Model Testing of Creative Strategies

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Model Testing of Creative Strategies and
Performance Targets in Napa County, California
PRESENTED BY Joseph Story, AICP DKS Associates
May 20, 2009
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Sensitivity Testing on a Regional Multimodal
Model Provided Insight on Its Usefulness for New
Policy Questions

• Setting of Napas Unique Travel Characteristics
• Overview of Napas Transportation Future Process
  and Recommendations
• Tool Solano / Napa Super-Regional Travel Demand
  Model
• Results of Testing of Recommended Strategies
• Strengths and Shortcomings of Model Application

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Napas Setting Well-Known Wine Country
Popularity Promotes a Growth Environment
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Napas Setting Tourism and Agricultural
Economies Produce Swings in Employment and Traffic

• Major Areas of Concern NOT Commuter Focused
• Difficult to Resolve Employment Estimates

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Napas Setting Land Preservation Strategies
Encourage Growth South of Downtown Napa
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Napas Transportation Future Process and
Recommendations

• Prior strategic plans had capital projects focus
• Project designed with extensive public
  discussion workshops, lectures, meetings
• Broad community recognition that goals to reduce
  single-occupant driving are important
• Model sensitivity testing done after preferred
  strategies emerged

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Napas Transportation Future Sets Specific 2035
Goals and Objectives

• GOAL REDUCE / RESTRAIN GROWTH OF AUTOMOBILE
  VEHICLE MILES TRAVELED (VMT)
• Objective 0 net growth in aggregate VMT
• GOAL SPREAD THE LOAD FROM PEAK TIMES TO NON-PEAK
  TIMES
• Objective Shift 10 of journey-to-work travel
  from peak to non-peak times
• GOAL SHIFT TRAVEL FROM SINGLE-OCCUPANCY VEHICLES
  TO OTHER MODES
• Objective Increase of trips made by transit
  to 5
• Objective Increase of trips made by bicycle
  and walking to 20
• GOAL REDUCE OVERALL ENERGY USE AND GREENHOUSE
  GAS (GHG) EMISSIONS
• Objective Reduce greenhouse gas emissions from
  all transportation modes to 40 below 1990 levels

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Study Group Recommendations Developed to Address
Policy Concerns Supply Strategies

• Investigate bus rapid transit systems for Napa
  County
• Promote energy efficient and environmentally
  benign transit systems
• Real-time bus tracking, traffic light
  synchronization, Dial 511 transportation
  information
• Maintain options for water transportation,
  promote freight rail in South County, support a
  full integration of air transportation
  connections

• Maintain critical street and road infrastructure
• Invest in strategic road system expansion in
  South County
• Convert high frequency intersections to
  roundabout configuration
• Build bike paths and sidewalks
• Create satellite park and ride sites
• Promote bypass road and transit strategies to
  address pass-through traffic
• Increase transit (bus) service
• Actively explore creating a passenger rail system

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Study Group Recommendations Developed to Address
Policy Concerns Demand Strategies

• Work with the wine and hospitality industries to
  create and promote car-free tourism services
• Address the special transportation needs of a
  growing senior population
• Work with employers to encourage alternatives for
  commuting and mid-day work trips
• Parking pricing strategies

• Promote workforce housing production near jobs
• Promote urban design and infrastructure
  development policies to encourage bike and
  pedestrian activity
• Promote safe non-auto routes to school, and
  after school programs
• Promote well-located health and social service
  delivery to minimize travel
• Institute comprehensive growth management
  guidelines that covers all jurisdictions

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The Tool Napa-Solano Multi-Modal Travel Demand
Model

• Model design finalized with 2003 work session
• Appropriately replicate current and future
  inter-regional travel demand
• Provide local network and TAZ detail in Solano
  and Napa counties
• Most focus on traffic count validation at peak
  hours
• Survey data provided from secondary sources not
  part of model scope

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The Tool Napa-Solano Multimodal Travel Demand
Model

• 1385 Traffic Analysis Zones
• Local Solano and Napa County models (989)
• Covers remaining San Francisco Bay Area (282)
• Sacramento region (102)
• San Joaquin and Lake Counties (12)
• Model validated to 2000
• Phase 1 Model (fixed mode shares) accepted in
  2006
• Phase 2 Model (HOV, walk / bike and transit mode
  shares) accepted in 2008

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The Tool Napa-Solano Multimodal Travel Demand
Model Network
Lake Co
SACOG Region
Napa Co
Solano Co
San Joaquin Co
Bay Area Counties
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A Series of Scenarios Were Tested to Show Results
of New Strategies

• SCENARIOS
• 1 Baseline Trends
• 2 Adopt Strategies Without Land Use Changes
• 3 Adopt Strategies With Land Use Changes
• 4 Slower Growth (Shift Jobs to Solano County)
• 5 The What Would It Take Scenario

Napas Transportation Future
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VMT and VHT Measured by Trip Tables to Best
Demonstrate Local Policy Choices

• Trip-Table Based VMT/VHT
• Origins or destinations within Napa
• Calculated based on vehicle trip ends
• Trips leaving / entering County counted as half
  of intra-county trips

• Link-Based VMT/VHT
• Portions of trips within Napa County
• Includes through trips
• Does not look at trip portions outside of
  County made by local residents / workers

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Testing of Baseline Trends (Scenario 1)

• Findings of all trips (to / from / within
  County)
• Trip-Based VMT increases 36 AM and 38 PM
• Trip-Based VHT increases 80 AM and 76 PM
• Observations
• Growth in most congested portion (South of Napa)
  of Napa County
• Growth areas are in Bay Area commuter markets
  with longer commutes
• Through trip increases from Napa County

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Testing of Strategies on Fixed Land Use (Scenario
2)

• Assumptions
• Roadways
• Widening / extensions of South County arterials
• Local road projects
• Transit frequencies doubled
• Bicycle-pedestrian connections improved to be
  twice as fast (attractive)

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Testing of Strategies on Fixed Land Use (Scenario
2)

• Results
• Combined improvements have small aggregate
  effect
• Over 300 fewer work trips in vehicles
• 80 to 90 fewer vehicle trips on the road
• HBW transit / walk / bicycle mode share forecast
  increased from 7.6 to 7.9 for intra-county
  trips
• Decrease in VMT and VHT of 1 to 4
• Greater at PM peak hour (shorter non-work trips)

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Testing of Strategies with Land Use Changes
(Scenario 3)

• Assumptions
• Relocation of 1500 households and 500 jobs to
  potential mixed-use growth areas
• Results
• Less profound changes in VMT / VHT than mere
  transportation improvements
• HBW transit / walk / bicycle mode share forecast
  remained 7.9 for intra-county trips
• Increased VMT / VHT from land use changes of 1
  to 2

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Testing of Slower Growth (Scenario 4)

• Assumptions
• Future jobs reduced from 97K to 85K
• Jobs relocated to Solano County
• No network changes from Scenario 1 Baseline
  (not strategy network)
• Network reflects less need to make and fund
  expansion
• Results
• 1 AM VMT reduction 2 increase in AM VHT
• 2 increase in PM VMT and VHT
• HBW transit / walk / bicycle mode share of 7.7
  for intra-county trips

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Testing of What Would It Take (Scenario 5)

• Assumptions
• Parking charges of 50 cents per hour everywhere
  in Napa County
• Bus frequencies at 10 minutes
• Pedestrian accessibility improved 500
• Bicycling becomes as attractive as nearby
  college town
• Results
• HBW transit / walk / bicycle mode share grows to
  27.6 for intra-county trips
• 4 decrease in AM and PM VMT 6 decrease in AM
  and PM VHT
• Benefits occurred on short-distance trips

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Strengths of Using this Model for Sensitivity
Testing

• Model showed some benefit in congestion reduction
  and slight mode shifts to transit / walk /
  bicycle, especially with short-distance trips
• Strategies illustrate the challenges of achieving
  carbon footprint reductions where land uses and
  lifestyles are fixed
• Scenarios demonstrated that shifting growth to
  the wrong areas even as mixed-use or
  high-density development can increase VMT / VHT
  if the area is congested
• Complex relationships between land use and
  transportation
• Density and diversity may not result in
  reductions

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Shortcomings of Using this Model for Sensitivity
Testing

• Model was not necessarily built or calibrated to
  answer emerging policy questions
• Model responsiveness appeared to somewhat fail
  because it did not respond significantly to
  varied scenario assumptions, although the
  inherent model design and fixed assumptions on
  behavior, land use and transportation were likely
  causes
• Metrics from partial geographic data prone to
  volatility that masks potential policy-based
  model inputs
• Trip-table-based VMT / VHT
• Use of VMT / VHT per household