utps (review from last time)
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GEOG 111/211A Transportation Planning
UTPS (Review from last time) • Urban Transportation Planning System
– Also known as the Four - Step Process– A methodology to model traffic on a network– Developed in 1962 (Chicago)
• Four Steps:– Trip Generation Estimate Person Trips for each
TAZ– Trip Distribution Distribute Person Trips from TAZ to TAZ
– Mode Choice Convert Person Trips to Vehicle Trips
– Traffic Assignment Assign Vehicles to the Network
Oct/Nov 2004
GEOG 111/211A Transportation Planning
Survey Data – interviews of persons about their behavior
Models of behavior – extract key aspects to capture most variation
Use models – incorporate models into a computerized map
If no survey available?
Discuss options in class!
GEOG 111/211A Transportation Planning
The Four Steps:• Trip Generation = Estimate Person Trips for each TAZ• Trip Distribution = Distribute Person Trips from TAZ to
TAZ• Mode Choice = Convert Person Trips to Vehicle Trips• Traffic Assignment = Assign Vehicles to the Network
• Pre 4-step = Land Use and Demographics?• Post 4-step = Emissions, Traffic Simulation, Link by Link
Evaluation
GEOG 111/211A Transportation Planning
Key Concepts of UTPS• TAZ: Traffic Analysis Zone
– A TAZ is an arbitrary subdivision of the study area– TAZs are used in trip generation and trip distribution– TAZs may be any shape or size, but US Census Blocks,
Block Groups, and Tracts are often used
Block Block Group Tract
i.e., a city block
GEOG 111/211A Transportation Planning
Key Concepts of UTPS• Centroid
– Every TAZ (Gate and Internal Zone) has a centroid, usually placed roughly at the geographic center of the TAZ
– All trips to or from a TAZ are assumed to start or end at the centroid
• Discussion– Why do we use TAZs and centroids to model trips?
GEOG 111/211A Transportation Planning
Key Concepts of UTPS• Gate TAZs
– TAZs placed outside the Study Area where major roads cross the boundaries of the study area
– Used to model External Trips (i.e., trips with an origin or destination or both outside the study area)
– Gate TAZs represent all areas outside of the study area
(Study Area)
Gate TAZ
Network
GEOG 111/211A Transportation Planning
Gate TAZ
Centroid
GEOG 111/211A Transportation Planning
Every zone is a node (the centroid) with an identifier and type
GEOG 111/211A Transportation Planning
Trip Generation
Additional suggested reading material: Ortuzar & Willumsen, third edition,
Chapter 4.
GEOG 111/211A Transportation Planning
Trip Generation Objectives• Estimate amount of trip making going out of a TAZ • Estimate amount of trip making going into a TAZ• Account for differences among TAZs due to person
and household characteristics• Account for differences among TAZs due to
business (establishments) characteristics• Develop functions to predict future amount of trip
making
GEOG 111/211A Transportation Planning
Trip Generation Usual Process• Collect Data, usually by Surveys and Census
– Sociodemographic Data and Travel Behavior Data• Create Trip Generation Models• Estimate the number of Productions and Attractions
for each TAZ, by Trip Purpose • Balance Productions and Attractions for each Trip
Purpose– Total number of Productions and Attractions must be
equal for each Trip Purpose
GEOG 111/211A Transportation Planning
Trip Generation Models• Regression Models
– Explanatory Variables are used to predict trip generation rates, usually by Multiple Regression
• Trip Rate Analysis– Average trip generation rates are associated with different trip
generators or land uses• Cross - Classification / Category Analysis
– Average trip generation rates are associated with different trip generators or land uses as a function of generator or land use attributes
• Models may be TAZ, Household, or Person - Based
GEOG 111/211A Transportation Planning
Usual Unit of Analysis• TAZ - zonal rates (Number of trips as a function of a
zone’s population characteristics)• Household rates (Number of trips as a function of
household characteristics)• Person rates (Number of trips as a function of person
characteristics)
• NEW (PennState Research)! Multilevel rates (Number of trips as a function of person & household & TAZ characteristics)
GEOG 111/211A Transportation Planning
Units and Models• TAZ-based models = productions and attractions
converted to origins and destinations
• Household and/or person - based models = origins and destinations
• Establishment - based = attractions need to convert to destinations
GEOG 111/211A Transportation Planning
Common Trip Definitions in CE422• Trip: a one - way movement from one place to another• HB = Home Based: a trip where the home of the traveler is
either the origin or the destination of the trip• HBW = Home Based Work: trips between home and work• HBNW = Home Based Non-Work: trips between home
and shopping, also called HBS (Home Based Shopping)• HBO = Home Based Other: trips between home and a non
- work / shopping location• NHB = Non Home Based: trips where neither end of the
trip is the home of the traveler
GEOG 111/211A Transportation Planning
Related Definitions
Home
Work
School
1.Home-based school trip
2.NonHome-based work trip
3. Home-based work trip
1+2+3=Tour or Trip Chain (home-based)
GEOG 111/211A Transportation Planning
Productions - Attractions
ResidentialArea
Non-ResidentialArea
Non-ResidentialArea
Non-ResidentialArea
Production
Production
Production
Attraction
Attraction
Attraction
Attraction
Production
All Home - Based Trips
Non - Home - Based Trips
= Origin= Destination
See also OW-p. 124
GEOG 111/211A Transportation Planning
Trip Balancing Methods• Hold Productions Constant
– Attractions are multiplied by the ratio of the sum of non-gate productions to the sum of non - gate attractions
– Most common form of trip balancing• Hold Attractions Constant
– Productions are multiplied by the ratio of the sum of non-gate productions to the sum of non - gate attractions
• Hold Neither Productions or Attractions Constant– Not used very often
Note: Gate Productions and Attractions are not included in this balancing process
GEOG 111/211A Transportation Planning
Examples• http://tmip.fhwa.dot.gov/clearinghouse/docs/Time-D
ay/ - discussion of time-of-day issues
• http://www.psrc.org/datapubs/index.htm (this is the metropolitan plan where models are used)
• http://tmip.fhwa.dot.gov/clearinghouse/ <the ultimate web site for GEOG 111/211A>
All sites verified October 2004
GEOG 111/211A Transportation Planning
Gate Trip Estimation• Gate Trips Must be Modeled Separately
– Gates have specific traffic volumes associated with them– Gates do not have sociodemographic data– Gates may represent trips with extremely variable trip
lengths• Gate Trip Modeling
– Correlate percentages of traffic volumes to different trip purposes (e.g., X% * Total daily volume observed = trips for commuting)
GEOG 111/211A Transportation Planning
ITE Trip Generation Manual• Trip Rate Analysis Model
– Univariate regression for trip generation– Primarily for businesses (attraction rates)– Explanatory variables are usually number of employees or
square footage– Models developed using data from national averages and
numerous studies from around the US
Copies of the ITE Trip Generation Manual may be Found in the Hammond and PTI Libraries
GEOG 111/211A Transportation Planning
GEOG 111/211A Transportation Planning
TAZ Issues
• Data availability limited by privacy issues• Larger TAZs, with complete data, are no longer
necessarily homogeneous• Model accuracy decreases with larger TAZs
TAZ Scale Modeling Accuracy Data Availability
Block Good Poor
Block Group Not Good Excellent
Tract Poor Good
GEOG 111/211A Transportation Planning
Model Formulation and Surveys• Privacy
– May limit data collection efforts– Private information must remain secure
• Response Rate– Good survey should have at least 85% response rate
• Representative Sample Size– Pop. representation most important
• Model Stability and Transferability– Over time, behavior may change– Behavior is not necessarily the same from place to place
GEOG 111/211A Transportation Planning
Trip Generation Example• Similar to the lab exercise• From the Puget Sound Region in 1989• Subsistence (work + school trips)• These are one way trips (origins) instead of
productions
GEOG 111/211A Transportation Planning
Sample DescriptivesDescriptive Statistics
1621 1.00 7.00 2.7378 1.17211621 .00 5.00 .4349 .79831621 .00 3.00 .2295 .55811621 .00 8.00 2.3146 1.11261559 15.00 90.00 46.9602 14.21441621 .00 1.00 .6539 .47591621 .00 7.00 .8421 .87401559
HHSIZETOT6_17TOT1_5NUMVEHAGEEMPLOYSFREQ1Valid N (listwise)
N Minimum Maximum MeanStd.
Deviation
Class: What do you observe?
GEOG 111/211A Transportation Planning
Trip Generation Linear RegressionModel for Subsistence Trips
Coefficientsa
.409 .120 3.413 .0019.99E-03 .035 .013 .283 .7782.50E-02 .042 .023 .595 .552
-.116 .049 -.075 -2.380 .017-8.5E-03 .019 -.011 -.437 .662-4.4E-03 .002 -.071 -2.685 .007
.986 .043 .536 22.838 .000
(Constant)HHSIZETOT6_17TOT1_5NUMVEHAGEEMPLOY
Model1
B Std. Error
UnstandardizedCoefficients
Beta
Standardized
Coefficients
t Sig.
Dependent Variable: SFREQ1a.
Class: Interpret the model
GEOG 111/211A Transportation Planning
Goodness of fitANOVAb
385.290 6 64.215 124.186 .000a
802.521 1552 .5171187.811 1558
RegressionResidualTotal
Model1
Sum ofSquares df
MeanSquare F Sig.
Predictors: (Constant), EMPLOY, TOT1_5, TOT6_17, NUMVEH, AGE, HHSIZEa.
Dependent Variable: SFREQ1b.
Model Summary
.570a .324 .322 .7191Model1
R R SquareAdjusted R
Square
Std. Errorof the
Estimate
Predictors: (Constant), EMPLOY, TOT1_5, TOT6_17,NUMVEH, AGE, HHSIZE
a.
GEOG 111/211A Transportation Planning
Let’s Improve the Model
If (age < 20) Teen = 1 .If (age >= 20 and age < 35) Young=1.If (age >= 35 and age < 65) Midage=1.If (age >= 65 and age < 75) Senior=1.If (age >=75) VSenior=1.
GEOG 111/211A Transportation Planning
Descriptives of the New VarsDescriptive Statistics
1621 .00 1.00 .1777 .38241621 .00 1.00 1.73E-02 .13031621 .00 1.00 .6268 .48381621 .00 1.00 .1154 .31961621 .00 1.00 2.47E-02 .15521621
YOUNGTEENMIDAGESENIORVSENIORValid N (listwise)
N Minimum Maximum MeanStd.
Deviation
GEOG 111/211A Transportation Planning
Linear RegressionCoefficientsa
.221 .094 2.355 .0191.037 .043 .565 24.120 .000.659 .163 .098 4.050 .000
-.133 .100 -.058 -1.321 .187-4.2E-02 .094 -.023 -.451 .652
-.118 .106 -.043 -1.106 .269-.197 .146 -.035 -1.343 .179
(Constant)EMPLOYTEENYOUNGMIDAGESENIORVSENIOR
Model1
B Std. Error
UnstandardizedCoefficients
Beta
Standardized
Coefficients
t Sig.
Dependent Variable: SFREQ1a.
GEOG 111/211A Transportation Planning
Leisure Trip GenerationCoefficientsa
2.298 .191 12.057 .000-9.9E-02 .087 -.032 -1.129 .259-4.8E-02 .331 -.004 -.146 .8841.38E-02 .204 .004 .068 .946-4.8E-02 .190 -.016 -.253 .800
-.170 .216 -.037 -.786 .432-.545 .298 -.058 -1.831 .067
(Constant)EMPLOYTEENYOUNGMIDAGESENIORVSENIOR
Model1
B Std. Error
UnstandardizedCoefficients
Beta
Standardized
Coefficients
t Sig.
Dependent Variable: LFREQ1a.
The same model as for subsistence did not work!!!!!
GEOG 111/211A Transportation Planning
New model for leisureCoefficientsa
1.682 .178 9.425 .000.339 .166 .052 2.045 .041
-8.0E-05 .000 -.027 -1.050 .294.261 .045 .144 5.771 .000
7.94E-02 .064 .031 1.241 .2152.64E-02 .033 .020 .795 .427-8.8E-02 .073 -.030 -1.206 .228-1.4E-03 .001 -.034 -1.384 .1679.96E-02 .046 .054 2.171 .030
(Constant)LICENSEWKDISTTOT6_17TOT1_5NUMVEHSEXSTUDENTS1
Model1
B Std. Error
UnstandardizedCoefficients
Beta
Standardized
Coefficients
t Sig.
Dependent Variable: LFREQ1a.
GEOG 111/211A Transportation Planning
Goodness of fitANOVAb
95.414 8 11.927 5.814 .000a
3306.909 1612 2.0513402.323 1620
RegressionResidualTotal
Model1
Sum ofSquares df
MeanSquare F Sig.
Predictors: (Constant), S1, SEX, STUDENT, TOT1_5, TOT6_17, LICENSE,WKDIST, NUMVEH
a.
Dependent Variable: LFREQ1b.
Model Summary
.167a .028 .023 1.4323Model1
R R SquareAdjusted R
Square
Std. Errorof the
Estimate
Predictors: (Constant), S1, SEX, STUDENT, TOT1_5,TOT6_17, LICENSE, WKDIST, NUMVEH
a.
GEOG 111/211A Transportation Planning
Compare frequencies
LFREQ1
12.010.08.06.04.02.00.0
1000
800
600
400
200
0
Std. Dev = 1.45
Mean = 2.2
N = 1621.00
SFREQ1
7.06.05.04.03.02.01.00.0
700
600
500
400
300
200
100
0
Std. Dev = .87
Mean = .8
N = 1621.00
Class: Which one is easier to estimate?
GEOG 111/211A Transportation Planning
Traditional Trip Generation• Input: social and economic characteristics• Output: productions/attractions, origins/destinations
by zone• Key concepts: trip generation by purpose maybe
more accurate but some purposes easier to predict (trips to work)
• Other: Goods movement productions/attractions are handled in a similar way (Freight Forecasting Manual exists)
GEOG 111/211A Transportation Planning
Post-MTC Lawsuit Models• Level of service = “quality” of transportation system
measured in travel time from an origin to a destination• Trip generation also function of level of service• New models for induced demand = new demand for
travel after improvements in level of service• Activity-based models to reflect “scheduling” of
persons, coordination of activities• Multilevel models to reflect within group coordination
GEOG 111/211A Transportation Planning
In the Lab - Check• TAZ population and productions• Businesses and attractions• What do you expect the relationship to be?• Does the relationship make sense?
GEOG 111/211A Transportation Planning
Summary• Collect data using surveys• Derive a model using statistics• Use the model to predict number of trips generated
in each zone• Apply this at each centroid representing a zone• Have all this ready for the next step – trip
distribution
If you cannot run a survey – use equations from ITE trip generation manual or other studies – check for similarities/verify results!
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