Human Factors Phase IV: Risk Analysis Tool for New Train Control Technology

Lanzilotta, E.; Sheridan, T.; John A. Volpe National Transportation Systems Center (U.S.); Massachusetts Institute of Technology; United States. Department of Transportation. Research and Special Programs Administration; United States. Department of Transportation. Federal Railroad Administration

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Human Factors Phase IV: Risk Analysis Tool for New Train Control Technology

2005-01-01
By Lanzilotta, E. ; Sheridan, T.

[PDF-2.92 MB]

English

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Details:

Creators:

Lanzilotta, E. ; Sheridan, T.

Lanzilotta, E. ; Sheridan, T. Less -
Corporate Creators:

John A. Volpe National Transportation Systems Center (U.S.) ; Massachusetts Institute of Technology ; United States. Department of Transportation. Research and Special Programs Administration ; United States. Department of Transportation. Federal Railroad Administration

John A. Volpe National Transportation Systems Center (U.S.) ; Massachusetts Institute of Technology ; United States. Department of Transportation. Research and Special Programs Administration ; United States. Department of Transportation. Federal Railroad Administration Less -
Subject/TRT Terms:

[+]

Automatic Train Control Automation Estimating High-speed Trains Human-in-the-loop Simulation Human Factors Markov Processes Operations Probability Railroads Railroad Safety Railroad Trains Risk Analysis Risk Estimation Safety Safety State Models Stochastic Processes Supervisory Controls Technology Train Control Transportation
Publication/ Report Number:

DOT-VNTSC-FRA-05-02 ; DOT/FRA/ORD-04/17

DOT-VNTSC-FRA-05-02 ; DOT/FRA/ORD-04/17 Less -
Resource Type:

Tech Report
Geographical Coverage:

United States
Edition:

Final Report August 1993 - July 1997
Corporate Publisher:

United States. Department of Transportation. Federal Railroad Administration
Abstract:

This report covers the theoretical development of the safety state model for railroad operations. Using data from a train control technology experiment, experimental application of the model is demonstrated. A stochastic model of system behavior is developed which is used to estimate the dynamic risk probability in a human-machine system. This model is based on a discrete Markov process model. Based on observer behavior of an existing system, the model is used to determine an instantaneous risk probability function, which is dependent on the system state.
Format:

PDF
Funding:

RR293/R2032 ; R2103/RR204

RR293/R2032 ; R2103/RR204 Less -
Collection(s):

Federal Railroad Administration Volpe Center
Main Document Checksum:

[+]

urn:sha256:c2280d9c0ef3dd59d545b78c856794671d28cd34c062c2155684e432637ae0ad
Download URL:

https://rosap.ntl.bts.gov/view/dot/8756/dot_8756_DS1.pdf
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Human Factors Phase IV: Risk Analysis Tool for New Train Control Technology

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