Traffic congestion has been an area of major bother across the globe. The existing infrastructure is not able to cope with the new traffic demand. Furthermore the restriction of the space and outside activities influencing the traffic congestion. The emerging country like India, where the traffic conditions comprise heterogeneous traffic with no lane discipline, further creates more complicated scenarios for the researcher. A substantial portion of working hours is getting wasted on the roads because of traffic congestion, which imposes the negative effect on the overall economy. There has been numerous of literature and studies for analysis of the traffic congestion and its impacts. However, the result has not been much satisfying. In the present study congestion forecast is aimed under mixed traffic with no lane discipline towards identifying the inherent viability of the diversified traffic situation and presents better recommendations in controlling and evading these prolonged traffic jams. The urban highway systems were considered as a study area. Required particulars were collected by a License Plate Matching method using video graphic survey for the day rush timing considered from 8:00 AM to 10:00 AM and off peak hours to estimate the travel time of a distinct class of motorized vehicles for selected sections of the urban roadway. Congestion indices for both the up and down traffic of a particular road were evaluated from the data collected from the video recording. Traffic congestion impacts were analyzed and possible mitigation measures have been suggested. The study mainly focused on traffic jam indices with regarded to travel time reliability measures to observe the functional effectiveness of the urban road network.

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Traffic congestion is a major problem around the globe. The prime reason for congestion is unavailability of traffic infrastructure to meet the traffic demand. Road users are forced to face undesirable delay, which influences the economy, environment and health. The present study examines the congestion in the urban roads of Bhubaneswar, a smart city in India. Travel time for various categories of vehicles was estimated and congestion indices in terms of buffer index were evaluated. Multiple linear regression modeling has been used to evaluate the congestion parameters. The p-value for all the independent variables in the developed model is < 0.05. Four elements, namely Strict traffic law implementation, Adequate parking facilities, Decentralization and Controlling the road side activities are required to improve the serviceability and mobility of urban road networks.