We've been covering Tesla Autopilot in-depth quite a bit lately. That said, it's worth exploring a key underlying rationale for developing autonomous vehicles in the first place: safety. Business Insider* just published a comprehensive series on the future of self-driving cars. In short, they forecast: "Within a few years, autonomous vehicles will be everywhere. You and I won't be driving, unless we want to for sport. Kids won't need to get their driver's licenses. Cities won't have to provide public parking. Street signs and gas stations may disappear." What does all this mean? Well... let's highlight some of their key findings — especially as it relates to improved safety.
Above: New Teslas being shipped are delivered with a Level 5 capable sensor suite (Image: Tesla)
It's reported that, "by 2030 driverless cars could make up as much as 60% of US auto sales, according to Goldman Sachs... While companies all have their own reasons for investing in this technology, they all agree that one of the biggest benefits of autonomous cars will be improved safety." How can a self-driving car be safer than a human? It all boils down to the tech. "Driverless cars are designed to have almost a superhuman-like ability to recognize the world around them. This is because they use loads of sensors to gather tons of data about their environment so that they can seamlessly operate in a constantly changing environment."
Above: Here's what a city with driverless cars might look like (Source: Business Insider*)
Furthermore, "All of this collected data is then fed into the car’s computer system, or 'brain,' so to speak, and is processed so that the car can make decisions. One of the leading companies building the brains for these cars is the chipmaker Nvidia. In fact, Tesla’s Autopilot system uses Nvidia’s Drive PX2, which is the company’s newest computer system for autonomous cars. Drive PX2 is a powerful computer platform about the size of a license plate that uses a variety of Nvidia's chips and software to take all of the data coming in from the sensors on an autonomous car to build a three-dimensional model of the car's environment."
Above: Tesla uses Nvidia’s Drive PX2 (Image: Business Insider*)
Danny Shapiro, senior director of Nvidia’s automotive business unit says, "In the brain of the car, it almost looks like a video game. We are essentially recreating the world in a virtual 3D space." To do this, Nvidia uses something called machine learning. "Machine learning is a way of teaching algorithms by example or experience and companies are using it for all kinds of things these days. For example, Netflix and Amazon both use machine learning to make recommendations based on what you have watched or purchased in the past."
Above: A look at the levels of vehicle automation that will come as self-driving cars evolve, eventually, to Level 5 (Image: Business Insider*)
Shapiro explains, “Initially, the computer doesn’t know anything. We have to teach it. And so what we want to do is if we want to teach it to recognize pedestrians, we would feed it pictures of pedestrians. But what we can do is feed it millions pictures of pedestrians because pedestrians look different. The more data we feed it the more vocabulary it has and the more it can recognize what a pedestrian is. And we do the same thing with bicyclists, cars, trucks, and we do it at all times of day and different weather conditions. So again, essentially it has this infinite capability to build up a memory and understanding of what all of these different types of things [it] could encounter would look like.”
Above: Tesla owner Jay Leno gives his theory on why Tesla Autopilot, and autonomous vehicles in general, are needed (Youtube: CNBC)
So in order to gain superhuman driving skills, "Once a computer model is created, then it’s loaded into the car’s brain and hooked up to the rest of the car’s sensors to create real-world model of the car’s environment. The car uses this model to make decisions about how it should respond in different situations. And because the car has sensors all around it, it has access to a lot more data than a human driver to help it make those decisions." Shapiro explains, "because it has a full 360 degrees view around the car, it can be tracking multiple objects, with much greater things happening, with much greater accuracy than any human."
*Source: Business Insider