Five weeks before Election Day, President Donald Trump’s sprawling effort to identify and remove noncitizen voters hasn’t produced the kind of large purges that could meaningfully affect the midterm elections.

Even a recent U.S. Supreme Court decision giving states access to a supercharged Department of Homeland Security computer program to verify voters’ citizenship will have a limited immediate impact, election experts say. 

As Republicans fight to retain control of Congress, Trump and his allies have spent the past year aggressively seeking to root out noncitizen voting. 

They have called into question the security of the upcoming elections, following the lead of the president, who has long made spurious claims of voter fraud to dismiss unfavorable results.

Those efforts are now colliding with federal law — and the reality long shown by studies and available data that noncitizen voting is rare.

Little impact seen from court ruling

The Supreme Court on Sept. 25 ruled in a 6-3 decision that states can access Homeland Security’s SAVE system, which draws upon citizenship information stored across the federal government to scour voter rolls in the hunt for possible noncitizens. A district court judge had blocked the program in June.

But the high court’s decision came during a quiet period under the National Voter Registration Act that prohibits most states from conducting mass purges of voters in the 90 days before a federal election. 

The timing limits election officials to only searching for information on individual voters, even though Homeland Security has touted SAVE to states as a tool that can quickly scan millions of names.

The Supreme Court’s conservative majority acknowledged as much, writing in its unsigned opinion that the quiet period “limits the potential impact” of the court’s decision. 

Justice Ketanji Brown Jackson, writing for the court’s three liberals, agreed the decision would have minimal short-term effects but argued the possibility of disenfranchising even a few lawful voters outweighed any risk of harm to the government.

David Becker, executive director of the nonpartisan Center for Election Innovation & Research, in a statement emphasized that voters will continue to experience the same safe, secure and reliable voting process this year as in the past.

“This decision will not have any significant impact on the 2026 election, as systematic voter list maintenance is prohibited within 90 days of a federal election, which the Supreme Court explicitly confirmed,” Becker said.

Post-2026

The more significant fallout from the Supreme Court’s decision may come in the weeks and months after the election, when states can once again remove large numbers of voters from their rolls. 

The Supreme Court is also set to hold oral arguments in December in a case that involves the reach of the National Voter Registration’s Act’s quiet period — leaving open the possibility the justices could give states more leeway to purge voters ahead of elections.

But for now, the restrictions remain in place.

“Until the Supreme Court says, reinterprets otherwise, the quiet period is still the quiet period,” Aaron Blacksberg, federal policy counsel at the Institute for Responsive Government, said in an interview.

Separately, a U.S. district court judge on Monday blocked the Trump administration’s efforts to require states to use SAVE as a condition of receiving some Federal Emergency Management Agency grants. Judge Amir H. Ali, an appointee of President Joe Biden, wrote that FEMA exceeded its authority in imposing election-related requirements.

Is the data reliable?

SAVE’s critics, which include Democrats and privacy advocates, warn that the system relies on incomplete and sometimes outdated data, resulting in false positives. SAVE was previously used to check whether noncitizens were eligible for various government benefits before the Trump administration last year repurposed it into a tool to check citizenship.

When U.S. District Judge Sparkle Sooknanan, a President Joe Biden appointee for a district court based in Washington, D.C., ruled against the program in June, she highlighted sworn declarations by naturalized citizens that Texas had threatened to revoke their voter registrations because of inaccurate Social Security data in SAVE.

“SAVE was never designed to verify citizenship: it relies on outdated and inaccurate data that produces false matches, risks disenfranchising eligible voters, and exposes sensitive personal information to misuse and bad actors,” Tim Harper, a project lead focused on elections and democracy at the Center for Democracy & Technology, a nonpartisan organization focused on civil liberties in the digital age, said in a statement.

The Trump administration and some Republicans hail SAVE as a powerful tool to ensure the accuracy of voter rolls and identify noncitizens who shouldn’t be registered to vote. They note that its use by states is voluntary.

“It’s remarkable that we had to file an emergency petition in the Supreme Court just so we can use government data to stop noncitizens from voting illegally. American elections are for Americans,” James Percival, Homeland Security’s general counsel, said in a statement.

In an email to States Newsroom, White House spokeswoman Lauren Bis faulted Democrats for not voting for the SAVE America Act, a bill that would require voters to produce documents proving their citizenship before voting. The bill has stalled in the U.S. Senate amid bipartisan opposition.

“The American people overwhelmingly support this commonsense legislation that enacts basic election security measures like voter ID and ensures only Americans are electing America’s leaders. President Trump is absolutely right: we fix this now, or we lose our country,” Bis said..

How many instances of noncitizen voting?

The Trump administration’s intense focus on noncitizen voting — which also includes a legal effort to force states to turn over voter data to the Department of Justice — contrasts with the extremely rare nature of noncitizen voting, according to past studies and election experts.

The U.S. Census in August identified about 24,000 instances of noncitizen voting in the 2020 election out of roughly 160 million votes cast, or 0.015% of all votes. One study of the 2016 election placed the prevalence of noncitizen voting at 0.0001% of votes cast.

But Homeland Security has suggested large numbers of noncitizens may be registered to vote. In July, the department said it had identified over 250,000 potential noncitizens on the voter rolls in California, New Jersey, Nevada and Pennsylvania.

On Monday, U.S. Senate Democrats in a letter to Homeland Security Secretary Markwayne Mullin wrote that they couldn’t trust those numbers. For instance, DHS initially floated nearly 16,000 possible noncitizen voters in Nevada. In the end, the agency provided state officials with a list of 185 people that officials said were noncitizens. All turned out to be citizens.

“Federal law already prohibits noncitizens from voting in federal elections, and every eligible voter across America has the right to cast a ballot — and should be able to do so without fear of being wrongly purged from the voting rolls,” Sen. Dick Durbin, an Illinois Democrat, said in a statement following the Supreme Court’s decision.

The alleged scale of potential noncitizen voter registration by Homeland Security also doesn’t match the scope of the agency’s law enforcement actions. Earlier in September, Homeland Security Investigations, a DHS agency, reported making 160 recent arrests from 1,600 open voter fraud cases.

When noncitizens do end up on voter rolls, administrative errors are sometimes to blame. In July, New Jersey Gov. Mikie Sherrill, a Democrat, announced that a software glitch caused about 6,600 noncitizens to become registered to vote and that about 400 had cast ballots. 

And in April, then-Texas Secretary of State Jane Nelson, a Republican, wrote in a letter to U.S. Citizenship and Immigration Services that some noncitizens had been registered to vote because of a clerical error despite acknowledging on a voter application that they weren’t U.S. citizens.

“That is why we urge voter registrars to use all available sources to confirm a person’s citizenship status — including SAVE data and other information about the registrant — when they are investigating whether the person is eligible to be a registered voter,” Nelson wrote in an email obtained by Democracy Forward, a pro-democracy legal organization.

The official poverty rate in the United States dipped slightly by half a percentage point last year to a historic low of 10.2%, according to U.S. Census Bureau data released Tuesday.

The supplemental poverty rate, a more holistic figure that includes an individual’s non-cash resources, remained essentially unchanged at 13.1%, according to the bureau’s annual poverty report. The report measured 2025 numbers in comparison with 2024 and previous years.

The median household income for 2025 rose 2.6% from the previous year to $87,460, the highest on record, according to the bureau’s annual income report.

Some experts cautioned that the data doesn’t reflect the effects of new federal policy changes that will be hitting households hard this year, and that the United States should expect grimmer statistics in next September’s report. Most significantly, the massive tax and spending bill passed by Congress last year slashed Medicaid, food assistance and other public benefits that have kept millions in the country hovering above the poverty line.

This week’s numbers are not all that surprising, but they may not reflect an entirely positive picture, said Steven Durlauf, a professor and director of the Stone Center for Research on Wealth Inequality and Mobility at the University of Chicago.

The supplemental poverty measure, he noted, is more all encompassing because it includes cash and noncash benefits and expenses, such as taxes and medical expenses, whereas the official poverty measure focuses just on cash resources. 

“There’s some basic good news there, and that is that median household income, you know, substantially increased 2.6% after inflation is nothing to to sneeze at,” Durlauf said. But he said the fact that the supplemental measure hasn’t budged could mean that people with lower incomes, and who may rely on more government benefits, aren’t really benefiting from “an economy that’s running hot.” 

Census data show women in full-time, year round work saw higher median earnings from last year by about 3%, while men in the same position saw a decline of 0.9%. 

And while it’s true there was growth in wage income this year, Durlauf said, he expects the numbers will be worse next year for people from more marginalized backgrounds. He pointed to “inequality-increasing” policies such as tax cuts for the rich, cuts to the Supplemental Nutrition Assistance Program, also known as food stamps, and major cuts to the Medicaid health insurance program for people with lower incomes. 

“The main issue for most individuals is going to be the fact that prices and inflation is outstripping wage growth, and so that’s obviously some diminution of real incomes for some people,” Durlauf said. 

U.S. Census Bureau data also show 92.1% of people were insured in 2025, as compared with 92% in 2024 – reflecting the relatively flat uninsurance curve in the U.S. since 2020, when 91.4% of people were insured. 

The Congressional Budget Office, a nonpartisan research arm of Congress, estimated that roughly 15 million people would become uninsured by 2034, well more than the current estimate of 1.3 million uninsured people. 

Additionally, the number of children receiving SNAP benefits fell by 1.2 million between July 2025 and July 2026, according to an August analysis released by the left-leaning research group Center on Budget and Policy Priorities. 

“The combination of the erratic fiscal policies, the effect on energy prices via this destabilization of the Middle East, and to be blunt, the utterly irresponsible fiscal policies of the country in terms of budget deficits, are not conducive to an economic environment in which the economy does well in terms of the usual ways we think about growth,” Durlauf said. 

Stateline reporter Shalina Chatlani can be reached at schatlani@stateline.org.

While routing and infrastructure shape fuel use at a macro level, vehicle idling represents one of the most immediate and controllable sources of waste.

Most districts have idling policies that meet or exceed state requirements, with exceptions for extreme weather. Historically, however, enforcement has been inconsistent due to a lack of data.

Telematics has changed that. School districts can now track idling time by vehicle, route, and driver, making it possible to identify patterns and enforce policies more effectively.

Data-driven approaches to idling typically combine policy enforcement with education and route optimization. Rather than treating idling as a disciplinary issue, district leaders use data to identify root causes and adjust operations accordingly.

“Idling is the clearest example of a problem that was previously invisible and is now entirely measurable,” said Craig Berndt, Geotab business segment manager of people transportation. “Most districts have an idling policy. Very few, until recently, had any way to know whether it was being followed.”

Berndt noted the emerging standard across many of the school districts with which Geotab works is a two- to five-minute engine-on idle limit. It can be longer in extreme weather conditions.

“Some states have regulatory requirements that align with this,” he said. “But the policy itself only has value if it’s enforced, and enforcement requires data.”

Complicating matters is H.R. 9317, which was introduced to Congress in June. Known as the BUSES Act, short for Buses Utilizing Safety and Environmental Standards, it would amend the Clean Air Act to prohibit state and local governments from enforcing engine idling restrictions on over the road buses and school buses if the engine idles for less than 15 minutes. It would also ban lawsuits filed against school bus owners or operators for alleged idling violations. The House Energy and Commerce Committee advanced the BUSES Act on Wednesday.

Still, Berndt noted telematics enables automatic idling alerts: A notification to a supervisor when a bus has been idling beyond the threshold, with location, driver and duration.

“This shifts enforcement from reactive, a complaint from a principal about exhaust near the front entrance, to proactive. And it creates an accountability loop that changes behavior over time,” he said. “Drivers who know their idle time is visible tend to idle less, not because of punitive pressure but because the visibility makes the issue concrete rather than abstract.”

Berndt noted the cost case is straightforward: A diesel school bus burns approximately 0.8 gallons per hour at idle.

“For a 100-bus fleet idling an average of 30 excess minutes per day, that’s 40 gallons per day in waste, $80 to $120 at current prices every operating day of the year,” he said. “With telematics-driven enforcement, districts routinely cut excess idle time by 30 to 50 percent.”

Beyond fuel, the idling conversation matters for public perception in ways that are becoming more acute, noted Berndt.

“School communities are increasingly attentive to emissions around buildings and bus queues, and districts that can demonstrate they’re actively managing and measuring this are in a much better position when parents or advocacy groups raise the issue,” he said.

Related: State School Bus Idling Rules & Regulations
Related: Green Bus Resources
Related: Data, Routing Analytics for Fuel Efficiency

St. Louis (Missouri) Public Schools supports school bus and vehicle contractor Zum’s idling policy, and Zum’s engine‑on/engine‑off data helps them enforce it, said Transportation Director Kacy L. Davis.

While Zum does not publicly state its idling policy, the company limits unnecessary school bus idling and trains drivers to minimize idle time by using routing technology to reduce waiting and fuel consumption. Meanwhile, The Missouri Department of Natural Resources encourages school districts to adopt anti-idling policies for school buses. Several counties including St. Louis and the Kansas City Ozone Maintenance Area restrict bus idling to 15 minutes in any 60-minute period to maintain passenger comfort.

“Reducing idling lowers fuel costs, improves air quality around schools and reduces engine wear,” he added. “Together, these tools give us a clear picture of how routing decisions affect fuel use, maintenance, and overall operational efficiency.”

SLPS also is preparing to launch a 30‑bus electric fleet in the 2027–2028 school year through the EPA Clean School Bus Program as part of the district’s broader Future Ready initiative to modernize operations and improve the student transportation experience.

The post Updated: Vehicle Idling Reduction Requires Data-Centric Approach appeared first on School Transportation News.

Even the most carefully designed route can diverge from reality once a school bus hits the road. That gap between planned and actual routing is one of the most underrecognized sources of inefficiency in school transportation. IT is also where data analytics come into play.

Craig Berndt, Geotab business segment manager of people transportation, noted GPS and post-route analysis, close this loop.

“When a transportation department can pull a daily report comparing planned mileage against odometer-confirmed actual mileage by route, by driver, and by day, they have a feedback mechanism that simply didn’t exist before telematics,” he said. “The goal isn’t to penalize drivers for deviations. Most deviations have legitimate causes. The goal is to make the routing software reflect reality, so the plan you’re managing against is accurate.”

Berndt noted that the most effective departments he works with treat this as a continuous process rather than an annual audit.

“They review variance reports weekly, push corrections back to the routing software monthly and build a culture where drivers report deviations because they know the data is used to improve routes, not to discipline them,” he said.

Ron Johnson, director of support operations for Indian Prairie School District #204 in Aurora, Illinois, noted his district’s use of Onscreen GPS software to review when and why drivers deviate from the planned route path.

“If a driver consistently takes an alternate path because it is safer or faster, the planned route path is updated,” he said. “If the deviation is inefficient, targeted driver coaching can correct it. This continuous feedback loop ensures that mileage reduction is achieved without compromising student safety or service reliability.”

Comparing planned versus actual routing allows the district to ensure that the actual route is as efficient as possible, said Jason Hibbard, supervisor of transportation for the Chenango Valley Central School District in Binghamton, New York.

“We regularly analyze our routes to minimize the amount of students having to cross the road at a stop,” he added. “We have adjusted stops when we find hazardous conditions, be it excessive cars passing through the reds, blind corners or just excessive traffic.”

Rich Casto, transportation supervisor for Jackson County Schools in West Virginia, noted analytics are helpful in viewing a planned route versus the actual route and accounting for unnecessary mileage.

Related: Data & Routing Analytics for Fuel Efficiency
Related: Routing Analytics Matter for Fuel Efficiency, Experts Agree
Related: School Districts Look for Innovative Approaches to Recruiting and Training
Related: Watch: Michigan Association Releases Lomas Brown PSA for Back to School

“Occasionally, there will be a situation where sometimes the analytics will have a route laid out that may or may not be possible for a larger vehicle,” Casto explained. “There are a lot of factors involved. Road conditions and clearance issues play in the equation. Sometimes not every produced path is a viable path for a bus.”

There is often a distinct gap between a route designed in a software environment and how it plays out in real life, noted Kathy Calkins, North Clackamas (Oregon) School District transportation director.

“Common disruptions include unexpected road construction, driver workarounds, shifting student addresses, and substitute drivers navigating unfamiliar areas,” she said. “To bridge this gap, we rely on a combination of GPS tracking, telematics and post-route analysis. Good communication from our community partners regarding construction before it starts, so that we can identify exactly where drivers are forced to detour. This allows our routers to update routes well in advance, without compromising student safety or service levels.”

The post Planned Versus Actual Routes and the Impact on Unnecessary Mileage appeared first on School Transportation News.

School transportation operations are increasingly turning to routing data, GPS, telematics, maintenance records and analytics tools to reduce fuel use, unnecessary mileage and related operating costs.

Transfinder recently announced that transportation leaders in 30 states cited operational challenges limiting route optimization in the software and hardware through the company’s School Bus Routing Efficiency Poll, with fuel costs being one pain point. The company noted California’s diesel per gallon prices in late May soared nearly 66 percent since April 2025 compared to 26 percent for gasoline, with one district turning to Transfinder routing software to help ensure logistically efficient routes.

“A route is never just a line on a map; it is a financial equation that directly impacts a district’s bottom line,” noted Ron Johnson, director of support operations for Indian Prairie School District #204 in Aurora, Illinois.

“As school districts nationwide grapple with tightening capital budgets, driver shortages and ambitious environmental goals, transportation directors are being asked to do more with less.”

True operational efficiency requires moving beyond reactive management, Johnson said, adding that transportation departments can transform themselves into data-driven strategic assets by leveraging advanced routing analytics, enforcing smart idling policies and optimizing fuel procurement.

Indian Prairie uses Tyler Technologies Versatrans
Routing and Planning with Tyler Drive tablets to analyze its routing practices and ensure reductions in fuel use and vehicle wear. “We positioned our dispatch centers and vehicle garage locations to reduce excessive deadhead miles,” he said. “Miles driven without students on board generate zero operational value while burning fuel and wearing down vehicles.”

The district has ongoing efforts to review outdated routes and changing ridership numbers. “A few years ago, we re-did our school boundaries, significantly reducing the miles driven,” Johnson said. “We also incorporated a practice to reduce idling and multiple stops in the same area. Left-hand turns against heavy traffic, stops placed too close together, routing through highly congested bottlenecks increase idle times, or slow average transit speeds and drives up fuel burn.”

Fuel efficiency in school transportation is fundamentally a systems problem, not just a driver behavior problem, said Craig Berndt, Geotab business segment manager for people transportation.

“A bus burning excess fuel is often a symptom of a route that was designed years ago against student populations and road networks that no longer exist,” he said, adding routing analytics make inefficiencies visible. By overlaying GPS tracking data against planned routes with Geotab’s routing partners, Berndt said patterns emerge quickly such as routes that consistently run 15 percent longer than planned, corridors where two routes shadow each other, and deadhead miles accumulating because a terminal is poorly positioned relative to the first pickup.

Districts taking a data-driven approach to routing optimization typically find 8- to 12-percent mileage reductions in the first year of active management, he noted.

“If you are not focused on efficiency, your routing can quickly overlap and become inefficient,” added Jason Hibbard, supervisor of transportation for the Chenango
Valley Central School District in Binghamton, New York.

“We focus on deadhead mileage. We are servicing multiple out-of-district locations. We constantly adjust routes to limit the time students are missing class time due to transportation and bell schedule conflicts.”

District data shows areas where a diesel bus could be run instead of gasoline to mitigate excessive brake use with the gas buses not having a supplemental exhaust brake, Hibbard said.

Meanwhile, Kathy Calkins, transportation director for North Clackamas School District in Oregon, said the district is using routing analytics to consolidate paths, eliminate excessive deadhead miles and ensure high bus capacity utilization.

Rich Casto, transportation supervisor at Jackson County Schools in West Virginia, agreed. He shared that analytics are playing a strong role in creating shorter,
better and smoother routes.

“When you’re looking at the ability to possibly combine a route without having that eagle’s eye view of mapping and routing with analytics, you really wouldn’t be able to see that without a lot of extra work,” he added.

Kacy L. Davis, Sr., the transportation director at St. Louis Public Schools in Missouri noted routing analytics are central to fuel efficiency “because every mile and every stop has a cost.” St. Louis provides student transportation through a partnership with Zum Services, using realtime GPS, telematics and routing analytics to reduce fuel use, improve route efficiency and enhance service reliability.

“This helps us eliminate outdated stops, reduce deadhead miles, tighten belltime coordination, and remove duplicated service areas which directly lowering fuel use
and operating costs,” said Davis.

Planned Versus Actual Routes
The gap between a planned route and the route a driver actually runs is one of the most underappreciated sources of cost in school transportation, noted Berndt.

Indian Prairie’s Johnson said a route may look flawless on a computer screen, but the divergence between the planned route and the actual path driven stems from
real-world variables.

“Construction zones, localized traffic, substitute drivers relying on historical workarounds, or dynamic student factors like missed stops all create a variance gap,” he said.

Johnson said his Onscreen GPS software allows his staff to review reports for when drivers deviate from the planned route path. Necessary adjustments can be made. St. Louis’ Davis said, “Zum’s platform shows us where buses deviate from planned routes due to construction, traffic, substitute drivers or outdated maps. When we see consistent patterns, we adjust routes, update turn-by-turn directions, and Zum coaches the drivers. This reduces unnecessary mileage without compromising safety.”

Hibbard in New York noted his district’s drivers are the ones on the road everyday. “We can sit in an office and use the best software available. However, when the driver hits the road, the route will not be perfect,” he said. “It takes constant work between the router and the driver to ensure the route is efficient. We use GPS regularly to ensure the driver is following the planned route to the best of their ability.”

West Virginia’s Casto noted it’s crucial to work with the vendors when changes and adjustments are needed. His district utilizes Zonar Systems. “For the most part, routes are routes. You have students and children in locations that you have to travel,” Casto said.

“But you can start to look at where you can combine the stops. Maybe you have another bus or an asset in an area that is a shorter distance to move those students over onto. “We’re in a rural area where you travel out further and deeper,” he continued. “Not all routes are interconnected through other side roads, so sometimes that’s not possible. But when you start to get into the more populated areas, then that’s where that plays in.”

Potholes in the Process
Road conditions also play a major role in fuel burning and maintenance cycles. “Zum’s telematics help us identify rough roads, steep grades and high stop-and-go
corridors that accelerate tire wear, brake cycles and suspension repairs,” Missouri’s Davis said. “Understanding these patterns allows us to reroute buses or collaborate with the city on infrastructure concerns.”

Road infrastructure and its impact on vehicle wear and tear is an area where telematics data can change how districts think about route assignments entirely,
Berndt at Geotab noted. Addressing road infrastructure and vehicle wear, Casto noted his district has examined that against the backdrop of being a rural school system.

“We travel a lot of back roads and secondary roads, so you have to take into consideration road conditions are not going to be what they would be in the inner-city area,” he said. “The biggest benefit of having that analytic option is to look at the route from a bird’s eye view and be able to see that there might a road that’s a little bit better and wouldn’t be as far for the parents to have to come if we have to move a route to stay on a better road.”

Hibbard said it is a daily focus of his staff to consider hills and brake usage, fuel efficiency, or just adjusting the route based on construction and/or traffic.

“When designing routes, we do our best to avoid certain problematic roads,” noted Calkins in Oregon. “However, student safety sometimes makes that unavoidable. To manage this, all buses undergo a comprehensive annual inspection, during which every component is thoroughly checked and maintained. This annual review is crucial, as it allows us to clearly evaluate the specific type of wear and tear each vehicle has experienced over the year.”

Understanding Idling Policies
Meanwhile, idling has a major compounding impact on fuel budgets, tailpipe emissions and public perception, especially when buses are queued near school zones and residential neighborhoods, noted Calkins.

“We address this through clear, enforced anti-idling policies [that are] communicated directly to our drivers during professional development and training,” she said.

“To uphold these standards, with our new tablets, we will utilize automated telematics system alerts. If a bus idles beyond a designated time threshold, notifications will be logged, allowing supervisors to review the data, follow up with the driver and ensure compliance. This strictly limits unnecessary fuel waste and protects air quality around our campuses.”

Chenango Valley Central School District follows New York state policy on not idling on school grounds unless it is excessively cold, Hibbard said.

Jackson County Schools has a 15-minute idling policy. “It’s not a real strict policy, but what having that available, is a conversation that you can have with the driver to point out here’s a place that we can make an improvement, here’s what that
over-idling costs the county in fuel costs. When you start putting those numbers on paper, you can sit down with a driver and look at that. It really hits home,” Casto said.

Vehicle idling is a compounding, costly and avoidable source of waste in school transportation, said Johnson, adding a typical school bus can burn up to a gallon of
fuel per hour while idling.

“Under Illinois statute, diesel school buses are generally restricted from idling for more than 10 minutes with a 15-minute exemption for passenger comfort,” Johnson said. “While running a bus for 15 minutes so a driver can sit in an air-conditioned cabin is a textbook violation, running that same bus to safely operate a wheelchair lift or to maintain a climate-controlled cabin for a student with severe thermoregulatory issues or a seizure disorder is a legally protected necessity.”

By using the district’s routing software to tag specific medical-necessity routes, the transportation department can filter out these legally exempt events from
its telematics reports, ensuring that driver coaching remains focused on actual waste rather than penalizing life-safety protocols, Johnson noted.

While routing analytics and idle reduction limit the physical volume of fuel burned, transportation directors must also optimize how that fuel is purchased, said Johnson.

“Transitioning from standard credit cards to a specialized government fleet fuel management program such as the WEX fuel card is a critical step in modernizing financial operations,” he added, noting additional benefits such as automating tax exemptions, capturing volume-based rebates, and providing security by utilizing driver PINS and odometer prompts.

Editor’s Note: As reprinted from the August 2026 issue of School Transportation News.

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Despite regional variability in climate, electricity sources, congestion, and the wide variation in individual driving patterns, electric vehicles generate less greenhouse gas emissions and do not cost more than comparable gas-powered vehicles for drivers and vehicle fleet owners in most parts of the United States, according to a new study by MIT researchers.

The team’s approach captures many key factors that contribute to regional and individual differences in the life-cycle emissions and ownership cost of electric vehicles, including meteorological data, the distance and duration of trips, and fuel prices.

To paint a fuller picture of emissions and costs than was previously available, the researchers sourced data from thousands of U.S. zip codes and drilled down to the level of individual drivers within those locations. Their study considers time-averaged fuel prices so as not to be overly influenced by fluctuations in prices at any one point in time. They finalized their analysis at the end of 2024 and early 2025.

Their results indicate that a person’s driving behaviors can matter as much as regional factors like the local electricity mix when it comes to the emissions savings of an electric vehicle, compared to a similar gas-powered vehicle. In most locations, a battery-electric vehicle reduces emissions between 40 and 60 percent, with larger impacts in urban areas. 

They also found that colder climates do not reduce overall emission benefits as much as some media reports assume.

The researchers utilized this detailed analysis to update a public tool they previously developed, carboncounter.com, which enables individuals to compare the life-cycle emissions and total ownership costs of nearly any car on the market. A new version of carboncounter.com is also being released today.

“There are a lot of statements being thrown around, like that electric vehicles don’t reduce emissions very much in cool climates, and we wanted to analyze these factors systematically and evaluate these statements against one another simultaneously. Rather than simply asking, ‘Are EVs better?’, this paper helps answer ‘better for whom, and under what conditions?’” says Marco Miotti PhD ’20, a senior researcher at ETH Zurich who completed this research while a graduate student in the Institute for Data, Systems, and Society (IDSS) at MIT. 

He is joined on the paper by senior author Jessika Trancik, a professor in IDSS. The research appears today in Environmental Research Letters.

A holistic approach

Many prior studies that compare emissions and costs of electric vehicles (EVs) to combustion-engine vehicles cover a few factors, like the amount of renewable energy in the grid and how gas prices impact affordability, Miotti says.

“To our knowledge, there have been few efforts so far that bring all these factors together. But if someone wants to buy a car and have a better understanding of the factors that affect emissions and costs, this holistic approach is important,” he adds.

The researchers focused on two types of EVs: battery-electric vehicles, which only operate on electricity, and plug-in hybrid electric vehicles, which also have a combustion engine that works in tandem with the battery to optimize fuel savings.

The team expanded and improved a set of previously developed vehicle cost and emissions models to incorporate a wider variety of factors and data types.

For instance, they refined an existing model that estimates energy use and gas mileage so it could capture more nuances of local climate variability. 

“But the real effort was not just in extending these different models, but in bringing together all these different data and making them work with the models in a consistent manner,” Miotti says.

The team sourced data on a wide variety of factors for each U.S. zip code, such as typical drive cycles, the amount of traffic, local gas and electricity prices, makeup of the regional electricity mix, meteorological profiles, and more. They used statistical approaches to amalgamate different types of data. 

For example, the team used a probabilistic matching technique to combine data on how often people drive, which was drawn from nationwide travel surveys, with more detailed GPS data that includes factors like drivers’ acceleration patterns and the distance they usually drive on each day of the week.

The researchers designed their analysis to focus on the spatial picture of emissions and costs, based on U.S. zip codes, while simultaneously considering the impact of the size and features of each specific vehicle model.

“At the end of the day, it’s the vehicle and fleet owners who make decisions about vehicle purchases. So, we wanted to make sure to consider their wide-ranging individual perspectives rather than simply performing a region-by-region comparison,” says Trancik.

Lower emissions, comparable costs

In the end, their modeling framework revealed that all factors they analyzed matter about equally in determining emissions-reduction potential of EVs compared to internal combustion vehicles. 

EVs reduce emissions the most in areas with a cleaner electricity mix, denser traffic, higher annual travel distances, and a mild climate, in decreasing order of importance. In each area, emission reductions increase for drivers who drive more often, drive larger vehicles, and are more frequently stuck in traffic. 

In a colder area like North Dakota, fuel economy of battery-electric vehicles might be reduced by as much as 50 percent on a particularly frigid night, but the effect on annual emission benefits is minimal. 

“We even did a sensitivity study to see if the range is reduced in very cold climates, and we found that, even in the most unfavorable conditions, EVs still reduce emissions by a substantial amount,” Miotti says.

On the cost side, the models show that, in most places across the U.S., EVs are competitive with comparable combustion-engine vehicles in terms of lifetime ownership cost, even without clean vehicle tax credits. And in areas where electricity is relatively affordable, battery-electric vehicles tend to cost less than their plug-in hybrid or combustion-engine counterparts.

In the future, the researchers want to expand this analysis to include a temporal dimension, so the framework also considers how changes in vehicle, fuel, and electricity prices affect emissions and costs over time. 

“While we found that the electricity mix is a big driver of the spatial variation in emissions savings of EVs, the electricity grid is decarbonizing everywhere. As that happens, emissions savings across space will become more homogenous for EVs, but the differences across one driver to another will remain,” Miotti says.

They could also use the framework to explore regions outside the United States or incorporate data on hybrid-electric vehicles that cannot be plugged in.

This work was funded, in part, by the MIT Martin Family Society of Fellows for Sustainability.

On May 6, MIT AgeLab’s Advanced Vehicle Technology (AVT) Consortium, part of the MIT Center for Transportation and Logistics, celebrated 10 years of its global academic-industry collaboration. AVT was founded with the aim of developing new data that contribute to automotive manufacturers, suppliers, and insurers’ real-world understanding of how drivers use and respond to increasingly sophisticated vehicle technologies, such as assistive and automated driving, while accelerating the applied insight needed to advance design and development. The celebration event brought together stakeholders from across the industry for a set of keynote addresses and panel discussions on critical topics significant to the industry and its future, including artificial intelligence, automotive technology, collision repair, consumer behavior, sustainability, vehicle safety policy, and global competitiveness.

Bryan Reimer, founder and co-director of the AVT Consortium, opened the event by remarking that over the decade AVT has collected hundreds of terabytes of data, presented and discussed research with its over 25 member organizations, supported members’ strategic and policy initiatives, published select outcomes, and built AVT into a global influencer with tremendous impact in the automotive industry. He noted that current opportunities and challenges for the industry include distracted driving, a lack of consumer trust and concerns around transparency in assistive and automated driving features, and high consumer expectations for vehicle technology, safety, and affordability. How will industry respond? Major players in attendance weighed in.

In a powerful exchange on vehicle safety regulation, John Bozzella, president and CEO of the Alliance for Automotive Innovation, and Mark Rosekind, former chief safety innovation officer of Zoox, former administrator of the National Highway Traffic Safety Administration, and former member of the National Transportation Safety Board, challenged industry and government to adopt a more strategic, data-driven, and collaborative approach to safety. They asserted that regulation must evolve alongside innovation, not lag behind it by decades. Appealing to the automakers in attendance, Bozzella cited the success of voluntary commitments on automatic emergency braking as a model for future progress. “That’s a way to do something important and impactful ahead of regulation.” They advocated for shared data platforms, anonymous reporting, and a common regulatory vision that sets safety baselines while allowing room for experimentation. The 40,000 annual road fatalities demand urgency — what’s needed is a move away from tactical fixes and toward a systemic safety strategy. “Safety delayed is safety denied,” Rosekind stated. “Tell me how you’re going to improve safety. Let’s be explicit.”

Drawing inspiration from aviation’s exemplary safety record, Kathy Abbott, chief scientific and technical advisor for the Federal Aviation Administration, pointed to a culture of rigorous regulation, continuous improvement, and cross-sectoral data sharing. Aviation’s model, built on highly trained personnel and strict predictability standards, contrasts sharply with the fragmented approach in the automotive industry. The keynote emphasized that a foundation of safety culture — one that recognizes that technological ability alone isn’t justification for deployment — must guide the auto industry forward. Just as aviation doesn’t equate absence of failure with success, vehicle safety must be measured holistically and proactively.

With assistive and automated driving top of mind in the industry, Pete Bigelow of Automotive News offered a pragmatic diagnosis. With companies like Ford and Volkswagen stepping back from full autonomy projects like Argo AI, the industry is now focused on Level 2 and 3 technologies, which refer to assisted and automated driving, respectively. Tesla, GM, and Mercedes are experimenting with subscription models for driver assistance systems, yet consumer confusion remains high. JD Power reports that many drivers do not grasp the differences between L2 and L2+, or whether these technologies offer safety or convenience features. Safety benefits have yet to manifest in reduced traffic deaths, which have risen by 20 percent since 2020. The recurring challenge: L3 systems demand that human drivers take over during technical difficulties, despite driver disengagement being their primary benefit, potentially worsening outcomes. Bigelow cited a quote from Bryan Reimer as one of the best he’s received in his career: “Level 3 systems are an engineer’s dream and a plaintiff attorney’s next yacht,” highlighting the legal and design complexity of systems that demand handoffs between machine and human.

In terms of the impact of AI on the automotive industry, Mauricio Muñoz, senior research engineer at AI Sweden, underscored that despite AI’s transformative potential, the automotive industry cannot rely on general AI megatrends to solve domain-specific challenges. While landmark achievements like AlphaFold demonstrate AI’s prowess, automotive applications require domain expertise, data sovereignty, and targeted collaboration. Energy constraints, data firewalls, and the high costs of AI infrastructure all pose limitations, making it critical that companies fund purpose-driven research that can reduce costs and improve implementation fidelity. Muñoz warned that while excitement abounds — with some predicting artificial superintelligence by 2028 — real progress demands organizational alignment and a deep understanding of the automotive context, not just computational power.

Turning the focus to consumers, a collision repair panel drawing Richard Billyeald from Thatcham Research, Hami Ebrahimi from Caliber Collision, and Mike Nelson from Nelson Law explored the unintended consequences of vehicle technology advances: spiraling repair costs, labor shortages, and a lack of repairability standards. Panelists warned that even minor repairs for advanced vehicles now require costly and complex sensor recalibrations — compounded by inconsistent manufacturer guidance and no clear consumer alerts when systems are out of calibration. The panel called for greater standardization, consumer education, and repair-friendly design. As insurance premiums climb and more people forgo insurance claims, the lack of coordination between automakers, regulators, and service providers threatens consumer safety and undermines trust. The group warned that until Level 2 systems function reliably and affordably, moving toward Level 3 autonomy is premature and risky.

While the repair panel emphasized today’s urgent challenges, other speakers looked to the future. Honda’s Ryan Harty, for example, highlighted the company’s aggressive push toward sustainability and safety. Honda aims for zero environmental impact and zero traffic fatalities, with plans to be 100 percent electric by 2040 and to lead in energy storage and clean power integration. The company has developed tools to coach young drivers and is investing in charging infrastructure, grid-aware battery usage, and green hydrogen storage. “What consumers buy in the market dictates what the manufacturers make,” Harty noted, underscoring the importance of aligning product strategy with user demand and environmental responsibility. He stressed that manufacturers can only decarbonize as fast as the industry allows, and emphasized the need to shift from cost-based to life-cycle-based product strategies.

Finally, a panel involving Laura Chace of ITS America, Jon Demerly of Qualcomm, Brad Stertz of Audi/VW Group, and Anant Thaker of Aptiv covered the near-, mid-, and long-term future of vehicle technology. Panelists emphasized that consumer expectations, infrastructure investment, and regulatory modernization must evolve together. Despite record bicycle fatality rates and persistent distracted driving, features like school bus detection and stop sign alerts remain underutilized due to skepticism and cost. Panelists stressed that we must design systems for proactive safety rather than reactive response. The slow integration of digital infrastructure — sensors, edge computing, data analytics — stems not only from technical hurdles, but procurement and policy challenges as well. 

Reimer concluded the event by urging industry leaders to re-center the consumer in all conversations — from affordability to maintenance and repair. With the rising costs of ownership, growing gaps in trust in technology, and misalignment between innovation and consumer value, the future of mobility depends on rebuilding trust and reshaping industry economics. He called for global collaboration, greater standardization, and transparent innovation that consumers can understand and afford. He highlighted that global competitiveness and public safety both hang in the balance. As Reimer noted, “success will come through partnerships” — between industry, academia, and government — that work toward shared investment, cultural change, and a collective willingness to prioritize the public good.

Car design is an iterative and proprietary process. Carmakers can spend several years on the design phase for a car, tweaking 3D forms in simulations before building out the most promising designs for physical testing. The details and specs of these tests, including the aerodynamics of a given car design, are typically not made public. Significant advances in performance, such as in fuel efficiency or electric vehicle range, can therefore be slow and siloed from company to company.

MIT engineers say that the search for better car designs can speed up exponentially with the use of generative artificial intelligence tools that can plow through huge amounts of data in seconds and find connections to generate a novel design. While such AI tools exist, the data they would need to learn from have not been available, at least in any sort of accessible, centralized form.

But now, the engineers have made just such a dataset available to the public for the first time. Dubbed DrivAerNet++, the dataset encompasses more than 8,000 car designs, which the engineers generated based on the most common types of cars in the world today. Each design is represented in 3D form and includes information on the car’s aerodynamics — the way air would flow around a given design, based on simulations of fluid dynamics that the group carried out for each design.

Each of the dataset’s 8,000 designs is available in several representations, such as mesh, point cloud, or a simple list of the design’s parameters and dimensions. As such, the dataset can be used by different AI models that are tuned to process data in a particular modality.

DrivAerNet++ is the largest open-source dataset for car aerodynamics that has been developed to date. The engineers envision it being used as an extensive library of realistic car designs, with detailed aerodynamics data that can be used to quickly train any AI model. These models can then just as quickly generate novel designs that could potentially lead to more fuel-efficient cars and electric vehicles with longer range, in a fraction of the time that it takes the automotive industry today.

“This dataset lays the foundation for the next generation of AI applications in engineering, promoting efficient design processes, cutting R&D costs, and driving advancements toward a more sustainable automotive future,” says Mohamed Elrefaie, a mechanical engineering graduate student at MIT.

Elrefaie and his colleagues will present a paper detailing the new dataset, and AI methods that could be applied to it, at the NeurIPS conference in December. His co-authors are Faez Ahmed, assistant professor of mechanical engineering at MIT, along with Angela Dai, associate professor of computer science at the Technical University of Munich, and Florin Marar of BETA CAE Systems.

Filling the data gap

Ahmed leads the Design Computation and Digital Engineering Lab (DeCoDE) at MIT, where his group explores ways in which AI and machine-learning tools can be used to enhance the design of complex engineering systems and products, including car technology.

“Often when designing a car, the forward process is so expensive that manufacturers can only tweak a car a little bit from one version to the next,” Ahmed says. “But if you have larger datasets where you know the performance of each design, now you can train machine-learning models to iterate fast so you are more likely to get a better design.”

And speed, particularly for advancing car technology, is particularly pressing now.

“This is the best time for accelerating car innovations, as automobiles are one of the largest polluters in the world, and the faster we can shave off that contribution, the more we can help the climate,” Elrefaie says.

In looking at the process of new car design, the researchers found that, while there are AI models that could crank through many car designs to generate optimal designs, the car data that is actually available is limited. Some researchers had previously assembled small datasets of simulated car designs, while car manufacturers rarely release the specs of the actual designs they explore, test, and ultimately manufacture.

The team sought to fill the data gap, particularly with respect to a car’s aerodynamics, which plays a key role in setting the range of an electric vehicle, and the fuel efficiency of an internal combustion engine. The challenge, they realized, was in assembling a dataset of thousands of car designs, each of which is physically accurate in their function and form, without the benefit of physically testing and measuring their performance.

To build a dataset of car designs with physically accurate representations of their aerodynamics, the researchers started with several baseline 3D models that were provided by Audi and BMW in 2014. These models represent three major categories of passenger cars: fastback (sedans with a sloped back end), notchback (sedans or coupes with a slight dip in their rear profile) and estateback (such as station wagons with more blunt, flat backs). The baseline models are thought to bridge the gap between simple designs and more complicated proprietary designs, and have been used by other groups as a starting point for exploring new car designs.

Library of cars

In their new study, the team applied a morphing operation to each of the baseline car models. This operation systematically made a slight change to each of 26 parameters in a given car design, such as its length, underbody features, windshield slope, and wheel tread, which it then labeled as a distinct car design, which was then added to the growing dataset. Meanwhile, the team ran an optimization algorithm to ensure that each new design was indeed distinct, and not a copy of an already-generated design. They then translated each 3D design into different modalities, such that a given design can be represented as a mesh, a point cloud, or a list of dimensions and specs.

The researchers also ran complex, computational fluid dynamics simulations to calculate how air would flow around each generated car design. In the end, this effort produced more than 8,000 distinct, physically accurate 3D car forms, encompassing the most common types of passenger cars on the road today.

To produce this comprehensive dataset, the researchers spent over 3 million CPU hours using the MIT SuperCloud, and generated 39 terabytes of data. (For comparison, it’s estimated that the entire printed collection of the Library of Congress would amount to about 10 terabytes of data.)

The engineers say that researchers can now use the dataset to train a particular AI model. For instance, an AI model could be trained on a part of the dataset to learn car configurations that have certain desirable aerodynamics. Within seconds, the model could then generate a new car design with optimized aerodynamics, based on what it has learned from the dataset’s thousands of physically accurate designs.

The researchers say the dataset could also be used for the inverse goal. For instance, after training an AI model on the dataset, designers could feed the model a specific car design and have it quickly estimate the design’s aerodynamics, which can then be used to compute the car’s potential fuel efficiency or electric range — all without carrying out expensive building and testing of a physical car.

“What this dataset allows you to do is train generative AI models to do things in seconds rather than hours,” Ahmed says. “These models can help lower fuel consumption for internal combustion vehicles and increase the range of electric cars — ultimately paving the way for more sustainable, environmentally friendly vehicles.”

“The dataset is very comprehensive and consists of a diverse set of modalities that are valuable to understand both styling and performance,” says Yanxia Zhang, a senior machine learning research scientist at Toyota Research Institute, who was not involved in the study.

This work was supported, in part, by the German Academic Exchange Service and the Department of Mechanical Engineering at MIT.