TU Graz/ Research/ Fields of Expertise/

Automated Driving

Several different accident statistics show that up to around 90% of traffic accidents are primarily caused by human error. Long and tiring car journeys reduce our quality of life and take up time that could be used to do other things. Incorrect driving styles and a rise in the volume of traffic increase fuel consumption and therefore also the emission of pollutants. The vision of a self-driving car is here and development in the automobile industry is going in the direction of automation: the car of the future is to take us to our destination - and the experience will be safe, relaxed and efficient. Researchers in the Field of Expertise Mobility & Production at TU Graz are investigating numerous technical, ergonomic and social questions prompted by the vision of an automated car.

Source: Branko Rogic – TU Graz/FTG
Source: Fotostudie Sissi Furgler
Arno Eichberger, head of the research field "Driver Assistance, Driving Dynamics, Chassis" with the specialist area "Automated Driving"

The work group Driver Assistance, Driving Dynamics, Chassis focusses on the complex relationship between driver, vehicle and environment, allowing for fascinating, interdisciplinary research in an area that continues to increase in importance - not only for technology but also for society as a whole.

The Vision of a Self-driving Car

A self-driving car would prevent dangerous situations, allow busy drivers to use digital media on the road and increase the mobility of elderly and ill people. Sensors would be able to look ahead and adapt the driving style to make it energy efficient. With many self-driving cars on the road, it would be possible to implement a superordinate traffic management system. This system would improve traffic flow and reduce both journey times and fuel usage for traffic as a whole.

The vision of a self-driving car brings many challenges, which require intensive research. The work group Driver Assistance, Vehicle Dynamics and Suspension at the Institute of Automotive Engineering is focussing on the following topics.

Topic 1

  • Safe functioning of the vehicle: Researchers transmit complex traffic situations to the test bench for testing.

Topic 2

  • Sensor technology: Here, the focus lies on intelligent integration of different sensors for the recognition and interpretation of traffic situations.

Topic 3

  • Human-Machine Interface: In the driving simulator, researchers investigate control elements and display elements to determine whether they can be used intuitively by the driver. 

Topic 4

  • Determination of road conditions combined with automation functions: Researchers are developing a safe and robust system to ascertain current road conditions, with the aim of ensuring that driver assistance and automation functions for actions such as lane changes are safe. 

Safety is Top Priority - Traffic Situations on the Test Bench

The unlimited number of highly complex traffic situations means that it requires a great deal of work to safeguard and coordinate the different systems. Take the city centre as an example: here the automation has to cope with changing lanes, zebra crossings, cyclists, narrow streets and many different turn-offs. The scientific approach consists of bringing the widespread testing of self-driving cars on streets into the laboratory and examining them using test benches and computers. Researchers closely investigate many different traffic situations using modelling and simulation. Using calculations, the automated driving functions are investigated virtually on a conceptual level. See image 1.

Reliable Recognition and Interpretation

For a self-driving car to function safely, the sensors, which are built in and can communicate with each other, need to be able to recognise and interpret traffic situations reliably. With today’s technology, this is made possible by the complex combination of different sensors such as RADAR, cameras and LIDAR. RADAR uses high frequency electromagnetic waves of several GHz (usually 24 GHz and 77 GHz) and LIDAR operates in the optical infrared range. This all means that the car costs more.

The work group Driver Assistance, Vehicle Dynamics and Suspension at the Institute of Automotive Engineering at TU Graz is researching cheaper alternatives that make use of intelligent sensor data provided by integration (data fusion), for example through the verification of camera data using redundant data from the radar sensor as well as bionic solutions. Bionic (also known as biomimicry or biomimetics) focuses on using natural phenomena in technology. Together with the Institute of Zoology, University of Graz is currently investigating the perception and movement of migratory locusts, which move in swarms of millions without colliding with each other, even swerving to avoid birds of prey. 

Initiative Use

Even the best systems are useless in practice if they cannot be operated intuitively by users. At the Institute of Automotive Engineering, a driving simulator has been developed that allows researchers to investigate the interaction between vehicle and driver by means of configurable control and display elements. Researchers use the driving simulator to check the usability and acceptability of new ideas: Can the driver easily use the new function? Does a new display element distract the driver from the traffic?

The simulator consists of a complete vehicle (Mini Countryman) in a light and sound insulated test bench room. It makes use of high quality visualisation, developed by Fraunhofer Austria. A 3D representation of a realistic driving environment with a 180° field of vision is made possible by the use of a parallax barrier, which means that there is no need for 3D glasses. It separates the image matrixes for the left and right eye, resulting in three-dimensional perception. The internal noise simulation, developed by AVL Graz, simulates wheels, wind and motor noise caused by the driver’s car as well as noises from other surrounding vehicles, using bass shakers and loudspeakers in the interior. Feedback on the driving conditions is provided by active use of the steering wheel and pedals - made possible by technology developed by SBW Technology and the Institute of Automotive Engineering at TU Graz. The human-machine interface (control and display devices), involving aspects such as the use of a brake assistant, can be configured individually. Relevant driver information such as line of vision and heart rate are recorded at the same time. One special feature is the simple integration of automated driving functions: virtual sensors and control algorithms for automated vehicle steering can be added to the vehicle model using a Matlab/Simulink © model. The vehicle model itself operates in real time and is based on the AVL software AVL-VSM©.

Road Conditions and Assistance Function

The complete automation of vehicles requires the analysis of complex driving situations, such as lane changes. Researchers are focussing on systematically transferring human driving behaviour ascertained in road trials to new fully automated assistance functions such as the lane change assistant.

The researchers from the specialist area “tyre-road interaction” are developing a system for the identification of road conditions. This will make it possible for automated driving functions to take current road conditions into account when planning and carrying out manoeuvres.

In the development of emergency stop assistant, researchers incorporate factors such as the dynamic of the vehicle when the driver completes an emergency stop, by identifying current and predicted frictional connections between tyres and road. 

Source: Branko Rogic, TU Graz/FTG

Image 1:
The safety of new automated driving functions is ensured by playing through different types of traffic situations, here focussing on the example of changing lanes.

Source: Cornelia Lex
Cornelia Lex, deputy leader of the research field "Driver Assistance, Driving Dynamics, Chassis" with the specialist area "Tyre-Lane Interaction"

Just like drivers, automated driving functions need to take current road conditions into account when planning and carrying out manoeuvres, such as when turning a corner. I am investigating a system to determine road conditions, which is robust and exact enough to be used for safe driving functions.

Source: TU Graz/FTG

The work group Driver Assistance, Vehicle Dynamics and Suspension at the Institute of Automotive Engineering developed the simulator single-handedly. This means that the simulator can be developed in whichever directions necessary, making it possible to investigate different traffic situations.

1st row from left: Markus Stromberger, Florian Büchele, Markus Peer, Arno Eichberger, Matthias Pirstinger, Stefan Bernsteiner

2nd row from left: Erich Erhart, Andreas Podlipnig, Aron Kiraly, Hannes Wohlfahrter, Cornelia Lex, Sajjad Samiee, Zoltan Magosi

Not on the photo: Daniel Hammer

The video shows the driving simulator of the work group Driver Assistance, Driving Dynamics, Chassis of the Institute of Automotive Engineering in use.

Source: TU Graz/FTG

Image of the driving simulator from outside

Source: TU Graz/FTG

Driver’s perspective in the driving simulator, ADSG (Driving Simulator Graz)

Further Information

Institute of Automotive Engineering
Inffeldgasse 11/2
8010 Graz, Austria

Assoc.Prof. Dipl.-Ing. Dr.techn.
Work group leader

Phone: +43 316 873 35210

Cornelia LEX
Dipl.-Ing. Dr.techn.
Phone: +43 316 873 35210

Source: TU Graz/FTG

A research vehicle from interior view:
The engineer observes the measured data and evaluates the validity of the test, e.g. the activation of brake and throttle is invalid in tests with Adaptive Cruise Control and will only be carried by the volunteer driver in case of loss of trust in the automated driving system.

Source: TU Graz/FTG

Two instrumented research vehicles at on-road testing of a Traffic Jam Assist in a simulated Stop-and-Go manoeuvre. The dynamic behaviour of both vehicles is synchronously measured with high precision measurement equipment and afterwards analysed, e.g. whether the behaviour of the automated driving system will be rated well by the volunteer driver or not.

Teamwork Brings Success

The highly complex nature of the interdisciplinary area Driver Assistance, Vehicle Dynamics and Suspension in the Field of Expertise Mobility & Production at TU Graz means that in-depth cooperation with industry and with scientific partner organisations is of great importance.


International Scientific Cooperation

  • K.N. Toosi University of Technology
  • Ludwig Maximilian University of Munich, Germany
  • Tongji University, China
  • Darmstadt University of Technology, Germany
  • Dresden University of Technology, Germany
  • University of Zurich/ETH Zürich 

National Scientific Cooperation

  • Factum Traffic and Social Analysis, Vienna
  • FGM Forschungsgesellschaft Mobilität/Austrian Mobility Research, Graz
  • Fraunhofer Austria GmbH, Visual Computing Work Group
  • Institute of Discrete Mathematics, TU Graz
  • Institute of Electrical Measurement and Measurement Signal Processing, TU Graz
  • Institute of High Voltage Engineering and System Performance, TU Graz
  • Institute of Highway Engineering and Transport Planning, TU Graz
  • Institute of Mechanics, TU Graz
  • Institute of Automation and Control, TU Graz
  • Institute of Statistics, TU Graz
  • Institute of Technical Informatics, TU Graz
  • Institute of Logistics Engineering, TU Graz
  • Institute of Zoology, University of Graz
  • Joanneum Research, Styria and Carinthia 

Partner Organisations in Industry

  • AVL List
  • EBE Solutions
  • MAGNA Steyr Fahrzeugtechnik
  • recoTech
  • RIMAC Automobili
  • SBW Technology LTD.
  • Scheuwimmer Fahrzeugbau
  • Thyssen Krupp Presta