Adaptation of the Washoe RTC Travel Demand Forecasting Model into Emme 3

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Adaptation of the Washoe RTC Travel Demand
Forecasting Model into Emme 3
Jia Hao Wu, Ph.D. and Allen Nie, Ph.D., TJKM
Transportation Consultants, Pleasanton,
California, USA
Peter Bang, Ph.D., Washoe Regional Transportation
Commission, Nevada, USA Shuguang He, Dan Florian,
INRO Solutions, Canada
20th International Emme Users Conference Montreal
, October 18 to 20, 2006
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Outline

• Background
• Motivations and Issues of Conversion
• RTC Travel Demand Model
• Regional Surveys
• Modeling Targets from Surveys
• Preliminary Results
• Conclusions

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Background

• RTC Travel Demand Model Developed in 2004 with
  EMME/2/Enif
• Many Regional and Local Applications
• Four RTC Staff Busy with the Model
• Some Modeling Issues Remaining

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Modeling Area
Reno 10 of work force RTC Area 581,866
AC Population 365,762
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Period 1990-2000 2005-2030 Population
3.0 1.9 Employment 3.7 2.4
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RTC Travel Demand Model

• Trip Generation
• Trip Distribution
• Mode Choice
• Auto Assignment
• Transit Assignment
• Integrated Park Ride Model
• Feedback Loops
• OD Demand Estimation

• Resident Trip Generation (HBW,HBS,HBS/R,HBS,HBO,N
  HB)
• Visitor Trip Generation (HBW,HBS,HBS/R,HBO,N(HOTE
  L)B)
• Air Passenger Model
• External Trip Generation/Distribution

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• Visit Mode Choice
• Auto
• Taxi
• Public bus
• Shuttle bus
• Walk

• Resident Mode Choice
• Walk access to transit
• Drive access to transit
• Drive alone auto
• 2, 3 person auto

• Nested logit models
• Parameters review and updates

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Motivations and Issues of Conversion

• Washoe RTC Regional Surveys
• Model Parameters
• New Regional Transportation Plan to Come
• Model Structures
• Macro Impacts

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RTC Household Survey
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Data Process

• Geocoding Process
• Data Weighting
• Survey Validation

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Survey Results for Model Components

• Trip Generation Models
• Mode Choice Models
• Friction Factors
• Vehicle Occupancy Rates
• Time of Day Factors

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Trip Generation

• Production Cross-classification
• Attraction Regression model
• Resident Model
• Visitor Model
• by Purpose

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Household Income Distribution
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Household Size Distribution
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Washoe RTC District Aggregation
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Trip Attraction Regression Models Are Also
Developed
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On-Board Survey Ridership Percentage
Trip Weighted Riderships by Route and Time of
Day Are Estimated
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Survey Daily Trip Length Distribution

• District by District Demands
• Ave. Trip Length 5.3mi
• FF factors to Be Calibrated
• Gravity Models by Purpose

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Daily Demands by Mode and Purpose Survey vs.
Model
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Emme 3 Implementation

• Modeling Environment
• Macros (Names)
• Matrix Names in Worksheet (matrix number and
  matrix name)
• Files to Work with (Emme 3 project file)
• Shortcut Files from Enif Plots and Lists in Emme
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• Emstart.bat (two levels deep only)
• UltaEdit to Execute Macros even When Emme 3 Is
  Active

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Modeling Environment in Windows
Execute RTC model
Project
Execute Emme Project
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Emme 3 and UltaEdit
Emme 3 Environment
To Execute Macros
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Some Survey Results in Emme 3
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Conclusions

• RTC 2005 regional surveys are used
• The RTC travel model is being updated
• Preliminary results are obtained
• 2006 new intersection counts and 30 mainline
  counts will be used for a recalibration
• Emme 3 was successfully implemented
• Network editing will be performed within Emme 3
• We do have a long wish list for Emme 3