STUDY ON THE SHORTEST PATH ALGORITHM BASED ON FLUID NEURAL NETWORK OF IN-VEHICLE TRAFFIC-FLOW GUIDANCE SYSTEM

This paper describes a new shortest path algorithm for route guidance that is based on a parallel Fluid Neural Network (FNN) and a genetic algorithm. Simulation results reveal that this method can be used to quickly find the shortest route from the origin node to the destination node in traffic networks.

Language

  • English

Media Info

  • Pagination: p. 110-113

Subject/Index Terms

Filing Info

  • Accession Number: 00963584
  • Record Type: Publication
  • Source Agency: UC Berkeley Transportation Library
  • Files: PATH
  • Created Date: Oct 2 2003 12:00AM