Using a multi-agent approach to optimise the train coupling and sharing system

Böcker, J.; Lind, Jürgen; Zirkler, Bernd

doi:10.1016/s0377-2217(00)00124-7

Cited by 46 publications

(21 citation statements)

References 3 publications

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“…Cuppari et al [9] employ a logic programming-based environment to prototype a MAS for the management of freight train traffic. The work presented in [4] uses a multiagent approach to the scheduling system for train coupling and sharing. The system is incremental, takes incomplete task specifications into account and generates an initial plan using the contract net protocol: then the post-optimization of the initial solution is achieved by means of the simulated trading protocol.…”

Section: Related Workmentioning

confidence: 99%

Exploiting MAS-Based Simulation to Improve the Indian Railways’ Efficiency

Ghosh

Dutta

Mascardi

et al. 2013

Multiagent System Technologies

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Abstract. Despite being one of the world's largest railways networks, with a daily transportation of over 25 million passengers and 2.8 million tons of freight, the Indian Railways perform their signaling, traffic management and trains scheduling activities in a completely manual way.The lack of automation causes not only significant delays, but also frequent collisions where passengers die or remain seriously injured.This paper describes how we modeled the Indian Railways system as a MAS and the results of the simulations run using NetLogo on real data retrieved from the Indian Railways dataset. The simulated system isunder some assumptions -collision-free and, thanks to the integration of the MAX-SUM algorithm, minimizes the individual train delay.

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Section: Related Workmentioning

confidence: 99%

Exploiting MAS-Based Simulation to Improve the Indian Railways’ Efficiency

Ghosh

Dutta

Mascardi

et al. 2013

Multiagent System Technologies

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“…These units may be completely different: drivers, trains, signals, but all of them have a high degree of autonomy, actively perceive the environment and act upon that environment. Owing to these characteristics, many systems in this domain are developed based on an agent approach [11,12]. Vernazza and Zunino [13] proposed a methodology which is to use Distributed Artificial Intelligence techniques to overcome the limitation of the centralized methodologies.…”

Section: Design Of Train Control Systems By Agentsmentioning

confidence: 99%

A framework for modeling train control systems based on agent and cellular automata

Xun

Ning

Tang

2010

WIT Transactions on the Built Environment

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A train control system is a system that is geographically and functionally distributed. Its subsystems have a high degree of autonomy. Because of these characteristics, this paper describes a two-layer framework for modeling train control systems. The upper-layer is defined by agents. The lower-layer is the cellular automata (CA) traffic model to simulate the train following dynamic. The CA model delivers the knowledge needed by the agents to make decisions. The interaction between agents can describe the decision-making processes of train control systems to achieve its functions. Its functions are classified into three levels: Service Control Functionality, Signaling Functionalities and Train Operation Functionality. A case study is used to illustrate the applicability of the proposed framework. The study results show that the proposed framework can be successfully used to analyze the influence on traffic flow, which is caused by the train control system.

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“…There exist many research activities in the same field based on various modelling and analysis approaches. But most of existing works about planning and/or performance evaluation of transportation systems mainly concern railway networks in a periodic working case (Braker, 1991); Bussieck et al (1997); De Vries et al (1998);Olsder et al (1998) ; Böcker et al (2001). Such systems are synchronized ones as trains have to wait for each other so as to prevent passengers from missing their connection.…”

Section: Introductionmentioning

confidence: 99%

Spectral analysis for performance evaluation in a bus network

Nait-Sidi-Moh

Manier

Moudni

2009

European Journal of Operational Research

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This paper deals with the performance evaluation of a public transportation system in terms of waiting times at various connection points. The behaviour of a bus network is studied in the framework of Discrete Event Systems (DES). Two possible operating modes of buses can be observed at each connection stop: periodic and nonperiodic mode. Two complementary tools, Petri nets and (max, +) algebra, are used to describe the network by a non stationary linear state model. This one can be solved after solving the structural conflicts associated to the graphical representation. From the characteristic matrix of the mathematical model, we determine eigenvalues and eigenvectors that we use to evaluate the connection times of passengers. This work is finally illustrated with a numerical example.

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Using a multi-agent approach to optimise the train coupling and sharing system

Cited by 46 publications

References 3 publications

Exploiting MAS-Based Simulation to Improve the Indian Railways’ Efficiency

Exploiting MAS-Based Simulation to Improve the Indian Railways’ Efficiency

A framework for modeling train control systems based on agent and cellular automata

Spectral analysis for performance evaluation in a bus network

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