Research on the Reliability of High-Speed Railway Dispatching and Commanding Personnel with Multi Physiological Signals

Liuxing Hu; Wei Zheng

doi:10.1007/978-3-031-40953-0_19

Research on the Reliability of High-Speed Railway Dispatching and Commanding Personnel with Multi Physiological Signals

Liuxing Hu
, Wei Zheng^*

^*Corresponding author for this work

Beijing Jiaotong University

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

Abstract

In the event of equipment failure, traffic accident, natural disaster and other abnormal situations, the timely emergency disposal of the traffic dispatcher is required. In order to accurately evaluate the human reliability of the high-speed railway traffic dispatcher in emergency scenarios, this paper proposes a reliability analysis method based on the Phoenix model. In order to eliminate the dependence of the traditional human reliability analysis method on expert experience, a quantification method based on multiple physiological signals is designed. This paper also gives a specific application of this method in the case of inbound signal machine failure. With this human reliability analysis method, the human reliability of the traffic dispatcher and the causative behavior with the highest probability of failure can be accurately calculated, which can provide a reference for the improvement of the emergency handling protocol.

Original language	English
Title of host publication	Computer Safety, Reliability, and Security. SAFECOMP 2023 Workshops - ASSURE, DECSoS, SASSUR, SENSEI, SRToITS, and WAISE, Proceedings
Editors	Jérémie Guiochet, Stefano Tonetta, Erwin Schoitsch, Matthieu Roy, Friedemann Bitsch
Publisher	Springer Science and Business Media Deutschland GmbH
Pages	230-238
Number of pages	9
ISBN (Print)	9783031409523
DOIs	https://doi.org/10.1007/978-3-031-40953-0_19
State	Published - 2023
Externally published	Yes
Event	International Conference on Computer Safety, Reliability, and Security, SAFECOMP 2023 - Toulouse, France Duration: 19 Sep 2023 → 22 Sep 2023

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	14182 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	International Conference on Computer Safety, Reliability, and Security, SAFECOMP 2023
Country/Territory	France
City	Toulouse
Period	19/09/23 → 22/09/23

UN SDGs

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

SDG 3 Good Health and Well-being

Keywords

Human reliability analysis
Physiological signals
Traffic dispatcher

Access to Document

10.1007/978-3-031-40953-0_19

Cite this

Hu, L., & Zheng, W. (2023). Research on the Reliability of High-Speed Railway Dispatching and Commanding Personnel with Multi Physiological Signals. In J. Guiochet, S. Tonetta, E. Schoitsch, M. Roy, & F. Bitsch (Eds.), Computer Safety, Reliability, and Security. SAFECOMP 2023 Workshops - ASSURE, DECSoS, SASSUR, SENSEI, SRToITS, and WAISE, Proceedings (pp. 230-238). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 14182 LNCS). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-031-40953-0_19

Hu, Liuxing ; Zheng, Wei. / Research on the Reliability of High-Speed Railway Dispatching and Commanding Personnel with Multi Physiological Signals. Computer Safety, Reliability, and Security. SAFECOMP 2023 Workshops - ASSURE, DECSoS, SASSUR, SENSEI, SRToITS, and WAISE, Proceedings. editor / Jérémie Guiochet ; Stefano Tonetta ; Erwin Schoitsch ; Matthieu Roy ; Friedemann Bitsch. Springer Science and Business Media Deutschland GmbH, 2023. pp. 230-238 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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abstract = "In the event of equipment failure, traffic accident, natural disaster and other abnormal situations, the timely emergency disposal of the traffic dispatcher is required. In order to accurately evaluate the human reliability of the high-speed railway traffic dispatcher in emergency scenarios, this paper proposes a reliability analysis method based on the Phoenix model. In order to eliminate the dependence of the traditional human reliability analysis method on expert experience, a quantification method based on multiple physiological signals is designed. This paper also gives a specific application of this method in the case of inbound signal machine failure. With this human reliability analysis method, the human reliability of the traffic dispatcher and the causative behavior with the highest probability of failure can be accurately calculated, which can provide a reference for the improvement of the emergency handling protocol.",

keywords = "Human reliability analysis, Physiological signals, Traffic dispatcher",

author = "Liuxing Hu and Wei Zheng",

note = "Publisher Copyright: {\textcopyright} 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.; International Conference on Computer Safety, Reliability, and Security, SAFECOMP 2023 ; Conference date: 19-09-2023 Through 22-09-2023",

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isbn = "9783031409523",

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publisher = "Springer Science and Business Media Deutschland GmbH",

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Hu, L & Zheng, W 2023, Research on the Reliability of High-Speed Railway Dispatching and Commanding Personnel with Multi Physiological Signals. in J Guiochet, S Tonetta, E Schoitsch, M Roy & F Bitsch (eds), Computer Safety, Reliability, and Security. SAFECOMP 2023 Workshops - ASSURE, DECSoS, SASSUR, SENSEI, SRToITS, and WAISE, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 14182 LNCS, Springer Science and Business Media Deutschland GmbH, pp. 230-238, International Conference on Computer Safety, Reliability, and Security, SAFECOMP 2023, Toulouse, France, 19/09/23. https://doi.org/10.1007/978-3-031-40953-0_19

Research on the Reliability of High-Speed Railway Dispatching and Commanding Personnel with Multi Physiological Signals. / Hu, Liuxing; Zheng, Wei.
Computer Safety, Reliability, and Security. SAFECOMP 2023 Workshops - ASSURE, DECSoS, SASSUR, SENSEI, SRToITS, and WAISE, Proceedings. ed. / Jérémie Guiochet; Stefano Tonetta; Erwin Schoitsch; Matthieu Roy; Friedemann Bitsch. Springer Science and Business Media Deutschland GmbH, 2023. p. 230-238 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 14182 LNCS).

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

TY - GEN

T1 - Research on the Reliability of High-Speed Railway Dispatching and Commanding Personnel with Multi Physiological Signals

AU - Hu, Liuxing

AU - Zheng, Wei

PY - 2023

Y1 - 2023

N2 - In the event of equipment failure, traffic accident, natural disaster and other abnormal situations, the timely emergency disposal of the traffic dispatcher is required. In order to accurately evaluate the human reliability of the high-speed railway traffic dispatcher in emergency scenarios, this paper proposes a reliability analysis method based on the Phoenix model. In order to eliminate the dependence of the traditional human reliability analysis method on expert experience, a quantification method based on multiple physiological signals is designed. This paper also gives a specific application of this method in the case of inbound signal machine failure. With this human reliability analysis method, the human reliability of the traffic dispatcher and the causative behavior with the highest probability of failure can be accurately calculated, which can provide a reference for the improvement of the emergency handling protocol.

AB - In the event of equipment failure, traffic accident, natural disaster and other abnormal situations, the timely emergency disposal of the traffic dispatcher is required. In order to accurately evaluate the human reliability of the high-speed railway traffic dispatcher in emergency scenarios, this paper proposes a reliability analysis method based on the Phoenix model. In order to eliminate the dependence of the traditional human reliability analysis method on expert experience, a quantification method based on multiple physiological signals is designed. This paper also gives a specific application of this method in the case of inbound signal machine failure. With this human reliability analysis method, the human reliability of the traffic dispatcher and the causative behavior with the highest probability of failure can be accurately calculated, which can provide a reference for the improvement of the emergency handling protocol.

KW - Human reliability analysis

KW - Physiological signals

KW - Traffic dispatcher

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U2 - 10.1007/978-3-031-40953-0_19

DO - 10.1007/978-3-031-40953-0_19

M3 - 会议稿件

AN - SCOPUS:85172417751

SN - 9783031409523

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

SP - 230

EP - 238

BT - Computer Safety, Reliability, and Security. SAFECOMP 2023 Workshops - ASSURE, DECSoS, SASSUR, SENSEI, SRToITS, and WAISE, Proceedings

A2 - Guiochet, Jérémie

A2 - Tonetta, Stefano

A2 - Schoitsch, Erwin

A2 - Roy, Matthieu

A2 - Bitsch, Friedemann

PB - Springer Science and Business Media Deutschland GmbH

T2 - International Conference on Computer Safety, Reliability, and Security, SAFECOMP 2023

Y2 - 19 September 2023 through 22 September 2023

ER -

Hu L, Zheng W. Research on the Reliability of High-Speed Railway Dispatching and Commanding Personnel with Multi Physiological Signals. In Guiochet J, Tonetta S, Schoitsch E, Roy M, Bitsch F, editors, Computer Safety, Reliability, and Security. SAFECOMP 2023 Workshops - ASSURE, DECSoS, SASSUR, SENSEI, SRToITS, and WAISE, Proceedings. Springer Science and Business Media Deutschland GmbH. 2023. p. 230-238. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-031-40953-0_19

Research on the Reliability of High-Speed Railway Dispatching and Commanding Personnel with Multi Physiological Signals

Abstract

Publication series

Conference

UN SDGs

Keywords

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