Nissan Thinks Like a Fish to Create Crash-Avoiding Cars
Borrowing control logic elements that prevent fish from bouncing off of each other when swimming in schools, Nissan has created a fleet of miniature robot cars that it believes will have implications for improving crash-avoidance technology on future full-size vehicles. Looking like a multi-hued assortment of aquatic refugees from some sci-fi film, the EPORO -- a cryptic acronym for its even more cryptic "EPisode O (Zero) Robot" (Episode aiming to be CO2-free and accident-free) formal name -- represent what Nissan says is "the world's first development of robot cars that can safely travel by sharing the position and information of others within a group via communication technologies." The secret to their success lies in applying the three fundamental laws that govern piscine behavior, namely navigating in ways that permit direction changes while avoiding collisions, traveling side by side and quickly closing distances when necessary. While schools of fish manage to pull off these dynamic spatial reorientations using a combination of conventional eyesight and a well-developed lateral-line sense, the EPORO use advanced Ultra Wide Band (UWB) communications technology to mimic the former and a laser range finder to cover the latter.
"We, in a motorized world, have a lot to learn from the behavior of a school of fish in terms of each fish's degree of freedom and safety within a school and high migration efficiency of a school itself. In EPORO, we recreated the behavior of a school of fish making full use of cutting-edge electronic technologies," said Toshiyuki Andou, manager of Nissan's Mobility Laboratory and principal engineer of the robot car project. "By sharing the surrounding information received within the group via communication, the group of EPOROs can travel safely, changing its shape as needed." It remains to be seen how effectively lessons learned from EPORO program can be applied to vehicles traveling on real-world, fixed-medium pathways. But Nissan feels confident that the data it generates will contribute to a safer driving experience for all somewhere on down the road.