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Dynamic Estimators of Origin-Destination Matrices Using Traffic Counts

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  1. D'Acierno, Luca & Cartenì, Armando & Montella, Bruno, 2009. "Estimation of urban traffic conditions using an Automatic Vehicle Location (AVL) System," European Journal of Operational Research, Elsevier, vol. 196(2), pages 719-736, July.
  2. Anselmo Ramalho Pitombeira-Neto & Carlos Felipe Grangeiro Loureiro & Luis Eduardo Carvalho, 2020. "A Dynamic Hierarchical Bayesian Model for the Estimation of day-to-day Origin-destination Flows in Transportation Networks," Networks and Spatial Economics, Springer, vol. 20(2), pages 499-527, June.
  3. Hänseler, Flurin S. & Bierlaire, Michel & Farooq, Bilal & Mühlematter, Thomas, 2014. "A macroscopic loading model for time-varying pedestrian flows in public walking areas," Transportation Research Part B: Methodological, Elsevier, vol. 69(C), pages 60-80.
  4. Lin, Pei-Wei & Chang, Gang-Len, 2007. "A generalized model and solution algorithm for estimation of the dynamic freeway origin-destination matrix," Transportation Research Part B: Methodological, Elsevier, vol. 41(5), pages 554-572, June.
  5. Chao Sun & Yulin Chang & Xin Luan & Qiang Tu & Wenyun Tang, 2020. "Origin-Destination Demand Reconstruction Using Observed Travel Time under Congested Network," Networks and Spatial Economics, Springer, vol. 20(3), pages 733-755, September.
  6. Van Der Zijpp, Nanne J. & De Romph, Erik, 1997. "A dynamic traffic forecasting application on the Amsterdam beltway," International Journal of Forecasting, Elsevier, vol. 13(1), pages 87-103, March.
  7. Chu, Lianyu & Liu, Henry X. & Recker, Will & Hague, Steve, 2003. "Evaluation of Potential ITS Strategies Under Non-Recurrent Congestion Using Microscopic Simulation," Institute of Transportation Studies, Research Reports, Working Papers, Proceedings qt74f7f2x0, Institute of Transportation Studies, UC Berkeley.
  8. Nguyen, S. & Pallottino, S. & Inaudi, D., 1996. "Postoptimizing equilibrium flows on large scale networks," European Journal of Operational Research, Elsevier, vol. 91(3), pages 507-516, June.
  9. Pedro J Zufiria & David Pastor-Escuredo & Luis Úbeda-Medina & Miguel A Hernandez-Medina & Iker Barriales-Valbuena & Alfredo J Morales & Damien C Jacques & Wilfred Nkwambi & M Bamba Diop & John Quinn &, 2018. "Identifying seasonal mobility profiles from anonymized and aggregated mobile phone data. Application in food security," PLOS ONE, Public Library of Science, vol. 13(4), pages 1-20, April.
  10. Hsun-Jung Cho & Yow-Jen Jou & Chien-Lun Lan, 2009. "Time Dependent Origin-destination Estimation from Traffic Count without Prior Information," Networks and Spatial Economics, Springer, vol. 9(2), pages 145-170, June.
  11. Camus, Roberto & Cantarella, Giulio E. & Inaudi, Domenico, 1997. "Real-time estimation and prediction of origin--destination matrices per time slice," International Journal of Forecasting, Elsevier, vol. 13(1), pages 13-19, March.
  12. Hazelton, Martin L., 2008. "Statistical inference for time varying origin-destination matrices," Transportation Research Part B: Methodological, Elsevier, vol. 42(6), pages 542-552, July.
  13. Huo, Jinbiao & Liu, Chengqi & Chen, Jingxu & Meng, Qiang & Wang, Jian & Liu, Zhiyuan, 2023. "Simulation-based dynamic origin–destination matrix estimation on freeways: A Bayesian optimization approach," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 173(C).
  14. Codina, Esteve & Garcia, Ricardo & Marin, Angel, 2006. "New algorithmic alternatives for the O-D matrix adjustment problem on traffic networks," European Journal of Operational Research, Elsevier, vol. 175(3), pages 1484-1500, December.
  15. Zhang, Liye & Meng, Qiang & Fang Fwa, Tien, 2019. "Big AIS data based spatial-temporal analyses of ship traffic in Singapore port waters," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 129(C), pages 287-304.
  16. Zhang, Chao & Osorio, Carolina & Flötteröd, Gunnar, 2017. "Efficient calibration techniques for large-scale traffic simulators," Transportation Research Part B: Methodological, Elsevier, vol. 97(C), pages 214-239.
  17. Flurin S. Hänseler & Nicholas A. Molyneaux & Michel Bierlaire, 2017. "Estimation of Pedestrian Origin-Destination Demand in Train Stations," Transportation Science, INFORMS, vol. 51(3), pages 981-997, August.
  18. Nie, Yu (Marco) & Zhang, H.M., 2008. "A variational inequality formulation for inferring dynamic origin-destination travel demands," Transportation Research Part B: Methodological, Elsevier, vol. 42(7-8), pages 635-662, August.
  19. Wong, S. C. & Tong, C. O., 1998. "Estimation of time-dependent origin-destination matrices for transit networks," Transportation Research Part B: Methodological, Elsevier, vol. 32(1), pages 35-48, January.
  20. Hänseler, Flurin S. & Lam, William H.K. & Bierlaire, Michel & Lederrey, Gael & Nikolić, Marija, 2017. "A dynamic network loading model for anisotropic and congested pedestrian flows," Transportation Research Part B: Methodological, Elsevier, vol. 95(C), pages 149-168.
  21. Hänseler, Flurin S. & Bierlaire, Michel & Scarinci, Riccardo, 2016. "Assessing the usage and level-of-service of pedestrian facilities in train stations: A Swiss case study," Transportation Research Part A: Policy and Practice, Elsevier, vol. 89(C), pages 106-123.
  22. Gunnar Flötteröd & Michel Bierlaire & Kai Nagel, 2011. "Bayesian Demand Calibration for Dynamic Traffic Simulations," Transportation Science, INFORMS, vol. 45(4), pages 541-561, November.
  23. A. de Palma & F. Marchal, 2000. "Dynamic traffic analysis with static data: some guidelines with an application to Paris," THEMA Working Papers 2000-55, THEMA (THéorie Economique, Modélisation et Applications), Université de Cergy-Pontoise.
  24. K. Ashok & M. E. Ben-Akiva, 2002. "Estimation and Prediction of Time-Dependent Origin-Destination Flows with a Stochastic Mapping to Path Flows and Link Flows," Transportation Science, INFORMS, vol. 36(2), pages 184-198, May.
  25. Yasuo Asakura & Eiji Hato & Masuo Kashiwadani, 2000. "Origin-destination matrices estimation model using automatic vehicle identification data and its application to the Han-Shin expressway network," Transportation, Springer, vol. 27(4), pages 419-438, December.
  26. Zhang, Michael & Nie, Yu & Shen, Wei & Lee, Ming S. & Jansuwan, Sarawut & Chootinan, Piya & Pravinvongvuth, Surachet & Chen, Anthony & Recker, Will W., 2008. "Development of A Path Flow Estimator for Inferring Steady-State and Time-Dependent Origin-Destination Trip Matrices," Institute of Transportation Studies, Research Reports, Working Papers, Proceedings qt3nr033sc, Institute of Transportation Studies, UC Berkeley.
  27. Cantelmo, Guido & Viti, Francesco & Cipriani, Ernesto & Nigro, Marialisa, 2018. "A utility-based dynamic demand estimation model that explicitly accounts for activity scheduling and duration," Transportation Research Part A: Policy and Practice, Elsevier, vol. 114(PB), pages 303-320.
  28. Guo, Jianhua & Liu, Yu & Li, Xiugang & Huang, Wei & Cao, Jinde & Wei, Yun, 2019. "Enhanced least square based dynamic OD matrix estimation using Radio Frequency Identification data," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 155(C), pages 27-40.
  29. K. Ashok & M. E. Ben-Akiva, 2000. "Alternative Approaches for Real-Time Estimation and Prediction of Time-Dependent Origin–Destination Flows," Transportation Science, INFORMS, vol. 34(1), pages 21-36, February.
  30. Osorio, Carolina & Punzo, Vincenzo, 2019. "Efficient calibration of microscopic car-following models for large-scale stochastic network simulators," Transportation Research Part B: Methodological, Elsevier, vol. 119(C), pages 156-173.
  31. Wu, Jifeng & Chang, Gang-Len, 1996. "Estimation of time-varying origin-destination distributions with dynamic screenline flows," Transportation Research Part B: Methodological, Elsevier, vol. 30(4), pages 277-290, August.
  32. Kumarage, Sakitha & Yildirimoglu, Mehmet & Zheng, Zuduo, 2023. "A hybrid modelling framework for the estimation of dynamic origin–destination flows," Transportation Research Part B: Methodological, Elsevier, vol. 176(C).
  33. Hjorth, Urban, 2002. "Traffic subflow estimation and bootstrap analysis from filtered counts," Transportation Research Part B: Methodological, Elsevier, vol. 36(4), pages 345-359, May.
  34. A. Stathopoulos & T. Tsekeris, 2003. "Framework for analysing reliability and information degradation of demand matrices in extended transport networks," Transport Reviews, Taylor & Francis Journals, vol. 23(1), pages 89-103, January.
  35. Cantelmo, Guido & Qurashi, Moeid & Prakash, A. Arun & Antoniou, Constantinos & Viti, Francesco, 2020. "Incorporating trip chaining within online demand estimation," Transportation Research Part B: Methodological, Elsevier, vol. 132(C), pages 171-187.
  36. Wu, Jifeng, 1997. "A real-time origin-destination matrix updating algorithm for on-line applications," Transportation Research Part B: Methodological, Elsevier, vol. 31(5), pages 381-396, October.
  37. Yong Lin, 2023. "Models, Algorithms and Applications of DynasTIM Real-Time Traffic Simulation System," Sustainability, MDPI, vol. 15(2), pages 1-30, January.
  38. Hu, Shou-Ren & Peeta, Srinivas & Chu, Chun-Hsiao, 2009. "Identification of vehicle sensor locations for link-based network traffic applications," Transportation Research Part B: Methodological, Elsevier, vol. 43(8-9), pages 873-894, September.
  39. M. Bierlaire & F. Crittin, 2004. "An Efficient Algorithm for Real-Time Estimation and Prediction of Dynamic OD Tables," Operations Research, INFORMS, vol. 52(1), pages 116-127, February.
  40. Yusen Chen & Henk J. van Zuylen & Wim van der Hoeven, 2010. "A Large-scale Urban Traffic Decision Support System with Dynamic Traffic Assignment," Chapters, in: Chris M.J. Tampere & Francesco Viti & Lambertus H. (Ben) Immers (ed.), New Developments in Transport Planning, chapter 17, Edward Elgar Publishing.
  41. Hjorth, U., 1999. "The inherent precision of regression estimated route probabilities," Transportation Research Part B: Methodological, Elsevier, vol. 33(8), pages 593-607, November.
  42. Chang, Gang-Len & Tao, Xianding, 1999. "An integrated model for estimating time-varying network origin-destination distributions," Transportation Research Part A: Policy and Practice, Elsevier, vol. 33(5), pages 381-399, June.
  43. Sherali, Hanif D. & Park, Taehyung, 2001. "Estimation of dynamic origin-destination trip tables for a general network," Transportation Research Part B: Methodological, Elsevier, vol. 35(3), pages 217-235, March.
  44. Zhou, Xuesong & Mahmassani, Hani S., 2007. "A structural state space model for real-time traffic origin-destination demand estimation and prediction in a day-to-day learning framework," Transportation Research Part B: Methodological, Elsevier, vol. 41(8), pages 823-840, October.
  45. Chi Xie & Jennifer Duthie, 2015. "An Excess-Demand Dynamic Traffic Assignment Approach for Inferring Origin-Destination Trip Matrices," Networks and Spatial Economics, Springer, vol. 15(4), pages 947-979, December.
  46. Simonelli, Fulvio & Marzano, Vittorio & Papola, Andrea & Vitiello, Iolanda, 2012. "A network sensor location procedure accounting for o–d matrix estimate variability," Transportation Research Part B: Methodological, Elsevier, vol. 46(10), pages 1624-1638.
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