Is Schrdingers Cat Alive in 2030 - PowerPoint PPT Presentation

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Is Schrdingers Cat Alive in 2030

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Photo Credits: JM http://www.logodesignweb.com/stockphoto. Scientific American. Mr. Zhuojun Jiang MORPC. 614-233-4147. Ms. Rebekah Anderson ODOT ... – PowerPoint PPT presentation

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Title: Is Schrdingers Cat Alive in 2030


1
Is Schrödingers Cat Alive in 2030?
Effects ofRolling Dice
or
2
Model Set-Up
Core Model Java
Socio-Economic Data
3 Iterations
Networks
4 Period Highway and Transit Assignments
3
Discrete Choice Effects
  • Three Ways to Run the Model
  • All Choices, Including Household and Person
    Files, Are Allowed to Vary
  • Household and Person Files Remain Constant Tour
    Generation, Distribution, Mode Choice Vary -
    Standard Run
  • Household and Person Files, Tour Generation and
    Distribution Remain Constant Mode Choice Varies
    (FTA New Starts Version No Feedback)

4
Model Formulation
5
2030 Model Runs
  • Standard Run Equilibrium Assignment with
    Gap.001
  • Standard Run Equilibrium Assignment with
    Gap.00001
  • Variable HH Run Equilibrium Assignment with
    Gap.00001

6
Total VMT - Regular Run
7
Total VMT - 0.00001 Gap
8
Total VMT - Variable Run
9
Total VMT
10
Freeway VMT
11
Arterial/Collector VMT
12
VMT by District
13
VMT by Ring
14
VMT by Ring 9
15
VMT by Sector
16
Non-Attainment Area
17
Ozone Redesignation
  • Ran the Model Several Times to Assess the Impacts
    of Variability
  • Ran the Assignments Through ODOTs Air Quality
    Analysis Post-Processor
  • Link Volumes by Hour, by Direction, by Functional
    Class x Emission Factors

18
Ozone Redesignation
19
HC
20
NOx
21
CO
22
PM2.5
23
What That Means for the Cat
  • No Run Was Off the Final Average for Any
    Pollutant by More than /- 0.2.
  • PM2.5 Was More Variable than HC, NOx, or CO.
  • Number of Equilibrium Iterations Affected the
    Final Outcome More than the Realization Effects.
  • In Columbus, the Cat is Always Alive in 2030.

24
Count Coefficient of Variation
  • Sampling Error Inherent in Traffic Counts
  • Coef of Variation St. Dev. / Mean
  • USDOTs Guide to Urban Traffic Counting
    Indicates Sampling Error for 24 Hour Counts is
  • CV (3.706633/ln(COUNT))-0.264598

25
Link Coefficient of Variation
26
Link Coefficient of Variation
27
Link Coefficient of Variation
  • CVcount (3.706633/ln(COUNT)) - 0.264598
  • CVregular (0.631385/ln(24 Hr Volume))
  • - 0.059902
  • CVvariable (0.258741/ln(24 Hr Volume))
  • - 0.011584

28
Link Coefficient of Variation
29
Link Coefficient of Variation
30
Link Coefficient of Variation
31
Photo Credits JM http//www.logodesignweb.com/sto
ckphoto Scientific American
  • Mr. Zhuojun Jiang MORPC
  • 614-233-4147
  • Ms. Rebekah Anderson ODOT
  • 614-752-5735

Thanks also to Greg Giaimo.
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