Research On Fuzzy Logic Algorithms For Urban Traffic Signal Control Based On Saturation Model

Traffic is very close to people's life. With economic growth, improvement of living standards and the sharp increase in vehicle fleet, the growth in urban transport demand is higher than that in transport infrastructure supply. Traffic congestion has become an important factor restricting social development. Through many years of practical experience, people find out that establishing an intelligent signal control system with intelligent technology is the most effective means to solve the traffic congestion. Given that urban transport system is a random, complex and uncertain system, we cannot establish a precise mathematical model by means of intelligent methods which must be possible to solve urban traffic problems. Therefore, an effective intelligent transportation system is the goal pursued by researchers.Fuzzy control is one kind of intelligent control methods. It does not need to establish the precise mathematical model. Combined with the Human's thinking and experience, fuzzy control can easily implement on the nonlinear and uncertain control objects. What is more, this control method has strong robustness with object properties parameters. Therefore, fuzzy control is particularly suitable for transportation systems. In this paper, urban single-intersection and Route is optimized by fuzzy control theory.In this paper, urban traffic signal is considered a control object. The research content and innovation are as follows.1. Saturation-based intersection evaluation model is the foundation of traffic signal control. The factors of the intersection level of service are more complex. Nowadays, there is no uniform level of service intersection signal control evaluation criteria in our country. The saturation-based congestion evaluation method is proposed in this paper. We install a detector downstream of a stop line which can be measured. With the cost of data collection reduced, this method has practical value. 2. Single exponential smoothing of the adaptive algorithm is researched and forecasting model saturation is established. This paper introduces error smoothing coefficient algorithm which can improve the single exponential smoothing and the accuracy of the forecasts saturation.3. Based on the characteristics of the traffic flow, single-intersection signal control method is proposed. In this paper, single intersection signal control model is established and it considers the rate of saturation as the input of the fuzzy controller. As a result, the time of output green light is extended. Then, by considering the balance of intersection traffic flow situation, this method can ensure the home team train can flow through the intersection. Besides, the right way of phase sub-queue traffic is optimized. This algorithm can simulate the traffic police's command, improve the utilization rate of the green light and reduce the average vehicle delay.4. Signal control of urban arterial road is analyzed to study the hierarchical coordination of arterial road control. Combined hierarchical structure with fuzzy control technology, a real-time coordination of traffic control algorithm is proposed.Finally, we make a conclusion and propose the future research directions in this filed.