Somewhere between the Flintstones and the Jetsons

A puff of smoke trails from Fred Flintstone’s bare feet as he manually propels his stone and wooden car down a prehistoric road. It’s safe to say that we’ve collectively taken technology well beyond this crude (and, of course, fictional) point in automotive history.

In fact, onboard FPGAs and SoCs, and even AI, are steering the automotive industry further and further toward fully autonomous vehicles. It’s a long road, however, to the advanced automotive automation of the flying car that collapses into George Jetson’s briefcase.

This is the gray area in which today’s automotive hardware engineers find themselves. According to the National Highway Traffic Safety Administration (NHTSA), “self-driving vehicles ultimately will integrate onto U.S. roadways by progressing through six levels of driver assistance technology advancements in the coming years.”

It’s an optimistic statement, but it leaves us with as many questions as answers: How long will this journey to fully autonomous cars and trucks take? And what path must we take to get there? The truth is complex, but the short, encouraging answer is that we’re already en route.

Like many other organizations, the NHTSA breaks vehicle automation into incremental levels of technological sophistication. Level zero indicates no automated systems whatsoever, meaning a driver is completely in control of the vehicle. On the other end of the scale, level five denotes complete automation.

Today, most consumer passenger vehicles include various advanced driver-assistance systems (ADAS), like adaptive cruise control, lane departure warnings or even self-park functionality. This puts most vehicles generally in levels one and two, with luxury features bleeding into level three.

Needless to say, we’ve got some serious ground to cover before a driver is reading a novel on their commute into the office.

How do we go from level two to level five?

A significant step in reaching the fully autonomous future of level five: Realize that we have to go through steps three and four to get there. We simply cannot expect to achieve the kind of seismic jump in automotive technology that would bring us immediately from Fred’s foot-powered car to George’s flying, collapsible one.

Instead, our road to truly independent autonomous systems will be incremental — which is why it is critical that we begin designing around technology with the adaptability to withstand a long, gradual period of development.

Fortunately, unlike the Jetsons’ car-in-a-briefcase, the technology that will take us to level five already exists. Uniquely positioned for extensive adaptability and scalability, Xilinx devices provide flexible, standards-based solutions that combine software programmability, high-performance image processing tightly coupled with analytics, and any-to-any connectivity with the security and safety needed for next-generation automotive systems.

AI capabilities require high processing power combined with low latency, and Xilinx adaptive solutions offer these characteristics with as little as 3ms of latency. Additionally, they allow for the incorporation of advanced neural networks to facilitate sophisticated machine-learning capabilities. That’s why high-compute–powered, low-latency, power-efficient and eminently flexible Xilinx FPGAs and SoCs are already in over 100 vehicle models across nearly 30 manufacturers.

Along with the impressive versatility of Xilinx automotive solutions, however, comes increased complexity in implementation. The good news? You’ve already found the only partner you’ll need to seamlessly integrate Xilinx products into your next automotive design. With Avnet’s extensive product development ecosystem, we’ve got everything you need to successfully leverage Xilinx solutions — and drive your product to market in record time.

Discover how Avnet and Xilinx can help ensure your next automotive design is ready to stand the test of time—and propel our vehicles from level two to level five.

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