A FUZZY LOGIC INFERENCE APPROACH FOR THE ESTIMATION OF THE PASSENGERS FLOW DEMAND

Aránzazu Berbey Alvarez, Rony Caballero George, Juan de Dios Sanz Bobi, Ramón Galán López

2010

Abstract

This paper presents a new approach that designs the flow of passengers in mass transportation systems in presence of uncertainties. One of the techniques used for the prediction of passenger demand is the origin-destination matrices. However, this method is limited to urban areas and rarely to explicit stations. Otherwise, the gravity models based on friction functions can be another alternative; however, it is difficult to fit into practical achievements. Another solution might be the application of artificial intelligence techniques so as to include some intuitive knowledge provided by an expert to predict the flow demand of passengers’ trips in explicit stations. This paper proposes to combine a matrix of origin-destination trips of travel zones, with the intuitive knowledge, applying a fuzzy logic inference approach.

References

  1. Cheng, Y.H. y Yang, Li-An, 2009. A Fuzzy Petri Nets approach for railway traffic control in case of abnormality: Evidence from Taiwan railway system. Expert Systems with Applications 36 (2009) 8040- 8048.
  2. Lindaren, R. y Tantiyanugulchai, S., 2003. Microscopic Simulation of Traffic at a Suburban Interchange.
  3. Watson, J. R. y Prevedouros, P. D., 2006. Derivation of Origin-Destination Distributions from Traffic Counts Implications for Freeway Simulation. Transportation Research Record: Journal of the Transportation Research Board,No. 1964, Transportation Research Board of the National Academies, Washington, D.C., 2006, pp. 260-269.
  4. S. Kikuchi y D. Miljkovic., 1999. Method To Preprocess Observed Traffic Data for Consistency Application of Fuzzy Optimization Concept. Transportation Research Record 1679 Paper No. 99-0129 73.
  5. Aldian, A y Taylor, M., 2003. Fuzzy multicriteria analysis for inter-city travel demand modelling. Journal of the Eastern Asia Society for Transportation Studies, Vol. 5, October, 2003.
  6. C. H. Murat., 2010. Sample size needed for calibrating trip distribution and behaviour of the gravity model. Journal of Transport Geography 18,183-190.
  7. C. Xie, K.M. Kockelman y S.T. Waller., 2010. A maximum entropy method for subnetwork origindestination 1 trip matrix estimation. The 89th Annual Meeting of the Transportation Research Board, January 2010 in Washington, DC, and for publication in Transportation Research Record. 2010.
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Paper Citation


in Harvard Style

Berbey Alvarez A., Caballero George R., de Dios Sanz Bobi J. and Galán López R. (2010). A FUZZY LOGIC INFERENCE APPROACH FOR THE ESTIMATION OF THE PASSENGERS FLOW DEMAND . In Proceedings of the International Conference on Fuzzy Computation and 2nd International Conference on Neural Computation - Volume 1: ICFC, (IJCCI 2010) ISBN 978-989-8425-32-4, pages 125-129. DOI: 10.5220/0003057701250129


in Bibtex Style

@conference{icfc10,
author={Aránzazu Berbey Alvarez and Rony Caballero George and Juan de Dios Sanz Bobi and Ramón Galán López},
title={A FUZZY LOGIC INFERENCE APPROACH FOR THE ESTIMATION OF THE PASSENGERS FLOW DEMAND},
booktitle={Proceedings of the International Conference on Fuzzy Computation and 2nd International Conference on Neural Computation - Volume 1: ICFC, (IJCCI 2010)},
year={2010},
pages={125-129},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0003057701250129},
isbn={978-989-8425-32-4},
}


in EndNote Style

TY - CONF
JO - Proceedings of the International Conference on Fuzzy Computation and 2nd International Conference on Neural Computation - Volume 1: ICFC, (IJCCI 2010)
TI - A FUZZY LOGIC INFERENCE APPROACH FOR THE ESTIMATION OF THE PASSENGERS FLOW DEMAND
SN - 978-989-8425-32-4
AU - Berbey Alvarez A.
AU - Caballero George R.
AU - de Dios Sanz Bobi J.
AU - Galán López R.
PY - 2010
SP - 125
EP - 129
DO - 10.5220/0003057701250129