Unraveling Mixed Traffic Complexity: A Fuzzy Clustering Approach to Establish the Level of Service Classifications

International Journal of Civil Engineering

© 2024 by SSRG - IJCE Journal

Volume 11 Issue 6

Year of Publication : 2024

Authors : Ketankumar Varmora , Tolaram Popat

10.14445/23488352/IJCE-V11I6P101

How to Cite?

Ketankumar Varmora , Tolaram Popat, "Unraveling Mixed Traffic Complexity: A Fuzzy Clustering Approach to Establish the Level of Service Classifications," SSRG International Journal of Civil Engineering, vol. 11,  no. 6, pp. 1-9, 2024. Crossref, https://doi.org/10.14445/23488352/IJCE-V11I6P101

Abstract:

Urban roads suffer from significant traffic congestion problems due to the rapid rise in vehicles, especially under mixed traffic conditions. A wide variety of vehicles‟ speeds and sizes in the same lane makes it more challenging to establish Level of Service (LOS) classifications. An approach for determining Level of Service (LOS) classifications, ranging from „A‟ to „F‟ introduced by the Highway Capacity Manual (HCM), is very helpful for homogenous traffic. The Indo HCM developed LOS classifications that have been established by examining speed data for mixed traffic. However, there has been limited research to identify distinct categories of determining the LOS for roads in urban areas carrying mixed traffic.  This study aims to offer useful information on determining the “Level of Service” categories for urban road segments in Ahmedabad city. Furthermore, it also attempts to address the current lack of research on this topic and provide a valuable basis to improve traffic management strategies by applying three variables, namely speed, flow, and density. The FCM results clearly represent clusters of input data collected for the road segments according to specific characteristics. This enables the recognition of patterns and observations that are relevant to the research.

Keywords:

Fuzzy c-means, Mixed traffic, MATLAB, Level of Service.

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