{"title":"Deriving Weeklong Activity-Travel Dairy from Google Location History: Survey Tool Development and A Field Test in Toronto","authors":"Melvyn Li, Kaili Wang, Yicong Liu, Khandker Nurul Habib","doi":"arxiv-2311.10210","DOIUrl":null,"url":null,"abstract":"This paper introduces an innovative travel survey methodology that utilizes\nGoogle Location History (GLH) data to generate travel diaries for\ntransportation demand analysis. By leveraging the accuracy and omnipresence\namong smartphone users of GLH, the proposed methodology avoids the need for\nproprietary GPS tracking applications to collect smartphone-based GPS data.\nThis research enhanced an existing travel survey designer, Travel Activity\nInternet Survey Interface (TRAISI), to make it capable of deriving travel\ndiaries from the respondents' GLH. The feasibility of this data collection\napproach is showcased through the Google Timeline Travel Survey (GTTS)\nconducted in the Greater Toronto Area, Canada. The resultant dataset from the\nGTTS is demographically representative and offers detailed and accurate travel\nbehavioural insights.","PeriodicalId":501487,"journal":{"name":"arXiv - QuantFin - Economics","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2023-11-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"arXiv - QuantFin - Economics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/arxiv-2311.10210","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
This paper introduces an innovative travel survey methodology that utilizes
Google Location History (GLH) data to generate travel diaries for
transportation demand analysis. By leveraging the accuracy and omnipresence
among smartphone users of GLH, the proposed methodology avoids the need for
proprietary GPS tracking applications to collect smartphone-based GPS data.
This research enhanced an existing travel survey designer, Travel Activity
Internet Survey Interface (TRAISI), to make it capable of deriving travel
diaries from the respondents' GLH. The feasibility of this data collection
approach is showcased through the Google Timeline Travel Survey (GTTS)
conducted in the Greater Toronto Area, Canada. The resultant dataset from the
GTTS is demographically representative and offers detailed and accurate travel
behavioural insights.