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Using App Usage Data From Mobile Devices to Improve Activity-Based Travel Demand Models
16 references·1 citing·40 second hopsampled
Using App Usage Data From Mobile Devices to Improve Activity-Based Travel Demand Models (2024)Using App Usage Data From Mobile Devices …Mobile phone records to feed activity-based travel demand models: MATSim for studying a cordon toll policy in Barcelona (2019)Mobile phone records to feed …Population dynamics based on mobile phone data to improve air pollution exposure assessments (2018)Population dynamics based on …A Generative Model of Urban Activities from Cellular Data (2017)A Generative Model of Urban A…The promises of big data and small data for travel behavior (aka human mobility) analysis (2016)The promises of big data and …Activity-Based Human Mobility Patterns Inferred from Mobile Phone Data: A Case Study of Singapore (2016)Activity-Based Human Mobility…Uncovering the spatial structure of mobility networks (2015)Uncovering the spatial struct…Origin–destination trips by purpose and time of day inferred from mobile phone data (2015)Origin–destination trips by p…Inferring Unusual Crowd Events from Mobile Phone Call Detail Records (2015)Inferring Unusual Crowd Event…Comparing and modelling land use organization in cities (2015)Comparing and modelling land …From mobile phone data to the spatial structure of cities (2014)From mobile phone data to the…Estimating human trajectories and hotspots through mobile phone data (2014)Estimating human trajectories…Dynamic population mapping using mobile phone data (2014)Dynamic population mapping us…Development of origin–destination matrices using mobile phone call data (2014)Development of origin–destina…The use of Bluetooth for analysing spatiotemporal dynamics of human movement at mass events: A case study of the Ghent Festivities (2011)The use of Bluetooth for anal…Social Event Detection in Massive Mobile Phone Data Using Probabilistic Location Inference (2011)Social Event Detection in Mas…A Tale of One City: Using Cellular Network Data for Urban Planning (2011)A Tale of One City: Using Cel…Determination of Urban Traveling Patterns With High Spatial and Temporal Resolution by Using GPS Cell Phone Data (2024)Determination of Urban Travel…Modelling Transport (2011)A Tale of Many Cities: Universal Patterns in Human Urban Mobility (2012)Unravelling daily human mobility motifs (2013)Understanding individual routing behaviour (2016)The Social Integration of American Cities: Network Measures of Connectedness Based on Everyday Mobility Across Neighborhoods (2019)The statistical physics of cities (2019)WHAT ABOUT PEOPLE IN REGIONAL SCIENCE? (1970)What about people in Regional Science? (1970)Understanding individual human mobility patterns (2008)Data from mobile phone operators: A tool for smarter cities? (2014)Traffic zone division based on big data from mobile phone base stations (2015)Urban magnetism through the lens of geo-tagged photography (2015)Mobile Landscapes: Using Location Data from Cell Phones for Urban Analysis (2006)The scaling laws of human travel (2006)Pattern mining in tourist attraction visits through association rule learning on Bluetooth tracking data: A case study of Ghent, Belgium (2014)Big data in tourism research: A literature review (2018)The potential impacts of digital technologies on co-production and co-creation (2019)Nonresponse Rates and Nonresponse Bias in Household Surveys (2006)A universal model for mobility and migration patterns (2012)Limits of Predictability in Human Mobility (2010)Modelling the scaling properties of human mobility (2010)The path most traveled: Travel demand estimation using big data resources (2015)Computational Social Science (2009)A survey of results on mobile phone datasets analysis (2015)Human development report 2015: work for human development (2015)Predicting poverty and wealth from mobile phone metadata (2015)Urban Spatial Structure (2010)Coupling mobile phone and social media data: a new approach to understanding urban functions and diurnal patterns (2017)On data processing required to derive mobility patterns from passively-generated mobile phone data (2017)The universal visitation law of human mobility (2021)Prospect Theory: An Analysis of Decision under Risk (1979)Prospect theory: An analysis of decision under risk (1988)The theory of planned behavior (1991)Applying mobile phone data to travel behaviour research: A literature review (2017)Big data and analytics in hospitality and tourism: a systematic literature review (2021)Travel and the Built Environment (2010)Human mobility and socioeconomic status: Analysis of Singapore and Boston (2018)Measuring inequality in community resilience to natural disasters using large-scale mobility data (2021)Big Data Integration (2013)Analyzing large-scale human mobility data: a survey of machine learning methods and applications (2018)
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References

  • 2014Dynamic population mapping using mobile phone data908 cited
  • 2015Origin–destination trips by purpose and time of day inferred from mobile phone data637 cited
  • 2016The promises of big data and small data for travel behavior (aka human mobility) analysis580 cited
  • 2014Development of origin–destination matrices using mobile phone call data508 cited
  • 2016Activity-Based Human Mobility Patterns Inferred from Mobile Phone Data: A Case Study of Singapore472 cited
  • 2014From mobile phone data to the spatial structure of cities458 cited
  • 2011A Tale of One City: Using Cellular Network Data for Urban Planning275 cited
  • 2011The use of Bluetooth for analysing spatiotemporal dynamics of human movement at mass events: A case study of the Ghent Festivities221 cited
  • 2014Estimating human trajectories and hotspots through mobile phone data212 cited
  • 2015Uncovering the spatial structure of mobility networks200 cited
  • 2017A Generative Model of Urban Activities from Cellular Data185 cited
  • 2015Comparing and modelling land use organization in cities94 cited
  • 2011Social Event Detection in Massive Mobile Phone Data Using Probabilistic Location Inference88 cited
  • 2019Mobile phone records to feed activity-based travel demand models: MATSim for studying a cordon toll policy in Barcelona

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69 cited
  • 2018Population dynamics based on mobile phone data to improve air pollution exposure assessments67 cited
  • 2015Inferring Unusual Crowd Events from Mobile Phone Call Detail Records63 cited
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    • 2024Determination of Urban Traveling Patterns With High Spatial and Temporal Resolution by Using GPS Cell Phone Data5 cited