2012
DOI: 10.2495/ut120311
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A fuzzy logic approach to modelling the passengers’ flow and dwelling time

Abstract: The passengers' flow and station dwell time estimation are important tasks for mass transit planning. However, classical methods are difficult to apply into some practical achievements. This paper presents a new approach that models passengers' flow and its effect on passenger alighting and boarding time in mass transportation systems in the presence of uncertainties. The applied technique combines origin destination matrices approach with the application of artificial intelligence. This new approach allows th… Show more

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Cited by 11 publications
(9 citation statements)
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“…This is an extension of existing studies [9]. Particularly, Niu and Zhou [10] and Niu et al [11] propose the concept of "effective loading time" that represents the actual time interval within which the arriving passengers can board a train.…”
Section: Introductionmentioning
confidence: 85%
“…This is an extension of existing studies [9]. Particularly, Niu and Zhou [10] and Niu et al [11] propose the concept of "effective loading time" that represents the actual time interval within which the arriving passengers can board a train.…”
Section: Introductionmentioning
confidence: 85%
“… Publications in scientific international congress [48][49][50][51]  Publications in scientific indexes journals [52][53]  Publications in international Professional magazines [54]  Publications in scientific-technical magazines [55][56][57] R&D Project: "Methodologies and Performance Indexes for railroad systems" [45][46][47] Construction of the content subject Fig. 2.…”
Section: Regional Link Between the Research And Teaching In The Umentioning
confidence: 99%
“…In this approach, triangular membership function levels are used. There are three basic levels of passenger flow: low, medium and high [15]. Figures 2 and 3 illustrate how the membership function levels describe the passenger's distribution in each car of the train according to the level of occupancy or preference.…”
Section: Fuzzy Inference Enginementioning
confidence: 99%
“…A fuzzy interference engine iteratively estimates the elements of the OD matrix based on the levels assigned to each station using the principle of maximum entropy. In [15], the authors consider an extended version of the OD matrix, including information of each car of the train. In this version of the algorithm, three levels of demand are assigned to each car of the trains in function of the preference of passengers for a given configuration of the platform geometry, access and location of facilities at each station.…”
Section: Introductionmentioning
confidence: 99%