Improving the Model s Sensitivity to Land Use Policies and Nonmotorized Travel

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Improving the Model s Sensitivity to Land Use Policies and Nonmotorized Travel presented to MWCOG/NCRTPB Travel Forecasting Subcommittee presented by John (Jay) Evans, P.E., AICP Cambridge Systematics, Inc. July 17, 2009 Transportation leadership you can trust. Author Acknowledgments Contributing authors include Xia Jin Vassilis Papayannoulis Paul Gilliam, Vision Engineering and Planning LLC Gene Bandy, Vision Engineering and Planning LLC 1 1

Introduction Among stated planning objectives of TPB is to seek improved coordination between land use and transportation planning Recent actions to further this objective Identification of 58 Regional Activity Centers and Clusters (RACCs) along major transportation facilities where focused development exists or is planned Completion of 2007/2008 household travel survey which was specially formulated to include representation of travel behavior associated with RACCs continued 2 Introduction Recent actions to further this objective (continued) Development elopment of a new traffic analysis zone (TAZ) system stem to permit study of observed travel at a finer scale Conflation of regional highway network to NAVTEQ centerline map to improve accuracy and allow enhanced coding detail 3 2

Introduction This task was developed to provide thoughts on how best to improve the regional model s sensitivity to land use and transportation in a practical way Reviewed and considered state of the practice, advanced practices, and the current TPB practice Explored key questions posed as part of the task Provided suggestions for possible short and longer term directions 4 Background Review Incorporation of Land Use Factors in Travel Models Almost half of MPOs forecast one or more of the following: household size, automobile ownership, and income Neighborhood land use density variables and accessibility variables have been shown to improve performance of tripbased travel demand models Accessibility and density measures can feed into many places in travel demand forecasting process Automobile ownership models Trip generation models Mode choice models 5 3

Background Review Nonmotorized Modeling More than half of large MPOs include nonmotorized trips as part of their model in some way but treatment varies widely Range of example treatments Pedestrian three step model special purpose studies (e.g., Central Artery/Tunnel model) Pedestrian environment factor e.g., included in auto ownership and mode choice models in Portland, OR Binary mode choice model after trip generation e.g., DVRPC and Triangle Regional Model (Raleigh, Durham, Chapel Hill) 6 Background Review Nonmotorized Modeling Triangle Regional Model Existing Nonmotorized Model within Trip Generation Set of binary choice models are applied as part of the trip generation step to split motorized and nonmotorized trips Separate model for each trip purpose Developed based on home interview survey data Developing Enhanced Nonmotorized Modeling New activity-oriented household survey collected in 2006 Incorporating additional objective independent variables in existing model framework Adding nonmotorized modeling through first three steps of model process (trip generation, trip distribution, mode choice) 7 4

Background Review Land Use Modeling Land use forecasts serve as fundamental inputs to travel model Transportation infrastructure, services, and policy could influence land use forecasts Some MPOs are moving towards integrating travel models with a formal land use model Baltimore Metropolitan Council halted further development of its TRANUS model in 2003 and switched to PECAS development in 2005 8 Variables RACC Indicator Based on recent household travel survey analysis showing differences in household composition and travel behavior in RACCs versus non-raccs it is attractive to look at this as possible dummy variable(s) for model estimation work However, it would be preferable to first determine if alternative, fully objective measures of pedestrian and transit supportive land use could be used to achieve similar differentiation of household composition and travel behavior This would avoid challenge of less-developed RACCs receiving similar treatment to more-developed RACCs and other potential unintended bias due to subjective treatment Likely that the selected objective measure(s) would be generally correlated with RACC designations 9 5

Variables Potential Density Measures Net Density Ratio of activity measured to the land area devoted specifically to that activity (e.g., total households/residential acres) Gross Density Ratio of activity measured to the total land area (e.g., total households/total acres) Composite Density Looks at population and employment together (e.g., total population + total employment / total acres 10 Variables Potential Accessibility Measures Transit Accessibility Number of jobs accessible in certain amounts of travel time Composite Utility Composite (highway and transit) travel time / cost impedance Other Amount of attractions accessible in certain amounts of walk travel time or highway travel time 11 6

Key Questions How can the finer-level TAZ system be used? Provides an opportunity to recognize and be responsive land use and transportation characteristics at a finer level Align with the RACC boundaries and can thereby be tagged with a RACC indicator TAZ system and network level of detail should be related (i.e., finer-level network coding follows) Permits more accurate portrayal of density, accessibility, or other land use related variables 12 Key Questions How would nonmotorized models be estimated? New household survey provides rich dataset on which new models could be estimated Develop binary choice models that split trip generation results into motorized versus nonmotorized trips Density, block size, connectivity, or other objective measures could be included as variables Sample holdout could be used to enable validation of models developed Look to other regions for possible guidance on most promising variables to use 13 7

Key Questions What changes to the model would be recommended? Vehicle Availability Model Current model uses household size, income level, area type, and employment accessibility Possible improvements include taking into account a RACC indicator or an alternative, objective measure, such as density Trip Generation Model Current model uses trip rates stratified by household size, income level, and vehicle availability Consideration to introducing additional market segments in the cross-classification framework such as RACC indicator, density, area type, and accessibility Expand nonmotorized treatment to all trip purposes 14 Key Questions How well can a regional travel model be expected to address these types of policies? Nonmotorized Improvements Less important to model for determining demand for nonmotorized facilities than for determining changes to motorized travel Planned nonmotorized improvements generally follow from policy directives and a desire to support lower vehicle trip generation as well as higher transit use continued 15 8

Key Questions How well can a regional travel model be expected to address these types of policies? Land Use Policies The travel behavior impacts of concentrated growth patterns should be discernable from regional travel model forecasts Impact of TOD on transit demand should be discernable Although not all underlying traveler response factors can be isolated, density and accessibility are solid indicators of travel behavior differences 16 Key Questions What modeling components in the existing model might be modified to most effectively improve the sensitivity of the models to land use policies and nonmotorized travel? Shorter-Term Improvements RACC Indicator versus Alternative Variable(s) Exploration Vehicle Availability Model Trip Generation Model (add Nonmotorized Split) continued 17 9

Key Questions What modeling components in the existing model might be modified to most effectively improve the sensitivity of the models to land use policies and nonmotorized travel? Longer-Term Improvements (Recommendations from Task 3 Regarding Framework Decisions) Time of Day Model Destination Choice Model Expand Treatment of Nonmotorized Trips Land Use Model 18 10