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Copula and Monte-Carlo simulation based path stroke time estimation method

A travel time and route technology, applied in the field of intelligent traffic information processing, can solve the problems of complex multivariate integral calculation and difficult application, and achieve the effect of improving applicability, good statistical characteristics, and simplifying multivariate probability integral calculation.

Active Publication Date: 2019-05-03
BEIHANG UNIV
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Although the Copula function can characterize the distribution of travel time of a route and analyze the direct correlation structure of the distribution of travel time of road segments, it also brings complex multivariate integral calculations, making it difficult to implement and apply in large-scale road networks.

Method used

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  • Copula and Monte-Carlo simulation based path stroke time estimation method
  • Copula and Monte-Carlo simulation based path stroke time estimation method
  • Copula and Monte-Carlo simulation based path stroke time estimation method

Examples

Experimental program
Comparison scheme
Effect test

Embodiment

[0082] A travel time estimation method for Copula and Monte-Carlo simulations, as follows:

[0083] 1) if figure 2 As shown, it is a road map of a certain city in China, figure 2 a shows a path consisting of five road sections, and marked the number of the road section and the starting and ending points, figure 2 b shows the travel time volatility of each road segment from 7:01-7:30 (time period t-1) to 7:31-8:00 (time period t) in 44 working days. The statistical information of the travel time fluctuation rate of the five road segments is shown in the following table:

[0084] road section

scope

average

median value

mean error

standard deviation

Skewness

kurtosis

L1

[-0.694,1.060]

0.325

0.352

0.053

0.352

-0.198

0.122

L2

[-1.259,0.895]

0.204

0.239

0.047

0.309

-2.034

9.325

L3

[-1.190,1.307]

0.457

0.480

0.060

0.397

-1.413

4.788

L4

[-0.258,0.666]

...

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Abstract

The invention discloses a Copula and Monte-Carlo simulation based path stroke time estimation method. The method comprises the steps that S1) the fluctuation ratio of path stroke time of different segments in a path is obtained; S2) edge distribution fitting is carried out on the fluctuation ratio of path stroke time of different segments by means of maximum likelihood estimation; S3) a Copula theory is used to fit a path stroke time fluctuation ratio distribution function on the basis of a distribution function of the fluctuation ratio of path stroke time of different segments; S4) Monte-Carlo simulation is used to obtain a path stroke time fluctuation ratio sequence on the basis of the Copula function; S5) a confidence interval in certain confidence level is determined, and an expected value of the path stroke time fluctuation ratio is calculated; and S6) the expected value of the path stroke time fluctuation ratio is combined with path stroke time in the last period to estimate thepath stroke time of the present period. Sequential fluctuation of stroke time of the different segments as well as spatial relation between the segment stroke time is taken into consideration, time-space characteristic of the stroke time is dug deeply, and the precision and reliability are higher.

Description

technical field [0001] The invention relates to the technical field of intelligent traffic information processing, and more specifically relates to a method for estimating route travel time based on Copula and Monte-Carlo simulation. Background technique [0002] At present, the proposal and application of Intelligent Transportation System (ITS) not only accelerates the development of urban economy, but also makes travelers put forward higher requirements for travel quality. Based on massive traffic data, it is also one of the important purposes of the intelligent transportation system to analyze and predict the future traffic status, maximize the utilization of road traffic resources, and reduce travel time, traffic congestion and traffic accidents. Real-time and accurate road travel time prediction is the premise of realizing traffic guidance and traffic control, and it is also a key factor for the transformation of intelligent transportation system from "passive response"...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G08G1/01
Inventor 马晓磊栾森陈汐鲁光泉李萌
Owner BEIHANG UNIV
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