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Inferring spatial–temporal attributes of vehicle itinerary with Automatic Vehicle Identification data: Methodology and application
16 references·0 citing·38 second hop
Inferring spatial–temporal attributes of vehicle itinerary with Automatic Vehicle Identification data: Methodology and application (2024)Inferring spatial–temporal attributes of …Understanding temporal and spatial patterns of urban activities across demographic groups through geotagged social media data (2023)Understanding temporal and sp…Analytics of location-based big data for smart cities: Opportunities, challenges, and future directions (2021)Analytics of location-based b…Individual mobility prediction using transit smart card data (2018)Individual mobility predictio…A Generative Model of Urban Activities from Cellular Data (2017)A Generative Model of Urban A…Discovering urban activity patterns in cell phone data (2015)Discovering urban activity pa…A Bayesian approach to detect pedestrian destination-sequences from WiFi signatures (2014)A Bayesian approach to detect…Summary of Travel Trends: 2009 National Household Travel Survey (2011)Summary of Travel Trends: 200…A GPS/GIS method for travel mode detection in New York City (2011)A GPS/GIS method for travel m…Processing Raw Data from Global Positioning Systems without Additional Information (2009)Processing Raw Data from Glob…Proceedings of the 16th ACM SIGSPATIAL international conference on Advances in geographic information systems (2008)Proceedings of the 16th ACM S…Learning and inferring transportation routines (2007)Learning and inferring transp…Discovering personally meaningful places (2007)Discovering personally meanin…Eighty Weeks of Global Positioning System Traces: Approaches to Enriching Trip Information (2004)Eighty Weeks of Global Positi…Elimination of the Travel Diary: Experiment to Derive Trip Purpose from Global Positioning System Travel Data (2001)Elimination of the Travel Dia…Generation of Synthetic Daily Activity-Travel Patterns (1997)Generation of Synthetic Daily…The Use of Disaggregate Choice Models in Semi-Markov Process Models of Trip Chaining Behavior (1979)The Use of Disaggregate Choic…WHAT ABOUT PEOPLE IN REGIONAL SCIENCE? (1970)Understanding individual human mobility patterns (2008)Modelling the scaling properties of human mobility (2010)Algorithmic Geographies: Big Data, Algorithmic Uncertainty, and the Production of Geographic Knowledge (2016)Transport mode detection based on mobile phone network data: A systematic review (2019)Household travel surveys: Where are we going? 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(2014)Understanding aggregate human mobility patterns using passive mobile phone location data: a home-based approach (2015)Big Data Driven Hidden Markov Model Based Individual Mobility Prediction at Points of Interest (2016)Limits of Predictability in Human Mobility (2010)Friendship and mobility (2011)Transport modelling in the age of big data (2017)Learning to Simulate Human Mobility (2020)Rethinking Behaviors and Activities of Base Stations in Mobile Cellular Networks Based on Big Data Analysis (2020)Speech and language processing (2010)Emerging Big Data Sources for Public Transport Planning: A Systematic Review on Current State of Art and Future Research Directions (2019)A hierarchical temporal attention-based LSTM encoder-decoder model for individual mobility prediction (2020)Discovering latent activity patterns from transit smart card data: A spatiotemporal topic model (2020)Tracking tourists in the digital age (2007)Using Mobile Positioning Data to Model Locations Meaningful to Users of Mobile Phones (2010)Applying mobile phone data to travel behaviour research: A literature review (2017)Route choice modeling with network-free data (2007)The Minimum Circuity Frontier and the Journey to Work (2009)Latent variables and route choice behavior (2011)Understanding Transport Demands and Elasticities: How Prices and Other Factors Affect Travel Behavior (2012)The influence of built environment on travel behavior of the elderly in urban China (2016)The decline in active school transportation (AST): A systematic review of the factors related to AST and changes in school transport over time in North America (2017)
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References

  • 2007Learning and inferring transportation routines798 cited
  • 2011Summary of Travel Trends: 2009 National Household Travel Survey550 cited
  • 2001Elimination of the Travel Diary: Experiment to Derive Trip Purpose from Global Positioning System Travel Data394 cited
  • 2009Processing Raw Data from Global Positioning Systems without Additional Information326 cited
  • 2011A GPS/GIS method for travel mode detection in New York City293 cited
  • 2015Discovering urban activity patterns in cell phone data236 cited
  • 2007Discovering personally meaningful places207 cited
  • 2017A Generative Model of Urban Activities from Cellular Data185 cited
  • 2004Eighty Weeks of Global Positioning System Traces: Approaches to Enriching Trip Information141 cited
  • 2018Individual mobility prediction using transit smart card data140 cited
  • 2021Analytics of location-based big data for smart cities: Opportunities, challenges, and future directions135 cited
  • 2008Proceedings of the 16th ACM SIGSPATIAL international conference on Advances in geographic information systems131 cited
  • 1997Generation of Synthetic Daily Activity-Travel Patterns91 cited
  • 1979The Use of Disaggregate Choice Models in Semi-Markov Process Models of Trip Chaining Behavior83 cited

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2014
A Bayesian approach to detect pedestrian destination-sequences from WiFi signatures
81 cited
  • 2023Understanding temporal and spatial patterns of urban activities across demographic groups through geotagged social media data79 cited
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