M
Manuel Bullejos
Researcher at Polytechnic University of Catalonia
Publications - 20
Citations - 340
Manuel Bullejos is an academic researcher from Polytechnic University of Catalonia. The author has contributed to research in topics: Kalman filter & Geology. The author has an hindex of 9, co-authored 15 publications receiving 274 citations.
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Journal ArticleDOI
Towards a generic benchmarking platform for origin–destination flows estimation/updating algorithms: Design, demonstration and validation
Constantinos Antoniou,Jaume Barceló,Martijn Breen,Manuel Bullejos,Jordi Casas,Ernesto Cipriani,Biagio Ciuffo,Tamara Djukic,Serge P. Hoogendoorn,Vittorio Marzano,Lidia Montero,Marialisa Nigro,Josep Perarnau,Vincenzo Punzo,Tomer Toledo,Hans van Lint +15 more
TL;DR: A common evaluation and benchmarking framework is proposed, providing a synthetic test bed, which enables implementation and comparison of OD estimation/updating algorithms and methodologies under “standardized” conditions.
Journal ArticleDOI
A Kalman Filter Approach for Exploiting Bluetooth Traffic Data When Estimating Time-Dependent OD Matrices
TL;DR: Ad hoc, Kalman filtering procedures that explicitly exploit Bluetooth sensor traffic data are presented and the numerical results from computational experiments performed at a network test site are reported.
A Kalman Filter Approach for the Estimation of Time Dependent OD Matrices Exploiting Bluetooth Traffic Data Collection
TL;DR: Ad hoc procedures based on Kalman Filtering, explicitly exploiting traffic data available from Bluetooth sensors, have been designed and implemented successfully and the numerical results of the computational experiments are discussed for freeway and network test sites.
Journal ArticleDOI
Robustness and Computational Efficiency of Kalman Filter Estimator of Time-Dependent Origin–Destination Matrices: Exploiting Traffic Measurements from Information and Communications Technologies
TL;DR: The results of a set of computational experiments with a microscopic simulation of the network of Barcelona's central business district that explore the sensitivity of the Kalman filter estimates in relation to design factor values are presented.
Advanced traffic data for dynamic OD demand estimation: the state of the art and benchmark study
Tamara Djukic,Jaime Barceló Bugeda,Manuel Bullejos,Lídia Montero Mercadé,Ernesto Cipriani,Hans van Lint,Serge P. Hoogendoorn +6 more
TL;DR: A common feature observed by methods indicates that advanced traffic data require more research attention and new techniques to turn them into usable information.