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Limitations of Recursive Logit for Inverse Reinforcement Learning of Bicycle Route Choice Behavior in Amsterdam
14 references·2 citing·35 second hop
Limitations of Recursive Logit for Inverse Reinforcement Learning of Bicycle Route Choice Behavior in Amsterdam (2021)Limitations of Recursive Logit for Invers…A tutorial on recursive models for analyzing and predicting path choice behavior (2020)A tutorial on recursive model…How Do People Cycle in Amsterdam, Netherlands?: Estimating Cyclists’ Route Choice Determinants with GPS Data from an Urban Area (2017)How Do People Cycle in Amster…Bike route choice modeling using GPS data without choice sets of paths (2016)Bike route choice modeling us…A decomposition method for estimating recursive logit based route choice models (2016)A decomposition method for es…Efficiency of choice set generation methods for bicycle routes (2014)Efficiency of choice set gene…A link based network route choice model with unrestricted choice set (2013)A link based network route ch…Route choice of cyclists in Zurich (2010)Route choice of cyclists in Z…Sampling of alternatives for route choice modeling (2009)Sampling of alternatives for …STOCHASTIC ROUTE CHOICE SET GENERATION: BEHAVIORAL AND PROBABILISTIC FOUNDATIONS (2007)STOCHASTIC ROUTE CHOICE SET G…A stochastic transit assignment model considering differences in passengers utility functions (2000)A stochastic transit assignme…Handbook of Transportation Science (1999)Handbook of Transportation Sc…Discrete Choice Methods and their Applications to Short Term Travel Decisions (1999)Discrete Choice Methods and t…A MODIFIED LOGIT ROUTE CHOICE MODEL OVERCOMING PATH OVERLAPPING PROBLEMS. SPECIFICATION AND SOME CALIBRATION RESULTS FOR INTERURBAN NETWORKS (1996)A MODIFIED LOGIT ROUTE CHOICE…Conditional logit analysis of qualitative choice behavior (1972)Conditional logit analysis of…Will e-bikes revolutionize urban mobility? Development and application of a transport model differentiating between conventional and electric bicycle traffic (2025)Will e-bikes revolutionize ur…Enhancing Pedestrian Route Choice Models Through Maximum-Entropy Deep Inverse Reinforcement Learning With Individual Covariates (MEDIRL-IC) (2024)Enhancing Pedestrian Route Ch…Elimination by aspects: A theory of choice. (1972)Discrete Choice Analysis: Theory and Application to Travel Demand. (1987)Discrete choice analysis: Theory and application to travel demand (1988)BIOGEME: a free package for the estimation of discrete choice models (2003)Where do cyclists ride? A route choice model developed with revealed preference GPS data (2012)A probabilistic multipath traffic assignment model which obviates path enumeration (1971)On Stochastic Models of Traffic Assignment (1977)Optimal strategies: A new assignment model for transit networks (1989)Chapter 2 Public Transit (2006)Using connectivity for measuring equity in transit provision (2014)Dynamic public transit accessibility using travel time cubes: Comparing the effects of infrastructure (dis)investments over time (2016)Discrete Choice Methods with Simulation (2001)Assessing the cost of transfer inconvenience in public transport systems: A case study of the London Underground (2010)Understanding cyclists’ perceptions, keys for a successful bicycle promotion (2014)Cycling or walking? Determinants of mode choice in the Netherlands (2018)Studies in the Economics of Transportation. (1956)MODELING THE CHOICE OF RESIDENTIAL LOCATION (1978)Optimal Replacement of GMC Bus Engines: An Empirical Model of Harold Zurcher (1987)A nested recursive logit model for route choice analysis (2015)A big data approach to understanding pedestrian route choice preferences: Evidence from San Francisco (2021)Making Cycling Irresistible: Lessons from The Netherlands, Denmark and Germany (2008)A GPS data-based analysis of built environment influences on bicyclist route preferences (2017)The overreliance on statistical goodness-of-fit and under-reliance on model validation in discrete choice models: A review of validation practices in the transportation academic literature (2020)A deep inverse reinforcement learning approach to route choice modeling with context-dependent rewards (2023)Financial Ratios and the Probabilistic Prediction of Bankruptcy (1980)Macroeconomics and Reality (1980)A Joint Location-Inventory Model (2003)Is a new applied transportation research field emerging?––A review of intermodal rail–truck freight transport literature (2003)Route choice modeling: past, present and future research directions (2009)Modeling multi-modal morning commute in a one-to-one corridor network (2010)Boundedly rational user equilibria (BRUE): Mathematical formulation and solution sets (2013)Developing advanced route choice models for heavy goods vehicles using GPS data (2015)Adaptive route choices in risky traffic networks: A prospect theory approach (2009)Residential mobility and location choice: a nested logit model with sampling of alternatives (2010)NETWORK KNOWLEDGE AND ROUTE CHOICE (2002)
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References

  • 1972Conditional logit analysis of qualitative choice behavior14,281 cited
  • 1999Discrete Choice Methods and their Applications to Short Term Travel Decisions981 cited
  • 1999Handbook of Transportation Science560 cited
  • 1996A MODIFIED LOGIT ROUTE CHOICE MODEL OVERCOMING PATH OVERLAPPING PROBLEMS. SPECIFICATION AND SOME CALIBRATION RESULTS FOR INTERURBAN NETWORKS449 cited
  • 2010Route choice of cyclists in Zurich320 cited
  • 2013A link based network route choice model with unrestricted choice set298 cited
  • 2009Sampling of alternatives for route choice modeling264 cited
  • 2000A stochastic transit assignment model considering differences in passengers utility functions210 cited
  • 2016Bike route choice modeling using GPS data without choice sets of paths166 cited
  • 2007STOCHASTIC ROUTE CHOICE SET GENERATION: BEHAVIORAL AND PROBABILISTIC FOUNDATIONS107 cited
  • 2017How Do People Cycle in Amsterdam, Netherlands?: Estimating Cyclists’ Route Choice Determinants with GPS Data from an Urban Area66 cited
  • 2016A decomposition method for estimating recursive logit based route choice models44 cited
  • 2020A tutorial on recursive models for analyzing and predicting path choice behavior44 cited
  • 2014Efficiency of choice set generation methods for bicycle routes33 cited

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Cited by

  • 2024Enhancing Pedestrian Route Choice Models Through Maximum-Entropy Deep Inverse Reinforcement Learning With Individual Covariates (MEDIRL-IC)5 cited
  • 2025Will e-bikes revolutionize urban mobility? Development and application of a transport model differentiating between conventional and electric bicycle traffic5 cited