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Travel Mode Identification With GPS Trajectories Using Wavelet Transform and Deep Learning
11 references·16 citing·36 second hop
Travel Mode Identification With GPS Trajectories Using Wavelet Transform and Deep Learning (2020)Travel Mode Identification With GPS Traje…Travel Mode Detection Using GPS Data and Socioeconomic Attributes Based on a Random Forest Classifier (2017)Travel Mode Detection Using G…Inferring transportation modes from GPS trajectories using a convolutional neural network (2017)Inferring transportation mode…Travel Mode Detection Based on GPS Raw Data Collected by Smartphones: A Systematic Review of the Existing Methodologies (2016)Travel Mode Detection Based o…Transportation mode detection – an in-depth review of applicability and reliability (2016)Transportation mode detection…Travel mode choice and transit route choice behavior in Montreal: insights from McGill University members commute patterns (2012)Travel mode choice and transi…Automating mode detection for travel behaviour analysis by using global positioning systems-enabled mobile phones and neural networks (2010)Automating mode detection for…Understanding mobility based on GPS data (2008)Understanding mobility based …Learning transportation mode from raw gps data for geographic applications on the web (2008)Learning transportation mode …Travel mode choice: affected by objective or subjective determinants? (2007)Travel mode choice: affected …Toward the design of intelligent traveler information systems (1998)Toward the design of intellig…DIRECT AND INVERSE SOLUTIONS OF GEODESICS ON THE ELLIPSOID WITH APPLICATION OF NESTED EQUATIONS (1975)DIRECT AND INVERSE SOLUTIONS …UPTM-LLM: Large language models-powered urban pedestrian travel modes recognition for intelligent transportation system (2025)UPTM-LLM: Large language mode…A New Breakthrough in Travel Behavior Modeling Using Deep Learning: A High-Accuracy Prediction Method Based on a CNN (2025)A New Breakthrough in Travel …Travel Mode Identification for Non-Uniform Passive Mobile Phone Data (2024)Travel Mode Identification fo…Transportation Mode Detection Technology to Predict Wheelchair Users' Life Satisfaction in Seoul, South Korea (2024)Transportation Mode Detection…Activity-travel pattern inference based on multi-source big data (2024)Activity-travel pattern infer…A multi-scale attributes fusion model for travel mode identification using GPS trajectories (2024)A multi-scale attributes fusi…Revealing Senior Mobility Patterns and Activities in Urban Transit Systems (2023)Revealing Senior Mobility Pat…A novel one-stage approach for pointwise transportation mode identification inspired by point cloud processing (2023)A novel one-stage approach fo…A Framework of Travel Mode Identification Fusing Deep Learning and Map-Matching Algorithm (2023)A Framework of Travel Mode Id…Travel mode classification based on GNSS trajectories and open geospatial data (2022)Travel mode classification ba…Trajectory-as-A-Sequence: A Novel Travel Mode Identification Framework (2022)Trajectory-as-A-Sequence: A N…The Smartphone-Based Person Travel Survey System: Data Collection, Trip Extraction, and Travel Mode Detection (2022)The Smartphone-Based Person T…GeoSDVA: A Semi-Supervised Dirichlet Variational Autoencoder Model for Transportation Mode Identification (2022)GeoSDVA: A Semi-Supervised Di…Using genetic programming on GPS trajectories for travel mode detection (2021)Using genetic programming on …Improving Transportation Mode Identification with Limited GPS Trajectories (2021)Improving Transportation Mode…Semi-supervised deep ensemble learning for travel mode identification (2020)Semi-supervised deep ensemble…Route Choice: Wayfinding in Transport Networks (1990)Dynamic network models and driver information systems (1991)Commuters route choice behaviour (2006)The Impact of Travel Time Information on Travelers’ Learning under Uncertainty (2006)Algorithms for Itinerary Planning in Multimodal Transportation Networks (2008)Quasi-random maximum simulated likelihood estimation of the mixed multinomial logit model (2001)A Comparison of Web and Mail Survey Response Rates (2004)The Economics of Urban Transportation (2007)Multimodal route choice models of public transport passengers in the Greater Copenhagen Area (2014)Exploring factors associated with commute mode choice: An application of city-level general social survey data (2018)A systematic comparative evaluation of machine learning classifiers and discrete choice models for travel mode choice in the presence of response heterogeneity (2022)The consequences of modernity (1990)The theory of planned behavior (1991)Measuring Attitudes in Research on Residential Self‐Selection and Travel Behaviour: A Review of Theories and Empirical Research (2009)Urban form and travel behavior: experience from a Nordic context (2012)Linking modal choice to motility: A comprehensive review (2013)Distinction: A Social Critique of the Judgement of Taste* (2018)Can using global positioning system (GPS) improve trip reporting? (1999)Inferring fine-grained transport modes from mobile phone cellular signaling data (2019)Using GPS to learn significant locations and predict movement across multiple users (2003)Learning and inferring transportation routines (2007)Next place prediction using mobility Markov chains (2012)Understanding Human Mobility from Twitter (2015)Human mobility: Models and applications (2018)Inferring High-Level Behavior from Low-Level Sensors (2003)Understanding transportation modes based on GPS data for web applications (2010)Transportation mode detection using mobile phones and GIS information (2011)WHAT ABOUT PEOPLE IN REGIONAL SCIENCE? (1970)OpenStreetMap: User-Generated Street Maps (2008)Emerging data for pedestrian and bicycle monitoring: Sources and applications (2020)Deriving and validating trip purposes and travel modes for multi-day GPS-based travel surveys: A large-scale application in the Netherlands (2009)The impact of supply chain structure on the use of supplier socially responsible practices (2010)Algorithms for geodesics (2012)The station-free sharing bike demand forecasting with a deep learning approach and large-scale datasets (2018)Semi-Supervised Deep Learning Approach for Transportation Mode Identification Using GPS Trajectory Data (2019)Transport mode detection based on mobile phone network data: A systematic review (2019)
this work references cited by second hop

References

  • 1975DIRECT AND INVERSE SOLUTIONS OF GEODESICS ON THE ELLIPSOID WITH APPLICATION OF NESTED EQUATIONS1,276 cited
  • 2008Understanding mobility based on GPS data1,131 cited
  • 2008Learning transportation mode from raw gps data for geographic applications on the web616 cited
  • 2017Inferring transportation modes from GPS trajectories using a convolutional neural network404 cited
  • 2007Travel mode choice: affected by objective or subjective determinants?340 cited
  • 1998Toward the design of intelligent traveler information systems207 cited
  • 2010Automating mode detection for travel behaviour analysis by using global positioning systems-enabled mobile phones and neural networks136 cited
  • 2012Travel mode choice and transit route choice behavior in Montreal: insights from McGill University members commute patterns120 cited
  • 2017Travel Mode Detection Using GPS Data and Socioeconomic Attributes Based on a Random Forest Classifier114 cited
  • 2016Transportation mode detection – an in-depth review of applicability and reliability97 cited
  • 2016Travel Mode Detection Based on GPS Raw Data Collected by Smartphones: A Systematic Review of the Existing Methodologies89 cited

Cited by

  • 2020Semi-supervised deep ensemble learning for travel mode identification69 cited
  • 2022Trajectory-as-A-Sequence: A Novel Travel Mode Identification Framework44 cited

Only edges whose both ends are imported exist here. Widen the year window, or show the whole map. Back to the work

  • 2023A Framework of Travel Mode Identification Fusing Deep Learning and Map-Matching Algorithm28 cited
  • 2024Activity-travel pattern inference based on multi-source big data23 cited
  • 2023A novel one-stage approach for pointwise transportation mode identification inspired by point cloud processing22 cited
  • 2022The Smartphone-Based Person Travel Survey System: Data Collection, Trip Extraction, and Travel Mode Detection17 cited
  • 2021Improving Transportation Mode Identification with Limited GPS Trajectories15 cited
  • 2021Using genetic programming on GPS trajectories for travel mode detection14 cited
  • 2022Travel mode classification based on GNSS trajectories and open geospatial data12 cited
  • 2025A New Breakthrough in Travel Behavior Modeling Using Deep Learning: A High-Accuracy Prediction Method Based on a CNN11 cited
  • 2024A multi-scale attributes fusion model for travel mode identification using GPS trajectories10 cited
  • 2025UPTM-LLM: Large language models-powered urban pedestrian travel modes recognition for intelligent transportation system10 cited
  • 2022GeoSDVA: A Semi-Supervised Dirichlet Variational Autoencoder Model for Transportation Mode Identification9 cited
  • 2023Revealing Senior Mobility Patterns and Activities in Urban Transit Systems9 cited
  • 2024Travel Mode Identification for Non-Uniform Passive Mobile Phone Data8 cited
  • 2024Transportation Mode Detection Technology to Predict Wheelchair Users' Life Satisfaction in Seoul, South Korea7 cited