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An analysis of the reliability of an origin-destination trip matrix estimated from traffic counts

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  1. Xing, Tao & Zhou, Xuesong & Taylor, Jeffrey, 2013. "Designing heterogeneous sensor networks for estimating and predicting path travel time dynamics: An information-theoretic modeling approach," Transportation Research Part B: Methodological, Elsevier, vol. 57(C), pages 66-90.
  2. Hyoshin (John) Park & Ali Haghani & Song Gao & Michael A. Knodler & Siby Samuel, 2018. "Anticipatory Dynamic Traffic Sensor Location Problems with Connected Vehicle Technologies," Service Science, INFORMS, vol. 52(6), pages 1299-1326, December.
  3. Patriksson, Michael, 2008. "On the applicability and solution of bilevel optimization models in transportation science: A study on the existence, stability and computation of optimal solutions to stochastic mathematical programs," Transportation Research Part B: Methodological, Elsevier, vol. 42(10), pages 843-860, December.
  4. Li, Xiaopeng & Ouyang, Yanfeng, 2011. "Reliable sensor deployment for network traffic surveillance," Transportation Research Part B: Methodological, Elsevier, vol. 45(1), pages 218-231, January.
  5. Xuesong Zhou & George F. List, 2010. "An Information-Theoretic Sensor Location Model for Traffic Origin-Destination Demand Estimation Applications," Transportation Science, INFORMS, vol. 44(2), pages 254-273, May.
  6. Fu, Hao & Lam, William H.K. & Shao, Hu & Ma, Wei & Chen, Bi Yu & Ho, H.W., 2022. "Optimization of multi-type sensor locations for simultaneous estimation of origin-destination demands and link travel times with covariance effects," Transportation Research Part B: Methodological, Elsevier, vol. 166(C), pages 19-47.
  7. 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).
  8. Yang, Yudi & Fan, Yueyue, 2015. "Data dependent input control for origin–destination demand estimation using observability analysis," Transportation Research Part B: Methodological, Elsevier, vol. 78(C), pages 385-403.
  9. Bera, Sharminda & Rao, K. V. Krishna, 2011. "Estimation of origin-destination matrix from traffic counts: the state of the art," European Transport \ Trasporti Europei, ISTIEE, Institute for the Study of Transport within the European Economic Integration, issue 49, pages 2-23.
  10. Hadavi, Majid & Shafahi, Yousef, 2016. "Vehicle identification sensor models for origin–destination estimation," Transportation Research Part B: Methodological, Elsevier, vol. 89(C), pages 82-106.
  11. Owais, Mahmoud & Moussa, Ghada S. & Hussain, Khaled F., 2019. "Sensor location model for O/D estimation: Multi-criteria meta-heuristics approach," Operations Research Perspectives, Elsevier, vol. 6(C).
  12. Lucio Bianco & Giuseppe Confessore & Monica Gentili, 2006. "Combinatorial aspects of the sensor location problem," Annals of Operations Research, Springer, vol. 144(1), pages 201-234, April.
  13. Xie, Chi & Kockelman, Kara M. & Waller, S. Travis, 2011. "A maximum entropy-least squares estimator for elastic origin–destination trip matrix estimation," Transportation Research Part B: Methodological, Elsevier, vol. 45(9), pages 1465-1482.
  14. Gomes, Gabriel C., 2004. "Optimization and Microsimulation of On-ramp Metering for Congested Freeways," Institute of Transportation Studies, Research Reports, Working Papers, Proceedings qt95k1q411, Institute of Transportation Studies, UC Berkeley.
  15. Liu, Jiangtao & Zhou, Xuesong, 2019. "Observability quantification of public transportation systems with heterogeneous data sources: An information-space projection approach based on discretized space-time network flow models," Transportation Research Part B: Methodological, Elsevier, vol. 128(C), pages 302-323.
  16. Chootinan, Piya & Chen, Anthony, 2011. "Confidence interval estimation for path flow estimator," Transportation Research Part B: Methodological, Elsevier, vol. 45(10), pages 1680-1698.
  17. Malik, Leeza & Tiwari, Geetam & Biswas, Udayin & Woxenius, Johan, 2021. "Estimating urban freight flow using limited data: The case of Delhi, India," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 149(C).
  18. Lo, Hong K. & Chen, Anthony & Castillo, Enrique, 2016. "Robust network sensor location for complete link flow observability under uncertaintyAuthor-Name: Xu, Xiangdong," Transportation Research Part B: Methodological, Elsevier, vol. 88(C), pages 1-20.
  19. Mínguez, R. & Sánchez-Cambronero, S. & Castillo, E. & Jiménez, P., 2010. "Optimal traffic plate scanning location for OD trip matrix and route estimation in road networks," Transportation Research Part B: Methodological, Elsevier, vol. 44(2), pages 282-298, February.
  20. Ehlert, Anett & Bell, Michael G.H. & Grosso, Sergio, 2006. "The optimisation of traffic count locations in road networks," Transportation Research Part B: Methodological, Elsevier, vol. 40(6), pages 460-479, July.
  21. Chen, Anthony & Chootinan, Piya & Recker, Will, 2009. "Norm approximation method for handling traffic count inconsistencies in path flow estimator," Transportation Research Part B: Methodological, Elsevier, vol. 43(8-9), pages 852-872, September.
  22. 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.
  23. M. Gentili & P. Mirchandani, 2005. "Locating Active Sensors on Traffic Networks," Annals of Operations Research, Springer, vol. 136(1), pages 229-257, April.
  24. Lucio Bianco & Giuseppe Confessore & Pierfrancesco Reverberi, 2001. "A Network Based Model for Traffic Sensor Location with Implications on O/D Matrix Estimates," Transportation Science, INFORMS, vol. 35(1), pages 50-60, February.
  25. Viti, Francesco & Rinaldi, Marco & Corman, Francesco & Tampère, Chris M.J., 2014. "Assessing partial observability in network sensor location problems," Transportation Research Part B: Methodological, Elsevier, vol. 70(C), pages 65-89.
  26. Fu, Hao & Lam, William H.K. & Shao, Hu & Kattan, Lina & Salari, Mostafa, 2022. "Optimization of multi-type traffic sensor locations for estimation of multi-period origin-destination demands with covariance effects," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 157(C).
  27. Abdullah Alshehri & Mahmoud Owais & Jayadev Gyani & Mishal H. Aljarbou & Saleh Alsulamy, 2023. "Residual Neural Networks for Origin–Destination Trip Matrix Estimation from Traffic Sensor Information," Sustainability, MDPI, vol. 15(13), pages 1-21, June.
  28. 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.
  29. Yang, Hai & Zhou, Jing, 1998. "Optimal traffic counting locations for origin-destination matrix estimation," Transportation Research Part B: Methodological, Elsevier, vol. 32(2), pages 109-126, February.
  30. Xiaopeng Li & Yanfeng Ouyang, 2012. "Reliable Traffic Sensor Deployment Under Probabilistic Disruptions and Generalized Surveillance Effectiveness Measures," Operations Research, INFORMS, vol. 60(5), pages 1183-1198, October.
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