Robotic eyes on self-driving vehicles could improve pedestrian safety

Robotic eyes on self-driving vehicles could improve pedestrian safety

Studies conducted at the University of Tokyo have shown that robotic eyes on self-driving vehicles could reduce the number of collisions between vehicles and pedestrians.

Participants were asked to examine scenarios via virtual reality (VR), deciding whether or not to cross a road in front of moving vehicles.

The research results showed that participants made safer choices when crossing in front of a vehicle equipped with eyes. The findings were based on robotic eyes that registered both the presence of the pedestrian and eyes looking away.

Are we envisioning a future of autonomous vehicles?

While autonomous vehicles currently represent a small part of the transportation industry, they are expected to have a significant impact on future technology.

Experts predict that self-driving vehicles will deliver our packages, plow the fields and even drive our children to school in the years to come. Once a futuristic idea, these vehicles are quickly becoming a reality.

However, researchers have recognized a missing link between autonomous vehicles and pedestrians. A key difference of self-driving cars is that drivers become more like passengers, sometimes not paying attention to the road, so pedestrians are unable to tell if drivers have registered their presence.

A lower concentration of drivers of autonomous vehicles poses the problem of more fatal accidents. The researchers therefore set out to find out how pedestrians could be informed that the vehicle has seen them and intends to stop.

The Role of Robotic Eyes in Keeping Pedestrians Safe

Researchers fitted a self-driving golf cart with remote-controlled eyes to test whether putting wiggly eyes on a car would increase people’s risk of “risky” behavior. In this case, they wanted to know if people would still cross the road in front of a moving vehicle when they were in a hurry.

Four scenarios were tested, with two autonomous vehicles equipped with eyes and two without. The scenarios were recorded with 360 degree video cameras and the participants played them out in virtual reality.

Participants were able to experience the scenarios multiple times, getting three seconds to decide whether or not to cross the road. Their choices and the error rates of their decisions were recorded to determine the impact of the eyes on their choices.

Chia-Ming Chang, the project’s senior lecturer at the University of Tokyo, said: “The results suggested a clear gender difference, which was very surprising and unexpected.

“In this study, male participants made many dangerous decisions to cross the road, but these errors were reduced by the gaze of the cart.

“On the other hand, the participants made more inefficient decisions and these errors were reduced by the gaze of the cart,” he explained.

While the robotic eyes on the self-driving vehicles were found to result in a smoother and safer pedestrian experience for all genders, attendees had mixed opinions about how the eyes made them feel.

Some described the eyes as “cute”, while others thought they were “creepy” or “creepy”. Professor Takeo Igarashi, from the Graduate School of Information, Science and Technology, explained: “We focused on eye movement but didn’t pay too much attention to their visual design in this particular study. We just built the simplest to minimize design and construction costs due to budget constraints.

“In the future, it would be better for a professional product designer to find the best design, but it would probably still be difficult to satisfy everyone. Personally, I like that. It’s pretty cute.

The researchers hope their study will inspire other institutions to conduct work on the relationship between autonomous vehicles and pedestrians. Igarashi concluded: “Switching from manual to automatic driving is a huge change. If eyes can really help safety and reduce traffic accidents, we should seriously consider adding them. In the future, we would like to develop an autonomous AI-connected robotic eye automatic control that could adapt to different situations.

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