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Travel mode detection based on GPS track data and Bayesian networks · Study

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ArticleTravel mode detection based on GPS track data and Bayesian networks

Guangnian Xiao2015

Article2015

Travel mode detection based on GPS track data and Bayesian networks

Guangnian Xiao · Zhicai Juan · Chunqin Zhang

154 citations·0/0 files stored·Computers Environment and Urban Systems

No readable copy stored yet — this record is metadata only.

Human Mobility and Location-Based Analysis Transportation Planning and Optimization Urban Transport and Accessibility

Abstract

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Citations in this library

Stored only when both papers are in the corpus — 154 citations exist upstream.

References

1972Conditional logit analysis of qualitative choice behavior 2014A Survey of Digital Map Processing Techniques 2009Deriving and validating trip purposes and travel modes for multi-day GPS-based travel surveys: A large-scale application in the Netherlands 2010Understanding transportation modes based on GPS data for web applications 2014Review of GPS Travel Survey and GPS Data-Processing Methods 2012Understanding intra-urban trip patterns from taxi trajectory data 2009Processing Raw Data from Global Positioning Systems without Additional Information 2011A GPS/GIS method for travel mode detection in New York City

Cited by

2016Travel Mode Detection Based on GPS Raw Data Collected by Smartphones: A Systematic Review of the Existing Methodologies 2021Transportation mode identification with GPS trajectory data and GIS information 2018Smartphones as an integrated platform for monitoring driver behaviour: The role of sensor fusion and connectivity 2017Who you are is how you travel: A framework for transportation mode detection using individual and environmental characteristics 2016Mapping Dynamic Urban Land Use Patterns with Crowdsourced Geo-Tagged Social Media (Sina-Weibo) and Commercial Points of Interest Collections in Beijing, China 2021Review and evaluation of methods in transport mode detection based on GPS tracking data 2017Spatial context mining approach for transport mode recognition from mobile sensed big data 2018Automatic Trip Detection with the Dutch Mobile Mobility Panel: Towards Reliable Multiple-Week Trip Registration for Large Samples

Details

Year2015

Typearticle

Published2015-06-15

VenueComputers Environment and Urban Systems

ISSN-L0198-9715

Languageen

Citations154

Files0 public / 0

ShelfHuman Mobility and Location-Based Analysis

Identifiers

doi10.1016/j.compenvurbsys.2015.05.005

openalex_workW616026467

Links

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