Level of service criteria of roads in urban indian context

Abstract

India is a highly populated country; it has a second largest road network in the world. Owing to boastfully population, the congestion is growing at zip, zap, zoom speed as thousands of heterogeneous vehicles are added to the urban roads in India. The Level of Service (LOS) is not passable defined for heterogeneous traffic flow with different operational features. Delineating LOS is essentially a classification problem. The diligence of cluster analysis is the worthiest proficiency to solve such problem for which adaboost algorithm, Genetic programming, Maximum-Likelihood Method and Expectation-Maximization Method are used in this study. Five cluster validation parameters are utilized to examine the optimal no clusters. After acquiring optimal no of clusters, these four methods are implemented to the free flow speed (FFS) data to get ranges of different urban street classes. Again, these four clustering method are enforced on average travel speeds of street segments to specify the ranges of different LOS categories. Speed data used in this study are collected using Trimble GeoXT GPS receivers fitted on mid-sized vehicles for five major urban corridors comprising of 100 street segments of Greater Mumbai region. Result shows that FFS of urban street classes and average travel speed of LOS categories are lower than that evoked in HCM 2000 on account of physical and surrounding environmental characteristics. Also, average travel speed of LOS categories expressed in terms percentage of FFS of urban street classes found to be different from that mentioned in HCM 2010.