Case Study:
Terrell, Texas
The City of Terrell is located in northeastern Texas, with approximately 18,000 citizens residing in 20 square miles. Schaumburg & Polk, Inc. (SPI), is a trusted engineering firm by municipalities and clients around Texas, providing specialized expertise and integrated services for the public and private sector for both large and small projects.
Challenges
The City of Terrell was unsure of the exact location and current condition of their street lights, street name signs, and traffic signs. Some of these road-related and adjacent assets were in poor condition and needed to be removed and replaced, while others were damaged beyond repair or missing entirely.
Without accurate details of their location and condition, the city could not appropriately prepare a budget and schedule for repairs and replacements. Taking a manual inventory of these assets would be time intensive and require many man hours, and in addition, the city did not have an efficient method or process of recording and retaining this kind of data.
The City of Terrell was looking for a streamlined way to objectively record the assets’ location and condition so they could confidently allocate funds and plan for the future.
Screenshot from within Terrell’s asset map, viewable on AgileMapper.
Solution
The City worked with SPI to develop a process to evaluate each street light, identify all traffic signs by location, inventory the traffic signs and post types, and evaluate the light and sign conditions overall. In addition, SPI was asked to provide recommendations for the replacement, repair, and maintenance of those assets.
SPI employed RoadBotics by Michelin’s AgileMapper platform for the traffic sign portions of the project. Each traffic sign in the city was photographed using a smartphone and then uploaded to AgileMapper. Once uploaded, the signs were automatically tagged using RoadBotics by Michelin’s artificial intelligence and placed geographically on an interactive map.
Using unique tags they were able to create themselves on the platform, SPI was able to clearly categorize 40 different types of signs like Yield, One Way, and Bus Stop. In the Comment area for each image, the engineers were also able to make specific notes about signs or sign posts that were damaged, vandalized, or otherwise in need of repair.
A photo taken for the inventory along with tags added by AI and SPI
Results
Using AgileMapper, SPI found that the City of Terrell’s traffic signs were in fair to poor condition. It is estimated that approximately 40% of signs would require replacement or remounting to bring the overall score to a good to excellent rating.
They also identified damaged signs and posts that could be scheduled for repair or replacement, including those that were faded, rusted, bent, or vandalized. SPI is recommending that the City strive for consistency with regard to sign heights, mounting, post type, location, etc. in addition to improving overall signs conditions.
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