Mentor targets autonomous vehicles with real-time data capture
- 저자:Ella Cai
- 에 출시:2017-04-07
Mentor, the EDA design tool firm recently acquired by Siemens, has introduced a design platform for automated driving systems.
With autonomous vehicles dependent on data from various sensor systems, the platform will capture data in real time from radar, LIDAR, vision and other sensors.
The DRS360 platform has sensing accuracy and overall system efficiency required for SAE Level 5 autonomous vehicles.
The system directly transmits unfiltered information from all system sensors to a central processing unit, where raw sensor data is fused in real time at all levels.
It accepts raw data from the sensors and so does not require pre-processing microcontrollers in system sensor nodes.
The advantage of this is low latency and improved real-time performance.
The system employs data transport techniques to further lowers system latency by minimising physical bus structures, hardware interfaces and complex, time-triggered Ethernet backbones.
This architecture also enables situation-adaptive redundancy and dynamic resolution by using centralised, unfiltered sensor data to ensure enhanced accuracy and reliability. The solution’s optimised signal processing software, advanced algorithms, and compute-optimised neural networks for machine learning run on a seamlessly integrated, automotive-grade platform.
Wally Rhines, CEO and chairman of Mentor, writes:
“Mentor has extended its investment to the automated driving technology sector. We look forward to playing a major role in helping the industry realise the massive potential and benefits of the autonomous vehicles era.”
Supplied by Mentor’s automotive division, the DRS360 platform has been designed to meet the safety, cost, power, thermal and emissions requirements for deployment in ISO 26262 ASIL D-compliant systems.
Data processing at the heart of the systems is provided by a Xilinx Zynq UltraScale+ MPSoC device in the first generation, while accommodating SoCs and safety controllers based on either X86- or ARM-based architectures.
With autonomous vehicles dependent on data from various sensor systems, the platform will capture data in real time from radar, LIDAR, vision and other sensors.
The DRS360 platform has sensing accuracy and overall system efficiency required for SAE Level 5 autonomous vehicles.
The system directly transmits unfiltered information from all system sensors to a central processing unit, where raw sensor data is fused in real time at all levels.
It accepts raw data from the sensors and so does not require pre-processing microcontrollers in system sensor nodes.
The advantage of this is low latency and improved real-time performance.
The system employs data transport techniques to further lowers system latency by minimising physical bus structures, hardware interfaces and complex, time-triggered Ethernet backbones.
This architecture also enables situation-adaptive redundancy and dynamic resolution by using centralised, unfiltered sensor data to ensure enhanced accuracy and reliability. The solution’s optimised signal processing software, advanced algorithms, and compute-optimised neural networks for machine learning run on a seamlessly integrated, automotive-grade platform.
Wally Rhines, CEO and chairman of Mentor, writes:
“Mentor has extended its investment to the automated driving technology sector. We look forward to playing a major role in helping the industry realise the massive potential and benefits of the autonomous vehicles era.”
Supplied by Mentor’s automotive division, the DRS360 platform has been designed to meet the safety, cost, power, thermal and emissions requirements for deployment in ISO 26262 ASIL D-compliant systems.
Data processing at the heart of the systems is provided by a Xilinx Zynq UltraScale+ MPSoC device in the first generation, while accommodating SoCs and safety controllers based on either X86- or ARM-based architectures.
