A New Method for Accurately Estimating the Weight of Moving Vehicles Using Piezoelectric Sensors and Adaptive-footprint Tire Model

Summary This paper presents new methods for estimating the axle weight of a moving vehicle, using two piezoelectric sensors and adaptive-footprint tire model. It is more difficult to weigh vehicles in motion accurately than to weigh standing vehicles. The difficulties in weighing moving vehicles result from sensor limitations as well as dynamic loading effects induced by vehicle/pavement interactions. For example, two identical vehicles with the same weight will generate sensor signals that differ in the shape and the peak value, depending the tire pressure, vehicle speed, road roughness, and sensor characteristics. This paper develops a method that is much less sensitive to these variable factors in determining the axle weight of a moving vehicle. In the developed method, first the piezoelectric sensor signal is reconstructed using the inverse dynamics of a high-pass filter representing the piezoelectric sensor. Then, the reconstructed signal, is normalized, using the nominal road/tire contact length obtained using an adaptive-footprint tire model, and then integrated. Experiments are performed with 3 vehicles of known weight ranging from 1,400 kg to 28,040 kg. The developed method is compared to two other algorithms. Results show that the developed method is most consistent and accurate.     

Improving the Performance of Loop-Sensor-Based Traffic-Information System by (M+PLL) Circuit

Conventionally a phase-shift detection method (PSDM) and a frequency-shift detection method (FSDM) have been used in loop detectors. The PSDM has a fast response time and is very effective in detecting vehicles traveling at normal speeds. However, it is well known that the detection results are erroneous for vehicles traveling at low speeds in heavy traffic conditions. On the other hand, the FSDM greatly improves the detector performance for heavy traffic conditions. However, this method is not effective in fast and normal traffic conditions. Thus, in order to collect accurate traffic data for all traffic conditions, this paper proposes combining two methods using the digital OR logic. In the developed circuit, a phase-locked loop (PLL) circuit is used for measuring the phase change. This paper also develops a new loop detector instrumentation method using the so-called M circuit for detecting frequency change. The developed method has been tested for various traffic conditions. Experimental results show that the new combined M and PLL detection method greatly improves the accuracy in all traffic conditions, reducing the error rate in measuring traffic flow by more than 83%, when compared to the PSDM.