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

04/24/2022
by   Kimia Kamal, et al.
0

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.

READ FULL TEXT

page 1

page 2

page 3

page 4

research
11/22/2021

Analysis of pedestrian stress level using GSR sensor in virtual immersive reality

Level of emotional arousal of one's body changes in response to external...
research
02/18/2020

Decoding pedestrian and automated vehicle interactions using immersive virtual reality and interpretable deep learning

To ensure pedestrian friendly streets in the era of automated vehicles, ...
research
04/16/2019

DeepSurvival: Pedestrian Wait Time Estimation in Mixed Traffic Conditions Using Deep Survival Analysis

Pedestrian's road crossing behaviour is one of the important aspects of ...
research
04/08/2023

Interpretable machine learning-accelerated seed treatment by nanomaterials for environmental stress alleviation

Crops are constantly challenged by different environmental conditions. S...
research
08/15/2023

AutoLTS: Automating Cycling Stress Assessment via Contrastive Learning and Spatial Post-processing

Cycling stress assessment, which quantifies cyclists' perceived stress i...
research
12/21/2022

Debiased machine learning for estimating the causal effect of urban traffic on pedestrian crossing behaviour

Before the transition of AVs to urban roads and subsequently unprecedent...

Please sign up or login with your details

Forgot password? Click here to reset