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A prediction and behavioural analysis of machine learning methods for modelling travel mode choice
11 references·14 citing·40 second hop
A prediction and behavioural analysis of machine learning methods for modelling travel mode choice (2023)A prediction and behavioural analysis of …A systematic comparative evaluation of machine learning classifiers and discrete choice models for travel mode choice in the presence of response heterogeneity (2022)A systematic comparative eval…ResLogit: A residual neural network logit model for data-driven choice modelling (2021)ResLogit: A residual neural n…Prediction and behavioral analysis of travel mode choice: A comparison of machine learning and logit models (2020)Prediction and behavioral ana…A systematic review of machine learning classification methodologies for modelling passenger mode choice (2020)A systematic review of machin…Machine Learning Travel Mode Choices: Comparing the Performance of an Extreme Gradient Boosting Model with a Multinomial Logit Model (2018)Machine Learning Travel Mode …A comparative study of machine learning classifiers for modeling travel mode choice (2017)A comparative study of machin…Mode Choice Analysis Using Random Forrest Decision Trees (2016)Mode Choice Analysis Using Ra…Predicting Travel Mode of Individuals by Machine Learning (2015)Predicting Travel Mode of Ind…Evaluating multiple classifiers for stock price direction prediction (2015)Evaluating multiple classifie…BIOGEME: a free package for the estimation of discrete choice models (2003)BIOGEME: a free package for t…A comparison of the predictive potential of artificial neural networks and nested logit models for commuter mode choice (2000)A comparison of the predictiv…An integrated mutual-information clustering and deep neural network framework for forecasting travel behaviour under flexible working arrangements (2026)An integrated mutual-informat…Understanding travel behavior and mode choice prediction for university commuters: insights from discrete choice models and machine learning (2025)Understanding travel behavior…Shared e-bikes demand in urban mobility: Temporal heterogeneity, driving factors, and strategic implications (2025)Shared e-bikes demand in urba…Predicting active travel durations in Tehran: A multilayer perceptron approach (2025)Predicting active travel dura…Non-linear built environment effects on travel behavior resilience under extreme weather events (2025)Non-linear built environment …Machine learning in travel mode choice studies: A systematic literature review of applications, methods, and challenges (2025)Machine learning in travel mo…Investigating the factors influencing intercity travel mode choice in urban agglomerations: Insights from a three-phase framework (2025)Investigating the factors inf…Integrating Travel Survey and Amap API Data Into Travel Mode Choice Analysis With Interpretable Machine Learning Models: A Case Study in China (2025)Integrating Travel Survey and…Examining the Determinants on OD Metro Ridership: Insights from Machine Learning Approaches (2025)Examining the Determinants on…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 …A multi-task Transformer with mixture-of-experts for personalized periodic predictions of individual travel behavior in multimodal public transport (2025)A multi-task Transformer with…A machine learning approach to study the effect of parking pricing on transport mode choice to work using 2022 NHTS dataset (2025)A machine learning approach t…Discrete Choice Models and Artificial Intelligence Techniques for Predicting the Determinants of Transport Mode Choice—A Systematic Review (2024)Discrete Choice Models and Ar…THE INFLUENCE OF TRAVEL MODE CHOICE ON SUBJECTIVE WELL-BEING - A CASE STUDY (2023)THE INFLUENCE OF TRAVEL MODE …Work Travel Mode Choice Modeling with Data Mining: Decision Trees and Neural Networks (2003)Logistics Innovation and Social Sustainability: How to Prevent an Artificial Divide in Human–Computer Interaction (2019)Deep neural networks for choice analysis: Extracting complete economic information for interpretation (2020)Enhancing discrete choice models with representation learning (2020)Discrete Choice Analysis: Theory and Application to Travel Demand. 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this work references cited by second hop

References

  • 2003BIOGEME: a free package for the estimation of discrete choice models884 cited
  • 2015Evaluating multiple classifiers for stock price direction prediction597 cited
  • 2017A comparative study of machine learning classifiers for modeling travel mode choice423 cited
  • 2020Prediction and behavioral analysis of travel mode choice: A comparison of machine learning and logit models406 cited
  • 2018Machine Learning Travel Mode Choices: Comparing the Performance of an Extreme Gradient Boosting Model with a Multinomial Logit Model214 cited
  • 2000A comparison of the predictive potential of artificial neural networks and nested logit models for commuter mode choice182 cited
  • 2020A systematic review of machine learning classification methodologies for modelling passenger mode choice154 cited
  • 2015Predicting Travel Mode of Individuals by Machine Learning149 cited
  • 2022A systematic comparative evaluation of machine learning classifiers and discrete choice models for travel mode choice in the presence of response heterogeneity108 cited
  • 2016Mode Choice Analysis Using Random Forrest Decision Trees104 cited
  • 2021ResLogit: A residual neural network logit model for data-driven choice modelling85 cited

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  • 2025Non-linear built environment effects on travel behavior resilience under extreme weather events26 cited
  • 2025Investigating the factors influencing intercity travel mode choice in urban agglomerations: Insights from a three-phase framework

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20 cited
  • 2025A multi-task Transformer with mixture-of-experts for personalized periodic predictions of individual travel behavior in multimodal public transport14 cited
  • 2024Discrete Choice Models and Artificial Intelligence Techniques for Predicting the Determinants of Transport Mode Choice—A Systematic Review13 cited
  • 2025A New Breakthrough in Travel Behavior Modeling Using Deep Learning: A High-Accuracy Prediction Method Based on a CNN11 cited
  • 2025Shared e-bikes demand in urban mobility: Temporal heterogeneity, driving factors, and strategic implications10 cited
  • 2025Machine learning in travel mode choice studies: A systematic literature review of applications, methods, and challenges9 cited
  • 2025Predicting active travel durations in Tehran: A multilayer perceptron approach8 cited
  • 2025Integrating Travel Survey and Amap API Data Into Travel Mode Choice Analysis With Interpretable Machine Learning Models: A Case Study in China7 cited
  • 2026An integrated mutual-information clustering and deep neural network framework for forecasting travel behaviour under flexible working arrangements7 cited
  • 2023THE INFLUENCE OF TRAVEL MODE CHOICE ON SUBJECTIVE WELL-BEING - A CASE STUDY7 cited
  • 2025Examining the Determinants on OD Metro Ridership: Insights from Machine Learning Approaches6 cited
  • 2025Understanding travel behavior and mode choice prediction for university commuters: insights from discrete choice models and machine learning5 cited
  • 2025A machine learning approach to study the effect of parking pricing on transport mode choice to work using 2022 NHTS dataset5 cited