by Erwin Schoitsch (AIT)

Highly automated and autonomous systems are currently a key issue in many application domains: automotive, transport in general (railways, metro-lines, aircraft, space, ships), industrial automation, health care, cooperating mobile robots and related machines (e.g., fork lifts, off-road construction engines, smart farming, mining, all kind of drones and robots for surveillance, rescue, emergency services, maintenance). Highly automated and autonomous systems play an important role in the ‘digital transformation’ - the strategic and disruptive evolution towards a ‘digital society’, which is the key focus of European Research in Horizon 2020. This is depicted in Figure 1, which is taken from an official presentation of DG CONNECT at various events.

by Daniel Watzenig (Virtual Vehicle Research Center, Graz)

Automated vehicle technology has the potential to be a game changer on the roads, altering the face of driving as we know it. Many benefits are expected, ranging from improved safety, lower stress for car occupants, social inclusion, reduced congestion, lower emissions, and more efficient use of roads due to optimal integration of private and public transport.

by Lan Anh Trinh, Baran Cürüklü and Mikael Ekström (Mälardalen University)

For the last decade, dependability – the ability to offer a service that can be trusted – has been the focus of much research, and is of particular interest when designing and building systems. We are developing a dependable framework for an autonomous system and its control.

by Christoph Schmittner, Zhendong Ma, Thomas Gruber and Erwin Schoitsch (AIT)

Connected, intelligent, and autonomous vehicles pose new safety and security challenges. A systematic and holistic safety and security approach is a key to addressing these challenges. Safety and security co-engineering in the automotive domain considers the coordination and interaction of the lifecycles, methodologies, and techniques of the two disciplines, as well as the development of corresponding standards.

by Baran Cürüklü (Mälardalen University), José-Fernán Martínez-Ortega (Universidad Politécnica de Madrid) and Roberto Fresco (CREA)

Machines are going to become smarter with autonomy as the new standard. Consequently, new services will emerge. For this to happen, however, we need a new approach to autonomy, which assumes different levels – and perhaps more importantly, machines that can handle these different levels.  Adaptive autonomy is a means to achieving this goal.

by Ioannis Chrysakis (ICS-FORTH)

Moving from the traditional to the digital business model gives the opportunity to car manufacturers and new non-traditional players of the car industry to create the autonomous cars of the future.

by Zsolt Szalay, Domokos Esztergár-Kiss, Tamás Tettamanti (Budapest University of Technology and Economics) and Péter Gáspár, István Varga (SZTAKI)

RECAR is a Hungarian research centre for autonomous vehicle technology providing internationally unique education and research with close cooperation with industrial partners. The research centre has technologically advanced laboratories to facilitate high quality R+D+I activities. RECAR is also expected to contribute to the increase in qualified workforce in the automotive industry in Hungary. Info-communication technology is creating big changes in road transportation (vehicles, infrastructure, and passengers) as well as society in general [1]. In the automotive industry, continuous expansion of automation is occurring [2]. In Hungary to date, research projects in the field of autonomous vehicles have been performed separately and in parallel, with little collaboration between institutes.

by Péter Gáspár, Tamás Szirányi, Levente Hajder, Alexandros Soumelidis, Zoltán Fazekas and Csaba Benedek (MTA SZTAKI)

A project was launched at the Institute ‒ relying on interdepartmental synergies ‒ with the intention of joining the autonomous vehicles R&D arena. In the frame of the project, demonstrations of the added capabilities ‒ appreciably making use of multi-modal sensor data ‒ in respect of path-planning, speed control, curb detection, road and lane following, road structure detection, road sign and traffic light detection and obstacle detection are planned in controlled traffic environments.

by Fabio Falcini and Giuseppe Lami (ISTI-CNR)

Deep learning is becoming crucial to the development of automotive software for applications such as autonomous driving. The authors have devised a framework that supports a robust, disciplined development lifecycle for such software, and a comprehensive integration with traditional automotive software engineering.

by Lisa Kristiana, Corinna Schmitt, and Burkhard Stiller (University of Zurich)

Vehicular-to-vehicular (V2V) communications requires a reliable information interchange system. However, in a three-dimensional environment, inevitable obstructions (e.g., road topology and buildings) need to be considered in order to design data forwarding schemes. As one approach, Vehicle-to-Vehicle Urban Network (V2VUNet) introduces Vertical Relative Angle (VRA) as one of the significant factors in the case of a three-dimensional environment.  VRA locates a participating vehicle’s coordinates more precisely, when its position cannot be calculated based only on distance. Therefore, the increased location precision leads to several forwarding algorithms (e.g., prediction mobility and transmission area efficiency), which are expected to overcome frequent topology changes and re-routing.

by Tom van der Sande (Eindhoven University of Technology), Jeroen Ploeg (TNO) and Henk Nijmeijer (Eindhoven University of Technology)

What is the link between cooperative automated vehicles and autonomous vehicles? At the Eindhoven University of Technology, we recently started the i-CAVE (integrated cooperative automated vehicles, STW14893) project, focusing on the development of dual-mode operation of cooperative automated and autonomous vehicles, which will provide an answer to this question. Here we discuss the state of the art of cooperative automated and autonomous vehicles using the guidelines as provided by the Society of Automotive Engineers (SAE) and show that contemporary systems are far from being fully autonomous.

by Alessio Iovine, Elena De Santis, Maria Domenica Di Benedetto (University of L’Aquila) and Rafael Wisniewski (Aalborg University)    

The safety issues associated with autonomous vehicles necessitate more robust and reliable solutions for Adaptive Cruise Control (ACC).  A human-inspired hybrid model with the design goal of replacing and imitating the behaviour of a human driver is being developed, ensuring an appropriate safety level while respecting comfort.

by Jonas Andersson, Azra Habibovic, Maria Klingegård, Cristofer Englund and Victor Malmsten-Lundgren (RISE Viktoria)

For safety reasons, autonomous vehicles should communicate their intent rather than explicitly invite people to act. At RISE Viktoria in Sweden, we believe this simple design principle will impact how autonomous vehicles are experienced in the future.

by Christophe Ponsard, Philippe Massonet and Gautier Dallons (CETIC)

There is a strong move towards assisting the driver, and even relieving the driver from driving duties, in various modes of transportation, including autonomous car, train and aircraft operation. Successive levels of automation are progressively shifting responsibility from the driver to the vehicle. We present a brief comparative analysis of automation levels in the automotive, railway and aeronautic domains with a focus on how to keep the human in the loop both at design and run-time.

by Thierry Fraichard (Inria)

Self-driving vehicles are here and they already cause accidents. Now, should road safety be considered in a trial and error perspective or should it be addressed in a formal way? The latter option is at the heart of our research.

by Robert Rößler, Thomas Kadiofsky, Wolfgang Pointner, Martin Humenberger and Christian Zinner (AIT)

Research at AIT on autonomous land vehicles is focusing on transport systems and mobile machines which operate in unstructured and heavily cluttered environments such as off-road areas. In such environments, conventional technologies used in the field of advanced driver assistance systems (ADAS) and highly automated cars show severe limitations in their applicability. Therefore, more general approaches for environmental perception have to be found to provide adequate information for planning and decision making. As a special challenge, our focus is on vehicles that actively change their environment, e.g., by cutting high plants or manipulating piles of pellet materials. To operate such machines autonomously, novel approaches for autonomous motion planning are required.

by Franco Mazzanti, Alessio Ferrari and Giorgio O. Spagnolo (ISTI-CNR)

Autonomous vehicles will become pervasive in the near future. The TRACE-IT project is investigating how gridlocks may be avoided.

by Farhad Arbab (CWI)

Components that comprise the agents, such as drones, in a distributed cyber-physical system may individually take seemingly reasonable actions, based on their available information Such actions may collectively lead to an eventual unacceptable system behaviour. How can we identify culpable components and agents? At CWI we develop formal models for compositional construction and analysis of such systems, along with tools and techniques to narrow the set of possible components that contribute to undesirable behaviour.

by Damiano Rotondo and Tor Arne Johansen (NTNU)

Small unmanned aircraft working in harsh weather conditions such as those encountered in the Arctic will suffer from the consequences of icing. In order to assure high efficiency and autonomous operation, a robust diagnosis scheme that detects both faults and icing is required. Research at NTNU is focusing on developing these schemes and integrating them with fault tolerant control techniques.