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RESEARCH ON VEHICLE DETECTION TECHNOLOGY BASED ON GEOMAGNETIC SENSOR
Wang Xianwei - PhD, Assistant Professor, Electronic Information Engineering College (Changchun University, Changchun, China); Cheng Guangliang - PhD, Assistant Professor, Electronic Information Engineering College (Changchun University, Changchun, China)
The vehicle detection process plays the key role in determining the success of intelligent transport management system solutions. Anisotropic magnetoresistance (AMR) sensors react to the magnetic fields of Earth and vehicles, whereas variation disturbances of magnetic field allow detecting the vehicles in the parking space. In this paper, we use a new vehicle detection algorithm based on AMR sensor, called the vehicle detection algorithm of adaptive state machine is presented. The algorithm can adaptively update the threshold and the baseline, uses the state machine to achieve the aim of the accurate and efficient vehicle detection. This method has good validity and feasibility of vehicle detection, vehicle identification rate.
Keywords: magnetic detection, adaptive state machine, AMR sensor, vehicle detection.
Introduction
As an important part of traffic information collection, vehicle detector has attracted more and more attention in the industry. The vehicle detector takes the motor vehicle as the detection target, detects the data of the vehicle's passing or existence condition, and provides sufficient information for the intelligent traffic control system to carry out the optimal control. There are many types of vehicle detectors in the parking lot system, mainly including ground sensor coil, microwave radar, infrared, geomagnetic, ultrasonic vehicle detector, etc.
At present, the common vehicle detectors have a certain application market, but they more or less have the disadvantages of being susceptible to environmental influence, low detection and recognition rate, difficult installation and maintenance, and high cost. In order to overcome the deficiencies of the existing detectors, meet the requirements of environmental adaptability, high
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efficiency, ease of use and high cost performance, as well as the characteristics of the application of intelligent parking system, we need to find a detector that has cost advantages and can accurately detect static vehicles.
AMR sensor based on geomagnetic sensing technology has a silicon chip with a thick coating of piezoresistive nickel-iron. The AMR effect is used in a wide array of sensors for measurement of Earth's magnetic field, for electric current measuring, for traffic detection and for linear position and angle sensing. As a new type of vehicle detector, An AMR sensor has the most outstanding advantages of small volume, high sensitivity, low cost, not easy to be affected by environment and convenient installation and maintenance. In order to achieve a higher detection success rate and lower computational complexity, based on analysis of a large amount of experimental data, we propose a vehicle detection algorithm named adaptive state machine detection algorithm.
AMR Sensor Applications
Although the earth's magnetic field varies with its location, it can be assumed that the magnitude of the magnetic field remains basically the same within a few kilometers of its radius when there is no interference from external strong magnetic factors. Periodic measurement of geomagnetic field changes in the parking space area is used to perceive the existence of ferromagnetic objects. When a vehicle appears near the geomagnetic sensor, the geomagnetic sensor module detects the geomagnetic field changes in the parking space and performs data sampling, so as to determine whether there is a car in the parking space.
The general application of magnetic sensor is interconnected by 4 AMR sensor resistance to form a typical Wheatstone bridge, so that the strength and direction of the magnetic field along a single axis can be measured. A common bridge resistance is 1kohm. For typical AMR sensors, the bandwidth is in the1 -5 MHz range. AMR sensor circuit is shown in Fig. 1.
Fig. 1. AMR sensor circuit The strength of the earth's magnetic field can be considered to be constant over a certain area. Whether a ferromagnetic object is stationary or moving, it
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RESEARCH ON VEHICLE DETECTION
TECHNOLOGY BASED ON GEOMAGNETIC SENSOR BtOHHtC TCTy. 2021. № 2 (61)
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will cause significant magnetic interference to the Earth's magnetic field within a certain range. The geomagnetic perturbation is particularly obvious at the wheel and engine of a car, where the magnetic field lines are twisted at the front and rear axles, as shown in Fig. 2. Therefore, in the data acquisition system of parking lot, the status of parking space can be determined according to the variation of magnetic field intensity detected by AMR sensor.
Fig. 2. The principle of geomagnetic detection vehicle
Method Design
The measurement of distortions of the Earth's magnetic field using ma g-netic field sensors served as the basis for designing a solution aimed at vehicle detection. The main work of the detection algorithm is to filter out the influence of the surrounding environment, serious noise and baseline drift. Therefore, an adaptive threshold vehicle detection algorithm is proposed. The original signal is filtered by means of sliding window average filtering, and the baseline and threshold are updated in real time. Combined with the finite state machine method, detection algorithm is shown in Fig. 3.
Geomagnetic Sensor
Fig. 3. Block diagram of the proposed algorithm The formula for raw geomagnetic output is shown below as:
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Ms (k) = Gs (k) + Ns (k) + Vs (k),
where the AMR sensor M5 (k) is superimposed by the background magnetic
field signal Gs (k) , interference signal N (k) and the vehicle signal Vs (k) at
moment k .
The specific algorithm steps are as follows: Step l: data filtering.
Due to the influence of ambient noise signals, there are a lot of burrs in the original signals collected by geomagnetic sensors. In order to improve the accuracy and reliability of vehicle detection system, a sliding window average filte ring method is adopted. This method can filter out the interference of high frequency noise signal and ensure the integrity and authenticity of original signal. The principle of average filtering of sliding window is as follows:
Ak )=<
M(k) + M(. 1) + •••+ M(1)
-o-(H k < N
M( k) + M(. k-i) +•••+ M(k -n+i) k>N
k
where M(k) is the original signal from the sensor output, A(k) is the filtered signal, N is the length of the sliding window filtering.
Step 2: Baseline and threshold updates.
The magnetic field changes caused by climate and road environment can't be eliminated by filtering, and will cause the drift of reference value. In order to eliminate the detection error caused by the drift of the reference value, the weight updating method is adopted, and the current baseline value is updated by the weighting function of the reference value. Function to update the base value:
\ B(k-1)(1 -a)+At)a
B(k) =)b ,
lB(k-i)
where a (=0.05) is the weighted coefficient, is base value before update,
B(t) is the base value after update, A(k) is the sampling value after sliding filtering.
In the process of updating the reference value, the threshold value also needs to be updated in real time to avoid the accumulation of errors caused by the fixed threshold value, which will lead to the reduction of the accuracy of the detection system. The expression of threshold update is as follows:
T(k) = (1 + P)B(k),
RESEARCH ON VEHICLE DETECTION TECHNOLOGY BASED ON GEOMAGNETIC SENSOR
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where f3 is the threshold update factor, ^ is the threshold value before update.
Step 3: Finite state machine.
Finite State Machine detection is to binarize the sampled signals after filtering and convert them into 0 and 1 to judge the vehicle state.
Finite-state machine detection includes: initialization state (S0), vacant state (S1), vehicle arrival count state (S2), fluctuation count state (S3), and occupied state (S4), as shown in the Fig. 4. Ideally, "1" means the parking spaces occupied and "0" means not. However, the actual traffic environment is rel a-tively complex, and there are often disturbances such as ferromagnetic substances, which leads to the misjudgment of the vehicle state. The vehicle arrival counting state (Cnt_Arr) and fluctuation counting state (Cnt_NoArr) are added in the state machine, which can effectively suppress the misjudgment caused by short-term runout and improve the vehicle detection accuracy.
Experiment and Data Process
In our experiments, we use Honeywell 3-axis magnetic sensor for vehicle detection. The sensor should be installed 1/3 from the rear of the car, 1.5 meters from the parking line, and ensure a distance of more than 1 meter from the ad-
Fk)=0&Cn t_NoArr<CN
Fk)=1
Fk)=1&Cnt_Arr<Cy
Fig. 4. Finite-state machine for vehicle state detection
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jacent parking space. On the parallel parking, the geomagnetic detector is installed on the central axis, as shown in fig. 5. When parking on the side normally, the rear axle of the vehicle is in the position of the geomagnetic sensor. The deployment of sensor nodes: The X-axis is parallel to the direction of vehicle entering, and the Y-axis is vertical to the direction of vehicle entering, the Z-axis is vertical.
Fig. 5. The parallel parking layout and the placement of AMR sensors
We deployed 4 nodes in the roadside open parking plot. This test results show that, according to the adjustment of geomagnetic threshold in the parking detection algorithm, the parking status can be accurately obtained in different experimental environments. the system has deal with the number of 1871 times of vehicle parking and above 98% of accuracy in the result as shown in Table 1.
Table 1
Vehicle detection result
ID The number of times of vehicle parking The number of times of detected vehicle parking Accuracy of the proposed algorithm
465 460 98.9%
497 488 98.2%
357 354 99.2%
552 545 98.7%
Conclusion
From the above, our experiments demonstrate that the proposed algorithm can accurately detect parking space occupancy. To Vehicle detection and parameter measurements this system is stability and has high detection accuracy. By running the system for more than a year, we observe that the vehicle detection accuracy is above 98%. This proposed system results will be significant supplement in parking space navigation, automatic parking fee to pay, management in traffic area.
RESEARCH ON VEHICLE DETECTION
TECHNOLOGY BASED ON GEOMAGNETIC SENSOR ВЕСТНИК! ТСГУ. 2021. № 2 (61)
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This paper was supported by the funds of Science Technology Department of Jilin Province, with grant numbers: 20200401146GX. Project Name: Key Technologies and Applications of Road-Occupying Parking System Based on NB-IoT Geomagnetic Detection.
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Заглавие: Исследования технологии обнаружения автомобилей на основе геомагнитного датчика
Авторы:
Ван Сяньвэй - Чанчуньский университет, Чанчунь, КНР Чэн Гуанлян - Чанчуньский университет, Чанчунь, КНР
ВЕСТНИК ТОГУ. 2021. № 2(61)
Аннотация: Процесс обнаружения транспортных средств играет ключевую роль в интеллектуальных системах управления транспортом. Датчики анизотропного магнитосопротивления (AMR) реагируют на магнитные поля Земли и транспортных средств, тогда как колебательные возмущения магнитного поля позволяют обнаруживать транспортные средства на парковочном месте. В этой статье используется новый алгоритм обнаружения транспортных средств, основанный на датчике AMR, который называется алгоритмом обнаружения транспортных средств с использованием адаптивного конечного автомата. Алгоритм может адаптивно обновлять порог и базовый уровень. Конечный автомат позволяет повысить эффективность обнаружения транспортных средств.
Ключевые слова: геомагнитный датчик, адаптивный конечный автомат, датчик AMR, обнаружение транспортных средств.
