Ordered-logit pedestrian stress model for traffic flow with automated vehicles

TL;DR

This paper introduces an ordered-logit model to assess how increasing automated vehicles in traffic reduce pedestrian stress levels at mid-block crossings, based on VR experiments and physiological data.

Contribution

It presents a novel ordered-logit model linking AV percentage to pedestrian stress, incorporating experimental data for urban traffic scenarios.

Findings

Stress levels decrease as the percentage of AVs increases.

VR experiments and skin resistance data effectively quantify pedestrian stress.

The model provides insights for urban traffic management with AV integration.

Abstract

An ordered-logit model is developed to study the effects of Automated Vehicles (AVs) in the traffic mix on the average stress level of a pedestrian when crossing an urban street at mid-block. Information collected from a galvanic skin resistance sensor and virtual reality experiments are transformed into a dataset with interpretable average stress levels (low, medium, and high) and geometric, traffic, and environmental conditions. Modelling results indicate a decrease in average stress level with the increase in the percentage of AVs in the traffic mix.