Intersection traffic state parameter estimation method and system based on multi-source data

Abstract

The invention discloses an intersection traffic state parameter estimation method and system based on multi-source data. The method comprises the following steps: building a vehicle delay model according to a traffic wave theory, and building a vehicle travel time model of a flow direction level according to the speed distribution characteristics of a vehicle; enabling a fixed-point detector to detect and obtain the flow of the road section entrance, and determining the number of vehicles arriving at the road section entrance; determining a traffic flow steering ratio of a road section by setting a virtual travel line according to a vehicle track acquired by a mobile detector; determining Bayesian networks of different flow directions according to the vehicle travel time model, the number of arrival vehicles and the traffic flow steering ratio; and solving the Bayesian network and determining the maximum queuing length and the average travel time of the vehicles in different flow directions. According to the embodiment of the invention, the vehicle track data and the fixed-point detector data are combined, and the parameter estimation method fusing the traffic wave theory and statistical analysis is established, so that the accuracy of traffic state parameter estimation is effectively improved.

Description

technical field [0001] The present application relates to the field of traffic control, in particular to a method and system for estimating traffic state parameters at intersections based on multi-source data. Background technique [0002] Traffic congestion is a representative "urban disease" problem faced in the process of new urbanization in my country, which has caused huge losses to social and economic development. The optimization of traffic conditions at intersections is the key to preventing and alleviating traffic congestion, and the estimation of traffic state parameters at intersections is an essential prerequisite for traffic optimization. In traditional traffic signal systems, fixed-point detectors are mostly used to obtain and estimate traffic state parameters, but factors such as the location of fixed-point detectors and detection frequency will affect the estimation accuracy of traffic state parameters, and the maintenance cost of fixed-point detectors is hig...

AI Technical Summary

Problems solved by technology

Moreover, the popularity of mobile detectors is not high at this stage, and the vehicle trajectory data still has the problem of low penetration rate. The lack of vehicle trajectory data also has a negative impact on the accuracy of traffic state parameter estimation.

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