Many of the greatest breakthroughs in science and technology are inextricably associated with a specific name. Think Einstein and the Theory of Relativity, Marie Curie and the discovery of radioactivity. Some landmarks, however, such as NASA’s Apollo program, are very much the product of a multitude of talented, but less celebrated, minds.
The autonomous car may not figure as high on the list of human achievements, but it is undoubtedly the most significant leap forward in its field since the arrival of Karl Benz’s first ‘true’ automobile in the 1880s. Equally certain is its place among the inventions that are the result of teamwork rather than individual brilliance. Indeed, one of the most striking characteristics of the development of the self-driving car is the sheer range of engineering disciplines required.
For evidence, look no further than the extended team behind Aptiv’s advanced safety solutions. In addition to delivering dramatic improvements in protection for today’s road users, systems such as autonomous emergency braking are very much the building blocks for tomorrow’s self-driving vehicles. And advanced safety represents one of the most multi-disciplinary areas of modern engineering, embracing mechanical, electrical and software engineers, roboticists, specialists in radar, control systems and object tracking, and many more besides.
But the challenge doesn’t lie simply in the diversity of skills needed. The depth of that expertise is critical too. When it comes to creating an autonomous vehicle, there’s only so much that can be learned in the classroom. In fact, we estimate that well over half the knowledge required comes from hands-on experience. In other words, it isn’t just our test vehicles that put the miles in, so do our engineers.
The final hurdle is to ensure that this apparently disparate team is working in harmony. As we’ve explained in a previous post (The Music of Math), a common language is provided by mathematics. Which is why highly talented algorithm engineers are another integral part of the Aptiv line-up. A rather less tangible bond is provided by a commitment to shared objectives, and the obvious satisfaction derived from saving lives that would otherwise be lost to road traffic accidents.
Of course, any form of mass market self-driving vehicle is still some distance away. What’s more, achieving it is likely to involve an even wider set of specialisms than those already at work. Perhaps surprisingly, that future development
includes experts in human behaviour and psychology.
Why’s that? Well, to date, there’s been a tendency to see vehicle automation in binary terms. Control is typically an all-or-nothing choice between human and vehicle. Going forward, however, a more nuanced approach should emerge. One that recognizes that automation and the human mind each have unique and distinct capabilities, and seeks to forge a partnership between the two. Rather than simply deciding whether automation needs to take over from the driver, we aim to identify and provide the precise support he or she needs in any given scenario. And that’s where human-machine collaboration will come into play.
For the moment, this concept of human-machine collaboration is largely at the theoretical stage. But it does fit rather neatly into the bigger picture; one in which the self-driving vehicle is very much being raised by a community.
So while there’s obvious appeal in inventions attributed exclusively to an outstanding hero or heroine, complete with ‘eureka moment,’ there is perhaps even more reason to celebrate in an approach built around cooperative values. The autonomous vehicle provides a timely reminder of just that... what can be achieved when we work together in pursuit of a higher purpose.