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Emme Modeller Applications
Puget Sound Regional Council’sModel Conversion via Emme Modeller
22nd International Emme Users’ ConferenceSeptember 15-16, 2011 • Portland, OR
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Presentation Overview
• Context
• Conversion
• Examples
• Conclusions
Context
44
Model Basics
General:• Hybrid Trip-based (Activity Generator for Trip Generation)• 5 Global Iterations (Feedback to Activity/Trip Generation)• 10 Trip Purposes (HBWork Stratified by 4 Income Groups)• 5 Time Periods (Homed-based Purposes, Auto Modes Only)• Mode Choice Market Segmentation (Car- Worker/Person)• 5 Transit Sub-Modes (Drive- and Walk-Access)• AM,MD Transit Assignments by Sub-Mode• Generalized Cost/Multi-Class Vehicle Assignments (11)• Approximately 200 Macros (Report Files x5)• Lengthy Runtimes (16 – 24 Hours)
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Model Structure
Emmebanks (5):• Bank 1 (4.4gb, 750 full matrices)
HBWork & College Distribution, Mode Choice, AM Transit and Auto Assignments
• Bank 2 (3.0 gb, 500 full matrices) HBNon-Work/NHB Distribution, Mode Choice, Mid-Day
Transit and Auto Assignments• Bank 3 (1.5 gb, 200 full matrices)
PM, Evening, Night Auto Assignments• Time of Day (1.4 gb, 250 full matrices)
P>A and A>P Shares by Time of Day by O-D Pair• Trip Generation (1.2 gb, 200 full matrices)
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Other Considerations
Integration with Other PSRC Models:• UrbanSim• Benefit-Cost Analysis Tool• Activity-Based Travel Model
Utilization of Staff Resources:• UrbanSim ~ 5 • Benefit-Cost ~ 1• Travel Modelers ~ 4• Other ~ 1
Regional Modeling Community:• Legacy Local Jurisdiction Models and Modellers• Production Model Ready for Next Major Project
Conversion
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Immediate Needs
Accommodate New Zones and Networks:• Zones increased from 1,200 to 4,000• Network links increased from 19,500 to 41,000
Restructure Model:• Smaller emmebanks (in terms of full matrices)• Disentangle/simplify complex models (e.g. HBW Mode Choice)
Testing:• Models• Structures• Improve runtimes
Documentation:• Incorporate changes, improvements, updates• Validation
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Longer Term Strategic Needs
Develop “Junior” Staff – Travel Modeling Capacity:• Limited Budgets/Staffing (i.e., “Do More with Less”)• AB Model
Develop Staff Python Language Skills:• PSRC Heavily Invested in Python• Range of Skill Levels (No Experience/Novice – Expert)
Maintain Culture of Research and Development:• In-House Model Specification/Estimation (e.g., OPUS and
UrbanSim)Serve Regional Modeling Community:• Clearinghouse/One-Stop-Shop/A-la-carte Services
Maintain Future Flexibility:• Tons of Unknowns
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Schedule and Status
Schedule:Original:
Conversion May-August, Finished by ConferenceActual: Installed Beta in May, Distracted by Other Stuff Until Mid-
August, Not Finished by Conference, Hope to Finish by End of Calendar Year
Progress:• Testing and Experimentation• Built/Implemented Simple Non-Work Distribution Demo Tool• Specs Exported
Examples
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Non-Work Distribution ~/ --- Prepare HB-Shopping friction factors 3.21 ~+|1|y|mf"hspfri"|n exp(-.1590*mf91) ~+|||y|1,956||1,956||2 ~+|1|y|mf"hspfri"|n mf"hspfri"*1 ~+|||y|1,956||1,956||2|q ~/ ~/ --- Set HB-Shopping Friction Factors Equal to Zero for ~/ Externals to Prevent E-E Trips 3.21 ~+|1|y|mf"hspfri"|n|0|||y|939,956||939,956||2|q ~/ ~/ --- Prepare HB-Other (not school or college) friction factors 3.21 ~+|1|y|mf"hbofri"|n exp(-.1455*mf91) ~+|||y|1,956||1,956||2|q ~/ ~/ --- Set HB-Other Friction Factors Equal to Zero for ~/ Externals to Prevent E-E Trips 3.21 ~+|1|y|mf"hbofri"|n|0|||y|939,956||939,956||2|q ~/ ~/ --- Prepare NHB Work-Other friction factors 3.21 ~+|1|y|mf"wkofri"|n exp(-.0795*mf91) ~+|||y|1,956||1,956||2|q ~/ ~/ --- Set NHB Work-Other Friction Factors Equal to Zero for ~/ Externals to Prevent E-E Trips 3.21 ~+|1|y|mf"wkofri"|n|0|||y|939,956||939,956||2|q ~/ ~/ --- Prepare NHB Other-Other friction factors 3.21 ~+|1|y|mf"otofri"|n exp(-.1235*mf91) ~+|||y|1,956||1,956||2|q ~/ ~/ --- Set NHB Other-Other Friction Factors Equal to Zero for ~/ Externals to Prevent E-E Trips 3.21 ~+|1|y|mf"otofri"|n|0|||y|939,956||939,956||2|q ~/ ~/ Non-Work Friction Factor Calculation Completed! reports=
~/ --- Compute distributed daily trips for Home-Based Shopping 3.22 ~+|1|mf"hspfri"|mo"hsppro"|md"hspatt"|y ~+|1,956||1,956||~?q=3|2|~?q=1|y||2|1|mf"hspdst"|n|2 q ~/ ~/ Sum Retail and FIRES Employment 3.21 ~+|1|y|md98|n|md"retail"+md"fires"|||n|2 q ~/ Reproportion HB Other Attractions ~<run2mac\predbal.mac mo"hbopro" md98 mf100 30 md"hboatt" ~/ ~/ --- Compute distributed daily trips for Home-Based Other 3.22 ~+|1|mf"hbofri"|mo"hbopro"|md"hboatt"|y ~+|1,956||1,956||~?q=3|2|~?q=1|y||2|1|mf"hbodst"|n|2 q ~/ ~/ --- Add special generators to HBO trip table ~/ 3.21 ~+|1|y|ms"upper2"|n|mo"upper2"|||y|1,956||+|2 ~+|1|y|mf"hbodst"|n|mf"hbodst" + mo"upper2"/ms"upper2"*(md"spghbo"+0.75*md"spgapt") ~+|||y|1,956||1,956||2 q ~/ ~/ --- Compute distributed daily trips for NHB Work-Other 3.22 ~+|1|mf"wkofri"|mo"wkopro"|md"wkoatt"|y ~+|1,956||1,956||~?q=3|2|~?q=1|y||2|1|mf"wkodst"|n|2 q ~/ ~/ --- Add special generators of airport trips to Work-Other trip table ~/ 3.21 ~+|1|y|md"wkotot"|n|mf"wkodst"|||y|1,956||1,956||+|2 ~+|1|y|mf"wkodst"|n|mf"wkodst" + 0.25*md"spgapt"*mf"wkodst"/md"wkotot" ~+||md"wkotot"|0,0,exclude|y|1,956||1,956||2 q ~/ ~/ --- Compute distributed daily trips for NHB Other-Other 3.22 ~+|1|mf"otofri"|mo"otopro"|md"otoatt"|y ~+|1,956||1,956||~?q=3|2|~?q=1|y||2|1|mf"otodst"|n|2 q
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Non-Work Distribution
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Non-Work Distribution
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Non-Work Distribution
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Non-Work Distribution
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Non-Work Distribution
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Non-Work Distribution
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Non-Work Distribution
2020
Non-Work Distribution
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Non-Work Distribution
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Non-Work Distribution
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Non-Work Distribution
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AM Auto Assignment~/ --- Setting Assignment Options and Parameters~+|2|2|1 ~+|s|@toll1|0.0383|mf"avehda"~+|h|@toll2|0.0199|mf"avehs2"~+|i|@toll3|0.0158|mf"avehs3"~+|j|@toll4|0.0059|mf"avpool"~+|s|@toll1|0.0627|mf"ahbw1v"~+|s|@toll1|0.0340|mf"ahbw2v"~+|s|@toll1|0.0233|mf"ahbw3v"~+|s|@toll1|0.0180|mf"ahbw4v"~+|v|@trkc1|0.0150|mf"alttrk"~+|u|@trkc2|0.0133|mf"amdtrk"~+|t|@trkc3|0.0120|mf"ahvtrk"/4000 / Maximum Memory for Paths0.001 / Path Cost Equality Tolerance (Initial Proportion)30 / Path Cost Equality Tolerance (Refinement Iteration)0.00001 / Path Cost Equality Tolerance (Refined Proportion)5 / Number of Iterations between Gap Computations%1% / Maximum Number of PG Assignment Iterations0.01 / Stopping Criterion for Best Relative Gap (Percent)0.0001 / Stopping Criterion for Relative Gap0.001 / Stopping Criterion for Normalized Gap (Excess Average Cost)~/ --- Running Path Based Assignment
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AM Auto Assignment
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AM Auto Assignment
Conclusions
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Conclusions
Some Lessons Learned:• Not Much Python Experience Needed• INRO Tutorial, Winnepeg Demo and Sourcecode Useful• Devote Significant Blocks of Time to Make Progress• Logbook an Added Bonus• Report Files Easier to Manage and Navigate• Powerful Desktop API More Relevant
Next Steps:• Develop Custom Tools for PSRC Toolbox• Link Tools for Basic Functional Model• Layer In Model Idiosyncrasies and Complexity• GUI Development
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Conclusions
Why Modeller?• Model Development and Organization• Staff Development
Applied Learning/Experimentation• Python-based• Flexibility• Just Ready For It…
No More Macros U-I Driven
Puget Sound Regional Council:
Chris Johnson and Craig Helmann