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Nissan Will Teach Autonomous Cars Each City's Driving Habits

In the future, your car may be more cultured than a well-traveled human.

Until the contents of the human psyche can be uploaded onto a hard drive, autonomous cars will always have one major downfall when compared to human drivers: the ability to break the rules when the situation calls for it. This poses a challenge for the manufacturers, which are beginning to realize that the driving style in an expansive countryside varies widely from the traffic shit show that takes place in most major cities. Auto Express sat down with Nissan to see just how the auto industry is taking this into account.

Maarten Sierhuis, director at Nissan's Research Center in Silicon Valley, sums it up by saying, “The way people drive in Sao Paolo differs from the way people drive in Silicon Valley, California. What is socially acceptable in Sao Paolo is not socially acceptable in Silicon Valley. Autonomous cars will need to take this into account.” To instill self-driving cars with the tools necessary to navigate between cities with widely varying and even conflicting driving styles, Nissan has hired the help of sociologists and anthropologists to help better understand the mentality of each city. The automaker’s approach to the problem is to apply a cultural lens to its autonomous software to allow its vehicles to alter reactions, following distances, and more.

If Nissan cared to make its cultural filters more accurate, it would ensure that cars in Los Angeles honk their horns once a minute and cars in New York have a signal in the shape of a middle finger. While it may seem more practical to simply program self-driving cars to adapt to the surrounding situation, Melissa Cefkin, principal scientist and design anthropologist at Nissan Research Center, says, “There are patterns that we can perhaps prime into the cars so the systems will be able to interpret the environment. With a social lens, we can do this without relying on miles and decades of technological sensing.” This is one of the many real world challenges faced by autonomous cars that erodes the theory that they are perfect solution.

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