Please use this identifier to cite or link to this item: http://hdl.handle.net/10553/54889
Title: Hierarchical interval type-2 Beta Fuzzy Knowledge Representation system for path preference planning
Authors: Zouari, Mariam
Baklouti, Nesrine
Kammoun, Habib
Sanchez-Medina, Javier 
Ben Ayed, Mounir
Alimi, Adel M.
UNESCO Clasification: 120326 Simulación
332907 Transporte
Keywords: Interval Type-2 Beta Fuzzy Logic System
Traffic congestion
Route choice
Traffic simulation
Knowledge representation
Issue Date: 2017
Publisher: 1098-7584
Journal: IEEE International Conference on Fuzzy Systems 
Conference: 2017 IEEE International Conference on Fuzzy Systems, FUZZ 2017 
Abstract: Traffic congestion leads to many problems, namely road users' dissatisfaction, air pollution and waste of time and fuel. For this reason, congestion detection at an early stage is required to perform an efficient exploitation of resources. This paper proposed a Hierarchical Type-2 Beta Fuzzy Knowledge Representation system for the selection of optimal route. Consequently, this system aims to avoid longer travel times, and to decrease traffic accidents and the number of traffic congestion situations. The selection is performed through itineraries assessment by contextual factors such as Max speed and density of a given path. For the validation, the traffic simulation was done with the open source microscopic road traffic simulator SUMO. When compared with the Dijkstra's algorithm, the proposed system showed better performance in terms of average travel time and path flow. These promising results prove the potential of our method to relieve traffic congestion.
URI: http://hdl.handle.net/10553/54889
ISBN: 9781509060344
ISSN: 1098-7584
DOI: 10.1109/FUZZ-IEEE.2017.8015683
Source: 2017 IEEE International Conference On Fuzzy Systems (Fuzz-IEEE) [ISSN 1098-7584], (2017)
Appears in Collections:Actas de congresos
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