Autonomous Driving is classified according to the amount of human driver intervention. It ranges from Level 0 (no automation) up to Level 5 (full automation).
Enabling Level 5 Autonomous Driving in Automotive, Defense and other Industries requires collecting, storing and processing data at an unprecedented degree. This has been until now unattainable by Embedded Devices and Edge Computers.
Companies in the Automotive industry are spending billions of dollars in investments for developing Level 5 Autonomous Driving technologies. All these players are encountering a number of new challenges that span across many disciplines and technologies.
Embedded systems installed into vehicles must face six main challenges to enable Level Five Autonomous Driving:
- Storage capacity
Sensors, LIDARS and other technologies supporting autonomous driving generate unprecedented amounts of data. They require ultra-high computational performance that goes beyond the traditional embedded computer capabilities.
Some sophisticated sensors require a bandwidth of 40Gb/s to transfer data, not only in peak conditions, but for continuous operations. Moreover, Level 5 Autonomous Driving applications require constant, reliable and real-time operations while keeping latency as low as possible.
Level 5 Autonomous Driving applications largely exceed the storage capacity of typical embedded computing devices. Thinking about the 40Gb/s bandwidth mentioned above, it translates to almost 20TB in only an hour of operations.
High Performance Embedded Computing (HPEC) systems and data loggers installed on vehicles must provide reliable, continuous operations for long period of time. They must operate in very harsh environments: withstanding shocks, vibrations, dust and wide temperature ranges.
Embedded and electronic systems and Edge Computers installed into vehicles must comply with industry standards.
Automotive certifications, such as E-Mark and IEC 60068-2-6 / 60068-2-27 for shock and vibration are objective ways for characterizing the behavior of the system under stress in actual operating conditions.
Space is more than often at a premium in embedded applications. Systems designed to fit into embedded environments must come with compact size, to be easily installed into vehicles.
However, HPEC systems provide tremendous amount of computational power and they easily heat up. Dissipating such an intense heat would require a proper and powerful cooling system that can be easily installed in the vehicle.
High Performance Computing systems are typically bulkier than embedded systems due to heat dissipation issues: they are usually equipped with big fans that cannot be used in embedded applications where performance is sacrificed to adapt to space constraints.
However, High Performance Embedded Computing systems for Autonomous Driving must provide HPC performances into a vehicle.
Eurotech has a lot of expertise in designing liquid-cooled HPC (High Performance Computing) and HPEC systems. Liquid cooling is an ideal solution for HPEC systems in Autonomous Driving, as most of the cars are already equipped with liquid cooling systems.
Compared to air cooling, liquid cooling allows more computational density and a better energy efficiency: even though Eurotech’s HPEC systems can use up to 500W, the coolant would maintain a temperature of around 41-43°C.
The DynaCOR 40-34 and the DynaCOR 50-35 are unique examples of High Performance Embedded Computing systems that comply with all these requirements, winning the challenges of Level 5 Autonomous Driving: they provide flexible and configurable platforms that allow the creation of in-vehicle Data Centers to bring Artificial Intelligence to the Edge (Edge AI).