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Generating Trajectories from Mobile Phone Data
1 references·16 citing·46 second hop
Generating Trajectories from Mobile Phone Data (2010)Generating Trajectories from Mobile Phone…Transportation Systems Engineering: Theory and Methods (2001)Transportation Systems Engine…An integrated method for inferring multimodal travel mode choices using mobile network data (2025)An integrated method for infe…Towards a transformation in urban commuting analysis with high-precision mobile phone signaling data: Identifying commuting characteristics based on individual scale (2024)Towards a transformation in u…A data fusion approach with mobile phone data for updating travel survey-based mode split estimates (2023)A data fusion approach with m…Bi-level clustering of vehicle trajectories for path choice set and its nested structure identification (2022)Bi-level clustering of vehicl…Mobile phone data in transportation research: methods for benchmarking against other data sources (2021)Mobile phone data in transpor…Modelling cellphone trace travel mode with neural networks using transit smartcard and home interview survey data (2020)Modelling cellphone trace tra…Modelling long-distance route choice using mobile phone call detail record data: a case study of Senegal (2019)Modelling long-distance route…Using Mobile Phone Data to Observe and Understand Mobility Behavior, Territories, and Transport Usage (2018)Using Mobile Phone Data to Ob…On Non-Routine Places in Urban Human Mobility (2018)On Non-Routine Places in Urba…Understanding Spatiotemporal Patterns of Human Convergence and Divergence Using Mobile Phone Location Data (2016)Understanding Spatiotemporal …SOMOBIL – Improving Public Transport Planning Through Mobile Phone Data Analysis (2016)SOMOBIL – Improving Public Tr…From Cells to Streets (2014)From Cells to StreetsBuilding a validation measure for activity-based transportation models based on mobile phone data (2014)Building a validation measure…Location-based social networking data : doubly-constrained gravity model origin-destination estimation of the urban travel demand for Austin, TX (2013)Location-based social network…Analysis of GSM calls data for understanding user mobility behavior (2013)Analysis of GSM calls data fo…Identifying users profiles from mobile calls habits (2012)Identifying users profiles fr…A statistical theory of spatial distribution models (1967)You are where you tweet (2010)Friendship and mobility (2011)A two-stage stochastic programming approach for dynamic OD estimation using LBSN data (2023)Predicting urban mobility patterns with a LightGBM-enhanced gravity model: Insights from the Wuhan metropolitan area (2025)Mobile Landscapes: Graz in Real Time (2007)Real-Time Urban Monitoring Using Cell Phones: A Case Study in Rome (2010)Using Mobile Positioning Data to Model Locations Meaningful to Users of Mobile Phones (2010)Big Data Research in Italy: A Perspective (2016)Extracting regular mobility patterns from sparse CDR data without a priori assumptions (2017)Analysis of tourist classification from cellular network data (2018)Understanding individual human mobility patterns (2008)Limits of Predictability in Human Mobility (2010)Unravelling daily human mobility motifs (2013)Characterizing activity sequences using profile Hidden Markov Models (2015)Identifying mismatch between urban travel demand and transport network services using GPS data: A case study in the fast growing Chinese city of Harbin (2015)Spatial–Temporal Convolutional Model for Urban Crowd Density Prediction Based on Mobile-Phone Signaling Data (2021)OpenStreetMap: User-Generated Street Maps (2008)Urban Dynamic Estimation Using Mobile Phone Logs and Locally Varying Anisotropy (2017)Data-Driven Methodology for Sustainable Urban Mobility Assessment and Improvement (2021)WHAT ABOUT PEOPLE IN REGIONAL SCIENCE? (1970)Understanding the Representativeness of Mobile Phone Location Data in Characterizing Human Mobility Indicators (2017)Sensing multiple semantics of urban space from crowdsourcing positioning data (2019)Calibrating the dynamic Huff model for business analysis using location big data (2020)Conditional logit analysis of qualitative choice behavior (1972)Discrete Choice Analysis: Theory and Application to Travel Demand. (1987)Discrete choice analysis: Theory and application to travel demand (1988)Hypothetical bias in stated choice experiments: Part I. Macro-scale analysis of literature and integrative synthesis of empirical evidence from applied economics, experimental psychology and neuroimaging (2021)Using an Internet of Behaviours to Study How Air Pollution Can Affect People’s Activities of Daily Living: A Case Study of Beijing, China (2021)Deriving transport appraisal values from emerging revealed preference data (2022)Understanding individual mobility patterns from urban sensing data: A mobile phone trace example (2012)Origin–destination trips by purpose and time of day inferred from mobile phone data (2015)The promises of big data and small data for travel behavior (aka human mobility) analysis (2016)Functional regions as a platform to define integrated transport system zones: The use of population flows data (2022)Big-Data Driven Framework to Estimate Vehicle Volume Based on Mobile Device Location Data (2023)Comparison of home detection algorithms using smartphone GPS data (2024)Understanding attitudes towards public transport and private car: A qualitative study (2007)How Good is Volunteered Geographical Information? A Comparative Study of OpenStreetMap and Ordnance Survey Datasets (2010)Evaluating geospatial context information for travel mode detection (2023)Comparing the impacts of built environment across different objective life neighborhoods on the out-of-home leisure activities of employed people using massive mobile phone data (2024)Spatiotemporal characteristics of residents' intercity travel in China under the impact of COVID-19 pandemic (2024)NETWORK KNOWLEDGE AND ROUTE CHOICE (2002)A Stated Preference Experiment for Measuring Service Quality in Public Transport (2008)Route choice modeling: past, present and future research directions (2009)A new approach for mobile positioning using the CDR data of cellular networks (2017)Population mobility modelling for mobility data simulation (2020)
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References

  • 2001Transportation Systems Engineering: Theory and Methods591 cited

Cited by

  • 2014Building a validation measure for activity-based transportation models based on mobile phone data58 cited
  • 2016Understanding Spatiotemporal Patterns of Human Convergence and Divergence Using Mobile Phone Location Data56 cited
  • 2014From Cells to Streets55 cited
  • 2012Identifying users profiles from mobile calls habits42 cited
  • 2023A data fusion approach with mobile phone data for updating travel survey-based mode split estimates40 cited
  • 2021Mobile phone data in transportation research: methods for benchmarking against other data sources34 cited
  • 2013Analysis of GSM calls data for understanding user mobility behavior25 cited
  • 2019Modelling long-distance route choice using mobile phone call detail record data: a case study of Senegal24 cited
  • 2013Location-based social networking data : doubly-constrained gravity model origin-destination estimation of the urban travel demand for Austin, TX15 cited
  • 2018On Non-Routine Places in Urban Human Mobility12 cited
  • 2016SOMOBIL – Improving Public Transport Planning Through Mobile Phone Data Analysis11 cited
  • 2022Bi-level clustering of vehicle trajectories for path choice set and its nested structure identification10 cited
  • 2020

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Modelling cellphone trace travel mode with neural networks using transit smartcard and home interview survey data
10 cited
  • 2024Towards a transformation in urban commuting analysis with high-precision mobile phone signaling data: Identifying commuting characteristics based on individual scale9 cited
  • 2025An integrated method for inferring multimodal travel mode choices using mobile network data9 cited
  • 2018Using Mobile Phone Data to Observe and Understand Mobility Behavior, Territories, and Transport Usage8 cited