Impact of development on VMTImpact of development on VMT

WOC-Low VMT: 338873 new households WOC-Low VMT: 338873 new households averaging 0.9266 * 2 miles of non-work travel averaging 0.9266 * 2 miles of non-work travel per dayper day

LIB-Low VMT: 297156 new households LIB-Low VMT: 297156 new households averaging 1.2559 * 2 miles of non-work travel averaging 1.2559 * 2 miles of non-work travel per dayper day

LIB-Random: 297160 new households LIB-Random: 297160 new households averaging 1.4024 * 2 miles of non-work travel averaging 1.4024 * 2 miles of non-work travel per dayper day

Impact of development on VMTImpact of development on VMT

Big picture…Big picture… LIB vs. WOC: 1.2559/0.9266 = 1.355LIB vs. WOC: 1.2559/0.9266 = 1.355

LIB is 36% worse than WOC even if you locate LIB is 36% worse than WOC even if you locate development in the most accessible areasdevelopment in the most accessible areas

LIB-random vs. WOC: 1.4024/0.9266 = 1.5134LIB-random vs. WOC: 1.4024/0.9266 = 1.5134 With no preference for accessible land, LIB-random With no preference for accessible land, LIB-random

is 51% “worse” than WOCis 51% “worse” than WOC

Impact of development on VMTImpact of development on VMT

Big picture…Big picture… Compared with baseline mileage, WOC, LIB Compared with baseline mileage, WOC, LIB

and LIB-random non-work VMT increases are:and LIB-random non-work VMT increases are: WOC: 17.8%WOC: 17.8% LIB: 23.8%LIB: 23.8% LIB-random: 26.6%LIB-random: 26.6%

Assuming 20% growth and 20mpg average, we Assuming 20% growth and 20mpg average, we estimate 4-6 million extra gallons of gas from estimate 4-6 million extra gallons of gas from LIB vs. WOC. LIB vs. WOC.

Prediction or prescription?Prediction or prescription?

Bottom line: Accessibility is important! (big Bottom line: Accessibility is important! (big differences between algorithms)differences between algorithms) It matters how you calculate it—e.g., VMT vs. It matters how you calculate it—e.g., VMT vs.

EUDIST, both are imperfectEUDIST, both are imperfect Also matters how you measure its impacts on future Also matters how you measure its impacts on future

growthgrowth Two roles: both a real-world driver of development Two roles: both a real-world driver of development

and something we want to optimize forand something we want to optimize for

Models are a two-way streetModels are a two-way street

Building an Algorithm: A few Building an Algorithm: A few philosophical issues that matterphilosophical issues that matter

Do different housing types “want” different Do different housing types “want” different things in the real world? things in the real world? Accessibility vs. open spaceAccessibility vs. open space

Simulate the market, or seek smart growth?Simulate the market, or seek smart growth? Prediction vs. prescriptionPrediction vs. prescription

LIB and WOC allocation strategies—same LIB and WOC allocation strategies—same or different?or different? Ease of comparison vs. faithfulness to modelEase of comparison vs. faithfulness to model

Prediction or prescription?Prediction or prescription?

What use are housing algorithms like ours for What use are housing algorithms like ours for the public dialogue? A few possibilities:the public dialogue? A few possibilities: A smart-growth ideal that can be used to influence A smart-growth ideal that can be used to influence

zoning debateszoning debates A way to engage local residents in the issue A way to engage local residents in the issue

Hey, there’s my neighborhoodHey, there’s my neighborhood Environmental impactEnvironmental impact

A two-way dialogue: Can they be used to get both A two-way dialogue: Can they be used to get both planners and residents involved in improving the planners and residents involved in improving the models?models?

Local vs. Regional: Where the Local vs. Regional: Where the rubber meets the roadrubber meets the road

Model looks at effects Model looks at effects over a huge regionover a huge region

Zoning decisions Zoning decisions happen at a local—even happen at a local—even hyperlocal—levelhyperlocal—level

Even if most people Even if most people “buy” the goals of “buy” the goals of MetroFuture, there will MetroFuture, there will still be fierce local still be fierce local battlesbattles

Winds of Change or Winds of Change or Patchwork of Change?Patchwork of Change?

How can finer resolution help?How can finer resolution help?

Visualizing the kind of change needed at the localVisualizing the kind of change needed at the local—and hyperlocal—level —and hyperlocal—level

Town planners may feel they have a handle on Town planners may feel they have a handle on their own towns—but what’s happening next door?their own towns—but what’s happening next door?

Finer-resolution models inevitably introduce some Finer-resolution models inevitably introduce some error—but they can also help get the conversation error—but they can also help get the conversation down to the level where decisions get madedown to the level where decisions get made