FONDUL SOCIAL EUROPEAN

Transcription

1 Investeşte în oameni! FONDUL SOCIAL EUROPEAN Programul Operaţional Sectorial pentru Dezvoltarea Resurselor Umane Axa prioritară: 1 Educatie si formare profesionala in sprijinul dezvoltarii si cresterii economice Domeniul major de intervenţie: 1.5 Programe doctorale si postdoctorale in sprijinul cercetarii Titlul proiectului: Proiect de dezvoltare a studiilor de doctorat in tehnologii avansate- PRODOC Cod Contract: POSDRU 6/1.5/S/5 Beneficiar: Universitatea Tehnica din Cluj-Napoca FACULTY of AUTOMATION and COMPUTER SCIENCE Math. Maria-Magdalena SANTA PhD Tesis DYNAMIC RESOURCE ALLOCATION FOR TRAIN TRAFFIC CONTROL Abstract Scientific Coordinator, PhD.Prof.Eng. Tiberiu LEŢIA

2 Table of contents (romanian) Cuprins Lista figurilor Lista tabelelor Capitolul 1. Introducere 1.1 Problema traficului feroviar 1.2 Necesitatea îmbunătăţirii controlului traficului feroviar 1.3 Obiectivele tezei 1.4 Conţinutul tezei Capitolul 2. Stadiul actual al cunoaşterii în domeniul aferent temei propuse 2.1 Organizarea traficului feroviar 2.2 Proiecte pentru modernizarea căilor ferate Stadiul în România Stadiul în Uniunea Europeană Stadiul actual al controlului traficului feroviar Proiectul Sistem inteligent de timp real pentru gestionare, control şi informare destinat traficului feroviar 2.3 Modele folosite pentru informatizarea proceselor Sisteme de comunicaţie folosite Sisteme de timp real Sisteme distribuite Agenţi inteligenţi şi sisteme multi-agent Limbajul UML şi RT-UML Algoritmi genetici Sisteme expert Reţele Petri Reţele de reguli 2.4 Calitatea serviciilor Capitolul 3. Rezoluţia temporală în diferite medii Java 3.1 Introducere 3.2 Definirea problemei abaterilor temporale 3.3 Rezoluţia temporală în diferite medii Java Testarea rezoluţiei temporale în Java Rezultatele testelor 3.4 Măsurarea deviaţiilor pentru solicitările periodice de planificare Arhitectura sistemului de testare Rezultatele experimentale ale testului pentru măsurarea deviaţiilor de sincronizare Testarea defectului de sincronizare în portul serial pentru sistemul Windows Vista 3.5 Concluzii Capitolul 4. Alocarea dinamică a resurselor şi controlul traficului feroviar 4.1 Elemente de construcţie a infrastructurii feroviare 4.2 Controlul traficului feroviar 4.3 Problema alocării resurselor 2

3 4.4 Alocarea dinamică a resurselor 4.5 Controlul în buclă deschisă cu controlere independente 4.6 Controlul în buclă închisă cu controlere independente 4.7 Controlul în buclă închisă cu controlere coordonate 4.8 Controlul în buclă închisă cu controlere cooperative 4.9 Teste şi verificări 4.10 Concluzii şi rezultate Capitolul 5. Planificarea trenurilor cu algoritmi genetici 5.1 Introducere 5.2 Modelarea reţelei de cale ferată cu reţele Petri temporizate 5.3 Planificarea trenurilor cu algoritmi genetici 5.4 Evaluarea performanţelor sistemului de alocare dinamică 5.5 Teste şi rezultate 5.6 Concluzii Capitolul 6. Sisteme multi-agent în planificarea trenurilor 6.1 Introducere 6.2 Planificarea trenurilor cu ajutorul agenţilor 6.3 Arhitectura sistemului multi-agent pentru calea ferată 6.4 Comportamentul agenţilor de tren 6.5 Algoritmul pentru planificarea trenului 6.6 Negocierea dintre agenţi 6.7 Negocierea cu un agent broker Capitolul 7. Planificarea trenurilor cu sisteme expert distribuite 7.1 Introducere 7.2 Arhitectura sistemului 7.3 Specificaţiile sistemului de control 7.4 Planificarea trenurilor cu reţele de reguli temporale 7.5 Algoritmul de găsire a căilor posibile pentru un tren 7.6 Algoritmul pentru planificarea unui tren 7.7 Algoritmul genetic pentru ghidarea planificării 7.8 Protocolul de comunicare între sistemele expert 7.9 Teste şi rezultate 7.10 Concluzii Capitolul 8. Concluzii finale şi contribuţii personale. 8.1 Avantajele şi dezavantajele sistemelor distribuite 8.2 Contribuţii conceptuale 8.3 Contribuţii de proiectare şi implementare Referinţe Anexa 1: Reţeaua Petri pentru controlul traficului feroviar cu buclă deschisă Anexa 2: Reţeaua Petri pentru controlul traficului cu buclă închisă şi controlere independente Anexa 3: Alocarea statică a resurselor în controlul traficului Anexa 4: Alocarea dinamică a resurselor în controlul traficului Anexa 5:Regulile pentru staţia A, Regulile pentru staţia B Anexa 6: Lucrări publicate 3

4 Chapter 1: Introduction In this chapter the motivation for developing this thesis is presented. It is also presented a resume of the thesis chapters. The main goals is developing solutions for control problem for railway traffic. Chapter 2: The current state of knowledge in relevant areas to the proposed theme The railway traffic organization and projects to modernize railways are presented. Models used for computerization process are presented in general with a special attention to those used in this thesis. The project Inteligent real time system for management, control and information for railway traffic control is also presented. Chapter 3: Temporal Resolution in Java and RTJava This chapter proposes a set of experiments, performed on different Java (Standard and Real Time) Virtual Machines running on several system configurations, in order to determine the JVMs temporal resolution. Another set of experiments, performed on the same platforms, in order to evaluate systems jitter while writing on serial port, are being described. The motivation for performing these tests is to evaluate the accuracy of control algorithm implementation in Java and RTJava. Chapter 4: Dynamic resource allocation and train traffic control The railway traffic control problem is solved using the resource allocation. The trains are considered tasks with specified temporal behaviors that have to fulfill their deadlines. The solutions based on open loop, closed loop with independent, coordinated and heterarchical controllers are defined and compared. The control signals are implemented and verified using time Petri nets. Some algorithms for control system implementation are given. The method evaluations are performed using the meter functions: utility, utilization, reservation and efficiency. The results obtained through simulations show that the proposed distributed controllers solve adequately the control problems and can be used for large scale implementation. Chapter 5: Genetic algorithm for trains scheduling The train traffic control problem is approached from the point of view of dynamic scheduling of resource allocation. The asynchronous train arrival times due to unexpected delays or previously unscheduled (charter) trains is considered. The train scheduling problem is solved using genetic algorithms. The chromosome specifies direction and waiting time of each train at its entrance in each interlocking. The railway network model is obtained by modeling the interlockings with Delay Time Petri Nets (DTPNs). The genetic algorithms are used for off-line scheduling of a set of trains in an empty railway structure, and for on-line scheduling adding a new set of trains in a crowded railway structure. Chapter 6: Multiagent systems for train scheduling For solving distributed problems are involving train agents with some degrees of autonomy and rationality capability. This field of study contains models for both decision- 4

5 making and negotiation activities between trading parties. As a result, it provides a potentially viable algorithm to modelling the transaction between train agents. The proposed method does not lead to deadlock due advance resource reservation. It has the advantage to apply on line and so it is able to diminish the variations of the train arrival times. The scheduling algorithm performances can be evaluated compute sum of all trains costs in a period. The proposed method can be used to design the railway networks such that to be capable of providing a specified throughput with real time feature. This paper highlights the benefits of applying agent technology to rail transportation system modeling. The on-board equipment with some intelligence enhances the autonomy of the train, simplifies the structure and reduces the equipment. The business and engineering activities in a rail system shown to provide an appropriate platform for agent application. The suitability of agent architecture and structure for system behavior studies has also been discussed. Such an approach can be seen as a catalyst to induce further work on the development of appropriate agent structures for modeling rail transportation and hence to promote the adoption of advance software techniques in railway management and operation. Chapter 7: Dynamic expert systems for trains scheduling The trains are considered tasks with specified temporal behaviors that have to fulfill their deadlines. The solutions are found with distributed expert systems. The control signals are implemented and verified using temporal Rule Nets, which are a formalism that seeks to express an automatism in a similar way to a human being: "IF conditions THEN actions. The results obtained through simulations show that the proposed distributed controllers solve the control problems and can be used for large scale implementation. A new algorithm for online train (task) scheduling is presented. The path and timelines for the train that is to be scheduled are found while the train is waiting in the departure station. Each station has an expert system that governs the allocation of resources within the station s territory. The border between two stations usually consists of one or several lines. The expert system in the departure station uses rule nets to determine the possible routes from departure point to the border between the departure and destination stations. The possible paths are ordered by the time the trains arrives at the border. The border line and time are sent to the expert system of the destination station, which finds a path and timelines that routes the train from the border to the destination. When such a path is found, the expert system sends the approval message, and the two paths and their timelines are added to the resource tables of each station. The train is then free to follow the path. By this algorithm, it is obvious that deadlocks are avoided implicitly when the approval message is sent. However, if the train does not follow the schedule, the path has to be rescheduled in order to guarantee deadlock avoidance. In that situation, the priority is deadlock avoiding rather than deadline fulfilling. are: Chapter 8: Final conclusions and personal contributions In this chapter the important and original contributions of this thesis are presented which - Designing a graphical model for representing railway networks; 5

6 - Developing of a distributed architecture for railway traffic control; - Controler with open loop, closed loop with independent, coordinated and heterarchical controllers are defined and compared; - Genetic algorithms for traffic control have been introduced; -Some Delay Timed Petri Nets and temporal Rule nets models of the railway traffic are realized. -Based on the design model of the processes simulation programs where design, implemented and tested to be used further for traffic resource allocation. 6