Expressway road traffic state estimation method based on dynamic Bayesian network

Abstract

The invention belongs to the technical field of road traffic detection and particularly discloses an expressway road traffic state estimation method based on a dynamic Bayesian network; the method comprises the following steps: (1) extracting relevant parameters of the road traffic state as nodes; (2) determining an interrelationship among the nodes and establishing the dynamic Bayesian network; (3) carrying out a fuzzy classification on data of the observable nodes, analyzing the historical data to obtain a clustering center of each classification and determining a membership degree of the data of the observable data, belonging to each classification; 4) for a target node selected in the dynamic Bayesian network, acquiring a corresponding conditional probability and a transition probability and establishing each moment characteristic table of the selected target node; 5) inputting road traffic flow parameters of the current moment to the dynamic Bayesian network and triggering to reason a target of each moment to obtain a traffic state estimation result. According to the expressway road traffic state estimation method disclosed by the invention, the uncertainty in a single parameter estimation state is solved and simultaneously the relevance in the traffic state is considered, so that better effect and reliability when the road traffic state is estimated are achieved.

Description

technical field [0001] The invention belongs to the technical field of road traffic detection, and in particular relates to a method for estimating a traffic state of an expressway section. Background technique [0002] With the increasing importance of expressway in my country's transportation, traffic congestion, traffic accidents, environmental pollution and other problems are becoming more and more serious. Whether it is traffic managers or travelers, the demand for traffic information management is gradually increasing. Therefore, how to use the existing detection equipment to realize the estimation of expressway traffic status as effectively and accurately as possible, and grasp the real-time and accurate traffic conditions of the current road section. Traffic conditions are the premise of efficient management and service, and have important theoretical and practical research significance. [0003] Various devices for traffic data acquisition, such as fixed detectors,...

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Problems solved by technology

[0005] (2) The Natural Science Edition of the Journal of Yangtze University (Volume 5, No. 4, December 2008) announced a road traffic state discrimination method based on the travel time of the road segment, which uses the collected GPS data to calculate the travel time of the road segment, and passes Comparing the actual travel time and the theoretical travel time of the road section to judge the traffic operation status of the road section, the experimental results show that the method can effectively judge the traffic operation status, but it is limited by the number of effective GPS data

[0009] Looking at the above methods for estimating the road traffic state, most of them use the travel time or driving speed as the basic data, and judge the traffic operation status by dividing the threshold value of the parameters at the current moment. However, related studies also mentioned that the travel time cannot It is directly collected and obtained through the integration of data from a single sample, which will lead to uncertainty in travel time due to reasons such as the number of samples, which in turn will lead to uncertainty in the estimated traffic state

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