Data analysis with multi-objective optimization algorithm: A study in smart traffic signal system

Traffic optimization is an emerging area in the recent few years, with the rapid development of data analysis studies and techniques. Intersection is the hub of road traffic and play a vital role in alleviating the pressure on road traffic. Therefore, this study was done to improve indexes of traffic control and ease road congestion, in order to refine the traffic situation of the interaction. In this paper, traffic signal timing of individual interactions will be discussed. After an analysis and comparison of various road indexes, a signal timing algorithm based on multi-objective optimization was developed. The algorithm aims to reduce vehicle delay time, reduce the number of stops and improve the traffic capacity. It is applied by dimensionally processing the indexes, building a multi-objective optimization model and then adopting the fixed-step search method to program and determine the optimal signal cycle scheme for the current road condition and eventually allocating the time of green clearance for each phase according to the principle of equal saturation. A real intersection was selected for this research. The specific data about this intersection was collected and used to launch experimental verification of the algorithm developed in this paper. Moreover, the optimization level of each phase and the current signal timing scheme for the interaction were compared.