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The recent economic growth in developing countries
like India has resulted in an intense increase of vehicle
ownership and use, as witnessed by severe traffic congestion
and bottlenecks during peak hours in most of the metropolitan
cities. Intelligent Transportation Systems (ITS) aim to reduce
traffic congestion by adopting various strategies such as
providing pretrip and enroute traffic information thereby
reducing demand, adaptive signal control for area wide
optimization of traffic flow, etc. The successful deployment
and the reliability of these systems largely depend on the
accurate estimation of the current traffic state and quick and
reliable prediction to future time steps. At a macroscopic level,
this involves the prediction of fundamental traffic stream
parameters which include speed, density and flow in spacetime
domain. The complexity of prediction is enhanced by
heterogeneous traffic conditions as prevailing in India due to
less lane discipline and complex interactions among different
vehicle types. Also, there is no exclusive traffic flow model for
heterogeneous traffic conditions which can characterize the
traffic stream at a macroscopic level. Hence, the present study
tries to explore the applicability of an existing macroscopic
model, namely the LighthillWhithamRichards (LWR) model,
for short term prediction of traffic flow in a busy arterial in
the city of Chennai, India, under heterogeneous traffic
conditions. Both linear and exponential speeddensity
relations were considered and incorporated into the
macroscopic model. The resulting partial differential
equations are solved numerically and the results are found to
be encouraging. This model can ultimately be helpful for the
implementation of ATIS/ATMS applications under
heterogeneous traffic environment.
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