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Mobility Collector
7 references·8 citing·40 second hop
Mobility Collector (2014)Mobility CollectorTransportation mode detection using mobile phones and GIS information (2011)Transportation mode detection…Learning transportation mode from raw gps data for geographic applications on the web (2008)Learning transportation mode …Deducing mode and purpose from GPS data (2008)Deducing mode and purpose fro…Using Global Positioning System Data to Understand Day-to-Day Dynamics of Morning Commute Behavior (2004)Using Global Positioning Syst…Learning significant locations and predicting user movement with GPS (2003)Learning significant location…Impact of Underreporting on Mileage and Travel Time Estimates: Results from Global Positioning System-Enhanced Household Travel Survey (2003)Impact of Underreporting on M…Elimination of the Travel Diary: Experiment to Derive Trip Purpose from Global Positioning System Travel Data (2001)Elimination of the Travel Dia…A novel one-stage approach for pointwise transportation mode identification inspired by point cloud processing (2023)A novel one-stage approach fo…Classification of users’ transportation modalities from mobiles in real operating conditions (2021)Classification of users’ tran…Workshop Synthesis: New developments in travel diary collection systems based on smartphones and GPS receivers (2018)Workshop Synthesis: New devel…Intrapersonal mode choice variation: Evidence from a four-week smartphone-based travel survey in the Netherlands (2018)Intrapersonal mode choice var…Exploring waiting times in public transport through a semi-automated dedicated smartphone app survey (2018)Exploring waiting times in pu…A series of three case studies on the semi-automation of activity travel diary generation using smarpthones (2017)A series of three case studie…Workshop Synthesis: Conducting Travel Surveys using Portable Devices - Role of Technology in Travel Surveys (2015)Workshop Synthesis: Conductin…Comparative framework for activity-travel diary collection systems (2015)Comparative framework for act…Understanding mobility based on GPS data (2008)Deriving and validating trip purposes and travel modes for multi-day GPS-based travel surveys: A large-scale application in the Netherlands (2009)Activity-based model for medium-sized cities considering external activity–travel: Enhancing FEATHERS framework (2019)Trip Chaining Model with Classification and Optimization Parameters (2020)Learning and inferring transportation routines (2007)Review of GPS Travel Survey and GPS Data-Processing Methods (2014)Applying mobile phone data to travel behaviour research: A literature review (2017)Inferring transportation modes from GPS trajectories using a convolutional neural network (2017)An examination of the determinants of day-to-day variability in individuals' urban travel behavior (1986)Classification issues in the analysis of complex travel behavior (1986)Understanding travel behaviour in an era of change (1997)Review and Synthesis of Road-Use Metering and Charging Systems (2005)Value of Reliability: High Occupancy Toll Lanes, General Purpose Lanes, and Arterials (2010)An Analysis of Commuting Distance and Job Accessibility for Residents in a U.S. Legacy City (2019)Inferring High-Level Behavior from Low-Level Sensors (2003)Using GPS to learn significant locations and predict movement across multiple users (2003)Understanding transportation modes based on GPS data for web applications (2010)The Museum Wearable: real-time sensor-driven understanding of visitors' interests for personalized visually-augmented museum experiences (2002)Discovering personally meaningful places (2007)Analysis of human mobility patterns from GPS trajectories and contextual information (2015)A survey on deep learning for human mobility (2023)Observing the rhythms of daily life: A six-week travel diary (2002)The Mixed Logit model: The state of practice (2003)Mobile Technology and Studies on Transport Behavior: A Literature Analysis, Integrated Research Model, and Future Research Agenda (2021)The influence of panel effects and inertia on travel cost elasticities for car use and public transport (2021)The role of coordination costs in mode choice decisions: A case study of German cities (2021)DIRECT AND INVERSE SOLUTIONS OF GEODESICS ON THE ELLIPSOID WITH APPLICATION OF NESTED EQUATIONS (1975)A Deep Semi-Supervised Machine Learning Algorithm for Detecting Transportation Modes Based on Gps Tracking Data (2022)From biases to opportunities: leveraging Location-Based-Service (LBS) data for next-generation transportation planning (2025)UPTM-LLM: Large language models-powered urban pedestrian travel modes recognition for intelligent transportation system (2025)Global Positioning System as Data Collection Method for Travel Research (2000)Applications of New Technologies in Travel Surveys (2006)Reducing Burden and Sample Sizes in Multiday Household Travel Surveys (2008)Improved methods to deduct trip legs and mode from travel surveys using wearable GPS devices: A case study from the Greater Copenhagen area (2015)Online Travel Mode Identification Using Smartphones With Battery Saving Considerations (2016)Tracking tourists in the digital age (2007)Using Mobile Positioning Data to Model Locations Meaningful to Users of Mobile Phones (2010)Exploring the route choice decision-making process: A comparison of planned and observed routes obtained using person-based GPS (2009)Health Impacts of the Built Environment: Within-Urban Variability in Physical Inactivity, Air Pollution, and Ischemic Heart Disease Mortality (2011)To what extent do e-bikes substitute travel by other modes? Evidence from the Netherlands (2017)
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References

  • 2008Learning transportation mode from raw gps data for geographic applications on the web616 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
  • 2003Learning significant locations and predicting user movement with GPS334 cited
  • 2003Impact of Underreporting on Mileage and Travel Time Estimates: Results from Global Positioning System-Enhanced Household Travel Survey178 cited
  • 2008Deducing mode and purpose from GPS data75 cited
  • 2004Using Global Positioning System Data to Understand Day-to-Day Dynamics of Morning Commute Behavior38 cited

Cited by

  • 2015Comparative framework for activity-travel diary collection systems26 cited
  • 2018Intrapersonal mode choice variation: Evidence from a four-week smartphone-based travel survey in the Netherlands24 cited
  • 2023A novel one-stage approach for pointwise transportation mode identification inspired by point cloud processing22 cited
  • 2018Exploring waiting times in public transport through a semi-automated dedicated smartphone app survey16 cited
  • 2018Workshop Synthesis: New developments in travel diary collection systems based on smartphones and GPS receivers16 cited
  • 2021Classification of users’ transportation modalities from mobiles in real operating conditions

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13 cited
  • 2015Workshop Synthesis: Conducting Travel Surveys using Portable Devices - Role of Technology in Travel Surveys7 cited
  • 2017A series of three case studies on the semi-automation of activity travel diary generation using smarpthones3 cited