Smarter Streets: How California Is Using AI and IoT to Reinvent Traffic

California’s traffic has long been infamous. Now, the state is leading the charge to fix the problem. Across cities like Los Angeles, San Francisco, and San Jose, agencies are deploying cutting-edge tech to reduce congestion, improve safety, and make commutes more predictable.

Fueled by real-time data from sensors, cameras, and connected vehicles, these systems are turning streets into smart, responsive networks. And this isn’t just about one state. What’s unfolding in California offers a glimpse into the future of urban mobility for cities everywhere. 

Let’s take a look at some of the key initiatives that are leveraging IoT and AI technology - and what they hold for the future of traffic control. 

Statewide and Multi-City Initiatives

With more than 52,000 lane miles in the state highway system, California has a lot of roads to cover. Here are some high-tech initiatives it’s using to better control traffic.

Caltrans Tackles One of the Nation’s Worst Traffic Corridors

LA traffic is legendary - for all the wrong reasons. To fight the gridlock, Caltrans and UC Berkeley’s PATH program rolled out an Integrated Corridor Management (ICM) pilot along a busy stretch of I-210 in Pasadena. Launched in 2020, the project combines IoT sensors and machine learning to monitor traffic in real-time and respond instantly to incidents.

Using high-speed simulations and predictive modeling, the system can quickly tweak signals, control the flow of vehicles entering the freeway via ramp meters, and come up with instant rerouting strategies when a crash or backup hits. While the full pilot results haven’t been made public, early modeling showed significant performance boosts during traffic incidents - hinting at the big potential for smarter, faster, cleaner commutes.

AI Traffic Cops Are Coming to California Streets

In a major shift, California greenlit its first automated speed camera program in 2023. Thanks to AB 645, six cities - including LA, San Francisco, and San Jose - can now deploy AI-powered speed enforcement in high-risk areas like school zones.

These smart cameras use machine vision to detect speeders and issue citations, with San Francisco already planning 33 cameras along its most dangerous corridors as part of its Vision Zero initiative. While statewide results are still to come, cities like New York have seen school-zone speeding drop by over 70% after similar rollouts.

The five-year pilot, running through 2032, will help California assess how AI can support safer, smarter streets.

Rethinking Green Lights with AI

California’s universities aren’t just studying traffic - they’re reprogramming it. At UC Berkeley, researchers created HumanLight, an AI system that uses reinforcement learning to optimize traffic signals based on how many people - not just cars - are moving through an intersection.

The AI rewards high-occupancy vehicles like buses and shuttles with more green time, cutting their travel times and nudging commuters toward shared rides. It’s a glimpse of what traffic could look like when signals prioritize efficiency and sustainability over vehicle volume.

The state government itself recognizes AI’s promise. In 2024, it called on tech companies to propose AI tools that could help California reduce traffic and make roads safer.

Los Angeles: Citywide Smart Traffic Control

Los Angeles has been a pioneer in smart traffic management, investing in connected infrastructure for decades. Let’s take a look at some of the initiatives happening in L.A.

LA’s OG Smart Traffic System Still Delivers

Long before “smart cities” were trending, Los Angeles launched ATSAC - its Automated Traffic Surveillance and Control system - for the 1984 Olympics. What started with 118 signals has now grown to a citywide network of over 4,850 adaptive traffic signals.

Powered by thousands of sensors and cameras, ATSAC adjusts signal timing on the fly based on real-time traffic flow. It’s one of the earliest large-scale examples of IoT-based traffic control - and it works. The system has slashed intersection delays by over 32% and cut vehicle emissions by about 3% across LA.

Smarter Signals, Faster Buses

Los Angeles doesn’t just use smart signals for cars - transit and emergency vehicles get special treatment too. Through ATSAC, buses, and Metro trains can get extra green lights when needed, shaving precious minutes off commute times.

The city also taps into data from connected vehicles and crowd-sourced apps like Waze to monitor traffic in real-time. 

Data-Driven Enforcement for Safer Streets

Los Angeles has long used red-light cameras to boost intersection safety. Now it’s stepping up its game. As part of California’s new speed camera pilot, LA will roll out automated enforcement in high-risk zones to crack down on dangerous speeding.

By layering crash data, smart signals, and AI-powered cameras, the city is turning its Vision Zero goals into action, and using tech not just to manage traffic, but to prevent collisions before they happen.

San Francisco: Smart Corridors and Automated Enforcement

San Francisco has embraced IoT and AI in both managing traffic flow and enforcing rules, often through federally supported smart city pilots. Let’s take a look at a few.

Mission Bay’s Smart Street Experiment

In 2021, San Francisco’s SFMTA launched a high-tech traffic pilot in Mission Bay, installing IoT and lidar sensors at 10 intersections along a single street. These sensors track vehicles, bikes, and pedestrians in real time - capturing speed, size, and direction multiple times per second.

The system then feeds that data into adaptive signal algorithms, allowing lights to adjust on the fly. Think longer greens for buses, or extra crosswalk time for slower pedestrians - without sacrificing flow on the corridor.

Serving a busy transit route, the pilot aimed to cut delays, boost safety, and make multimodal travel smoother. The results? A promising blueprint for scaling smart intersections across the city.

Cameras on Buses, Not Just Corners

San Francisco has been a pioneer in smart traffic enforcement. Beyond red-light cameras, the city launched an innovative program in 2008 that equips Muni buses with AI-assisted cameras to catch drivers blocking transit-only lanes.

The system snaps photos of violators’ plates and automatically sends out tickets - no officer required. It worked: transit lane violations dropped nearly 47% during the pilot, helping buses move faster and stay on schedule.

San Jose: AI for Safer Streets and Smoother Transit

San Jose, the largest city in Silicon Valley, has been actively integrating AI and IoT into its transportation systems with a focus on safety and transit efficiency. Here are a few key initiatives.

San Jose’s AI Eyes on the Street

In 2024, San Jose launched a next-gen traffic safety effort with help from a $260,000 grant from the Toyota Mobility Foundation. The goal? Use AI and computer vision to spot road hazards in real time - especially those that put pedestrians and cyclists at risk.

Still in its early stages, the program combines smart cameras with AI analytics to enable faster, more targeted responses to dangerous conditions. It’s a modern Vision Zero move, pairing safety with innovation while also exploring how to protect public privacy.

If it works, San Jose could set the standard for AI-powered hazard detection in cities across the country.

AI That Gives Buses the Green Light

San Jose is putting its “transit-first” policy into action with AI-powered signal priority. Working with tech partners, the city has equipped key corridors with a system that detects oncoming buses and adjusts traffic lights - holding greens or shortening reds to keep things moving.

The results are impressive: on routes with signal priority, bus travel times improved by over 50%, and VTA bus ridership jumped 15% in early 2024. Faster, more reliable service is proving to be a smart way to bring riders back on board.

Other Notable City Efforts in California

Several other California cities and regional agencies are implementing IoT and AI in traffic management on a smaller scale or in pilot stages:

Oakland’s Buses Get AI Backup

In August 2024, AC Transit rolled out AI-powered enforcement cameras on its buses to keep transit lanes clear. Built by Bay Area startup Hayden AI, the system auto-detects vehicles blocking bus stops or driving in bus-only lanes—no manual input needed.

The impact was immediate: in just six weeks, the AI flagged over 1,100 violations, leading to 787 citations - a massive leap from the 22 tickets issued with older tech over a similar period.

For Oakland and the East Bay, smarter enforcement is keeping buses moving and transit lanes free from freeloaders. 

Long Beach Gets Smarter - and Safer

Long Beach is stepping up its traffic tech with adaptive signals and automated speed enforcement. Along key routes like Pacific Coast Highway, the city has installed smart signal systems that adjust green lights based on real-time traffic—cutting congestion and keeping cars moving.

As one of six cities in California’s speed camera pilot, Long Beach also plans to target high-crash zones with AI-powered enforcement, pairing safer streets with smarter infrastructure.

Glendale’s Road to Safer Streets

Glendale is turning to data and enforcement tech to curb rising collisions. As part of California’s speed camera pilot, the city plans to install automated cameras near schools and high-speed corridors.

Glendale has also upgraded its traffic signals for centralized control and added intersection cameras for real-time monitoring. While its system isn’t as advanced as LA’s, the city’s Traffic Management Center uses live IoT data to manually adjust signals during events or disruptions.

With grant applications for AI-powered signal systems and participation in LA County’s regional data-sharing network, Glendale is laying the groundwork for a smarter, safer traffic future.

The Road Ahead

From cloud-connected traffic lights to AI-powered enforcement, California is proving that smarter streets aren’t just possible - they’re already here. , while this could mean more speeding tickets for drivers, it could also mean safer roads. And, as cities test and scale these innovations, the lessons learned could shape how communities everywhere rethink congestion, safety, and mobility.