{"title":"通过整合信息熵和标准偏差测量城市居民通勤的旅行时间可靠性","authors":"Junjun Zhan","doi":"10.1155/2024/8249757","DOIUrl":null,"url":null,"abstract":"<div>\n <p>Travel Time Reliability (TTR) plays a pivotal role in commuting. Nevertheless, existing measurement methods are not specifically designed for commuting scenarios, and their direct application to assess TTR for commuting may yield results incongruent with actual commuting conditions, as they overly rely on measures like mean and percentiles. Drawing on the cyclical characteristics of commuting, the study has established a TTR measurement model based on information entropy and standard deviation, tailored to individual commuters. By selecting commuting data from extensive travel datasets and applying both this model and conventional measurement methods, the focus is on quantitatively analyzing TTR for metro commuters and car commuters under various feature conditions, with a particular emphasis on commuting to work. The objective is to verify the feasibility and advantages of the proposed model. The research indicates that, compared to typical measurement methods, this model more accurately reflects TTR for commuting purposes. The results underscore a significantly superior TTR for metro commuters over car commuters. Distance and departure time exert a substantial impact on the TTR of car commuters, while distance and transfer times moderately influence the TTR of metro commuters. These findings serve as a crucial foundation for enhancing the quality of commuting experiences.</p>\n </div>","PeriodicalId":2,"journal":{"name":"ACS Applied Bio Materials","volume":null,"pages":null},"PeriodicalIF":4.6000,"publicationDate":"2024-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1155/2024/8249757","citationCount":"0","resultStr":"{\"title\":\"Measuring Travel Time Reliability for Urban Residents’ Commutes via the Integration of Information Entropy and Standard Deviation\",\"authors\":\"Junjun Zhan\",\"doi\":\"10.1155/2024/8249757\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div>\\n <p>Travel Time Reliability (TTR) plays a pivotal role in commuting. Nevertheless, existing measurement methods are not specifically designed for commuting scenarios, and their direct application to assess TTR for commuting may yield results incongruent with actual commuting conditions, as they overly rely on measures like mean and percentiles. Drawing on the cyclical characteristics of commuting, the study has established a TTR measurement model based on information entropy and standard deviation, tailored to individual commuters. By selecting commuting data from extensive travel datasets and applying both this model and conventional measurement methods, the focus is on quantitatively analyzing TTR for metro commuters and car commuters under various feature conditions, with a particular emphasis on commuting to work. The objective is to verify the feasibility and advantages of the proposed model. The research indicates that, compared to typical measurement methods, this model more accurately reflects TTR for commuting purposes. The results underscore a significantly superior TTR for metro commuters over car commuters. Distance and departure time exert a substantial impact on the TTR of car commuters, while distance and transfer times moderately influence the TTR of metro commuters. These findings serve as a crucial foundation for enhancing the quality of commuting experiences.</p>\\n </div>\",\"PeriodicalId\":2,\"journal\":{\"name\":\"ACS Applied Bio Materials\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":4.6000,\"publicationDate\":\"2024-09-16\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://onlinelibrary.wiley.com/doi/epdf/10.1155/2024/8249757\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"ACS Applied Bio Materials\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://onlinelibrary.wiley.com/doi/10.1155/2024/8249757\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"MATERIALS SCIENCE, BIOMATERIALS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"ACS Applied Bio Materials","FirstCategoryId":"5","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1155/2024/8249757","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"MATERIALS SCIENCE, BIOMATERIALS","Score":null,"Total":0}
Measuring Travel Time Reliability for Urban Residents’ Commutes via the Integration of Information Entropy and Standard Deviation
Travel Time Reliability (TTR) plays a pivotal role in commuting. Nevertheless, existing measurement methods are not specifically designed for commuting scenarios, and their direct application to assess TTR for commuting may yield results incongruent with actual commuting conditions, as they overly rely on measures like mean and percentiles. Drawing on the cyclical characteristics of commuting, the study has established a TTR measurement model based on information entropy and standard deviation, tailored to individual commuters. By selecting commuting data from extensive travel datasets and applying both this model and conventional measurement methods, the focus is on quantitatively analyzing TTR for metro commuters and car commuters under various feature conditions, with a particular emphasis on commuting to work. The objective is to verify the feasibility and advantages of the proposed model. The research indicates that, compared to typical measurement methods, this model more accurately reflects TTR for commuting purposes. The results underscore a significantly superior TTR for metro commuters over car commuters. Distance and departure time exert a substantial impact on the TTR of car commuters, while distance and transfer times moderately influence the TTR of metro commuters. These findings serve as a crucial foundation for enhancing the quality of commuting experiences.