ESTIMATION OF PERCENTAGE OF PASS-BY TRIPS GENERATED BY A SHOPPING CENTER USING ARTIFICIAL NEURAL NETWORKS

New development in an area has the potential of affecting the surrounding transportation infrastructure. To asses the effect of a development, transportation planners need to perform a Site Impact Traffic Evaluation (SITE). A development generates three different types of trips: primary trips, diverted linked trips, and pass-by trips. This paper isolates pass-by trips to estimate the actual impact of a new development on the surrounding infrastructure, and it proposes a method to predict better the percentage of pass-by trips that a proposed shopping center development will generate. The traditional method of regression analysis is applied to the database used, and an Artificial Neural Network (ANN)- based model is developed to capture the relationship between the percentage of pass-by trips and the influencing factors.

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  • Corporate Authors:

    GORDON AND BREACH SCIENCE PUB.

    AMSTERDAM:
    ,    
  • Authors:
    • Faghri, A
    • Aneja, S
    • Vaziri, M
  • Publication Date: 1999

Language

  • English

Media Info

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Filing Info

  • Accession Number: 00768015
  • Record Type: Publication
  • Files: TRIS
  • Created Date: Aug 29 1999 12:00AM