Unpacking the relationship between task complexity and driving risk: Insights from a UK on-road trial

IF 3.2 Q3 TRANSPORTATION
Evita Papazikou , Rachel Talbot , Laurie Brown , Sally Maynard , Ashleigh Filtness
{"title":"Unpacking the relationship between task complexity and driving risk: Insights from a UK on-road trial","authors":"Evita Papazikou ,&nbsp;Rachel Talbot ,&nbsp;Laurie Brown ,&nbsp;Sally Maynard ,&nbsp;Ashleigh Filtness","doi":"10.1016/j.iatssr.2025.03.003","DOIUrl":null,"url":null,"abstract":"<div><div>This study investigates the intricate relationship between task complexity and driving risk through a comprehensive four-phase on-road trial conducted in the UK. Employing Structural Equation Modelling (SEM), the research illuminates the factors influencing task complexity and its association with risk, treating both as latent concepts—unobservable variables in the study. The findings reveal a notable positive correlation between task complexity and risk, particularly concerning the headway indicator. In essence, the study demonstrates that an escalation in task complexity corresponds to an increased level of risk.</div><div>Throughout the four SEM analyses performed across two waves of on-road trials, the time spent in each safety tolerance zone level for headway measurements emerges as a key indicator of the latent construct of risk in all phases. Notably, the variables constituting the latent concept of task complexity—those proven statistically significant—show slight variations across phases. Variables consistently significant across all phases include the number of right Lane Departure Warnings (LDWs) per 30 s and the day of the week.</div><div>The models reveal the feasibility of quantifying the risk-task complexity relationship in real-world driving settings. This study provides insights to inform efforts to mitigate risk exposure through design and training interventions, targeting the most predictive factors linked to task complexity. Driver demographics did not emerge as statistically significant, emphasising the need for a holistic approach to improve road safety.</div></div>","PeriodicalId":47059,"journal":{"name":"IATSS Research","volume":"49 2","pages":"Pages 127-136"},"PeriodicalIF":3.2000,"publicationDate":"2025-03-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"IATSS Research","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0386111225000123","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"TRANSPORTATION","Score":null,"Total":0}
引用次数: 0

Abstract

This study investigates the intricate relationship between task complexity and driving risk through a comprehensive four-phase on-road trial conducted in the UK. Employing Structural Equation Modelling (SEM), the research illuminates the factors influencing task complexity and its association with risk, treating both as latent concepts—unobservable variables in the study. The findings reveal a notable positive correlation between task complexity and risk, particularly concerning the headway indicator. In essence, the study demonstrates that an escalation in task complexity corresponds to an increased level of risk.
Throughout the four SEM analyses performed across two waves of on-road trials, the time spent in each safety tolerance zone level for headway measurements emerges as a key indicator of the latent construct of risk in all phases. Notably, the variables constituting the latent concept of task complexity—those proven statistically significant—show slight variations across phases. Variables consistently significant across all phases include the number of right Lane Departure Warnings (LDWs) per 30 s and the day of the week.
The models reveal the feasibility of quantifying the risk-task complexity relationship in real-world driving settings. This study provides insights to inform efforts to mitigate risk exposure through design and training interventions, targeting the most predictive factors linked to task complexity. Driver demographics did not emerge as statistically significant, emphasising the need for a holistic approach to improve road safety.
求助全文
约1分钟内获得全文 求助全文
来源期刊
IATSS Research
IATSS Research TRANSPORTATION-
CiteScore
6.40
自引率
6.20%
发文量
44
审稿时长
42 weeks
期刊介绍: First published in 1977 as an international journal sponsored by the International Association of Traffic and Safety Sciences, IATSS Research has contributed to the dissemination of interdisciplinary wisdom on ideal mobility, particularly in Asia. IATSS Research is an international refereed journal providing a platform for the exchange of scientific findings on transportation and safety across a wide range of academic fields, with particular emphasis on the links between scientific findings and practice in society and cultural contexts. IATSS Research welcomes submission of original research articles and reviews that satisfy the following conditions: 1.Relevant to transportation and safety, and the multiple impacts of transportation systems on security, human health, and the environment. 2.Contains important policy and practical implications based on scientific evidence in the applicable academic field. In addition to welcoming general submissions, IATSS Research occasionally plans and publishes special feature sections and special issues composed of invited articles addressing specific topics.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信