Motor vehicle dynamic OD matrix estimation method based on multi-source data

Abstract

The invention provides a motor vehicle dynamic OD matrix estimation method based on multi-source data, which fully utilizes multi-source data such as population, employment, economic data, checkpoint data and floating vehicle data, and proposes a dynamic OD estimation method based on a splitting factor. The motor vehicle dynamic OD matrix estimation method comprises the specific steps of: step 1, proposing a motor vehicle static OD matrix according to a traffic four-phase model; step 2, deducing a motor vehicle time-phased OD matrix by utilizing the checkpoint data and the floating vehicle data; step 3, constructing a time-varying splitting factor; step 4, and segmenting the static OD matrix to obtain a dynamic OD matrix. The motor vehicle dynamic OD matrix estimation method has the advantages of high practicability and high implementation performance, can obtain the dynamic OD matrix of the current stage, can use the planning year static OD matrix deduced by segmenting the currently obtained splitting factor, further obtains the dynamic OD matrix of the planning year, and provides input data for microscopic simulation of the planning year.

Description

technical field [0001] The invention belongs to the technical field of traffic planning and management, in particular to a method for estimating a motor vehicle dynamic OD matrix based on multi-source data. Background technique [0002] OD matrix (or OD table) is a matrix of travel traffic volume between all origins (Origin) and destinations (Destination) in the transportation network, which reflects the basic transportation needs of urban residents. OD matrix is ​​the basic data of urban traffic planning and urban traffic operation, and also the basic input data of traffic allocation models and some commonly used microscopic traffic simulation systems. Traffic districts are multiple sub-regions that divide the research area according to the population, land use, economy, and other basic characteristics of different sub-regions in the research area. The traffic area transforms the chaotic individual travel OD into the OD information between the traffic areas, which is more ...

AI Technical Summary

Problems solved by technology

However, the dynamic OD back-estimation method based on the mathematical model is often difficult to solve and difficult to reflect the change of traveler's route choice behavior, which is not desirable in the practical application of urban road network dynamic OD estimation.

[0005] Although some scholars have proposed a dynamic OD estimation method based on AVI (called automatic electronic label identification) data or GPS-based mobile detection data in recent years, this method is still immature because of the reliability of mobile source data, sample size, Issues such as market share and space coverage need further study

In addition, since these methods require a large amount of real-time link flow information, it is impossible to estimate and predict the dynamic OD matrix of the planning year

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