KR20000018253A - Acoustical Vehicle Detection System - Google Patents

Abstract

PURPOSE: A transportation sensing device using a sound is provided to easily know road transportation information by storing transportation information data in road information database and monitor noise of a road circumference without a special noise measuring device. CONSTITUTION: A transportation sensing device comprises a sensor for converting measured noise (sound) data of a vehicle running on the road into an analog voltage signal, a transportation signal processor for supplying transportation information data by extracting first transportation information and generating a second additional information, and road information database installed in a central control management center to store and manage the transportation information data.

Description

Traffic detection device using sound {Acoustical Vehicle Detection System}

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to an acoustic vehicle detection system (AVDS) using sound. In particular, an intelligent traffic information system uses a microphone as a sensor to convert a frequency of a noise detected spectrum of a vehicle traveling on a road into a vehicle. The present invention relates to a traffic detection apparatus using sound that can provide traffic information by extracting primary information such as speed, vehicle flow rate, and vehicle type, and extracting secondary incidental information such as estimated road loss.

Generally, the technical fields of Intelligent Transportation System (ITS) are Advanced Transportation System (ATMS), Advanced Travel Information System (ATIS), and Advanced Public Information System (ATIS). There are five major parts: the Transportation System (APTS), the Commercial Vehicle Operation (CVO), and the Advanced Vehicle and Highway System (AVHS).

The advanced traffic management system (ATMS) manages and controls traffic on all existing roads, and automatically recognizes driving vehicles to maximize traffic flow (sensor technology + application database (storage of collected information) + traffic control S). / W (control traffic using the current degree and information stored in the database).

The advanced traffic information system (ATIS) provides the driver with various traffic information according to the travel plan and provides alternative routes, thereby providing advanced traffic information so that the trip is stable, efficient and convenient.

The public transportation information system (APTS) provides real-time traffic information (arrival, travel time, transfer, route, dispatch information, etc.) to passengers in the car and waiting passengers.

The advanced logistics management system (CVO) tracks and manages the operation of freight vehicles to enable efficient logistics management and dangerous goods vehicle management.

The advanced vehicle road system (AVHS) provides artificial intelligence to vehicles and roads to enable safe driving and automatic driving, and to prevent vehicle collisions, auto-adjust vehicle intervals, vehicle clustering, unmanned safety roads, and the like.

If one of the various types of ITS systems listed above is listed as part of the ATMS or ATMS of the system to be invented, the operating system of the intelligent traffic information system (ITS) is shown in FIG. 1. ), Traffic information processing (S2), traffic information supply (S3) process is provided.

Each piece of information obtained from the information collection unit is processed to process information such as vehicle speed, flow rate, vehicle type, occupancy rate, queue, etc. on the road and transmitted to the central control center, and the central control center can respond appropriately to the situation.

The composition of the ITS operating system to be invented is related to the collection of traffic information and the processing of traffic information. The existing technologies of the sensor unit corresponding to the collection of traffic information are described in Table 1 below.

Detection method Explanation Advantages Disadvantages Radar detector ▶ Detection using a radar Multi-lane measurement ▶ Difficulty cracking down on specific vehicles ▶ Affected by radio waves and other radar waves Laser detector ▶ Detection using laser ▶ Easy to install and repair ▶ Install 1 lane 1 device ▶ Please check Video detector ▶ It is a system to get necessary traffic information using emotion of change of video screen. In other words, the sensor collects information by detecting a change in the pixel on the screen. ▶ Possible to crack down on a specific vehicle ▶ Easy to install when measuring distance ▶ Influenced by weather conditions such as climate. ▶ Error such as gradient Loop detector ▶ By installing circular or rectangular roof coils of the road, when the vehicle passes over the roof coils, it detects the change in the strength of the magnetic field generated in the coils and collects the road information. ▶ Less influence on environment changes such as time zone and weather ▶ Possible to detect other traffic variables ▶ Difficult to maintain

By processing each piece of information obtained from the information collection unit, information such as vehicle speed on the road, vehicle flow rate, vehicle type, occupancy rate, queue, etc. is processed and transmitted to the central control center so that it can cope with traffic conditions. .

However, in the existing traffic information system, the sensor technology has a problem in that it is costly at the time of installation as well as maintenance and change of the installation location.

The present invention has been proposed to solve the above problems of the prior art, an object of the present invention is to detect the noise (acoustics) using a microphone as a sensor in an intelligent traffic information system, and then A / D converting the high-speed Fourier ( Analyze the frequency spectrum using FFT and Wavelet transforms to extract primary traffic information such as vehicle speed, vehicle flow rate, vehicle type (large, medium and small), and road noise level. Secondary traffic information, such as the estimated road loss, can be extracted, and the traffic detection device using the sound which is easy to install, easy to change the installation location, and low in maintenance cost at low cost.

1 is a flowchart illustrating an operating system of a conventional intelligent traffic information system (ITS).

2 is a conceptual diagram of a traffic detection apparatus using sound according to the present invention;

3 is a system configuration diagram of a traffic detection apparatus using sound according to an embodiment of the present invention.

4 is a conceptual diagram for explaining the principle of a condenser microphone;

Figure 5 is a graph of measuring the spectrum of the vehicle noise on the time axis for detecting the speed of the vehicle in the acoustic data analysis unit.

6 is a graph illustrating modeling of road conditions and measurement spectra.

7 is a graph illustrating modeling of a vehicle noise spectrum seen from a frequency axis.

8 is a vehicle noise spectrum.

Explanation of symbols on the main parts of the drawings

9: microphone (sensor) 10: traffic information signal processing unit

11: A / D converter 12: FFT signal processor / Wavelet signal processor

13: acoustic data analysis unit 14: secondary data analysis unit

17: road information DB

ITS: Intelligent Transportation System

In order to achieve the above object, the present invention provides a traffic information system for obtaining traffic information on a vehicle on a road: a sensor unit for measuring noise (acoustic) data of a vehicle traveling on a road and converting the signal into an analog voltage signal (9). ); After receiving the analog voltage signal, A / D conversion and frequency conversion are used to extract the primary traffic information such as vehicle speed, vehicle type (large, medium, small), vehicle flow rate, noise level, etc. A traffic information signal processor 10 for generating additional information and providing traffic information data; And a road information DB 17 installed in a central control center to store and manage the traffic information data.

Hereinafter, exemplary embodiments of the present invention will be described in detail with reference to the accompanying drawings.

2 is a traffic detection system using sound according to the present invention, which is composed of a microphone 9, a traffic information signal processing unit 10 which is a signal processing unit, and a road information DB 17 of a central control center.

3 is a system of a traffic detection apparatus using sound according to an embodiment of the present invention includes a microphone 9, a traffic information signal processor 10, and a road information DB 17.

The traffic information signal processor 10 includes an A / D converter 11, an FFT signal processor / Wavelet signal processor 12, an acoustic data analyzer 13, and a secondary data analyzer 14.

The microphone 9 measures noise (acoustic) data of a vehicle traveling on a road, converts the data into an analog voltage signal, and provides the same to the A / D converter 11.

The A / D converter 11 receives the analog voltage signal from the microphone 9, converts the analog voltage signal into a digital voltage signal, and provides it to the FFT signal processor / Wavelet signal processor 12.

The FFT signal processor / Wavelet signal processor 12 receives the digital voltage signal and analyzes noise (acoustic) data by using a fast fourier transform (FFT) or wavelet transform. 13) to provide.

The acoustic data analysis unit 13 receives the frequency-converted data from the FFT signal processing unit / Wavelet signal processing unit 12 as a primary analyzer, and analyzes the noise information as the magnitude and frequency of sound pressure to analyze traffic information. By using the Doppler effect to determine the speed of the vehicle, and to measure the primary traffic information, such as the flow volume of the vehicle, the vehicle type (large, medium, small) and the noise level to the secondary data analysis unit 14 to provide.

The secondary data analysis unit 14 provides secondary road information, such as a road loss estimate and a speed violation, to the road information DB 17 using the primary traffic information as a secondary analyzer.

The administrator of the central control center detects the traffic information situation of the road information DB 17 by the application and takes appropriate measures.

4 is a conceptual diagram for explaining the principle of a condenser microphone.

The microphone 9 is a device for converting an acoustic pressure change into an electrical signal and used as a sensor capable of detecting sound. The principle of this microphone is as follows. I will explain the selection of commonly used condenser microphones.

In the condenser microphone, as shown in FIG. 4, when positive and negative power are connected between positively spaced positive poles, charge is accumulated between the positive poles. If one of the positive and negative poles (B) is fixed and the other side (A) is connected to the diaphragm, the vibration of air caused by sound (negative pressure) causes the diaphragm to vibrate. The distance is changed to change the amount of charge stored, and thus the voltage between the anodes is changed. In other words, the sound (sound pressure) is turned into an electrical signal.

The acoustic data analyzer 13 measures the spectrum of the vehicle noise on the time axis to detect the speed of the vehicle, and is represented by a graph as shown in FIG. 5.

6 illustrates modeling of road conditions and measurement spectra.

(1) vehicle speed measurement

Iii) The closest straight line distance r1 between the vehicle and the microphone is assumed to be known (since it depends on the distance the microphone is installed, since the distance is almost constant along the lane).

Ii) In theory, the magnitude of sound, ie the magnitude of sound pressure, is inversely proportional to distance. This is the case under ideal conditions (no reflection, no damping by the medium, etc.), which is different from actual road conditions. However, it can be assumed that some functional relationship exists between the distance and the decay of sound pressure, and the ratio of distance can be considered as a function of the decay rate of sound pressure.

(Measurement speed of vehicle 1)

Ⅰ) Find the ratio of distance r1 and r2 by the ratio of sound pressure P1 and P2.

In other words,

Ii) Since r1 is already known, r2 can be found.

I) Since r1 and r2 are known, the distance r3 traveled by the car between the times t1 and t2 can be obtained by the Pythagorean theorem.

속도) Velocity is a function of time and distance, and since both time and distance are found, velocity can be found.

,

7 shows a graph illustrating the modeling of the vehicle noise spectrum seen from the frequency axis.

(Vehicle speed measurement method 2)

I) The frequency change due to the Doppler effect is expressed as follows.

Where MS is the speed of the source (Mach number), θ is the angle between the measuring point and the source,

fa: frequency of the measured sound, fs: frequency of the original source)

Thus, if we know the ratio between the original frequency and the measured frequency, and θ, we can know the speed.

Ii) The ratio of the original frequency and the measured frequency can be obtained by using a wavelet transform or a fast Fourier transform. However, the value of the original frequency is the highest at the sound pressure. Value, because it is at the closest position to the microphone, and thus the value of θ becomes 90 degrees.)

I) In the case of θ value, as in Method 1, the ratio between r1 and r2 can be obtained, so that the cosθ value can be obtained.

Iii) Therefore, the Mach number of the vehicle can be obtained using the Doppler effect, and the speed of the vehicle can be obtained using the Doppler effect.

(2) detection of the number of vehicles

The number of vehicles can be detected by using the vehicle noise spectrum as shown in FIG. 8 to calculate the number of peaks of the vehicle's noise, or by removing a predetermined sound pressure or less and calculating the number of remaining parts. It is detected by the method.

(3) approximate vehicle model detection

The vehicle type (large / medium / small) can be classified using the magnitude of the noise level and its frequency characteristic.

(4) road noise monitoring

Knowing the sound pressure of the noise, the peak and average values of the noise around the road can be obtained.

The secondary data analysis unit 14 is not a necessary part of the traffic information signal processing unit 10, and is a part which does not need to be located at the site where the microphone 9 is located. The acoustic data analyzing unit 13 processes information that can be processed only when all parts of the data measured by the microphone 9 are complete, whereas the secondary data analyzing unit 14 which is a secondary analyzer is the primary analyzer. It is a device which grasps the situation of the road using some simple information, such as the speed of the vehicle, the flow amount of the vehicle, and the model of the vehicle, obtained by the data analyzing unit 13.

Therefore, by measuring the noise (acoustic) data of the vehicle using a low-cost microphone as a sensor, it extracts the primary traffic information such as the speed of the vehicle, the type of vehicle, and the flow of the vehicle, and collects secondary additional information such as the estimated road loss. By generating and storing the traffic information data in the road information database, the road traffic information can be easily identified.

As described above, the traffic detection device using the sound according to the present invention measures the noise (acoustic) data of the vehicle using a low-cost microphone as a sensor to measure the speed and type of vehicle, the flow rate of the vehicle, etc. from the noise spectrum of the vehicle. The road traffic information can be easily grasped by extracting the primary traffic information and storing the traffic information data in the road information database.

In addition, the installation and maintenance cost of the traffic detection system is low, and in addition to the traffic information on the road, the noise level around the road can be measured from the vehicle creepy spectrum as a noise environment monitoring system. Noise can be monitored and other useful information can be obtained, and if the analysis technology is to be developed in the future, it is possible to improve the performance by simply replacing software without replacing external sensor equipment such as a microphone.

Although the above has been described with reference to a preferred embodiment of the present invention, those skilled in the art will be able to variously modify and change the present invention without departing from the spirit and scope of the invention as set forth in the claims below. It will be appreciated.

Claims (7)

In a traffic information system to get traffic information for vehicles on the road: A sensor unit 9 measuring noise (acoustic) data of a vehicle traveling on a road and converting the signal into an analog voltage signal; After receiving the analog voltage signal, A / D conversion and frequency conversion are used to extract the primary traffic information such as vehicle speed, vehicle type (large, medium, small), vehicle flow rate, noise level, etc. A traffic information signal processor 10 for generating additional information and providing traffic information data; And Traffic detection device using the sound, characterized in that consisting of a road information DB (17) installed in the central control center to store and manage the traffic information data. The method of claim 1, The traffic information signal processor 10 An A / D converter 11 for receiving the analog voltage signal from the microphone 9 and converting the analog voltage signal into a digital voltage signal; An FFT signal processor / Wavelet signal processor for receiving the digital voltage signal from the A / D converter 11 and analyzing noise (acoustic) data using a fast fourier transform (FFT) or wavelet transform ( 12); In order to analyze the traffic information by receiving the frequency-converted data from the FFT signal processor / Wavelet signal processor 12, the noise information is analyzed for each frequency, and the vehicle is classified using the Doppler effect by using the Doppler effect. An acoustic data analysis unit 13 for measuring the primary traffic information such as large / medium / small); And Secondary data analysis unit 14 for providing secondary roadside information, such as a road loss estimate and a speed violation, to the road information DB 17 by using the primary traffic information from the acoustic data analysis unit 13. Traffic detection device using a sound, characterized in that consisting of. The method of claim 1, The sensor unit 9 is a device that converts acoustic pressure fluctuations into an electrical signal to obtain traffic information, and is a sensor capable of detecting sound. The sensor unit 9 uses the microphone 9 to measure noise or acoustic data of a vehicle. Traffic detection device using the sound, characterized in that. The method of claim 1, The traffic information signal processor 10 measures the sound pressures P1 and P2 at the times t1 and t2 of the measurement vehicle to detect the speed of the vehicle, respectively. Calculated by the function relationship and the distance between tl time and t2 time Find the speed of the vehicle by the formula ,In other words Traffic detection apparatus using the sound, characterized in that for calculating the speed of the vehicle by the function relationship. The method of claim 1, The traffic information signal processor 10 formulates a frequency change due to the Doppler effect. Where MS is the speed of the source (vehicle), θ is the angle between the measurement point and the source, fa is the frequency of the measured sound, and fs is the frequency of the original source. The cosθ value can be calculated by obtaining the ratio (fs / fa) between the original frequency and the measured frequency by the Wavelet transform or the Fast Fourier transform, and calculating the value of θ by the ratio between r1 and r2. So that means , The Mach number of the vehicle is calculated using the Doppler effect, and then the speed of the vehicle is calculated using this value. The method of claim 1, The traffic information signal processing unit 10 calculates and obtains the number of peak values of the vehicle noise from the noise spectrum of the vehicle analyzed by the FFT signal processing unit / Wavelet signal processing unit 12 to detect the number of vehicles, or Traffic detection device using the sound, characterized in that to calculate the number of vehicles by removing the predetermined sound pressure (Sound pressure) or less and the number of remaining parts. The method of claim 1, The traffic information signal processing unit 10 extracts a sound pressure value analyzed from the noise spectrum of the vehicle by detecting a noise level for detecting the vehicle type, and uses a predetermined predetermined classification value by using the magnitude and characteristics of the noise level. Traffic detection device using the sound, characterized in that for determining the vehicle type (large / medium / small).