Montgomery, AL automates road assessments using Ai
Montgomery partners with RoadBotics for AI-driven road condition surveys.
Highlights
Addressing all of Montgomery’s road paving needs would cost $12 million, but the city can only afford to spend $2 million on paving per year.
To better allocate its budget, Montgomery engaged RoadBotics to survey roads using its machine learning, image-recognition technology.
The RoadBotics approach delivers up-to-date, objective road condition data to guide improved spending decisions – at a fraction of the cost of traditional, manual surveying.
The new data also enables preventive road maintenance, with each $1 spent on preventative maintenance saving as much as $20 in deferred maintenance.
Summary
Allocating city budget for road paving is always a sore point for Montgomery, AL. The city has approximately $12 million of paving needs across its 1,100 miles of road, but it only has the budget to spend roughly $2 million on paving per year. Council members often request more be spent on paving in their districts, so deciding which stretches of road to prioritize is a challenging process.
In the past, Montgomery contracted a team of independent asphalt field inspectors and GIS technicians to survey the condition of the roads, and used that assessment to guide its budgeting decisions. However, this approach was so time-consuming and expensive that the last survey was carried out eight years ago.
With its sights set on gaining up-to-date insight into road conditions without breaking its budget, Montgomery turned to RoadBotics. This Pittsburgh-based start-up uses machine learning technology to analyze roads and rank their condition quickly and cost effectively. The RoadBotics team was able to simply drive across Montgomery’s roads collecting images via smartphones, then analyze the photos with its image recognition AI solution.
Focusing on 200 miles of road that were known to be in need of attention, the RoadBotics assessment took just 30 days.
The new survey provided objective information that is enabling the city to implement a data-driven pavement management strategy – helping it to prioritize spending fairly on the roads that need it most. Additionally, Montgomery can now take preventative maintenance measures to tackle paving issues early, before they become more serious and more expensive to fix.
As well as saving money and guiding budgeting decisions, the city also hopes that the new survey data will lead to innovative solutions to Montgomery’s paving problem. What’s more, the steps towards better roads are helping prepare the city for autonomous vehicles.