Earlier this spring, a self-driving car struck and killed a woman, and it made national news. News about the deadly pedestrian accident involving an autonomous vehicle has increased the public’s concerns about the safety of self-driving cars. Can autonomous technology really prevent auto accidents, or do we need to be more concerned about software mistakes and other technological errors that could lead to deadly collisions between self-driving vehicles and pedestrians?
According to a recent article in U.S. News & World Report, drivers are more skeptical than ever of the safety value of self-driving cars, and many believe that they are likely to cause more car crashes than to prevent them. The study reports that, in order for people to trust autonomous technology, they would need evidence that it is significantly safer than human drivers.
Weighing the Risks and Benefits of Self-Driving Cars
How much safer must autonomous technology be in order for the public to trust it? The study, which was published in the journal Risk Analysis, determined that autonomous vehicles must be up to five times as safe as human-driven cars for the public to accept the new technology. And it is, indeed, news of the recent fatal crash as well as other self-driving car collisions that have the public concerned.
Even though there are conveniences associated with self-driving cars and safety features to consider, those do not appear to outweigh the dangers that many Americans now view as being associated with autonomous technology.
Researchers know that human error is the cause of a majority of auto accidents in the United States. Approximately 94 percent of all traffic collisions result from human error. One of the reasons why self-driving cars were developed was to lessen the risks of crashes caused by driver negligence. However, many drivers are beginning to see self-driving cars as having a similar error rate as humans, meaning that they are less likely to trust them. In fact, self-driving cars are much safer than motor vehicles operated by human drivers, where the chance for error is significantly higher.
Classifying Tolerable and Broadly Acceptable Self-Driving Vehicles
In the recent study, researchers developed three categories for self-driving cars: those that are unacceptable to the public, those that are tolerable, and those that are broadly acceptable. In order for an autonomous vehicle to be classified as tolerable, there must be evidence that it is nearly fives times as safe as an automobile driven by a human. In order for a self-driving car to reach the classification of broadly acceptable to the public, the authors of the study found that the vehicles would need to show hundredfold improvement over risks in traffic, or the same order of magnitude experienced in models of public transportation.
The study makes clear that safety standards likely will need to be improved for self-driving cars if they are to become accepted, and commonplace, on the roads.
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