Transactions and the IEEE International Transportation Systems Magazine.

Intelligent Vehicle (IV) technologies have in the last couple of decades greatly improved the perception of the road environment. However, their effect on road safety still demands appropriate methods and tools, especially considering the continued, gradual integration of mobile environment applications for the vehicular context, which compete with other systems already available in the car. Whereas the feasibility of incorporating new technology-driven functionality to vehicles has played a central role in automotive design, safety issues related to usability and human capabilities and which affect a system’s operation have not always been taken into consideration. This presentation gives an overview of the impact of IV technologies, including automation, on driving performance and safety.



Towards Future Mobility with Mesh Connected Vehicles

João Barros

Brief Bio
João Barros Founder and CEO of Veniam
An award-winning wireless engineer, academic leader and passionate entrepreneur, João loves to turn complex theorems and algorithms into products and services that can make a real difference in people's lives. After more than a decade developing new wireless networking technologies at Technische Universitaet Muenchen, Universidade do Porto, MIT, and Carnegie Mellon, João founded two venture-backed startups, Streambolico and Veniam, where he serves as board director and CEO respectively. His work has led to 160 science and technology papers, as well as feature articles by NPR, BBC, MIT Technology Review, The Atlantic, and TechCrunch.
João Barros has received several awards, including the 2010 IEEE Communications Society Young Researcher Award for the Europe, Middle East and Africa region, the 2011 IEEE ComSoC and Information Theory Society Joint Paper Award, the 2012 BES National Innovation Award, the 2013 Building Global Innovators Grand Prize (ISCTE-IUL and MIT) and a state-wide best teaching award by the Bavarian State Ministry of Sciences, Research and the Arts.
João Barros has a Ph.D. degree in Electrical Engineering and Information Technology from the Technische Universitaet Muenchen (Germany), his undergraduate education in Electrical and Computer Engineering from the Universidade do Porto, Portugal and Universitaet Karlsruhe, Germany, and a performing arts degree in flute from the Music Conservatory of Porto, Portugal.

The most cost-effective solution to acquire massive amounts of actionable urban data and expand wireless coverage for everyone in the city may be to rapidly connect as many vehicles moving around the city as possible. In fact, vehicles are everywhere, have large batteries, come with dozens of sensors and benefit from a dedicated frequency band (DSRC 5.9 GHz). Once we turn vehicles into mobile Wi-Fi hotspots, they can connect to many other things – inside and outside of the vehicle – serving as the perfect data couriers for the Internet of Things. Last but not last, they can easily connect with each other over high-speed wireless links, building mesh networks that can span an entire city.
After our company Veniam connected hundreds vehicles with multi-purpose, multi-network onboard units in September 2014, this real-world mesh has served more than 5 million Internet sessions and has since proven to be a real asset as Porto strives to overcome the digital divide, increase safety, reduce pollution, and control traffic. Singapore and New York City are now following suit.
Since roughly 26% of the world’s 1.2 billion vehicles belong to enterprise fleets that generally travel many miles every day, starting with commercial vehicles like buses, taxis and shared vehicles appears to be the best strategy to scale the number of connected vehicles. Add to that the current trend towards mobility as an on-demand service – which will probably be provided in the near future by fleets of shared autonomous vehicles. Soon this strategy may actually be the only one we need to create vibrant connected cities with exciting new mobility services worldwide.



Autonomy Requirements for Smart Vehicles

Emil Vassev
Lero - The Irish Software Research Centre, UL, Limerick

Brief Bio
Dr. Emil Vassev received his M.Sc. in Computer Science (2005) and his PhD in Computer Science (2008) from Concordia University, Montreal, Canada. Currently, he is a Senior Research Fellow at Lero-the Irish Software Research Centre, University of Limerick, Ireland where he has led and is currently leading a few important projects including projects with the European Space Agency. Dr. Vassev's research focuses on knowledge representation and awareness for self-adaptive systems. A part from the main research, his research interests include engineering autonomic systems, compilers (including llvm), distributed computing, formal methods, cyber-physical systems and software engineering. He has published three books and over 140 internationally peer-reviewed papers, including the recently published book on "Autonomy Requirements and Engineering for Space Missions". As part of his collaboration with NASA, Vassev has been awarded two patents.

In one aspect of our life or another, today we all live with AI. For example, the mechanisms behind the search engines operating on the Internet do not just retrieve information, but also constantly learn how to respond more rapidly and usefully to our requests. Basically, AI depends on our ability to efficiently transfer knowledge to software-intensive systems. A computerized machine can be considered as one exhibiting AI when it has the basic capabilities to transfer data into context-relevant information and then that information into conclusions exhibiting knowledge.

Closely related to AI, autonomous systems not only exhibit knowledge but also autonomously interact with their operational environment and perceive important structural and dynamic aspects of the same. The underlying mechanism for this autonomy helps such systems monitor, draw inferences and react. The integration and promotion of autonomy in software-intensive systems is an extremely challenging task. Among the many challenges software engineers must overcome are those related to elicitation and expression of autonomy requirements.

In this talk, the speaker will draw upon his experience with the Autonomy Requirements Engineering (ARE) approach to present how ARE handles autonomy requirements for smart vehicles. The emphasis will be put on using ARE to extend upstream control software with special self-managing objectives (self-* objectives) intended to provide an ability to autonomously and automatically discover, diagnose, and cope with various problems that need to be overcome during car operation.