Qualitative Level of Service Analysis of Urban Streets in Indian Context

Priyanka, Atmakuri (2015) Qualitative Level of Service Analysis of Urban Streets in Indian Context. MTech thesis.



Level of service (LOS) methodology incorporating user perceptions provides a tool to describe how well a transportation facility satisfies their road users. India being a developing country, the traffic especially in urban streets is highly heterogeneous consisting of various kind of vehicles having different operational characteristics and a complex interaction between them. There are several engineering factors other than average speed and density that affect drivers perceptions for service quality. As LOS is not well defined for highly heterogeneous traffic flow condition on urban corridors in India, an attempt has been made to represent variability and complexity of human perceptions. About 250 responses of road users have been collected from three mid-sized cities of India, i.e. Rourkela, Vishakhapatnam, and Trivandrum, which can be characterized by different types of road geometrics and operational conditions. A questionnaire has been prepared considering various factors that affecting the quality of service, which were grouped into eight factors using factor analysis. A regression model was developed taking these eight factors as predictors and overall satisfaction as dependent variable. Ranges of LOS scores was obtained by K-means clustering. Further, Fuzzy logic method in which fuzzification of input parameters, generation of fuzzy rules, and Defuzzification of output has been applied. The result show the model is reliable and has a good correlation coefficient (R2 = 0.71). LOS categories obtained from the regression and fuzzy logic models were compared with perceived LOS, and were found to be almost similar indicating the effectiveness of the models. Only gender had statistically significant effect on the subject's ratings of overall satisfaction

Item Type:Thesis (MTech)
Uncontrolled Keywords:LOS, user perceptions, multiple regression, fuzzy logic, clustering
Subjects:Engineering and Technology > Civil Engineering > Transportation Engineering
Divisions: Engineering and Technology > Department of Civil Engineering
ID Code:6907
Deposited By:Mr. Sanat Kumar Behera
Deposited On:20 Jan 2016 13:57
Last Modified:20 Jan 2016 13:57
Supervisor(s):Bhuyan, P K

Repository Staff Only: item control page