Dynamic origin-destination matrix estimation for networks operating under free-flow conditions using macroscopic flow dynamics

Autor: Englezou, Yiolanda, Timotheou, Stelios, Panayiotou, Christos G.

Publikováno v: In IFAC PapersOnLine 2024 58(10):213-218

Simultaneous identification of sensor faults and origin-destination matrix estimation

Autor: Englezou, Yiolanda ^*, Timotheou, Stelios ^*, Panayiotou, Christos G. ^*

Publikováno v: In IFAC PapersOnLine 2022 55(6):151-156

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Bayesian Traffic State Estimation Using Extended Floating Car Data

Autor: Englezou Yiolanda, Kyriacou Victor, Panayiotou G. Christos, Timotheou Stelios

Traffic state estimation is a challenging task due to the collection of sparse and noisy measurements from specific points of the traffic network. The emergence of Connected and Automated Vehicles (CAVs) provides new capabilities for traffic state es

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=od______2659::a81d3e2fc62e524a64e351bc2c544aca
https://zenodo.org/record/7485921

Probabilistic traffic density estimation using measurements from Unmanned Aerial Vehicles

Autor: Englezou, Yiolanda, Timotheou, Stelios, Panayiotou, G. Christos

Publikováno v: Proceedings of the 2022 IEEE International Conference on Unmanned Aircraft Systems (ICUAS)
2022 International Conference on Unmanned Aircraft Systems (ICUAS)

Traffic state estimation (TSE) is an important task for traffic management, however it can be challenging due to the sparse deployment of traffic sensors in the network. The advancement of new technologies, such as the Unmanned Aerial Vehicles (UAVs)

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::41a315ca143ba7aff3f3a2c1872feb36
https://doi.org/10.1109/icuas54217.2022.9836098