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Traffic Measurement and Vehicle Classification with Single Magnetic Sensor.
| 题名： | Traffic Measurement and Vehicle Classification with Single Magnetic Sensor. |
| 作者： | Cheung-Sing-Yiu; Coleri-Sinem; Dundar-Baris; Ganesh-Sumitra; Tan-Chin-Woo; Varaiya-Pravin |
| 关键词： | Accuracy-; Algorithms-; Loop-detectors; Neural-networks; Vehicle-classification |
| 摘要： | Vehicle class is an important parameter in the process of road traffic measurement. Inductive loop detectors (ILD) and image sensors are rarely used for vehicle classification because of their low accuracy. To improve their accuracy, a new algorithm is suggested for ILD using backpropagation neural networks. In the developed algorithm, inputs to the neural networks are the variation rate of frequency and occupancy time. The output is five classified vehicles. The developed algorithm was assessed at test sites, and the recognition rate was 91.7%. Results verified that, compared with the conventional method based on ILD, the proposed algorithm improves the vehicle classification accuracy. |
| 总页数： | Transportation Research Record: Journal of the Transportation Research Board. 2005. (1917) pp164-172 (1 Phot., 8 Fig., 5 Tab., 15 Ref.) |
| 报告类型： | 科技报告 |
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