RPS Land Use and Transportation Modeling Results Presentation to RPS TAC & MPO TAC Brian Gregor...
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Transcript of RPS Land Use and Transportation Modeling Results Presentation to RPS TAC & MPO TAC Brian Gregor...
RPS Land Use and RPS Land Use and
Transportation Modeling Transportation Modeling
ResultsResults
Presentation to RPS TAC & MPO TACBrian Gregor
Transportation Planning Analysis UnitMay 17, 2006
Presentation Outline
• Modeling background
• Description of land use model (LUSDR)
• Land use results
• Transportation results
Modeling BackgroundModeling Background
Land Use and Transportation Planning
Legend
County
Urban Growth Area
Poss. Urban Reserve
Highway
Poss. Highway
Urban development goesin urban growth boundaries.
County lands arepredominantly resourcezoning and very low densitydevelopment.
Urban reserves are future sourcesof land for inclusion into urbangrowth boundaries. They affect future transportation demand.Highway location affects
land development patterns.
Approaches to Land Use and Approaches to Land Use and Transportation ModelingTransportation Modeling
• Most common practice is to make aspirational-concensus land use forecasts. These are fixed for all transportation modeling.
• With integrated land use and transport models, land use allocations vary with transportation, but almost all just produce one land use pattern.
• The LUSDR model is also sensitive to transportation policies but recognizes that land many develop in many ways.
Why Evaluate Alternative Land Use Why Evaluate Alternative Land Use Patterns? Patterns?
• The overall number of trips may not change much, but the patterns of trip origins and destinations will.
• Roadway traffic can be very different depending on the land use assumptions.
• Assessment of many plausible land use patterns help identify potential problems.
O
O
O O
D
D
D D
Modeling Multiple Scenarios to Assess Risks
A
B
A
0 2000 4000 6000 8000
05
15
25
Traffic Volume
Num
ber
of
Sce
na
rios
Num
ber
of
Sce
na
rios
B
0 2000 4000 6000 8000
05
15
25
35
Traffic Volume
• Goal of RPS: To achieve regional consensus on where urban reserves should be designated to accommodate a doubling of population.
• Modeling Objectives
– Develop a moderately large set of plausible future land use patterns.
– Model the effects of the different land use patterns on the transportation system.
– Identify key features of land use patterns affecting transportation performance.
Jackson County Regional Problem Solving Jackson County Regional Problem Solving (RPS) Study(RPS) Study
What is LUSDR and What is LUSDR and How Does It Work?How Does It Work?
LLand and UUse se SScenario cenario DDevelopeevelopeRR
• Creates variation through stochastic microsimulation.
• Stochastic means that there is a random component to the model but average behavior is replicated.
• Microsimulation means that individual household, business and development decisions are modeled.
Stochastic MicrosimulationStochastic Microsimulation
= all of these places meet requirements
Shopping center might be located here in one simulation
Might be located here in another simulation
Start with Population by Age & Start with Population by Age & Total Population GrowthTotal Population Growth
0-4 10-14 20-24 30-34 40-44 50-54 60-64 70-74 80-84
Population by Age
Age
Pro
po
rtio
n
0.0
00
.01
0.0
20
.03
0.0
40
.05
0.0
6
HhSize Worker AgeOfHead Income Ownrent BldgtypeHh1 h2 w2 a1 i4 rent SFDHh2 h2 w1 a4 i2 rent SFDHh3 h2 w3 a1 i2 rent A5PHh4 h3 w2 a2 i3 own SFDHh5 h1 w2 a2 i1 own SFDHh6 h4 w4 a2 i5 own SFDHh7 h2 w3 a1 i3 rent SFDHh8 h2 w1 a2 i5 own SFDHh9 h2 w3 a3 i1 rent SFDHh10 h2 w1 a3 i5 own SFDHh11 h2 w1 a3 i4 rent SFAHh12 h3 w2 a4 i4 rent A24Hh13 h4 w3 a2 i4 rent MHHh14 h2 w2 a2 i2 own SFD
Generate HouseholdsGenerate Households
Comparisons of Observed and Comparisons of Observed and Simulated Household Building Simulated Household Building TypesTypes
Building Type Categories
1990 Census
1990 Estimated
2000 Census
2000 Estimated
Single Family Detached
63.9 63.7 63.9 63.8
Single Family Attached
2.2 3.1 2.2 3.1
2-4 Unit Apartment 7.6 8.0 8.3 7.7
5+ Unit Apartment 8.0 8.7 9.3 8.6
Mobile Home 17.5 16.0 14.9 16.4
Other 0.8 0.4 0.5 0.4
Assign to Assign to DevelopmentsDevelopments
HhSize Worker AgeOfHead Income Ownrent Bldgtype DevIdHh1 h1 w1 a1 i5 own SFDH SFDH-161Hh2 h1 w1 a1 i3 own MHpark MHpark-1Hh3 h1 w1 a1 i4 rent SFDM SFDM-126Hh4 h1 w1 a1 i1 rent SFDM SFDM-207Hh5 h1 w1 a1 i2 rent SFDM SFDM-758Hh6 h1 w1 a1 i2 rent SFDM SFDM-660
Development Sizes of SFDM Subdivisions
Subdivision Size
Nu
mb
er
0 100 200 300 400 500
01
00
30
05
00
Generate Employment Establishments Generate Employment Establishments and Put in Developmentsand Put in Developments
Histogram of Observed and Simulated Firm Sizes
log(employment)
De
nsi
ty
0 2 4 6 8
0.0
0.1
0.2
0.3
Id DevType LocType NumEmp UnitArea TotArea UnitPrice Period ACC-3 ACC EmpGrp6 3 6256.882 22524.775 9.133772 p4 ACC-1 ACC EmpGrp6 98 6256.882 735809.323 9.133772 p1 ACC-12 ACC EmpGrp6 1 6256.882 7508.258 9.133772 p2 ACC-14 ACC EmpGrp6 2 6256.882 15016.517 9.133772 p4 ACC-8 ACC EmpGrp6 2 6256.882 15016.517 9.133772 p3 ACC-4 ACC EmpGrp6 6 6256.882 45049.550 9.133772 p1
Locate DevelopmentsLocate Developments
• For each development– Identify set of candiate TAZs– Choose TAZ based on preference
probabilities (considering slope, distance to interchange, traffic exposure, accessibility)
• For each TAZ– Balance supply and demand based on
plan compatibility and willingness to pay
• Repeat as necessary until all developments are sited
Preference Probability Example 1: Construction & Manufacturing
Retail Preference ProbabilitiesPreference Probability Example 1: Retail and similar
Land Use Land Use ResultsResults
How to Interpret the Shapes ofHow to Interpret the Shapes ofBox Percentile PlotsBox Percentile Plots
3600
037
000
3800
039
000
Em
ploy
men
t
center line shows the
medianvalue
fifty percent of thevalues are between the
top and bottom horizontal lines
top and bottomshow the range
of values
the width indicatesthe relative frequencyof the value
5
05000
10000
15000
20000
25000
30000
Total Households by District
Num
ber of H
ouse
hold
s
Eagle
Poin
t
White
City
Central
Poin
t
Jack
sonvi
lle
West
Medfo
rd
East
Medfo
rd
Phoenix
Tale
nt
Ash
land
Tolo
North
Medfo
rd
010000
20000
30000
40000 Total Employment by District
Eagle
Poin
t
White
City
Central
Poin
t
Jack
sonvi
lle
West
Medfo
rd
East
Medfo
rd
Phoenix
Tale
nt
Ash
land
Tolo
North
Medfo
rd
3000
5000
7000
9000
1: Eagle Point
p1 p3 p5 p7 p9
3000
4000
5000
6000
2: White City
p1 p3 p5 p7 p9
8000
1200
016
000
2000
0 3: Central Point
p1 p3 p5 p7 p9
2000
3000
4000
5000
4: Jacksonville
p1 p3 p5 p7 p9
1400
018
000
5: West Medford
p1 p3 p5 p7 p9
2000
030
000
4000
0
6: East Medford
p1 p3 p5 p7 p9
4500
5500
7: Phoenix
p1 p3 p5 p7 p9 3500
4000
4500
5000
8: Talent
p1 p3 p5 p7 p9
1000
012
000
1400
0
9: Ashland
p1 p3 p5 p7 p9
Comparison of Households for Runs Starting at 2002(black) and 2030(red)(horizontal red line = 2030 base)
1000
3000
5000
1: Eagle Point
p1 p3 p5 p7 p9
6000
1000
014
000
2: White City
p1 p3 p5 p7 p9
4000
8000
1200
0
3: Central Point
p1 p3 p5 p7 p9
1000
1400
1800
4: Jacksonville
p1 p3 p5 p7 p9
2500
030
000
3500
0
5: West Medford
p1 p3 p5 p7 p9
2500
035
000
4500
0
6: East Medford
p1 p3 p5 p7 p9
2000
4000
6000
7: Phoenix
p1 p3 p5 p7 p9
2000
3000
4000
8: Talent
p1 p3 p5 p7 p9
9000
1000
011
000
9: Ashland
p1 p3 p5 p7 p9
Comparison of Employment for Runs Starting at 2002(black) and 2030(red)(horizontal red line = 2030 base)
Transportation ResultsTransportation Results
Variation in Total Vehicle Miles Travelled
Percentage of Average
Num
ber of S
cenarios
-0.5 0.0 0.5
02
46
8
1 2 3 4 5 30 1 1638000 964000 1027000 1025000 239000 62000 2 1646000 978000 1024000 998000 243000 62000 3 1612000 972000 1042000 1002000 252000 61000 4 1646000 961000 1025000 1035000 233000 63000 5 1668000 952000 1022000 1004000 244000 64000 6 1639000 955000 1032000 1016000 252000 61000 7 1648000 958000 1034000 1023000 252000 63000 8 1634000 948000 1054000 1031000 257000 61000 9 1631000 950000 1021000 1011000 246000 6200010 1628000 974000 1045000 1020000 255000 6100011 1639000 969000 1024000 1027000 239000 6100012 1650000 938000 1053000 1021000 243000 6200013 1620000 968000 1034000 996000 250000 6200014 1635000 965000 1034000 1019000 234000 6100015 1633000 969000 1033000 1021000 248000 63000
VMT by Functional Class and VMT by Functional Class and ScenarioScenario
Variation in Percentage of Total VMT Occurring on Freeways
Percentage of VMT
Num
ber of S
cenarios
32.4 32.6 32.8 33.0 33.2 33.4 33.6 33.8
02
46
8
Variation in Percentage of Total Vehicle Hours Travelled
Percentage of Average
Num
ber of S
cenarios
-1.5 -1.0 -0.5 0.0 0.5 1.0
05
10
15
Variation in Percentage of Total Vehicle Hours of Delay
Percentage of Average
Num
ber of S
cenarios
-20 -15 -10 -5 0 5 10 15
02
46
8
1 2 3 4 5 6 7 8 1 43800 8000 12300 55400 36300 47900 12300 23100 2 40800 7200 13500 56000 34400 47800 11100 23700 3 43600 7800 13100 54800 36600 46800 11100 23600 4 41300 7800 13400 56500 36600 48300 11700 23200 5 43300 7900 13100 57000 35200 49100 11600 22900 6 44000 7700 10200 53700 38100 47600 10800 23400 7 43500 8600 15600 58600 39400 46500 11100 23900 8 44000 7700 11100 54600 42100 48000 10400 24100 9 44500 8300 11700 55100 34900 48500 11000 2310010 43600 8200 12300 54500 40800 48600 11300 2340011 41400 7600 11800 54000 42300 47900 10500 2350012 44400 7200 10200 54300 41500 49700 11200 2290013 46800 7500 17200 58600 35700 47300 11400 2390014 43300 7800 12200 55100 37700 49700 12000 2330015 45000 8500 13100 55900 36400 47800 11300 23600
ADT by Location and ScenarioADT by Location and Scenario
1 2 3 4 5 6 7 8 9 10 1 12.5 5.1 3.2 6.9 11.9 13.3 8.1 13.9 8.0 5.0 2 11.6 4.6 3.6 7.0 11.3 13.3 7.3 14.2 7.9 5.4 3 12.4 5.0 3.5 6.9 12.0 13.0 7.3 14.2 8.0 5.1 4 11.8 5.0 3.5 7.1 12.0 13.4 7.7 13.9 8.0 5.6 5 12.3 5.1 3.4 7.1 11.5 13.6 7.6 13.8 8.1 5.0 6 12.5 4.9 2.7 6.7 12.5 13.2 7.1 14.0 7.8 5.1 7 12.4 5.5 4.1 7.3 12.9 12.9 7.3 14.3 8.1 5.6 8 12.5 4.9 2.9 6.8 13.8 13.3 6.8 14.5 7.8 5.1 9 12.7 5.3 3.1 6.9 11.4 13.5 7.2 13.9 7.9 5.310 12.4 5.2 3.2 6.8 13.4 13.5 7.4 14.0 8.0 5.611 11.8 4.9 3.1 6.8 13.8 13.3 6.9 14.1 7.9 6.012 12.6 4.6 2.7 6.8 13.6 13.8 7.4 13.8 8.0 5.113 13.3 4.8 4.5 7.3 11.7 13.1 7.5 14.3 7.9 5.114 12.3 5.0 3.2 6.9 12.4 13.8 7.8 14.0 7.9 5.315 12.8 5.4 3.4 7.0 11.9 13.3 7.4 14.1 7.9 5.6
ADT by Location and ScenarioADT by Location and Scenario
RPS TAC Project Should be RPS TAC Project Should be Compared With ImpactsCompared With Impacts
Next StepsNext Steps
• Complete analysis of transportation performance measures.
• Show measures of transportation results as well as variation in measures.
• Identify transportation problems.• Analyze relationship between transportation
problems and land use patterns.• Write up results.• Develop presentation of results.