Enhancing intelligent agent collaboration for flow optimization of railroad traffic

Jeremy Joseph Blum, Azim Eskandarian

Research output: Contribution to journalArticlepeer-review

25 Scopus citations

Abstract

Intelligent agents have successfully solved the train pathing problem on a small portion of railroad network [Tsen, 1995, Ph.D. Thesis, Carnegie Mellon University, USA]. As the railroad network grows, it is imperative that the agents collaborate to operate as efficiently as possible. In this paper, the authors demonstrate a collaboration protocol based on a conditional measure of agent effectiveness. Because agent effectiveness is not directly measurable, a suitable metric for agent effectiveness is introduced. Where typically agents run with uniform frequency, the collaboration protocol schedules the agents with a frequency proportional to their expected effectiveness. This protocol introduced a 10-fold improvement in the agent efficiency when tested with a simulation program on a portion of the Burlington Northern railroad.

Original languageEnglish (US)
Pages (from-to)919-930
Number of pages12
JournalTransportation Research Part A: Policy and Practice
Volume36
Issue number10
DOIs
StatePublished - Dec 1 2002

All Science Journal Classification (ASJC) codes

  • Management Science and Operations Research
  • Civil and Structural Engineering
  • Transportation

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