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Research Project Overview

Comparing Aggregate Trip-Based and Disaggregate Tour-Based Travel Demand Models: Columbus Highway Results. Research Project Overview. Research led by University of Texas-Austin with AECOM, John Bowman, Mark Bradley & Ram Pendyala

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Research Project Overview

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  1. Comparing Aggregate Trip-Based and Disaggregate Tour-Based Travel Demand Models: Columbus Highway Results

  2. Research Project Overview • Research led by University of Texas-Austin with AECOM, John Bowman, Mark Bradley & Ram Pendyala • Main objective: examine the performance of the trip-based and tour-based frameworks for Columbus in the context of a before-and-after project analysis

  3. Major Tasks • Update trip-based model to resolve differences in estimation datasets, TOD, geographic coverage and other areas • Develop 1990, 2000 and 2005 scenarios (including socio-economic data, networks, traffic counts, etc.) • Compare models’ regional-level results to Census (1990, 2000), Household Interview Survey (1999), ACS (2005) • Decide on study projects • Compare models’ project level-results

  4. Brief Model Comparison

  5. Validation - VMT

  6. Validation - % RMSE

  7. Model-to-Model Comparisons • Trip distance by trip purpose • Delta volume bandwidth plots • ∆ volume = Tour model – Trip model

  8. Comparison of Trip Length by Purpose

  9. Delta Volume Bandwidth Plot1990

  10. Delta Volume Bandwidth Plot2000

  11. Delta Volume Bandwidth Plot2005

  12. Regional-Level Results • Vehicle ownership • Tour model performs better in Franklin County • Trip model performs better in other counties • Work flows • Both models generally perform the same, except for inter-county movements where the tour model generally performs better • Average work travel time • Both models generally perform the same

  13. Findings from the Report • Need to investigate why tour-based model systematically under-performs in vehicle ownership outside Franklin County • Overall there are few major differences between the two models (slight overall edge to tour-based model?) • It is difficult to make disaggregate model comparisons when the models have different units of travel • Translating units leads to inconsistencies at a disaggregate level, making the tour-based model’s full range of potential benefits difficult to compare to trip-based models • More comparisons between trip- and tour-based models are needed to verify these findings

  14. Project-Level Analysis • Polaris – IR 71/ SR 750 Polaris Parkway • Large retail and employment growth • Interchange and other roadway improvements • Rome-Hilliard – IR 70/IR 270 • Large land-use development • No roadway improvements • Spring-Sandusky – downtown Columbus • No major land-use changes • Major roadway improvements • Control area – IR 71 in southwest Columbus • No major land-use changes or roadway improvements

  15. All Study Areas Polaris Study Area Hilliard-Rome Study Area Spring-Sandusky Study Area Control Area

  16. Polaris - 1988

  17. Polaris - 2008

  18. Spring-Sandusky Study Area

  19. Hilliard-Rome Study Area

  20. Control Area

  21. Volume to CountsPolaris – 1990 Trip Tour Red – Overassigned Blue - Underassigned

  22. Volume to CountsPolaris – 2000 Red – Overassigned Blue - Underassigned Tour Trip

  23. Volume to CountsPolaris – 2005 Red – Overassigned Blue - Underassigned Tour Trip

  24. Volume to CountsSSI – 1990 Red – Overassigned Blue - Underassigned Trip Tour

  25. Volume to CountsSSI – 2000 Red – Overassigned Blue - Underassigned Trip Tour

  26. Volume to CountsSSI – 2005 Red – Overassigned Blue - Underassigned Tour Trip

  27. Design Forecasts • Add 1 more “model” • Fratared a matrix of 1s to the Trip Ends from the Tour model

  28. Volume/Counts and Forecasts • Polaris

  29. Volume/Counts and Forecasts • Spring-Sandusky Interchange

  30. Volume/Counts and Forecasts • Rome-Hilliard

  31. Volume/Counts and Forecasts • Control Area

  32. Speed Comparison

  33. Conclusions • With an aggregate assignment, there isn’t much difference between the demand models for your run-of-the-mill project traffic forecasts. • Biggest difference is in what questions your model can answer • Develop a model that answers questions that are being asked in your region. • Use your crystal ball to determine what questions are likely to be asked over the next 20 years.

  34. Contacts • Greg Giaimo – ODOT – 614-752-5738 greg.giaimo@dot.state.oh.us • Rebekah Anderson – ODOT – 614-752-5735 rebekah.anderson@dot.state.oh.us • Zhuojun Jiang – MORPC – 614-233-4147 • Chandra Bhat – UT at Austin bhat@mail.utexas.edu • Dave Schmitt – AECOM David.Schmitt@aecom.com

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