PhD study programme

Automotive Innovation Lab, as being part of the Slovak Technical University in Bratislava, offers full range of PhD study programme both at Faculty of Informatics and Information Technologies (FIIT) as well as Faculty of Mechanical Engineering (FME).

PhD research topics

Cooperative control for connected automated vehicles  

The topic is focused on autonomous transport in the context of cooperative control, which includes platooning or group start. An effective solution needs to be proposed to increase the flow and safety of traffic. The improved traffic flow results in a reduction in energy consumption and emissions. The topic itself represents a complex problem, within which it is necessary to consider that in the future, there will be vehicles that will not meet the required level of autonomous driving to ensure platooning or group start. Additionally, it is possible to use different types of communication for autonomous vehicles. The communication can occur directly between the vehicles or between the infrastructure and the vehicle. The presented topic provides the possibility of research in the areas of algorithm optimization, architecture design, or solving network problems at the Vehicle-to-Infrastructure or Vehicle-to-Vehicle levels. 

Supervisor: assoc. Prof. Rastislav Bencel, PhD.

Utilisation of 5G for mission-critical applications in connected and cooperative automated mobility 

Cooperative intelligent transport systems are systems that have been rapidly developing recently and are based on an environment of connected (or autonomous) vehicles. These vehicles are connected not only to each other, but also actively communicate with external services or devices, which are the transport infrastructure itself. This connection makes it possible to increase road safety, but also to effectively manage the entire traffic situation. Communication in different networks is usually heterogeneous, different access technologies (wireless, mobile, satellite) and different protocols are used. Effective management and control of such an environment is not a trivial task. It opens up a number of problems that a doctoral student can address in his research. 

Supervisor: assoc. Prof. Peter Trúchly, PhD.

Collective perception and sensory data fusion for connected automated vehicles 

The vehicles, which aim to provide autonomous driving at level 3 and above, are equipped with a number of different sensors, thanks to which they collect huge volumes of data in real time. In order for the vehicle to be able to make informed decisions without compromising safety, it is important to understand this information correctly and to interconnect it appropriately. Also vehicles themselves are being interconnected and with the rising deployment of standalone 5G networks this trend will accelerate. In the field of sensory data fusion, there are a number of open research problems today focused on how to correctly interpret this collected data in the context of autonomous vehicle driving. Due to the huge amount of this data, this topic is especially suitable for those who want to deal with optimization problems and data science during their doctoral research, mobile networks respectively.

Supervisors: assoc. Prof. Peter Trúchly, PhD., Marek Galinski, PhD.

Communication in the Internet of Things environment

The Internet of Things represents a complex structure of non-homogeneous elements with different degrees and levels of intelligence. Its mutual communication therefore represents a different level of complexity and a specific architecture. The topic concerns the issue of investigating a selected part of the methods of this communication, including communication in computer networks. It covers formal methods of describing the properties of communication media and protocols. It is mainly focused on mobile communication means and systems, including the solution of security aspects at different levels.

Supervisor: Prof. Pavel Čičák, PhD.

*Disclaimer: Images are for illustration purpose only and were generated using DALL-E model by OpenAI