{"title":"A new paradigm in driving comfort measurement: Environment-specific comfort index and its real-time application in Indian context","authors":"Ishita Sar , Soumitra Kundu , Aurobinda Routray , Biswajit Mahanty","doi":"10.1016/j.iatssr.2025.09.002","DOIUrl":null,"url":null,"abstract":"<div><div>Driving comfort assessment is a prerequisite to improve the journey experience for the drivers as well as the passengers. In this work, we proposed an advanced approach for the measurement of driving comfort in real-time. Different types of environmental features are considered along with the traditionally used Comfort Index (CI), and an Environment-specific Comfort Index (EsCI) is proposed. EsCI is also inversely proportional to the drivers' comfort level, just like CI. We also developed an android application named QDCL (Quantification of Driver Comfort Level) for overall data collection and computation of EsCI from the same. A series of driving experiments at different times of the day and different traffic conditions have been performed in Indian urban road scenarios to assess the performance of QDCL and the relevance of EsCI. We extended the work by studying the effects of different external stimuli on the computed driving comfort level. The performance of EsCI is observed to outperform the traditionally used CI (Comfort Index) in terms of accuracy for the quantification of overall driving comfort.</div></div>","PeriodicalId":47059,"journal":{"name":"IATSS Research","volume":"49 3","pages":"Pages 353-361"},"PeriodicalIF":3.3000,"publicationDate":"2025-09-11","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/S0386111225000329","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 comfort assessment is a prerequisite to improve the journey experience for the drivers as well as the passengers. In this work, we proposed an advanced approach for the measurement of driving comfort in real-time. Different types of environmental features are considered along with the traditionally used Comfort Index (CI), and an Environment-specific Comfort Index (EsCI) is proposed. EsCI is also inversely proportional to the drivers' comfort level, just like CI. We also developed an android application named QDCL (Quantification of Driver Comfort Level) for overall data collection and computation of EsCI from the same. A series of driving experiments at different times of the day and different traffic conditions have been performed in Indian urban road scenarios to assess the performance of QDCL and the relevance of EsCI. We extended the work by studying the effects of different external stimuli on the computed driving comfort level. The performance of EsCI is observed to outperform the traditionally used CI (Comfort Index) in terms of accuracy for the quantification of overall driving comfort.
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.