networked car on the road

Applications

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

V2X

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

V2X

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

References

Current
Projects

SMACS

In diesem Projekt wurde die Verwendbarkeit von Second-Life-Batterien für die stationäre Speicherung untersucht. Wir entwickelten ein Design-Tool zur Auswahl geeigneter Batteriezellen oder -module auf der Grundlage von Alterungsmechanismen.

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SIMBAT

This project developed a multi-physics simulation model to evaluate thermal safety in vehicles.

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LEWE

Low-noise and low-vibration turnout

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PREVENT+

This project focuses on the simulation framework for particle-gas flow inside a battery pack. ​

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LIBERTY

LIghtweight Battery System for Extended Range at Improved SafeTY

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Use Cases

Further Topics

Future car

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