Are our roads and transportation systems ready for the mass return to office? A new study says probably not—and I would agree. Let’s take a closer look.
At the end of July, the U.S. Chamber of Commerce Foundation and RoadBotics released a study that assessed 75 miles of roadway in 20 cities selected to represent a cross section of major metropolitan areas. The companies used AI (artificial intelligence) to assess roadway conditions.
Here are how roads ranked across the country, with Philadelphia being the best for road infrastructure and Phoenix and Detroit tying for the worst of the areas studied.
- Philadelphia
- Jacksonville
- New York City (tie)
- Denver (tie)
- Nashville
- San Francisco
- Chicago
- Charlotte
- San Antonio
- Washington, D.C. (tie)
- Boston (tie)
- Minneapolis
- Houston
- Seattle
- Columbus
- Saint Paul
- Los Angeles (tie)
- Oklahoma City (tie)
- Phoenix (tie)
- Detroit (tie)
Let me tell you. If Chicago ranks in the top half for the best for road infrastructure, I don’t want to know what those other cities look like, but I digress.
Here’s what I like about this study. It opens our eyes to both the challenges and the new opportunities that exist with our infrastructure. Our two big current challenges are: our road network is massive and assessing conditions requires manpower that we just don’t have.
Let me flesh this out a little bit. It takes a geographic information systems analyst and road maintenance worker roughly 600 hours—or 25 days—to conduct a manual assessment of a 150-centerline mile network. At a combined hourly rate of $50, this equates to a total cost of about $30,000. Talk about pricey.
Technology can step in here and help. Not only does it save time in a market that is already crunched for quality labor, but it can also provide data in less time and it can ultimately save money.
Here is a specific example. With cameras mounted to the windshields of vehicles, AI can collect and analyze the data. Video, in combination with the AI, can identify surface distresses like potholes and cracks. Some agencies are already using these AI data collection methods for roads, transit systems, and fixed rail. This data can also be used to optimize budgets.
Or how about this: Some agencies are using connected and automated vehicles to detect hazards and collect data as well. While the main intent is for predictive applications, it is also providing observations of individual vehicle kinematics, acceleration and deceleration, braking, horsepower, fuel consumption, seatbelt use, and more. This can help transportation analysts better understand the human element and show driving environments with poor safety performance. This data can then be used for planning purposes.
This example can help in two other ways. First, it can provide trajectory data, which is a series of time-stamped latitude and longitude coordinates that reconstruct an individual trip. Second, it can supply probe data, which is an aggregation of trajectory data and most applied to the driving mode to offer estimated travel times.
This may help assess travel time and road network mobility performance. This is so vital for transportation agencies—especially today. The return to office is going to be slow. Agencies are going to need realtime data to determine transit conditions and usage as we ramp back up. Artificial intelligence can help anticipate this. It can measure traffic volumes and infer trip routes, and then we can use that data to help build the required infrastructure.
At the end of the day, AI technology can help accelerate the road assessment process, while also imparting data that can be used to inform other infrastructure decisions. Now what we do with that data is another thing altogether. I would argue the folks over in Washington and even in our local governments have known for years that this is a problem and yet very little has been done.
The good news is we are finally starting to see some movement happening in Washington. In July, we saw a bipartisan group of senators come up with an agreement on an infrastructure package, or so we hope. This would help make improvements in many of our critical infrastructure categories that we so desperately need. It would help repair our roads and bridges, modernize our transit systems, and help us build our infrastructure to meet the needs of our businesses and communities. And that is certainly something worth fighting for.
Want to tweet about this article? Use hashtags #IoT #sustainability #AI #5G #cloud #edge #futureofwork #digitaltransformation #green #ecosystem #environmental #circularworld