A macroscopic traffic flow parameter estimation method for urban expressways

Abstract

The invention discloses a method for estimating macroscopic traffic flow parameters of an urban expressway. The method uses a random macroscopic traffic flow model to estimate the parameters of the urban expressway. The estimated parameters include the average density of the road section and the average speed of the road section. The main content of the method is the establishment of the model and parameter estimation. The establishment of the model is divided into three steps: the establishment of the theoretical framework of the model, the determination of the parameters of the model and the system matrix, the determination of the transfer rate matrix of the model mode; the parameters Estimation is based on the establishment of the model, using the transfer rate matrix to obtain the random distribution value of the traffic state of the road section at any time interval, and substituting the random value of the traffic state of the road section at the current moment and the macroscopic traffic flow parameters into the model to estimate the road section at the next moment The parameters of the traffic flow can realize the purpose of navigating the driver and providing information support for the traffic manager.

Description

technical field [0001] The invention belongs to the field of intelligent transportation, and in particular relates to a method for estimating macroscopic traffic flow parameters of urban expressways. Background technique [0002] With the rapid improvement of people's living standards, people's demand for transportation is increasing. Cars are especially favored by travelers because of their fast speed and the characteristics that the destination can be freely selected according to travel needs. [0003] With the rapid increase in the number of motor vehicles in cities, the construction speed of traffic facilities cannot catch up with the growth rate of motor vehicles, and urban congestion is becoming more and more serious. Urban expressways, as the main roads for urban traffic operations, have particularly serious congestion. [0004] The complex traffic state of urban expressway also makes its traffic flow state change from the original single free or congested state to th...

AI Technical Summary

Problems solved by technology

[0011] The ARZ model describes the macroscopic traffic flow state well in mathematical form, but in previous studies, the model is usually solved in a fixed mode (free or congested), which is obviously not realistic The situation greatly affects the estimation accuracy of the ARZ model in the estimation of macroscopic traffic flow parameters, and it is easy to cause the final estimation results to deviate too much from the actual traffic flow parameters, causing misleading information to drivers and traffic managers, thereby further Increased the imbalance between supply and demand in the transportation system, resulting in a larger scale, larger-scale traffic congestion, on this basis, we propose a stochastic macro-traffic flow model

Images