Design of Detection Characteristics and Layout Orientation of Traffic Flow in Different Weather Based on Thunder-Sight Integrated Machine

As the core link of intelligent transportation system, the accuracy and stability of traffic flow detection directly affect traffic efficiency and safety management. The traditional single sensor has limitations in detection range, anti-interference ability and environmental adaptability, especially in extreme weather such as rain and snow. The integrated radar and video provides multi-dimensional data support for traffic flow detection under complex meteorological conditions by integrating radar and video, but its detection performance is affected by weather changes and layout orientation. In this study, by analyzing the influence of different weather (sunny, cloudy, rain, snow) on the detection of the ray-vision integrated machine, the layout orientation is optimized, including the layout height, side angle and pitch angle. A quadratic polynomial regression model with detection accuracy, coverage and anti-interference ability as the basic factors is constructed, and substituted into the λ comprehensive performance index to evaluate the influence of the layout height, side angle and pitch angle of the mine-view integrated machine on the overall performance. The data of manual measurement and the number of vehicles detected by the mine-view integrated machine are substituted into the model for analysis and research, and the most suitable installation position is obtained.