Traffic congestion costs the U.S. economy 121 billion a year, mostly due to lost productivity, and produces about 25 billion kilograms of carbon dioxide emissions, Carnegie Mellon University professor of robotics Stephen Smith told the audience at a White House Frontiers Conference last week. In urban areas, drivers spend 40 percent of their time idling in traffic, he added. The next step is to have traffic signals talk to cars. Pittsburgh is the test bed for Uber's self-driving cars, and Smith's work on AI-enhanced traffic signals that talk with self-driving cars is paving the way for the ultimately fluid and efficient autonomous intersections.
Most autonomous vehicle control software is deliberately designed for well-constrained driving that's nice, calm, and under control. At Georgia Tech, researchers are developing control algorithms that allow small-scale autonomous cars to power around dirt tracks at ludicrous speeds. Such aggressive driving is necessary when the speed of the vehicle exceeds its friction limit--a potentially dangerous condition for inexperienced robot drivers and human drivers alike. Just as expert human drivers can take advantage of how their vehicles handle at the very limits of control in order to drive fast yet safely in extremely challenging conditions, self-driving cars should be able to use the same techniques to avoid accidents in bad weather.
The company is working out the bugs in its self-driving technology.Video provided by Newsy Newslook Uber's new self-driving car has begun testing on the streets of Pittsburgh. The ride-hailing behemoth announced in a blog post Thursday that it has begun testing a self-driving car in Pittsburgh, home of the company's nascent Advanced Technologies Center. The car, a Ford Fusion Hybrid with a roof-full of radar, lasers and cameras, will be collecting road-mapping data as well as testing its real-world traffic reactions. As with all self-driving cars that are approved for testing on public roads, Uber's vehicle will have a safety driver who can take over the controls should the situation demand it.
Uber's new self-driving car has begun testing on the streets of Pittsburgh. The ride-hailing behemoth announced in a blog post Thursday that it has begun testing a self-driving car in Pittsburgh, home of the company's nascent Advanced Technologies Center. The car, a Ford Fusion Hybrid with a roof-full of radar, lasers and cameras, will be collecting road-mapping data as well as testing its real-world traffic reactions. Given the pace of autonomous car research, many in the space believe driverless cars will be ready for consumers within the next three to four years.
That's the backlog of pre-orders that Tesla Motors tallied up in the days after announcing its latest car, the Tesla Model 3. Aside from a handful of parts that need routine replacement--think tires and wiper blades--the bulk of the vehicle's components and functions were designed to be upgraded, not by mechanics wielding wrenches, but by software engineers working in Tesla's Silicon Valley research and development labs. A fix, the message informed him, was automatically downloaded to Robert's car (and every other Tesla) overnight while it charged in his garage. And this is happening not just in transportation but virtually every industry, as I write in my latest book "The Digital Revolution: How Connected Digital Innovations Are Transforming Your Industry, Company and Career."
The company has been in stealth mode for the past year, working on applying deep learning techniques to self-driving cars. Its core team is made up of experts with a wealth of experience developing deep learning systems in all kinds of different domains, including natural language processing, computer vision, and (most recently) autonomous driving. "Drive.ai is a deep learning company," Reiley says. "We're solving the problem of a self driving car by using deep learning for the full autonomous integrated driving stack--from perception, to motion planning, to controls--as opposed to just bits and pieces like other companies have been using for autonomy.
Last year, he and some friends dropped out of the University of Waterloo and started Varden Labs, an automated vehicle startup based out of a rented house just north of San Jose. It doesn't go very fast and, therefore, doesn't have to predict how it will drive very far down the road, unlike Google cars cruising at highway speeds. But these days, as some of the key pieces of technology have dropped in price and investor interest has soared, even a few college dropouts can get one on the road. Varden said they had to steer clear of Facebook's founding mantra, "Move fast and break things".