Modelling cognitive load using drift-diffusion models in pedestrian street-crossing: a method supported by neural...

Area of Science:

• Cognitive psychology
• Neuroscience
• Transportation safety

Background:

• Cognitive load negatively affects pedestrian street-crossing behavior and road safety.
• The precise mechanisms behind this impact require further investigation.

Purpose of the Study:

• To investigate how cognitive load influences pedestrian decision-making during street crossing.
• To model the effects of cognitive load on crossing behavior and neural signals.

Main Methods:

• A computer-based pedestrian crossing experiment was conducted.
• Drift-diffusion models were used to analyze decision-making under cognitive load.
• Centro-parietal positive potential (CPP) was measured using electroencephalography (EEG).

Main Results:

• Cognitive load weakened the influence of time-to-arrival (TTA) on crossing probability.
• Response times increased, collision probability rose, and CPP amplitude decreased under cognitive load.
• A drift-diffusion model demonstrated that cognitive load reduces responsiveness to evidence, correlating with CPP signals.

Conclusions:

• Cognitive load impairs pedestrian safety by reducing sensitivity to critical environmental cues like TTA.
• Reduced responsiveness to perceptual evidence is a key mechanism explaining the effects of cognitive load on non-automatised tasks.
• Findings provide a neuro-computational explanation for cognitive load's impact on pedestrian behavior and road safety.