Literature DB >> 23298705

Effectiveness and acceptance of the intelligent speeding prediction system (ISPS).

Guozhen Zhao1, Changxu Wu.   

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.
Copyright © 2012 Elsevier Ltd. All rights reserved.

Entities:  

Mesh:

Year:  2013        PMID: 23298705     DOI: 10.1016/j.aap.2012.12.013

Source DB:  PubMed          Journal:  Accid Anal Prev        ISSN: 0001-4575


  4 in total

1.  The Five Key Questions of Human Performance Modeling.

Authors:  Changxu Wu
Journal:  Int J Ind Ergon       Date:  2016-05-21       Impact factor: 2.656

2.  The impairing effects of mental fatigue on response inhibition: An ERP study.

Authors:  Zizheng Guo; Ruiya Chen; Xian Liu; Guozhen Zhao; Yan Zheng; Mingliang Gong; Jun Zhang
Journal:  PLoS One       Date:  2018-06-01       Impact factor: 3.240

3.  Method-oriented systematic review on the simple scale for acceptance measurement in advanced transport telematics.

Authors:  Jan C Zoellick; Adelheid Kuhlmey; Liane Schenk; Stefan Blüher
Journal:  PLoS One       Date:  2021-03-25       Impact factor: 3.240

4.  Contingent negative variation during a modified cueing task in simulated driving.

Authors:  Zizheng Guo; Xi Tan; Yufan Pan; Xian Liu; Guozhen Zhao; Lin Wang; Zhen Peng
Journal:  PLoS One       Date:  2019-11-11       Impact factor: 3.240

  4 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.