U.S. congestion rose in 2025, but NYC held steady. Here’s how AI, congestion pricing, and green traffic tech can cut gridlock, emissions, and costs for cities.
Why U.S. Traffic Got Worse — Except in New York
Drivers in the U.S. lost 49 hours to congestion in 2025, up from 43 hours the year before. That’s more than a full workweek burned in traffic for the “average” driver.
The surprise isn’t that congestion grew. The surprise is where it didn’t. While Chicago took the top spot as the most congested city, New York City held the line on traffic delays — and that’s after launching congestion pricing and putting serious data and AI behind its transport strategy.
This matters because transportation is one of the biggest levers cities have for climate action. Gridlock isn’t just annoying. It’s wasted fuel, higher emissions, worse air quality, and lost productivity. The flip side: when cities use green technology and AI to manage traffic, they don’t just move cars faster — they move their climate goals faster too.
Here’s the thing about congestion right now: it’s growing faster than our ability to build our way out of it. That’s exactly why smart cities are shifting from more asphalt to more intelligence.
In this post, I’ll break down:
- What INRIX’s 2025 traffic data really says about U.S. cities
- Why New York’s congestion story is a blueprint for green mobility
- How AI traffic signals, predictive data, and pricing can cut both delays and emissions
- Practical steps cities and mobility leaders can take in 2026
What the 2025 Congestion Numbers Really Tell Us
The INRIX Global Traffic Scorecard paints a clear picture: demand is back, infrastructure isn’t ready, and the climate cost is rising.
Key numbers from the 2025 scorecard
- Chicago is now the most congested U.S. city
- The typical U.S. driver lost 49 hours in traffic (up from 43 hours)
- Baltimore and Philadelphia both saw 31% jumps in delays, driven by infrastructure disruptions and transit constraints
- New York City held steady on congestion, despite heavy demand
INRIX analyst Bob Pishue summed it up well: traffic is “growing right along with our infrastructure needs,” and most new spending is just catching up to today’s volumes, not preparing for tomorrow.
From a green technology lens, that’s a critical point:
Building more roads without changing how we manage demand is like buying bigger hard drives without fixing your data pipeline.
You might “solve” the problem for a moment, but the underlying pattern stays broken.
Why this matters for sustainability
When congestion rises:
- Fuel consumption goes up: stop‑and‑go conditions burn more fuel than steady flows
- Per‑trip emissions rise: vehicles spend more time idling and accelerating
- Mode shift suffers: unreliable roads and transit push people back to private cars
- Public pressure builds for short-term fixes instead of long-term, sustainable plans
If your city or organization has net-zero or decarbonization goals, you can’t ignore those 49 hours. They’re baked into your emissions inventory whether you measure them or not.
Why New York Didn’t Get Worse: A Quiet Congestion Pricing Case Study
New York City is the outlier in this story: no increase in congestion, even though demand is high and the metro area is massive.
INRIX data shows that five NYC corridors were in the top 25 busiest in 2024, but only one remained in 2025. Pishue is blunt about why:
“The congestion pricing program, no doubt, played a role.”
What congestion pricing actually does
Congestion pricing is simple in concept: charge vehicles to enter or drive in the busiest areas at the busiest times. Done well, it:
- Reduces unnecessary car trips into core zones
- Encourages mode shift to transit, biking, walking, and shared mobility
- Smooths peaks, improving average speeds and reducing idling
- Generates dedicated revenue for transit and sustainable mobility projects
From a green technology perspective, it’s one of the cleanest examples of pricing in externalities — making drivers pay for the space, pollution, and delay their trips impose on everyone else.
Why NYC’s experience matters for other cities
Most cities hesitate on congestion pricing because it’s politically hard. But the New York data suggests three things:
- It’s measurable. INRIX data captured the drop in “top 25 busiest corridors” year over year.
- It works without waiting for huge infrastructure builds. Pricing is software and policy, not a 10‑year construction project.
- It pairs naturally with green investments. Pricing revenue can fund zero-emission buses, bike networks, and transit electrification.
If you’re working on a mobility or climate roadmap for 2026, congestion pricing isn’t just a traffic tool — it’s a demand management and funding engine that makes other green technologies viable at scale.
When Infrastructure Fails: Baltimore and Philadelphia as Warning Signals
Baltimore and Philadelphia show the other side of the equation: what happens when infrastructure breaks or transit is constrained, and you don’t have enough smart, flexible systems to absorb the shock.
- In Baltimore, the collapse of the Francis Scott Key Bridge cut a major four-lane artery.
- In Philadelphia, the Federal Railroad Administration ordered inspections of 223 rail cars after onboard fires, forcing cuts to train service.
The result in both cases: about a 31% jump in traffic delays.
What these disruptions teach smart cities
You can’t predict exactly which bridge will fail or which rolling stock will get sidelined. But you can build a transportation system that’s:
- Data-rich: real-time understanding of flows across modes
- Mode-flexible: able to shift demand across transit, shared mobility, and active modes
- Signal-aware: using AI traffic signals and dynamic timing to re-balance corridors fast
- Communications-strong: informing travelers in real time so behavior can adapt
INRIX’s Ahmed Darrat calls the system “incredibly complex,” which is true — but complexity is exactly what AI and predictive data are good at managing.
Resilience is a climate issue as well: when systems fail and drivers are stuck in backups for months, emissions spike and trust erodes, making long-term sustainability investments harder to sell.
How AI and Green Technology Are Reshaping Urban Traffic
Cities that are serious about both congestion and climate are increasingly turning to AI, predictive data, and green infrastructure instead of defaulting to more lanes.
AI-based traffic signals: small boxes, big impact
States like North Carolina are already installing thousands of AI-based traffic signals. These systems:
- Analyze live traffic flows from sensors and cameras
- Adjust red/green times in real time to keep platoons moving
- Coordinate multiple intersections along a corridor
- Prioritize transit vehicles or emergency responders when needed
From a sustainability point of view, AI signals are one of the highest-ROI tools available:
- Less idling → lower CO₂ and NOx
- Smoother speeds → better fuel economy for all vehicles
- More predictable travel times → easier to shift trips to off-peak or to transit
I’ve seen mid-sized cities cut delay on key corridors by 20–30% using coordinated, adaptive signals alone. That’s not a silver bullet, but it’s a big win that doesn’t require adding a single new car lane.
Predictive data: solving tomorrow’s jam today
Another fast-maturing area is predictive traffic and safety analytics. With the right data sets:
- Planners can spot corridors that are trending toward recurring congestion before they hit crisis levels
- Agencies can forecast the impact of an event, like a lane closure or stadium game, and adjust plans and messaging
- Safety teams can identify high-risk segments where a small design or signal change would prevent crashes
As Pishue puts it,
With the right data sets, you can start making decisions earlier and get that out to the public.
That’s exactly what green technology in transport should do: move decisions upstream, where they’re cheaper, faster, and lower-carbon.
Multi-modal optimization: cars aren’t the only variable
A recurring blind spot in traditional traffic management is focusing on car throughput alone. Darrat’s reminder is spot on: people now have many transportation options — ride-hailing, robotaxis, buses, micromobility, biking, and walking.
AI-based tools can:
- Optimize signals to reduce delay for zero-emission buses instead of single-occupancy vehicles
- Identify corridors where protected bike lanes would absorb car trips most effectively
- Reveal first/last-mile gaps that keep people from using high-capacity transit
If you’re evaluating green technology, the best question isn’t, “Will this move cars faster?” but, “Will this move people more efficiently and with lower emissions?”
Practical Moves for Cities and Mobility Leaders in 2026
If you’re responsible for transport, climate, or urban planning, there’s a clear pattern forming from the INRIX data and recent city moves.
Here’s a concrete playbook.
1. Treat congestion as a climate and data problem
Don’t silo congestion in a “traffic ops” corner. Make it a joint responsibility between:
- Transportation operations
- Sustainability / climate teams
- Transit agencies
- Data / IT teams
Align KPIs around both delay reduction and emissions reduction, not one or the other.
2. Start with high-ROI smart infrastructure
If budgets are tight, prioritize:
- Adaptive, AI-driven signal control on your worst congested corridors
- Centralized data platforms that integrate road, transit, and micromobility data
- Open APIs so startups and researchers can build useful tools on top
You’ll see measurable benefits in months, not years.
3. Build toward demand management, not just supply
Use the NYC story as a reference point:
- Begin with time-of-day pricing pilots on bridges, tunnels, or key corridors
- Pair them with transit improvements and equity protections (discounts, exemptions)
- Use INRIX-style scorecards and dashboards to show the public what’s changing: less delay, better air, more reliable buses
Demand management is where the climate math really starts to move.
4. Design for resilience and redundancy
Baltimore and Philadelphia highlight how brittle systems can be. Build plans that assume:
- A bridge will close
- A rail fleet will be pulled for inspection
- A weather event will disrupt major routes
Then:
- Use predictive modeling to pre-define detour signal plans
- Map alternate routes for buses and freight
- Pre‑script public communication and wayfinding strategies
Resilient networks are both greener and more politically durable because they fail less catastrophically.
5. Bring the public into the data story
Public support is the quiet success factor behind most green technology in cities. Share:
- Before/after congestion heatmaps
- Emissions estimates for major corridors
- Travel time reliability improvements for transit and freight
When residents and businesses can see that their 10 minutes saved per trip also means less pollution in their neighborhood, support for bolder steps grows.
Where Green Traffic Technology Goes Next
The INRIX 2025 scorecard doesn’t just rank cities; it shows a fork in the road.
One direction is obvious: more vehicles, more delays, more emissions, and more reactive spending to “catch up” to today. The other direction is what New York and AI-forward states are starting to show: manage demand, use data intelligently, and let green technology stretch the capacity of what you already have.
For anyone building smart city strategies or green mobility products, this is the moment to be bold. Congestion pricing, AI traffic signals, and predictive analytics aren’t futuristic anymore — they’re deployed, measurable, and politically survivable when you bring the public along.
If your city or organization is ready to:
- Cut congestion without carving new highways
- Turn traffic data into climate progress
- Use AI and green technology to move people, not just cars
then your next step is straightforward: pick one corridor, one district, or one policy lever and prove it. The data from 2025 is clear enough — congestion won’t fix itself. But with the right tools, it can become one of your most powerful climate allies.