Transit Modeling Guidance by Rosella Picado and ... - FSUTMSOnline

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Why an Auto Ownership Model? Transit and non-motorized accessibility matters. An auto ownership model can be sensitive to accessibility, while a classification model is not. Can be estimated and validated from readily available data. Several effects are measurable: household size, workers, income and type of housing unit are good predictors of auto ownership. Reduces the number of IPF dimensions, which helps the household classification model to converge more quickly.
Proposed Auto Ownership Model Multinomial logit Choice set: 0,1,2,3,4+ autos per household Explanatory variables: • Household size, income, workers • Type of housing unit • Household and employment density • Transit and non-motorized accessibility
Page 1 and 2:
Transit Modeling Update presented t
Page 3 and 4:
Transit Working Group Vidya Mysore,
Page 5 and 6:
Project Overview On-Board Rider Sur
Page 7 and 8:
Principles of Model Calibration and
Page 9 and 10: Case for the Project Workshop Pilot
Page 11 and 12: New PT Features in Cube Voyager 6.0
Page 13 and 14: Examples of Drive-Access Coding Aer
Page 15 and 16: Examples of Drive-Access Coding Net
Page 17 and 18: Drive-Access Generation in 5.x Hist
Page 19 and 20: Drive-Access Generation Examples in
Page 21 and 22: Drive-Access Generation Examples in
Page 23 and 24: Drive-Access Generation in 6.x Cube
Page 25 and 26: Enhanced Drive-Access Generation Ex
Page 27 and 28: Output Files by PT AUTOCON Process
Page 29 and 30: Enhanced Fares along with BestPathO
Page 31 and 32: Fare Process in 5.x Output example
Page 33 and 34: Enhanced Fare Process in 6.x Exampl
Page 35 and 36: Enhanced Fare Process in 6.x Exampl
Page 37 and 38: Enhanced Transit Line Keywords in 6
Page 43 and 44: Transit Modeling Update TRIP MARKET
Page 45 and 46: Proposed New Trip Purposes HB Colle
Page 47 and 48: Proposed New Trip Purposes NHB Work
Page 49 and 50: Key Travel Market Attributes Model
Page 51 and 52: Key Travel Market Attributes FTA Re
Page 53 and 54: Building the Household Classificati
Page 55 and 56: Building the Household Classificati
Page 57 and 58: Household Workers Classification Mo
Page 59: Transit Modeling Update AUTO OWNERS
Page 63 and 64: Mixed Household / Employment Densit
Page 65 and 66: Sample Auto Ownership Coefficients
Page 67 and 68: Trip Production Model Home-Based Wo
Page 69 and 70: Transit Modeling Update TRIP ATTRAC
Page 71 and 72: Trip Attraction Model Linear regres
Page 73 and 74: Transit Modeling Update SPECIAL TRI
Page 75 and 76: Example 1: Portland Air Passenger T
Page 77 and 78: Transit Modeling Update TIME OF DAY
Page 79 and 80: FSUTMS Approach to Time of Day Effe
Page 81 and 82: Implications for other model compon
Page 83 and 84: FSUTMS Diurnal Factors Developed fr
Page 85 and 86: Travel Time Feedback: Why? Ensure c
Page 87 and 88: Transit Modeling Update TRIP DISTRI
Page 89 and 90: Destination Choice Advantages Sensi
Page 91 and 92: Destination Choice Model Multinomia
Page 93 and 94: Trip Market Stratification At least
Page 95 and 96: Attraction Balancing Whether to sha
Page 97 and 98: Destination Choice Estimation Requi
Page 99 and 100: Destination Choice Estimation Sampl
Page 101 and 102: Destination Choice Estimation Size
Page 103 and 104: Destination Choice The mode choice
Page 105 and 106: Transit Modeling Update TRANSIT NET
Page 107 and 108: Good transit coding practices … R
Page 109 and 110: Good transit coding practices … R
Page 111 and 112:
Transit network coding Access Conne
Page 113 and 114:
Path building and skimming Path Bui
Page 115 and 116:
Transit Modeling Update MODE CHOICE
Page 117 and 118:
Trip market segmentation Household
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Tier B/C Cities Mode Choice Nesting
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FSUTMS Nesting Coefficients 0.8 0.5
Page 123 and 124:
Nested Logit Model: How? Choice Aut
Page 125 and 126:
Logit Model Curve 1 Auto Probabilit
Page 127 and 128:
Coordinating DC and MC Calibration
Page 129 and 130:
Trip Generation EE Trips Visitor &
Page 131 and 132:
Build Hwy Networks & Skims Build Pe
Page 133 and 134:
Trip Generation EE Trips HH Classif
Page 135 and 136:
Travel time feedback
Page 137 and 138:
Trip Distribution Destination choic
Page 139 and 140:
Model Inputs: What’s New? Zonal D
Page 141 and 142:
Model Parameters: What’s New? Pea
Page 143 and 144:
Catalog Keys: What’s New? Auto oc
Page 145 and 146:
Deliverables Technical Memoranda
Page 147:
Deliverables Workshops • Case for
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Transit Modeling Guidance by Rosella Picado and ... - FSUTMSOnline

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