Design of Urban Traffic Control Algorithm Based on Traffic Big Data

Urban intersections are the main locations where traffic congestion occurs, especially in second tier cities with high traffic volume and underdeveloped transportation. Many level crossings have insufficient capacity compared to the average capacity of relevant road sections. The traffic volume of urban roads is constantly increasing, and the supply speed of road infrastructure is far less than the growth rate of traffic demand. The supply and demand of traffic has become seriously imbalanced, and traffic congestion occurs every day in the road network of first and second tier cities in China, causing significant difficulties for the daily travel of urban residents. In this regard, this paper designs the urban traffic control algorithm based on the traffic big data, which can scientifically organize the traffic data resources, thus realizing the timely processing of massive data, and can efficiently process the traffic data. This is the prominent advantage of big data and other technologies in the field of intelligent transportation. The experimental results show that the coordinated control method is far superior to single point timed control in terms of travel time on the main line and total traffic delay time within the control area. Prove that the control algorithm proposed in this paper is feasible and effective.