Research on traffic signal cycle optimization based on Webster algorithm

Abstract

This study by combining data cleaning, clustering analysis and signal timing method, Webster to famous scenic town traffic control provides a scientific and efficient solution. By removing the missing license plate numbers and abnormal data in the open source data set, the processed data were visualized and analyzed. The cluster analysis was used to divide the peak period of traffic flow, the statistics of the traffic flow period data, the Webster method was used to optimize the timing of traffic lights, and the service level model was established to analyze the results. It was found that it could effectively improve the traffic efficiency. Ease traffic congestion. This research is not only of great significance in theory, but also has application value in actual traffic management, showing its innovation and practical value. The future research of algorithms and to further explore the more advanced technology, to achieve more accurate and efficient traffic flow control.