Urban road network dynamic division method and device, computer equipment and storage medium
A technology of urban road network and division algorithm, which is applied in traffic control systems of road vehicles, traffic flow detection, instruments, etc., can solve the problems of data scale, data diversity and uncertainty increasing the difficulty of dynamic division of large-scale road networks. , to achieve the effect of improving the level of refined management
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Embodiment 1
[0056] In this example, if figure 1As shown, a method for dynamic division of urban road network is provided, which includes:
[0057] Step 110, acquiring road network traffic status data.
[0058] In this embodiment, first, a large amount of road network traffic state data is collected and acquired, and the road network traffic state data records the traffic state data of each road section of the road network at each time period. It is worth mentioning that, in the following embodiments, the road network traffic state data is also referred to as a road network traffic state data set.
[0059] Step 120, decomposing the road network traffic state data, dynamically extracting the distribution characteristics of the road network traffic state in time and space, and constructing a spatial state factor matrix.
[0060] In this step, the road network traffic state data is decomposed, and the three-dimensional tensor of the road network traffic state data is decomposed to obtain th...
Embodiment 2
[0115] In this embodiment, considering the complex spatio-temporal characteristics of urban road network traffic conditions, the traditional static division of road network space is extended to the dynamic road network division problem in the space-time dimension, and a large-scale traffic network dynamic division method is proposed, which can solve The technical problems are as follows: 1) Using a high-order singular value decomposition algorithm to dynamically extract the long-term, short-term and spatial multi-dimensional evolution characteristics of road network traffic status from massive historical data, the use of double-iterative singular value decomposition technology can improve the decomposition algorithm 2) In order to consider the interaction between the traffic states of each road section in the sub-road network, the Pearson coefficient method and the sliding window technology are used to quantify the temporal and spatial correlation of traffic states, and a dynami...
Embodiment 3
[0164] In this example, if figure 2 As shown, a device for dynamically dividing urban road networks is provided, including:
[0165] Road network traffic status data acquisition module 210, used to acquire road network traffic status data;
[0166] The space state factor matrix construction module 220 is used to decompose the road network traffic state data, dynamically extract the distribution characteristics of the road network traffic state in time and space, and construct the space state factor matrix;
[0167] The Gaussian similarity matrix acquisition module 230 is used to calculate the Gaussian similarity matrix between different road sections based on the principal component vector of the space state factor matrix;
[0168] The traffic state spatio-temporal correlation coefficient matrix construction module 240 is used to calculate the correlation between the traffic states of each road segment based on the analysis of the traffic state of each road segment in the ro...
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