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A road section travel time estimation method based on road spatio-temporal correlation

A technology related to travel time and space-time, which is applied in the field of intelligent transportation and can solve problems such as difficulty in estimating travel time on roads with sparse data

Inactive Publication Date: 2017-03-15
WUHAN UNIV
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0008] In order to solve the problem of difficulty in estimating road section travel time caused by data sparsity, the present invention provides a method for inferring road section travel time based on road spatiotemporal correlation, comprising the following steps:

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  • A road section travel time estimation method based on road spatio-temporal correlation
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  • A road section travel time estimation method based on road spatio-temporal correlation

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Embodiment Construction

[0025] In order to facilitate those of ordinary skill in the art to understand and implement the present invention, the present invention will be described in further detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the implementation examples described here are only for illustration and explanation of the present invention, and are not intended to limit this invention.

[0026] please see figure 1 In this embodiment, the road network in some areas of Wuhan is used as a research area, and each road section is given a number. This embodiment takes road sections 76, 77, 81, 82, and 88 as examples to specifically illustrate the implementation of the present invention.

[0027] please see Figure 6 A method for inferring road section travel time based on road spatio-temporal correlation provided by the present invention comprises the following steps:

[0028] Step 1: Calculate the travel time of the bicycle section;

[002...

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Abstract

The invention discloses a road segment travel time deducing method based on a road space-time incidence relation. The method comprises a step 1 of performing statistic on road segment travel time traffic data on the basis of an intersection running state; a step 2 of extracting a characteristic relation between a target road segment and an adjacent road segment on the basis of a pass mode periodicity; and a step 3 of predicting target road segment travel time on the basis of a three-layer neural network model. In view of a fact that a conventional method cannot fully predict the road segment travel time when data losses, the method deduces the target road segment travel time by using road segment travel time big data and solves a problem of an incapability of deducing the travel time because of data sparseness. Further, verification is performed by means of Wuhan floating vehicle GPS historical data and manifests that the method is effective.

Description

technical field [0001] The invention belongs to the technical field of intelligent transportation, and in particular relates to a method for estimating travel time of road sections based on road spatiotemporal correlations. Background technique [0002] A taxi equipped with a GPS receiver is used as a traffic status sensor. The information collected includes real-time speed, time stamp, latitude and longitude coordinates, and azimuth angle, etc., which reflect the operating status of urban traffic to a certain extent. The estimation of travel time plays an important role. However, due to the low frequency of taxi GPS collection and the limitation of the driving area, the trajectory information collected by taxi GPS cannot cover all urban road networks in real time, so the data is sparse. How to use sparse data to infer link travel time is an urgent problem to be solved. [0003] Currently, there are many model-based methods using floating car data to estimate link travel t...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G08G1/01
Inventor 呙维张发明朱欣焰刘异
Owner WUHAN UNIV