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Transportation Mode Detection by Using Smartphones and Smartwatches with Machine Learning
16 references·5 citing·53 second hopsampled
Transportation Mode Detection by Using Smartphones and Smartwatches with Machine Learning (2022)Transportation Mode Detection by Using Sm…Facing the needs for clean bicycle data – a bicycle-specific approach of GPS data processing (2021)Facing the needs for clean bi…Smartphone Data Classification Technique for Detecting the Usage of Public or Private Transportation Modes (2020)Smartphone Data Classificatio…Detecting travel modes from smartphone-based travel surveys with continuous hidden Markov models (2019)Detecting travel modes from s…Transport mode choice and body mass index: Cross-sectional and longitudinal evidence from a European-wide study (2018)Transport mode choice and bod…Applying a random forest method approach to model travel mode choice behavior (2018)Applying a random forest meth…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…A Novel Segment-Based Approach for Improving Classification Performance of Transport Mode Detection (2017)A Novel Segment-Based Approac…A comparative study of machine learning classifiers for modeling travel mode choice (2017)A comparative study of machin…Travel Mode Detection with Varying Smartphone Data Collection Frequencies (2016)Travel Mode Detection with Va…New walking and cycling infrastructure and modal shift in the UK: A quasi-experimental panel study (2016)New walking and cycling infra…Making pervasive sensing possible: Effective travel mode sensing based on smartphones (2016)Making pervasive sensing poss…Comparison of advanced imputation algorithms for detection of transportation mode and activity episode using GPS data (2016)Comparison of advanced imputa…Travel mode detection based on GPS track data and Bayesian networks (2015)Travel mode detection based o…Mode Choice for School Trips (2015)Mode Choice for School TripsDecision tree method for modeling travel mode switching in a dynamic behavioral process (2015)Decision tree method for mode…Machine learning in travel mode choice studies: A systematic literature review of applications, methods, and challenges (2025)Machine learning in travel mo…Social norms and perceptions of Saudis on active transportation (2024)Social norms and perceptions …Discrete Choice Models and Artificial Intelligence Techniques for Predicting the Determinants of Transport Mode Choice—A Systematic Review (2024)Discrete Choice Models and Ar…Smartphone-Based CO2e Emission Estimation Using Transportation Mode Classification (2023)Smartphone-Based CO2e Emissio…Application of machine learning to predict transport modes from GPS, accelerometer, and heart rate data (2022)Application of machine learni…MODELING THE CHOICE OF RESIDENTIAL LOCATION (1978)The New Zealand Medical Journal 1887-1987. 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(1979)Mail and Telephone Surveys: The Total Design Method. (1982)A systematic review of the effect of infrastructural interventions to promote cycling: strengthening causal inference from observational data (2019)Building back better: The COVID-19 pandemic and transport policy implications for a developing megacity (2021)Demand, Services and Social Aspects of Mitigation (2023)Conditional logit analysis of qualitative choice behavior (1972)Discrete Choice Analysis: Theory and Application to Travel Demand. (1987)Travel and the Built Environment (2010)Is your dataset big enough? Sample size requirements when using artificial neural networks for discrete choice analysis (2018)Prediction and behavioral analysis of travel mode choice: A comparison of machine learning and logit models (2020)Non-linear associations between built environment and active travel for working and shopping: An extreme gradient boosting approach (2021)Inferring High-Level Behavior from Low-Level Sensors (2003)Learning transportation mode from raw gps data for geographic applications on the web (2008)Inferring fine-grained transport modes from mobile phone cellular signaling data (2019)Travel Mode Identification With GPS Trajectories Using Wavelet Transform and Deep Learning (2020)A systematic comparative evaluation of machine learning classifiers and discrete choice models for travel mode choice in the presence of response heterogeneity (2022)DIRECT AND INVERSE SOLUTIONS OF GEODESICS ON THE ELLIPSOID WITH APPLICATION OF NESTED EQUATIONS (1975)Understanding mobility based on GPS data (2008)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)Effects of Age on Validity of Self-Reported Height, Weight, and Body Mass Index (2001)Obesity relationships with community design, physical activity, and time spent in cars (2004)Walking, Cycling, and Obesity Rates in Europe, North America, and Australia (2008)Dependence between travel distance, individual socioeconomic and health-related characteristics, and the choice of the travel mode: a cross-sectional study for Kaunas, Lithuania (2020)Equity and accessibility of cycling infrastructure: An analysis of Santiago de Chile (2021)Walking, cycling, and public transport for commuting and non-commuting travels across 5 European urban regions: Modal choice correlates and motivations (2021)On the measurement of inequality (1970)Built environments and mode choice: toward a normative framework (2002)The effects of attitudes and personality traits on mode choice (2005)Examining non-linear built environment effects on elderly’s walking: A random forest approach (2020)To walk or not to walk? Examining non-linear effects of streetscape greenery on walking propensity of older adults (2021)A Survey of Digital Map Processing Techniques (2014)Travel Mode Detection Based on GPS Raw Data Collected by Smartphones: A Systematic Review of the Existing Methodologies (2016)Smartphones as an integrated platform for monitoring driver behaviour: The role of sensor fusion and connectivity (2018)Transportation mode identification with GPS trajectory data and GIS information (2021)
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References

  • 2018Applying a random forest method approach to model travel mode choice behavior491 cited
  • 2017A comparative study of machine learning classifiers for modeling travel mode choice423 cited
  • 2017Inferring transportation modes from GPS trajectories using a convolutional neural network404 cited
  • 2015Travel mode detection based on GPS track data and Bayesian networks154 cited
  • 2016New walking and cycling infrastructure and modal shift in the UK: A quasi-experimental panel study119 cited
  • 2017Travel Mode Detection Using GPS Data and Socioeconomic Attributes Based on a Random Forest Classifier114 cited
  • 2018Transport mode choice and body mass index: Cross-sectional and longitudinal evidence from a European-wide study86 cited
  • 2016Comparison of advanced imputation algorithms for detection of transportation mode and activity episode using GPS data83 cited
  • 2016Travel Mode Detection with Varying Smartphone Data Collection Frequencies77 cited
  • 2015Mode Choice for School Trips54 cited
  • 2016Making pervasive sensing possible: Effective travel mode sensing based on smartphones51 cited
  • 2015Decision tree method for modeling travel mode switching in a dynamic behavioral process49 cited
  • 2017A Novel Segment-Based Approach for Improving Classification Performance of Transport Mode Detection38 cited
  • 2019Detecting travel modes from smartphone-based travel surveys with continuous hidden Markov models

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36 cited
  • 2021Facing the needs for clean bicycle data – a bicycle-specific approach of GPS data processing34 cited
  • 2020Smartphone Data Classification Technique for Detecting the Usage of Public or Private Transportation Modes33 cited
  • Cited by

    • 2024Discrete Choice Models and Artificial Intelligence Techniques for Predicting the Determinants of Transport Mode Choice—A Systematic Review13 cited
    • 2022Application of machine learning to predict transport modes from GPS, accelerometer, and heart rate data12 cited
    • 2023Smartphone-Based CO2e Emission Estimation Using Transportation Mode Classification10 cited
    • 2025Machine learning in travel mode choice studies: A systematic literature review of applications, methods, and challenges9 cited
    • 2024Social norms and perceptions of Saudis on active transportation8 cited