Trip Generation ModelingâCross-Classification

1 / 8

# Trip Generation ModelingâCross-Classification - PowerPoint PPT Presentation

Trip Generation Modeling—Cross-Classification. CE 573 Transportation Planning Lecture 2 (2 nd part). Cross-classification (category analysis): Introduction. Trip production: p = trip purpose i = zone h = household type grouping a i ( h ) = number of households of type h in zone i

I am the owner, or an agent authorized to act on behalf of the owner, of the copyrighted work described.

## PowerPoint Slideshow about 'Trip Generation ModelingâCross-Classification' - dawn-sanford

Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author.While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server.

- - - - - - - - - - - - - - - - - - - - - - - - - - E N D - - - - - - - - - - - - - - - - - - - - - - - - - -
Presentation Transcript

### Trip Generation Modeling—Cross-Classification

CE 573 Transportation Planning

Lecture 2 (2nd part)

Cross-classification (category analysis): Introduction
• Trip production:
• p = trip purpose
• i = zone
• h = household type grouping
• ai(h) = number of households of type h in zone i
• tp(h) = trip rate for trip of type p for households of type h
Cross-classification (category analysis): Example

Situation: Zone 23 characteristics are as follows:

Home based work (HBW) trip production data are as follows:

• Establish household groupings
• Assign households to the groupings
• Total, for each grouping the observed trips [Tp(h)]
• p is the trip purpose
• h is the grouping
• Total, for each grouping the observed households [H(h)]
• H is the number of households observed
• h is the grouping
• Calculate the trip rates by grouping [tp(h) = Tp(h)/ H(h)]
Cross-classification (category analysis)
• Independent of zone system
• No regression related assumptions necessary