Connected vehicle project could end motorway pileups
The Multi-Car Collision Avoidance (MuCCA) research and development project announced that it has used artificial intelligence (AI) and vehicle-to-vehicle (V2V) communications to instruct autonomous vehicles to cooperatively make decisions to avoid potential incidents. The goal is to radically reduce the number of multi-vehicle collisions on motorways.
The project, funded by Innovate UK and the Centre for Connected and Autonomous Vehicles (CCAV), and delivered by a consortium led by Applus IDIADA with Cranfield University, Westfield Sports Cars, Cosworth, SBD Automotive, and Connected Places Catapult, has seen MuCCA-equipped vehicles successfully complete replicas of real-life UK motorway scenarios on test tracks. When the technology in the vehicles detects an incident, the cars share information by radio links, and the onboard computers calculate the best maneuver to avoid the obstacles and then safely steer the agreed path to avoid an accident. The MuCCA-equipped vehicles also avoid each other and remove the need to brake suddenly—which may have caused vehicles behind to drive into them.
“Computer simulations enabled us to model how human drivers behave on motorways, and how the proximity of surrounding cars influences their behavior,” said Icaro Bezerra-Viana, Research Fellow in Autonomous Cars in the Signals and Autonomy Group in the Centre for Electronic Warfare Information and Cyber at Cranfield University. “The movement of the cars that surround a vehicle over the next few seconds can then be predicted in order to avoid a collision. Being part of the MuCCA consortium and working with partners has enabled us to learn more technically and work together to find the most appropriate solutions.”
For more information, visit https://cp.catapult.org.uk.