Dynamic od matrix estimation method based on monitoring data

Abstract

The invention provides a dynamic OD matrix estimation method based on monitoring data, which belongs to the field of intelligent transportation. A traditional method does not take into account the sparsity of some actual road network OD matrices, and the calculated OD matrix and the traffic distributed on a road network are deviated from the actual. In a solution process, distributing the OD matrix to the road network takes a certain time. Especially when a road segment is in congestion, a traditional OD matrix distribution algorithm takes a long time, which is difficult to meet real-time requirements. According to the invention, a dynamic OD matrix estimation model under sparse constraints is constructed, and a fast dynamic OD matrix estimation algorithm under sparse constraints is proposed; an OD matrix distribution function is fitted based on a radial basis neural network; on the basis, key problems to be solved comprise the dynamic OD matrix estimation model under sparse constraints and the real-time dynamic OD matrix estimation algorithm under sparse constraints; and in theory, the proposed scheme can accurately estimate a dynamic OD matrix to meet real-time requirements.

Description

technical field [0001] The invention belongs to the field of intelligent transportation and studies a dynamic OD matrix estimation method. Background technique [0002] In recent years, with the continuous development of social economy and the continuous improvement of living standards, people's travel demand has shown a rapid growth trend, followed by such as traffic congestion, air and noise pollution, traffic safety problems and the resulting quality of life However, it is increasingly plaguing major cities. Traffic problems have become one of the most difficult modern social problems to eradicate. Although governments around the world have invested or are investing a lot of financial resources to expand road supply, traffic conditions have not been significantly improved. After long-term and extensive research, it is found that only relying on building more roads and expanding the scale of the road network to solve the problem of traffic congestion is no longer effecti...

AI Technical Summary

Problems solved by technology

However, the traditional method does not take into account the sparsity of the OD matrix of some actual road networks, and the calculated OD matrix and the flow allocated on the road network have a large deviation from the actual; It takes a certain amount of time, especially when the road section is congested, the traditional OD matrix allocation algorithm takes a long time, and it is difficult to meet the real-time requirements

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