Impacts of information quantity and display formats on driving behaviors in a connected vehicle environment
File(s)Manuscript-2024201.docx (3.99 MB)
Accepted version
Author(s)
Type
Journal Article
Abstract
The emerging connected vehicle (CV) technologies facilitate the development of integrated advanced driver assistance systems (ADASs), with which various functions are coordinated in a comprehensive framework. However, challenges arise in enabling drivers to perceive important information with minimal distractions when multiple messages are simultaneously provided by integrated ADASs. To this end, this study introduces three types of human-machine interfaces (HMIs) for an integrated ADAS: 1) three messages using a visual display only, 2) four messages using a visual display only, and 3) three messages using visual plus auditory displays. Meanwhile, the differences in driving performance across three HMI types are examined to investigate the impacts of information quantity and display formats on driving behaviors. Additionally, variations in drivers' responses to the three HMI types are examined. Driving behaviors of 51 drivers with respect to three HMI types are investigated in eight field testing scenarios. These scenarios include warnings for rear-end collision, lateral collision, forward collision, lane-change, and curve speed, as well as notifications for emergency events downstream, the specified speed limit, and car-following behaviors. Results indicate that, compared to a visual display only, presenting three messages through visual and auditory displays enhances driving performance in four typical scenarios. Compared to the presentation of three messages, a visual display offering four messages improves driving performance in rear-end collision warning scenarios but diminishes the performance in lane-change scenarios. Additionally, the relationship between information quantity and display formats shown on HMIs and driving performance can be moderated by drivers' gender, occupation, driving experience, annual driving distance, and safety attitudes. Findings are indicative to designers in automotive industries in developing HMIs for future CVs.
Date Issued
2024-08
Date Acceptance
2024-05-05
Citation
Accident Analysis and Prevention, 2024, 203
ISSN
0001-4575
Publisher
Elsevier
Journal / Book Title
Accident Analysis and Prevention
Volume
203
Copyright Statement
Copyright © 2024 Elsevier Ltd. All rights reserved. This is the author’s accepted manuscript made available under a CC-BY licence in accordance with Imperial’s Research Publications Open Access policy (www.imperial.ac.uk/oa-policy)
License URL
Identifier
https://www.ncbi.nlm.nih.gov/pubmed/38729056
Subjects
Advanced driver assistance systems
Connected vehicles
Driving performance
Field tests
Human-machine interfaces
Publication Status
Published
Coverage Spatial
England
Article Number
107621
Date Publish Online
2024-05-10