It has happened to virtually everyone at least once: You hear the sirens before you see the flashing lights. You know you need to stay out of the way, but you’re approaching an intersection, and the light’s about to change—which means you have nowhere to go. There’s certainly no room for an ambulance or fire truck to squeeze through. They can run red lights, but you can’t. It’s a nightmare scenario for emergency responders rushing to an urgent call. And it wastes precious minutes that can be the difference between life and death for someone going into cardiac arrest.
But what if artificial intelligence could change traffic lights so ambulances never get stuck?
Good news: It’s already happening. LYT (pronounced “light”), a California-based traffic tech company, has been revolutionizing the way first responders travel to emergency scenes. Founder and CEO Tim Menard likens the technology to air traffic control but for ground transportation. Alongside 911 dispatch centers, there’s a traffic room where people try to keep the city moving in real time to respond to emergencies.
“Imagine that stuff was just linked up directly, so that 911 call comes in, you know where it’s at, and all of a sudden the traffic lights can just change automatically,” Menard says. “That’s the magic over here—being able to take all these lessons learned from two to three decades… and now put them into one window with automation behind it, so that you can just clear routes.”
How it works
Whenever emergency vehicles are dispatched, the system automatically changes traffic lights so that emergency vehicles almost always get the green light, making it easier for other cars to move out of the way so ambulances, fire trucks and police cars can keep moving. The system both proactively changes lights based on anticipated arrival times of emergency vehicles and responds to the vehicle’s active location so it doesn’t get stuck with a string of red lights if there’s an unexpected delay.
Each locality can set its own rules for the system—say, for example, that ambulances get priority over police cars, and that there’s a hierarchy for different classes of emergency. Responding to a cardiac arrest would likely take priority over a vehicle that has picked up a patient whose life is not in immediate danger and is en route to the hospital. So far, LYT’s services have been enlisted by cities including Seattle; Boston; Toronto; Portland, Oregon; Tempe, Arizona; and several others across the U.S.
In Sacramento, California, Menard said response times improved by about 70% after partnering with LYT. By the end of this year, he said they’ll be working with nearly every major metropolitan area on the West Coast and getting started is pretty “plug and play for a city that has been investing itself.” While getting on board requires some staff training, compatible systems can be brought online the same day the municipality signs up for the service.
AI investments could save taxpayer money in the long run
LYT’s most obvious use case is for emergency vehicles, but the technology also works to help buses run more efficiently. And while that’s great for people riding the bus who don’t want to get stuck in traffic on their way to work, it’s also great for the rest of the city’s taxpayers—they can save untold thousands of dollars each year in fuel costs and staff overtime when everything runs as intended. Menard declined to share information about how much LYT services cost for a city to implement but shared that LYT partners across North America reduced their fuel costs by 14% in 2023.
As with emergency vehicles, the system is responsive. So, if a bus is delayed for some reason, such as to pick up a passenger who needs some extra assistance, the lights will be instructed not to wait for the bus and to allow traffic to move normally until the bus gets back on track.
The real-life trolley problem
The classic trolley problem often comes up in conversations about how AI could impact our future. The basic gist is this: You’re driving a trolley, and you see a group of five or six people on the tracks up ahead. You won’t be able to stop in time, but you can divert the trolley to a track where there’s just one person who’s in the way. Do nothing, and six people die. Pivot, and one person dies. Ethicists have debated the hypothetical scenario inside and out for years on end, but now we’re in a position where we have to tell AI what to do in such a scenario.
If you ask Menard, though, AI is likely to be a better—or at least fairer—arbiter of life-and-death decision-making than flawed humans might be.
“There’s physical bias that can build up in these systems, and that’s always something that’s curated and trimmed in a system like this,” he says. In other words: The system is unbiased. It doesn’t prioritize an ambulance responding to an event in a wealthy neighborhood over one responding to an event in a low-income area. Where humans might act with unconscious bias, AI can treat everyone equally.
“It’s all system-dependent on rule and logic,” Menard says.
A traffic-free utopia
The long-term vision, Menard says, is to create a society where AI essentially acts as air traffic control for ground transportation. In a future where vehicles are autonomous, people will walk out their front door and get picked up and taken where they want to go—with no gridlock, thanks to a smart, responsive traffic management system that’s completely automatic.
“This is actually a part of everyone’s, I would say, shared vision,” Menard says—a utopian vision, with autonomous vehicles. “Where you don’t own [a car]. It’s just like Uber or you subscribe to it, and even more so it’s totally integrated with your life. It knows your calendar and your schedule, and cars just show up and go.”
For now, LYT is the public sector’s answer to how to use big data in the environments we already have, Menard says.
“We can continue to use the city layouts and the environments that we have,” he says, “but use them to their best possible capacity.”
Photo by jpreat/Shutterstock.com
