Modelling traffic flow on interchange

Abstract

The rapid urbanization alters the life style in high scale and metropolitan cities adapt traffic diverting structures like interchanges and bridges to handle the ever increasing traffic growth. It is high time to effectively utilize these traffic systems, hence a traffic model explaining the effective travel pattern is obligatory. Fuzzy logic is an effective concept in interpreting and reciprocating performance similar to human reasoning and can describe complex systems in linguistic terms instead of numerical values. In this thesis, a system was established based on Fuzzy Inference System (FIS) with output data as Vehicular Speed (S) and input data as various highway geometric elements. The study was conducted on two steps as for up - ramp condition and down – ramp condition. Two Traffic models (TFup & TFdn) were developed with radius of curvature, super elevation, frictional coefficient and slope as governing factors. The inferences show that these models can be used to predict and understand the traffic flow along the interchanges with the effect of gravity and friction on the travelling vehicle. A correlation was established between the geometric elements and speed of the vehicle. A simulation study and real life data analysis were performed to demonstrate model fitting the performances of the proposed model.