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dc.contributor.author
Montini, Lara
dc.contributor.supervisor
Bar-Gera, Hillel
dc.contributor.supervisor
Axhausen, Kay W.
dc.date.accessioned
2017-10-25T08:17:25Z
dc.date.available
2017-06-12T12:42:36Z
dc.date.available
2017-10-25T08:17:25Z
dc.date.issued
2016
dc.identifier.uri
http://hdl.handle.net/20.500.11850/120639
dc.identifier.doi
10.3929/ethz-a-010740244
dc.description.abstract
Travel surveys are increasingly taking advantage of global positioning system (GPS) data offering precise and objective route and time observations whilst potentially reducing response burden. However, there are still several open issues concerning the automated post-processing of these large datasets. Without a reliable post-processing, GPS-based studies require either a considerable amount of manual analysis, leading to costly surveys or extensive prompted-recall interviews with the respondents. As part of this thesis a travel diary study was conducted in the Greater Zurich Area. 150 participants carried dedicated GPS devices for up to one week and corrected their diaries in a web-based prompted recall tool. Using the resulting data set, the existing POSition DAta Processing framework was extended by a trip purpose module. Random forests, a machine learning technique, is used for classification. For trip purpose a share of correct predictions between 80 and 85 % is achieved for different setups. High variability in accuracy between persons is observed. Hence, personalisation strategies are tested. It is shown that the classifier is improved if it is learned on data that includes some of the participant?s annotations (median accuracy + 5.5 %). The updated processing tool, and also lessons learned from the GPS survey in Zurich are tested in the PEACOX project, a joint project with many partners where a smartphone cross modal trip planner was developed that encourages ecological friendly behaviour. GPS and accelerometer time series for 33 study participants in Vienna and Dublin are available for analysis; these were tracked simultaneously with smartphones and dedicated devices for 8 weeks. Therefore, further insight into the usefulness of smartphones and dedicated GPS devices for collecting current travel survey data is gained. Meaningful diaries can be extracted from both data sources. However, if high resolution data is needed, results suggest that dedicated GPS devices are still relevant; they have no battery issues, meaning that more data is recorded and that data quality is more stable. High resolution data is particularly interesting to observe taken routes. Two potential applications are shown here: route choice models are estimated for all travel modes (public transport, car, bicycle and walking) and parking search is shown to be hard to identify in our data.
en_US
dc.language.iso
en
en_US
dc.publisher
ETH Zürich
en_US
dc.rights.uri
http://rightsstatements.org/page/InC-NC/1.0/
dc.subject
ZURICH, DISTRICT (CANTON OF ZURICH)
en_US
dc.subject
FALLSTUDIEN (DOKUMENTENTYP)
en_US
dc.subject
CASE STUDIES (DOCUMENT TYPE)
en_US
dc.subject
TRANSPORT STATISTICS + TRAFFIC CENSUS (TRANSPORTATION AND TRAFFIC)
en_US
dc.subject
GLOBAL POSITIONING SYSTEM, GPS + INDOOR GPS (GEODESY)
en_US
dc.subject
GLOBAL POSITIONING SYSTEM, GPS + INDOOR GPS (GEODÄSIE)
en_US
dc.subject
ZIELFÜHRUNG + WEGWEISUNG (VERKEHR UND TRANSPORT)
en_US
dc.subject
ROUTE GUIDANCE (TRANSPORTATION AND TRAFFIC)
en_US
dc.subject
VERKEHRSSTATISTIK + VERKEHRSZÄHLUNG (VERKEHR UND TRANSPORT)
en_US
dc.subject
STATISTICAL DATA HANDLING (MATHEMATICAL STATISTICS)
en_US
dc.subject
ZÜRICH, BEZIRK (KANTON ZÜRICH)
en_US
dc.subject
VERARBEITUNG UND AUSWERTUNG STATISTISCHER DATEN (MATHEMATISCHE STATISTIK)
en_US
dc.title
Extraction of transportation information from combined position and accelerometer tracks
en_US
dc.type
Doctoral Thesis
dc.rights.license
In Copyright - Non-Commercial Use Permitted
dc.date.published
2016
ethz.size
204 p.
en_US
ethz.code.ddc
6 - Technology, medicine and applied sciences::624 - Civil engineering
en_US
ethz.code.ddc
3 - Social sciences::380 - Commerce, communications, transport
en_US
ethz.identifier.diss
23531
en_US
ethz.identifier.nebis
010740244
ethz.publication.place
Zürich
en_US
ethz.publication.status
published
en_US
ethz.leitzahl
ETH Zürich::00002 - ETH Zürich::00012 - Lehre und Forschung::00007 - Departemente::02115 - Dep. Bau, Umwelt und Geomatik / Dep. of Civil, Env. and Geomatic Eng.
en_US
ethz.leitzahl
ETH Zürich::00002 - ETH Zürich::00012 - Lehre und Forschung::00007 - Departemente::02115 - Dep. Bau, Umwelt und Geomatik / Dep. of Civil, Env. and Geomatic Eng.::02610 - Inst. f. Verkehrspl. u. Transportsyst. / Inst. Transport Planning and Systems::03521 - Axhausen, Kay W. / Axhausen, Kay W.
en_US
ethz.leitzahl
ETH Zürich::00002 - ETH Zürich::00012 - Lehre und Forschung::00007 - Departemente::02100 - Dep. Architektur / Dep. of Architecture::02655 - Netzwerk Stadt und Landschaft D-ARCH::02226 - NSL - Netzwerk Stadt und Landschaft / NSL - Network City and Landscape
en_US
ethz.leitzahl
ETH Zürich::00002 - ETH Zürich::00012 - Lehre und Forschung::00007 - Departemente::02100 - Dep. Architektur / Dep. of Architecture::02655 - Netzwerk Stadt und Landschaft D-ARCH
*
ethz.leitzahl.certified
ETH Zürich::00002 - ETH Zürich::00012 - Lehre und Forschung::00007 - Departemente::02115 - Dep. Bau, Umwelt und Geomatik / Dep. of Civil, Env. and Geomatic Eng.::02610 - Inst. f. Verkehrspl. u. Transportsyst. / Inst. Transport Planning and Systems::03521 - Axhausen, Kay W. / Axhausen, Kay W.
ethz.date.deposited
2017-06-12T12:45:48Z
ethz.source
ECOL
ethz.source
ECIT
ethz.identifier.importid
imp593654b7689ed92501
ethz.identifier.importid
imp59366b9e967b043870
ethz.ecolpid
eth:49830
ethz.ecitpid
pub:182712
ethz.eth
yes
en_US
ethz.availability
Open access
en_US
ethz.rosetta.installDate
2017-07-18T21:43:36Z
ethz.rosetta.lastUpdated
2018-11-05T23:13:44Z
ethz.rosetta.exportRequired
true
ethz.rosetta.versionExported
true
ethz.COinS
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