Details:

• Creators:
  Frisbie, Todd ; Sines, Daniel ; Sosa, Zoami ; Day, Christopher ; Young, Stanley ; ... More +

  Frisbie, Todd ; Sines, Daniel ; Sosa, Zoami ; Day, Christopher ; Young, Stanley ; Hainen, Alex ; Mir, Faizan ; Sandhu, Rimple Less -
• Corporate Creators:
  City of Colorado Springs ; National Renewable Energy Laboratory (NREL) (U.S.)

  City of Colorado Springs ; National Renewable Energy Laboratory (NREL) (U.S.) Less -
• Subject/TRT Terms:
  [+]

  Automatic Data Collection Systems Axis Camera Units Data Collection EVO RADAR Information Processing Intersections Laser Radar LiDAR Multi-sensor Data Fusion Algorithms Object-level Data Perception Sensors Radar Sensors Travelers Vehicle Occupants Vehicle Personnel Wireless Sensor Networks
• DOI:
  https://doi.org/10.21949/g3r6-5954
• Resource Type:
  Tech Report
• Geographical Coverage:
  United States
• Corporate Publisher:
  Strengthening Mobility and Revolutionizing Transportation (SMART) Program
• Abstract:
  The City of Colorado Springs (the City) is at the forefront of modernizing its transportation infrastructure through a staged, innovative approach to sensor-driven, adaptive traffic management. This journey began in 2016, when, in partnership with Iowa State University (ISU), the City implemented the nation’s first proof-of-concept for trajectory-based signal control—what is now recognized as the first generation of high-resolution adaptive traffic management. That foundational system, currently deployed across Colorado Springs, uses radar sensors at intersections to continuously track approaching vehicles, enabling controllers to optimize signal timing in real time. The system’s algorithm learns typical traffic flows, identifies bi-directional breaks between platoons of traffic, to serve side street traffic, and actively avoids creating “dilemma zones” for drivers, improving both safety and efficiency for all road users. Building on this success, the City has leveraged USDOT SMART Grant funding to launch Stage 1 of a next-generation adaptive traffic management system. While the first-generation system proved the viability and value of real-time, perception-based signal control, Stage 1 advances this concept by integrating new perception dimensions enabled by state-of-the-art sensor hardware—including radar, LiDAR, and video analytics—as well as a sophisticated “digital twin” of intersection operations. This work not only evaluates the latest technologies but also sets the stage for a second-generation system capable of even higher-resolution perception, expanded context awareness (including real-time V2X communications with first responders, city transit, and snowplows), and dynamic adaptation to both traffic and environmental conditions.
• Format:
  PDF
• Funding:
  69A3552341025
• Collection(s):
  SMART Program
• Main Document Checksum:
  [+]

  urn:sha-512:3c75af8c4ea705e9c8d199caf75aeed4e84a054fba9d140ad527ed040d05e85dfb60031c132a32173a2be9d4fededa31ea402488b622db150350c2de698597df
• Download URL:
  https://rosap.ntl.bts.gov/view/dot/84611/dot_84611_DS1.pdf
• File Type:
  [PDF-9.10 MB]