The conventional surveillance methods used in ITS to detect
real-time traffic data, e.g. video image processing and inductive
loops detection, have several shortcomings, such as limited
coverage and high costs of implementation and maintenance. Wireless
Sensor Networks (WSNs) offer the potential of providng real-time
traffic data without these drawbacks. Hence, in the past decade,
WSNs have been applied to ITS to improve the performance of ITS.
Controlling traffic lights plays a key role in ITS. We investigate
how to design methods and algorithms for adaptive traffic light
control in a WSN-based ITS. We propose models and schemes for
adaptive traffic light control for both isolated intersections and
multiple intersections. The proposed approaches take advantage of
real-time traffic information collected by WSNs to achieve high
system throughput, low waiting time and few stops for the vehicles.
We have implemented the proposed schemes on our testbed for
Intelligent Services with WSNs, iSensNet to evaluate and
demonstrate the performance. Our experimental results show that our
approaches can deal with different traffic conditions in an
effective manner.
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