I recently chaired a UJA Tech Talk on "The Future Of Autonomous Cars" with former General Motors Vice-Chairman Steve Girsky. The auto executive enthusiastically shared his vision for the next 15-25 years of driving – a congestion-free world of automated wheeled capsules zipping commuters to and from work. Girsky stated that connected cars with safety assist (autonomy-lite) features are moving much faster toward mass adoption than fully autonomous vehicles (sans steering wheels and pedals). In his opinion, the largest roadblocks toward a consumer-ready robocar are the current technical inefficiencies of prototypes on the road today, which burn huge amounts of energy supporting enhanced computing and arrays of sensors. This makes the sticker price closer to a 1972 Ferrari than a 2018 Prius.
As close to a quarter million people descended on a city of six hundred thousand, CES 2018 became the perfect metaphor for the current state of modern society. Walking the floor last week at the Las Vegas Convention Center (LVCC), the hum of the crowd buzzed celebrating the long awaited arrival of the age of social robots, autonomous vehicles, and artificial intelligence.
Deep neural networks (DNNs) have enabled great progress in a variety of application areas, including image processing, text analysis, and speech recognition. DNNs are also being incorporated as an important component in many cyber-physical systems. However, recent research has shown that DNNs are vulnerable to adversarial examples: Adding carefully crafted adversarial perturbations to the inputs can mislead the target DNN into mislabeling them during run time. There have been several techniques proposed to generate adversarial examples and to defend against them. In this blog post we will briefly introduce state-of-the-art algorithms to generate digital adversarial examples, and discuss our algorithm to generate physical adversarial examples on real objects under varying environmental conditions.
Uber and Volvo announced an agreement where Uber will buy, in time, up to 24,000 specially built Volvo XC90s which will run Uber's self-driving software and, presumably, offer rides to Uber customers. While the rides are some time away, people have made note of this for several reasons. I'm not clear who originally said it -- I first heard it from Marc Andreesen -- but "the truest form of a partnership is called a purchase order." In spite of the scores of announced partnerships and joint ventures announced to get PR in the robocar space, this is a big deal, but it's a sign of the sort of deal car makers have been afraid of. Volvo will be primarily a contract manufacturer here, and Uber will own the special sauce that makes the vehicle work, and it will own the customer.
Governor Andrew Cuomo of the State of New York declared last month that New York City will join 13 other states in testing self-driving cars: "Autonomous vehicles have the potential to save time and save lives, and we are proud to be working with GM and Cruise on the future of this exciting new technology." For General Motors, this represents a major milestone in the development of its Cruise software, since the the knowledge gained on Manhattan's busy streets will be invaluable in accelerating its deep learning technology. In the spirit of one-upmanship, Waymo went one step further by declaring this week that it will be the first car company in the world to ferry passengers completely autonomously (without human engineers safeguarding the wheel).
But under the plain meaning of this provision (and a related definition of "interstate commerce"), a developer could operate a fleet of vehicles equipped with its own automated driving system within a state without certifying that those vehicles comply with the FMVSS. This is the background law against which Congress might legislate--and against which its bills should be evaluated. Both bills would dramatically expand the number of exemptions that NHTSA could grant to each manufacturer, eventually reaching 100,000 per year in the House version. Some critics of the bills have suggested that this would give free rein to manufactures to deploy tens of thousands of automated vehicles without any prior approval. But considering this provision in context provides two key insights. First, automated driving developers may already be able to lawfully deploy tens of thousands of their vehicles without any prior approval--by designing them to comply with the FMVSS, by claiming testing or evaluation, or by deploying an in-state service. Second, the exemption process gives NHTSA far more power than it otherwise has: The applicant must convince the agency to affirmatively permit it to market its system.
Many websites paint a very positive picture of the robocar future. And it is positive, but far from perfect. One problem I worry about in the short term is the way robocars are going to make traffic worse before they get a chance to make it better. The goal of all robocars is to make car travel more pleasant and convenient, and eventually cheaper. You can't make something better and cheaper without increasing demand for it, and that means more traffic.
In recent years, self-driving cars have become a priority for automotive companies. BMW, Bosch, Google, Baidu, Toyota, GE, Tesla, Ford, Uber and Volvo are investing in autonomous driving research. Also, many new companies have appeared in the autonomous cars industry: Drive.ai, Cruise, nuTonomy, Waymo to name a few (read this post for a list of 260 companies involved in the self-driving industry). The rapid development of this field has prompted a large demand for autonomous cars engineers.