Long Beach tests traffic lights that respond to real-time congestion
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The California city will test whether artificial intelligence-driven connected vehicle technology can alleviate traffic congestion and improve air quality.
A smart infrastructure pilot will test whether traffic signals in Long Beach, Calif., can respond to changing driving patterns in real time.
The city will work with Mercedes-Benz and Xtelligent, deploying a fleet of up to 50 smart vehicles and artificial intelligence software that will communicate real-time traffic data to an intelligent intersection control system. The vehicles will primarily be sharing location data, a common feature in most cars with onboard navigation systems. However, in this case, the vehicles will share data with each other and with city infrastructure.
City planners and engineers will be able to use the shared data to measure traffic congestion and even calculate emissions based on the type of vehicle and distances travelled, city officials said. Data analysis from connected test vehicle fleets and existing physical sensors around the city may also inform future transportation policy and traffic engineering decisions.
Long Beach Smart Cities Program Manager Ryan Kurtzman told the Long Beach Business Journal that he believes the project, which is expected to last 10 months, could put the city ahead of the curve and yield a number of potential benefits.
The system is expected to not only improve traffic flow by anticipating congestion based on crashes or school pick-up and drop-off times and re-routing traffic using customized red and green periods at specific intersections, Xtelligent Co-Founder Michael Lim told the news site.
The software will also help enhance livability and environmental sustainability in Long Beach. In areas with poor air quality, adaptive signaling could reduce the amount of time cars spend sitting at red lights. Plus, the increased efficiency would benefit electric vehicles. “When you have a more predictive, flowing type of movement, they’re able to maintain energy more effectively,” Lim said.
All data from the program will be anonymized, so that the movements of individual cars cannot be tracked. The pilot’s project’s exact location is yet to be determined, although parts of downtown and an area near the local Mercedes-Benz facility are expected to be among the potential areas. If all goes well, the project will launch by the end of the year. When the pilot concludes, the team will evaluate results and explore opportunities to scale the effort.
“Systems like that have the potential to improve the efficiency of our transportation network,” Kurtzman said. “This project helps us inform how we could deploy this type of technology on a larger scale across the city.”
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