This research group carries out research in the field of software development for autonomous vehicles and its testing according to pre-set standards and methods (AUTOSAR, ISO26262). A part of research relates to networks and protocols in vehicles (CAN, LIN, FlexRay). Furthermore, there is a part of research which deals with developing advanced image processing algorithms for automotive cameras used in autonomous driving. Numerous machine learning methods are applied in this process. The research group employs state-of-the-art equipment purchased within the EU project DRIVE.
Another part of the research group deals with intelligent transport systems (vehicular ad-hoc networks, VANETs), aimed at developing, implementing, testing and evaluating algorithms for efficient information propagation between vehicles and infrastructure. There are applications serving various purposes like traffic security improvement (collision avoidance, accident notification), enhanced driving efficiency (traffic congestion monitoring, booking free parking spaces) and commercial services (entertainment, work). It is crucial for every application to provide the right information in the right place at the right time to be able to make informed decisions.
Finally, the research group is also dedicated to analysing the operation and topology of vehicle drives, auxiliary systems and synthesising aimed to optimise the energy flow and energy efficiency of vehicles. Special emphasis is placed on hybrid energy storage systems, advanced power supply systems and power electronics systems for energy control in vehicles. Through modelling and solving inverse engineering problems, the research group tends to develop control methods aimed at improving the efficiency of the vehicle itself and integrating the electric vehicle into the existing transport system according to EU guidelines of integrated, sustainable and efficient transport system.
