An Estimation of Intercity Bus Travel Time by Using Auto Travel Time Data

This paper will focus on the development of an analytic model for estimating inter-city bus arrival time at a certain bus stop by utilizing link travel time data from the passenger car. The methodology adopted in the development of the estimation model was the artificial neural network algorithm. Three objectives were identified for the research. These were: 1) collecting field data for identifying characteristics of bus route, 2) formulating an artificial neural network model for estimating the bus travel time, and 3) testing the model with real data. According to the preliminary results, artificial neural network model was very much promising in terms of error rates.

• Corporate Authors:

  ITS America

  1100 17th Street, NW, 12th Floor
  Washington, DC  United States  20036
• Authors:
  • Bae, Sanghoon
• Conference:
  • 12th World Congress on Intelligent Transport Systems
  • Location: San Francisco California, United States
  • Date: 2005-11-6 to 2005-11-10
• Publication Date: 2005

Language

• English

Media Info

• Media Type: Print
• Features: CD-ROM; Figures; References; Tables;
• Pagination: 7p
• Monograph Title: Proceedings of the 12th World Congress on Intelligent Transport Systems

Subject/Index Terms

• TRT Terms: Artificial intelligence; Automobile travel; Bus transit; Bus transportation; Data collection; Estimation theory; Intercity transportation; Neural networks; Public transit; Travel time
• Subject Areas: Data and Information Technology; Highways; Motor Carriers; Operations and Traffic Management; Planning and Forecasting; Public Transportation; I72: Traffic and Transport Planning;

Filing Info

• Accession Number: 01015872
• Record Type: Publication
• Files: TRIS
• Created Date: Jan 31 2006 9:56AM