It’s truly an exciting time for in-vehicle computing. What started with parking assist and rearview cameras has evolved into lane departure warning and dynamic cruise control, requiring more intelligence and compute in the vehicle. Each step toward the vision of connected and fully automated driving brings with it more sensors, more data, and more demand on compute. Through it all, security and safety must remain at the foundation of connected and automated vehicle design.
I’m excited when I think about how in-vehicle computing serves as the automated vehicle’s second engine. To help ensure the safety of passengers and the people around the vehicle, the vehicle must sense and react to its environment in real time. It must also provide dynamic, end-to-end protection against cybersecurity vulnerabilities. This requires a scalable in-vehicle computing platform capable of extreme multimodal sensor fusion, uncompromising reliability, and flexible hardware acceleration and security. Let’s take a look under the hood of in-vehicle computing, so to speak, and see how it is all coming together thanks to the most powerful growth engine in human history: collaboration.
Tremendous Compute Meets Scalable Architecture
Did you know that a self-driving car generates about 1GB of data every second? This means automated vehicles require substantial in-vehicle computing and a complex set of technologies for data collection, sensor fusion, edge analytics, and machine learning to sense, interpret, and classify vehicle data. I’m delighted to be part of a team that is delivering incredibly high compute performance per watt with a broad range of power-efficient silicon.
Our transportation roadmap provides scalable computing to strategically place computing resources with the best combination of power efficiency, performance, and cost. Our broad portfolio of power-efficient silicon ranges from field-programmable gate arrays (FPGAs) to Intel E5 processors. Intel believes an open, standards-based platform drives software reuse, flexibility, and a broader array of products and solutions that can scale across original equipment manufacturer (OEM) fleets and brands.
Intel is focusing on heterogeneous architecture designs that are well-suited to level 3 (“eyes off the road”), level 4 (“mind off the road”), and level 5 (“driver off the steering wheel”) automated vehicles. Rather than pursuing a single architecture to handle everything, Intel is designing for real-time decisions to be made independent of where the workload is running.
Collaboration is Key for Vehicle Safety
Thanks to round-the-clock and across-the-globe collaboration within the Intel IoT ecosystem, our portfolio of automotive-grade, functionally safe products is growing by the year. With our continued focus on security and safety, Intel provides layered protection from door lock to data center with features rooted in the hardware. These include secure boot and Intel Trusted Execution Engine (Intel TXE) to help resist attacks and infection from malware. We also provide secure storage for key exchange and encryption to ensure only authorized over-the-air (OTA) software updates are downloaded. Finally, Intel Virtualization Technology for Directed I/O (Intel VT-d) ensures the most safety-critical functions have priority access to the processor.
Everyone knows the automotive landscape is changing. Less clear is how to make the most of that change. As part of Intel’s portfolio of automotive assets, Wind River is helping build the highway to our transportation future. Powered by deep software expertise in mission-critical industries, Wind River is actively working with Intel on automotive technologies that speed the development for tomorrow’s connected and automated cars.
In addition to working with Wind River, Intel is also collaborating with software companies like Green Hills Software, QNX, and other key partners to provide solutions for the software-defined cockpit and automated driving.
Furthermore, to make self-driving vehicles and future mobility concepts a reality, BMW Group, Intel, and Mobileye have joined forces. By combining our expertise in automotive, technology, computer vision, and machine learning, we are creating an open platform for highly and fully automated driving. Together, we will bring solutions into series production by 2021. The BMW iNEXT model will be the foundation for BMG Group’s automated driving strategy and set the basis for fleets of fully automated vehicles.
In-Vehicle Compute Across Automakers
Another key requirement for self-driving cars is the ability to see and accurately interpret surroundings. With Intel’s acquisition of Itseez, we’re able to deliver expertise in computer vision algorithms and implementations for embedded and specialized hardware. With Intel’s acquisition of Yogitech, we’re building our expertise in semiconductor functional safety, methodologies, and related standards.
I’m tremendously excited to be able to work with some of the world’s leading automakers, as they turn to Intel technology to power in-vehicle infotainment, imaging, and navigation systems. Among them are BMW, Hyundai, Infiniti, Kia, Ford, Jaguar Land Rover, and Toyota.
From successful collaborations to innovative new technology, there’s much to be excited about for automated vehicles. We look forward to continuing to drive down that road together.
To learn more about the road ahead for automated vehicles, visit www.intel.com/automotive. For more on Intel IoT developments, subscribe to our RSS feed for email notifications of blog updates, or visit intel.com/IoT, LinkedIn, Facebook, and Twitter.