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A nested recursive logit model for route choice analysis

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  1. Oyama, Yuki & Hato, Eiji, 2019. "Prism-based path set restriction for solving Markovian traffic assignment problem," Transportation Research Part B: Methodological, Elsevier, vol. 122(C), pages 528-546.
  2. Liu, Shan & Jiang, Hai, 2022. "Personalized route recommendation for ride-hailing with deep inverse reinforcement learning and real-time traffic conditions," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 164(C).
  3. Yao, Rui & Bekhor, Shlomo, 2022. "A variational autoencoder approach for choice set generation and implicit perception of alternatives in choice modeling," Transportation Research Part B: Methodological, Elsevier, vol. 158(C), pages 273-294.
  4. Nassir, Neema & Hickman, Mark & Ma, Zhen-Liang, 2019. "A strategy-based recursive path choice model for public transit smart card data," Transportation Research Part B: Methodological, Elsevier, vol. 126(C), pages 528-548.
  5. Austin Knies & Jorge Lorca & Emerson Melo, 2020. "A Recursive Logit Model with Choice Aversion and Its Application to Transportation Networks," Papers 2010.02398, arXiv.org, revised Oct 2021.
  6. Yuki Oyama, 2023. "Global path preference and local response: A reward decomposition approach for network path choice analysis in the presence of locally perceived attributes," Papers 2307.08646, arXiv.org.
  7. Selin Damla Ahipaşaoğlu & Uğur Arıkan & Karthik Natarajan, 2019. "Distributionally Robust Markovian Traffic Equilibrium," Transportation Science, INFORMS, vol. 53(6), pages 1546-1562, November.
  8. Mai, Tien & Frejinger, Emma & Fosgerau, Mogens & Bastin, Fabian, 2017. "A dynamic programming approach for quickly estimating large network-based MEV models," Transportation Research Part B: Methodological, Elsevier, vol. 98(C), pages 179-197.
  9. Song, Yuchen & Li, Dawei & Liu, Dongjie & Cao, Qi & Chen, Junlan & Ren, Gang & Tang, Xiaoyong, 2022. "Modeling activity-travel behavior under a dynamic discrete choice framework with unobserved heterogeneity," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 167(C).
  10. Mai, Tien, 2016. "A method of integrating correlation structures for a generalized recursive route choice model," Transportation Research Part B: Methodological, Elsevier, vol. 93(PA), pages 146-161.
  11. Cortés, Cristián E. & Donoso, Pedro & Gutiérrez, Leonel & Herl, Daniel & Muñoz, Diego, 2023. "A recursive stochastic transit equilibrium model estimated using passive data from Santiago, Chile," Transportation Research Part B: Methodological, Elsevier, vol. 174(C).
  12. Tran, Hung & Mai, Tien, 2024. "Network-based representations and dynamic discrete choice models for multiple discrete choice analysis," Transportation Research Part B: Methodological, Elsevier, vol. 184(C).
  13. Mogens Fosgerau & Nikolaj Nielsen & Mads Paulsen & Thomas Kj{ae}r Rasmussen & Rui Yao, 2024. "Substitution in the perturbed utility route choice model," Papers 2409.08347, arXiv.org.
  14. Mogens Fosgerau & Mads Paulsen & Thomas Kj{ae}r Rasmussen, 2021. "A perturbed utility route choice model," Papers 2103.13784, arXiv.org, revised Sep 2021.
  15. Oyama, Yuki, 2024. "Global path preference and local response: A reward decomposition approach for network path choice analysis in the presence of visually perceived attributes," Transportation Research Part A: Policy and Practice, Elsevier, vol. 181(C).
  16. Mai, Tien & Bastin, Fabian & Frejinger, Emma, 2017. "On the similarities between random regret minimization and mother logit: The case of recursive route choice models," Journal of choice modelling, Elsevier, vol. 23(C), pages 21-33.
  17. Taoyuan Yang & Peng Zhao & Xiangming Yao, 2020. "A Method to Estimate URT Passenger Spatial-Temporal Trajectory with Smart Card Data and Train Schedules," Sustainability, MDPI, vol. 12(6), pages 1-13, March.
  18. Guan, Xiangyang & Chen, Cynthia, 2021. "A behaviorally-integrated individual-level state-transition model that can predict rapid changes in evacuation demand days earlier," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 152(C).
  19. Evanthia Kazagli & Michel Bierlaire & Matthieu de Lapparent, 2020. "Operational route choice methodologies for practical applications," Transportation, Springer, vol. 47(1), pages 43-74, February.
  20. Mai, Tien & Bui, The Viet & Nguyen, Quoc Phong & Le, Tho V., 2023. "Estimation of recursive route choice models with incomplete trip observations," Transportation Research Part B: Methodological, Elsevier, vol. 173(C), pages 313-331.
  21. Guarda, Pablo & Qian, Sean, 2024. "Statistical inference of travelers’ route choice preferences with system-level data," Transportation Research Part B: Methodological, Elsevier, vol. 179(C).
  22. Oyama, Yuki & Hara, Yusuke & Akamatsu, Takashi, 2022. "Markovian traffic equilibrium assignment based on network generalized extreme value model," Transportation Research Part B: Methodological, Elsevier, vol. 155(C), pages 135-159.
  23. Oskar Blom Västberg & Anders Karlström & Daniel Jonsson & Marcus Sundberg, 2020. "A Dynamic Discrete Choice Activity-Based Travel Demand Model," Transportation Science, INFORMS, vol. 54(1), pages 21-41, January.
  24. Papola, Andrea & Tinessa, Fiore & Marzano, Vittorio, 2018. "Application of the Combination of Random Utility Models (CoRUM) to route choice," Transportation Research Part B: Methodological, Elsevier, vol. 111(C), pages 304-326.
  25. Shiva Habibi & Emma Frejinger & Marcus Sundberg, 2019. "An empirical study on aggregation of alternatives and its influence on prediction in car type choice models," Transportation, Springer, vol. 46(3), pages 563-582, June.
  26. Fiore Tinessa & Vittorio Marzano & Andrea Papola, 2021. "Choice probabilities and correlations in closed-form route choice models: specifications and drawbacks," Papers 2110.07224, arXiv.org.
  27. Ding-Mastera, Jing & Gao, Song & Jenelius, Erik & Rahmani, Mahmood & Ben-Akiva, Moshe, 2019. "A latent-class adaptive routing choice model in stochastic time-dependent networks," Transportation Research Part B: Methodological, Elsevier, vol. 124(C), pages 1-17.
  28. Tien Mai & The Viet Bui & Quoc Phong Nguyen & Tho V. Le, 2022. "Estimation of Recursive Route Choice Models with Incomplete Trip Observations," Papers 2204.12992, arXiv.org.
  29. Meyer de Freitas, Lucas & Becker, Henrik & Zimmermann, Maëlle & Axhausen, Kay W., 2019. "Modelling intermodal travel in Switzerland: A recursive logit approach," Transportation Research Part A: Policy and Practice, Elsevier, vol. 119(C), pages 200-213.
  30. Hou, Xianlei & Zhang, Rui & Yang, Minghui & Cheng, Shida, 2024. "Modeling the lane-changing behavior of non-motorized vehicles on road segments via social force model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 633(C).
  31. Kazagli, Evanthia & Bierlaire, Michel & Flötteröd, Gunnar, 2016. "Revisiting the route choice problem: A modeling framework based on mental representations," Journal of choice modelling, Elsevier, vol. 19(C), pages 1-23.
  32. Mai, Tien & Yu, Xinlian & Gao, Song & Frejinger, Emma, 2021. "Routing policy choice prediction in a stochastic network: Recursive model and solution algorithm," Transportation Research Part B: Methodological, Elsevier, vol. 151(C), pages 42-58.
  33. Zhang, Pujun & Lei, Dazhou & Liu, Shan & Jiang, Hai, 2024. "Recursive logit-based meta-inverse reinforcement learning for driver-preferred route planning," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 185(C).
  34. Jiang, Gege & Fosgerau, Mogens & Lo, Hong K., 2020. "Route choice, travel time variability, and rational inattention," Transportation Research Part B: Methodological, Elsevier, vol. 132(C), pages 188-207.
  35. van Oijen, Tim P. & Daamen, Winnie & Hoogendoorn, Serge P., 2020. "Estimation of a recursive link-based logit model and link flows in a sensor equipped network," Transportation Research Part B: Methodological, Elsevier, vol. 140(C), pages 262-281.
  36. Yuki Oyama, 2022. "Capturing positive network attributes during the estimation of recursive logit models: A prism-based approach," Papers 2204.01215, arXiv.org, revised Jan 2023.
  37. Hung Tran & Tien Mai, 2023. "Network-based Representations and Dynamic Discrete Choice Models for Multiple Discrete Choice Analysis," Papers 2306.04606, arXiv.org.
  38. Knies, Austin & Lorca, Jorge & Melo, Emerson, 2022. "A recursive logit model with choice aversion and its application to transportation networks," Transportation Research Part B: Methodological, Elsevier, vol. 155(C), pages 47-71.
  39. Rambha, Tarun & Nozick, Linda K. & Davidson, Rachel, 2021. "Modeling hurricane evacuation behavior using a dynamic discrete choice framework," Transportation Research Part B: Methodological, Elsevier, vol. 150(C), pages 75-100.
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