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Transportation Modes Identification from Mobile Phone Data Using Probabilistic Models
6 references·12 citing·39 second hop
Transportation Modes Identification from Mobile Phone Data Using Probabilistic Models (2011)Transportation Modes Identification from …Resolving Social Dilemmas (2013)Resolving Social DilemmasAdaptive route choices in risky traffic networks: A prospect theory approach (2009)Adaptive route choices in ris…Understanding mobility based on GPS data (2008)Understanding mobility based …Learning transportation mode from raw gps data for geographic applications on the web (2008)Learning transportation mode …Inferring High-Level Behavior from Low-Level Sensors (2003)Inferring High-Level Behavior…Advances in prospect theory: Cumulative representation of uncertainty (1992)Advances in prospect theory: …Advancing Fine-Grained Travel Mode Identification in Real Mobile Phone Signaling Data: A Deep Learning Approach (2025)Advancing Fine-Grained Travel…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…Airport accessibility surveys and mobile phone records data fusion for the analysis of air travel behaviour (2024)Airport accessibility surveys…Semi-supervised Mode Classification of Inter-city Trips from Cellular Network Data (2022)Semi-supervised Mode Classifi…Analyzing detour behavior of metro passengers based on mobile phone data (2022)Analyzing detour behavior of …Methods for Travel Pattern Analysis Using Large-Scale Passive Data (2021)Methods for Travel Pattern An…Trip mode inference from mobile phone signaling data using Logarithm Gaussian Mixture Model (2020)Trip mode inference from mobi…Modelling cellphone trace travel mode with neural networks using transit smartcard and home interview survey data (2020)Modelling cellphone trace tra…Transport mode detection based on mobile phone network data: A systematic review (2019)Transport mode detection base…CellTrans (2019)CellTransPublic Transportation Mode Detection from Cellular Data (2017)Public Transportation Mode De…Transportation mode recognition using GPS and accelerometer data (2013)Transportation mode recogniti…Learning significant locations and predicting user movement with GPS (2003)PEIR, the personal environmental impact report, as a platform for participatory sensing systems research (2009)Prospect Theory: An Analysis of Decision under Risk (1979)Prospect theory: An analysis of decision under risk (1988)Which road do I take? A learning-based model of route-choice behavior with real-time information (2010)The impact of travel information’s accuracy on route-choice (2012)Response to Travel Information: A Behavioural Review (2015)Judgment under Uncertainty: Heuristics and Biases (1975)Loss Aversion in Riskless Choice: A Reference-Dependent Model (1991)Individual differences in reasoning: Implications for the rationality debate? (2000)A perspective on judgment and choice: Mapping bounded rationality. (2003)Increasing the accuracy of trip rate information from passive multi-day GPS travel datasets: Automatic trip end identification issues (2006)Deriving and validating trip purposes and travel modes for multi-day GPS-based travel surveys: A large-scale application in the Netherlands (2009)Combining GPS, GIS, and Accelerometry: Methodological Issues in the Assessment of Location and Intensity of Travel Behaviors (2010)Applying mobile phone data to travel behaviour research: A literature review (2017)Inferring transportation modes from GPS trajectories using a convolutional neural network (2017)Using GPS to learn significant locations and predict movement across multiple users (2003)Learning and inferring transportation routines (2007)Urban Computing (2014)A survey of methods for time series change point detection (2016)Human mobility: Models and applications (2018)Mobility Detection Using Everyday GSM Traces (2006)Activity-Based Human Mobility Patterns Inferred from Mobile Phone Data: A Case Study of Singapore (2016)Semi-Supervised Deep Learning Approach for Transportation Mode Identification Using GPS Trajectory Data (2019)Improving Transportation Mode Identification with Limited GPS Trajectories (2021)Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement (2009)Preferred Reporting Items for Systematic Reviews and Meta-Analyses: The PRISMA Statement (2009)Preferred reporting items for systematic reviews and meta-analyses: the PRISMA Statement. (2009)Inferring fine-grained transport modes from mobile phone cellular signaling data (2019)Analytics of location-based big data for smart cities: Opportunities, challenges, and future directions (2021)Transit OD matrix estimation using smartcard data: Recent developments and future research challenges (2021)Understanding individual human mobility patterns (2008)Modelling the scaling properties of human mobility (2010)CellSense (2021)Ubiquitous Transportation Mode Estimation using Limited Cell Tower Information (2023)Robust and Ubiquitous Mobility Mode Estimation Using Limited Cellular Information (2024)Ostracism (2006)The bystander-effect: A meta-analytic review on bystander intervention in dangerous and non-dangerous emergencies. (2011)Ingroup favoritism in cooperation: A meta-analysis. (2014)
this work references cited by second hop

References

  • 1992Advances in prospect theory: Cumulative representation of uncertainty15,457 cited
  • 2008Understanding mobility based on GPS data1,152 cited
  • 2008Learning transportation mode from raw gps data for geographic applications on the web617 cited
  • 2003Inferring High-Level Behavior from Low-Level Sensors529 cited
  • 2009Adaptive route choices in risky traffic networks: A prospect theory approach242 cited
  • 2013Resolving Social Dilemmas162 cited

Cited by

  • 2013Transportation mode recognition using GPS and accelerometer data244 cited
  • 2019Transport mode detection based on mobile phone network data: A systematic review212 cited
  • 2017Public Transportation Mode Detection from Cellular Data18 cited
  • 2019CellTrans17 cited
  • 2020Trip mode inference from mobile phone signaling data using Logarithm Gaussian Mixture Model16 cited
  • 2020Modelling cellphone trace travel mode with neural networks using transit smartcard and home interview survey data10 cited
  • 2024Towards a transformation in urban commuting analysis with high-precision mobile phone signaling data: Identifying commuting characteristics based on individual scale9 cited
  • 2022Semi-supervised Mode Classification of Inter-city Trips from Cellular Network Data8 cited

Only edges whose both ends are imported exist here. Widen the year window, or show the whole map. Back to the work

  • 2024Airport accessibility surveys and mobile phone records data fusion for the analysis of air travel behaviour7 cited
  • 2025Advancing Fine-Grained Travel Mode Identification in Real Mobile Phone Signaling Data: A Deep Learning Approach4 cited
  • 2022Analyzing detour behavior of metro passengers based on mobile phone data4 cited
  • 2021Methods for Travel Pattern Analysis Using Large-Scale Passive Data3 cited