Belief Reliability Analysis of Traffic Network: An Uncertain Percolation CML Model

Y. Yang; X. Chen; L. H. Guo; S. Y. Huang; W. S. Xie; W. Liu

doi:10.1109/IEEM50564.2021.9672604

Belief Reliability Analysis of Traffic Network: An Uncertain Percolation CML Model

Y. Yang
, X. Chen
, L. H. Guo^*
, S. Y. Huang
, W. S. Xie
, W. Liu

^*Corresponding author for this work

School of Reliability and Systems Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

Most research on traffic network reliability considered about aleatory uncertainty but ignored the effect of epistemic uncertainty which may misguide the traffic management. In this paper, we will introduce uncertainty theory and belief reliability theory to propose a belief reliability analysis method for traffic network based on the traffic performance margin. To analyze the belief reliability of roads, a method considering three uncertain factors to get the distribution function of capacity threshold will be proposed. To describe the process of traffic congestion considering both aleatory and epistemic uncertainty, an uncertain percolation coupled-map-lattice (CML) model is constructed, where the uncertain percolation model is utilized to describe the performance degradation of traffic network and the CML model is to represent the process of the load redistribution between nodes. Then, a method combing uncertain simulation and UPC model is put forward to calculate the belief reliability of traffic network. The proposed methods are illustrated with a case study.

Original language	English
Title of host publication	2021 IEEE International Conference on Industrial Engineering and Engineering Management, IEEM 2021
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	1503-1507
Number of pages	5
ISBN (Electronic)	9781665437714
DOIs	https://doi.org/10.1109/IEEM50564.2021.9672604
State	Published - 2021
Event	2021 IEEE International Conference on Industrial Engineering and Engineering Management, IEEM 2021 - Virtual, Online, Singapore Duration: 13 Dec 2021 → 16 Dec 2021

Publication series

Name	2021 IEEE International Conference on Industrial Engineering and Engineering Management, IEEM 2021

Conference

Conference	2021 IEEE International Conference on Industrial Engineering and Engineering Management, IEEM 2021
Country/Territory	Singapore
City	Virtual, Online
Period	13/12/21 → 16/12/21

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 9 Industry, Innovation, and Infrastructure

Keywords

Belief reliability
CML model
Congestion index
Epistemic uncertainty
Uncertain random simulation

Access to Document

10.1109/IEEM50564.2021.9672604

Cite this

Yang, Y., Chen, X., Guo, L. H., Huang, S. Y., Xie, W. S., & Liu, W. (2021). Belief Reliability Analysis of Traffic Network: An Uncertain Percolation CML Model. In 2021 IEEE International Conference on Industrial Engineering and Engineering Management, IEEM 2021 (pp. 1503-1507). (2021 IEEE International Conference on Industrial Engineering and Engineering Management, IEEM 2021). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/IEEM50564.2021.9672604

Yang, Y. ; Chen, X. ; Guo, L. H. et al. / Belief Reliability Analysis of Traffic Network : An Uncertain Percolation CML Model. 2021 IEEE International Conference on Industrial Engineering and Engineering Management, IEEM 2021. Institute of Electrical and Electronics Engineers Inc., 2021. pp. 1503-1507 (2021 IEEE International Conference on Industrial Engineering and Engineering Management, IEEM 2021).

@inproceedings{ccf1d3804ea043e3a3d604eee3c2d5cf,

title = "Belief Reliability Analysis of Traffic Network: An Uncertain Percolation CML Model",

abstract = "Most research on traffic network reliability considered about aleatory uncertainty but ignored the effect of epistemic uncertainty which may misguide the traffic management. In this paper, we will introduce uncertainty theory and belief reliability theory to propose a belief reliability analysis method for traffic network based on the traffic performance margin. To analyze the belief reliability of roads, a method considering three uncertain factors to get the distribution function of capacity threshold will be proposed. To describe the process of traffic congestion considering both aleatory and epistemic uncertainty, an uncertain percolation coupled-map-lattice (CML) model is constructed, where the uncertain percolation model is utilized to describe the performance degradation of traffic network and the CML model is to represent the process of the load redistribution between nodes. Then, a method combing uncertain simulation and UPC model is put forward to calculate the belief reliability of traffic network. The proposed methods are illustrated with a case study.",

keywords = "Belief reliability, CML model, Congestion index, Epistemic uncertainty, Uncertain random simulation",

author = "Y. Yang and X. Chen and Guo, \{L. H.\} and Huang, \{S. Y.\} and Xie, \{W. S.\} and W. Liu",

note = "Publisher Copyright: {\textcopyright} 2021 IEEE.; 2021 IEEE International Conference on Industrial Engineering and Engineering Management, IEEM 2021 ; Conference date: 13-12-2021 Through 16-12-2021",

year = "2021",

doi = "10.1109/IEEM50564.2021.9672604",

language = "英语",

series = "2021 IEEE International Conference on Industrial Engineering and Engineering Management, IEEM 2021",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

pages = "1503--1507",

booktitle = "2021 IEEE International Conference on Industrial Engineering and Engineering Management, IEEM 2021",

address = "美国",

}

Yang, Y, Chen, X, Guo, LH, Huang, SY, Xie, WS & Liu, W 2021, Belief Reliability Analysis of Traffic Network: An Uncertain Percolation CML Model. in 2021 IEEE International Conference on Industrial Engineering and Engineering Management, IEEM 2021. 2021 IEEE International Conference on Industrial Engineering and Engineering Management, IEEM 2021, Institute of Electrical and Electronics Engineers Inc., pp. 1503-1507, 2021 IEEE International Conference on Industrial Engineering and Engineering Management, IEEM 2021, Virtual, Online, Singapore, 13/12/21. https://doi.org/10.1109/IEEM50564.2021.9672604

Belief Reliability Analysis of Traffic Network: An Uncertain Percolation CML Model. / Yang, Y.; Chen, X.; Guo, L. H. et al.
2021 IEEE International Conference on Industrial Engineering and Engineering Management, IEEM 2021. Institute of Electrical and Electronics Engineers Inc., 2021. p. 1503-1507 (2021 IEEE International Conference on Industrial Engineering and Engineering Management, IEEM 2021).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Belief Reliability Analysis of Traffic Network

T2 - 2021 IEEE International Conference on Industrial Engineering and Engineering Management, IEEM 2021

AU - Yang, Y.

AU - Chen, X.

AU - Guo, L. H.

AU - Huang, S. Y.

AU - Xie, W. S.

AU - Liu, W.

PY - 2021

Y1 - 2021

N2 - Most research on traffic network reliability considered about aleatory uncertainty but ignored the effect of epistemic uncertainty which may misguide the traffic management. In this paper, we will introduce uncertainty theory and belief reliability theory to propose a belief reliability analysis method for traffic network based on the traffic performance margin. To analyze the belief reliability of roads, a method considering three uncertain factors to get the distribution function of capacity threshold will be proposed. To describe the process of traffic congestion considering both aleatory and epistemic uncertainty, an uncertain percolation coupled-map-lattice (CML) model is constructed, where the uncertain percolation model is utilized to describe the performance degradation of traffic network and the CML model is to represent the process of the load redistribution between nodes. Then, a method combing uncertain simulation and UPC model is put forward to calculate the belief reliability of traffic network. The proposed methods are illustrated with a case study.

AB - Most research on traffic network reliability considered about aleatory uncertainty but ignored the effect of epistemic uncertainty which may misguide the traffic management. In this paper, we will introduce uncertainty theory and belief reliability theory to propose a belief reliability analysis method for traffic network based on the traffic performance margin. To analyze the belief reliability of roads, a method considering three uncertain factors to get the distribution function of capacity threshold will be proposed. To describe the process of traffic congestion considering both aleatory and epistemic uncertainty, an uncertain percolation coupled-map-lattice (CML) model is constructed, where the uncertain percolation model is utilized to describe the performance degradation of traffic network and the CML model is to represent the process of the load redistribution between nodes. Then, a method combing uncertain simulation and UPC model is put forward to calculate the belief reliability of traffic network. The proposed methods are illustrated with a case study.

KW - Belief reliability

KW - CML model

KW - Congestion index

KW - Epistemic uncertainty

KW - Uncertain random simulation

UR - https://www.scopus.com/pages/publications/85125425018

U2 - 10.1109/IEEM50564.2021.9672604

DO - 10.1109/IEEM50564.2021.9672604

M3 - 会议稿件

AN - SCOPUS:85125425018

T3 - 2021 IEEE International Conference on Industrial Engineering and Engineering Management, IEEM 2021

SP - 1503

EP - 1507

BT - 2021 IEEE International Conference on Industrial Engineering and Engineering Management, IEEM 2021

PB - Institute of Electrical and Electronics Engineers Inc.

Y2 - 13 December 2021 through 16 December 2021

ER -

Yang Y, Chen X, Guo LH, Huang SY, Xie WS, Liu W. Belief Reliability Analysis of Traffic Network: An Uncertain Percolation CML Model. In 2021 IEEE International Conference on Industrial Engineering and Engineering Management, IEEM 2021. Institute of Electrical and Electronics Engineers Inc. 2021. p. 1503-1507. (2021 IEEE International Conference on Industrial Engineering and Engineering Management, IEEM 2021). doi: 10.1109/IEEM50564.2021.9672604

Belief Reliability Analysis of Traffic Network: An Uncertain Percolation CML Model

Abstract

Publication series

Conference

UN SDGs

Keywords

Access to Document

Other files and links

Fingerprint

Cite this