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Railway cognitive radio to enhance safety, security, and performance of positive train control.

Filetype[PDF-1.75 MB]


English
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  • Creators:
    Amanna, Ashwin
  • Corporate Creators:
    Virginia Polytechnic Institute and State University
  • Subject/TRT Terms:
  • Publication/ Report Number:
    DOT/FRA/ORD-13/09
  • Resource Type:
    Tech Report
  • Geographical Coverage:
    United States
  • Corporate Publisher:
    United States. Federal Railroad Administration. Office of Research and Development
  • NTL Classification:
    NTL-RAIL TRANSPORTATION-Rail Safety;NTL-SAFETY AND SECURITY-Rail Safety;NTL-OPERATIONS AND TRAFFIC CONTROLS-Traffic Control Devices;
  • Abstract:
    Robust and interoperable wireless communications are vital to Positive Train Control (PTC). The railway industry has started adopting software-defined radios (SDRs) for packet-data transmission. SDR systems realize previously fixed components as reconfigurable software. This project developed a railway cognitive radio (Rail-CR) which implements Artificial Intelligence (AI) decisionmaking in concert with an SDR to adapt to changing wireless conditions and learn from past experience. Objectives of the project included developing a concept of operations for wireless link adaptation based on use-case scenarios for packet radio systems, designing and implementing a decisionmaking architecture on an SDR, designing strategies for radio environment observations, defining operational objectives and performance metrics, and designing and exercising a test plan to demonstrate performance under varying conditions. The decisionmaking architecture of the Rail-CR begins with observations of the wireless environment and performance metrics. The architecture enables adaptation to new situations and the capability to learn from past decisions. The Rail-CR was tested under a variety of interference conditions designed to simulate real-world experiences. Results show that a radio operating with no-cognition was unable to mitigate interference conditions causing either significantly high errors or a loss of connectivity. The Cognitive Engine (CE) successfully overcame the interference by changing configurable parameters.
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