Automated Driving & Driver Assistance

No other technology changes the driving experience of a vehicle as strongly and sustainably as the new assistance functions and the automation of driving. The vehicle is continuously changing into a mobile living space. Mastering this transformation process secures the technological leadership and economic success of automobile manufacturers and suppliers and characterizes a successful national and European transport policy.

The transformation is reflected in ever more powerful driver assistance systems: Vehicles recognize lane boundaries and traffic signs. They understand the condition and needs of drivers and passengers. They adjust to the driver and passengers, perform automatic emergency braking or are able to follow the preceding vehicle automatically. However, a variety of interdisciplinary research and development work is still required to make self-driving vehicles suitable for everyday use in road traffic.

Fraunhofer Automotive bundles the necessary competencies - e.g. in the fields of communication technology, microelectronics, artificial intelligence, algorithms, reliability, big data, test engineering and human-technology-environment-interaction. In addition, the institutes are also working in the areas of system engineering and systems research on business models, acceptance research and the analysis of the economic and social framework conditions for passenger and freight traffic in order to accompany manufacturers and suppliers and to be able to set new impulses on the way to autonomous driving.

1. Radar Technologies and Sensor Applications

Messfahrzeug REDAR des Fraunhofer ITWM
© Fraunhofer ITWM
Measuring vehicle REDAR

Radar technologies are a key for many driver assistance functions and especially for autonomous driving. Together with ultrasonic technologies and camera-based processes that use visible light or infrared radiation, radar sensors provide environmental information for automated driving functions. Compared to cameras, the radar is robust under poor visibility conditions. However, the sensors are not only important for the detection of the environment. They can also be used in the interior to detect critical driver conditions and monitor the interior situation for safety and comfort functions and to provide services.

Modern ADAS and AD systems require high-precision map data and highly accurate georeferenced 3D environmental models that serve as ground truth for the development and testing of assistance and automation systems.

In order to capture 3D environmental data as a basis for realistic simulations, a measurement vehicle with state-of-the-art laser measurement technology was set up at Fraunhofer ITWM. This multisensor measuring system REDAR (Road and Environment Data Acquisition Rover) consists of the following main components:

  • Inertial system with DGPS and distance sensor
  • 2 laser scanners
  • 6 high-resolution cameras

The data collected with REDAR forms the basis for the VMC® Road and Scene Generator.


  • Equipping vehicles with sensors, especially cameras, radars and evaluation technology
  • Development and qualification of specialized 24-GHz and 77-GHz radar sensors
  • Antenna development for the automotive industry, automotive radars based on LTCC technology
  • Investigation and characterization of materials (e.g. bumpers, plastic parts on the vehicle) with regard to their electromagnetic properties
  • Simulation of radar signatures in software-in-the-loop as well as in hardware-in-the-loop applications
  • Digitization of real test tracks for (multi-body) simulations,
  • Recording of real environment for virtual 3D landscape and city models, especially for use in interactive driving simulators (e.g. in RODOS©)
  • Creation of virtual scenarios from map data and 3D laser scans (e.g. in OpenDrive format) with the VMC® Road and Scene Generator


Project examples

2. Driver Assistance Systems

© metamorworks -

Driver assistance systems support the driver in driving the vehicle and can make a fundamental contribution to increasing safety, thus reducing the number and consequences of accidents, improving the driver's performance and increasing driving comfort. Powerful sensor systems suitable for vehicle use are being developed for »machine-based understanding« of driving situations. In order to test new driver assistance systems and concepts with regard to their usability and acceptance as well as the potential effects on road safety and driving comfort, empirical investigations are carried out in the driving simulator and in real traffic.


  • Software development for sensor, image and video data processing in vehicles, especially for lane and obstacle detection
  • Development of vehicle and driver-adapted safety and warning functions (e.g. for tracking, collision avoidance)
  • Development of driver assistance systems for two-wheelers
  • Equipping vehicles with sensors, especially cameras, radars and evaluation technology
  • Development of specialized 24-GHz and 77-GHz radar sensors for driver assistance solutions
  • Rapid Prototyping and simulation of assistance functions and MMI concepts
  • Driving tests in simulators as well as with vehicles on test tracks and in real traffic
  • Development of methods and tools for the evaluation of driver assistance systems
  • Creation of simulation models for routes, vehicles, display and operating elements
  • Ergonomic studies of display, operating and interaction concepts
  • Design and simulation of infrastructure concepts (e.g. intersection design)
  • Metrological recording and generation of realistic scenarios (e.g. in OpenDrive or OpenScenario format) with the VMC® Road and Scene Generator for virtual testing and validation of ADAS & AD functions


Project examples

3. Driving Automation

Versuchsfahrzeuge für Technologie-Experimente (VERTEX)
© Fraunhofer IOSB
Experimental Vehicles for Technology Experiments (VERTEX)

Autonomous driving moves society and the professional world. While on the one hand it is being discussed under which circumstances and under which legal conditions (fully) automated driving is possible, on the other hand the research and development departments are constantly advancing the technological possibilities. Last but not least, prominent examples such as the Google car, Daimler's Bertha-Benz drive in Baden-Württemberg, the distance travelled by a self-driving Audi A7 from Silicon Valley to Las Vegas and the self-driving vehicles in the city traffic of Shanghai, Parma and Braunschweig show the rapid technological progress. But automated driving also offers potential for freight transport and innovative logistics solutions.

The transformation to autonomous driving takes place in five stages. Before vehicles can operate autonomously in all situations, efficient and affordable technologies must be developed. Aspects of reliability and cyber security must be clarified. Answers to ethical and insurance law questions must be found. Legal framework conditions must be created for this purpose. The currently volatile social acceptance and the expected market acceptance must be taken into account. These socio-technical aspects result in a branch of research that deals with the occupants of automated vehicles and their activities from a technological, psychological and sociological point of view, which go far beyond the classical aspects of human-vehicle interaction.


  • Development and investigation of control transfer scenarios and procedures for semi-automated driving
  • Sensors and algorithms for the automation of motion tasks
  • Development of specialized 24-GHz and 77-GHz radar sensors for vehicle automation
  • Development of situation prediction and manoeuvre planning, sometimes using AI for complex driving situations
  • Evaluation of deployment scenarios in freight transport and urban logistics
  • Studies on autonomous driving in passenger and freight transport
  • Alternative activities in vehicles - research and development of mobile living spaces with empirical methods in studies and experiments in simulators and on the road
  • Investigation of complex interaction patterns between automated and non-automated road users (mixed traffic) in interactive simulation
  • Networking of interactive driving simulators with pedestrian interaction (virtual reality laboratories)
  • Development of concepts for validation & verification of highly automated driving functions
  • Simulation methods for highly automated driving functions

Project examples


Studies and Publications

4. Human-in-the-Loop Driving Simulation

Fahrsimulator RODOS® am Fraunhofer ITWM im Einsatz
© Fraunhofer ITWM
RODOS® Driving Simulator

Driving simulators outside the real traffic situation with the human in the control loop are used for training purposes, in driving research and in vehicle development. The latter is also due to the fact that, for many applications, human cognition and behavior cannot be represented by a digital model. Driving simulation in virtual reality already provides a product experience in early development phases of vehicles and vehicle systems and clarifies questions of acceptance, usability and user experience.

In addition, driving simulators with real drivers and virtual road traffic allow controlled investigation conditions for empirical studies and statistically secured R&D results. They allow the investigation of high-risk situations, risk groups of drivers and passengers and rare driving situations. And they enable efficient tests under standardized conditions and traffic situations.


  • Simulation of high-risk traffic situations
  • Hybrid simulation with hardware, software and human in the control loop
  • Empirical research into driving behavior under controlled simulated conditions
  • Empirical studies on the vehicle as »third« living environmen
  • Investigation of symptoms of motion sickness (kinetosis) during automated driving
  • Planning, execution and evaluation of test person studies on driver-vehicle-environment-interaction (communication between road users, driver-vehicle communication, communication between automated vehicles and pedestrians, intention mediation etc.)
  • Concept studies for driver assistance and automation functions
  • Safeguarding driver assistance functions and driving automation
  • Real-time simulation, audibility and evaluation of acoustic vehicle, component and environmental properties under realistic audiovisual conditions


Project examples