Adaptive Traffic Light Control In WSN-Based ITS

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.