Publications

Benoît Matet, Etienne Côme, Angelo Furno, Sebastian Hörl, Latifa Oukhellou. Use of Origin-Destination data for calibration and spatialization of synthetic travel demand. hEART'23. 11th Symposium of the European Association for Research in Transportation, Sep 2023, Zurich (CH), Switzerland. ⟨hal-04201484⟩.

Benoit Matet, Angelo Furno, Marco Fiore, Etienne Côme, Latifa Oukhellou. Adaptative generalisation over a value hierarchy for the k -anonymisation of Origin–Destination matrices. Transportation research. Part C, Emerging technologies, 2023, 154, pp.104236. ⟨10.1016/j.trc.2023.104236⟩. ⟨hal-04302102⟩.

Angelo Furno. Data-driven Approaches for Enhancing Resilience in Large-scale Transport Networks: A journey through data analysis, traffic modelling, complex networks and flexible software architectures for resilient and sustainable cities. Computer Science [cs]. ENTPE, University Claude Bernard Lyon 1 - HDR Thesis, 2023. ⟨tel-04462782⟩.

Benoît Matet, Etienne Come, Furno Angelo, Loïc Bonnetain, Latifa Oukhellou, et al.. A lightweight approach for origin-destination matrix anonymization. ESANN 2021, The 29th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning, Oct 2021, Bruges, Belgium. pp 487-492, ⟨10.14428/esann/2021.ES2021-56⟩. ⟨hal-03922211⟩.

Benoît Matet, Etienne Côme, Angelo Furno, Sebastian Hörl, Latifa Oukhellou, and Nour-Eddin El Faouzi. Improving the generation of synthetic travel demand using origin–destination matrices from mobile phone data. Transportation, September 2024. doi: 10.1007/s11116-024-10524-2. https://hal.science/hal-04692975.

Milena Suarez Castillo, Francois Sémécurbe, Cezary Ziemlicki, Haixuan Xavier Tao, and Tom
Seimandi. Temporally Consistent Present Population from Mobile Network Signaling Data for Official Statistics. Journal of Official Statistics, 39(4):535–570, 2023. doi: 10.2478/jos-2023-0025. https://hal.science/hal-05024940.

Romain Rochas, Angelo Furno, and Nour-Eddin El Faouzi. Contextual Data Integration for Bikesharing Demand Prediction with Graph Neural Networks in Degraded Weather Conditions. In 2023 IEEE 26th International Conference on Intelligent Transportation Systems (ITSC), pages 5436 – 5441, Bilbao, Spain, September 2023. IEEE. doi: 10.1109/itsc57777.2023.10422448. https://hal.science/hal-04796111.

Ali Shateri Benam, Angelo Furno, and Nour-Eddin El Faouzi. A Signature-based Approach for Datadriven Analysis of the Inter-modal Demand Dynamics. In International Conference on Models and Technologies for Intelligent Transportation Systems (MT-ITS), pages 1 – 6, Nice, France, June 2023. doi: 10.1109/mt-its56129.2023.10241701. https://hal.science/hal-04796339.