PREDICTIVE ACCURACY OF DISAGGREGATE BEHAVIOURAL MODELS OF NEW RAILWAY STATION'S USAGE

The predictability of Nested Logit (NL) models was examined at the aggregate level as well as the disaggregate sample level, using the before-and-after data on a new railway station. The NL models tested have a three-level structure, containing line-haul mode, station, and access mode choices. We showed (1) the temporal stability of the choice structure, the independent variables and the parameters is very high, and (2) the prediction error on the usage of the new railway station is within 20 percent, using simplified aggregation procedures. So, we concluded that the NL models have high applicability for the prediction of the station's usage. (Author abstract)

• Availability:
  • Find a library where document is available. Order URL: http://worldcat.org/issn/05783747
• Corporate Authors:

  Japan Society of Civil Engineers

  1-chome, Yotsuya, Shinjuku-ku
  Tokyo,   Japan  160-0004
• Authors:
  • HARATA, N
  • OHTA, K
  • NIITANI, Y
• Publication Date: 1984-7

Media Info

• Features: References;
• Pagination: p. 49-58
• Serial:
  • Japan Society of Civil Engineers, Proceedings
  • Issue Number: 347
  • Publisher: Japan Society of Civil Engineers
  • ISSN: 0578-3747

Subject/Index Terms

• TRT Terms: Disaggregate analysis; Logits; Mathematical models; Railroad facilities; Railroad stations; Structural design; Transportation
• Uncontrolled Terms: Nested logit models
• Old TRIS Terms: Aggregate level; Disaggregate behavioral models; Disaggregate models; Predictive accuracy; Station design
• Subject Areas: Planning and Forecasting; Transportation (General);

Filing Info

• Accession Number: 00455220
• Record Type: Publication
• Source Agency: Engineering Index
• Files: TRIS
• Created Date: Aug 27 2004 10:00PM