Driving is one of the more complex activities performed by human beings, involving judgment calls such as adapting to changing weather conditions.

Despite Decades of Work, Autonomous Vehicles Not Ready to Safely Hit the Nation’s Roads

In June 2016, Business Insider boldly predicted that “10 million self-driving cars will be on the road by 2020.” General Motors, Waymo, Toyota, and Honda all seemed certain that they would be manufacturing self-driving cars that year, and Elon Musk announced that Tesla would be making them by 2018 (which was later revised to 2020). However, 2020 has come and gone, and will likely be forever known for the COVID-19 pandemic, not for autonomous vehicles. What is the current status of self-driving cars?

What’s the Holdup? It’s Complicated

Despite efforts made by automakers and technology experts, self-driving cars are currently on the road only in special trial programs. Although cars are available with technology that will automatically apply the brakes in anticipation of a collision or keep you safely in your lane, companies are still struggling to make fully autonomous cars widely available.

Engineers have been working on prototypes of self-driving cars since the mid-1980s, basing their efforts on a simple approach: equip a vehicle with cameras that can detect nearby objects, enable the car to react should it be about to veer into one of them, teach these in-car computers the rules of the road, and allow them to navigate to their own destinations.

However, this seemingly simple project has proved to be extremely complicated, since driving is one of the more complex activities performed by human beings. Merely following the rules of the road is not adequate to enable an autonomous vehicle to drive as well as a human can, because it is hard to program a computer to do things such as adapting to changing weather conditions and making numerous other judgment calls.

A self-driving car’s computers must create a picture of where other vehicles, bicycles, pedestrians, and obstacles are at all times, making it necessary for automakers to collect and draw on millions of miles of driving data to form expectations about how other objects on the roadway might behave. Since it can be difficult to gather enough training data on the road, autonomous cars also train from simulation data, which requires them to rely on artificial intelligence (AI).

According to a February 2020 Vox report, “the ideal way to train a self-driving car would be to show it billions of hours of footage of real driving and use that to tech the computer good driving behavior.” However, some driving events occur very infrequently, such as witnessing a motor vehicle accident or dealing with debris on the roadway. This makes it necessary to “train” the vehicle by driving more miles, simulating specific occurrences, or engineering certain driving situations — which tends to make the process expensive and time-consuming.

However, despite the hurdles, automakers are continuing to invest money in autonomous vehicles, since when they finally hit the roads in great numbers, they will radically change driving in the U.S. and make their creators immense amounts of money.

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