A Bayesian Network Model for Origin-Destination Matrices Estimation Using Prior and Some Observed Link Flows

This paper presents a Bayesian network model for estimating origin-destination matrices. Most existing Bayesian methods adopt prior OD matrixes, which are always troublesome to be obtained. Since transportation systems normally have stored large amounts of historical link flows, a Bayesian network m...

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Main Authors: Lin Cheng, Senlai Zhu, Zhaoming Chu, Jingxu Cheng
Format: Article
Language:English
Published: Wiley 2014-01-01
Series:Discrete Dynamics in Nature and Society
Online Access:http://dx.doi.org/10.1155/2014/192470
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author Lin Cheng
Senlai Zhu
Zhaoming Chu
Jingxu Cheng
author_facet Lin Cheng
Senlai Zhu
Zhaoming Chu
Jingxu Cheng
author_sort Lin Cheng
collection DOAJ
description This paper presents a Bayesian network model for estimating origin-destination matrices. Most existing Bayesian methods adopt prior OD matrixes, which are always troublesome to be obtained. Since transportation systems normally have stored large amounts of historical link flows, a Bayesian network model using these prior link flows is proposed. Based on some observed link flows, the estimation results are updated. Under normal distribution assumption, the proposed Bayesian network model considers the level of total traffic flow, the variability of link flows, and the violation of the traffic flow conservation law. Both the point estimation and the corresponding probability intervals can be provided by this model. To solve the Bayesian network model, a specific procedure which can avoid matrix inversion is proposed. Finally, a numerical example is given to illustrate the proposed Bayesian network method. The results show that the proposed method has a high accuracy and practical applicability.
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institution Kabale University
issn 1026-0226
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publishDate 2014-01-01
publisher Wiley
record_format Article
series Discrete Dynamics in Nature and Society
spelling doaj-art-a0450e8ab34f4f7facf6e430d8ec43ad2025-02-03T05:46:45ZengWileyDiscrete Dynamics in Nature and Society1026-02261607-887X2014-01-01201410.1155/2014/192470192470A Bayesian Network Model for Origin-Destination Matrices Estimation Using Prior and Some Observed Link FlowsLin Cheng0Senlai Zhu1Zhaoming Chu2Jingxu Cheng3School of Transportation, Southeast University, Nanjing 210096, ChinaSchool of Transportation, Southeast University, Nanjing 210096, ChinaSchool of Transportation, Southeast University, Nanjing 210096, ChinaSchool of Transportation, Southeast University, Nanjing 210096, ChinaThis paper presents a Bayesian network model for estimating origin-destination matrices. Most existing Bayesian methods adopt prior OD matrixes, which are always troublesome to be obtained. Since transportation systems normally have stored large amounts of historical link flows, a Bayesian network model using these prior link flows is proposed. Based on some observed link flows, the estimation results are updated. Under normal distribution assumption, the proposed Bayesian network model considers the level of total traffic flow, the variability of link flows, and the violation of the traffic flow conservation law. Both the point estimation and the corresponding probability intervals can be provided by this model. To solve the Bayesian network model, a specific procedure which can avoid matrix inversion is proposed. Finally, a numerical example is given to illustrate the proposed Bayesian network method. The results show that the proposed method has a high accuracy and practical applicability.http://dx.doi.org/10.1155/2014/192470
spellingShingle Lin Cheng
Senlai Zhu
Zhaoming Chu
Jingxu Cheng
A Bayesian Network Model for Origin-Destination Matrices Estimation Using Prior and Some Observed Link Flows
Discrete Dynamics in Nature and Society
title A Bayesian Network Model for Origin-Destination Matrices Estimation Using Prior and Some Observed Link Flows
title_full A Bayesian Network Model for Origin-Destination Matrices Estimation Using Prior and Some Observed Link Flows
title_fullStr A Bayesian Network Model for Origin-Destination Matrices Estimation Using Prior and Some Observed Link Flows
title_full_unstemmed A Bayesian Network Model for Origin-Destination Matrices Estimation Using Prior and Some Observed Link Flows
title_short A Bayesian Network Model for Origin-Destination Matrices Estimation Using Prior and Some Observed Link Flows
title_sort bayesian network model for origin destination matrices estimation using prior and some observed link flows
url http://dx.doi.org/10.1155/2014/192470
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