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When is big data big enough? Implications of using GPS-based surveys for travel demand analysis
16 references·16 citing·44 second hopsampled
When is big data big enough? Implications of using GPS-based surveys for travel demand analysis (2015)When is big data big enough? Implications…Urban activity pattern classification using topic models from online geo-location data (2014)Urban activity pattern classi…Review of GPS Travel Survey and GPS Data-Processing Methods (2014)Review of GPS Travel Survey a…Transportation mode recognition using GPS and accelerometer data (2013)Transportation mode recogniti…Inferring hybrid transportation modes from sparse GPS data using a moving window SVM classification (2012)Inferring hybrid transportati…Transportation mode detection using mobile phones and GIS information (2011)Transportation mode detection…Understanding transportation modes based on GPS data for web applications (2010)Understanding transportation …Deriving and validating trip purposes and travel modes for multi-day GPS-based travel surveys: A large-scale application in the Netherlands (2009)Deriving and validating trip …Modeling the structural relationships among short-distance travel amounts, perceptions, affections, and desires (2008)Modeling the structural relat…Search for a global positioning system device to measure person travel (2007)Search for a global positioni…Latent lifestyle preferences and household location decisions (2006)Latent lifestyle preferences …Comparative Analysis of Global Positioning System-Based and Travel Survey-Based Data (2006)Comparative Analysis of Globa…Impact of Underreporting on Mileage and Travel Time Estimates: Results from Global Positioning System-Enhanced Household Travel Survey (2003)Impact of Underreporting on M…Integration of Choice and Latent Variable Models (2002)Integration of Choice and Lat…Elimination of the Travel Diary: Experiment to Derive Trip Purpose from Global Positioning System Travel Data (2001)Elimination of the Travel Dia…Economic Choices (2001)Economic ChoicesBehavioural theories of dispersion and the mis-specification of travel demand models (1982)Behavioural theories of dispe…Urban Mobility Pattern Detection: Development of a Classification Algorithm Based on Machine Learning and GPS (2024)Urban Mobility Pattern Detect…Deriving transport appraisal values from emerging revealed preference data (2022)Deriving transport appraisal …Transport behavior-mining from smartphones: a review (2021)Transport behavior-mining fro…Review of Transit Data Sources: Potentials, Challenges and Complementarity (2021)Review of Transit Data Source…Applying frequent-pattern mining and time geography to impute gaps in smartphone-based human-movement data (2021)Applying frequent-pattern min…Mitigating Bias in Big Data for Transportation (2020)Mitigating Bias in Big Data f…Travel mode imputation using GPS and accelerometer data from a multi-day travel survey (2019)Travel mode imputation using …A correlation analysis of information use, social networks and cooperation consciousness in travel behaviors (2019)A correlation analysis of inf…A bi-partite generative model framework for analyzing and simulating large scale multiple discrete-continuous travel behaviour data (2019)A bi-partite generative model…Trip chain extraction using smartphone-collected trajectory data (2017)Trip chain extraction using s…Spatial context mining approach for transport mode recognition from mobile sensed big data (2017)Spatial context mining approa…Open PFLOW: Creation and evaluation of an open dataset for typical people mass movement in urban areas (2017)Open PFLOW: Creation and eval…Extracting regular mobility patterns from sparse CDR data without a priori assumptions (2017)Extracting regular mobility p…Air Transport versus High-Speed Rail: An Overview and Research Agenda (2017)Air Transport versus High-Spe…Crowdsourcing mobility insights – Reflection of attitude based segments on high resolution mobility behaviour data (2016)Crowdsourcing mobility insigh…BIG DATA IN CIVIL ENGINEERING: A STATE-OF-THE-ART SURVEY (2016)BIG DATA IN CIVIL ENGINEERING…Can Land-use Policy Really Affect Travel Behaviour? A Study of the Link between Non-work Travel and Land-use Characteristics (1998)GPS tracking in neighborhood and health studies: A step forward for environmental exposure assessment, a step backward for causal inference? (2013)The promises of big data and small data for travel behavior (aka human mobility) analysis (2016)Friendship and mobility (2011)Discovering themes and trends in transportation research using topic modeling (2017)Social-media data for urban sustainability (2018)Applications of artificial intelligence for disaster management (2020)Exploring Millions of Footprints in Location Sharing Services (2021)Predicting Depression via Social Media (2021)Learning and inferring transportation routines (2007)Learning transportation mode from raw gps data for geographic applications on the web (2008)Understanding mobility based on GPS data (2008)Applying mobile phone data to travel behaviour research: A literature review (2017)Inferring transportation modes from GPS trajectories using a convolutional neural network (2017)Using GPS to learn significant locations and predict movement across multiple users (2003)Transportation mode inference from anonymized and aggregated mobile phone call detail records (2010)What We Know and Don't Know about Online Word-of-Mouth: A Review and Synthesis of the Literature (2014)Analysis of human mobility patterns from GPS trajectories and contextual information (2015)Where do cyclists ride? A route choice model developed with revealed preference GPS data (2012)Big Data and Cycling (2015)Transport mode detection based on mobile phone network data: A systematic review (2019)Stated choice methods analysis and applications (2000)Stated Choice Methods (2000)Discrete Choice Methods with Simulation (2003)Self‐Selection: A Key to a Better Understanding of Location Choices, Travel Behaviour and Transport Externalities? (2009)Neighborhood satisfaction in suburban versus traditional environments: An evaluation of contributing characteristics in eight California neighborhoods (2010)Incorporating the influence of latent modal preferences on travel mode choice behavior (2013)Discrete Choice Analysis: Theory and Application to Travel Demand. (1987)Structural Equations with Latent Variables. (1991)Psychology and Economics (1997)A non-compensatory choice model incorporating attribute cutoffs (2001)Extended discrete choice models : integrated framework, flexible error structures, and latent variables (2001)How, when and why integrated choice and latent variable models are latently useful (2016)A New Approach to Consumer Theory (1966)Judgment under Uncertainty: Heuristics and Biases (1974)Choices, values, and frames. (1984)Hybrid Choice Models: Progress and Challenges (2002)Food Values (2008)The impact of personal dispositions on information sensitivity, privacy concern and trust in disclosing health information online (2010)Evaluating the feasibility of a passive travel survey collection in a complex urban environment: Lessons learned from the New York City case study (2010)Using Geographic Information Systems (GIS) to assess the role of the built environment in influencing obesity: a glossary (2011)Transportation mode-based segmentation and classification of movement trajectories (2012)Tracking tourists in the digital age (2007)Using Mobile Positioning Data to Model Locations Meaningful to Users of Mobile Phones (2010)
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References

  • 2001Economic Choices1,052 cited
  • 2002Integration of Choice and Latent Variable Models511 cited
  • 2009Deriving and validating trip purposes and travel modes for multi-day GPS-based travel surveys: A large-scale application in the Netherlands501 cited
  • 2010Understanding transportation modes based on GPS data for web applications485 cited
  • 2011Transportation mode detection using mobile phones and GIS information451 cited
  • 2001Elimination of the Travel Diary: Experiment to Derive Trip Purpose from Global Positioning System Travel Data394 cited
  • 2014Review of GPS Travel Survey and GPS Data-Processing Methods350 cited
  • 2006Latent lifestyle preferences and household location decisions331 cited
  • 2014Urban activity pattern classification using topic models from online geo-location data289 cited
  • 2007Search for a global positioning system device to measure person travel246 cited
  • 2013Transportation mode recognition using GPS and accelerometer data235 cited
  • 1982Behavioural theories of dispersion and the mis-specification of travel demand models222 cited
  • 2012Inferring hybrid transportation modes from sparse GPS data using a moving window SVM classification191 cited
  • 2003Impact of Underreporting on Mileage and Travel Time Estimates: Results from Global Positioning System-Enhanced Household Travel Survey

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178 cited
  • 2006Comparative Analysis of Global Positioning System-Based and Travel Survey-Based Data144 cited
  • 2008Modeling the structural relationships among short-distance travel amounts, perceptions, affections, and desires87 cited
  • Cited by

    • 2017Air Transport versus High-Speed Rail: An Overview and Research Agenda82 cited
    • 2017Spatial context mining approach for transport mode recognition from mobile sensed big data61 cited
    • 2021Review of Transit Data Sources: Potentials, Challenges and Complementarity56 cited
    • 2020Mitigating Bias in Big Data for Transportation42 cited
    • 2017Open PFLOW: Creation and evaluation of an open dataset for typical people mass movement in urban areas40 cited
    • 2019A bi-partite generative model framework for analyzing and simulating large scale multiple discrete-continuous travel behaviour data33 cited
    • 2016Crowdsourcing mobility insights – Reflection of attitude based segments on high resolution mobility behaviour data31 cited
    • 2019Travel mode imputation using GPS and accelerometer data from a multi-day travel survey27 cited
    • 2024Urban Mobility Pattern Detection: Development of a Classification Algorithm Based on Machine Learning and GPS25 cited
    • 2021Transport behavior-mining from smartphones: a review22 cited
    • 2019A correlation analysis of information use, social networks and cooperation consciousness in travel behaviors21 cited
    • 2021Applying frequent-pattern mining and time geography to impute gaps in smartphone-based human-movement data20 cited
    • 2017Extracting regular mobility patterns from sparse CDR data without a priori assumptions20 cited
    • 2016BIG DATA IN CIVIL ENGINEERING: A STATE-OF-THE-ART SURVEY20 cited
    • 2022Deriving transport appraisal values from emerging revealed preference data19 cited
    • 2017Trip chain extraction using smartphone-collected trajectory data19 cited