Quantification of Congestion using Fuzzy Logic and Network Analysis using GIS

  

R. Narayanan
Research Scholar, Anna University,Chennai-25.
Sathish5_us@yahoo.co.in

R. Udayakumar
Teaching Research Associate, Anna University, Chennai-25.
rudaya78@rediffmail.com

K. Kumar
Deputy Planner, CMDA, Chennai - 8

L. Subbaraj
Scientist, IRS,Anna University, Chennai - 25


Introduction
There has been a phenomenal growth of motor vehicles in India in the recent past. The disproportionate growth in the traffic vis-a-vis growth in road length, along with unauthorised encroachments on road space, lack of traffic and lane discipline and deficiencies in traffic control have contributed to the increasing problem of congestion in urban areas. In addition to increased travel time and delays, traffic congestion increases air pollution due to vehicular emissions.

There is no consistent definition of congestion in terms of a single measure or set of measures that considers severity, duration, and spatial extent. Measures related to travel time and speed are the most flexible and useful for a wide range of analyses. Congestion can be defined as follows.

• Congestion is travel time or delay in excess of that normally incurred under light or free flow travel conditions.
• Unacceptable congestion is travel time or delay in excess of an agreed upon norm. The agreed upon norm may vary by type of transportation facility, travel mode, geographic location and time of day.

Research organization and technical bodies have recommended standards and specifications for all design parameters to the generalized situations. But the congestion severity on an urban road is affecting the general design condition in a diverse ways and the recommendations become ineffective. The type and intensity of congestion depends on many quantifiable factors such as volume, speed, headway, ratio of slow

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