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Artificial Intelligence: AI is solving traffic problems to get you to safety

“I haven’t met anyone who really loves transportation,” said Karina Ricks of the Federal Transportation Administration.

Except, maybe, professionals like her who are tasked with reducing it.

Ricks made her career by being interested in traffic patterns. Before assuming the role of associate administrator for research, innovation, and demonstration at FTA, she served as the director of infrastructure and mobility for the City of Pittsburgh in Pennsylvania. She’s spent countless hours thinking about cars, transit, roads, and pedestrians — and how to make it all more fluid.

“When you are in peak travel time, when the system is already full, even a small disruption can cause really big problems,” says Ricks. “The job is to quickly flag those disruptions and quickly retool the system to work around them.”

What Ricks aims to optimize for affects anyone traveling from point A to point B, especially in cities. She explains that congestion is the number one problem in traffic, and is a common occurrence in urban areas. Add to that the number of variables at any given time, including the people driving the vehicle and the geography, and it leads to a conundrum even to try to solve.

If there was an easy way to reduce traffic, it would have been done in the last 50 years, she said. Instead, she, government organizations and startups in the field, such as Lytall are looking at the vast amount of available traffic data — from traffic sensors to ride-sharing and even bike and scooter data from smartphones — and using it to Make decisions about how to get people to work, home, and groceries safely and quickly.

That solution involves artificial intelligence and machine learning.

Tim Menard, founder and chief executive officer of Lyt, a software engineering platform that provides mobility solutions to cities, explains: “There are tasks where humans are not that good at machines. , and that’s how to tell. “AI is a great technology to use, because you are looking at all the parts of the system. You can start giving it different information and you can put it into a system that can make changes in performance.”

Menard founded Lyt after researching intelligent transportation systems for more than 13 years. His company uses vehicle data to solve traffic problems, especially when it comes to the efficiency of public transit options. For Menard, the ultimate goal is “to make more cities more equal by making public transit more reliable, predictable and faster.”

Both Ricks and Menard believe that the way to reduce traffic is to put more people on public transport, such as buses, subways and light rail systems. Public transport is the safest mode of ground transportation, with fewer injuries and deaths. It’s also a faster way to move larger numbers of people.

Ricks explains that most of the congestion is caused by “low-mass vehicles”. single-seat car. Those drivers are human; some drive faster, some slower; some change lanes frequently, others stop abruptly when the traffic light turns yellow before turning red. Because people behave so differently, there is a degree of unpredictability in the transportation system. Much of her work is aimed at making public transport more appealing to commuters.

Ricks added: “You’re reducing the odds of a possible collision by reducing the number of vehicles there.

With that in mind, Menard started looking at the Internet of Things for its cloud platform, pulling data from smartphones, car sensors, public transport and vehicle logs to understand traffic patterns. Traffic patterns at different times of the day as well as during special times – in addition to events, such as a sports game at a local stadium. The first hurdle, he says, is operating from a place of known information rather than guesswork; In the past, he explained, people spent hours looking at video screens to start estimating next steps.

He founded in San Jose, California, where for the past three years he has partnered with the city to optimize bus routes by 20%, thereby reducing fuel consumption by 14% and emissions. at intersections down 12%. Using predicted estimated arrival times at each traffic light, his platform reduced travel time between bus stops by optimizing bus lanes and traffic lights to ensure buses can move as efficiently as possible without disrupting other traffic. He now works in other cities in northern California, including other Bay Area towns and Sacramento, as well as in the Pacific Northwest: Seattle and Portland, Ore.

Menard is also looking at bicycle and pedestrian traffic, which he says is a concern and priority for many transportation regulators. He has worked to make cycling safer by creating dedicated bike lanes with curbs with individual traffic signals that are synchronized with the traffic signals of other vehicles. convenient to help avoid collisions between cars and bicycles. For pedestrians, Ricks explains that pedestrian traffic uses sensors and adaptive controls to adjust settings in real-time based on demand — the moment when AI algorithms and real-time data intersect. together.

Another benefit of AI technology to traffic patterns surrounds first responders. Menard used machine learning to analyze data from emergency vehicles like ambulances and fire trucks to improve speed. He noted that in many urban environments, congestion and traffic prevent first responders from reaching the scene or hospital in a life-or-death situation. In Sacramento, California, he solved this problem.

He said of looking at the accumulated data from all the stakeholders in the city: “It was literally better night and day in less than 15 minutes. There he improved the slowest 10% of emergency vehicles to more than 10 miles per hour, allowing them to arrive 70% faster in the event of any response. Even the top 10% of vehicles saw a speed increase of 6 mph.

For every passenger car that changes to public transport, there will be less traffic on the road causing congestion. Menard often reminds people that when they are in their car, stuck in traffic, there are many other people around them doing the same thing. If they switch to shared transportation — a high-capacity mode of transportation — they can get up to speed very quickly.

But inspiring commuters to change their habits is always a challenge, so the new choice needs to be compelling enough to motivate them to adjust the way they operate. “What you want in a transit system is display right now [and] Ricks said. “We need to solve the traffic problem to make transit an attractive alternative. There’s still quite a bit of work to do. “

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