Abstract: An intelligent optimization system was developed in consideration of traffic light operating states and
time traffic flow to save energy and alleviate the pressure on the urban traffic in Wuhan, China. Since Wuhan’s
traffic light working time is relatively fixed, the system uses detecting apparatus to monitor the traffic on the road
and then feedbacks collected signals to the microcontroller control system. Adaptive intelligent traffic lights were
designed based on the existing traffic light control equipments in Wuhan, with content networking technologies
being used and particle swarm optimization being achieved using Matlab software . The results show that
the particle swarm optimization algorithm reduces the average vehicle traffic time by 20% compared with the
Webster algorithm, with the vehicle idle time reduced and the idle oil consumption saved.

Key words: urban traffic, emission reducing and energy saving, hour traffic flow, traffic lights, intelligent optimization, microcontrollers