KR100378956B1 - Acoustical Vehicle Detection System - Google Patents

Abstract

The present invention relates to a traffic detection apparatus using sound. In a traffic information system for obtaining traffic information about a vehicle on a road, the sensor unit 9 measures a noise (acoustic) data of a vehicle driving on a road and converts the data 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 a road information DB 17 installed in a central control center to store and manage the traffic information data. 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.

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, in an intelligent traffic information system, a microphone is used as a sensor to convert a frequency of noise of a vehicle traveling on a road into a vehicle, and thus to speed up the vehicle. The present invention relates to a traffic detection apparatus using sound that can provide traffic information by extracting primary information such as flow volume 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 Management System (ATMS), Advanced Travel Information System (ATIS), Advanced Transportation Information System (Advanced). There are five major parts: Public Transportation System (APTS), Commercial Vehicle Operation (CVO), and 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 (controls traffic using current and DB stored information).

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.

Among the various ITS systems listed above, the system to be invented belongs to the ATMS field. The operating system of the intelligent traffic information system (ITS) is provided in the traffic information collection (S1), traffic information processing (S2), traffic information supply (S3) process as shown in FIG.

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 certain 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. ▶ Able to crack down on specific vehicles ▶ Can be used for distance measurement ▶ Easy to install ▶ 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 using a microphone as a sensor, the speed of the vehicle, the flow amount of the vehicle, etc. using the detected acoustic signal In addition, another object of the present invention is to convert a signal received through a microphone for each vehicle into a frequency domain so as to extract the sound pressure for each frequency of the existing database in the various vehicles. It is to provide a traffic detection device using a sound that can identify the vehicle type, such as large, medium or small compared to the other. Another object of the present invention by using the primary traffic information noise on the surrounding residential area Traffic using sound to extract secondary traffic information such as accuracy or road loss estimates To provide a support device.

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;

5 is a graph illustrating an example of a result of measuring vehicle noise on a time axis for detecting a vehicle speed in an embodiment of the present invention.

6 is a graph illustrating data modeling in road conditions and time domain.

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

FIG. 8 is a graph illustrating an example of a result of a state in which vehicle noise is measured about a time axis for detecting the number of vehicles in an embodiment of the present invention, but a predetermined size or less is filtered out; FIG.

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, a microphone for outputting an analog voltage signal by receiving the noise (sound) of the vehicle traveling on the road to convert the acoustic pressure fluctuation into an electrical signal; It receives analog voltage signal from the microphone and filters out unnecessary frequencies after A / D conversion, extracts primary traffic information such as vehicle speed, vehicle type, vehicle flow rate, noise level, and adds secondary estimates such as road loss estimates. A traffic information signal processor for generating information and providing traffic information data; And a road information DB installed in a central control center so as to store and manage the traffic information data of the traffic information signal processing unit, and traffic using sound applied to a traffic information system for obtaining traffic information about vehicles on the road. In the sensing device, The traffic information signal processing unit, A / D converter for converting an analog voltage signal from the microphone into a digital voltage signal; An FFT signal processor / Wavelet signal processor for receiving a digital voltage signal from the A / D converter and analyzing noise (acoustic) data using an FFT transform or a wavelet transform; In order to analyze the traffic information by receiving the frequency-converted data from the FFT signal processor / Wavelet signal processor, noise information is analyzed for each frequency, and the vehicle type is classified according to the magnitude of sound pressure, and between the vehicle and the microphone is the first position. An acoustic data analyzer for measuring primary traffic information such as measuring a vehicle speed by using a sound pressure ratio and a time delay or a Doppler effect when the second position is present; And a secondary data analyzer configured to calculate a road loss estimate using primary traffic information input from the acoustic data analyzer, and extract secondary additional information to provide the secondary information to the road information DB. According to an additional aspect of the present invention, the traffic information signal processor measures sound pressures P1 and P2 at the time t1 and t2 of the measurement vehicle to detect the speed of the vehicle, respectively. At time t1, distance r1 is measured, so at time t2, 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 It is preferable to calculate the speed of the vehicle by a function relationship of. Also, according to another additional aspect of the present invention, the traffic information signal processing unit may calculate the 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 , It is preferable to calculate the Mach number of the vehicle using the Doppler effect and then calculate the speed of the vehicle using this value. Further, according to another additional aspect of the present invention, the traffic information signal processing unit may be configured to detect the number of vehicles. A technique for calculating the number of peaks of vehicle noise from the noise spectrum of the vehicle analyzed by the FFT signal processor / Wavelet signal processor, or by removing a predetermined sound pressure or less and calculating the number of remaining parts. It is desirable to calculate the number of vehicles.

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 is composed of a microphone 9, a traffic information signal processing unit 10 which is a signal processing unit, and 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 processing unit / Wavelet signal processing unit 12 receives the digital voltage signal, filters out unnecessary frequency bands, and removes the unnecessary frequency bands, and the shape (eg, noise level) required for each information extraction unit (vehicle speed, vehicle type, flow amount). The noise signal is processed into the sound data analyzing unit 13.

The acoustic data analysis unit 13 receives the processed noise signal from the FFT signal processing unit / Wavelet signal processing unit 12 as a primary analyzer and measures the time delay of the noise signal input from the two microphones, and extracts the vehicle speed. Analyze the flow of the vehicle by analyzing the change in the noise signal size, compare the frequency shape of each noise signal, classify the vehicle type (large, medium, small), and extract the noise level by grasping the size of the noise signal. The primary traffic information of the measurement is provided to the secondary data analysis unit 14.

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.

When the acoustic data analyzer 13 measures vehicle noise on the time axis to detect the vehicle speed, the result may be represented by a graph as shown in FIG. 5.

6 illustrates modeling of road conditions and measured data in the time domain.

(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). Since noise generated from a vehicle propagates at a constant speed as sound, when two microphones are distributed in a direction in which the vehicle travels, the microphones are measured at each microphone according to a difference in sound propagation paths. There is a time delay between the noises. This time delay can be extracted from the measured noise and the speed of the vehicle can be extracted using the distance between the microphones which are already known.

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.

, In summary, when establishing a geographical relationship between the microphone and the vehicle that is the sound source, the relationship between the sound pressures P1 and P2 of the vehicle measured by each microphone is established. That is, there is a time delay D between the measured microphone signals, which can be easily obtained by looking at the correlation between the two signals. When measuring time delay, the two noise signals collected through the microphone are converted into a cross-correlation function of the two signals by a filter that calculates the magnitude of the noise, and the following theory finds the time delay. The correlation function of the two sound pressures is the same as that of one of the two autocorrelation functions in parallel with respect to the time axis, and a time delay can be obtained by using the correlation function of the two signals. When the time delay D between the two signals is found, the speed of the vehicle, that is, the sound source generating the measured noise signal, can be measured.

7 shows a graph illustrating the modeling of the vehicle noise spectrum viewed 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 calculating the number of peaks of the noise of the vehicle using the vehicle noise, or by detecting a number of remaining portions by removing the sound pressure or less. FIG. 8 is a graph illustrating an example of a result of a state in which vehicle noise is measured about a time axis for detecting the number of vehicles, but less than a predetermined size is filtered out in an embodiment of the present invention. Detection is by detecting local peaks over time in the energy shape of vehicle noise. That is, when the vehicle passes by, the energy of the noise collected by the microphone is also increased as the vehicle approaches the microphone, which is the largest when the vehicle is closest and becomes smaller as the vehicle moves further away. Therefore, the number of vehicles can be detected by finding each shape. First, the energy is found from the vehicle noise signal, and the found energy value is smoothed through the low-pass filter, so that the shape of the noise energy when the vehicle passes. Make it easy to find. If it is the shape of the vehicle noise energy, the shape of the vehicle noise energy is found by calculating the time variation of the measured vehicle noise energy at the local peak that should be obtained and finding the point where the change amount is zero. Local peaks are also found by other noise components rather than by vehicle noise. To prevent this, the local peak is a point where the amount of change occurring after the value of the change amount exceeds a certain value becomes zero. That is, only the points except for the point where the value of the change is less than the reference value is 0 is considered as the local highest point due to the vehicle noise, and the number of them is calculated to determine the number of vehicles.

(3) approximate vehicle model detection

In general, since the noise of a vehicle has a frequency characteristic according to the vehicle type, the vehicle type (large / medium / small) can be classified using the magnitude of the noise level and the frequency characteristic thereof.

(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 apparatus 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 of the vehicle. The road traffic information can be easily grasped by extracting the primary traffic information and generating secondary information such as the estimated road loss and storing the traffic information data in the road information database.

In addition, the installation and maintenance cost of the traffic detection system is inexpensive, and in addition to the traffic information on the road, the noise level around the road can be measured from the vehicle noise as a noise environment monitoring system. It is possible to monitor and obtain other useful information, and if the analysis technology is to be developed in the future, it is possible to improve the performance by simply replacing the 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)

A microphone 9 for receiving a noise (sound) of a vehicle traveling on a road and converting an acoustic pressure change into an electrical signal and outputting an analog voltage signal; It receives analog voltage signal from microphone 9 and filters out unnecessary frequency after A / D conversion, and removes primary traffic information such as vehicle speed, vehicle type (large, medium, small), flow volume of vehicle, noise level, etc. A traffic information signal processor 10 for extracting and generating secondary additional information such as an estimated road loss 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 of the traffic information signal processing unit 10, the traffic information system for obtaining traffic information for vehicles on the road. In the traffic detection device using the applied sound, The traffic information signal processor 10 includes: an A / D converter 11 for receiving an 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 12 for receiving a digital voltage signal from the A / D converter 11 and analyzing noise (acoustic) data using a fast fourier transform (FFT) or wavelet transform ); In order to analyze the traffic information by receiving the frequency-converted data from the FFT signal processing unit / Wavelet signal processing unit 12, noise information is analyzed for each frequency, and the vehicle type (large / medium / small / small) is classified according to the magnitude of the sound pressure. Acoustic data analysis for measuring primary traffic information such as measuring the speed of the vehicle using sound pressure ratio and time delay or Doppler effect between the microphones 9 at the first position and at the second position Part 13; And secondary data analysis for calculating road loss estimates using primary traffic information input from the acoustic data analysis unit 13, extracting secondary additional information, and providing the secondary additional information to the road information DB 17. Traffic detection device using the sound, characterized in that the unit (14). delete delete The method of claim 1, The traffic information signal processing unit 10 measures sound pressures P1 and P2 at the time t1 and t2 of the measurement vehicle to detect the speed of the vehicle, respectively, and the distance r1 is measured at the time t1. 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. delete