Norman Washington G arrick CE 2710 Spring 2014 Lecture 07
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Transportation Forecasting Trip Generation
description
Transportation Forecasting Trip Generation. Norman Washington G arrick CE 2710 Spring 2014 Lecture 07. The Four Step Model. Trip Generation Estimates the number of trips from given origins and destinations Trip Distribution - PowerPoint PPT Presentation
Transcript of Norman Washington G arrick CE 2710 Spring 2014 Lecture 07
Transportation ForecastingTrip Generation
The Four Step Model• Trip Generation
Estimates the number of trips from given origins and destinations
• Trip DistributionDetermines the destination for each trip from a given origin
• Mode ChoiceDetermines the mode choice for each trip
• Route AssignmentDetermines the specific route for each trip
Trip GenerationTrip Generation model is used to estimate the number of person-trips
that will begin or end in a given traffic analysis zone (TAZ)
The unit of analysis for traffic generation is the TAZ
1
23
4
5
6
87
Trip GenerationDeveloping and Using the Model
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
Survey Base YearSocio-economic, land use
and Trip making
Trip GenerationForm 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
Trip GenerationTravel 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
Trip GenerationTrip 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
Trip GenerationExample of a Trip Generation Model
One way of presenting the trip generation model developed from a survey is as a cross-classification table
Trip GenerationThe Survey and The Model
Calibrated Model
Relating trip making to socio-economic and land use data
Survey Base YearSocio-economic, land use
And Trip making
Trip GenerationTrip Rates
Total Home-Based-Non-Work Trip RatesPersons per Household
Type of Area
Vehicles per HH
1 2,3 4 5+
High Density 01
2+Low Density 0
12+
Trip GenerationTrip Rates
Total Home-Based-Non-Work Trip RatesPersons per Household
Type of Area
Vehicles per HH
1 2,3 4 5+
High Density 0 0.61 1.5
2+ 1.8Low Density 0
12+
Trip GenerationTrip Rates
Total Home-Based-Non-Work Trip RatesPersons per Household
Type of Area
Vehicles per HH
1 2,3 4 5+
High Density 0 0.6 7.01 1.5 7.9
2+ 1.8 8.3Low Density 0
12+
Trip GenerationTrip Rates
Total Home-Based-Non-Work Trip RatesPersons per Household
Type of Area
Vehicles per HH
1 2,3 4 5+
High Density 0 0.6 2.1 4.6 7.01 1.5 3.0 5.5 7.9
2+ 1.8 3.4 5.9 8.3Low Density 0
12+
Trip GenerationTrip Rates
Total Home-Based-Non-Work Trip RatesPersons per Household
Type of Area
Vehicles per HH
1 2,3 4 5+
High Density 0 0.6 2.1 4.6 7.01 1.5 3.0 5.5 7.9
2+ 1.8 3.4 5.9 8.3Low Density 0 1.0 2.5 5.0 7.4
1 1.9 3.5 6.0 8.42+ 2.3 3.9 6.4 9.0
Trip GenerationEstimating Target Year Data
Calibrated Model
Relating trip making to socio-economic and land use data
Estimated Target year
socio-economic,land use data
Trip GenerationTarget Year Data
Number of Households in Target YearPersons per Household
Type of Area
Vehicles per HH
1 2,3 4 5+
High Density 01
2+Low Density 0
12+
Trip GenerationTarget Year Data
Number of Households in Target YearPersons per Household
Type of Area
Vehicles per HH
1 2,3 4 5+
High Density 0 100 200 100 100
1 200 300 200 100
2+ 100 200 100 200
Low Density 01
2+
Trip GenerationTarget Year Data
Number of Households in Target YearPersons per Household
Type of Area
Vehicles per HH
1 2,3 4 5+
High Density 0 100 200 100 100
1 200 300 200 100
2+ 100 200 100 200
Low Density 0 50 100 100 100
1 100 200 100 100
2+ 100 100 100 10
Trip GenerationPredicting 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
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 01
2+Low Density 0
12+
Trip GenerationPredicting Number of Trips
Number of Trips = trip rate*no. of HH = 0.6 * 100 = 60
60
Trip GenerationPredicting 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 0 60 420 460 700
1 300 900 1100
790
2+ 180 680 590 1660
Low Density 0 50 250 500 740
1 190 700 600 840
2+ 230 390 640 90
Trip GenerationPlanning 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
Trip GenerationSources 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 demographicsWill 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
Trip GenerationEffect 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
Trip GenerationDemographics 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
