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 would in turn 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 maximise 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.
“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,” said Professor Gustav...