Using Artificial Intelligence and Machine Learning Solutions for a Median Inventory and Traffic Volume Estimation in Missouri Cost $80,000 and $45,000, Respectively.

Pilot Projects by the Missouri Department of Transportation in 2024 Tested the Cost Effectiveness of Automating Two Transportation Management Center Tasks.

Made Public Date
08/27/2025
Identifier
2025-SC00576

Recent trends in big data combined with technological breakthroughs in Artificial Intelligence (AI) and Machine Learning (ML) have the potential to transform transportation planning and operations. State departments of transportation are recognizing potential benefits, such as personnel time savings, data-informed decision-making, and enhanced worker safety. Thus, the Missouri Department of Transportation (MoDOT) evaluated opportunities offered by AI and ML to support agency operations. MoDOT tested two pilot projects where AI/ML could be applied: a highway median inventory and annual average daily traffic (AADT) factor grouping. This project took place between June 2022 and June 2024 at MoDOT’s St. Louis Transportation Management Center.

The highway median inventory pilot used aerial imagery in combination with AI/ML techniques to identify movable acres of median across southern MoDOT maintenance districts. The AADT factor grouping pilot created an automated process to define adjustment factors for traffic counts and improve the accuracy of AADT estimates.

  • The median inventory pilot had a total cost of $80,000 to develop a model capable of delineating 48 million square feet of unpaved and paved medians. This was compared to an estimate of $61,110 to complete the task manually over one year. The ML model had a prediction accuracy of 93 percent and could not serve as a median inventory without correcting the seven percent error, which would take between six to nine months. The report also suggested that it would be more cost effective to update the inventory by hand irrespective of the original inventory generation method.
  • The AADT pilot had a total cost of $45,000 to develop a tool that clustered and classified traffic counts. This was compared to an estimate of $124,800 for two years of staff time to complete the task manually (a cost savings of $79,800). MoDOT estimated that some additional work would be required to integrate the AADT tool into their existing systems, costing between $10,000 and $30,000.