A.K. Das, P.K. Bhuyan

pdf icon

Pages: 75-88

Abstract
The speed range of Levels of Service (LOS) categories is not well defined for highly heterogeneous traffic flow on urban streets in Indian context. Determination of speed ranges of LOS categories of urban traffic facilities helps in planning, design of transportation projects and also allocation of resources among competing projects. In this study an attempt has been made to define LOS criteria for urban street in Indian context considering the free flow speed (FFS), congested travel speed, the geometric and surrounding environmental conditions. Defining LOS criteria is basically a classification problem and cluster analysis is found to be the most suitable technique that can be applied. In this study Clustering Large Applications (CLARA) method is used. Large numbers of speed data are used as an input to CLARA. Using Global Positioning System (GPS) large numbers of second by second speed data are collected and GIS was used in handling large amount of speed data. The clustering algorithm is used twice in this study. The optimal number of clusters is determined using six cluster validation parameters which help in deciding the classification of street segments into numbers of classes. CLARA algorithm was used to classify the FFS data into a number of classes to get the FFS ranges of different urban street classes such that street segments following a class must satisfy its functional and geometric characteristics. In the second stage CLARA algorithm is used on average travel speed data collected during both peak and off-peak hours to determine the speed ranges of different LOS categories. From the above study the FFS ranges for different urban street classes and speed ranges for different LOS categories are defined and the values are found to be lower than that suggested by HCM-2000. Average travel speed of LOS categories expressed in terms of percentage of FFS of the street classes are found to be 85 and above, 70-85, 55-70, 40-55, 30-40, 30 and below respectively for LOS “A” to “F”. This result closely follows the percentage shown in HCM-2010.

Keywords: Level of service; urban streets; GPS; CLARA; free flow speed; cluster validation measures


Issues per Year