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Showing 1 to 7 of 7 for “"Travel Behavior Analysis"”.

  1. Cell phone location data for travel behavior analysis

    … digital traces when and where individuals travel, improving our ability to understand, model, and predict human mobility. Especially in this era of rapid urbanization, mobile phone data presents exciting new opportunities to plan transportation infrastructure and services that meet the …

    mit Repository record for Cell phone location data for travel behavior analysis (opens in a new tab)

  2. Travel Behavior Analysis and Mode Choice Prediction for Commuting to Campus - Performance Comparison of Discrete Choice and Machine Learning Models

    Extensive studies exist on various aspects of travel behaviour of the general population; however, few works explore the commuting behaviour of university commuters. This thesis investigates university commuters' commuting habits/attitudes to better understand their commuting behaviour and compares …

    calgary Repository record for Travel Behavior Analysis and Mode Choice Prediction for Commuting to Campus - Performance Comparison of Discrete Choice and Machine Learning Models (opens in a new tab)

  3. Preference accommodating and preference shaping : incorporating traveler preferences into transportation planning

    … the psychological factors that influence travel behavior such as people's personality traits, environmental attitudes, car pride and perceptions of convenience and comfort. Despite the recognition of the importance of these psychological factors in better understanding travel behavior, …

    mit Repository record for Preference accommodating and preference shaping : incorporating traveler preferences into transportation planning (opens in a new tab)

  4. Understanding transit travel behavior : value added by smart cards

    Travel behavior represents a particularly complex area of research in transportation given the interaction between transport supply characteristics and the user perceptions which guide his/her decisions. Thanks to the advent of automated data collection including smart cards, each customer …

    mit Repository record for Understanding transit travel behavior : value added by smart cards (opens in a new tab)

  5. Innovations in Urban Computing: Uncertainty Quantification, Data Fusion, and Generative Urban Design

    … the application of deep learning in urban system analysis has a lot of challenges. Within the vast and complex scope of urban computing combined with deep learning, this dissertation zooms in on three emerging issues: uncertainty quantification, data fusion, and generative urban design while …

    mit Repository record for Innovations in Urban Computing: Uncertainty Quantification, Data Fusion, and Generative Urban Design (opens in a new tab)

  6. Interrelationships Between Urban Travel and Other Infrastructure

    … electricity consumption as proxy indicators of travel demand. First, it shows that sentiment derived from geo-tagged Twitter posts can be structured into covariates that significantly improve forecasts of telecommuting prevalence, particularly during disruptive events such as the COVID-19 …

    uic