Project

Use of single inductive loop sensor for vehicle classification

Project (M.S., Electrical and Electronic Engineering)--California State University, Sacramento, 2018.

One of the most crucial parameters for traffic measurement is vehicle classification. Currently, several different methods for analyzing and interpreting vehicle classification exist: magnetics, magnetometer sensors and inductive loops [1] are just a few of the most common sensor technologies utilized. However, inductive-loop sensors have been the preferred method for the last fifty years mainly because of their flexibility, standardization, and cost. The common method for inductive-loop sensors is to use two or three loops to detect the speed and class of a vehicle. The future goal of this project is to reduce the system to a single inductive loop sensor that can be used for vehicle classification. The advantages of using a single-loop over multiple-loop system are cost effectiveness, simplicity, and speed. For this project, different classes of vehicles have been simulated in HFSS. First, the background of the project is introduced and the Inductive-loop theory is presented. Alternative designs of the inductive-loop detectors, analysis of both small-area and large-area designs are discussed. Further, the sensitivity of varying sizes of loops has been simulated and the self-inductance of different loops has also been discussed to discover the most effective method. MATLAB and HFSS simulations and analysis of different classes of vehicles above the inductive loop have also been carried out. Finally, the changing of the inductance of the loop has been conducted in HFSS and the results have been compared with previously published data and raw signatures gained from the real road test.

One of the most crucial parameters for traffic measurement is vehicle classification. Currently, several different methods for analyzing and interpreting vehicle classification exist: magnetics, magnetometer sensors and inductive loops [1] are just a few of the most common sensor technologies utilized. However, inductive-loop sensors have been the preferred method for the last fifty years mainly because of their flexibility, standardization, and cost. The common method for inductive-loop sensors is to use two or three loops to detect the speed and class of a vehicle. The future goal of this project is to reduce the system to a single inductive loop sensor that can be used for vehicle classification. The advantages of using a single-loop over multiple-loop system are cost effectiveness, simplicity, and speed. For this project, different classes of vehicles have been simulated in HFSS. First, the background of the project is introduced and the Inductive-loop theory is presented. Alternative designs of the inductive-loop detectors, analysis of both small-area and large-area designs are discussed. Further, the sensitivity of varying sizes of loops has been simulated and the self-inductance of different loops has also been discussed to discover the most effective method. MATLAB and HFSS simulations and analysis of different classes of vehicles above the inductive loop have also been carried out. Finally, the changing of the inductance of the loop has been conducted in HFSS and the results have been compared with previously published data and raw signatures gained from the real road test.

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