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10 references·4 citing·44 second hop
AllAboard (2014)AllAboardOrigin–destination trips by purpose and time of day inferred from mobile phone data (2015)Origin–destination trips by p…Urban Sensing Using Mobile Phone Network Data: A Survey of Research (2014)Urban Sensing Using Mobile Ph…The impact of biases in mobile phone ownership on estimates of human mobility (2013)The impact of biases in mobil…Estimating Origin-Destination Flows Using Mobile Phone Location Data (2011)Estimating Origin-Destination…Understanding individual human mobility patterns (2008)Understanding individual huma…Transit network design and scheduling: A global review (2008)Transit network design and sc…Public Transit Planning and Operation: Theory, Modeling and Practice (2007)Public Transit Planning and O…A Column-Generation Approach to Line Planning in Public Transport (2007)A Column-Generation Approach …Optimal strategies: A new assignment model for transit networks (1989)Optimal strategies: A new ass…Experiments In Migration Mapping By Computer (1987)Experiments In Migration Mapp…FBVA: A Flow-Based Visual Analytics Approach for Citywide Crowd Mobility (2019)FBVA: A Flow-Based Visual Ana…Analysis of public transit trip chain of commuters based on mobile phone data and GPS data (2017)Analysis of public transit tr…Visualization Analysis for Urban Human Traveling Behavior Based on Mobile Phone Data (2015)Visualization Analysis for Ur…Comparing Urban Sensing Applications Using Event and Network-Driven Mobile Phone Location Data (2015)Comparing Urban Sensing Appli…The origin of bursts and heavy tails in human dynamics (2005)The scaling laws of human travel (2006)Friendship and mobility (2011)A universal model for mobility and migration patterns (2012)A Theoretical Foundation for the Gravity Equation. (1979)Real-Time Urban Monitoring Using Cell Phones: A Case Study in Rome (2010)Understanding individual mobility patterns from urban sensing data: A mobile phone trace example (2012)A new insight into land use classification based on aggregated mobile phone data (2014)Development of origin–destination matrices using mobile phone call data (2014)A probabilistic multipath traffic assignment model which obviates path enumeration (1971)The existence, uniqueness and stability of traffic equilibria (1979)Transit Assignment for Congested Public Transport Systems: An Equilibrium Model (1993)A review of urban transportation network design problems (2013)Crowding in public transport systems: Effects on users, operation and implications for the estimation of demand (2013)Limits of Predictability in Human Mobility (2010)Modelling the scaling properties of human mobility (2010)Unravelling daily human mobility motifs (2013)The path most traveled: Travel demand estimation using big data resources (2015)Activity-Based Human Mobility Patterns Inferred from Mobile Phone Data: A Case Study of Singapore (2016)The promises of big data and small data for travel behavior (aka human mobility) analysis (2016)Reality mining: sensing complex social systems (2005)Exploring the capacity of social media data for modelling travel behaviour: Opportunities and challenges (2016)On data processing required to derive mobility patterns from passively-generated mobile phone data (2017)Gender gaps in urban mobility (2020)Big data: The next frontier for innovation, competition, and productivity (2011)Coupling mobile phone and social media data: a new approach to understanding urban functions and diurnal patterns (2017)Transport modelling in the age of big data (2017)Transport mode detection based on mobile phone network data: A systematic review (2019)An efficient approach to solving the road network equilibrium traffic assignment problem (1975)Network Design and Transportation Planning: Models and Algorithms (1984)Assessing the cost of transfer inconvenience in public transport systems: A case study of the London Underground (2010)Planning, operation, and control of bus transport systems: A literature review (2015)Evaluation and optimization of urban public transportation networks (1980)Bus network design (1986)Selfish Routing in Capacitated Networks (2004)Line planning in public transportation: models and methods (2011)Optimizing Bus Bridging Services in Response to Disruptions of Urban Transit Rail Networks (2015)An eigenmodel for iterative line planning, timetabling and vehicle scheduling in public transportation (2016)Potential Contributions of Spatial Analysis to Geographic Information Systems for Transportation (GIS‐T) (1999)Mapping the geography of science: Distribution patterns and networks of relations among cities and institutes (2010)Manual of Digital Earth (2019)Synchronization of bus timetabling (2012)Analysis of a new public-transport-service concept: Customized bus in China (2015)Customized bus service design for jointly optimizing passenger-to-vehicle assignment and vehicle routing (2017)
this work references cited by second hop

References

  • 2008Understanding individual human mobility patterns6,071 cited
  • 1989Optimal strategies: A new assignment model for transit networks777 cited
  • 2008Transit network design and scheduling: A global review671 cited
  • 2015Origin–destination trips by purpose and time of day inferred from mobile phone data637 cited
  • 2011Estimating Origin-Destination Flows Using Mobile Phone Location Data511 cited
  • 2007Public Transit Planning and Operation: Theory, Modeling and Practice361 cited
  • 2014Urban Sensing Using Mobile Phone Network Data: A Survey of Research334 cited
  • 2007A Column-Generation Approach to Line Planning in Public Transport287 cited
  • 1987Experiments In Migration Mapping By Computer253 cited
  • 2013The impact of biases in mobile phone ownership on estimates of human mobility246 cited

Cited by

  • 2015Comparing Urban Sensing Applications Using Event and Network-Driven Mobile Phone Location Data12 cited
  • 2019FBVA: A Flow-Based Visual Analytics Approach for Citywide Crowd Mobility11 cited
  • 2017Analysis of public transit trip chain of commuters based on mobile phone data and GPS data8 cited
  • 2015Visualization Analysis for Urban Human Traveling Behavior Based on Mobile Phone Data4 cited

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