Mercedes-Benz Co-Operative Car Concept Uses Turquoise Leds To ‘Talk’ To Pedestrians

Some researchers in the field of autonomous cars call it “the handshake” — that’s the process of figuring out how pedestrians and human drivers will interact with driverless vehicles on the roads. Research has revealed that pedestrians don’t feel comfortable when sharing space with autonomous cars, but Mercedes-Benz says its research shows humans feel better when such cars are clearly marked.

Mercedes-Benz Co-Operative Car

The carmaker put four semi-circular pods with turquoise LEDs on the roof, and turquoise LED light bars at the top of the windshield and backlight. Even the light strips on the side mirrors flash in turquoise. Mercedes chose turquoise because it doesn’t appear anywhere else in the transportation sphere. The brand would like to see this color become the standard for car-to-pedestrian communication. Two directional speakers fill the corner intakes on the front bumper. The exhibition model should do especially well in the U.S. Northeast, since Daimler’s graphic designers unintentionally created a remarkable likeness of the New England Patriots logo on the flanks.

When small portions of the light bars illuminate, the Co-Operative Car is in autonomous mode. Sensors can not only detect people around the car, they can detect faces. The LEDs in this case become analogous to pupils, making ‘eye contact’ with and tracking pedestrians.

The technology demonstrator was shown to media during another of Daimler’s FutureInsight talks, this one focused on programming empathetic communication into self-driving vehicles and signaling vehicle intent. This would be an experimental evolution of the autonomous S-Class sedans Daimler and Bosch are using for real-world research in Stuttgart, Germany right now and San Jose, California next year.

And because no story like this is complete without invoking SkyNet, Daimler futurologist Alexander Mankowsky said, “The discussions about the basics [among manufacturers] have already begun,” and that we could begin to see results in a few years. He added, “Machine learning has no ‘ah ha’ moment. There is only training.”

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