Car buffs take note — just like the movies predicted, the highways and byways of the future will likely include autonomous self-driving cars. Don’t believe me? Just look at the recent headlines… Lexus unveils a self-parking car… Google's self-driving car is licensed to drive in Nevada, etc. Love ’em or hate ’em, autonomous or robotic cars coming. Along with the connected car, it’s clear that automakers see autonomous cars as the next big opportunity as they race to create the safest and most efficient systems possible.
One Stanford professor believes we should take the concept of the autonomous car one step further, by enabling the car to act more as a “driving coach” or “partner” to help us navigate the roads. Stanford associate professor Chris Gerdes, who also acts as the director for the Center for Automotive Research at Stanford (CARS) and the Dynamic Design Lab, is one of the drivers (OK, enough puns) behind the university’s autonomous car research. Oh, and did we mention he develops robotic racecars in his spare time?
To better understand the act of driving a car, Gerdes and his team studied the brain waves of human drivers. The study confirmed that the brain does a tremendous job of handling the workload associated with driving, which prompted Gerdes conclusion that the optimal autonomous car tech will not necessarily replace humans, but should instead act as our coach. He believes that the optimal car will combine technology with human intuition and reflexes.
This vision might come as a bit of a surprise to the typical commuter who dreams about a commute where they can lay back and post Facebook updates, catch up with friends, and watch the latest episode of Game of Thrones during what would have been an awful and unhealthy commute.
During his career, Gerdes has contributed to some awe-inspiring work with self-driving cars, which only adds to his case for a driving experience with the right balance between human skills and robot processing power. In his TED presentation for example, he pointed to research comparing the way a computer would determine the optimal line (most efficient path) for driving a racetrack lap versus the way a human driver would approach the problem. Guess which line was more efficient and theoretically faster? Neither. The line calculated by the computer was almost identical to the line driven by a professional racecar driver, who’s brain’s “workload” was monitored by telematics. The conclusion? Humans can at least equal computers when it comes to figuring out the most efficient driving line – without the benefit of an algorithm – and they do it instinctively, over and over again.
In another example, Gerdes showed the real-time electrical brain activity (“mental workload”) of a racecar driver during a lap at the Laguna Seca racecourse. Most of us would assume that extreme driving situations, such as the act of correcting severe over steer, would take a lot more mental energy than the amount required to handle a normal driving situation. However, Gerdes discovered that in the instances he studied, extreme driving required no more mental workload than normal driving. Invoking the term, “trickle-down technology,” Gerdes hopes to take “this reflexive action that we’ve seen in the very best race car drivers” and introduce it to prototype autonomous cars.
So would you drive or ride along in an autonomous car? I’m guessing a lot of suffering commuters would prefer to be chauffeured by an autonomous car, while driving purists would more likely prefer to do the driving themselves. However, the purists should be open to a little coaching – as long as, in Gerdes’ words, the cars are “a little less algorithmic and more intuitive/instinctive.”