Ford, Virginia Tech test pedestrian communication with ‘self-driving’ vehicles
Looking to prepare for how a self-driving car with no human driver will communicate with pedestrians, cyclists, or humans operating other cars, Ford Motor Company partnered with Virginia Tech Transportation Institute to test out a method for communicating a vehicle’s intent by soliciting real-world reactions to a self-driving car on public roads.
“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,” said John Shutko, Ford’s Human Factors Technical Specialist. “We need to solve for 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.”
The joint research project set out to investigate the most effective means for the vehicle to communicate. Researchers decided lighting signals are the most effective means for creating a visual communications protocol for self-driving vehicles. As light signals for turning and braking indication are already standardized and widely understood, they determined the use of lighting signals is best to communicate whether the vehicle is in autonomous drive mode, beginning to yield, or about to accelerate from a stop.
Ford outfitted a Transit Connect van with a light bar placed on the windshield. To simulate a fully self-driving experience without using an actual autonomous vehicle, the Virginia Tech Transportation Institute team developed a way to conceal the driver with a “seat suit.”
The suit creates the illusion of a fully autonomous vehicle, which is necessary to test and evaluate real-world encounters and behaviors. The researchers then experimented with three light signals to test the communication of the vehicle’s intent:
- Yield: Two white lights that move side to side, indicating vehicle is about to yield to a full stop
- Active autonomous driving mode: Solid white light to indicate vehicle is driving autonomously
- Start to go: Rapidly blinking white light to indicate vehicle is beginning to accelerate from a stop
The simulated autonomous Transit Connect was driven on public roads in northern Virginia—home to a density of traffic and pedestrians—throughout August, with researchers capturing video and logs of pedestrian reactions. More than 150 hours of data over approximately 1800 miles of driving was collected in an urban environment, including encounters with pedestrians, bicyclists, and other drivers. External signals were activated more than 1650 times at locations around Arlington, VA, including at intersections, parking lots, garages, and airport roadways.
Numerous high-definition cameras mounted in the study vehicle provided a 360-degree view of surrounding areas and captured the behavior of other road users. Researchers say this data will be valuable to understanding if other road users change their behaviors in response to self-driving vehicles and the signals they employ.
"This work is of value not only to vehicle users and manufacturers, but also to anyone who walks, rides, or drives alongside autonomous vehicles in the future,” said Andy Schaudt, Project Director, Center for Automated Vehicle Systems, Virginia Tech Transportation Institute. “We are proud to support Ford in developing this important research.”
Ford is already working with several industry organizations to push toward creation of a standard, including the International Organization for Standardization and SAE International. A common visual communications interface most people can understand across all self-driving vehicles in all locations will help ensure safe integration into transportation systems. Ford is also working on ways to communicate with those who are blind or visually impaired as part of a separate work stream.
“Preparing for a self-driving future is going to take all of us working together,” said Shutko. “That’s why we’re developing and advocating for a standard solution so it can be adopted by the industry and applied to all self-driving vehicles.”