{"title":"Collection duration of driving tracking data of older drivers","authors":"Misako Yamagishi","doi":"10.1016/j.iatssr.2025.09.007","DOIUrl":null,"url":null,"abstract":"<div><div>Driving tracking, or the observation of actual and naturalistic driving, is an effective approach for understanding and assessing the driving behaviors of older drivers. However, limited information is available regarding the effects of data collection duration on the characteristics of driving behavior. This study examined how different data collection durations (2 weeks and 1, 3, 6, and 12 months) influence older drivers' long-term driving behavior, specifically rapid deceleration events (RDEs). Analysis of the varying durations revealed common tendencies related to low-mileage bias (LMB) as well as differences in the likelihood of RDE occurrence. These factors were incorporated into predictive models, with values estimated using negative binomial regression across the different data collection durations. The results indicated that the characteristics of driving behavior differ between short-term (2 weeks and 1 month) and long-term (3, 6, and 12 months) data collection. Finally, this study provides insights into establishing a methodology for tracking driving behavior in older adults.</div></div>","PeriodicalId":47059,"journal":{"name":"IATSS Research","volume":"49 3","pages":"Pages 410-417"},"PeriodicalIF":3.3000,"publicationDate":"2025-10-01","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/S038611122500038X","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
Driving tracking, or the observation of actual and naturalistic driving, is an effective approach for understanding and assessing the driving behaviors of older drivers. However, limited information is available regarding the effects of data collection duration on the characteristics of driving behavior. This study examined how different data collection durations (2 weeks and 1, 3, 6, and 12 months) influence older drivers' long-term driving behavior, specifically rapid deceleration events (RDEs). Analysis of the varying durations revealed common tendencies related to low-mileage bias (LMB) as well as differences in the likelihood of RDE occurrence. These factors were incorporated into predictive models, with values estimated using negative binomial regression across the different data collection durations. The results indicated that the characteristics of driving behavior differ between short-term (2 weeks and 1 month) and long-term (3, 6, and 12 months) data collection. Finally, this study provides insights into establishing a methodology for tracking driving behavior in older adults.
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.