CATEGORIZATION OF URBAN TRAFFIC CONGESTION BASED ON THE FUZZIFICATION OF CONGESTION INDEX VALUE AND INFLUENCING PARAMETERS

Nilanchal Patel () and Alok Bhushan Mukherjee ()
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Nilanchal Patel: Birla Institute of Technology Mesra, Ranchi, Jharkhand – 835215, India
Alok Bhushan Mukherjee: Birla Institute of Technology Mesra, Ranchi, Jharkhand – 835215, India

Theoretical and Empirical Researches in Urban Management, 2014, vol. 9, issue 4, 36-51

Abstract: Traffic congestion is a dynamic phenomenon; it is not possible to determine the actual degree of congestion prevailing on the field using sharp boundaries of the influencing parameters. To overcome this, in this paper we have employed fuzzy concept to fuzzify the two influencing parameters viz. congestion index value and average speed that facilitated the categorization of the congestion status into five different classes i.e. highly congested, high-moderate congested, moderate congested, low congested, least congested as compared to the only two congestion classes determined through the traditionally used congestion index value of the influencing parameters. For each route, pre-defined membership values (between 0 and 1) were assigned to the congestion index value and average speed respectively based on the empirical observations made in the field. Using the same logic, knowledge-based weights were assigned to the five different classes of congestion. Subsequently, fuzzy OR operation was performed on the membership values of the two influencing parameters for each route separately. Finally, different routes of the study area were categorized as one of the five classes of congestion based on the resultant value of the fuzzy OR operation. The research demonstrated that application of the fuzzy concept and knowledge-based congestion weights can provide better realistic status of the congestion in the field as compared to traditionally used congestion index value of the influencing parameters.

Keywords: traffic congestion; fuzzy technique; GIS; empirical field observation. (search for similar items in EconPapers)
Date: 2014
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Citations: View citations in EconPapers (3)

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