Commercially-off-the-Shelf (COTS) and Emerging Technologies Sensor Testing and Evaluation

This report addresses Task S of the Intersection Decision Support (IDS) project funded by Federal Highway Administration (FHWA) and Caltrans. The objective of Task S is to evaluate and select Commercially-Off-The-Shelf (COTS) and emerging technology products that could eventually be deployed at intersections as part of the IDS system. Many sensors were considered and every plausible detection technology was reviewed for this task. The emphasis was on finding sensors that detect and track vehicle movements. This effort started with establishing a background and general guidelines for what this task was set to accomplish. Then, our hypothesis and assumptions as well as our constraints and limitations to achieve our goals were clearly defined. At last, the evaluation criteria were established. By considering the above, a comprehensive survey was done to find the sensors and detectors that show the most promises to be included in the IDS system. This survey covered devices from a variety of different detection technologies: microwave, passive infrared, video image processing, active magnetic, passive magnetic, passive acoustic, active laser, and inductive. After the preliminary selection process revealed the most promising sensor products, the research team contacted the vendors and installed these sensors at Richmond Field Station’s Intelligent Intersection. Some of the sensors were donated by the vendors to PATH, some were loaned to PATH, and one sensor type was actually purchased for further in-depth evaluation. For each sensor type, a set of experiments were set up. After each experiment, the data was analyzed and the results can be found in this report. The following sensors were evaluated in-depth: Conago Microloops by 3M, VDS240 by Sensys Networks, Traficon Video Detection system by Traficon, RTMS by EIS, and stand in-pavement loops. It should be noted that all of COTS products are designed for conventional traffic monitoring purposes and therefore are not intended for the types of functionalities and specifications required by IDS applications. With that in mind, after the results of our experiments were finalized, we found no single detection system can, by itself, meet the detection requirements of IDS system. It is our belief that a combination of different sensors need to be assembled together to provide a reliable detection system to be used in our warning algorithm.