Deriving weeklong activity-travel dairy from Google Location History: survey tool development and a field test in Toronto
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作者:
Li, Melvyn
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机构:
Univ Toronto, Dept Civil & Mineral Engn, 35 St George St, Toronto, ON M5S 1A4, CanadaUniv Toronto, Dept Civil & Mineral Engn, 35 St George St, Toronto, ON M5S 1A4, Canada
Li, Melvyn
[1
]
Wang, Kaili
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机构:
Univ Toronto, Dept Civil & Mineral Engn, 35 St George St, Toronto, ON M5S 1A4, CanadaUniv Toronto, Dept Civil & Mineral Engn, 35 St George St, Toronto, ON M5S 1A4, Canada
Wang, Kaili
[1
]
Liu, Yicong
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机构:
Univ Toronto, Dept Civil & Mineral Engn, 35 St George St, Toronto, ON M5S 1A4, CanadaUniv Toronto, Dept Civil & Mineral Engn, 35 St George St, Toronto, ON M5S 1A4, Canada
Liu, Yicong
[1
]
Nurul Habib, Khandker
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Univ Toronto, Dept Civil & Mineral Engn, 35 St George St, Toronto, ON M5S 1A4, CanadaUniv Toronto, Dept Civil & Mineral Engn, 35 St George St, Toronto, ON M5S 1A4, Canada
Nurul Habib, Khandker
[1
]
机构:
[1] Univ Toronto, Dept Civil & Mineral Engn, 35 St George St, Toronto, ON M5S 1A4, Canada
GPS survey;
Smartphone-based travel survey;
Google Location History;
GLOBAL POSITIONING SYSTEMS;
DIARY COLLECTION;
TRIP PURPOSE;
SMARTPHONE;
D O I:
10.1007/s11116-024-10523-3
中图分类号:
TU [建筑科学];
学科分类号:
0813 ;
摘要:
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 utilizes the existing travel survey software, TRavel Activity Internet Survey Interface (TRAISI), which allows for the design and implementation of surveys through highly modular and customizable components. A new module was developed within this software to serve as a repository for GLH, enabling the derivation of activity-travel diaries from each respondent's 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.