Cameras were first installed on the windshields of some Metro buses last year, but the first tickets were issued in mid-February. Initially, the only buses to have cameras were along line 212, from Hollywood/Vine to Hawthorne/Lennox stations via La Brea Avenue, and line 720, from Santa Monica to downtown L.A. via Wilshire Boulevard. Line 70, which services Olive Street and Grand Avenue, and lines 910 and 950 that serve Metro's J Line have since been included. The AI-powered cameras scan for illegally parked cars and compile a video of each violation, a photo of the license plate and the time and location, according to the Los Angeles County Metropolitan Transportation Authority. Each citation is reviewed by a human.

Artificial intelligence-powered cameras are being installed on Los Angeles Metro buses to help ticket cars parked in bus lanes. Testing is planned for this summer and the program is expected to go live by the end of 2024, Metro said, after two months of community outreach to "ensure that the public is aware of the purpose, timing and impacts of this new program." "Once cameras are installed, there will be a 60-day warning period for drivers. During the first 60 days, warning citations will only be used as informational notices and will not result in any violations," the agency said. The program, designed by technology company Hayden AI, is meant to improve bus times, increase ridership and address mobility concerns.

Public transport forms the backbone of any urban mobility system, enabling cities to be more dynamic and competitive while creating more jobs. However, most cities' public bus systems are hemorrhaging riders in recent years due to slow speeds compared to options such as ridesharing services. Not to mention the continuously rising threats of transit agency budget cuts, traffic congestion and public safety. Hayden AI – a company creating smart city solutions purposely built for modern traffic conditions and increased urbanization – asking the question, What can we do to reverse this? The answer isn't bulking up on traffic enforcement, but rather, to enable smarter, more scalable enforcement.

That lawsuit is currently under appeal, but Bell is undeterred. He's expanded his scope to include bus lanes, which, like bike lanes, often play host to vehicles that are not buses. Buses, Bell says, are a less polarizing issue than bikes. Bus ridership has plummeted in New York and route speeds are slowing to a glacial pace. "We should all be able to get behind the bus issue," Bell tells Fast Company.

A savvy computer scientist has developed an algorithm to figure out just how bad New York City's bike lanes really are. Using machine learning, New Yorker Alex Bell discovered precisely how often parked cars, delivery trucks and waiting cabs are guilty of illegally blocking the city's bike lanes and bus routes, according to the New York Times. The results showed that it's not just disgruntled bikers and bus drivers imagining the problem -- New York City's cycling and bus lanes are routinely obstructed. Using machine learning, Alex Bell discovered precisely how often parked cars, delivery trucks and waiting cabs are guilty of illegally blocking the city's bike lanes and bus routes Bell trained the algorithm with about 2,000 images of buses, cars and trucks to differentiate between vehicles that were allowed to idle there legally and those that weren't. Specifically, he collected 10 days worth of publicly available footage from a traffic camera in Harlem fixed on one city block.

Alex Bell hates it when the designated bike lane he is pedaling down is blocked. So, too, do many cycling New Yorkers. But Mr. Bell hates it so much that he has tried to do something about it: Three years ago he sued U.P.S., targeting the delivery company's trucks for blocking his bike path, a case he lost that is in its second round of appeals. Now Mr. Bell is trying another tack -- the 30-year-old computer scientist who lives in Harlem has created a prototype of a machine-learning algorithm that studies footage from a traffic camera and tracks precisely how often bike lanes are obstructed by delivery trucks, parked cars and waiting cabs, among other scofflaws. It is a piece of data that transportation advocates said is missing in the largely anecdotal discussion of how well the city's bus and bike lanes do or do not work.

Alex Bell likes to bike around New York City, but he got fed up with how often bike lanes were blocked by delivery trucks and idling cars. So he decided to do something about it, the New York Times reports. Bell is a computer scientist and he developed a machine learning algorithm that can study traffic camera footage and calculate how often bike and bus lanes are blocked by other vehicles. He trained the algorithm with around 2,000 images of different types of vehicles and for bus lanes, he set the system to be able to tell the difference between buses that are allowed to idle at bus stops and other vehicles that aren't. Then, he applied his algorithm to 10 days of publicly available video from a traffic camera in Harlem.

It took Bell around three weeks to develop the algorithm and his system took about a day to analyze the traffic cam footage. The results showed that the bus lane on the block covered by the camera was blocked 57 percent of the time while the two bike lanes were blocked 40 percent of the time. Based on those numbers, Bell determined that approximately 850 vehicles had blocked the bike lane during those 10 days and 1,000 blocked the bus lane. And while these findings are based on just one city block and a short period of time, the other 101 miles of bus lanes and 435 miles of bike lanes throughout the city suffer from the same issues. It's a problem many people want a solution to.

For the past several decades, cities have designed streets around the assumption that they'll be used for personal cars. If you need a poster child for this, you just have to look at Los Angeles' Wilshire Boulevard -- it has a whopping 10 lanes for vehicles, and even the bus lanes are almost treated like afterthoughts. It's no wonder gridlock is such a common problem, since LA is practically inviting more drivers and the traffic chaos that results. Lyft isn't happy with this state of affairs, and it thinks urban planners need to reinvent the road if they want to reduce traffic and embrace the future. It's partnering with designers at Perkins Will and Nelson/Nygaard on a conceptual Wilshire Boulevard redesign for an era when car ownership fades away and public options dominate.