Perrone Robotics has developed a novel approach for measuring characteristics of moving vehicles using an array of overhead and wayside lasers. This laser-based vehicle measurement system is used to detect and classify individual vehicles, measure their characteristics such as speed, width, height, and length, and detect front and rear vehicle locations for triggering of external cameras and systems. Working with Transcore Corporation for deployments on the Pennsylvania Turnpike, the system has been running 24×7 and has proven capable of handling a wide variety of environmental conditions and vehicle types. The system is also being used in axle counting and also, in conjunction with scales, to weigh vehicles in motion at highway speeds in an open tolling environment. Be it operation in rain, snow, fog, or bright sun, the system intelligently filters environmental noise to provide crisp laser-accurate images of vehicles traveling from stop and go speeds to 100 mph. Be it tolled, gated, or open tolling, the system is capable of handling motorcycles, cars, trucks, tractor trailers, vehicles with trailer hitches, utility vehicles, and the wide class of vehicles that operate on a highway.
- Overhead lasers (SICK LMS sensors)
- Computing System to calculate vehicle characteristics based on laser data.
- Integrate-able with other sensors and systems (e.g. cameras, scales, RFID).
- Extensible, robust, and proven.
- Intelligent vehicle detection and separation (including vehicles with trailers)
- Accurate vehicle speed calculations
- Accurate vehicle dimensional measurements (height, width, length)
- Triggering of cameras for license plate capture
- Classification of vehicle types
- Open tolling, tolled, or gated lanes
- Stop & go, slow, normal, or high (100 mph) speeds
- Filtering of environmental noise (e.g. rain, snow, dust trails)
- Dynamic ground profile adjustments (e.g. due to snow accumulation)
Perrone Robotics presented an overview of this laser-based vehicle measurement system at Oracle’s 2010 JavaOne conference.