1. Oregon Statewide Integrated Model
Title slide option 1
Overview of Version 2.5
OMSC Modeling Program Coordination Committee Presented by: Becky Knudson, Senior Transportation Economist Transportation Planning Analysis Unit, ODOT April 19, 2017

2. Outline
New Features
Peer Review
Application
SWIM 2.5

3. SWIM Schematic

4. Why 2.5… 4. SWIM assignment with VISUM 2. Refined Economic Module
5. Generalized Transit
2. Refined Economic Module
3. New Commercial Travel Mode
1. Replaced PI module with PECAS-AA

6. PECAS AA
Production, Exchange, Consumption Allocation System - Activity Allocation Module
Spatial input-output model
Integrated representation of spatially distinct markets
Represents how activities of households, industries, business and government locate
Location determined by developer space
Location responsive to how activity interacts with each other
Pricing mechanism clears markets
Steps through time

7. Model area forecasts for output and employment
NED
New Economics & Demographics Module
Model area forecasts for output and employment
Produces outputs by AA Activity, inputs & outputs, population in 5 yr age groups
Uses DAS IHS-Global Insight forecast used for official revenue forecast

8. Generates freight flows for model area based on AA ModuleCT
Commercial Travel Module
Calibrated to traffic counts
Generates freight flows for model area based on AA Module
Uses FAF data and Rail Waybill

9. CT Original recipe

10. CT Updates in place Revise using FAF4 OD data
and updated border truck counts

11. TS To VISUM Transport Supply (TS) replaced with VISUM
Highway and transit skimming and assignment
Microsimulated trip subarea analysis
Networks already maintained in VISUM
All spatial input data managed by VISUM (zonal, highway and transit)
Simplification of transit network representation
No longer managing local bus networks
Modeling local bus LOS with local transit functions borrowed from the California STDM
Various revisions to process requested by ODOT

12. Generalized Transit
Calculates local transit in-vehicle time and out-of-vehicle time skims
Based on California Statewide Travel Demand Model local transit functions (LTF)
Builds transit connectors to premium network using LTF matrices
The Transit Assignment process reads transit demand data created by the previously run SWIM modules and assigns it to the transit network managed in the version file. In the process, various skims are created (time, wait, cost, etc.), as well as assignment results and reports.
The module does not have a local transit network. Instead, it calculates local transit in-vehicle time and out-of-vehicle time skims according to the California Statewide Travel Demand Model Local Transit Functions (LTF). This step also builds transit connectors to the premium network using the LTF in-vehicle time and out-of-vehicle time matrices from the zone centroid to the zone of the nearest X transit stops. Finally, it adjusts the intracity skims so only the skimmed skims or the LTF skims are available for an OD pair.

13. SWIM Small Test Bed for Changes to SWIM 20 zone version Procedures
Parameters
Settings
Inputs
Takes minutes to run instead of hours
Big time saver

14. Applications and Peer Review
On the same page because we did these simultaneously
Applications and Peer Review

15. SWIM 2.5 Peer Review Frank Koppelman, Northwestern University, retired
David Simmonds, Simmonds & Assoc, Cambridge England
Michael Wegener, Univ. of Dortmund, Germany
Keith Lawton, Oregon, formerly Metro
Julie Dunbar, Dunbar & Associates
Kim Fisher, Univ. Of Maryland, formerly TRB
Bill Upton, Oregon, formerly ODOT
SWIM 2.5 Peer Review

16. Panel Topics SWIM 2.5 performance Use for applications
Refinement suggestions
Lessons learned
SWIM 2.5
Becky: ODOT wants this from Panel

17. Oregon’s Economy Relies on Freight Movement
History of analysis: RRA1 arose from a question prompted by a Minnesota study… We used SWIM 2.0 and had no bridge deterioration model, was an exploratory analysis to understand the potential risk to the economy.
RRA2 refines the analysis, using better tools with more information – yet a major reveal was the need for more data… We included a TAC to refine the outreach and messaging aspects.
2014
2017

18. RRA2 Detour

19. RRA2 Detour

20. Visualization Automation

26. SWIM TLUMIP