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dSPACE

Rathenaustr. 26
Paderborn, 33102
Germany
  • Value Proposition

    Data is crucial for the development of self-driving vehicles because they use a large number and types of sensors to perceive their environment, generating a wealth of information that has to be evaluated. AI-based solutions from dSPACE ensure that the right data is available in the right quality and quantity. Simulation solutions from dSPACE make development and testing in the virtual domain just as realistic as the real world – and with much more efficiency. dSPACE with its 30+ years of experience enables to bring safe and reliable vehicles, algorithms, and controllers faster to the market.

  • Use Case/Customer Profile

    Automotive, as well as other industries, use dSPACE’s comprehensive, end-to-end solutions to efficiently test the vehicle software and hardware components, ensuring safety and reliability, long before a new model is allowed on the road. That is why all major automotive OEMs and suppliers rely on dSPACE.

  • Technology Description

    dSPACE hardware and software simulation solutions take into account the vehicle, the traffic, environment, and perception sensors such as lidar, radar, and camera. dSPACE offers an end-to-end, seamless solution for data-driven development, from data logging to data enrichment, from measurement data-based scenario generation to sensor simulation and large-scale scenario-based testing in the cloud.

    The sensor simulation models provide the behavior of lidar sensors such as Velodyne VLP-16, VLP- 32, and HDL-64 with more to come. These models speak the Velodyne protocol so they can substitute the real sensors in various use cases, including test, development, and visualization without adjustments on the receiver side.

    In addition, the Real-time Multisensor Application RTMaps enables users to time-stamp, record, synchronize, and playback data from various sensors and vehicle buses. RTMaps contains ready-to-use components for:

    • Retrieving point clouds from real Velodyne sensors or dSPACE sensor models
    • Log point clouds during a test-drive
    • Replay of point clouds for testing and validating functions
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