Skip navigation
Please use this identifier to cite or link to this item: https://repository.esi-sba.dz/jspui/handle/123456789/643
Title: Graph Based Learnig For Multimodal Route Recommendation
Authors: DAOUD, BRahim
Keywords: Multimodal Route Recommendation
Graph-Based Learning
Climate-Aware Routing
Real-Time Traffic Data
User Preference Modeling
High-Fidelity Transportation Graph
Sustainable Transport
Mobility Optimization
Issue Date: 2024
Abstract: In this engineering thesis, a practical system is presented for recommending multimodal transport routes for students of the CESI campus in France as part of the ”MonTrajet Vert” project, with a focus on user comfort and environmental sustainability. The system is designed to optimize travel routes by integrating various modes of transport such as buses, trains, and bicycles within a synthesized multimodal transport graph. The project is divided into two main stages: the first stage involves creating a set of synthetic data and developing a transport graph that accurately reflects the real network. The second stage focuses on applying advanced machine learning algorithms to this graph, providing route recommendations that consider factors such as real-time traffic conditions, climate impact, and seasonal variations. To enhance the reliability and applicability of the recommendations, real-time traffic data has been integrated, and comprehensive testing has been conducted using the Strasbourg transport network. The system has been evaluated in various scenarios, demonstrating its robustness and effectiveness in providing accurate and environmentally friendly travel routes. This report describes the technical details of implementing the system, including data integration, algorithm development, and performance evaluation. The results underscore the importance of incorporating environmental considerations into urban transport planning, highlighting the system’s potential to contribute to more sustainable and user-friendly transport solutions. *** Dans cette th`ese d’ing´enierie , un syst`eme pratique pour recommander des itin´eraires de transport multimodal pour les ´etudiants du campus CESI en France est pr´esent´e comme partie du projet ”MonTrajet Vert”, avec un accent sur le confort des utilisateurs et la durabilit´e environnementale. Le syst`eme est con¸cu pour optimiser les itin´eraires de voyage en int´egrant divers modes de transport tels que les bus, les trains et les v´elos au sein d’un graphe de transport multimodal synth´etis´e. Le projet est divis´e en deux principales ´etapes : la premi`ere consiste `a cr´eer un ensemble de donn´ees synth´etiques et `a d´evelopper un graphe de transport qui refl`ete fid`element le r´eseau r´eel. La deuxi`eme se concentre sur l’application d’algorithmes avanc´es d’apprentissage automatique `a ce graphe, fournissant des recommandations d’itin´eraires prenant en compte des facteurs tels que les conditions de trafic en temps r´eel, l’impact climatique et les variations saisonni`eres. Pour am´eliorer la fiabilit´e et l’applicabilit´e des recommandations, des donn´ees de trafic en temps r´eel ont ´et´e int´egr´ees et des tests approfondis ont ´et´e r´ealis´es en utilisant le r´eseau de transport de Strasbourg. Le syst`eme a ´et´e ´evalu´e dans divers sc´enarios, d´emontrant sa robustesse et son efficacit ´e dans la fourniture d’itin´eraires de voyage pr´ecis et respectueux de l’environnement. Ce rapport d´ecrit les d´etails techniques de la mise en oeuvre du syst`eme, y compris l’int´egration des donn´ees, le d´eveloppement algorithmique et l’´evaluation des performances. Les r´esultats soulignent l’importance d’incorporer des consid´erations environnementales dans la planification des transports urbains, mettant en ´evidence le potentiel du syst`eme pour contribuer `a des solutions de transport plus durables et conviviales.
Description: Supervisor : Mr. KHALDI Belkacem / Mr. Zakaryia Ghalmane
URI: https://repository.esi-sba.dz/jspui/handle/123456789/643
Appears in Collections:Ingenieur

Files in This Item:
File Description SizeFormat 
Engeneering The Last-1-1.pdf60,44 kBAdobe PDFView/Open
Show full item record


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.