Artificial intelligence used to reduce traffic jams | News

VSConsistently ranked as one of the worst cities for traffic in the United States, traffic congestion in Los Angeles has continued to climb back to pre-pandemic levels. To combat the inefficiencies that lead to increased traffic levels, cloud-based software platform Lyt has used artificial intelligence and machine learning technologies to help improve vehicle flow.

“There are so many different flavors of AI and machine learning, and that’s the future,” said Bobby Lee, chief marketing officer at Lyt. “What’s really exciting about what we’re doing here at Lyt is that we’re tackling the central nerve of what’s going to improve mobility, reduce congestion and get people where they want to go.”

To accomplish its mission, Lyt uses AI and machine learning to optimize traffic lights. The technology works by installing a unique edge device in a city’s traffic management center that allows vehicles to communicate with each networked traffic light on the Lyt platform.

For example, an emergency vehicle that needs to arrive at its destination in their city might have a clear route because the city’s traffic light cloud network might clear a path. Lee explained that emergency vehicle preemption and transit signal priority technology originated in the 1950s as a hardware solution, but speed limits and travel habits have changed over the past 70 years. years.

“We are taking a cloud-based software approach to solving this problem,” Lee said. “Instead of installing all these pieces of hardware, hoping we can close the intersection, waiting for the light to turn green…we’re saying, ‘Wait a second, let’s back up here. Let’s take a 10,000 foot view of the city. Let’s look at this whole hallway. Let’s look at everything that’s happening in context and apply machine learning to what’s happening.

“With emergency vehicles, your fire station could be across town. It could be four or five miles to get to a heart attack, or to get to a three-alarm fire. We want to make sure these vehicles can get there immediately, which means clearing the entire path of traffic. … We’re the cloud system, the software, the machine learning that sits above the city and sees what’s going on, and we can provide the information to the city and their signals so they can take the right decisions on how to optimize traffic lights.”

In the Rancho Cordova suburb of Sacramento, Lyt deployed its emergency vehicle preemption solution to address traffic challenges posed by the community’s location above the gore point of I-80 and Highway 50, which comes out of Lake Tahoe. Traffic in Rancho Cordova had gotten so bad that city engineers had to manually turn traffic lights to green one afternoon to help emergency vehicles cross the roadway.

After deployment, Lyt’s system was able to increase fire truck speeds by 69% and response times were reduced by an average of 42 seconds.

“With cardiac events like a heart attack, every minute reduces your chance of survival by 10%, so 42 seconds is important,” Lee said. “We were able to start in just a few weeks, and all we needed was the green light to move forward from the city. So for this software, the advantage is that once the city approves it, we get there very, very quickly, and we can provide those immediate benefits to the community. And we’ve heard anecdotally of residents calling, when they were testing the system on and off, and they noticed the difference. »

Lee said the same model works for transit vehicles, such as buses, by studying ridership patterns and routes. A signal could be sent from a bus to inform the nearest traffic light on the route of its presence.

“(Bus riders) want reliability,” Lee explained. “They want frequency, so good service every 10 minutes, every 15 minutes. And they want to know if it will get them where they want to go when they need it. With a system like this, a solution like this, it’s really going to help the agency resell that to riders.

Lee cited the example of Lyt’s work in a “mixed-use, transit-dependent” neighborhood in San Jose, where the community relies heavily on travel on Route 77, a north-south corridor. Lyt’s team installed their AI-powered priority signals at 17 intersections and created a web portal that showed the actual location and activity of the Santa Clara Valley Transportation Authority Bus Team, including their routes, speeds and upcoming stops.

After installation, residents’ travel time decreased by 20% and the Santa Clara Valley Transportation Authority’s diesel consumption was reduced by 14%.

“You have a win-win here, which is shorter commute times to get people between work, home and school, the transit agency saving on diesel, and a community breathing less of those harmful particles,” Lee said. “We also deployed one of our large transit deployments, actually, in Portland. We are on a new expressway…I believe there are about 60 intersections. They go from downtown Portland all the way to the suburbs, the eastern suburbs. (That’s) about 10,000 runners a day. … From our presence in the field and from our partners, our agency partners, we’ve seen a dramatic improvement in speeds, reliability, and timeliness up there.

Lee insisted that Lyt’s model would be successful in downtown Los Angeles because dense urban centers contain a large user base and require a high frequency of connectivity between users and their destinations. By encouraging DTLA residents to use public transportation, Lyt could reduce traffic because fewer vehicles would be on the roads.

“If you are able to demonstrate to these users that each of these lines crossing the city centre, through the connected corridors, that they receive these priority green lights and that they benefit from excellent journey times and great speeds, and by getting them home, to work or to school as quickly as possible, they will want to switch modes, i.e. abandon their car or abandon other modes of transport and take the bus.

“Every transit agency across the country has seen a drop in ridership, and we have seen this reverse effect in the use of private vehicles on the roadway, with traffic returning to 95-100% of what it was before COVID. So the only way to get out of this congestion situation is to offer an attractive alternative, which is to encourage people to take public transit again.

According to reports, the average American driver spent more than 50 hours, nearly one hour per week, in traffic in 2022. While Lyt’s solutions currently focus on emergency and transit vehicles, Lee said the technology is applicable to all classes of vehicles.

“It’s a really fascinating approach that this industry, which is used to expensive hardware…they have a different approach,” he explained. “We believe that many communities here in California and beyond can really be helped by Lyt and our solutions.”

The core of Lyt’s mission is to provide faster, more reliable journeys through more efficient and environmentally friendly methods of travel, without the need to build infrastructure or install hardware replacements. . Lee explained that the traffic light is the “only controlled device on the roadway”, so tackling its signal is the best starting point to find solutions to congestion that will affect the entire traffic network. mobility of a city.

“It’s a technology that, of course, consumers don’t buy directly from, but that every community should be looking at,” Lee explained. “The power of cloud computing, the power of AI and machine learning can be applied in many different ways, and this is just one solid example of how it can really change the way we move .

“We think that’s what’s going to really drive things forward over the next 10, 20 plus years in helping us move. … Really, the sky’s the limit.

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