An evaluation of the transferability of cross classification trip generation models.

Details

• Creators:
  Caldwell, Lawrence C ; Demetsky, Michael J
• Corporate Creators:
  United States. Federal Highway Administration ; Virginia Highway & Transportation Research Council
• Subject/TRT Terms:
  • Trip generation
  • Travel demand
  • Mathematical models
  • Trip generation--Virginia
  • Trip generation--Analysis
  • Trip generation--Mathematical models
  • Transportation--Mathematical models--Virginia
• Publication/ Report Number:
  VHTRC 78-R39
• Resource Type:
  Tech Report
• Geographical Coverage:
  Virginia
• Corporate Publisher:
  Virginia Transportation Research Council (VTRC)
• Abstract:
  This report describes the results of the application in Virginia of the trip generation procedures described in the Federal Highway Administration report entitled Trip Generation Analysis and published in 1975. Cross classification models, disaggregate regression models, aggregate regression models, and trip rates were developed for three cities. The model for each of the cities was transferred to the two other cities and comparisons were made. The comparisons revealed that models calibrated on aggregate zonal data perform better than models calibrated with disaggregate household data when forecasting with aggregate data. However, if cross classification models are acceptable, they can be transferred between cities if good judgment is used to select cities that are similar enough for transferring models. The report recommends the establishment of a standard procedure for data collection and trip generation analysis in selected studies of the near future so that the transferability question can be properly addressed. The emphasis should be on the development of new prototype models for application in groups of cities.
• Format:
  PDF
• Download URL:
  https://rosap.ntl.bts.gov/view/dot/18789/dot_18789_DS1.pdf
• File Type:
  [PDF - 2.06 MB]
• Collection(s):
  US Transportation Collection
• Main Document Checksum:
  urn:sha256:8ee1a97361c215242272521d5a0bf271802faeb38f13f3682381f17be103c069