dSPACE, a leader in simulation and validation in the automotive industry, has joined the Velodyne programme ‘Automated with Velodyne', that aims to accelerate ecosystem interactions and integrate lidar innovations into a range of autonomous solutions including autonomous driving.
Participation in the programme will give dSPACE the opportunity to emulate new laser sensors from Velodyne into simulation solutions at an earlier development stage. dSPACE will also develop simulation models for testing and validation, and provide the sensor simulation environment for validating camera, lidar and radar sensors throughout the development process – accelerating development projects.
The dSPACE simulation solution generates point clouds in real time to simulate objects. The simulation models help determine the most effective positioning of the sensor on the vehicle (sweet spot), as well as the sensor limits (corner cases). Through the partnership programme, Velodyne’s customers will be able to integrate sensor models from dSPACE into their development activities.
“The earlier in the development process that validation can be achieved, the faster new functions for autonomous driving can be safely launched by our customers. The cooperation with Velodyne contributes to this process significantly,” said Caius Seiger, Product Manager Sensor Simulation at dSPACE.
Velodyne, a specialist in 3D lidar systems, has attracted a variety of technology companies to their Automated with Velodyne programme. These companies use lidar technology in various areas – from automotive and aerospace to industrial automation.
“The simulation accuracy provided by dSPACE is remarkably close to reality, and our customers will appreciate the efficiency these Velodyne simulation models will offer them”, said Jon Barad, Vice President of Business Development, from Velodyne. “This capability can effectively support the entire automotive industry in advancing the development of robust and safe ADAS and AV applications.”
dSPACE offers an end-to-end solution for data-driven development that enables consistent processing -- from data acquisition, data annotation, and measurement-data-based scenario generation via sensor simulation, to highly scalable, scenario-based tests in the cloud.
