Transitional Probabilities of Influencing Factors on Road Traffic Congestion on Urban Roads

Traffic Congestion is a phenomena occurring temporarily acting as a hurdle block in a transportation system. Congestion exhibits multiple faces when it is calibrated for its causes and effects in a study area. Traffic Congestion in Indian Roads are due to different influencing factors – Traffic Composition, Pavement Surface Condition, and Road Geometrics, Right of Way Violation, Land Use, Pedestrians, Stationed Vehicles and Functional Hierarchy of roads. Moreover, congestion and behavior of congestion does not restrict itself to a single factor. It has a tendency to transit from one factor to the other. The cities are growing at a rapid rate with reference to Business, Commercial, Educational and technological aspects; the land use pattern is also getting promoted to decentralized activities of business, educational and residential. Due to this the functionality of the road is changing but then the geometrical condition remains same which leads to many urban traffic issues. In short the traffic has become dynamic but the network characteristics remains static. As there is a rapid increase in traffic volumes which are almost all equal to or sometimes exceeding the capacity of the road the level of service is falling down. The travel time has gone upto 1.4 to 1.5 times the journey time due to congestions resulting into a burden or loss to society of about 1.44 Lakh crore as per a uber study in recent times. This can seriously have an impact in the economy of a city or a nation. Vehicle operating cost increases along with the potential of pollution due to recurring traffic congestions in the urban districts specially in central business districts in peak hours. Researchers in the recent past have suggested that the analysis of urban traffic congestion must be predicted upon theoretically consistent models using the old conventional factors. In the present study, a mechanism is proposed based on the rationality of influencing factors imparting different level of congestions and actual influencing factors leading to the congestions are identified. The study area is earmarked with the help of google earth and improvised with Qgis and Autocad to obtain a clear map or view of the study area. The change in land use and Builtup Area are studied with right of violation & stationed vehicles which have been found to be the most predominant factor of influencing the traffic congestions. It is observed that quality of traffic congestion varies with different type of influencing factor. Hence actual influencing factors which are causing the severity in traffic congestion are identified by observations and detailed network study.