ADAS Siemens announced software for the data acquisition of driver assistance systems
Editor: Jochen Schwab
Siemens Digital Industries Software announced Simcenter™ SCAPTOR™ software for Advanced Driver Assistance Systems (ADAS) data collection, further expanding the Simcenter™ portfolio for autonomous vehicle performance engineering.
Simcenter SCAPTOR from Siemens Digital Industries Software helps enable closed-loop development of autonomous vehicles by combining hardware and software to record, visualize and replay high-fidelity raw data.
(Source: Siemens)
Simcenter SCAPTOR combines hardware and software to record, visualize and replay high-fidelity raw data, and greatly speeds the development process. By linking ADAS development to noise, vibration and harshness (NVH) and vehicle dynamics performance, the Simcenter™ portfolio now offers a 360-degree view of performance attributes of autonomous vehicles. This enables a closed-loop development process for autonomous vehicles with a solution that spans the physical and virtual aspects of development, including real-world data collection, 1D and 3D modeling for system development and virtual testing. Simcenter is part of the Xcelerator™ portfolio, Siemens’ integrated portfolio of software, services and application development platform.
As autonomous vehicles generate even more data, it is important to bridge the gap between vehicle development and data center technology. The development of safe and reliable autonomous vehicles requires authentic, high-speed, high-fidelity, raw data from multiple sensors. The high-quality nature of this data is essential to train reliable and robust vision and detection algorithms, and to validate and verify the autonomous and advanced driver assistance systems. Simcenter SCAPTOR, developed using proven industry-leading technology from ADAS developer b-plus, helps companies merge test and simulation through the phases of data capture, analysis, exploration, verification and validation and back to data collection. The new capabilities can be used to create a powerful toolchain to record, visualize and replay high-fidelity raw data. It can greatly speed the development process and close the loop of the autonomous development process through real-world ADAS data collection. The solution is flexible, modular, adapts to the requirements of advanced sensor technologies, and is robust for long-term in-vehicle usage.
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