Skip to Main content Skip to Navigation
New interface
Conference papers

P-ADRIP : un système multi-agent auto-organisateur pour la prévision du trafic routier

Abstract : Traffic forecasting has gained more and more interests in both academic and industrial research activities. Recently, many methods for traffic forecasting based on machine learning and deep learning approaches are proposed. However, these models always encounter the unsolved questions relating to the reliability and the feasibility. Indeed, traffic forecasting is a very challenging task due to the complex spatial correlations, the high-level time dependency and the difficulty of long-term prediction. To address the mentioned challenges, we propose a novel system based on multi-agent systems approach called P-ADRIP (Prediction subsystem - Adaptive multi-agent system for DRIving behaviors Prediction) that aims to provide dynamic and real-time traffic prediction. The conducted experiments demonstrate the outstanding performance of P-ADRIP comparing to the state-ofthe-art prediction methods.
Document type :
Conference papers
Complete list of metadata

https://hal.archives-ouvertes.fr/hal-03764716
Contributor : Ha-Nhi NGO Connect in order to contact the contributor
Submitted on : Tuesday, August 30, 2022 - 2:56:56 PM
Last modification on : Friday, October 14, 2022 - 10:38:47 AM

File

P_ADRIP___un_syst_me_multi_age...
Files produced by the author(s)

Identifiers

  • HAL Id : hal-03764716, version 1

Citation

Ha-Nhi Ngo, Elsy Kaddoum, Marie-Pierre Gleizes, Jonathan Bonnet, Goursolle Anaïs. P-ADRIP : un système multi-agent auto-organisateur pour la prévision du trafic routier. Journées Francophones sur les Systèmes Multi-Agents : SMA et Smart Cities (JFSMA 2022), Jun 2022, Saint-Etienne, France. ⟨hal-03764716⟩

Share

Metrics

Record views

39

Files downloads

6