Prediction of traffic density for congestion analysis under Indian traffic conditions

Abstract

Traffic congestion is a serious problem which traffic engineers all over the world are trying to solve. Congestion increases the uncertainty in travel times leading to human stress and unsafe traffic situations. Better management of traffic through Intelligent Transportation Systems (ITS) applications, especially by predicting the congestion on various roads and informing the travelers regarding the same is one possible solution. Accurate and quick prediction is one of the important factors on which the reliability of such a system depends. If one is able to predict congestion on a roadway, then the travelers can be warned of the same either pre-trip or enroute so that they can take well informed travel decisions. The number of vehicles in a given stretch of a roadway (usually referred to as “traffic density”) is one of the most commonly used congestion indicator. Also, the travelers in general will be more interested to know what they can expect when they make the trip in future rather than the present scenario. This makes the short term prediction to future time intervals important. In this study, some of the reported techniques for density prediction under homogeneous traffic conditions are attempted under heterogeneous traffic conditions in order to determine their feasibility under the Indian traffic scenario.