Leeds aims to improve safety in autonomous vehicles

The researchers at Leeds University explored a decision-making model called drift diffusion to determine whether it 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 with or without explicit signals.

This prediction capability could help autonomous vehicles to communicate more effectively with pedestrians, the team believes, in terms of their movements in traffic and any external signals such as flashing lights.

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 the study's senior author Professor Gustav Markkula, from Leeds University’s Institute for Transport Studies.