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Post Processing Procedures in Travel Demand Modeling

Post Processing Procedures in Travel Demand Modeling. Why Post Process?. Models are based on many assumptions. We are dealing with the future. There is no crystal ball. No model is perfect. We can assume that if the model is wrong now, it will not magically improve itself in the future.

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Post Processing Procedures in Travel Demand Modeling

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  1. Post Processing Procedures in Travel Demand Modeling

  2. Why Post Process? • Models are based on many assumptions. • We are dealing with the future. • There is no crystal ball. • No model is perfect. • We can assume that if the model is wrong now, it will not magically improve itself in the future.

  3. Base Model • We always start off by building a base year model. • This model is used to test our assumptions and compare the model output to empirical data. (i.e. Traffic Counts) • There will always be some amount of error.

  4. Forecast Model • Since we know there are areas in our base model with error…. • We need to account for that error in the forecast model. • This is referred to as “Post Processing”

  5. Guarantees Of Omitting Post Processing • Some day, it will predict less traffic than current levels • It will recommend too much construction; implications on: • Funding • Environmental • Design feasibility/ROW constraints • It will Undermine credibility of entire process – Most likely in public

  6. 2 Refinement Methods • Link-based refinement • Screenline/Cutline-based refinement • Both Require Judgement

  7. Link-based Refinements

  8. Link-Based Refinement • Adjust future assignment based on: • Absolute difference in base • (Count - Assignment) • Ratio difference in base • (Count/Assignment) • Apply both to future; Then Average • Assumes relative is ±15% • >15%; Use only the absolute • (Dampens Extremes)

  9. Example: Link-Base Refinement • Base: Count – 11,000 VPD Assign - 10,000 VPD • To bring assignment in line, increase assignment by 10% (Ratio difference) • Or, add 1000 VPD (Absolute Difference) • If Future Assignment = 15,000 VPD • Adjustment: Ratio = (15,000/10,000)*11,500 = (11,000/10,000)*15,000 = 16,500 VPD Absolute = (11,000-10,000)+15,000 = 16,000 VPD Average = 16,250 VPD

  10. Example: Link-Base Refinement • Base: Count –2,000 VPD Assign - 4,000 VPD • To bring assignment in line, decrease assignment by 50% (Ratio difference) • Or, subtract 2000 VPD (Absolute Difference) • If Future Assignment = 15,000 VPD • Adjustment: Ratio = (2000/4000)*15,000 = (15,000/4000)*2000 = 7,500 VPD Absolute = 13,000 VPD … use this one … why?

  11. Base Year Yellow shows where model volumes are greater than counts

  12. Base Year Red shows where counts are greater than model volumes

  13. Horizon or Future Year 2030 Unadjusted Model Volumes

  14. Horizon or Future Year 2030 Adjusted Model (ratio adjustment)

  15. Horizon or Future Year 2030 Adjusted Model (additive adjustment)

  16. Screenline/Cutline-based Refinements (NCHRP 255)

  17. Screenline/Cutline Refinement • Similar to link adjustment; Considers capacity (remember, your roads must be able to handle the traffic you adjust to) • Question: what happens to “equilibrium” when we post process? • Considers multiple links in one analysis • Attempt to smooth highs/lows over parallel routes in the corridor (alt. to Dial’s method?)

  18. Screenline/Cutline Refinement Screen/Cutline

  19. Screenline/Cutline Adjustment Concept • Influencing factors: • Base year traffic patterns • Change in traffic (base to future) • Change in network (e.g., adding a new route) • Congestion • Influence of capacity/base count (See next page)

  20. Capacity and Base Count Adjustments 1.00 0.00 0.90 0.10 0.80 0.20 0.70 0.30 0.60 0.40 Count Adjustment Factor Capacity Adjustment Factor 0.50 0.50 0.40 0.60 0.30 0.70 0.20 0.80 0.10 0.90 0.00 1.00 0.8 1.2 1.5 0.0 0.3 0.6 0.7 0.9 1.1 1.3 0.2 0.1 0.4 0.5 1.0 1.4 Future Year Screenline V/C Ratio

  21. * Notes: • FCAP and FCOUNT from chart • in this example, the refined future assignment RA(f) is averaged, despite the ratio being > 15%

  22. Summary/Opinions

  23. Simple application Reasonably defensible Can be applied on a regional scale May not balance out system highs/lows Only moderately responsive to congestion (Adjustments not really capacity restrained) Adjustment difficult without base data (new facilities/limited counts) In areas of high growth, adjustments based on base year calibration may not make much sense Link-based Refinement Advantages Disadvantages

  24. For at least study area - balance highs/lows - More dynamic Reasonably defensible Spreadsheet/GIS applications make more practical What is application area? Constantly changing-Must re-evaluate Adjustment less defensible without base data (new facilities/ limited counts) Not reasonable for regional analysis – Without GIS application Screen line/Cutline Refinement Advantages Disadvantages

  25. Thanks to: Bill Troe, AICPVice President, URS Corporation Bill_Troe@urscorp.com 515-284-5500 and Phil Mescher, Iowa DOT 515-239-1629

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