978-1-4673-4766-2/12/$31.00 ©2012 IEEE A Multimodal Transportation System: Hybrid Petri Net-based Modeling and Simulation Faiza MAHI Oran University Oran, Algeria faiza_mahi2OO4@yahoo.fr Ahmed NAIT-SIDI-MOH Laboratory of Innovative Technologies University of Picardie Jules Verne, INSSET Saint Quentin, France ahmed.nait-sidi-moh@u-picardie.fr Fatima DEBBAT Mascara University Mascara, Algeria Fati_debbat@yahoo.fr Mohamed-Fayçal KHELFI Computer Science Department, Faculty of Sciences University of Oran Es-Sénia, Algeria Oran, Algeria mf_khelfi@yahoo.fr Abstract— The paper deals with the modeling and simulation of a public transportation system wherein passengers need to use more than one transportation mode for their moving. Many studies have been developed in the literature for such problematic, and many modeling tools are proposed. In this paper we focus on the use of hybrid Petri nets (HPN) and the mathematical techniques they propose for performance evaluation and minimization of passengers waiting times in connection stations. HPN is used as an adequate formal tool to model both continuous and discrete behavior of the considered system. The continuous behavior corresponds to the exchange of the passenger flows between two different transportation modes (bus and train). The discrete behavior represents the moving of transportation entities on their own lines. The system is evaluated and analyzed using the fundamental equation and its evolution is studied using IB-State techniques in HPN. The proposed approach is illustrated with a numerical example. Keywords: Multimodal Transportation System; Hybrid Petri net; Modelling and Evaluation. I. INTRODUCTION Multimodal transportation is a major component of contemporary economics in the world. It has to face with two challenges: a society that expects always more mobility and a public opinion that cannot bear any more chronic delays and the poor quality of the performance of some services. Indeed, the flexibility of individual transportation modes grew for some years whereas the public transport offer is not sometimes up to the demand. This partially explains the rise of urban traffic involving more pollution and risks of accidents. The development of multimodal transport is an alternative solution to reduce these risks. However, the behavior of this transportation mode is often extremely complex. The diversity of its transport means and the increasing number of vehicles and platforms using for passengers exchange is a direct consequence for the generation of several related issues, for example, congestion, management of connections, allocation of vehicles, traffic management, etc.. In this context and with the desire to offer a better service to users, our work focuses on the management, for optimization and improvement issues, of passenger flows in a multimodal transportation network. For doing so, we describe and analyze the behavior of many connections stops of a multimodal transport network. Multimodal transportation systems include continuous and discrete events simultaneously represented respectively by passenger flows and discrete quantities of transport vehicles (e.g. bus, train, taxi), Flows of passengers arriving at each connection stop. Considering these two behaviours, we aim, through this contribution, to establish a comprehensive and readable model that highlights different parts of the network. Therefore, our choice fell on HPN as a powerful modeling tool for systems with hybrid behaviors. It turned out that this tool allows to model hybrid system taking into account the connection complexity of different parts of such systems. In the field of multimodal transportation systems, several approaches have been used for modeling, simulation and evaluation. In [1], Zidi proposes an assistant decision system named SARR to assist the developers in their exploitation management tasks in the cases of complex and simultaneous disturbances. The author has proposed two approaches. The first one, named ACFRS (Ant Colony Algorithm for the spatial Reconfiguration, is based on ant colony for the spatial reconfiguration. The second one is developed for rescheduling and called ACFRH (Ant Colony for the Hourly Regulation). DSS, for Decision Support System, is a developed system enabling to provide a decision support for regulators [2]. Also,