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Related Experiment Video

Updated: Jan 11, 2026

Using a Virtual Reality Walking Simulator to Investigate Pedestrian Behavior

Using a Virtual Reality Walking Simulator to Investigate Pedestrian Behavior

Published on: June 9, 2020

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

Siwei Ma¹, Xuedong Yan¹, Lu Ma¹

¹MOT Key Laboratory of Transport Industry of Big Data Application Technologies for Comprehensive Transport, Beijing Jiaotong University, Beijing 100044, PR China.

Accident; Analysis and Prevention

|November 17, 2025

Summary

This summary is machine-generated.

Cognitive load impairs pedestrian street-crossing decisions by reducing responsiveness to time-to-arrival cues. This impacts road safety by increasing collision risks and response times.

Keywords:

Centro-parietal positive potential Cognitive load Decision-making Drift-diffusion model Pedestrian crossing

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Last Updated: Jan 11, 2026

Using a Virtual Reality Walking Simulator to Investigate Pedestrian Behavior

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Published on: October 13, 2023

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.