A BEHAVIORAL COMPONENT ANALYSIS OF ROUTE GUIDANCE SYSTEMS USING NEURAL NETWORKS

Route guidance systems (RGS) are considered to be a low-cost alternative for reduction of traffic congestion by providing real-time information to drivers to redistribute traffic in space and time to enable use of highway networks more efficiently. This paper looks at the behavioral component, 1 of 3 components of a practical RGS developed within a 4-year project at the University of Delaware. Development of the behavioral model is based on the premise that drivers perceive and behave differently in response to the information provided. Backpropagation neural networks with their ability to map complex input-output relationships were used to structure the model, which was tested on 2 networks under both recurring and nonrecurring congestion. A comparative analysis of the measures of effectiveness revealed that the performance of the developed RGS is significantly better than the performance under existing non-RGS conditions.

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  • Corporate Authors:

    Blackwell Publishing

    350 Main Street
    Malden, MA  United States  02148
  • Authors:
    • Hamad, K
    • Faghri, A
    • Nanda, R
  • Publication Date: 2003-11

Language

  • English

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Filing Info

  • Accession Number: 00964518
  • Record Type: Publication
  • Files: TRIS
  • Created Date: Oct 10 2003 12:00AM