A hybrid Petri nets-based simulation model for evaluating the design of railway transit stations

Kaakai, Fateh; Hayat, S.; Moudni, Abdellah El

doi:10.1016/j.simpat.2007.05.003

Cited by 69 publications

(35 citation statements)

References 25 publications

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“…Broadly, it can be distinguished between empirical studies (Daly et al, 1991;Cheung and Lam, 1998;Pettersson, 2011;Ganansia et al, 2014), and those concerned with its modeling (Lee et al, 2001;Daamen, 2004;Kaakai et al, 2007;Xu et al, 2014). A review of the literature is provided by Mustafa and Ashaari (2015).…”

Section: Introductionmentioning

confidence: 99%

“…Many studies are solely based on theoretical demand scenarios (Hoogendoorn and Daamen, 2004;Rindsfüser and Klügl, 2007;Davidich et al, 2013). Other studies rely on simple assumptions to estimate demand (Kaakai et al, 2007;van den Heuvel and Hoogenraad, 2014), or consider railway stations that serve only a single line (Lee et al, 2001;Xu et al, 2014). Yet knowledge of pedestrian demand is a prerequisite for the analysis of pedestrian flows in train stations, be it for the design of infrastructure, the optimization of operations such as the train-track assignment, or real-time management and control of pedestrian flows.…”

Section: Introductionmentioning

confidence: 99%

“…In the context of pedestrian flows in train stations, mode choice is irrelevant, and the choice of departure time is mainly governed by the train timetable, which is discussed in this work. A variety of approaches have been proposed for route choice (Cheung and Lam, 1998;Hoogendoorn and Bovy, 2004;Daamen et al, 2005), and for network loading models a rich literature is available as well (Lee et al, 2001;Daamen, 2004;Kaakai et al, 2007;Xu et al, 2014;Starmans et al, 2014). The problem of pedestrian OD demand estimation in train stations is thus in principle amenable to 'classical' estimation techniques.…”

Section: Introductionmentioning

confidence: 99%

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Estimation of Pedestrian Origin-Destination Demand in Train Stations

Hänseler

Molyneaux

Bierlaire

2017

Transportation Science

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1We present a framework for estimating pedestrian demand within a train station. It takes into account ridership data, and various direct and indirect indicators of demand. Such indicators may include link flow counts, density measurements, survey data, historical or other information. The problem is considered in discrete time and at the aggregate level, i.e., for groups of pedestrians associated with the same origin-destination pair and departure time interval. The formulation is probabilistic, allowing to consider the stochasticity of demand. A key element of the framework is the use of the train timetable to better capture demand peaks. A case study analysis of a Swiss train station underlines its practical applicability. Compared to a classical estimator that ignores the notion of a train timetable, the gain in accuracy in terms of RMSE is between 20% and 50%. More importantly, the incorporation of the train schedule allows for prediction when little or no data besides the timetable and ridership information is available.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Estimation of Pedestrian Origin-Destination Demand in Train Stations

Hänseler

Molyneaux

Bierlaire

2017

Transportation Science

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“…Reference [16] implied Colored Petri Nets to model the switch control of a railway system, and the project is to teach students to model the railway with up to five trains. Reference [17] presented a simulation model based on hybrid Petri Nets, which is able to help transit authorities to carry out performance evaluation procedures in order to prevent, reduce, and if possible avoid accidents of transit authorities. Reference [18] used interval Colored-Timed Petri Nets to model and analyze railway stations; the method constructed a reduced reachability graph and exploited the fact that delays were described by an interval.…”

Section: Introductionmentioning

confidence: 99%

A High-Speed Train Operation Plan Inspection Simulation Model

Yang

Mou

Jiang

2018

Mathematical Problems in Engineering

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We developed a train operation simulation tool to inspect a train operation plan. In applying an improved Petri Net, the train was regarded as a token, and the line and station were regarded as places, respectively, in accordance with the high-speed train operation characteristics and network function. Location change and running information transfer of the high-speed train were realized by customizing a variety of transitions. The model was built based on the concept of component combination, considering the random disturbance in the process of train running. The simulation framework can be generated quickly and the system operation can be completed according to the different test requirements and the required network data. We tested the simulation tool when used for the real-world Wuhan to Guangzhou high-speed line. The results showed that the proposed model can be developed, the simulation results basically coincide with the objective reality, and it can not only test the feasibility of the high-speed train operation plan, but also be used as a support model to develop the simulation platform with more capabilities.

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“…The system can be simulated with little or no investment, and the optimal plan can be obtained by constantly modifying the parameters. Therefore, simulation modelling is an effective way to handle the complex production process [3,4]. Currently, simulation modelling methods for complex systems mainly include queuing network modelling [5], bottleneck shifting modelling of production logistics [6], influence net modelling [7], inventory control modelling [8][9][10], and Petri net based simulation modelling [11,12].…”

Section: Introductionmentioning

confidence: 99%

Simulation of Steel Production Logistics System Based on Multi-Agents

Zhao¹,

Wang²,

Xu³

2017

Int. j. simul. model.

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To deal with the complex structure and difficulty in precise expression of the interaction between entities in the steel production logistics system, this paper uses complex network theory and multiagent system engineering to simulate the complex steel production logistics system, and thereby calculate related parameters, gather statistics, and optimize the steel production logistics system. According to the analysis, the processing of logistics is low in efficiency because 19 pieces of equipment are involved from the beginning of the logistics subject processing to the final formation of steel, while only a few processes are required for about half of the auxiliary material or auxiliary process. The system logistics is not compact because most of the equipment used in steel production has only a single function and a limited service area, whereas a higher degree distribution indicates a higher importance in a piece of equipment in the network. This is a must to guarantee the normal operation of the equipment with a higher degree distribution. The simulation results are basically the same with the actual production results, and the error is within the acceptable range, which proves that the simulation system is correct and effective.

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A hybrid Petri nets-based simulation model for evaluating the design of railway transit stations

Cited by 69 publications

References 25 publications

Estimation of Pedestrian Origin-Destination Demand in Train Stations

Estimation of Pedestrian Origin-Destination Demand in Train Stations

A High-Speed Train Operation Plan Inspection Simulation Model

Simulation of Steel Production Logistics System Based on Multi-Agents

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