California’s VMT Problem: How Flawed Data Blocks Climate-Friendly Housing
California has pledged to be a national leader in the fight against climate change and the housing crisis. But a new report from UC Berkeley’s Terner Center and a companion analysis from California YIMBY show that the state’s own rules may be undermining both goals. At issue is how the state defines “low-VMT neighborhoods” — areas where residents drive fewer miles, helping to reduce emissions. These neighborhoods are supposed to qualify for streamlined housing approvals under state law. But flawed and outdated data models mean that many climate-friendly, high-opportunity urban neighborhoods are being excluded.
The Terner Center report, Aligning Housing with Climate Goals: The Importance of Measuring VMT, authored by Rachel Strangeway and Zack Subin, examines how different tools for estimating vehicle miles traveled (VMT) influence what housing gets built — and where. Their findings are stark: California’s current model misidentifies large swaths of urban areas that should be eligible for fast-track housing development. And it systematically disadvantages the very neighborhoods where more housing would best serve both environmental and social equity goals.
VMT plays a central role in aligning land use with the state’s climate targets. Under Senate Bill 743, California evaluates the environmental impact of housing developments partly through how much driving the new residents are likely to do. Projects in areas with VMT at least 15 percent below the regional average may qualify for CEQA streamlining, enabling faster construction. But if VMT is mismeasured, neighborhoods that are walkable, transit-rich, and already support low emissions could be wrongly excluded from streamlined approval — and the homes needed to make those neighborhoods more accessible simply don’t get built.
The Terner Center study compared three different tools for estimating VMT across California neighborhoods: the State model, which relies heavily on pre-pandemic data from regional agencies; Replica, a simulation platform that uses anonymized mobile device data to model travel behavior in near real-time; and LATCH, a national model based on 2017 household travel survey data. Of the three, the State model is the most commonly used for CEQA streamlining — and it’s also the least accurate, the report finds.
In Los Angeles, for example, the Replica model identified 62 percent of the population as living in low-VMT areas. The State model identified just 40 percent. In San Jose, similarly, dense and transit-accessible neighborhoods were recognized as low-VMT by Replica, but not by the state’s outdated tool. The difference is not academic: it determines where housing gets approved, how fast, and with how much legal risk for developers and local governments.
One of the biggest problems lies in how VMT thresholds are defined. California currently evaluates neighborhoods against their regional VMT averages. In car-dependent regions like the Central Valley or Inland Empire, this makes it relatively easy for a neighborhood to qualify as “low-VMT.” But in already low-driving regions like the Bay Area, the regional baseline is so low that many otherwise climate-friendly areas narrowly miss the cut.
This creates a perverse outcome: the greener a region already is, the harder it is for any neighborhood within it to qualify for VMT-based streamlining. The Terner Center found that using a statewide VMT baseline — rather than regional — would increase eligibility by 40 percent in the Bay Area. In other words, California’s own framework is punishing the regions that have already done the most to reduce driving and support sustainable development.
Beyond the climate implications, this also undermines equity. The YIMBY blog post highlights that the State model often fails to identify neighborhoods designated as “high opportunity” by the California Tax Credit Allocation Committee’s (CTCAC) Opportunity Map. These neighborhoods typically have strong public schools, good transit, and access to jobs — places where more housing could provide life-changing access for lower-income families. But because they often exist in regions with already-low VMT, they’re penalized by the current methodology. Meanwhile, some car-dependent, lower-resource areas are greenlit, simply because their regional VMT baseline is higher.
The Replica model, by contrast, shows much stronger alignment with both actual traffic volume data and with California’s stated equity goals. It not only maps travel behavior more accurately, but also highlights neighborhoods that overlap with high-opportunity areas. These are exactly the places where more housing could advance both environmental and social objectives — yet they are being left out of the fast-track process.
There are clear steps the state can take to fix this problem.
First, California should modernize its VMT modeling framework by adopting tools like Replica that incorporate current, public data — including anonymized smartphone mobility data, which better captures how people actually move through cities today. Pre-pandemic models based on outdated regional data fail to reflect post-COVID behavioral shifts, including increases in remote work and changing transit patterns.
Second, the state should rethink its strict reliance on VMT as the only way to determine environmental eligibility for streamlined housing. Walkability scores, residential density, and transit proximity are also meaningful proxies for lower emissions and could offer more equitable and accurate alternatives for identifying climate-friendly development areas.
Third, and perhaps most urgently, California should replace the regional VMT baseline with a statewide comparison, especially in regions like the Bay Area where low driving is already the norm. This change would allow the state to reward — not punish — places that have long supported sustainable growth and efficient transportation.
Misidentifying low-VMT areas doesn’t just slow housing approvals. It reinforces patterns of exclusion and inequality. By blocking new homes in transit-rich, high-opportunity neighborhoods, California effectively maintains barriers to integration and undercuts its own climate targets. CEQA streamlining, if implemented correctly, should unlock housing where it does the most good — where it reduces emissions and expands access. Instead, under current rules, it’s too often doing the opposite.
Aligning housing policy with climate goals means ensuring that the right data drives the right decisions. As the Terner Center and California YIMBY make clear, the stakes are high. If California continues to use flawed models, it will miss the neighborhoods that matter most — and the homes, families, and futures that depend on them.