Artificial Intelligence for Traffic and Weather

The Artificial Intelligence for Traffic and Weather (AI4TW) program is a $1.17M program to install and evaluate smart traffic and weather AI applications to improve the safety and efficiency of traffic flow on and off the Fort Carson Army post in Colorado Springs, Colorado.

US Ignite was awarded a contract from the U.S. Army Engineer Research and Development Center (ERDC) to advance the Army Installation Modernization Pilot Program (AIMP2, formerly known as Installations of the Future) initiatives under the Assistant Secretary of the Army (Installations, Energy and Environment). The AI4TW program is a follow-on to the Fort Carson Smart Transportation Testbed Program, which US Ignite also led for the U.S. Army Corps of Engineers.

Through the AI4TW program, US Ignite worked closely with Fort Carson leadership to design, develop and implement data-driven decision-making tools. Specifically, the Inclement Weather Decision Support App (IWDS) was created and launched to provide the garrison’s operational staff with better data on the risk weather poses on traffic safety when deciding whether to close due to winter weather. Through the App’s intuitive interface, decision-makers have access to a number of visualizations and alerts that provide a greater understanding of the expected conditions on the roadways during a winter weather event.


Screenshot of the IWDS application opened on a desktop computer

About the Inclement Weather Decision Support Application

During an inclement weather event, the Fort Carson leadership must quickly decide between courses of action: keeping the base open, reducing presence to mission essential personnel only, or reducing operating hours. Commuter safety must be balanced with the urgency of ongoing operations. However, to make that call, decision-makers must understand the safety implications of that decision for service members commuting between the base and surrounding communities.

Previously, the leadership relied solely on a mix of weather forecasts and ad-hoc community coordination to decide. To improve this process, US Ignite built the IWDS app. The AI-driven application provides operational recommendations based on real-time and forecasted weather and traffic conditions. It is designed to help improve efficiency, increase commuter safety, and reduce costs for the Fort Carson installation.

IWDS’ Data and Algorithm

The IWDS app uses weather forecasts and observational data from the National Weather Service as a baseline. This data is supplemented by an Intellisense Micro Weather Station installed onsite by US Ignite, which delivers a comprehensive array of environmental observations that offer greater accuracy on current weather conditions, specifically at Fort Carson.

Micro Weather Station

Intellisense Micro Weather Station at Fort Carson


The IWDS App’s AI was trained on historical weather data from the National Digital Forecast Database [NDFD], along with historical data on roadway characteristics like curvature and gradient, historical traffic pattern data, and historical crash data. The AI correlates these data sources to understand how different combinations of roadway feature characteristics, usage characteristics, and weather lead to increased incidence of crashes so that when new weather forecasts come in, decision-makers can have an advanced look at how that weather is expected to impact commuter safety.

Top Features:

  • AI Predictive Routines: The IWDS app fuses data on roadway characteristics like curvature and gradient, weather data, traffic pattern data and crash data to correlate inclement weather with an increased likelihood of crashes. The predictive routine then ingests hourly 7-day weather forecasts from the National Weather Service to create a prediction of how forecasted weather will affect commuter safety.
  • Dashboard: The IWDS app offers a dashboard with a map that quickly summarizes the weather and traffic safety risk levels across the regions that commuters travel to and from Fort Carson, and it gives users the ability to drill down between weather, roadway, and region layers to get a detailed understanding of the situation.
  • SMS, email, and dashboard notifications: The IWDS app notifies users via email, SMS, and within the dashboard when a weather event is first detected, and along each step in the decision-making process so stakeholders can stay informed as the situation develops.
  • Hyper-Local Forecasts: The IWDS App draws weather and environmental data from an Intellisense Micro Weather Station installed at Fort Carson to offer greater accuracy on forecasts.
  • User-friendly interface: The IWDS app has a user-friendly interface accessible from both desktop and mobile devices, so decision-makers can easily access the information they need, whether in the command center or from home when making decisions overnight.
  • Customized recommendations: The IWDS App generates customized recommendations specifically for the Fort Carson Installation while utilizing and adhering to their operational standards and requirements.

Next Steps

USACE-ERDC and US Ignite are working on a plan that would allow the new app to be transitioned to the Army’s Virtual Testbed for Installation Mission Effectiveness (VTIME) and identify pathways to replicate and scale the solution in other installations.


“...we were delighted to select... US Ignite as very worthy first winner of the Award, based on the readiness & utility of the application, its contribution to public health and safety, and its readiness and portability to be delivered on various infrastructure platforms." Philippe Cases, Chairman of the Judging Panel, Topio Networks

News and Recognition

Topio Networks selected US Ignite’s Inclement Weather Decision Support App as the Intelligent Infrastructure Application of the Year!

Read the Announcement

Government Technology reported on US Ignite’s Inclement Weather Decision Support App and its innovative use of real-time weather, transportation, and other data to shape decisions around base operations.

Check out the Article

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