Macroscopic traffic flow parameter estimation method for urban expressway

Abstract

The invention discloses a macroscopic traffic flow parameter estimation method for an urban expressway. According to the method, a random macroscopic traffic flow model is used for carrying out parameter estimation on an urban expressway, wherein the estimated parameter has an average road density and an average road speed. The method mainly comprises two parts: model establishment and parameter estimation. The model estimation is carried out by three steps: model theory framework construction, determination of various parameters of the model and a system matrix, and determination of a model modal transfer rate matrix. According to the parameter estimation, a random distribution value of the traffic state of the road segment at any time interval is obtained by using the transfer rate matrix; the random value of a road section traffic state at a current time and a macro traffic flow parameter are substituted into the model; and a traffic flow parameter of the road section at a next timeis estimated. Therefore, objectives of carrying out navigation for a driver and providing an information support for the traffic manager are achieved.

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...

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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

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