Sensors · 2014 · 67 citations · 13 references
EngineeringAutomotive EngineeringSensorsTransportationUltrasoundAcoustic SensorsIntelligent Transportation SystemsSensor NetworksUltrasonicsWireless NetworksWireless Sensor NetworksAccelerometer SensorsLow-power Sensor SystemsTraffic SurveillanceUltrasonic DetectionUltrasonic SensingUltrasonic SensorsVehicle DetectionWireless Sensor-based Detection
Existing traffic information acquisition systems are costly and lack scalability, and although magnetic, acoustic, and accelerometer sensors have been explored for WSN‑based traffic surveillance, ultrasonic sensors remain unstudied, while WSN limitations require power‑saving methods and low‑complexity vehicle‑detection algorithms. The study models and analyzes optimal power‑saving methods for an ultrasonic sensor and presents a computationally‑efficient vehicle‑detection algorithm using ultrasonic data. The authors implemented the power‑saving methods and vehicle‑detection algorithm on a tiny microprocessor and evaluated them on real roads. Evaluation results demonstrate that the algorithm’s low computational complexity does not compromise vehicle‑detection accuracy.
Existing traffic information acquisition systems suffer from high cost and low scalability. To address these problems, the application of wireless sensor networks (WSNs) has been studied, as WSN-based systems are highly scalable and have a low cost of installing and replacing the systems. Magnetic, acoustic and accelerometer sensors have been considered for WSN-based traffic surveillance, but the use of ultrasonic sensors has not been studied. The limitations of WSN-based systems make it necessary to employ power saving methods and vehicle detection algorithms with low computational complexity. In this paper, we model and analyze optimal power saving methodologies for an ultrasonic sensor and present a computationally-efficient vehicle detection algorithm using ultrasonic data. The proposed methodologies are implemented and evaluated with a tiny microprocessor on real roads. The evaluation results show that the low computational complexity of our algorithm does not compromise the accuracy of vehicle detection.
13
TRAFFIC CONTROL SYSTEMS HANDBOOK
R L Gordon, R A Reiss, H E Haenel et al. · 1996 · 228 citations
Engineering, Systems Engineering, Transportation Planning +14
Acoustic Sensor Network for Vehicle Traffic Monitoring
Barbara Barbagli, Gianfranco Manes, R. Facchini et al. · 2012 · 36 citations
Engineering, Automotive Engineering, Systems Engineering +14