Abstract: A traffic information quantization method in an intelligent network environment includes: step S1: extracting traffic information sources according to collected videos and classifying the traffic information sources; step S2: obtaining a state set and a probability distribution of each traffic information source through actual observation and calculation; step S3: using information theory to quantify the traffic information sources. Further, a traffic information quantization system in the intelligent network environment is provided, and the traffic information quantization method in the intelligent network environment and its system are adopted to quantify the driving information of the driving process and calculate the amount of information. The method and system can transform uncertain information into certain information, improve driving efficiency, help drivers optimize the driving process, and ensure driving safety.

Abstract: A mapping method for right-turn conflict warning lines at urban road intersections includes: obtaining the conflict data of urban intersections and the driving trajectory information of large vehicles and obtaining the outermost rear wheel trajectory curve and the innermost rear wheel trajectory curve through the driving trajectory information of large vehicles; using the regression model to construct the dynamic model of the right-turn conflict area of large vehicles and obtain the relationship between the parameters of the outermost rear wheel trajectory curve and the innermost rear wheel trajectory curve and the dynamic and static indexes; inputting the dynamic and static indexes of other road intersections into the dynamic model of the right-turn conflict area of large vehicles to obtain the corresponding outermost rear wheel trajectory curve and the innermost rear wheel trajectory curve, and drawing the urban road warning line.