In combination with Virginia Tech Transportation Institute, Ford is developing a communication method using lighting, so that self-driving vehicles can signal intent to pedestrians, human drivers and cyclists.
With CAVs unable to communicate their intended actions, Ford has looked to create a standard visual language, which will combat a scenario in which pedestrians are unsure of an unmanned vehicle’s next move.
The test, which took place on public roads in northern Virginia, simulated a fully self-driving experience and used an innovative seat to conceal the driver. With the illusion of a fully autonomous vehicle, the OEM could monitor real-world encounters.
Through the use of a light bar on the windshield, the car could notify pedestrians of three scenarios: two white lights moving sideways indicated yielding; a solid white light suggested active autonomous driving; and a rapidly blinking light showed the intention to start moving.
Throughout August the test captured over 150 hours of video, showing people’s reactions over approximately 1,800 miles of driving.
With the data set to be used to show how other road users change their behavior in response to CAV signals, project director Andy Schaudt spoke about the benefit to the automotive industry: “This work is of value not only to vehicle users and manufacturers, but to anyone who walks, rides or drives alongside an autonomous vehicle in the future.”
John Shutko, Ford’s human factors technical specialist, highlighted the importance of the test to the future of Ford: “Understanding how self-driving vehicles impact the world as we know it today is critical to ensuring we’re creating the right experience for tomorrow.
“We need to solve the challenges presented by not having a human driver, so designing a way to replace the head nod or hand wave is fundamental to ensuring safe and efficient operation of self-driving vehicles in our communities.”
September 20, 2017
