Evaluation Method Of Regional Road Running Situation Based On Cloud Model

With the rapid development of the world economy and the automobile industry,the amount of car ownership is increasing,this brings a lot of environmental and traffic problems.One of the major problems is traffic congestion,traffic congestion not only brings inconvenience to travel,and it will increase the emission of the tail gas.The cloud model is the uncertainty transformation model between the qualitative concept and quantitative data representation.Due to the randomness of vehicles in the traffic flow and the data obtained as quantitative data,conforming to the characteristics of the cloud model.Therefore,a cloud model is used to evaluate the regional running situation,the process is mainly divided into the following aspects.(1)Using VISSIM to establish road network environment under urban and high speed conditions,and carry out simulation under different traffic flow and obtain a large number of basic simulation data.(2)The parameters needed in the simulation data are extracted and combined with the theory of vehicle dynamics to realize the transformation of the basic driving parameters to the driving state parameters.(3)According to the classification standard of the driver's classification in the literature,the driver type is determined according to the digital feature value of the cloud model of the yaw rate,the center of mass side and the longitudinal velocity of the vehicle.(4)From the historical data,the number of A and B drivers in the regional section is constructed with the forward cloud,the rear part cloud and the reverse cloud,and the data of several small time periods before the prediction of the day are input,and the expected Ex,entropy En and the super entropy He of the traffic and average speed in the regional section are obtained,and the 8 parameters are input to the trained BP,the neural network gets the running situation of the regional section.