networked car on the road


Cooperative, Networked, Automated Mobility

Intense research is done in terms of self-driving cars, but would drivers even get on board?

At VIRTUAL VEHICLE, we have been researching groundbreaking technologies for more than 12 years, such as Lidar sensors, Car-2-Car communication, and Data Exchange Platforms.


Did you know that we developed the first self-driving car in Austria at VIRTUAL VEHICLE back in 2015?

With over 20 ongoing EU projects focused on automated driving, our research center has attained a leading international position.

Central Research Topics


  • Development of self-driving vehicles (Level 3 and beyond)
  • Supporting anticipatory driving behavior through driver assistants
  • Exploring inhibiting factors of drivers and how these can be reduced


How We Support Our Customers

Automated Drive Demonstrator

Performance tests and validation on public roads and test tracks


Definition of use cases and test plans


Traffic simulations


Connectivity via mobile and V2X


Open Vehicle Development Platform

Integration and evaluation of functions (perception, planning, control, localization, etc.)


Provision of automated driving functions


Digital twin of the vehicle for different simulation environments


CI/CD pipeline for efficient development

AD Sensor Integration


Provision of sensor and vehicle data


Algorithm development


Sensor fusion


Reference measurement sensors

Austria’s First Self-Driving Car

Automated Drive Demonstrator

With our test vehicle, the Automated Drive Demonstrator, we explore various methods of autonomous driving. State-of-the-art sensor technology is used to enable a 360-degree view.

Additionally, we have developed algorithms and “Embedded Intelligence” to test various functions of autonomous driving.


Trust in Automated Driving
In addition to technical feasibility, the human factor also plays an important role. We study why drivers might hesitate to let go of control of their vehicles, and we take this into account in our research.

ADD Fusion

Lidar Sensor Technology

Lidar, abbreviated for Light Detection and Ranging, is a remote sensing technology that uses laser light to measure distances and create detailed three-dimensional maps of the surroundings.


Applications in autonomous driving include:


  • Object detection: Lidar helps identify and classify objects like pedestrians, vehicles, and obstacles.
  • Mapping and localization: Lidar creates high-resolution maps and supports precise vehicle localization in its environment.
  • Obstacle avoidance: Lidar data is used to detect obstacles on the vehicle’s path and make real-time decisions for safe navigation.
  • Path planning: Lidar information is crucial for planning the vehicle’s path through dynamic and complex environments.


Lidar Sensor


Car-2Car Communication

Self-driving vehicles need to communicate with each other in order to operate effectively in traffic.


We test this so-called Car-2-Car communication with our autonomous test vehicles. In “Car2Car,” vehicles inform each other about their route to avoid collisions and optimize their own route. They also warn each other about traffic jams and hazards like black ice.

Car-2-Car communication


Vehicle-to-Infrastructure Communication

Vehicle-to-Infrastructure (V2I) communication refers to the exchange of information between vehicles and surrounding infrastructure elements such as traffic lights, road signs, and other transportation systems.


V2I-communication is crucial for autonomous vehicles as it provides real-time information about road conditions, traffic, and the status of infrastructure.


This helps autonomous vehicles navigate safely and efficiently through complex environments.



Vehicle-to-Infrastructure Communication




The overarching goal is to gain insights into aspects such as usability, trust, and acceptance, contributing to a comprehensive understanding of the project’s outcomes and implications.

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The research project will develop novel LiDAR-based systems for predictive hazard assessment with VRUs in urban areas. Achieving a substantial enhancement in both field of view and resolution necessitates innovations across all components of a LiDAR sensor.

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Use Cases

Further Topics

Future car


Get in Touch with Us and Accelerate Your Innovation