Abstract
The distribution of traffic flow at intersection is an important basis for traffic signal control, based on the characteristics of time and the characteristics of road segments that affect the dynamic changes of traffic flow, this paper proposes an adaptive control strategy for road traffic lights. Firstly, neural network technology is applied to traffic flow state analysis, scientifically define traffic flow patterns based on road-segment information and completes fast and accurate short-term traffic flow distribution state identification online. Secondly, according to the traffic distribution status of intersections, the signal design process is proposed to improve the traffic signal control efficiency. Finally, the verification of the actual traffic flow of Jingming South Road and Juxian Street in Kunming shows that the adaptive traffic signal control method proposed in this paper can effectively reduce intersection delay, number of stops and queue length.
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