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Hierarchical travel demand estimation using multiple data sources: A forward and backward propagation algorithmic framework on a layered computational graph
16 references·16 citing·42 second hopsampled
Hierarchical travel demand estimation using multiple data sources: A forward and backward propagation algorithmic framework on a layered computational graph (2018)Hierarchical travel demand estimation usi…The promises of big data and small data for travel behavior (aka human mobility) analysis (2016)The promises of big data and …The path most traveled: Travel demand estimation using big data resources (2015)The path most traveled: Trave…Inferring land use from mobile phone activity (2012)Inferring land use from mobil…Understanding individual human mobility patterns (2008)Understanding individual huma…The Economics of Urban Transportation (2007)The Economics of Urban Transp…Handbook of Transport Modelling (2007)Handbook of Transport Modelli…Dynamic Origin–Destination Demand Estimation Using Automatic Vehicle Identification Data (2006)Dynamic Origin–Destination De…The propagation of uncertainty through travel demand models: An exploratory analysis (2002)The propagation of uncertaint…NETWORK KNOWLEDGE AND ROUTE CHOICE (2002)NETWORK KNOWLEDGE AND ROUTE C…Handbook of Transport Modelling (2000)Handbook of Transport Modelli…Link-Nested Logit Model of Route Choice: Overcoming Route Overlapping Problem (1998)Link-Nested Logit Model of Ro…Sensitivity Analysis for Equilibrium Network Flow (1988)Sensitivity Analysis for Equi…Urban transportation networks: Equilibrium analysis with mathematical programming methods (1986)Urban transportation networks…The most likely trip matrix estimated from traffic counts (1980)The most likely trip matrix e…Urban Travel Demand: A Behavioral Analysis (1977)Urban Travel Demand: A Behavi…Urban travel demand: A behavioral analysis (1976)Urban travel demand: A behavi…Potentials of digital twin system for analyzing travel behavior decisions (2024)Potentials of digital twin sy…An Interdisciplinary Survey on Origin-destination Flows Modeling: Theory and Techniques (2024)An Interdisciplinary Survey o…End-to-End Learning of User Equilibrium with Implicit Neural Networks (2022)End-to-End Learning of User E…Dynamic demand estimation on large scale networks using Principal Component Analysis: The case of non-existent or irrelevant historical estimates (2022)Dynamic demand estimation on …Transit OD matrix estimation using smartcard data: Recent developments and future research challenges (2021)Transit OD matrix estimation …Theory-based residual neural networks: A synergy of discrete choice models and deep neural networks (2021)Theory-based residual neural …Dynamic activity chain pattern estimation under mobility demand changes during COVID-19 (2021)Dynamic activity chain patter…Semi-supervised route choice modeling with sparse Automatic vehicle identification data (2020)Semi-supervised route choice …Estimating multi-class dynamic origin-destination demand through a forward-backward algorithm on computational graphs (2020)Estimating multi-class dynami…Development of people mass movement simulation framework based on reinforcement learning (2020)Development of people mass mo…Deep neural networks for choice analysis: Extracting complete economic information for interpretation (2020)Deep neural networks for choi…Deep neural networks for choice analysis: Architecture design with alternative-specific utility functions (2020)Deep neural networks for choi…A Review of Big Data Applications in Urban Transit Systems (2020)A Review of Big Data Applicat…Observability quantification of public transportation systems with heterogeneous data sources: An information-space projection approach based on discretized space-time network flow models (2019)Observability quantification …Dynamic origin-destination matrix calibration for large-scale network simulators (2018)Dynamic origin-destination ma…Data-driven activity scheduler for agent-based mobility models (2018)Data-driven activity schedule…Conditional logit analysis of qualitative choice behavior (1972)Discrete Choice Analysis: Theory and Application to Travel Demand. (1987)Prospect theory: An analysis of decision under risk (1988)Urban Growth and Transportation (2012)Productive Cities: Sorting, Selection, and Agglomeration (2014)Transportation Costs and the Spatial Organization of Economic Activity (2015)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)Estimation of trip matrices from traffic counts and survey data: A generalized least squares estimator (1984)Development of origin–destination matrices using mobile phone call data (2014)Entropy in urban and regional modelling (2021)The existence, uniqueness and stability of traffic equilibria (1979)Traffic Equilibrium and Variational Inequalities (1980)Network Design and Transportation Planning: Models and Algorithms (1984)Bilevel programming in traffic planning: Models, methods and challenge (1995)Heuristic algorithms for the bilevel origin-destination matrix estimation problem (1995)An equivalent continuously differentiable model and a locally convergent algorithm for the continuous network design problem (2001)Limits of Predictability in Human Mobility (2010)Activity-Based Human Mobility Patterns Inferred from Mobile Phone Data: A Case Study of Singapore (2016)The TimeGeo modeling framework for urban mobility without travel surveys (2016)Understanding congested travel in urban areas (2016)Prospect Theory: An Analysis of Decision under Risk (1979)The theory of planned behavior (1991)Applying mobile phone data to travel behaviour research: A literature review (2017)Coupling mobile phone and social media data: a new approach to understanding urban functions and diurnal patterns (2017)Big data and analytics in hospitality and tourism: a systematic literature review (2021)The Importance of Utility Balance in Efficient Choice Designs (1996)The optimal migration duration and activity choice after re-migration (1999)Mixed MNL models for discrete response (2000)The Influence of Urban Form on Travel: An Interpretive Review (2000)Urban Form and a Child’s Trip to School: The Current Literature and a Framework for Future Research (2005)Models and algorithms for road network design: a review and some new developments (1998)Foundations of Dynamic Traffic Assignment: The Past, the Present and the Future (2001)Selfish Routing and the Price of Anarchy (2016)Construction of experimental designs for mixed logit models allowing for correlation across choice observations (2010)Robust optimization for emergency logistics planning: Risk mitigation in humanitarian relief supply chains (2010)A justice-theoretic approach to the distribution of transportation benefits: Implications for transportation planning practice in the United States (2012)A Conditional Probit Model for Qualitative Choice: Discrete Decisions Recognizing Interdependence and Heterogeneous Preferences (1978)Built environments and mode choice: toward a normative framework (2002)How the built environment affects physical activity (2002)
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References

  • 2008Understanding individual human mobility patterns6,071 cited
  • 1986Urban transportation networks: Equilibrium analysis with mathematical programming methods2,352 cited
  • 1977Urban Travel Demand: A Behavioral Analysis1,300 cited
  • 2007The Economics of Urban Transportation1,035 cited
  • 1980The most likely trip matrix estimated from traffic counts623 cited
  • 2016The promises of big data and small data for travel behavior (aka human mobility) analysis580 cited
  • 1976Urban travel demand: A behavioral analysis567 cited
  • 2015The path most traveled: Travel demand estimation using big data resources418 cited
  • 1988Sensitivity Analysis for Equilibrium Network Flow339 cited
  • 2000Handbook of Transport Modelling330 cited
  • 2002NETWORK KNOWLEDGE AND ROUTE CHOICE311 cited
  • 2012Inferring land use from mobile phone activity299 cited
  • 2007Handbook of Transport Modelling265 cited
  • 1998Link-Nested Logit Model of Route Choice: Overcoming Route Overlapping Problem237 cited
  • 2006Dynamic Origin–Destination Demand Estimation Using Automatic Vehicle Identification Data203 cited
  • 2002

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The propagation of uncertainty through travel demand models: An exploratory analysis
197 cited

Cited by

  • 2021Transit OD matrix estimation using smartcard data: Recent developments and future research challenges118 cited
  • 2020Deep neural networks for choice analysis: Extracting complete economic information for interpretation117 cited
  • 2020Deep neural networks for choice analysis: Architecture design with alternative-specific utility functions111 cited
  • 2018Dynamic origin-destination matrix calibration for large-scale network simulators87 cited
  • 2020Estimating multi-class dynamic origin-destination demand through a forward-backward algorithm on computational graphs87 cited
  • 2020A Review of Big Data Applications in Urban Transit Systems79 cited
  • 2018Data-driven activity scheduler for agent-based mobility models71 cited
  • 2021Theory-based residual neural networks: A synergy of discrete choice models and deep neural networks60 cited
  • 2024An Interdisciplinary Survey on Origin-destination Flows Modeling: Theory and Techniques55 cited
  • 2020Semi-supervised route choice modeling with sparse Automatic vehicle identification data42 cited
  • 2022End-to-End Learning of User Equilibrium with Implicit Neural Networks41 cited
  • 2024Potentials of digital twin system for analyzing travel behavior decisions31 cited
  • 2022Dynamic demand estimation on large scale networks using Principal Component Analysis: The case of non-existent or irrelevant historical estimates29 cited
  • 2020Development of people mass movement simulation framework based on reinforcement learning27 cited
  • 2021Dynamic activity chain pattern estimation under mobility demand changes during COVID-1927 cited
  • 2019Observability quantification of public transportation systems with heterogeneous data sources: An information-space projection approach based on discretized space-time network flow models25 cited