Source: NHI course on Travel Demand Forecasting, Ch. 8 (152054A)

Objectives Define external trip purposes Identify the trip distribution inputs for each external trip purpose Identify the trip distribution outputs for each external trip purpose Apply a Fratar distribution to a sample data set

Terminology

Study area boundary location Encompass current urban area plus forecasted urban area (20-25 years) Extend boundary to include commute trips into the area for work, etc. (practical?) Have no more than 15% of VMT from trips that begin or end outside of study area Cover non-attainment area Trip length characteristics Trip characteristics differ depending on whether the trip maker lives within or outside of the study area (so different friction factor curve, right? Really?)

Key Concepts IE is usually modeled as a separate trip purpose Q: what about II trips made by IE travelers?

Inputs and Outputs Inputs for external-internal trips (from external survey) Productions for each external station TAZ Trip length frequency distribution Travel time impedance matrix Scaled NHB attractions by TAZ Inputs for external-external trips Counts at each external station TAZ Origin and destination trip table (base-year) Outputs 24-hr external-internal trip table (P&A) 24-hr external-external trip table (O&D)

Data Collection Vehicle Counting and Classification 24-hr traffic counts for each external station TAZ (to expand survey data) Manual counts used to correct automatic counts (vehicle classification)

External Station Survey Methodology… Have an approved traffic control plan Survey in outbound direction (why?) Move vehicles out of traffic stream Conduct interviews or give postcards Interview in daylight hours only Survey maximum number of vehicles Sample all high volume locations Take random sample of low volume locations

Data Elements to Collect Number of persons in vehicle Highway name/number (for entry and departure) Time entered study area Time departed study area Address of last stop in study area Trip purpose of last stop and next stop Home address (to see if they live in the study area)

Data analysis Expand survey data (count to survey ratio) Separate trips between external-internal and external-external Develop TLFD for external-internal trips (to calibrate gravity model) Distribute external-internal trips Use scaled NHB trips as a proxy Apply the gravity model

Data Analysis Diagonal Always zero

Forecasting Future Year Trip Tables Forecast total volume for each external station Assume split between external-internal and external-external is same as base year Forecast external-internal trip tables Forecast external-external trip tables

Fratar Example