SmartGAP User’s Guide (2013) / Chapter Skim
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Contents 1 CHAPTER 1 Introduction to the SHRP 2 C16 Project 1 Project Overview 1 Project Objectives 2 Organization of this User's Guide 3 CHAPTER 2 Design Of SmartGAP 3 Objectives of the Software Tool 4 Model Structure 8 CHAPTER 3 Installation Instructions 8 Introduction 8 Installing R 9 Installing SmartGAP 15 CHAPTER 4 Running SmartGAP 15 About the User Interface 16 The Project Menu 20 Browsing to Inputs to Create a Base Scenario 22 The Scenario Menu 27 The Help Menu 27 Running the Model 29 Outputs 32 Reports 35 CHAPTER 5 Developing Input Data 35 Built Environment 39 Demand 43 Transport Supply 43 Policy 48 CHAPTER 6 Performance Metrics 48 Direct Travel Impacts 50 Environment and Energy Impacts 51 Financial and Economic Impacts 53 Location Impacts 53 Community Impacts
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55 CHAPTER 7 SmartGAP Application Examples 55 Developing the Base Scenario 55 Designing Scenarios 58 Analyzing Scenario Results 62 References
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1 CHAPTER 1 Introduction to the SHRP 2 C16 Project Project Overview This document is the user's guide for the Smart Growth Area Planning (SmartGAP) software, which is a tool for evaluating the impact of various smart growth policies.
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2 Organization of this User's Guide This user's guide is organized into the following sections: • SmartGAP introduction and model design (more detail on the technical aspects of the model such as discussion of model specifications can be found in the SHRP 2 C16 final report, The Effect of Smart Growth Policies on Travel Demand) • Installation instructions: installing R, about R, and installing SmartGAP • Running SmartGAP: about the user interface, creating projects and scenarios, running the model, viewing and exporting output, and creating charts to compare results across scenarios • Developing input data • Evaluating outputs: performance metrics • SmartGAP implementation examples: examples from the pilot testing of SmartGAP to provide guidance on how an agency could use SmartGAP
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3 CHAPTER 2 Design of SmartGAP Objectives of the Software Tool SmartGAP is a tool for evaluating the impact of various smart growth policies. SmartGAP is designed to be a high-level evaluation at a regional scale that can bridge the distance between evaluating smart growth policies during a regional visioning process and evaluating smart growth policies at a project or alternative level in a regional transportation plan.
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4 transportation planning processes. SmartGAP is intended to precede and supplement more sophisticated modeling efforts, which can be used to evaluate specific smart growth projects.
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5 SmartGAP does not provide specific spatial results beyond the built environment categories at the regional level, but does capture individual household and firm characteristics and the interactions between policies. The disaggregate nature of the model captures impacts that may be occurring for small portions of the population (say zero-vehicle households)
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6 Vehicle Model • Calculate Vehicle Ownership - Each household is assigned the number of vehicles it is likely to own based on the number of persons of driving age in the household, whether only elderly persons live in the household, the income of the household, the population density where the household lives, the freeway supply, the transit supply, and whether the household is located in an urban mixed-use area. Travel Demand Model • Calculate Travel Demand - The average daily vehicle miles traveled via auto and transit trips for each household is modeled based on household information determined in previous steps for the base conditions.
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7 Following initial calculations for baseline conditions, the model has feedback loops, which allow for changes in travel demand and other impacts based on induced travel demand and for changes in policies for a given scenario. Congestion is recalculated following these adjustments to demand.
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8 CHAPTER 3 Installation Instructions Introduction The installation of SmartGAP is a two-step process.
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9 • Online resource list: http://rwiki.sciviews.org/doku.php? id=links:link • Books: www.r-project.org/doc/bib/R-books.html • R function reference card: http://cran.r-project.org/doc/contrib/Short-refcard.pdf • R search engine: www.rseek.org/ • Webinar: FHWA's TMIP Webinar series included a webinar on travel modeling using R in February 2011 (http://tmip.fhwa.dot.gov/webinars/usingR)
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10 policy scenario folders as they are created. There are no caveats for naming the future scenario directories except that they should not be called "parameters" as that would create a conflict with the parameters folder.
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11 RUN_SmartGAP.bat RUN_SmartGAP.bat is a batch file that calls the R script that opens the SmartGAP GUI. It must be edited to correct the path to the installation of R on your computer and to the installation location of SmartGAP.
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12 Figure 3.4. SmartGAP Shortcut Properties Window.
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13 Depending on the operating system and settings of your computer and your administrative rights there can occasionally be problems with installing R packages. If errors occur during the download and loading of packages as SmartGAP opens, please refer to the two platform-specific FAQ sites that contain detailed installation instructions for Windows (http://cran.r-project.org/bin/windows/base/rw-FAQ.html)
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14 Figure 3.6. SmartGAP Graphical User Interface on opening.
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15 CHAPTER 4 Running SmartGAP About the User Interface Figure 3.6 above shows the appearance of the user interface when it is opened. The model opens in the base scenario of the demo project, an example project that is supplied with the software so that users can see a complete set of inputs and try running the model without needing to first create a complete set of input files.
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16 The Project Menu The project menu allows creation of new projects, navigation between projects, and editing of model parameters that are used in scenarios across a project. The distinction between projects and scenarios is discussed in more detail below, but essentially a project represents a holder for a set of scenarios testing alternative policies within a specific geography.
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17 Figure 4.4. The new project is opened after naming.
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18 Figure 4.7. Project menu "open" command allows navigation between the existing projects.
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19 Figure 4.9. Before being allowed to edit parameters, users are warned about the possible consequences of doing so.
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20 Browsing to Inputs to Create a Base Scenario When a new project is created using the "new" command, all of the inputs are shown as missing (Figure 4.11) and the user must browse to files that represent each of the inputs.
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21 Figure 4.12. In the base scenario for a project, browse to an input file.
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22 Figure 4.14. Partially-filled base scenario.
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23 Figure 4.15. Creating a new scenario menu.
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24 Figure 4.17. Selecting an input file to edit.
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25 input comment dialog (Figure 4.21)
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26 Figure 4.22. Completed input file comment.
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27 Figure 4.23. File structure showing projects and scenarios.
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28 following run times were observed for a single scenario, which increased close to linearly as the population of the region increased: • Cecil County, Maryland, 2035 population of 170,000: 2 to 3 minutes • Thurston County, Washington, 2040 population of 425,000: 4 to 5 minutes • Montgomery County, Maryland, 2035 population of 1.1 million: 15 minutes • Portland Metropolitan region, 2035 population of 2.3 million: 25 minutes • Atlanta Region, 2040 population of 8.3 million: 1 hour, 45 minutes Figure 4.24. Running the model.
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29 Figure 4.25. Stopping the model.
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30 4.28 shows the "outputs" window after the scenario has been run)
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31 Figure 4.28. Model "outputs" tab after a scenario has been run.
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32 Figure 4.29. "View" window displaying the fuel consumption output.
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33 first scenario displayed indexed to 100 and other scenarios relative to that) , or "Index (0)
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34 Figure 4.31. Example chart comparing Dvmt by area type for two scenarios.
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35 CHAPTER 5 Developing Input Data Input data files are built primarily from national sources and can be modified based on regional data sources. Policy inputs are provided by the user for a particular scenario.
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36 Table 5.2. Place Types Urban Core Close in Community Suburban Rural Residential Commercial Mixed-Use Transit Oriented Development Rural/Greenfield An initial typology or system to organize place types can be traced to the Smart Growth Transect, which contained six zones in its original configuration including: • Rural Preserve • Rural Reserve • Edge • General • Center • Core This approach to classifying place types was further refined in the Caltrans Smart Mobility Study, which defined the following seven place types including: • Urban Centers • Close-In Compact Communities • Compact Communities • Suburban Communities • Rural and Agricultural Lands • Protected Lands • Special Use Areas Several of these place type Categories provided additional options, such as the Close-In Compact Communities which had three sub-definitions including Close-In-Centers, Close-In Corridors, and Close-In Neighborhoods.
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37 employees, or a mix of the two. Station areas are also characterized on their relative intensity as well as shown in Figure 5.1.
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38 • The Rural place type is defined as settlements of widely spaced towns separated by farms, vineyards, orchards, or grazing lands. These areas would be characterized by widely dispersed residential uses, little or no transit service, and very limited pedestrian facilities.
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39 The conversion of land use data to the place type scheme used in SmartGAP involved taking ARC's Unified Growth Policy Map (UGPM) Areas and converting them to the 13 SmartGAP place types.
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40 • Auto – is the regional average of auto trips per capita, including drive alone and shared ride travel. This data can be derived from the National Household Travel Survey (http://nhts.ornl.gov/index.shtml)
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41 • 4 employees, • 5-9 employees, • 10-19 employees, • 20-99 employees, • 100-249 employees, • 250-499 employees, • 500-999 employees, • 1,000-2,499 employees, • 2,500-4,999 employees, and • Over 5,000 employees. A database of preprocessed CBP data is provided with SmartGAP, but users can also format their own local data into the file format.
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42 Table 5.6. File Format for employment_growth.csv Population (Existing and Growth)
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43 (www.fhwa.dot.gov/policyinformation/hpms.cfm) and local sources, or the regional travel demand model if one exists.
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44 Percent Growth by Place Type (place_type_growth.csv) This file is a table of the percent growth for each of the 13 place types.
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45 • Arterial is a similar value to freeway except that it measures arterial lane mile growth. It is also proportional to population growth, • Bus – is the percent increase in transit revenue miles per capita for bus.
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46 Table 5.15. File Format for its.csv Auto Operating Surcharge per Vehicle Miles Traveled (vmt_charge.csv)
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47 • PropCashOut – proportion of employment parking that is converted from being free to pay under a "cash-out buy-back" type of program. • PrkOthChrgd – proportion of other parking that is not free.
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48 CHAPTER 6 Performance Metrics The performance metrics, reported in SmartGAP's output data files, are designed to address a variety of impacts that are helpful for decision-making. The output data are saved as .RData files and can be exported as tabular text files with a comma separated value (CSV)
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49 Table 6.1. Vehicle Trip Elasticities D Description Vehicle Trip Decrease Density Household/Population Density -0.043 Diversity Land Use Mix (entropy)
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50 Vehicle Hours of Travel, Delay The congestion model calculates vehicles hours of travel using the VMT by speed distributions discussed above. The amount of delay is calculated by comparing the vehicle hours of travel with the amount of vehicle hours of travel that would have taken place if travel was at free flow speeds.
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51 Table 6.3. Carbon Intensity by Fuel Type (Grams CO2e per Megajoule)
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52 Urbanized. The numbers in Table 6.4 are in 2002 dollars; FHWA advises escalation to current dollars using its National Highway Construction Cost Index (NHCCI, which is available online at www.fhwa.dot.gov/policyinformation/nhcci.cfm)
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53 Annual Traveler Cost (Fuel plus Charges) The traveler costs values reported by SmartGAP are the total of the following components: 1.
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54 • Fatal: 1.14 per 100 Million Miles Traveled • Injury: 51.35 per 100 Million Miles Traveled • Property damage: 133.95 per 100 Million Miles Traveled Walking Percentage Increase The percentage change in the amount of walking is calculated by applying a set of elasticities developed in their 4D Meta Analysis by Cervero and Ewing (Table 6.6)
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55 CHAPTER 7 SmartGAP Application Examples This section of the user's guide provides some examples from the pilot testing of SmartGAP of how a set of scenarios might be developed, tested, and analyzed by an agency. Chapter 4 of the SHRP 2 C16 Final Report provides a more complete discussion of the pilot testing process.
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56 of the pilot studies tested a relatively consistent set of eight scenarios, and an additional two scenarios are reported in the SHRP 2 C16 Final Report that were tested in Portland by the research team. The scenarios, shown in Table 7.1, focus initially on testing changes individually to understand the impacts of those policies separately.
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57 During the pilot testing, the agencies implemented the scenarios based on their knowledge of their own regions. This meant applying caps in some cases to the amount of land use reallocated in Scenarios #5 through #7, for example.
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58 Analyzing Scenario Results SmartGAP produces results in the form of performance metrics, which are described in Chapter 6. The results are available in tabular form via the "outputs" tab in SmartGAP, or can be displayed and exported in form of charts in the "report" tabs.
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59 The "reports" tab settings to produce the left and right charts respectively are as follows: Scenarios: Select base and Scenarios #2-8 Select base and Scenarios #2-8 Metric: Daily vehicle miles traveled Daily vehicle miles traveled Aggregation: All All Measure: Number Index (0) Figure 7.3.
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60 The "reports" tab settings to produce the left and right charts respectively are as follows: Scenarios: Select base scenarios Select base scenarios Metric: Population Employment Aggregation: Development type Development type Measure: Percentage Percentage Figure 7.4. TRPC Percent of 2040 Population and Employment by Development Type.
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61 The "reports" tab settings to produce the left and right charts respectively are as follows: Scenarios: Select base and Scenarios #2-7 Select base and Scenarios #9-10 Metric: Accidents Vehicle Hours of Delay Aggregation: Accident severity Vehicle Type Measure: Index (0) Number Figure 7.5.
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62 References Center for Transit-Oriented Development (2010) Performance-Based Transit-Oriented Development Typology Guidebook.
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