Automated vehicles could be made more pedestrian-friendly thanks to new research which could help them predict when people will cross the road.
October 5,2021 Automated vehicles could be made more pedestrian-friendly thanks to new research which could help them predict when people will cross the road. University of Leeds-led scientists investigating how to better understand human behavior in traffic say that neuroscientific theories of how the brain makes decisions can be used in automated vehicle technology to improve safety and make them more human-friendly. The researchers set out to determine whether a decision-making model called drift diffusion could predict when pedestrians would cross a road in front of approaching cars, and whether it could be used in scenarios where the car gives way to the pedestrian, either with or without explicit signals. This prediction capability will allow the autonomous vehicle to communicate more effectively with pedestrians, in terms of its movements in traffic and any external signals such as flashing lights, to maximize traffic flow and decrease uncertainty. Drift diffusion models assume that people reach decisions after accumulation of sensory evidence up to a threshold at which the decision is made. Professor Gustav Markkula, from the University of Leeds’ Institute for Transport Studies and the senior author of the study, said: « When making the decision to cross, pedestrians seem to be adding up lots of different sources of evidence, not only relating to the vehicle’s distance and speed, but also using communicative cues from the vehicle in terms of deceleration and headlight flashes.
