VE Wiki documentation¶
The purpose of this wiki is to provide an in-depth technical resource for those developing strategic travel models in Oregon built on the VisionEval (VE) platform. Oregon specific policies and data inputs are used throughout.
This wiki focuses on the VisionEval Regional Strategic Planning Model (VE-RSPM), intended for metropolitan planning organizations (MPO) staff, statewide planners, local planners, and other decision makers interested in regional scenario planning to assess the impacts of different transportation and land use policies.
More information on the VisionEval project can be accessed at the following links:
_Documentation of the Pooled Funds VE Development https://github.com/VisionEval/VisionEval/wiki _Development of VisionEval: https://github.com/VisionEval/VisionEval-Dev The VisionEval project website: https://visioneval.org/ The current binary release of VisionEval available for download: https://visioneval.org/category/download.html This wiki is intended to sit between the detailed information on the VisionEval GitHub site and the planning level documents which discuss the benefits and reasoning for using a strategic model. This VE Primer is the introduction to the detailed tool information which will be linked to throughout this technical wiki: https://github.com/VisionEval/VisionEval/wiki/VisionEval-Primer
Revised Combined Wiki Outline – January 19, 2021
- Introduction (the why)
- 1.1 Oregon transportation and environmental planning.
1.1.1. Target rule and concepts/ policies to reduce GHG.
1.1.2. Rulemaking (TBD).
1.2 What is VisionEval: VE-RSPM and its relationship to other models.
- 1.3 Scenario planning options in Oregon (describing briefly the purpose and process, showing the options are progressive)
1.3.1. Local Baseline Assessment to STS Vision (least intense, planning 1-4).
1.3.2. Strategic Assessment (scenario planning 1-5).
1.3.3. Preferred scenario (most intense, planning 1-6).
Scenario Planning Process.
2.1. Establish Scenario Planning Framework.
2.1.1. Stakeholders.
2.1.2. Data and projects that inform the models.
2.1.3. Principles, issues and outcomes (this is about framing the discussion around issues and strategies people are most interested in).
2.1.4. Strategies for GHG reductions. (This is describing “levers” and the info/data we require to code them; a non-exhaustive list may include: TDM, Vehicle technologies and powertrains, Land Use, Transportation System, ITS, Transit).
2.2. Develop Evaluation Criteria.
2.3. Set Up Scenario Modeling
2.3.1. Base Year (link to section 3.3)
2.3.2. Future Baseline Reference Scenario (link to section 3.5)
2.3.3. Develop and Evaluate Alternative Scenarios (link to section 3.7)
2.4. Develop and Select a Preferred Scenario (link to 3.7 and set up 4.0)
2.4.1. Sensitivity Testing
2.4.2. Key Paths
VisionEval – Developing a Model
3.1. Model Geography and inputs by geography
3.2. Set up Base Model
3.2.1. socio-economic
3.2.2. travel data
3.3. Model Calibration (base year) and Validation (testing sensitivity to key variables)
3.3.1. Base Year Outputs
3.3.2. Calibration variables and sources of data
3.4. Modeling the GHG reduction strategies (this would be formats and sources of data for the policies listed in section 2/ planning process).
3.5. Set Up Scenarios (future)
3.5.1. Future Baseline Reference Scenario
3.5.2. Target Rule Scenario
3.5.3. Alternative Scenarios (future policies and exploratory scenario planning)
3.6. Analyzing & Visualizing Outputs
3.6.1. Comparing scenarios
3.6.2. Model Outputs
3.6.3. Visualizing outputs
3.7. Finalizing and Sharing Results (for modelers)
Reporting and Implementing Results
4.1. Identify Key Paths and Strategies
4.1.1. Group Polies, strategies and actions into Key Paths
4.1.2. Identify High ROI Strategies
4.2. Linking To Transportation and Land Use Plans
4.3. Monitoring Process
4.4. Documenting and Sharing Results
Case studies
Support and Resources (This would be consolidated links and contact information, like bibliography)