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From page 97... ... 97 A P P e n D I x A The Built environment's Impacts on Peak Auto Demand Performance Metrics There are a variety of performance metrics for evaluating the effect of the built environment's impacts on peak auto demand. This section includes examples of metrics from state transportation departments and metropolitan planning organizations (MPOs) Read the entire page →
From page 98... ... 98 System-wide congestion indicators include VMT, VMT per capita, congested lane miles of highway, percent of highway system congested, VHD, and VHD per capita. Corridor-specific congestion indicators include the number of routes where the duration of the congested period improved, the number of routes where the average peak travel time improved, and the number of routes where 95% reliable travel time improved. Read the entire page →
From page 99... ... 99 direct ridership models (DRM) , best management practices (BMP) Read the entire page →
From page 100... ... 100 101 Table A.1. Capabilities of Planning Tools for Evaluating Interactions between Land Use and Transportation Macro Regional or County Meso Subregional or Corridor Micro Neighborhood or Community C V E T iP IN U F R F M Q T R M X P M X V D R M B M P T D M C V E T iP IN U F R F M Q T R M X P M X V D R M B M P T D M C V E T iP IN U F R F M Q T R M X P M X V D R M B M P T D M Land Use Representation Place types b b b b b b b b b b b b b b b b b b b b b b b Parcel-based b b b b b b b b b b b b b b b b b b b Grid-Cell-based b b b b b b b b b b b b b b b b b b Census block b b b b b b b b b b b b b b b b b b Traffic analysis zone b b b b b b b b b b b b Major Transport Net Representation Internal major multimodal net b b b b b b b b Shares data with network model b b b b b b b b b b b b b b b b b b b b Only local connectivity and transit stations b b b b b b b b b b b Relationships Addressed Built Environment ➔ Demand b b b b b b b b b b b b b b b b b b b b b b b b b b Demand Management ➔ Demand b b b b b b b b b b b b b b b b b Demand  Supply ➔ Congestion b b b b b b Feedback/Induced Growth b b b b Feedback/Induced Travel b b Freight b b Note: Comprehensive, multi-issue land use transportation planning tools: CV = CommunityViz, ET = Envision Tomorrow, iP = iPLACE3S, IN = INDEX, UF = Urban Footprint, RF = Rapid Fire, MQ = MetroQuest, and TR = TREDIS. Read the entire page →
From page 101... ... 102 103 data on person and household travel characteristics. These models also require significant time investments in data assembly and model development and resources, which are major challenges typically best addressed by the largest MPOs. Read the entire page →
From page 102... ... 104 jobs-housing balance (Kuzmyak 2006) , and predict daily traffic for land use and transportation options along proposed multi-modal corridors (Fehr & Peers 2004) Read the entire page →
From page 103... ... 105 hours of advanced driver assistance service, and transit revenue hours. Auto metrics include park-and-ride capacity and utilization. Read the entire page →
From page 104... ... 106 traffic attributable to the TOD is assumed to be 50% - [(14,000 - 12,000) Read the entire page →
From page 105... ... 107 By using simple factor methods (more formally, sometimes called "postprocessing") , one can make a plausible, empirically informed adjustment of internal captures accounting for the induced demand impacts of suburban, mixed-use development. Read the entire page →
From page 106... ... 108 response to a legal challenge from an environmental group regarding the suitability of the Wasatch Front Regional Council (WFRC) travel demand model for analyzing highway expansion (Schiffer et al. Read the entire page →
From page 107... ... 109 links or at intersections in the immediate proximity of the developments, but requires methods and metrics that can attribute the impacts to source. Methods and metrics that can serve this purpose are • Traffic volumes on individual network links or inter sections by time of day and direction; and • Proportion of those volumes comprising trips with a relationship to the study area (both origin and destination, or either origin or destination within the study area) Read the entire page →
From page 108... ... 110 and efficient, and also lead to a high percentage of internally captured non-home-based trips. Application Tools It is acknowledged that conventional TAZ-based travel forecasting models are poorly suited to estimate the effects of smart growth land patterns on travel behavior. Read the entire page →
From page 109... ... 111 for basic travel. If walking and biking are viable alternatives, they can serve as a substitute for auto trips, provide improved access to and from transit, and allow both residents and visitors to travel between non-home-based locations without relying on a car. Read the entire page →
From page 110... ... 112 Figure A.2. 2030 daily traffic flows in US-1 North Corridor. Read the entire page →
From page 111... ... 113 Figure A.3. Internal capture analysis for US-1 North Corridor. Read the entire page →
From page 112... ... 114 using simple or sophisticated accessibility indices, entropy equations, and other functions, around points of interest (e.g., homes and businesses) , routes of interest, and/or zones. Read the entire page →
From page 113... ... 115 • Local/jurisdictional revenues; • Land consumption; • Fiscal impact; • Resource usage and waste generation; • Housing affordability; and • Storm water management. The next section addresses whether each of the available application tools is capable of producing the above list of metrics. Read the entire page →
From page 114... ... 116 • Rapid Fire; • Urban Footprint; and • TREDIS. Each of these tools has been used by at least a handful of MPOs and/or at a state level to perform interactive smart growth scenario evaluations of a broad array of social, economic and environmental indicators. Read the entire page →
From page 115... ... 117 also need to investigate the lack of application tools equipped to address these issues. References Burchell, R., G Read the entire page →
From page 116... ... 118 Use Developments. Transportation Research Board of the National Academies, Washington, D.C. Read the entire page →

From page 97...

... 97 A P P e n D I x A The Built environment's Impacts on Peak Auto Demand Performance Metrics There are a variety of performance metrics for evaluating the effect of the built environment's impacts on peak auto demand. This section includes examples of metrics from state transportation departments and metropolitan planning organizations (MPOs)