US drivers lost 49 hours to traffic in 2025. Here’s how congestion pricing, AI traffic signals, and smart mobility can cut gridlock, emissions, and costs.
Most U.S. drivers lost about 49 hours to traffic in 2025. That’s more than a full workweek burned in gridlock — with engines idling, emissions climbing, and tempers flaring.
Yet one of the most traffic‑choked places on earth, New York City, managed to keep congestion from getting worse this year while cities like Chicago, Baltimore, and Philadelphia all saw big jumps. That contrast tells you something important: congestion isn’t inevitable. It’s a policy and technology choice.
This matters because transportation is one of the biggest levers we’ve got for green technology, climate action, and cleaner air. When cities use tools like AI-based traffic signals, congestion pricing, and predictive analytics, they don’t just move cars faster — they cut fuel use, reduce CO₂, and make streets more livable.
In this post, I’ll break down what’s happening with U.S. congestion, why New York bucked the trend, and how cities and businesses can use smart, green tech to get ahead of the problem instead of constantly chasing it.
Congestion is rising — but it doesn’t have to
Traffic delays are growing across U.S. cities. According to INRIX’s 2025 Global Traffic Scorecard, the typical U.S. driver lost 49 hours to congestion this year, up from 43 hours in 2024. Chicago replaced New York City as the most congested U.S. metro, and cities like Baltimore and Philadelphia saw delays jump by 31%.
Here’s the thing about congestion: it tends to grow faster than infrastructure. As INRIX analyst Bob Pishue put it, most new road building is just to catch up to current demand, not to change the underlying pattern. If you keep adding lanes without changing behavior, you get a few years of relief and then… you’re right back where you started.
From a green technology perspective, that pattern is a red flag:
- More congestion means more idle time, and idle time is pure waste: fuel burned, emissions up, productivity down.
- Longer delays nudge people away from transit and active modes, reinforcing car dependence.
- Billions in road expansion lock cities into high‑carbon infrastructure instead of funding smart mobility and clean transit.
The reality? Traditional “build more lanes” thinking is expensive, slow, and environmentally backwards. Cities that are serious about climate and air quality are shifting toward data‑driven traffic management and demand management instead.
Why NYC held the line while others slipped
New York City is still one of the most congested places in the country, but there’s a crucial nuance: its congestion didn’t increase this year, even as the national average climbed and Chicago took the top spot.
Congestion pricing as a climate and traffic tool
One big factor is congestion pricing. While the specifics evolve, the basic idea is simple: charge vehicles to enter and drive in the most crowded core at peak times, then reinvest that revenue into better transit and safer streets.
For green technology and sustainable mobility, congestion pricing is powerful because it:
- Reduces car trips into the most polluted, congested areas
- Smooths demand across time, flattening the worst rush hours
- Funds alternatives like electric buses, subways, and cycling infrastructure
In the INRIX data, New York went from having five of the top 25 busiest road corridors in 2024 to only one in 2025. That’s not an accident. Congestion pricing directly changes behavior: some drivers shift to transit, others change their trip times, some decide not to drive at all.
I’ve found this is where many cities hesitate — pricing sounds politically risky. But the New York story suggests something important: modest behavior change at scale is enough to stabilize congestion, and that’s already a big win for emissions and air quality.
Contrast: Baltimore and Philadelphia’s sudden spikes
Baltimore and Philadelphia show the other side of the story: how fragile urban mobility can be without smart tools.
- Baltimore lost the four‑lane Francis Scott Key Bridge after a cargo ship collision and collapse. That wasn’t just a tragic event; it removed a critical artery, forcing traffic onto smaller roads and longer detours.
- Philadelphia saw train service cut while 223 rail cars underwent safety inspections after onboard fires. Commuters who normally rode rail pivoted to driving, instantly overloading road networks.
Both cities ran into the same core problem: when a single link fails, the rest of the system has no slack. Without predictive traffic management, adaptive signals, or strong non‑car options, delays spike fast.
For green technology advocates, these cases are a warning and an opportunity. Climate disruption and infrastructure shocks are going to happen. Cities that invest now in resilient, AI‑supported traffic systems will ride out the next disruption far better than those that rely on static timing plans and wishful thinking.
How AI-based traffic management cuts congestion and emissions
AI‑based traffic signals and predictive analytics are no longer pilot‑project novelties. They’re becoming core infrastructure in states like North Carolina, which has installed around 2,500 AI traffic signals to adapt in real time.
At a high level, the value is straightforward: AI reduces stop‑and‑go driving, and that’s where a lot of fuel and emissions are wasted.
What AI traffic signals actually do
AI‑driven signal systems use sensors, cameras, and historical data to:
- Detect queues and adjust green time dynamically
- Coordinate signals along a corridor to form “green waves”
- Respond to disruptions (crashes, events, weather) faster than humans can
- Prioritize transit vehicles or emergency services when needed
For drivers, that means fewer starts and stops, smoother travel times, and less sitting with the engine running. For cities focused on green technology, it means:
- Lower fuel consumption across thousands of vehicles
- Reduced CO₂ and NOx emissions from idling
- Better performance from electric fleets (since stop‑and‑go drains range)
I’m blunt on this: every medium‑to‑large city that isn’t already planning an AI‑based traffic signal upgrade is leaving congestion relief and emissions cuts on the table.
Predictive data: from reactive to proactive
The other big shift is from reactive management (“the highway is jammed, send a message”) to predictive operations.
Using historical congestion data, weather, event calendars, and even incident patterns, cities can:
- Forecast where and when congestion will spike
- Adjust signal timing or ramp metering before the crush hits
- Push early warnings to drivers and transit riders
- Schedule maintenance and work zones for low‑impact periods
As INRIX’s analysts point out, the right data sets let agencies make earlier decisions and, crucially, communicate them. Public buy‑in is easier when people see that the city is consistently one step ahead of traffic instead of scrambling to catch up.
Rethinking mobility: cars, transit, robotaxis, and more
Modern urban transportation isn’t just private cars vs. buses. Ahmed Darrat, INRIX’s Chief Product Officer, highlighted how complex the system is now: ride‑hailing, robotaxis, micro‑mobility, public transit, biking, and walking are all overlapping.
For congestion and emissions, that complexity can be an asset or a mess. It depends entirely on whether cities are integrating these modes intentionally.
Why mode mix is a climate strategy, not a side issue
If your goal is less congestion and lower emissions, mode shift is non‑negotiable:
- Shifting even 5–10% of peak‑hour car trips to transit, cycling, or walking can keep a corridor from tipping into gridlock.
- Well‑integrated ride‑hailing and robotaxis can complement transit, but unmanaged they often add empty miles and induce trips.
- Safe, continuous bike and pedestrian networks are cheap compared to highways and carry a lot of short trips that otherwise clog roads.
From a green technology standpoint, the smartest moves combine digital tools and physical design:
- Use real‑time data and apps to show people the fastest low‑carbon route (e.g., subway + scooter instead of a solo car trip).
- Coordinate pricing so that driving and parking reflect their true cost, while transit and shared modes are more attractive.
- Feed robotaxis and on‑demand shuttles into transit hubs instead of duplicating busy bus and rail corridors.
Cities that treat every mode as a separate silo will keep fighting congestion on ten fronts at once. Cities that analyze how all modes interact can design a system where cars are just one option, not the default.
Practical steps for cities and mobility leaders
Most cities and transport agencies already know congestion is a problem. The question is what to prioritize next. Here’s a practical roadmap grounded in the trends above.
1. Start with the data you already have
You don’t need a moonshot to begin:
- Use existing traffic counts, GPS data, and transit ridership to identify top 10 delay hotspots.
- Compare patterns by time of day and day of week to spot predictable peaks.
- Overlay crash data to find locations where safety and congestion overlap — these are high‑value intervention sites.
Once you’ve got this baseline, tools like the INRIX scorecard become a springboard, not just a report. You can target investments instead of guessing.
2. Modernize signals where the pain is greatest
If you’re constrained on budget (who isn’t?), focus AI‑based signals and adaptive control on:
- Key arterials that feed downtowns and major job centers
- Corridors that consistently show high delay per mile
- Routes that carry a mix of freight, transit, and commuters
Measure results in travel time, fuel savings, and emissions, not just level of service. That framing helps build support from environmental and public health stakeholders, not just drivers.
3. Pair pricing and tech with visible benefits
Policies like congestion pricing, low‑emission zones, or curb fees work best when people see where the money goes.
- Commit a clear share of revenue to transit upgrades, bike lanes, and safer crossings.
- Use real‑time dashboards to show how delays and emissions change over time.
- Communicate early and often — drivers will tolerate change if they see shorter trips and better options.
The political lesson from New York and other congestion pricing cities is simple: transparency plus tangible benefits beats vague promises every time.
4. Build cross‑department teams around mobility and climate
Traffic engineers can’t do this alone. The most effective green mobility work happens when:
- Transportation, climate, and public health staff share data and goals
- IT teams support robust, secure data platforms for traffic and transit
- Economic development understands how less congestion and cleaner air boost competitiveness
If you’re a mobility tech vendor or consultant, this is exactly where you can add value: helping cities connect the dots between operations, emissions, and quality of life.
Where congestion meets the future of green technology
Urban congestion in 2025 isn’t just a headache — it’s a live test of whether cities will embrace smart, low‑carbon mobility or double down on 20th‑century road expansion.
The contrast is already clear:
- Chicago, Baltimore, and Philadelphia show how quickly delays can spike when infrastructure is brittle and systems are mostly reactive.
- New York, for all its flaws, shows that pricing, data, and strong transit can at least keep congestion from getting worse even as travel demand grows.
For anyone working in green technology — from AI traffic platforms to EV fleets and mobility‑as‑a‑service — this isn’t a side topic. It’s the front line. The tools you’re building can directly decide whether the next five years look like 49 hours of delay per driver… or a lot less.
If your city or organization is still stuck in a “more lanes, same thinking” mindset, now’s the moment to push for a smarter approach: congestion pricing where it fits, AI‑based signals, predictive data, and a serious push toward cleaner, shared modes.
The future of urban mobility will be data‑driven either way. The question is whether that data is used to manage congestion and emissions on purpose, or just to measure how bad things have become.