On the generation of a variable structure airport surface traffic control system

Cover title.Includes bibliographical references (p. 23-24).Support provided by the U.S. Office of Naval Research. N00014-84-K-0519Jacques J. Demaël, Alexander H. Levis

Contribution to the evaluation and optimization of passengers' screening at airports

Security threats have emerged in the past decades as a more and more critical issue for Air Transportation which has been one of the main ressource for globalization of economy. Reinforced control measures based on pluridisciplinary research and new technologies have been implemented at airports as a reaction to different terrorist attacks. From the scientific perspective, the efficient screening of passengers at airports remain a challenge and the main objective of this thesis is to open new lines of research in this field by developing advanced approaches using the resources of Computer Science. First this thesis introduces the main concepts and definitions of airport security and gives an overview of the passenger terminal control systems and more specifically the screening inspection positions are identified and described. A logical model of the departure control system for passengers at an airport is proposed. This model is transcribed into a graphical view (Controlled Satisfiability Graph-CSG) which allows to test the screening system with different attack scenarios. Then a probabilistic approach for the evaluation of the control system of passenger flows at departure is developped leading to the introduction of Bayesian Colored Petri nets (BCPN). Finally an optimization approach is adopted to organize the flow of passengers at departure as best as possible given the probabilistic performance of the elements composing the control system. After the establishment of a global evaluation model based on an undifferentiated serial processing of passengers, is analyzed a two-stage control structure which highlights the interest of pre-filtering and organizing the passengers into separate groups. The conclusion of this study points out for the continuation of this theme

Abridged Petri Nets

A new graphical framework, Abridged Petri Nets (APNs) is introduced for bottom-up modeling of complex stochastic systems. APNs are similar to Stochastic Petri Nets (SPNs) in as much as they both rely on component-based representation of system state space, in contrast to Markov chains that explicitly model the states of an entire system. In both frameworks, so-called tokens (denoted as small circles) represent individual entities comprising the system; however, SPN graphs contain two distinct types of nodes (called places and transitions) with transitions serving the purpose of routing tokens among places. As a result, a pair of place nodes in SPNs can be linked to each other only via a transient stop, a transition node. In contrast, APN graphs link place nodes directly by arcs (transitions), similar to state space diagrams for Markov chains, and separate transition nodes are not needed. Tokens in APN are distinct and have labels that can assume both discrete values ("colors") and continuous values ("ages"), both of which can change during simulation. Component interactions are modeled in APNs using triggers, which are either inhibitors or enablers (the inhibitors' opposites). Hierarchical construction of APNs rely on using stacks (layers) of submodels with automatically matching color policies. As a result, APNs provide at least the same modeling power as SPNs, but, as demonstrated by means of several examples, the resulting models are often more compact and transparent, therefore facilitating more efficient performance evaluation of complex systems.Comment: 17 figure

Experiences of simulation use in industrial projects

This paper presents experiences obtained from our involvement in the development of industrial simulation projects. Some important, common questions are covered, such as the need to define model behavior using a conceptual model, the problem of choosing the appropriate tool to code the model, and the validation and verification process required. As we will see, the scope of applicability of simulation is broad and the tools are therefore diverse. A clear understanding of the objectives of the simulation, the client’s aims and the resources at our disposal are key issues that often determine the success of a simulation project.Peer ReviewedPostprint (published version

Simplifying the verification of simulation models through Petri net to FlexSim mapping

Simplifying the encoding of a simulation conceptual model representation reduces the number of errors that will be detected in the verification phase. In this paper, we present a mapping between Petri nets, a well-known formalism, and FlexSim, a well-known simulation tool. The proposal is illustrated through an example of how a model specified in a Petri net can be encoded easily, reducing the time needed to understand and verify the model. In the proposed methodology, the mapping must be defined at the initial stage of the encoding, starting from (in this case) a Petri net conceptual model, and ending at the encoding tool (FlexSim in this case). The main advantages of the proposed methodology are discussed.Peer ReviewedPostprint (author's final draft

Recent advances in petri nets and concurrency

CEUR Workshop Proceeding