PSYCH OpenIR  > 社会与工程心理学研究室
Effectiveness and acceptance of the intelligent speeding prediction system (ISPS)
Zhao, Guozhen1,2; Wu, Changxu1; Wu, CX (reprint author), SUNY Buffalo, Cognit Engn Syst Lab, Buffalo, NY 14260 USA.
2013
Source PublicationACCIDENT ANALYSIS AND PREVENTION
ISSN0001-4575
Subtype期刊论文
Volume52Issue:0Pages:19-28
Contribution Rank2
Abstract

Background: The intelligent speeding prediction system (ISPS) is an in-vehicle speed assistance system developed to provide quantitative predictions of speeding. Although the ISPS's prediction of speeding has been validated, whether the ISPS can regulate a driver's speed behavior or whether a driver accepts the ISPS needs further investigation. Additionally, compared to the existing intelligent speed adaptation (ISA) system, whether the ISPS performs better in terms of reducing excessive speeds and improving driving safety needs more direct evidence. Objectives: An experiment was conducted to assess and compare the effectiveness and acceptance of the ISPS and the ISA. Method: We conducted a driving simulator study with 40 participants. System type served as a between-subjects variable with four levels: no speed assistance system, pre-warning system developed based on the ISPS, post-warning system ISA, and combined pre-warning and ISA system. Speeding criterion served as a within-subjects variable with two levels: lower (posted speed limit plus 1 mph) and higher (posted speed limit plus 5 mph) speed threshold. Several aspects of the participants' driving speed, speeding measures, lead vehicle response, and subjective measures were collected. Results: Both pre-warning and combined systems led to greater minimum time-to-collision. The combined system resulted in slower driving speed, fewer speeding exceedances, shorter speeding duration, and smaller speeding magnitude. Conclusions: The results indicate that both pre-warning and combined systems have the potential to improve driving safety and performance. (C) 2012 Elsevier Ltd. All rights reserved.

KeywordSpeeding Speeding prediction Speed assistance system Intelligent speed adaptation (ISA)
Subject AreaOther Subjects Of Applied Psychology
URL查看原文
Indexed BySCI
Language英语
WOS Research AreaEngineering ; Public, Environmental & Occupational Health ; Social Sciences - Other Topics ; Transportation
WOS SubjectErgonomics ; Public, Environmental & Occupational Health ; Social Sciences, Interdisciplinary ; Transportation
WOS IDWOS:000317444100003
WOS HeadingsScience & Technology ; Social Sciences ; Technology ; Life Sciences & Biomedicine
WOS KeywordLONG-TERM USE ; DRIVER BEHAVIOR ; ADAPTATION ; PERFORMANCE ; ASSISTANCE
Citation statistics
Cited Times:5[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Identifierhttp://ir.psych.ac.cn/handle/311026/10798
Collection社会与工程心理学研究室
Corresponding AuthorWu, CX (reprint author), SUNY Buffalo, Cognit Engn Syst Lab, Buffalo, NY 14260 USA.
Affiliation1.SUNY Buffalo, Buffalo, NY 14260 USA
2.Chinese Acad Sci, Inst Psychol, Beijing 100864, Peoples R China
Recommended Citation
GB/T 7714
Zhao, Guozhen,Wu, Changxu,Wu, CX . Effectiveness and acceptance of the intelligent speeding prediction system (ISPS)[J]. ACCIDENT ANALYSIS AND PREVENTION,2013,52(0):19-28.
APA Zhao, Guozhen,Wu, Changxu,&Wu, CX .(2013).Effectiveness and acceptance of the intelligent speeding prediction system (ISPS).ACCIDENT ANALYSIS AND PREVENTION,52(0),19-28.
MLA Zhao, Guozhen,et al."Effectiveness and acceptance of the intelligent speeding prediction system (ISPS)".ACCIDENT ANALYSIS AND PREVENTION 52.0(2013):19-28.
Files in This Item:
File Name/Size DocType Version Access License
WOS_000317444100003.(1021KB)期刊论文出版稿限制开放CC BY-NC-SAView Application Full Text
Related Services
Recommend this item
Bookmark
Usage statistics
Export to Endnote
Google Scholar
Similar articles in Google Scholar
[Zhao, Guozhen]'s Articles
[Wu, Changxu]'s Articles
[Wu, CX (reprint author), SUNY Buffalo, Cognit Engn Syst Lab, Buffalo, NY 14260 USA.]'s Articles
Baidu academic
Similar articles in Baidu academic
[Zhao, Guozhen]'s Articles
[Wu, Changxu]'s Articles
[Wu, CX (reprint author), SUNY Buffalo, Cognit Engn Syst Lab, Buffalo, NY 14260 USA.]'s Articles
Bing Scholar
Similar articles in Bing Scholar
[Zhao, Guozhen]'s Articles
[Wu, Changxu]'s Articles
[Wu, CX (reprint author), SUNY Buffalo, Cognit Engn Syst Lab, Buffalo, NY 14260 USA.]'s Articles
Terms of Use
No data!
Social Bookmark/Share
File name: WOS_000317444100003.pdf
Format: Adobe PDF
All comments (0)
No comment.
 

Items in the repository are protected by copyright, with all rights reserved, unless otherwise indicated.