Ai Paves the Way for Transportation Industry Revolution
Ten years ago, if you asked someone what they thought the year 2018 would look like, they would probably envision sleek phones, futuristic housing, and streets filled with completely autonomous vehicles. Due to new advancements in Ai technology, the future of transportation is finally here. There are many startups paving the way for the integration of automated vehicles into the transportation industry. A few of the hottest names in the self-driving car industry are Cruise, Drive.ai, and TuSimple. These rapidly growing startups are gaining investments for Ai research at an impressive rate, and some have become acquired by larger companies such as GMC.
San Francisco is a hotspot for the development of self-driving vehicles, which have recently been allowed to undergo testing on public roads in select communities. This is the safety-conscious approach taken by Drive.ai, which credits Frisco, Texas for allowing them to integrate their completely autonomous vehicles into the community. Drive.ai outlines three stages in their plan to integrate their vehicles into society. First, they are conducting tests in Frisco with the use of safety drivers, who are tasked with taking over the vehicle under circumstances where the AI computer would not perform properly. They claim that, over time, the machine learning technology will be able to recognize and correct its performance and intelligence. Next, the vehicles will operate with a “chaperone,” who rides along as a passenger in order to monitor the AI systems, but is not expected to take control of the vehicle. Lastly, the vehicles will only drive passengers while a monitor observes multiple vehicles from a computer screen. Cruise, on the other hand, has recently released plans to debut a self-driving car to the public as early as next January. One of the fastest growing startups in this field, Cruise was acquired by GMC back in 2016 to lead the autonomous vehicle revolution efforts. Since the acquisition, Cruise employee base has grown eightfold. They are currently working on a fleet of Chevrolet Bolts that include a series of cameras, lasers, and radars, all linked to an AI computer. Another hot startup that uses state-of-the-art AI technology in their vehicles is TuSimple. TuSimple specializes in autonomous trucks and flatbeds for transportation of commercial goods. They use Nvidia GPU’s and computers in order to develop autonomous trucks capable of transporting commercial goods across the country. Nvidia is leading the way in artificial intelligence machinery and software, and with offices in Beijing and San Diego, TuSimple is also leading in autonomous vehicle application.
Like many AI systems, the function that makes self-driving vehicles possible is the computers ability to learn and grow based on experience and observation. Self-driving cars are usually equipped with a number of radars, lasers, sensors, and signs that take in information about the vehicle’s surroundings as well as the route it will take to reach its destination. It also includes many safety features, such as signs on all sides of the vehicle, which relay information to not only passengers, but also pedestrians. Developing these systems requires repetition in order to teach the computer the millions of maneuvers it will have to make when driving on public streets. However, this is a relatively simple task for an AI computer capable of sifting through large amounts of data quickly.
The recent push towards autonomy has pressured companies such as Uber to innovate so that they are not left behind. Uber used to be at the forefront of autonomous vehicle research, however, the haste to release their model of self-driving cars had drastic consequences. A few years back, Uber released a small fleet of autonomous vehicles in Pittsburgh. It seemed as though Uber was ahead of the game in this field; however, after a number of accidents, a few of which being fatal, Uber has suspended their fleet and autonomous vehicle research program indefinitely.
The two major applications of autonomous vehicles are passenger and goods transportation. Once autonomous vehicles are completely integrated into society, we can expect traffic to drastically decrease, crash rates to decline, and environmental benefits such as cleaner emissions and decreased need for parking lots. Companies working on autonomous vehicles are receiving extreme support and investments for research and development. With AI paving the way for autonomous vehicle production, many hope the entire transportation industry will be revolutionized by as soon as 2030. Although, some of the brightest minds in Ai research have raised skepticism since most of this technology is pretty new and still not capable of performing all the human tasks needed for driving.
Written by Vic Sinopoli, Edited by Rachel Weissman & Alexander Fleiss
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