Abstract
Summary. With the rapid growth of urban traffic, the gap between traffic demand and supply is increasing by the day, and traffic congestion has become a part of urban Indian life. The following aspects have become important for transportation planners and managers: identification of the frequently congested road sections, estimating their influence on the entire road network, and improving the connectivity and accessibility of the whole road network. Identification of congestion metric is the first step in such endeavour as it would be of help in selecting appropriate remedial measures. This paper presents some insights on how to identify the traffic congestion and establish the congestion thresholds on urban arterials. Stream speed emerges as one of the candidate metrics in identifying congestion on urban arterials. Further, speed studies conducted on an interrupted heterogeneous mix of vehicles plying Delhi urban arterials is also presented.
Highlights
Traffic congestion has been one of the major issues that most metropolises face, and many measures have been adopted to mitigate congestion
The standard deviations were calculated for the congested regime and the free-flow regime at various locations and the time duration is identified after assessing the stream speed
Average free speed observed on study 48.7
Summary
Traffic congestion has been one of the major issues that most metropolises face, and many measures have been adopted to mitigate congestion. The two principal categories of causes of congestion are (a) micro-level factors (e.g. those relating to traffic on the road) and (b) macro-level factors that relate to overall demand for road use. The micro level factors include many people and freight wanting to move at the same time and too many vehicles for limited road space and intersection capacity. The essential macro level factors useful in identifying the demand for road use are land-use patterns, employment patterns, income levels, car ownership trends, infrastructure investment, regional economic dynamics, etc. This paper tries to identify congestion metric(s) that can be used for quantification and mitigation.
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