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Urban road network congestion evolution analysis method considering time-space characteristics

A technology of spatio-temporal characteristics and urban road network, applied in design optimization/simulation, complex mathematical operations, instruments, etc., can solve problems such as difficult to predict and complex changes in road network status

Pending Publication Date: 2022-01-18
TONGJI UNIV
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Problems solved by technology

However, compared with the above-mentioned events, the impact of the epidemic may last for a long time. During this period, the road congestion pattern is affected by various factors, such as travel restrictions, resumption of work and production, holidays, etc., and changes in road network status more complex and unpredictable

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  • Urban road network congestion evolution analysis method considering time-space characteristics
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Embodiment Construction

[0006] The urban road network congestion evolution analysis method considering the spatio-temporal characteristics proposed by the present invention, the method is based on the statistical analysis theory of data, and the specific steps are as follows:

[0007] Step1: Construction of velocity space-time matrix

[0008] First clean the data, mainly to deal with missing data. If there is a large amount of missing data in the traffic area, it will be discarded directly. If there are few missing data, it will be interpolated according to the speed of the time slice before and after, and then the space-time matrix M={m ij}, where m ij is the average speed of the i-th traffic area in the j-th hour;

[0009] Step2: Space-time matrix decomposition

[0010] For the space-time matrix M, use the RPCA algorithm to decompose it into the sum of a low-rank matrix L and a sparse matrix S, and balance the two optimization objectives through the coefficient λ, where the low-rank matrix repres...

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Abstract

The invention discloses an urban road network congestion evolution analysis method considering time-space characteristics, and aims to accurately evaluate and analyze road network congestion change characteristics under the influence of multiple factors from two dimensions of time and space. The method comprises the following steps: firstly, constructing a vehicle speed space-time matrix through average vehicle speed data of a traffic zone to extract space-time change characteristics; then extracting common features and heterogeneous fluctuations in traffic state time change of each traffic zone from the overall features by using a robust principal component analysis (RPCA) method; extracting a typical scene of traffic state change by using a clustering method, and analyzing spatial and temporal distribution of heterogeneous parts; and finally, analyzing the fluctuation characteristics of the heterogeneous part through an iterative cumulative sum of squares (ICSS) algorithm.

Description

technical field [0001] The invention belongs to the field of spatio-temporal data mining and urban risk management and control. More specifically, the present invention relates to a more comprehensive and comprehensive method for evaluating the spatio-temporal characteristics of urban road network congestion changes under the influence of events. Background technique [0002] A large number of studies have shown that there is a close interaction between the epidemic and travel activities. On the one hand, human travel, especially travel based on public transportation, is an important factor in the rapid spread of the virus. On the other hand, during the epidemic, people consider their own safety, and the travel originally based on public transportation may turn to private cars. For example, a survey on the travel patterns of Shanghai residents after the epidemic showed that about 82% of the respondents who used to commute by public transportation have switched to private tr...

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Application Information

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IPC IPC(8): G06F30/27G06K9/62G06F17/16G06F119/12
CPCG06F30/27G06F17/16G06F2119/12G06F18/23213
Inventor 李健许鹏飞李玮峰
Owner TONGJI UNIV
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