Implementing VMT as the LOS Replacement Metric in San Francisco Drew Cooper, SFCTA SAN FRANCISCO COUNTY TRANSPORTATION AUTHORITY DATE

A brief history Level of Service Measures vehicle delay Under CEQA intersection delay is an environmental impact, requires study, mitigation

A brief history Can’t cause delay at intersections, might as well build suburban

A brief history And maybe some extra wide roads just to be sure…

A brief history But spread out development + lots of road space + probably not well-served by transit = lots of driving Lots of driving = lots of emissions = bad for the environment SB375 – set GHG reduction targets SB743 – says LOS can’t be used as sole measure of impact under CEQA OPR rulemaking process, not yet complete put out preliminary guidance for VMT SF decides to not wait for state

Legislative Direction SB 375 SB 743 Office of Planning and Research SB375 – set GHG reduction targets SB743 – says LOS can’t be used as sole measure of impact under CEQA OPR rulemaking process, not yet complete put out preliminary guidance for VMT SF likes to be first to things, so we decided not to wait Although Pasedena beat us to it

Goals Align CEQA impacts with City policies Encourage projects with better environmental outcomes Consistent and fair methodology Predictable outcomes So we formed a working group and laid out some goals for ourselves. First we want to make sure that CEQA transportation analysis is consistent with City goals City Hall by Roberto Arias https://commons.wikimedia.org/wiki/San_Francisco#/media/File:San_Francisco_City_Hall_4.jpg

Some Things Considered VMT Per person… household… project… person-trip… etc. Maxwell We considered VMT in combination with any and all denominators you could think of. We considered inverting it so VMT is the denominator and called it a Maxwell. Ultimately we decided to go with VMT per person

Why VMT? Measure of how much driving Already use VMT for GHG accounts for both # trips and distance Already use VMT for GHG Measure of how much driving accounts for both # trips and distance Already use VMT for GHG By Daniel Schwen - Own work, CC BY-SA 2.5, https://commons.wikimedia.org/w/index.php?curid=1072327

Methodology We started off by dividing up land use projects into three broad categories: residential, office, and retail. Then for each of these categories we developed a unique VMT-based metric, and a threshold of significance. Then, using outputs from our travel demand model, we calculated the metric for each TAZ in the Bay Area.

Methodology Residential and office: fairly straightforward Residential is average daily VMT per person. Relatively simple because with model output we can trace their movements through the day, determine which trips happened in cars, add up the VMT, and tag that VMT to their home location Office is similar: miiples, if workers, have a primary work location, and we can add up the VMT from all the work-related trips and assign it to the work location With VMT calculated, we then simply divide by number of people for res or jobs for office

Everything gets weird when you talk about retail Trip 1 Trip 4 Trip 2 Residential and office are easy because they are anchor points of daily travel. Retail isn’t like that, though, so we needed a different methodology. We think that people choose these destinations more based on their location and accessibility relative to the anchor locations. It’s not appropriate to look at daily VMT for these locations so we used a trip-based measure instead Start with all trips where at least one trip end is not home, work, or school Add up VMT for all drive trips to a TAZ If the other end of the trip is home, work, or school then 100% goes to this TAZ Otherwise, split VMT 50-50 between both TAZs Trip 3

Everything gets weird when you talk about retail VMT = Trip 1 + ½ Trip 2 Trip 1 Trip 4 Trip 2 Residential and office are easy because they are anchor points of daily travel. Retail isn’t like that, though, so we needed a different methodology. We think that people choose these destinations more based on their location and accessibility relative to the anchor locations. It’s not appropriate to look at daily VMT for these locations so we used a trip-based measure instead Start with all trips where at least one trip end is not home, work, or school Add up VMT for all drive trips to a TAZ If the other end of the trip is home, work, or school then 100% goes to this TAZ Otherwise, split VMT 50-50 between both TAZs VMT = Trip 1 + ½ Trip 2 Trip 3

Everything gets weird when you talk about retail What do we divide by? “Retail size” measure Base on how model chooses “other” destinations Residential and office are easy because they are anchor points of daily travel. Retail isn’t like that, though, so we needed a different methodology. We think that people choose these destinations more based on their location and accessibility relative to the anchor locations. It’s not appropriate to look at daily VMT for these locations so we used a trip-based measure instead Start with all trips where at least one trip end is not home, work, or school Add up VMT for all drive trips to a TAZ If the other end of the trip is home, work, or school then 100% goes to this TAZ Otherwise, split VMT 50-50 between both TAZs What do we divide by? “Retail size” measure Current “retail size” based on the way the model chooses “other” destinations Accounts for # retail + households + CIE + school enrollment, and a few other land use categories

Thresholds and Results OPR suggested a threshold of 15% below the regional average, so rather than try to pick our own arbitrary number, we went with that. These maps show, on the left, TAZs that exceed 85% of the regional daily residential VMT, and on the left, TAZs that exceed 85% of the regional daily work-related VMT

Thresholds and Results And finally, TAZs that exceed the retail threshold. The upshot of all this is that, if a project is located in one of these grey zones and they don’t propose something egregious, they’re project is going to be presumed to have less than significant impacts on VMT and wouldn’t require an EIR for transportation-related issues.

Takeaways Analysis tools may put restrictions on the methodology Similar methodologies may have profoundly different implications for different regions and jurisdictions One size does not fit all Simple is best

Thanks! drew.cooper@sfcta.org