Because 90% of all driving accidents are caused by operator error, automating vehicles through onboard computers would reduce injuries, deaths and related costs by staggering amounts, according to a study released today by the non-profit Eno Center for Transportation.

Alcohol, drugs, inexperience, speeding, wet and icy roads can all contribute to an accident. If computers controlled vehicles, they could sense and anticipate road conditions and objects around them, helping to avoid accidents, the study showed. In fact, if just 10% of all vehicles in the U.S. were self-driving, the number accidents each year would be cut by 211,000; 1,100 lives would be saved; and economic costs would be cut by $22.7B, the study said.

If 90% of vehicles in the U.S. were self-driving, as many as 4.2 million accidents could be avoided, saving 21,700 lives and $450 billion in related costs.

According to the National Highway Traffic Safety Administration, 40% of fatal crashes are the result of alcohol or drug use, driver distraction and/or fatigue. Since computers don't drink or do drugs and they don't become distracted or tired, their use in vehicles would dramatically reduce fatalities, the study concluded.

Through vehicle-to-vehicle and vehicle-to-infrastructure communication, autonomous cars and trucks could reduce freeway and artery congestion by more than 75%, the study said. For one, traffic congestion would also be dramatically reduced through fewer accidents. The Federal Highway Administration estimates that up to 25% of traffic jams are caused by accidents.

Additionally, autonomous vehicles are expected to be able to detect other vehicles around them - even communicating with other cars and trucks about their routes. Therefore, self-driving vehicles could anticipate a lead vehicle's braking and acceleration decisions, allowing for smoother travel and leading to the avoidance of the traffic pileups that occur today.

By communicating with each other, self-driving vehicles could anticipate breaking and acceleration, reducing congestion on highways caused by g "shockwave propagation," or the domino effect.

Anticipating breaking and acceleration in other vehicles would also lead to fuel savings and less brake wear.

Car manufacturers and technology companies, such as Google, have announced plans to launch self-driving vehicle lines by 2020.

As of August, California and Nevada have enacted legislation to allow self-driving car licensing. Florida and Washington D.C. have begun autonomous vehicle testing, and similar legislation is pending in Hawaii, Massachusetts, Michigan, Minnesota, New Jersey, New York, South Carolina, Washington, and Wisconsin, according to the Eno Center study.

"Of course, many such benefits may not be realized until high [numbers of self-driving vehicles] are present. For example, if 10% of all vehicles on a given freeway segment are [autonomous], there will likely be an [autonomous vehicle] in every lane at regular spacing during congested times, which could smooth traffic for all travelers," the study's authors wrote.

Conversely, if just one out of 200 vehicles is autonomous, the impact would be "non-existent or greatly lessened."

There are still many issues to resolve with autonomous vehicles: How much of the functionality would be automated? Could automakers prevent hackers from getting into onboard computers? Will drivers accept computer-controlled vehicles? And who would be liable in the event of an accident in a self-driving car? All are potential stumbling blocks.

Self-driving vehicles "will be driving on our streets and highways within the next decade, but it is uncertain when they will comprise a substantial share of the U.S. fleet," the study said. "As long as...crucial questions go unanswered, the nation will be hampered in its ability to successfully plan for and introduce [autonomous vehicles] into the transportation system."

Lucas Mearian covers storage, disaster recovery and business continuity, financial services infrastructure and health care IT for Computerworld. Follow Lucas on Twitter at @lucasmearian or subscribe to Lucas's RSS feed . His e-mail address is lmearian@computerworld.com.

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