Rehoboth Beach, Delaware
(Getty Images/Scott Dunn)
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Delaware’s low elevation, mix of crowded beaches, and limited evacuation routes make it particularly vulnerable to major floods, but officials say an influx of federal infrastructure funding will help artificial intelligence help plan future evacuations. Expect it to start automatically.
The Biden administration was due Thursday to announce a total of $53 million in grants to Delaware and seven other states for high-tech solutions to traffic congestion problems. The money comes from the Infrastructure Act the president signed into law in 2021, but many of the programs have evolved since then, including donating $5 million to flood relief efforts in Biden’s home state.
“What’s new is predictive analytics. It’s machine learning,” former Delaware Secretary of Transportation and U.S. Highway Secretary Shailene Butt said in an interview with The Associated Press. “Nowadays, we have access to all kinds of data, so it’s hard for humans to understand what is data and what is actionable information.”
Delaware officials enforce weekly evacuation procedures during the tourist season, with long lines of cars heading to the beach on weekend mornings and back at night. However, flooding poses a unique problem. For example, roads can become flooded, making the most direct route out of town even more dangerous than simply evacuating in place.
“You don’t want your vehicle to get caught in a delayed decision,” said Gene Donaldson, operations manager for the state’s 24-hour traffic management center.
The Delaware Department of Transportation manages more than 90% of the roads in the state with the lowest average elevation in the country and is tasked with implementing high-water evacuation plans, but this is a rapidly changing situation. It’s a bureaucratic nightmare to think about.
“Having people monitor thousands of detectors and data sources is overwhelming,” said transportation director of Blue Halo, an Arlington, Virginia-based company that has worked with Delaware to develop the software. says George Zhao.
That’s where AI comes in. Rather than sending workers to the scene to block impassable roads, the system can also use sensors to detect and predict weather threats. It then sends the information directly to the driver through mobile phone alerts and simultaneously broadcasts to electronic highway signs.
The amount of data continues to grow, and many self-driving cars can now not only inform drivers of hazards ahead, but also inform systems to warn others.
Researchers at the Missouri Institute of Technology tested an early version of a flood prediction analysis system on the Mississippi River from 2019-2022. Co-author of the study, Steve Cornes, associate professor of engineering management and systems engineering, said the system was able to detect in minutes what previously took hours.
But now, Cornes said, the capabilities are much more sophisticated and useful, provided that the technology is sufficiently funded to keep it from becoming obsolete.
To date, legislation has provided more than $300 million in congestion relief subsidies, and Bhatt said the agency received $385 million in the latest $52.8 million petition under the Infrastructure Act. . He said it “shows a great deal of appetite” for innovative solutions to address traffic problems.
Other payments in this grant include $14 million for machine learning traffic prediction and signal timing in Maryland, and Ann Arbor, Michigan’s transit system to deploy cellular technology as a potential national template. Includes $12.7 million. Also included is $11.6 million to expand microtransit services in Grand Rapids, Minnesota.
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