Modeling and Supervisory Control of Urban Traffic Flows in Medium-sized Cities Using Hybrid Approach

Modeling and Supervisory Control of Urban Traffic Flows in Medium-sized Cities Using Hybrid Approach

Bilal Tolbi* Fares Bouriachi Hicham Zatla

Department of Automatic, University of Sidi Bel-Abbes, BP 89, Sidi Bel-Abbes 22000, Algeria

Department of Instrumentation and control, USTHB, BP 32, Algiers 16111, Algeria

Laboratoire d’Automatique et Informatique de Guelma (LAIG), University of Guelma, Guelma 24000, Algeria

Laboratoire d’Automatique de Tlemcen (LAT), University of Tlemcen, Tlemcen 13000, Algeria

Corresponding Author Email: 
bilal.tolbi@univ-sba.dz
Page: 
171-178
|
DOI: 
https://doi.org/10.18280/ria.340207
Received: 
19 December 2019
|
Accepted: 
10 February 2020
|
Published: 
10 May 2020
| Citation

OPEN ACCESS

Abstract: 

This paper presents an optimal supervisory control technique of urban traffic flows, through a hybrid modeling approach of two phases intersections in medium-sized cities. These last are considered as a multi-agent system, this system is made up of all agents who represent all physical spaces of the urban traffic network. The behaviors of interconnected agents are supervised by Timed Petri Nets that control the traffic light cycles according to an optimal timing plan defined by the Continuous Genetic Algorithm and it can be used to estimate the delay of vehicles. A real intersection in Sidi Bel-Abbes City is presented as an example. The proposed timing plan is compared with the current one using SUMO software for the most important objective functions. Also, the proposed model’s behavior is compared with TSIS-CORSIM software’s model, and all obtained experiments results show the effectiveness of the approach and its possibility to be extended and applied to a many-phases intersection.

Keywords: 

supervisory control, modeling, traffic flow, genetic algorithm, Petri net, timing plan, multi-agent system

1. Introduction
2. Timed Petri Nets Definition
3. Problem Formulation in Mas
4. Hybrid Model Presentation
5. Case Study
6. Timing Optimization Problem
7. Experiments Results
8. Conclusions
Acknowledgment