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SwRI's ActiveVision Enables Transportation Agencies to Automate Traffic Monitoring

By Hannah Smith , Jun 05, 2019 10:50 AM EDT
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ActiveVision applies a combination of advanced computer vision and machine learning capabilities to detect and report actionable traffic condition changes. (Photo : Southwest Research Institute)

SAN ANTONIO - June 4, 2019 - Southwest Research Institute (SwRI) has announced the release of Activision, a machine vision tool that transportation agencies can use to autonomously detect and report traffic condition changes. Activision's algorithms process camera data to provide real-time information on weather conditions and other anomalies affecting congestion.

Designed for integration with intelligent transportation systems (ITS), ActiveVision can be configured with existing traffic cameras to analyze roadway conditions with no human monitoring required.

"The goal is to help transportation officials enhance their ITS capabilities with advanced algorithms that autonomously scan vast amounts of visual data, extracting and reporting actionable data," said Dan Rossiter, a SwRI research analyst leading ActiveVision development.

ActiveVision integrates with the SwRI-developed ActiveITS software in addition to other ITS and advanced traffic management systems (ATMS) used by state and local agencies across the country. A leader in transportation and traffic management software, SwRI has over 20 years of experience developing and deploying ITS software for state and local agencies. SwRI-developed intelligent transportation systems have been applied to more than 13,000 miles of urban and rural managed roadways in 10 states and Puerto Rico.

"Work in the ITS arena inspired our team to find a solution that could be integrated agnostically into just about any advanced traffic management system, using existing cameras and infrastructure," added Steve Dellenback, vice president of SwRI's Intelligent Systems Division. The division specializes in traffic management systems and connected and automated vehicles in addition to machine learning solutions used in autonomous robotics, health diagnostics, markerless motion capture, and methane leak detection.

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