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

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Objectives Improve the preparation of transit demand forecasts in Florida to a point consistent with federal expectations Incorporate state of the practice techniques and tools in FSUTMS through a prototype model application
Transit Working Group Vidya Mysore, FDOT Systems Planning Vladimir Majano, FDOT Systems Planning Diana Fields, FDOT Systems Planning Diane Quigley, FDOT Transit Office Scott Seeburger, FDOT District 4 Shi-Chiang Li, FDOT District 4 Danny Lamb, FDOT District 7 Larry Foutz, Miami-Dade MPO Dan Macmurphy, Traf-O-Data Jeannette Berk, Advanced Planning, Inc. Myung-Hak Sung, Gannett Fleming
Page 1: Transit Modeling Update presented t
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 and 60:
Transit Modeling Update AUTO OWNERS
Page 61 and 62:
Proposed Auto Ownership Model Multi
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
Page 119 and 120:
Tier B/C Cities Mode Choice Nesting
Page 121 and 122:
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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