As on-board vehicle control systems continue to advance, the behind-the-scenes validation strategies required to develop them must advance as well. New innovations in connectivity and automation require that OEMs and Tier-1s devise new test methods to verify proposed systems for both function and safety.
Self-driving cars are the new black. Every OEM and major tech company is taking on the autonomous challenge, and the competition is fierce.
As an OEM or Tier 1 supplier, the landscape is rife with offerings, software tools that are aimed at assisting all areas of autonomous vehicle development and validation, many of them pioneering grabs at what is promising to be the Wild West of automotive engineering in the coming years. And yes, some of these tools are either direct or indirect products of the gaming industry.
If anyone asked the question, “Would you trust your autonomous vehicle validation to a game?” most of us would cringe a little. But such questions are actually not too far off the mark these days.
If one needs an illustration of the sensor complexity that is arising from ADAS-capable vehicles evolving into new autonomous and semi-autonomous modes of transport, look no further than the highly automated Delphi Drive concept vehicle. External awareness sensors such as radar, LiDAR, and cameras are just the tip of the iceberg for this vehicle. On board one can find touch sensors on the steering wheel, driver-facing cameras in the A-pillars, a fingerprint reader in console, and logic-activated haptic feedback motors in the seats.
With its myriad sensors, and feedback devices, and information processing strategies, and so on, this highly modified Audi SQ5 is in use now as a rolling test bed and demonstration platform for all manner of human-to-vehicle and vehicle-to-infrastructure (V2X) possibilities. Oddly, this test bed of today may be evidence that we are not far from a time when even “normal” production vehicles carry this level of sensing capability.
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.
In recent decades there has been a decided shift in the way new cars are introduced into the marketplace. Compression of time-to-market cycles has been unprecedented; auto manufacturers are designing, developing, testing, refining, approving, and deploying vehicles into the world faster than ever before. And this is occurring simultaneously with the uptake and integration of staggering engineering-level complexities in the form of Vehicle-to-Everything (V2X) systems as well as on-board technologies such as Advanced Driver Assistance Systems (ADAS).
An economist might call this scenario a "problem" in the classic economic sense, i.e., one of the means of production (the available time to design and test a new vehicle) is changing and so too is at least one of the ends of production (the definition of what defines a "good car"). So the question becomes: What can be done to help solve this "problem?"
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.
If driving the Trans-Canada Highway in Newfoundland is not quite adventurous enough for you (and if the ripping wind does not force you to park your vehicle on the roadside), it might be worth your time to head for the northern-most extremes that can be reached, up highway 430 out of Deer Lake. It will take every bit of 5 hours to reach L'Anse aux Meadows, the spot where (as far as we know) humans first closed the loop on global exploration, where European Viking culture bumped into American Native culture sometime around the year 1000 CE.