Startup Uses Machine Learning to Drive Better Road InvestmentEmily Pollock
posted on January 18, 2019 |
RoadBotics turns visual road scans into maps that show areas in need of repair. (Image courtesy of RoadBotics.)
Move over, RoboCop! The newest robot looking after Detroit’s streets is RoadBotics’ pavement-analyzing machine learning algorithm, which uses driver-collected data to determine which areas of the city are in most dire need of roadwork.
RoadBotics is a startup with a simple premise: you provide a map of the roads you want scanned, and it will scan them and tell you where the potholes are the biggest. To do that, the company has drivers travel down all the roads with dashboard-mounted smartphones recording a continuous stream of video and then cross-references that information with GPS data. After RoadBotics has a rough map, it analyzes the footage with a machine learning algorithm trained on common road defects (unsealed cracks, potholes, etc.) Finally, its platform aggregates the total damage on a section of road and assigns it a rating from 1-5 (with 1 being a practically new road, and 5 being a road that is in serious need of repairs).
For cities and states, the allure of RoadBotics is that it gives “objective” data without human analysis, and that it provides its users with an easy-interface map afterward. So far, the company has assessed over 90 communities in 15 states. Detroit is one of the most recent cities to be announced for the process, and the first to be the beneficiary of the company’s new AIM (AI maintenance) tool for unsealed cracks. With assistance from Planet M, a Michigan-based partnership that connects mobility professionals from the private, public and not-for-profit sectors, RoadBotics and the city have forged a strong alliance.
"The City is thrilled to be working with RoadBotics on this project,” said Oladayo Akinyemi, deputy director at Department of Public Works for the City of Detroit. “This partnership and pilot will provide us with data and insights about our road conditions that will help our engineers determine where to objectively allocate our resources and maximize investment in maintaining our residential streets in the best condition.”
The survey is only part of Detroit’s push toward data-driven asset management. Since 2017, the city has taken an “open data” approach to its website: giving its citizens access to as much of the city’s data as it can, along with the tools to understand it. The city’s site is a so-called “open data portal,” with contracts, records and statistics laid out in an easy-to-navigate format. Detroiters can already look up data on mobility options, bus stop locations and traffic crashes; the RoadBotics data will become just another piece of their data puzzle.
“It is outstanding that Detroit is committed to being at the forefront of using cutting-edge AI to fundamentally reshape how they ensure safe and high-quality roads for all people,” DeSantis said. “Our hope is that their example of leadership catalyzes more cities across the U.S. to adopt a data-driven approach to pavement management via our solution.”