Driver Behaviors at Level Crossings from Fixed and Moving Driving Simulators

Inhi Kim; Gregoire Larue; Luis Ferreira; Andry Rakotonirainy; Khaled Shaaban

doi:10.1016/j.procs.2018.04.018

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Driver Behaviors at Level Crossings from Fixed and Moving Driving Simulators

Journal article

Open access

Peer reviewed

Driver Behaviors at Level Crossings from Fixed and Moving Driving Simulators

Inhi Kim, Gregoire Larue, Luis Ferreira, Andry Rakotonirainy and Khaled Shaaban

Procedia Computer Science, Vol.130, pp.103-110

2018

DOI: https://doi.org/10.1016/j.procs.2018.04.018

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Abstract

braking reaction time

compliance rates

fixed driving simulator

moving driving simulator

speed profiles

Many studies were conducted to evaluate safety at railway crossings equipped with different types of warning devices. In this study, a desktop driving simulator (fixed simulator) and an advanced simulator (moving simulator) were used to identify the impacts of two warning devices namely stop sign and in-vehicle audio warning on alerting drivers at railway crossings. Although these high-end technologies have been widely used for safety evaluation in many areas, there is a little research on their application and comparison at railway crossings. This paper reports the results of a comparison of the two simulators. As a preliminary result, vehicle speeds at given distance/time were analyzed. The results showed that when the warning started, drivers in the fixed simulator were slower than those in the moving simulator in responding. However, after four seconds of warning, the speed from both simulators showed statistically identical results. In summary, the different properties of the simulator lead drivers to react to warnings differently.

Details

Title: Driver Behaviors at Level Crossings from Fixed and Moving Driving Simulators
Authors: Inhi Kim (Author) - Monash University
Gregoire Larue (Author) - Queensland University of Technology
Luis Ferreira (Author) - The University of Queensland
Andry Rakotonirainy (Author) - Queensland University of Technology
Khaled Shaaban (Author) - Qatar University
Publication details: Procedia Computer Science, Vol.130, pp.103-110
Publisher: Elsevier BV
Date published: 2018
DOI: 10.1016/j.procs.2018.04.018
ISSN: 1877-0509
Copyright note: Copyright © 2018 The Authors. Published by Elsevier B.V. This work is licensed under a Creative Commons license Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0). The details of the license is available here: https://creativecommons.org/licenses/by-nc-nd/4.0/
Organisation Unit: Road Safety Research Collaboration; University of the Sunshine Coast, Queensland; School of Law and Society
Language: English
Record Identifier: 99649478802621
Output Type: Journal article

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Web Of Science research areas: Computer Science, Artificial Intelligence; Computer Science, Hardware & Architecture; Computer Science, Theory & Methods

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