Mentor Announces Autonomous Driving Design Platform 'DRS360'
Integrated Management of Raw Data and Real-time Sensing Capabilities

Mentor (Siemens Business), which has demonstrated outstanding software technological capabilities in the automotive field through Linux, AUTOSAR and other solutions, has unveiled a hardware platform with self-developed architecture, expressing confidence in the autonomous vehicle market.

By utilizing innovative technologies applied to 'DRS360', an autonomous vehicle design platform, raw data can be captured and integrated in real time from a wide range of sensing methods including radar, LIDAR, vision and other sensors. The DRS360 platform significantly reduces the latency required for SAE Level 5 autonomous vehicle design verification and dramatically improves sensing accuracy and overall system efficiency.


DRS360 is the first autonomous driving platform to directly transmit unfiltered information from all system sensors to the central processing unit for real-time fusion at all levels. Through partnerships with major sensor suppliers, the innovative "raw data sensors" adopted in this platform are equipped with microcontrollers, eliminating power, cost, and size concerns required for the associated processing.

Removing preprocessing microcontrollers from all system sensor nodes provides extensive advantages. Real-time performance is achieved, system cost and complexity are significantly reduced, and by accessing all captured sensor data, the highest resolution model of vehicle environment and driving conditions can be obtained.

Amin Kashi, Director of ADAS and Autonomous Driving Division, stated "Traditional data processing in ADAS has been a distributed processing approach, but Mentor has achieved a paradigm shift to a centralized data processing method," adding "This approach lowers costs, simplifies the system, and increases efficiency accordingly."

In other words, due to continuously added sensors, current ADAS systems inevitably encounter delays by obtaining only partial data, but this can now be intelligently processed through a centralized processing platform.

Enables Use in Systems Complying with ISO 26262 ASIL D Standards

This platform's simplified data transmission architecture further reduces system latency by minimizing physical bus structures, hardware interfaces, and complex time-triggered Ethernet backbones. This architecture also improves accuracy and reliability by using centralized and unfiltered sensor data to reduce redundant operations and realize dynamic resolution according to context. The optimized signal processing software of this solution and advanced algorithms, along with neural networks optimized for machine learning computation, are seamlessly integrated and executed on an automotive-grade platform.



The DRS360 platform is designed as a product meeting safety, cost, power, thermal, and emissions requirements for use in systems complying with ISO 26262 ASIL D standards.

DRS360 uses Xilinx Zynq UltraScale+ MPSoC devices providing FPGA flexibility and superior signal processing efficiency in the first generation product, and adopts SoC and safety controllers based on X86 or ARM-based architecture. Accordingly, a comprehensive solution supporting full autonomous driving within a 100W power range has been realized, according to Director Amin Kashi.