Year: 2025
Type: conference-paper
Abstract: With the increase in the number of motor vehicles and the rapid development of urbanization, traffic congestion has become a common phenomenon in life. Through the popularization and application of big data analysis and artificial intelligence technology, the traffic flow control optimization model can realize the efficiency of traffic flow and make traffic management intelligent and convenient. Based on the traffic flow data of 12 intersections on two trunk roads in four directions, through data cleaning, screening and cluster analysis, a line chart of traffic flow changes at major intersections is calculated by using one week's data, and the contour correction coefficient is used to optimize the contour correction coefficient based on the traffic flow analysis. Then, the traffic flow model is established, and the signal lights at all intersections on the two main roads are optimally configured so that the average speed of the traffic flow on the two main roads is the largest. Based on the behavior judgment of vehicles appearing at the same or adjacent intersections for many times in a short period of time and the analysis of the frequency and time difference of vehicles, the frequent occurrence of cruising vehicles at specific intersections is identified, and the parking demand is estimated according to their activity rules, and the results show that in order to cope with the parking demand during peak hours, parking spaces need to be temporarily requisitioned near the scenic spot. Finally, through moving average and standardization, it is found that the traffic flow increases significantly and the smoothness decreases during the long holiday, indicating that it is still necessary to strengthen and improve traffic control.
Authors: Xuemei Yu, Zhiyuan Li, Qizhuo Shi, Liexu Shen
Language: English
Subfield: Control and Systems Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: hybrid
OpenAlex ID: W4413602123