RT Journal Article
T1 Research of distorted vehicle magnetic signatures recognitions, for length estimation in real traffic conditions
A1 Miklusis, Donatas
A1 Markevicius, Vytautas
A1 Navikas, Dangirutis
A1 Cepenas, Mindaugas
A1 Balamutas, Juozas
A1 Valinevicius, Algimantas
A1 Zilys, Mindaugas
A1 Cuiñas Gómez, Íñigo
A1 Klimenta, Dardan
A1 Andriukaitis, Darius
K1 3327 Tecnología de Los Sistemas de Transporte
K1 3317.10 Ingeniería del Tráfico
K1 3325 Tecnología de las Telecomunicaciones
AB Reliable cost-effective traffic monitoring stations are a key component of intelligent transportation systems (ITS). While modern surveillance camera systems provide a high amount of data, due to high installation price or invasion of drivers’ personal privacy, they are not the right technology. Therefore, in this paper we introduce a traffic flow parameterization system, using a built-in pavement sensing hub of a pair of AMR (anisotropic magneto resistance) magnetic field and MEMS (micro-electromechanical system) accelerometer sensors. In comparison with inductive loops, AMR magnetic sensors are significantly cheaper, have lower installation price and cause less intrusion to the road. The developed system uses magnetic signature to estimate vehicle speed and length. While speed is obtained from the cross-correlation method, a novel vehicle length estimation algorithm based on characterization of the derivative of magnetic signature is presented. The influence of signature filtering, derivative step and threshold parameter on estimated length is investigated. Further, accelerometer sensors are employed to detect when the wheel of vehicle passes directly over the sensor, which cause distorted magnetic signatures. Results show that even distorted signatures can be used for speed estimation, but it must be treated with a more robust method. The database during the real-word traffic and hazard environmental condition was collected over a 0.5-year period and used for method validation.
PB Sensors
SN 14248220
YR 2021
FD 2021-11-26
LK http://hdl.handle.net/11093/2874
UL http://hdl.handle.net/11093/2874
LA eng
NO Sensors, 21(23): 7872 (2021)
NO Lietuvos Mokslo Taryba | Ref. S-MIP-21-34
DS Investigo
RD 28-sep-2023