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Norman Washington Garrick CE 2710 Spring 2014 Lecture 07

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1 Norman Washington Garrick CE 2710 Spring 2014 Lecture 07
Transportation Forecasting Trip Generation Norman Washington Garrick CE Spring Lecture 07

2 The Four Step Model Trip Generation
Estimates the number of trips from given origins and destinations Trip Distribution Determines the destination for each trip from a given origin Mode Choice Determines the mode choice for each trip Route Assignment Determines the specific route for each trip

3 Trip Generation Trip Generation model is used to estimate the number of person-trips that will begin or end in a given traffic analysis zone (TAZ) 1 2 3 4 5 6 8 7 The unit of analysis for traffic generation is the TAZ

4 Trip Generation Developing and Using the Model
Survey Base Year Socio-economic, land use and Trip making Calibrated Model Relating trip making to socio-economic and land use data Estimated Target year socio-economic, land use data Predict Target year No. of Trips

5 Trip Generation Form of the Model
The trip generation model typically can take the form of No. of trips = Function (population, income, auto ownership rates) The model is developed and calibrated using the BASE year data

6 Trip Generation Travel Survey
Trip Generation models are often developed from travel surveys. These surveys are used to determine the trip making pattern for a sampling of households in the area. This trip making pattern is then related to land use and socioeconomic factors that are considered to affect travel patterns Common socioeconomic factors considered include population, income, and auto ownership rates

7 Trip Generation Trip Purpose
Often separate predictions are mode for different type of trips since travel behavior depends on trip purpose In other words different models must be developed for each trip type The category of trip types commonly used include Work trips School trips Shopping trips Recreational trips

8 Trip Generation Example of a Trip Generation Model
One way of presenting the trip generation model developed from a survey is as a cross-classification table

9 Trip Generation The Survey and The Model
Survey Base Year Socio-economic, land use And Trip making Calibrated Model Relating trip making to socio-economic and land use data

10 Trip Generation Trip Rates
Total Home-Based-Non-Work Trip Rates Persons per Household Type of Area Vehicles per HH 1 2,3 4 5+ High Density 2+ Low Density

11 Trip Generation Trip Rates
Total Home-Based-Non-Work Trip Rates Persons per Household Type of Area Vehicles per HH 1 2,3 4 5+ High Density 0.6 1.5 2+ 1.8 Low Density

12 Trip Generation Trip Rates
Total Home-Based-Non-Work Trip Rates Persons per Household Type of Area Vehicles per HH 1 2,3 4 5+ High Density 0.6 7.0 1.5 7.9 2+ 1.8 8.3 Low Density

13 Trip Generation Trip Rates
Total Home-Based-Non-Work Trip Rates Persons per Household Type of Area Vehicles per HH 1 2,3 4 5+ High Density 0.6 2.1 4.6 7.0 1.5 3.0 5.5 7.9 2+ 1.8 3.4 5.9 8.3 Low Density

14 Trip Generation Trip Rates
Total Home-Based-Non-Work Trip Rates Persons per Household Type of Area Vehicles per HH 1 2,3 4 5+ High Density 0.6 2.1 4.6 7.0 1.5 3.0 5.5 7.9 2+ 1.8 3.4 5.9 8.3 Low Density 1.0 2.5 5.0 7.4 1.9 3.5 6.0 8.4 2.3 3.9 6.4 9.0

15 Trip Generation Estimating Target Year Data
Calibrated Model Relating trip making to socio-economic and land use data Estimated Target year socio-economic, land use data

16 Trip Generation Target Year Data
Number of Households in Target Year Persons per Household Type of Area Vehicles per HH 1 2,3 4 5+ High Density 2+ Low Density

17 Trip Generation Target Year Data
Number of Households in Target Year Persons per Household Type of Area Vehicles per HH 1 2,3 4 5+ High Density 100 200 300 2+ Low Density

18 Trip Generation Target Year Data
Number of Households in Target Year Persons per Household Type of Area Vehicles per HH 1 2,3 4 5+ High Density 100 200 300 2+ Low Density 50 10

19 Trip Generation Predicting Number of Trips
Calibrated Model Relating trip making to socio-economic and land use data Estimated Target year socio-economic, land use data Predict Target year No. of Trips

20 Trip Generation Predicting Number of Trips
Number of Trips in Target Year for Each HH Type Persons per Household Type of Area Vehicles per HH 1 2,3 4 5+ High Density 2+ Low Density 60 Number of Trips = trip rate*no. of HH = 0.6 * 100 = 60

21 Trip Generation Predicting Number of Trips
Number of Trips in Target Year for Each HH Type Persons per Household Type of Area Vehicles per HH 1 2,3 4 5+ High Density 60 420 460 700 300 900 1100 790 2+ 180 680 590 1660 Low Density 50 250 500 740 190 600 840 230 390 640 90

22 Trip Generation Planning for the Future and Uncertainties
Earlier we talked about the uncertainties associated with making prediction for the future and the importance of not treating predictions as if they are set in stone but rather as a guide to help in decision making In considering the ‘trip generation’ process it is important to understand some potential sources of uncertainties

23 Trip Generation Sources of Uncertainties in Predicting Number of Trips
Significant errors can creep into the trip generation process in a number of places including Errors in the survey Who is surveyed, how well was the survey constructed, did we consider all important parameters? Errors in the prediction of future demographics Will the population grew, what will be the make up of the population Errors in how well the model can actually reflect the future Will the land use change, will transportation change, will technology change, will peoples attitudes change

24 Trip Generation Effect of Changes in Land Use
Changes in Land use and the type of transportation provided can have a huge impact on travel But the trip generation process typically assume that this factor is constant over the period of the study

25 Trip Generation Demographics and Trip Making Factors affected by Land Use
The land use pattern and transportation type may affect Car ownership rates Household size and composition Number of daily trips Mode of trips Length of trips


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