Mentor Automotive's New DRS360 Platform Enables Level 5 Autonomous Driving

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【Summary】The DRS360 fuses raw unfiltered data from radar, LIDAR, vision and other sensors from an autonomous vehicle in real-time. The platform is designed to deliver the low-latency, high-accuracy sensing required for Level 5 autonomous vehicles capable of navigating with no driver input.

Original Eric Walz    May 24, 2017 4:35 PM PT
Mentor Automotive's New DRS360 Platform Enables Level 5 Autonomous Driving

Mentor Automotive recently introduced the DRS360 platform. The company is a division of Mentor, a Siemens business, and was founded in 1981 in Wilsonville, Oregon. The company's DRS360 is a first for autonomous driving platforms, in that the platform directly transmits unfiltered information from all of a vehicle's sensors to a central processing unit, where raw sensor data is fused in real time at all levels.

The DRS360 fuses raw data from radar, LIDAR, computer vision, and other sensors from an autonomous vehicle in real-time. The platform is designed to deliver the low-latency, high-accuracy sensing required for Level 5 autonomous vehicles capable of navigating with no driver input.


The DRS360 platform delivers dramatic improvements in latency reduction, sensing accuracy, and the overall system efficiency required for SAE Level 5 autonomous vehicles.

Automotive-Grade Platform

The DRS360 platform is engineered for production to meet the safety, cost, power, thermal and emissions requirements for deployment in ISO 26262 Automotive Safety Integrity level (ASIL) D-compliant systems.

DRS360 leverages the flexibility and superior signal processing efficiency of field-programmable gate arrays (FPGAs), deploying a Xilinx Zynq UltraScale+ multiprocessor system-on-chip (MPSoC) device in the first generation, while accommodating SoCs and safety controllers based on either X86- or ARM-based architectures. The hardware supports fully automated driving within a 100 watt power envelope.

   Product Demo Video from Mentor Automotive

Reduced Cost for Automakers

The DRS360 platform has advanced neural networking algorithms for machine learning, and a host of integration services built on system support package utilizing Mentor's IP. Since the platform uses a "raw data" approach, it eliminates processing at sensor nodes from all of the nodes on an existing vehicle's CAN-bus network. This results in reduced cost and complexity for automotive OEM's, suppliers, and autonomous driving developers working on systems that can "see" and react at the highest possible resolution.

"Mentor's technology for automotive electrical and electronics design is world-leading." Mr. Yan Gang, Deputy General Manager, JAC Motors

"Mentor Automotive's approach to centralized, real-time raw sensor data fusion represents a new innovation for automated driving system developers," said Arun Iyengar, Xilinx Vice President – Global Markets Group.  "With its extreme flexibility, efficient power operation and highly optimized signal processing capabilities, the Xilinx Automotive Zynq UltraScale+ MPSoC family targets these types of applications and plays a key role in enabling the capturing, pre-processing and fusion of data from a wide variety of sensors. Xilinx is pleased to enable this innovative and compelling automotive solution from Mentor Automotive."

Centralized Data Fusion

Most recently, the development of more advanced driver assist system (ADAS) features has led to a proliferation of new sensors installed on a vehicle. Traditionally, these ADAS systems have used a distributed computer architecture, that pushes data processing to each node in the network. These include the camera, RADAR, LiDAR and other sensors which wind up independently filtering and processing large streams of data, which are then sent to different applications or fusion modules.

The traditional distributed approach has limitations, including unacceptable system latency in the transfer of safety critical information, which is critical for self-driving vehicles, and the loss of potentially useful data at the edge nodes. These systems increase in cost and consume more power as driver-assist systems become more complicated.


DRS360 takes a different approach: centralized raw data fusion. Rather than try to scale lower levels of ADAS upwards, DRS360 is a system optimized for Level 5 autonomous driving, and engineered to easily scale down to Levels 4, 3 and even 2 if required.

Centralized raw data fusion eliminates the inherent limitation of today's distributed ADAS/AD architectures. DRS360 connects raw sensor data to a centralized automated driving module over high-speed communication (bus) lines, and then fuses this data in real time. This high-speed, low latency communication framework developed by Mentor makes all sensor data — raw and processed — available across the system at all times. With access to a high-resolution model of the vehicle's surrounding environment, perception algorithms can make ADAS decisions faster and with more efficient use of processing power.


About Mentor Automotive

The company is currently working with 17 of the world's top 20 carmakers,  is a leading supplier of automotive networking solutions, and the number one supplier of automotive Linux. The company provides hardware and design tools in the areas of automotive connectivity, electrification, autonomous drive and vehicle architecture.

"For more than 25 years, Mentor has worked with the world's top automotive OEMs and suppliers. "With the introduction of the compelling DRS360 solution, Mentor extends this leadership and investment to the automated driving technology sector. We look forward to playing a major role in helping the industry realize the massive potential and benefits of the autonomous vehicles era."

"Mentor Automotive's DRS360 platform represents a highly differentiated and radically innovative approach to automated driving from a company with decades of experience in helping engineers successfully create some of the most sophisticated systems ever developed," said Dr. Andreas Erich Geiger, Chairman of Mentor's recently formed Automotive Strategy Board.

"In the final analysis, self-driving cars are essentially highly complex systems, and this plays to Mentor's well-established proficiency in architecting, designing and integrating highly successful systems for many of world's largest and most innovative companies."

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