Some might assert that autonomous personal vehicles are being developed to improve safety, reduce fuel consumption, decrease urban infrastructure strains, and so on.  But let’s be honest: One of the key economic “drives” for this technology, no pun intended, is related to the prospect that people will have new time windows in their days in which to consume visual media.  However, due to some fundamental aspects of human physiology, this lucrative ambition may prove to be more difficult to implement than imagined.

In an age when so many vehicle sub-systems and components can be verified and signed off virtually – via off-line computer modeling, virtual test driving in Driver-in-the-Loop (DIL) simulators, and so on – it’s ironic that the one component that arguably has the biggest impact on overall vehicle performance continues to remain just out of reach for computational analysists: The tire.

Broadly speaking, today’s vehicles have significantly shorter production runs than the enduring products of yore. To wit: Volkswagen’s Beetle was manufactured for approximately 33 years.  Some might say 65 years, but that’s another story…

Are there any recent examples of such long-lived model runs?  Well, in 2014 the first-generation Volvo XC90 reached the end of a 12-year production run – which is certainly impressive. But any car that survives a decade would be an exception to the rule in the auto industry these days.  Let’s face it:  Modern carmakers have the arduous task of designing, developing, and deploying new products and major model updates at a tremendous pace.

These are still the early days for the human-machine interfaces (HMI) that will be crucial to the success of autonomous vehicles. And it’s unclear whether cross-industry standards will emerge regarding the application of autonomous technologies – not just in terms of functionality, but in the way  that conceptual HMIs convey functionality to drivers / occupants.

Recent accident data leaves little doubt that safety will be one of the justifications for developing autonomous vehicle technologies in the coming years. In 2015, 2,348 more people – for a total of 35,092 – died in US traffic crashes, a 7.2% increase from the previous year that ends a five-decade trend of declining fatalities. Simultaneously, the White House and US Department of Transportation issued a call to action to scientists and public health experts to do more to prevent road traffic deaths.

With some studies estimating that autonomous vehicle technologies could reduce the number of accidents by as much as 90%, this rapidly emerging field is sure to remain a leading destination for research dollars.

Modern vehicles are equipped with a startling amount of on-board computer processing technology.  Perhaps this is because we, as consumers, have come to expect cars to be something more than utilitarian mobility devices.  Or perhaps vehicle manufacturers would rather monetize silicon than steel.  Either way, it seems these systems are now a part of what defines an automobile.

Some on-board systems are meant to ease the task of driving a car – Electronic Stability Control (ESC) and any number of Advanced Driver Assistance Systems (ADAS) are examples – while other on-board systems are aimed at improving efficiency and performance, reducing fuel consumption, or, in the case of “Infotainment” systems, simply adding pleasure to the overall driving experience.

Driver-in-the-Loop (DIL) simulators are becoming a more important ADAS and Autonomous vehicle / system development tool. But how can this be?  After all, the intent of these emerging in-car technologies is to “reduce the burden” of a human driver’s vehicle control task, so first-pass logic might conclude that involving real drivers in a vehicle simulation loop is becoming superfluous. In fact, it is the opposite…

Market-readiness for any vehicle with driver assist / handover technology requires a development process that encourages early and often contact between real drivers and imagined systems.  So we are, in effect, witnessing a re-introduction of real drivers into the model-based development process that has come to dominate vehicle developments during the last few decades.

As evidenced by a flyer put out this last weekend by Costco, retail treasure hunting has never been better for automotive enthusiasts.  More specifically, buying a driving simulator has never been easier.  Appearing between advertisements for a garden shed and a box of cookies, the flyer shows a “full motion driving simulator.” Now to be fair, Costco is famous for spicing up its consumer product offerings with specialty shopping cart items.  But a driving simulator? 

If you are an engineer who uses driving simulators to develop Advanced Driver Assistance Systems (ADAS), then the terminology “ground truth” means something specific to you.  Ground truth representations define how your sensors and on-board systems interact with the virtual world, with calculated surfaces and objects.  But if you are a technical manager, “ground truth” can have a double meaning.

At this junction in history, Advanced Driver Assistance Systems (ADAS) and other on-board electronic systems are not only a reality; they are a dominating presence within vehicle development programs. Sophisticated sensor-plus-intelligence features that have been on the concept board for decades have already been successfully introduced via high-end vehicles, and are now commonplace in city cars – e.g. Automatic Emergency Braking (AEB). ADAS-type sensors and information processing technologies are also on the forward edge of autonomous vehicle control – literally and figuratively.