Abstract Manager

Traditional inductive loop detectors have formed the backbone of highway and signalized intersection detection for decades; however, increasing urban density and operational complexity have exposed the limitations of inductive loop technology. Loop detectors provide limited spatial coverage, minimal object classification, and lack of reliable data for stationary-vehicle and lane demarcation capabilities. As a result of mass urbanization, agencies are emphasizing on proactive safety and adaptive real-time operation improvement measures, there is a growing need to transition toward next-generation detection technologies capable of delivering richer, more accurate, and reliable data. 

This presentation examines emerging detection technologies currently available in the market, namely: forward-firing radar, 360-degree long-range radar, LiDAR, and video-based analytics. Technologies from various vendors are reviewed to highlight their operational capabilities and suitability for highway queue warning and adaptive traffic real-time operation improvement measures application. Several of these technologies have already been piloted and implemented by Canadian agencies on highways and signalized corridors.  These systems process traffic data in real time to detect, classify, and track both stationary and moving vehicles on a lane-by-lane basis, providing information on speed, classification, and location. 

• Highway applications: Detection data from roadside devices are integrated into traffic management and signal control systems to support automated queue detection, incident detection, and the autonomous activation and deactivation of real-time warning signs. By reliably distinguishing between stopped vehicles and queuing traffic, the system significantly reduces false alarms, increases operator trust in automated alerts, improves response times, and enhances roadway safety. 

• Arterial signalized intersections: The same detection capabilities support adaptive signal control at complex arterial intersections. Lane-level detection, queue-length measurement, and vehicle classification enable functions such as green extensions, spillback management, and movement-specific phase adjustments. These capabilities deliver measurable congestion reduction through responsive signal timing during peak periods, while allowing agencies to transition to reactive monitoring during off-peak operations. 

 The findings demonstrate that next-generation detection technologies can effectively replace or supplement legacy systems while supporting multiple applications from a single roadside system. The presentation will share insights from Canadian deployments and offer practical guidance for agencies transitioning to scalable, multi‑application sensing solutions.