JP5784173B2 - Vehicle judgment system - Google Patents

Description

  The present invention relates to a system for determining whether or not an object traveling on a traffic path is a vehicle.

In an ETC (Electronic Toll Collection System) lane installed at the entrance and exit of a toll road, there is a system for detecting a vehicle and discriminating a vehicle type in order to manage the vehicle passing therethrough. ETC is a registered trademark (the same applies hereinafter).
In such a system, for example, the passage of an object is detected by detecting light shielding due to the passage of the object using a transmissive optical sensor. Further, for example, by using an axle sensor embedded in a road, it is detected whether or not the object passed is a vehicle, the number of axles, and the like.
Since the optical sensor on the transmission side detects the passage of an object based on the presence or absence of light shielding, it does not know whether the object is a vehicle.
Further, since the axle sensor is embedded in the road, the installation cost becomes high.
Further, it is impossible to detect the parallel running of the two-wheeled vehicle.

JP 2003-263698 A Japanese Patent Laid-Open No. 11-120480 JP 2005-114588 A JP 2003-263698 A JP 2006-107064 A Japanese Patent Laid-Open No. 10-21437

  An object of the present invention is to determine and count a two-wheeled vehicle and a vehicle that is not a two-wheeled vehicle among objects passing through a road.

A vehicle determination system according to the present invention includes:
In a vehicle determination system for detecting a vehicle passing through a roadway,
The vehicle determination system includes a three-dimensional shape storage unit, a three-dimensional shape measurement device, a vehicle determination unit, and an object counting unit,
The three-dimensional shape storage unit stores a three-dimensional shape of each of a plurality of objects including a two-wheeled vehicle, a vehicle that is not a two-wheeled vehicle, and an object that is not a vehicle,
The three-dimensional shape measuring apparatus measures a three-dimensional shape of an object passing through the passage,
The vehicle determination unit compares the three-dimensional shape measured by the three-dimensional shape measurement device with each of a plurality of three-dimensional shapes stored in the three-dimensional shape storage unit, and measures the three-dimensional shape measurement device. Determine whether the three-dimensional shape is a motorcycle, a vehicle that is not a motorcycle, or an object that is not a vehicle,
The object counting unit counts the number of two-wheeled vehicles that pass through the road and the number of vehicles that are not two-wheeled vehicles among the vehicles that pass through the road based on the determination result of the vehicle determining unit. And

  According to the vehicle determination system according to the present invention, it is possible to determine and count a two-wheeled vehicle and a vehicle that is not a two-wheeled vehicle among objects passing through a traffic path.

FIG. 3 is a perspective view showing an example of an appearance of a traffic vehicle management system 800 in the first embodiment. 1 is a system configuration diagram illustrating an example of an overall configuration of a traffic vehicle management system 800 according to Embodiment 1. FIG. FIG. 2 is a block configuration diagram showing an example of a configuration of a three-dimensional shape measuring apparatus 100 in the first embodiment. FIG. 3 is a block configuration diagram illustrating an example of a block configuration of the sensor device 110 according to the first embodiment. FIG. 3 is a side sectional view showing an example of the structure of the radiation optical system 120 in the sensor device 110 according to the first embodiment. FIG. 4 is a side sectional view showing an example of the structure of the light receiving optical system 130 in the sensor device 110 according to the first embodiment. FIG. 3 is a front view showing an example of arrangement of sensor devices 110a to 110c of the three-dimensional shape measuring apparatus 100a in the first embodiment. FIG. 3 is a front view showing an example of arrangement of sensor devices 110a to 110c of the three-dimensional shape measuring apparatus 100a in the first embodiment. FIG. 3 is a block configuration diagram illustrating an example of a configuration of an object shape calculation device 150 according to the first embodiment. FIG. 6 is a diagram illustrating an example of a cross-sectional shape calculated by a cross-sectional shape calculating unit 151 according to the first embodiment. FIG. 6 is a diagram illustrating an example of a cross-sectional shape calculated by a cross-sectional shape calculating unit 151 according to the first embodiment. FIG. 6 is a flowchart showing an example of a flow of a cross-sectional shape calculation process S610 in the first embodiment. FIG. 4 is a flowchart showing an example of a flow of a three-dimensional shape calculation process S620 in the first embodiment. FIG. 3 is a block configuration diagram showing an example of a configuration of a vehicle determination unit 210 in the first embodiment. FIG. 4 is a diagram illustrating an example of a three-dimensional shape stored in a three-dimensional shape storage unit 211 in the first embodiment. FIG. 4 is a diagram illustrating an example of a three-dimensional shape stored in a three-dimensional shape storage unit 211 in the first embodiment. FIG. 4 is a diagram illustrating an example of a three-dimensional shape stored in a three-dimensional shape storage unit 211 in the first embodiment. The flowchart figure which shows an example of the flow of vehicle determination process S630 in Embodiment 1. FIG. FIG. 6 is a flowchart showing an example of a flow of entrance management processing S640 in the first embodiment. FIG. 6 is a flowchart showing an example of a flow of exit management processing S660 in the first embodiment. FIG. 6 is a perspective view showing an example of the appearance of a traffic vehicle management system 800 in a second embodiment. The front view which shows an example of arrangement | positioning of sensor apparatus 110a, 110b of the three-dimensional shape measuring apparatus 100a in Embodiment 2. FIG. The front view which shows an example of arrangement | positioning of sensor apparatus 110a, 110b of the three-dimensional shape measuring apparatus 100a in Embodiment 2. FIG. FIG. 10 is a system configuration diagram illustrating an example of an overall configuration of a traffic vehicle management system 800 according to a third embodiment. FIG. 11 is a block configuration diagram showing an example of a configuration of a charge category calculation unit 260 in the third embodiment.

Embodiment 1 FIG.
The first embodiment will be described with reference to FIGS.

FIG. 1 is a perspective view showing an example of the appearance of a traffic vehicle management system 800 in this embodiment.
A traffic vehicle management system 800 (traffic object management system) is a system that manages vehicles traveling on a traffic path 801. The traffic vehicle management system 800 manages vehicles existing in the management range 810 in the traffic path 801. The direction in which the vehicle traveling on the road 801 travels is called the z direction, the direction perpendicular to the z direction to the right is called the x direction, and the upward direction is called the y direction. Also, the reverse direction of each direction is expressed by adding “-” to the head. That is, the direction in which the vehicle enters is referred to as “−z direction”, the direction perpendicular to the left with respect to the z direction is referred to as “−x direction”, and the downward direction is referred to as “−y direction”.
There are islands 802 on both sides of the road 801. Note that an island located on the left side (−x direction) of the road 801 is called an island 802a, and an island located on the right side (x direction) is called an island 802b. Hereinafter, similarly, when there are a plurality of elements having the same reference numerals, there may be cases where the reference numerals are followed by a lower case alphabet.
The island 802 is one step higher than the passage 801 so that the vehicle cannot pass. Therefore, the vehicle passes through the entrance 811 or the exit 812 and enters the management range 810 or leaves the management range 810. In principle, the vehicle enters the management range 810 from the entrance 811 (lane inlet) and exits from the outlet 812 (lane outlet).
On the island 802, four pillars 803, a driving device 410, and a blocking bar 420 are provided. A total of six sensor devices 110 are provided on the four pillars 803.
Of the four columns 803, two columns 803 a and 803 b are provided on both sides of the inlet 811. Two sensor devices 110a and 110c are provided on the left column 803a. One sensor device 110b is provided on the right column 803b.
The remaining two pillars 803d and 803e are provided on both sides of the outlet 812. Two sensor devices 110d and 110f are provided on the left column 803d. One sensor device 110e is provided on the right column 803e.
The blocking bar 420 is provided at the end of the outlet 812. The driving device 410 opens and closes the blocking bar 420. When the vehicle does not exist within the management range 810, the blocking bar 420 is closed to block the outlet 812 and prevent the vehicle from entering in the reverse direction from the outlet 812.

FIG. 2 is a system configuration diagram showing an example of the overall configuration of the passing vehicle management system 800 in this embodiment.
The traffic vehicle management system 800 includes two three-dimensional shape measuring devices 100, a management device 200, a communication device 300, and an exit blocking device 400.

The two three-dimensional shape measuring apparatuses 100 (laser type vehicle detectors) measure the three-dimensional shape and the traveling direction of an object passing through the passage 801.
The three-dimensional shape measuring apparatus 100a (entrance three-dimensional shape measuring apparatus) includes three sensor devices 110a to 110c provided at the inlet 811. The three-dimensional shape measuring apparatus 100a measures the three-dimensional shape and the traveling direction of an object passing through the entrance 811 using the three sensor devices 110a to 110c. Hereinafter, the three-dimensional shape measured by the three-dimensional shape measuring apparatus 100a is referred to as an inlet three-dimensional shape.
The three-dimensional shape measuring apparatus 100b (exit three-dimensional shape measuring apparatus) includes three sensor devices 110d to 110f provided at the outlet 812. The three-dimensional shape measuring apparatus 100b measures the three-dimensional shape and the traveling direction of an object passing through the outlet 812 using the three sensor devices 110d to 110f. Hereinafter, the three-dimensional shape measured by the three-dimensional shape measuring apparatus 100b is referred to as an outlet three-dimensional shape.

The management device 200 manages vehicles existing in the management range 810 based on the three-dimensional shape and the traveling direction of the object measured by the two three-dimensional shape measurement devices 100.
The management device 200 includes a vehicle determination unit 210, an in-passage object shape storage unit 220, a reverse object determination unit 230, a passing object determination unit 240, and an in-passage object counting unit 250.

The management device 200 is a computer, for example. The management device 200 includes a processing device, a storage device, an input device, and an output device that are not shown. The processing device processes data by executing a program stored in the storage device, and controls the entire computer. The storage device stores a program executed by the processing device and data processed by the processing device. The input device inputs a signal from outside the computer and converts the input signal into data in a format that can be processed by the processing device. The data converted by the input device may be processed directly by the processing device, or may be temporarily stored by the storage device. The output device converts the data processed by the processing device and the data stored in the storage device into a signal format to be output to the outside of the computer, and outputs the converted signal to the outside.
The functions of the blocks such as the vehicle determination unit 210 shown in this figure are realized by the processing device executing the program stored in the storage device. A part or all of some or all of the blocks such as the vehicle determination unit 210 may be realized by hardware other than a computer such as an electronic circuit or a device such as an analog circuit or a digital circuit.

When the traveling direction of the object measured by the three-dimensional shape measurement apparatus 100a is the z direction (that is, the direction in which the object enters the management range 810), the vehicle determination unit 210 (vehicle determination apparatus) is the three-dimensional shape measurement apparatus 100a. Whether or not the object observed by the three-dimensional shape measuring apparatus 100a is a vehicle is determined based on the measured three-dimensional shape of the entrance.
For example, the vehicle determination unit 210 inputs a signal indicating the traveling direction of the object and the entrance 3D shape measured by the 3D shape measurement apparatus 100a using the input device. The vehicle determination unit 210 uses the processing device to determine whether the traveling direction represented by the input signal is the z direction or the −z direction. When the traveling direction is the z direction, the vehicle determination unit 210 uses the processing device to determine whether the three-dimensional shape of the entrance represented by the input signal is the shape of the vehicle or the shape of an object other than the vehicle such as a human. Determine.
The vehicle determination unit 210 may be configured not only to determine whether or not the object is a vehicle, but also to determine the vehicle type, vehicle length, vehicle height, vehicle width, number of axles, and the like when the object is a vehicle. .

  The object shape storage unit 220 in the passage (object shape storage device in the passage) is measured by the three-dimensional shape measurement device 100a when the vehicle determination unit 210 determines that the object observed by the three-dimensional shape measurement device 100a is a vehicle. The three-dimensional shape of the inlet is stored as the object shape in the passage. For example, the in-passage object shape storage unit 220 uses the storage device to convert data representing the entrance three-dimensional shape (hereinafter referred to as “entrance three-dimensional shape data”) into data representing the in-passage object shape (hereinafter “passage”). It is called “internal object shape data”).

  In the reverse object determination unit 230 (reverse object determination device), the traveling direction of the object measured by the three-dimensional shape measuring apparatus 100a is the -z direction (that is, the direction in which the object moves backward from the management range 810). In some cases, it is determined whether or not a three-dimensional shape that matches the three-dimensional shape of the entrance measured by the three-dimensional shape measuring apparatus 100a is in the object shape in the passage stored in the object shape storage unit 220 in the passage. That is, in the reverse object determination unit 230, the object that has run backward from the management range 810 is the same object as any of the objects that the object shape storage unit 220 stores the object shape in the passage. It is determined whether or not.

  For example, the reverse object determination unit 230 inputs a signal representing the traveling direction of the object and the entrance three-dimensional shape measured by the three-dimensional shape measuring apparatus 100a. The reverse object determination unit 230 uses the processing device to determine whether the traveling direction represented by the input signal is the z direction or the −z direction. When the traveling direction is the −z direction, the reverse object determination unit 230 determines the object shape in the passage represented by the three-dimensional shape of the entrance represented by the input signal and the object shape data in the passage stored in the object shape storage unit 220 in the passage. Based on the above, the processing device is used to compare the object shape in the passage and the three-dimensional shape of the entrance, and calculate the degree of coincidence indicating how much they match. The reverse object determination unit 230 uses the processing device to determine the highest matching degree from the calculated matching degrees. The reverse object determination unit 230 uses the processing device to compare the determined degree of coincidence with a predetermined threshold value. When the degree of coincidence is greater than or equal to the threshold value, the reverse object determination unit 230 determines that the object shape in the passage corresponding to the degree of coincidence matches the entrance three-dimensional shape using the processing device. When the degree of coincidence is less than the threshold value, the reverse object determination unit 230 uses the processing device to match the three-dimensional shape of the entrance among the object shapes in the passage stored in the object shape storage unit 220 in the passage. Judge that it does not exist.

  The reverse object determination unit 230 determines that the object shape in the passage stored in the object shape storage unit 220 in the passage includes a three-dimensional shape that matches the three-dimensional shape of the entrance measured by the three-dimensional shape measuring apparatus 100a. In this case, it means that the object has run backward from within the management range 810. The in-passage object shape storage unit 220 deletes the in-passage object shape determined by the reverse object determination unit 230. For example, the in-passage object shape storage unit 220 uses the processing device to delete the in-passage object shape data representing the in-passage object shape determined by the reverse object determination unit 230 from the stored in-passage object shape data. .

The passing object determination unit 240 (passing object determination device) measures the three-dimensional shape when the traveling direction of the object measured by the three-dimensional shape measurement apparatus 100b is the z direction (that is, the direction in which the object exits from the management range 810). It is determined whether or not a three-dimensional shape that matches the three-dimensional shape of the outlet measured by the apparatus 100b is in the object shape in the passage stored in the object shape storage unit 220 in the passage. That is, the passing object determination unit 240 determines whether or not the object that has left the management range 810 is the same object as any of the objects that the object shape storage unit 220 stores the object shape in the passage. To do.
For example, the passing object determination unit 240 inputs a signal representing the traveling direction of the object and the exit three-dimensional shape measured by the three-dimensional shape measuring apparatus 100b. The passing object determination unit 240 uses the processing device to determine whether the traveling direction represented by the input signal is the z direction or the −z direction. When the traveling direction is the z direction, the passing object determination unit 240 converts the three-dimensional shape of the exit represented by the input signal and the object shape in the passage represented by the object shape data in the passage stored in the object shape storage unit 220 in the passage. Based on this, the processing device is used to compare the object shape in the passage with the three-dimensional shape of the exit, and calculate the degree of coincidence indicating how much they match. The passing object determination unit 240 determines the highest matching degree from the calculated matching degrees using the processing device. The passing object determination unit 240 compares the determined degree of coincidence with a predetermined threshold using the processing device. When the degree of coincidence is equal to or greater than the threshold value, the passing object determination unit 240 determines that the object shape in the passage corresponding to the degree of coincidence matches the exit three-dimensional shape using the processing device. When the degree of coincidence is less than the threshold value, the passing object determination unit 240 uses the processing device to find that there is a match with the exit three-dimensional shape among the object shapes in the passage stored in the object shape storage unit 220 in the passage. Judge that not.

  When the passing object determining unit 240 determines that there is a three-dimensional shape that matches the three-dimensional shape of the exit measured by the three-dimensional shape measuring apparatus 100b among the in-passage object shapes stored in the in-passage object shape storage unit 220. , It means that the object has come out normally from within the management range 810. The in-passage object shape storage unit 220 erases the in-passage object shape determined by the passing object determination unit 240. For example, the intra-passage object shape storage unit 220 uses the processing device to delete the intra-passage object shape data representing the intra-passage object shape determined by the passing object determination unit 240 from the stored intra-passage object shape data.

The in-passage object counting unit 250 (in-passage object counting device) counts the number of vehicles existing in the management range 810.
For example, the in-passage object counting unit 250 uses a storage device to represent data indicating the number of vehicles existing in the management range 810 (hereinafter referred to as “the number of objects in the passage”) (hereinafter “in-passage object number data”). Memorize). When the vehicle determination unit 210 determines that the object observed by the three-dimensional shape measuring apparatus 100a is a vehicle and the object shape storage unit 220 in the passage stores the object shape in the passage, the object counting unit 250 in the passage Is used to increase the number represented by the stored object number data in the passage by one. Conversely, when there is a vehicle that has gone out of the management range 810 based on the determination results of the reverse object determination unit 230 and the passing object determination unit 240, the in-passage object counting unit 250 uses the processing device, The number represented by the stored object number data in the passage is decreased by one.

  When there is a vehicle in the management range 810 based on the number of objects in the passage managed by the management device 200, the communication device 300 (roadside wireless device) can manage the communication range 810 via an antenna (not shown). Communicate with the vehicle inside. For example, the communication device 300 communicates with an ETC in-vehicle device mounted on a vehicle.

  The exit blocking device 400 opens and closes the blocking bar 420 based on the number of objects in the passage managed by the management device 200. The outlet blocking device 400 includes a driving device 410 and a blocking bar 420. When a vehicle is present in the management range 810, the driving device 410 operates to open the blocking bar 420. When there is no vehicle in the management range 810, the drive device 410 operates to close the blocking bar 420.

FIG. 3 is a block configuration diagram showing an example of the configuration of the three-dimensional shape measuring apparatus 100 in this embodiment.
The three-dimensional shape measurement apparatus 100 includes three sensor devices 110 and an object shape calculation device 150 (detection device).

  The sensor device 110 (distance measuring device) emits laser light. The laser light emitted from the sensor device 110 strikes and reflects an object such as a vehicle. A point where the laser beam emitted from the sensor device 110 is reflected is called a reflection point. The laser beam that is returned from the reflection of the laser beam emitted from the sensor device 110 is called a reflected laser beam. The sensor device 110 receives reflected laser light. The sensor device 110 measures the distance to the reflection point based on the received reflected laser beam. The sensor device 110 changes the direction in which laser light is emitted within a predetermined plane. A surface from which the sensor device 110 emits laser light is referred to as a scanning surface. The sensor device 110 measures distances to a plurality of reflection points in the scanning plane. The sensor device 110 outputs a signal representing the direction in which the laser light is emitted and the distance to the reflection point in that direction.

The object shape calculation device 150 calculates the three-dimensional shape of the passed object based on the results measured by the three sensor devices.
The scanning surface of each sensor device 110 is determined in advance. The object shape calculation device 150 calculates a two-dimensional shape of a cross section obtained by cutting the passed object with a scanning plane for each sensor device 110 based on the result measured by each sensor device 110. The two-dimensional shape of the cross section calculated by the object shape calculating device 150 is referred to as a cross-sectional shape. As the object passes in front of the sensor device 110, the positional relationship between the object and the scanning surface changes, and the cross-sectional shape changes. The object shape calculation device 150 calculates the three-dimensional shape of the object by combining the cross-sectional shapes calculated based on the measurement results at each time.

FIG. 4 is a block configuration diagram showing an example of a block configuration of the sensor device 110 according to this embodiment.
The sensor device 110 includes a modulation signal generation circuit 111, a continuous wave modulation light source (hereinafter referred to as “CW light source 112”), a scanning signal generation circuit 113, a direction calculation circuit 114, and a long photodiode (hereinafter referred to as “long PD115”). A current-voltage converter (hereinafter referred to as “TIA 116”), a phase detection circuit 117, a distance calculation circuit 118, a radiation optical system 120, and a light receiving optical system 130.

ただし、Ｓ_０は、変調信号の振幅を表わし、０超１未満の実数である。φは、変調信号のｔ＝０における位相を表わし、０以上２π未満の実数である。Ａ_０は、放射光の平均強度を表わし、０超の実数である。 The modulation signal generation circuit 111 generates a sine wave signal (hereinafter referred to as “modulation signal”). The frequency f of the modulation signal generated by the modulation signal generation circuit 111 is, for example, 10 megahertz.
The CW light source 112 (radiating device) emits laser light. The wavelength of laser light emitted from the CW light source 112 (hereinafter referred to as “radiated light”) is 1.4 micrometers or more, for example, 1.48 micrometers. If the wavelength of the synchrotron radiation is 1.4 micrometers or more, 10 seconds in the safety standard for class 1 laser products defined in Japanese Industrial Standards (hereinafter referred to as “JIS”) C6802 “Safety Standards for Laser Products” Compared with the case where the wavelength is less than 1.4 micrometers, for example, an output of 10 milliwatts is recognized for the above exposure, the output of the emitted light can be increased. As a result, the signal-to-noise ratio is improved, and the accuracy of distance determination is improved.
The emitted light emitted from the CW light source 112 is continuously wave-modulated by the modulation signal generated by the modulation signal generation circuit 111. Continuous wave modulation is a modulation method that continuously emits radiated light, unlike discontinuous modulation methods such as pulse modulation. As the continuous wave modulation, for example, there is an intensity modulation method for modulating the intensity of laser light.
For example, the modulation signal S (t) and the intensity A (t) of the emitted light at time t are expressed by the following equations.

Here, S ₀ represents the amplitude of the modulation signal and is a real number greater than 0 and less than 1. φ represents the phase of the modulation signal at t = 0, and is a real number not less than 0 and less than 2π. A ₀ represents the average intensity of the emitted light, and is a real number exceeding 0.

The scanning signal generation circuit 113 generates a signal (hereinafter referred to as “scanning signal”) that indicates the radiation direction of the radiation emitted by the CW light source 112.
The radiation optical system 120 (scanning device) bends the direction of the emitted light emitted from the CW light source 112 in accordance with the scanning signal generated by the scanning signal generation circuit 113 to make the light go in the instructed emission direction.
The direction calculation circuit 114 calculates the radiation direction of the emitted light based on the scanning signal generated by the scanning signal generation circuit 113. The direction calculation circuit 114 generates and outputs a signal indicating the calculated radiation direction (hereinafter referred to as “direction signal”).
The radiation direction of the emitted light reciprocates once, for example, with a period of 4 milliseconds (hereinafter referred to as “scanning period”). For example, if the vehicle passes at 80 kilometers per hour, the distance traveled in 4 milliseconds is about 9 centimeters. Therefore, even if the interval between vehicles that pass continuously is about 50 centimeters, it is possible to sufficiently determine whether the number of vehicles that have passed is one or two.

The radiated light emitted from the radiating optical system 120 hits the reflective object and is reflected. The reflected light reflected by the reflecting object enters the long PD 115 via the light receiving optical system 130.
The long PD 115 (light receiving device) is a photodiode having a long light receiving surface. The light receiving surface of the long PD 115 is, for example, a rectangle 30 mm long × 1 mm wide. A current proportional to the intensity of the received light flows through the long PD 115 regardless of the position where the light is received. Since the light receiving surface of the long PD 115 is long, it is not necessary to scan the light receiving side. As a result, mechanical elements that cause failure can be reduced, and the life of the three-dimensional shape measuring apparatus 100 can be extended.
The TIA 116 converts the current flowing through the long PD 115 into a voltage (hereinafter referred to as “light reception voltage”).

  The phase detection circuit 117 detects the phase difference between the modulation signal and the light reception voltage based on the modulation signal generated by the modulation signal generation circuit 111 and the light reception voltage converted by the TIA 116. Since the phase difference between the modulation signal and the received light voltage corresponds to the delay time until the reflected light hits the reflecting object and receives the reflected light, the distance to the reflecting object can be known based on this. The phase detection circuit 117 outputs a signal representing the detected phase difference.

ただし、θは、受光信号のｔ＝０における位相を表わし、０以上２π未満の実数である。なお、ここでは、ドップラー効果による周波数シフトを無視している。 For example, the phase detection circuit 117 uses a band-pass filter (hereinafter referred to as “BPF”) to extract only the frequency component close to the frequency f of the modulation signal from the received light voltage, and extract other frequency components. Remove. If the extracted signal (hereinafter referred to as “light reception signal”) is R (t),

Here, θ represents the phase at t = 0 of the received light signal, and is a real number not less than 0 and less than 2π. Here, the frequency shift due to the Doppler effect is ignored.

The phase detection circuit 117 calculates the product of the modulation signal S (t) and the light reception signal R (t).

The phase detection circuit 117 uses a low-pass filter (hereinafter referred to as “LPF”) to remove a component having a frequency higher than the frequency f of the modulation signal from the calculated product, and to obtain a low-frequency component (Equation 13). Only the first term) is extracted. The phase detection circuit 117 calculates the product of the amplitude S0 of the modulation signal and the amplitude R0 of the received light signal. The phase detection circuit 117 generates a signal (hereinafter referred to as “phase signal”) representing a quotient obtained by dividing the extracted signal by the calculated product. The phase signal P (t) generated by the phase detection circuit 117 is expressed by the following equation.

  Therefore, if the phase difference θ−φ is in the range of 0 to π, the phase difference between the modulation signal and the light reception signal can be obtained from the phase signal generated by the phase detection circuit 117. For example, when the frequency f of the modulation signal is 10 megahertz, the phase difference θ−φ is π when the optical path length is about 15 meters, so the distance between the sensor device 110 and the reflecting object is about 7.5 meters or less. If so, the distance to the reflecting object can be obtained based on the phase signal.

  The phase detection circuit 117 may further be configured to calculate a product of a signal obtained by shifting the modulation signal by 90 degrees and the received light signal. Then, if the phase difference θ−φ is in the range of 0 to less than 2π, the phase difference between the modulation signal and the light reception signal can be obtained from the phase signal generated by the phase detection circuit 117.

  The distance calculation circuit 118 calculates the optical path length based on the phase signal generated by the phase detection circuit 117, and calculates the distance to the reflecting object. The distance calculation circuit 118 generates and outputs a signal representing the calculated distance (hereinafter referred to as “distance signal”).

FIG. 5 is a side sectional view showing an example of the structure of the radiation optical system 120 in the sensor device 110 according to this embodiment.
The sensor device 110 includes a fine electromechanical element scanner (hereinafter referred to as “MEMS scanner 121”) and a window 141 as the radiation optical system 120.

The MEMS scanner 121 is a micromachine formed on a silicon substrate or other substrate by a semiconductor integrated circuit manufacturing technique, and includes, for example, a mirror and a drive unit. The mirror can change its angle around a predetermined axis. The drive unit moves the mirror based on the scanning signal input from the scanning signal generation circuit 113. The emitted light emitted from the CW light source 112 is reflected by the mirror and travels in the radiation direction. Since the MEMS scanner 121 can move the mirror at a higher speed than a polygon mirror or the like, high-speed scanning is possible. Further, the MEMS scanner 121 has a long lifetime with few failures due to wear and the like.
The mirror of the MEMS scanner 121 rotates within a range of about 20 degrees, for example, with a direction perpendicular to the paper surface as an axis. Therefore, the radiated light reflected by the MEMS scanner 121 scans one-dimensionally within a range of about 40 degrees, for example.
The window 141 is provided in the case 140 that covers the entire sensor device 110. The window 141 is for allowing the radiated light reflected by the MEMS scanner 121 to travel in the scanning direction range, and in order to prevent entry of dust and the like, a transparent material such as glass is fitted.

  In this example, the radiated light emitted by the sensor device 110 scans a fan-shaped range around the mirror position of the MEMS scanner 121. A position that becomes the center of the radiated light emitted from the sensor device 110 is referred to as a “radiation base point”.

FIG. 6 is a side sectional view showing an example of the structure of the light receiving optical system 130 in the sensor device 110 according to this embodiment.
The sensor device 110 includes a window 142 and a convex mirror 131 as the light receiving optical system 130.

A light shielding wall (not shown) is provided between the radiation optical system 120 and the light reception optical system 130 so that the radiation light emitted from the CW light source 112 does not enter the long PD 115.
The window 142 is provided in the case 140. The window 142 is for allowing the reflected light reflected by the reflecting object to pass through, and a transparent material such as glass is fitted to prevent entry of dust and the like. The window 142 has a structure that blocks light from outside the scanning direction range so as not to enter the long PD 115. The window 142 has a slit shape, for example.
The convex mirror 131 reflects the reflected light incident from the window 142 and causes it to enter the long PD 115. Instead of the convex mirror 131, a plane mirror or a concave mirror may be used, or the long PD 115 may directly receive the reflected light incident from the window 142.

FIG. 7 is a front view showing an example of the arrangement of the sensor devices 110a to 110c of the three-dimensional shape measuring apparatus 100a in this embodiment.
The arrangement of the sensor devices 110d to 110f of the three-dimensional shape measuring apparatus 100b is the same.
This figure is a view looking down from the sky (y direction) to the down direction (−y direction). In the figure, the left is the -z direction (the direction in which the vehicle enters), and the right is the z direction (the direction in which the vehicle travels).

The passage scanning range 501a is a range in which the emitted light emitted from the sensor device 110a hits the passage 801 and the island 802. Therefore, when there is no vehicle or the like, the passage 801 and the island 802 reflect the emitted light as a reflecting object. The passage scanning range 501b is a range in which the emitted light emitted from the sensor device 110b hits the passage 801 and the island 802. The passage scanning range 501c is a range in which the emitted light emitted from the sensor device 110c hits the passage 801 and the island 802.
The width of the traffic path 801 (hereinafter referred to as “traffic path width 511”) is, for example, 4 meters.
The passage scanning ranges 501a, 501b, and 501c are substantially parallel to each other and are substantially perpendicular to the vehicle traveling direction. An interval between the traffic path scanning range 501a and the traffic path scanning range 501b (hereinafter referred to as “travel direction position difference 513”) is, for example, 50 cm or less, and preferably 15 to 25 cm. The traveling direction position difference 513 is set shorter than the vehicle tire diameter (for example, 60 centimeters).
The traffic path scanning range 501c is located approximately at the center of the two traffic path scanning ranges 501a and 501b. Note that the path scanning range 501c may be a position close to one of the two path scanning ranges 501a and 501b. If the frequency f of the modulation signal is set to a frequency different from that of the sensor device 110c, the sensor device 110a, or the sensor device 110b, the reflected light reflected by the reflecting object is detected by the radiated light emitted by the other sensor device 110. However, since the phase detection circuit 117 can be removed, the distance to the reflecting object can be calculated correctly.
The passage scanning ranges 501a, 501b, and 501c cover almost the entire width direction of the passage 801.

FIG. 8 is a front view showing an example of the arrangement of the sensor devices 110a to 110c of the three-dimensional shape measuring apparatus 100a in this embodiment.
This figure is a view of the z direction (the direction in which the vehicle travels) from the −z direction (the direction in which the vehicle enters). In the figure, the left is the -x direction (left direction), and the right is the x direction (right direction).

The height of the radiation base point 502a of the sensor device 110a and the radiation base point 502b of the sensor device 110b with respect to the passage 801 (hereinafter referred to as “side sensor height 515”) is, for example, 1 meter. The side sensor height 515 is set lower than the vehicle height (for example, 2 meters) of a vehicle having a low vehicle height. The side sensor height 515 may be different between the sensor device 110a and the sensor device 110b.
The distance between the radiation base point 502a of the sensor device 110a and the radiation base point 502b of the sensor device 110b (hereinafter referred to as “cross-direction position difference 514”) in the direction (x direction) crossing the passage 801 perpendicular to the vehicle traveling direction. For example) is 6 meters. Since the actual distance between the radiation base point 502a and the radiation base point 502b is the length of the hypotenuse of the right triangle, if the traveling direction position difference 513 is 50 centimeters, for example, it is about 6.02 meters.
The height of the radiation base point 502c of the sensor device 110c with respect to the passage 801 (hereinafter referred to as “upper sensor height 516”) is, for example, 4.7 meters. The upper sensor height 516 is set to a height at which at least the vehicle height of a vehicle whose vehicle height is lower than the threshold value can be measured with reference to a threshold value (for example, 2 meters) for determining the vehicle height.

The scanning plane 503a is a plane that represents a range in which the radiated light emitted from the sensor device 110a falls. The scanning plane 503a has an emission base point 502a of the sensor device 110a as a vertex, and is in a range of, for example, about 10 degrees to 40 degrees below the horizontal on the side of the passage 801.
The scanning plane 503b is a plane that represents a range in which the radiated light emitted from the sensor device 110b hits. The scanning plane 503b has an emission base point 502b of the sensor device 110b as a vertex, and is in a range of, for example, about 10 to 40 degrees below the horizontal on the side of the passage 801.
The scanning plane 503c is a plane that represents a range where the radiated light emitted from the sensor device 110c is irradiated. The scanning plane 503c has an emission base point 502c of the sensor device 110c as a vertex, and is in a range of, for example, about 40 to 80 degrees below the horizontal.

FIG. 9 is a block configuration diagram showing an example of the configuration of the object shape calculation device 150 in this embodiment.
The object shape calculation device 150 includes a cross-sectional shape calculation unit 151, a cross-sectional shape storage unit 152, a cross-sectional shape verification unit 153, a movement amount calculation unit 154, and a three-dimensional shape calculation unit 155.

The object shape calculation device 150 is a computer, for example. The object shape calculation device 150 includes a processing device, a storage device, an input device, and an output device that are not shown. The processing device processes data by executing a program stored in the storage device, and controls the entire computer. The storage device stores a program executed by the processing device and data processed by the processing device. The input device inputs a signal from outside the computer and converts the input signal into data in a format that can be processed by the processing device. The data converted by the input device may be processed directly by the processing device, or may be temporarily stored by the storage device. The output device converts the data processed by the processing device and the data stored in the storage device into a signal format to be output to the outside of the computer, and outputs the converted signal to the outside.
The functions of blocks such as the cross-sectional shape calculation unit 151 shown in this figure are realized by the processing device executing a program stored in the storage device. A part or all of some or all of the blocks such as the cross-sectional shape calculation unit 151 may be realized by hardware other than a computer such as an electronic circuit or a device such as an analog circuit or a digital circuit. .

The cross-sectional shape calculation unit 151 (cross-sectional shape calculation device) calculates the cross-sectional shape for each of the three sensor devices 110 based on the distance to the reflection point measured by the sensor device 110.
For example, the cross-sectional shape calculation unit 151 inputs a signal output from the sensor device 110 using an input device. Based on the time when the signal output from the sensor device 110 is input, the cross-sectional shape calculation unit 151 calculates the time when the sensor device 110 measures the distance to the reflection point using the processing device. Hereinafter, the time when the sensor device 110 measures the distance to the reflection point is referred to as “measurement time”. Since the delay time from the measurement time to the time when the sensor device 110 outputs a signal is substantially constant, the cross-sectional shape calculation unit 151 is configured to regard the time when the signal output from the sensor device 110 is input as the measurement time. It may be. Alternatively, the sensor device 110 may output a signal representing the measurement time, direction, and distance, and the cross-sectional shape calculation unit 151 may acquire the measurement time represented by the input signal.
The cross-sectional shape calculation unit 151 uses a processing device to convert the coordinates of the reflection point represented by the direction and distance represented by the input signal, and a three-dimensional orthogonal coordinate system having the radiation base point 502 of the sensor device 110 as the origin. The coordinates at (hereinafter referred to as “relative coordinates”) are calculated. The storage device stores in advance coordinates (hereinafter referred to as “absolute coordinates”) in a three-dimensional orthogonal coordinate system representing the absolute position of each sensor device 110 with a predetermined point as the origin. The cross-sectional shape calculation unit 151 uses the processing device to convert the calculated relative coordinates based on the stored absolute coordinates representing the absolute position of each sensor device 110 and calculates the absolute coordinates of the reflection point. The cross-sectional shape calculation unit 151 accumulates data representing the measurement time and the calculated absolute coordinates of the reflection point using the storage device until the scanning direction of the laser light emitted from the sensor device 110 is completed. The cross-sectional shape calculation unit 151 uses the accumulated data (a set of data representing the absolute coordinates of a plurality of reflection points) as data representing the cross-sectional shape (hereinafter referred to as “cross-sectional shape data”).

  The cross-sectional shape storage unit 152 stores the cross-sectional shape calculated by the cross-sectional shape calculation unit 151. For example, the cross-sectional shape storage unit 152 stores the cross-sectional shape data generated by the cross-sectional shape calculation unit 151 using a storage device.

The cross-sectional shape matching unit 153 checks the cross-sectional shapes stored in the cross-sectional shape storage unit 152 to determine how much they match. For example, the cross-sectional shape matching unit 153 selects two cross-sectional shape data from the cross-sectional shape data stored in the cross-sectional shape storage unit 152 using the processing device. The cross-sectional shape matching unit 153 uses the processing device to compare the two selected cross-sectional shape data and calculate the degree of coincidence indicating how much they match.
Note that, when comparing cross-sectional shapes based on distances measured by different sensor devices 110, the range scanned by the sensor device 110 is different, so the cross-sectional shape matching unit 153 has a range scanned by the sensor device 110 out of the cross-sectional shapes. Compare the overlapping parts.

The movement amount calculation unit 154 calculates the movement amount of the object based on the determination result of the cross-sectional shape matching unit 153.
For example, the movement amount calculation unit 154 uses a processing device based on the degree of coincidence calculated by the cross-sectional shape matching unit 153, and a cross-section based on the measurement result of the sensor device 110a and a cross-section based on the measurement result of the sensor device 110c. A set of two cross-sectional shapes having the highest degree of coincidence with the shape is determined. If this is a cross-sectional shape in the same cross section of the object, the object scans the scanning surface 503a of the sensor device 110a and the sensor device 110c between the measurement time measured by the sensor device 110a and the measurement time measured by the sensor device 110c. The distance between the surface 503c is moved. The movement amount calculation unit 154 calculates the difference between the two times using the processing device. The movement amount calculation unit 154 obtains the movement speed (movement amount) of the object by calculating a quotient obtained by dividing the distance between the scanning planes 503a and 503c by the calculated time difference.

The three-dimensional shape calculation unit 155 (three-dimensional shape calculation device) combines the cross-sectional shapes stored in the cross-sectional shape storage unit 152 based on the movement amount calculated by the movement amount calculation unit 154 to obtain the three-dimensional shape of the object. calculate.
For example, the three-dimensional shape calculation unit 155 converts the absolute coordinates of the reflection point represented by the cross-sectional shape data stored in the cross-sectional shape storage unit 152 using the processing device based on the movement amount calculated by the movement amount calculation unit 154. Then, the coordinates in the three-dimensional coordinate system in which the origin moves together with the moving object (hereinafter referred to as “object system coordinates”) are calculated. In the object system coordinates, since the origin moves with the moving object, the cross-sectional shapes observed at different times can be superimposed regardless of the measurement time. The three-dimensional shape calculation unit 155 accumulates data representing the converted object system coordinates using the storage device. The three-dimensional shape calculation unit 155 uses the accumulated data (a set of data representing a plurality of object system coordinates) as data representing the three-dimensional shape of the object (hereinafter referred to as “three-dimensional shape data”).
Note that the three-dimensional shape calculation unit 155 calculates a three-dimensional shape for each object based on the calculated continuity of the three-dimensional shape. When the three-dimensional shape calculated by the three-dimensional shape calculation unit 155 is divided into a plurality of parts that are not continuous with each other, each part is considered to be one object. When the calculated three-dimensional shape is divided into a plurality of parts that are not continuous, the three-dimensional shape calculation unit 155 divides the calculated three-dimensional shape into the respective parts to obtain a three-dimensional shape for each object.

FIG. 10 is a diagram illustrating an example of a cross-sectional shape calculated by the cross-sectional shape calculation unit 151 in this embodiment.
The cross-sectional shape 521a is a cross-sectional shape detected by the cross-sectional shape calculation unit 151 based on the observation result of the sensor device 110a. The cross-sectional shape 521b is a cross-sectional shape calculated by the cross-sectional shape calculating unit 151 based on the observation result of the sensor device 110b. The cross-sectional shape 521c is a cross-sectional shape calculated by the cross-sectional shape calculating unit 151 based on the observation result of the sensor device 110c.
The cross-sectional shape 521 is represented by a solid line. A two-dot chain line represents a shape of a portion that is not visible from the sensor device 110 and is not detected as the cross-sectional shape 521 due to reasons such as being out of the scanning plane 503 or hidden behind another reflecting object. The same applies to the subsequent figures.

  In this example, the reflective objects are only the road 801 and the island 802, and the vehicle and other objects do not pass through any of the three scanning surfaces 503a, 503b, and 503c. The storage device stores the cross-sectional shape data representing the cross-sectional shape at this time as road surface cross-sectional shape data. The cross-sectional shape calculation unit 151 extracts only the portion different from the cross-sectional shape represented by the road surface cross-sectional shape data from the calculated cross-sectional shape and sets it as the cross-sectional shape of the object. The road surface cross-sectional shape data may be stored in advance in the storage device, or the road surface cross-sectional shape is determined from the cross-sectional shapes detected by the cross-sectional shape calculating unit 151, and the road surface representing the determined road surface cross-sectional shape The cross-sectional shape data may be stored in the storage device. Since the cross-sectional shape of the road surface has a feature that there is no movement, for example, the cross-sectional shape calculation unit 151 has a cross-sectional shape that is a road surface cross-sectional shape when the cross-sectional shape does not move for a time longer than a predetermined time. Is determined.

FIG. 11 is a diagram illustrating an example of a cross-sectional shape calculated by the cross-sectional shape calculating unit 151 in this embodiment.
In this example, how a passenger car passes in front of the sensor devices 110a to 110c is shown in chronological order.

At time _{t 1,} the cross-sectional shape 521a based on the observation of the sensor device 110a is a different shape and the road cross-section. Since there is no change in the cross-sectional shape 521b based on the observation of the sensor device 110b and the cross-sectional shape 521c based on the observation of the sensor device 110c, it can be understood that the object has entered from the −z direction.

In time _{t 2, the} become cross section 521c also differ from the road cross-section shape. Sectional shape matching unit 153 determines a cross-sectional shape 521c at time _{t 2, the} comparing the cross-sectional shape 521a at time _{t 1,} and substantially matches. Movement amount calculation unit 154 determines based on the determination result of the cross-sectional shape matching section 153, during the period from time t ₁ to time t _2, the the object has moved by the amount of the distance to the scanning surface 503c from the scanning surface 503a To do. The three-dimensional shape calculation unit 155, based on the determination result of the movement amount calculation unit 154, and a cross-sectional shape 521a~521c at time _{t 1,} by combining the cross-sectional shape 521a~521c at time _{t 2, the} three-dimensional shape calculate.

At time _{t 3,} becomes the cross-sectional shape 521b is also different from the road cross-section shape. Sectional shape matching section 153 determines the cross-sectional shape 521c at time _{t 3,} and compared to the cross-sectional shape 521a at time _{t 1} and time _{t 2,} towards the cross-sectional shape 521a at time _{t 2} coincides better. Movement amount calculation unit 154 determines based on the determination result of the cross-sectional shape matching section 153, during the period from the time t ₂ to time t _3, the object has moved by the amount of the distance to the scanning surface 503c from the scanning surface 503a To do. The three-dimensional shape calculation unit 155, based on the determination result of the movement amount calculation unit 154, the calculated three-dimensional shape, further coupling the cross-sectional shape 521a~521c at time _{t 3.}

  Hereinafter, the three-dimensional shape calculation unit 155 calculates the three-dimensional shape in the same manner.

In some cases, such as when the cross-sectional shape of the object is not significantly changed, the amount of movement of the object may not be accurately calculated only by checking the cross-sectional shape. In that case, the movement amount calculation unit 154, for example, the time when the tip of the object has approached the scanning surface 503a (in this example, t ₁ ), the time when the object has approached the scanning surface 503c (in this example, t ₂ ), the scanning surface The moving speed of the object is calculated based on the time approaching 503b (in this example, t ₃ ). Since the moving speed of the object does not change so rapidly, the moving amount calculation unit 154 assumes that the moving speed of the object is constant, and unless the result of the cross-sectional shape matching unit 153 matches the assumption, A configuration in which the amount of movement of the object is calculated based on the assumption may be employed.

  In this example, the sensor devices 110a and 110c are located on the left side of the passage 801 and mainly observe the left side of the object, whereas the sensor device 110b is located on the right side of the passage 801 and Therefore, the cross-sectional shape 521b based on the observation of the sensor device 110b and the cross-sectional shapes 521a and 521c based on the observation of the sensor device 110a or the sensor device 110c are not collated. However, since a vehicle or the like usually has a substantially symmetrical shape on the left and right, the cross-sectional shape matching unit 153 uses the fact that the cross-sectional shape 521b and the cross-sectional shape are reversed after the cross-sectional shape 521b is reversed left and right. The structure which collates with 521c may be sufficient.

Further, in addition to cross-sectional shape verification, it is determined that a special event such as the start or end of object detection or axle detection has occurred, and the movement amount calculation unit 154 calculates the movement amount of the object based on the time difference. It may be configured to. For example, the movement amount calculation unit 154 calculates the time (in this example, t ₁ ) when the object detection is started in the cross-sectional shape 521a. Similarly, the shift amount calculating unit 154, the start time _(t 2) of the object detection in the cross-sectional shape 521c, calculates the start time of the object detecting _{(t 3)} in cross-section 521b. The movement amount calculation unit 154 calculates the movement amount of the object based on the calculated object detection start time.
Normally, only the tire portion is in contact with the road surface, and the other portions are away from the road surface. Therefore, the axle position can be detected by analyzing the cross-sectional shape 521. For example, by analyzing the cross-sectional shape 521a, axles at time _{t 4} it can be seen that in front of the scanning surface 503a. The movement amount calculation unit 154 calculates the axle detection time (t ₄ ) in the cross-sectional shape 521a and the axle detection time (t ₆ ) in the cross-sectional shape 521b. The movement amount calculation unit 154 calculates the movement amount of the object based on the calculated axle detection time.

FIG. 12 is a flowchart showing an example of the flow of the cross-sectional shape calculation process S610 in this embodiment.
In the cross-sectional shape calculation process S610, the cross-sectional shape calculation unit 151 calculates the cross-sectional shape 521.
The cross-sectional shape calculation process S610 includes a distance direction input step S611, a relative coordinate calculation step S612, an absolute coordinate calculation step S613, an absolute coordinate storage step S614, a scanning round determination step S615, a cross-sectional shape output step S616, and an absolute coordinate erase step S617. .

  In the distance direction input step S <b> 611, the cross-sectional shape calculation unit 151 inputs a signal output from any of the sensor devices 110 using an input device, and sets the direction and distance of the reflection point measured by the sensor device 110. To get.

  In the relative coordinate calculation step S612, the cross-sectional shape calculation unit 151 uses the processing device to convert the direction and distance of the reflection point acquired in the distance direction input step S611, and sets the radiation base point 502 of the sensor device 110 as the origin. Relative coordinates are calculated.

  In the absolute coordinate calculation step S613, the cross-sectional shape calculation unit 151 uses the processing device to reflect the reflection point based on the absolute coordinates of the radiation base point 502 of the sensor device 110 and the relative coordinates calculated in the relative coordinate calculation step S612. Calculate absolute coordinates of.

  In the absolute coordinate storage step S614, the cross-sectional shape calculation unit 151 accumulates and stores the absolute coordinates of the reflection point calculated in the absolute coordinate calculation step S613 using a storage device.

In the scanning round determination step S615, the cross-sectional shape calculation unit 151 determines, based on the direction acquired in the distance direction input step S611, whether the scanning direction of the sensor device 110 has made a round using the processing device.
When the scanning direction is completed, one scanning is completed. The cross-sectional shape calculation unit 151 proceeds to the cross-sectional shape output step S616 using the processing device.
When the scanning direction is not complete, the cross-sectional shape calculation unit 151 returns to the distance direction input step S611 using the processing device and inputs the next signal.

In the cross-sectional shape output step S616, the cross-sectional shape calculation unit 151 outputs the absolute coordinates of the reflection points accumulated and stored in the absolute coordinate storage step S614 as the cross-sectional shape 521 using the processing device.
The cross-sectional shape storage unit 152 receives the cross-sectional shape 521 output from the cross-sectional shape calculation unit 151 using the processing device. The cross-sectional shape storage unit 152 stores the input cross-sectional shape 521 using a storage device.

In the absolute coordinate erasing step S617, the cross-sectional shape calculating unit 151 erases the absolute coordinates of the reflection points accumulated and stored in the absolute coordinate storing step S614 as preparation for calculating a new cross-sectional shape 521 using the processing device. To do.
Using the processing device, the cross-sectional shape calculation unit 151 returns to the distance direction input step S611 and inputs the next signal.

FIG. 13 is a flowchart showing an example of the flow of the three-dimensional shape calculation process S620 in this embodiment.
In the three-dimensional shape calculation process S620, the object shape calculation device 150 calculates the three-dimensional shape of the object.
The three-dimensional shape calculation process S620 includes a third cross-sectional shape selection step S621, a first cross-sectional shape selection step S622, a cross-sectional shape verification step S623, a movement amount calculation step S624, a coordinate system conversion step S625, a cross-sectional shape storage step S626, and an independent shape. It has a determination step S627, a three-dimensional shape output step S628, and an independent shape elimination step S629.

In the third cross-sectional shape selection step S621, the cross-sectional shape matching unit 153 uses the processing device to select from the cross-sectional shapes 521c based on the observation of the sensor device 110c among the cross-sectional shapes 521 stored in the cross-sectional shape storage unit 152. One cross-sectional shape 521c that has not yet been selected is selected.
When all the cross-sectional shapes 521c have been selected and there is no cross-sectional shape 521c that has not yet been selected, the cross-sectional shape matching unit 153 waits for the cross-sectional shape calculating unit 151 to calculate a new cross-sectional shape 521c, and then the cross-sectional shape The cross-sectional shape 521c newly stored in the storage unit 152 is selected.

In the first cross-sectional shape selection step S622, the cross-sectional shape matching unit 153 uses the processing device to select from the cross-sectional shapes 521a based on the observation of the sensor device 110a among the cross-sectional shapes 521 stored in the cross-sectional shape storage unit 152. One cross-sectional shape 521a that has not yet been selected is selected.
If all the cross-sectional shapes 521a have been selected and there is no cross-sectional shape 521a that has not yet been selected, the cross-sectional shape matching unit 153 proceeds to the movement amount calculation step S624 using the processing device.
If there is a cross-sectional shape 521a that has not yet been selected, and the cross-sectional shape 521 is selected, the cross-sectional shape verification unit 153 proceeds to the cross-sectional shape verification step S623 using the processing device.
The cross-sectional shape verification unit 153 uses the cross-sectional shape 521c to be verified based on the observation time of the cross-sectional shape 521c selected in the third cross-sectional shape selection step S621 and the movement amount calculated by the movement amount calculation unit 154. The structure which narrows down the range of the observation time of 521a may be sufficient.

In the cross-sectional shape verification step S623, the cross-sectional shape verification unit 153 uses the processing device to determine the cross-sectional shape 521c selected in the third cross-sectional shape selection step S621 and the cross-sectional shape 521a selected in the first cross-sectional shape selection step S622. The degree of coincidence is calculated by comparison. The cross-sectional shape matching unit 153 stores the calculated coincidence in association with the cross-sectional shape 521a selected in the first cross-sectional shape selecting step S622 using the storage device.
The cross-sectional shape matching unit 153 returns to the first cross-sectional shape selection step S622 using the processing device, and selects the next cross-sectional shape 521a.

In the movement amount calculation step S624, the movement amount calculation unit 154 selected in the third cross-sectional shape selection step S621 using the processing device based on the degree of coincidence stored by the cross-sectional shape verification unit 153 in the cross-sectional shape verification step S623. A cross-sectional shape 521a that matches the cross-sectional shape 521c is determined. For example, the movement amount calculation unit 154 determines the highest matching degree from the matching degrees stored by the cross-sectional shape matching unit 153. The movement amount calculation unit 154 compares the determined degree of coincidence with a predetermined threshold value. When the coincidence is equal to or greater than the threshold, the movement amount calculation unit 154 determines that the cross-sectional shape 521a associated with the coincidence matches the cross-sectional shape 521c. When the degree of coincidence is less than the threshold, the movement amount calculation unit 154 determines that there is no cross-sectional shape 521a that matches the cross-sectional shape 521c.
The movement amount calculation unit 154 calculates the movement amount of the object using the processing device based on the determined result.

  In the coordinate system conversion step S625, the three-dimensional shape calculation unit 155 uses the processing device to store the cross-section stored in the cross-sectional shape storage unit 152 based on the movement amount calculated by the movement amount calculation unit 154 in the movement amount calculation step S624. The system coordinates are calculated by converting the absolute coordinates of the reflection points constituting the shape 521.

  In the cross-sectional shape storage step S626, the three-dimensional shape calculation unit 155 stores the physical system coordinates of the reflection point calculated in the coordinate system conversion step S625 as a three-dimensional shape using the storage device.

In the independent shape determination step S627, the three-dimensional shape calculation unit 155 has not yet been observed using the processing device based on the object system coordinates of the reflection points constituting the three-dimensional shape stored in the cross-sectional shape storage step S626. It is determined whether there is an independent part that is not continuous with the part.
When there is an independent part, the observation of the three-dimensional shape of the object corresponding to that part is finished. The three-dimensional shape calculation unit 155 proceeds to the three-dimensional shape output step S628 using the processing device.
When there is no independent part, the three-dimensional shape calculation unit 155 returns to the third cross-sectional shape selection step S621 using the processing device, and selects the next cross-sectional shape 521c.

  In the three-dimensional shape output step S628, the three-dimensional shape calculation unit 155 uses the processing device to determine the three-dimensional shape of the portion determined to be an independent portion in the independent shape determination step S627 among the stored three-dimensional shapes. Output.

In the independent shape deletion step S629, the three-dimensional shape calculation unit 155 deletes the three-dimensional shape of the portion output in the three-dimensional shape output step S628 out of the stored three-dimensional shapes using the processing device.
The three-dimensional shape calculation unit 155 returns to the third cross-sectional shape selection step S621 using the processing device, and selects the next cross-sectional shape 521c.

  The three-dimensional shape calculation unit 155 does not wait for the three-dimensional shape to end and the three-dimensional shape to become independent, but at the stage where the observation from the top of the three-dimensional shape to the position of a predetermined length is completed. The configuration may be such that a three-dimensional shape is output.

FIG. 14 is a block configuration diagram showing an example of the configuration of the vehicle determination unit 210 in this embodiment.
The vehicle determination unit 210 (personnel separation determination unit) includes a three-dimensional shape storage unit 211, a three-dimensional shape verification unit 212, and a type determination unit 213.

The three-dimensional shape storage unit 211 stores the three-dimensional shapes of a plurality of objects in advance. The objects that the three-dimensional shape storage unit 211 stores the three-dimensional shape include at least both the vehicle and an object other than the vehicle. Even if it is a vehicle, the shape may vary greatly depending on the type of vehicle. Therefore, the three-dimensional shape storage unit 211 has as many types of vehicles as possible, such as the shape of a motorcycle, the shape of a passenger car, the shape of a truck, the shape of a bus, etc. It is desirable to memorize the three-dimensional shape. Also, since there are various objects other than vehicles, the three-dimensional shape storage unit 211 is not a vehicle that the sensor device 110 may observe, such as a human shape in a plurality of poses, for example. It is desirable to store as many types of object shapes as possible.
The three-dimensional shape storage unit 211 stores whether or not the three-dimensional shape is a vehicle shape in association with each stored three-dimensional shape. The three-dimensional shape storage unit 211 may be configured to store not only whether or not the three-dimensional shape is a vehicle shape, but also the type of the object such as the vehicle type.
For example, the three-dimensional shape storage unit 211 uses a storage device to store data representing the three-dimensional shape of an object (hereinafter referred to as “collation shape data”) and data representing the type of the object (hereinafter referred to as “type data”). Is called).

The three-dimensional shape matching unit 212 compares the three-dimensional shape of the entrance observed by the sensor device 110a with the three-dimensional shapes of a plurality of objects stored in the three-dimensional shape storage unit 211, and determines the best matching three-dimensional shape. To do.
For example, the three-dimensional shape matching unit 212 inputs a signal representing the inlet three-dimensional shape measured by the three-dimensional shape measuring apparatus 100a using the input device. The three-dimensional shape matching unit 212 uses the processing device to compare the entrance three-dimensional shape represented by the input signal with the three-dimensional shape represented by the matching shape data stored in the three-dimensional shape storage unit 211. The degree of coincidence indicating whether or not they match is calculated. The three-dimensional shape matching unit 212 determines the highest matching degree from the calculated matching degrees using the processing device. The three-dimensional shape matching unit 212 determines that the three-dimensional shape represented by the matching shape data corresponding to the determined matching degree is the best match with the entrance three-dimensional shape.

The type determination unit 213 determines whether or not the entrance three-dimensional shape is a vehicle shape based on the result determined by the three-dimensional shape matching unit 212.
For example, the type determining unit 213 uses the processing device based on the result determined by the three-dimensional shape matching unit 212 to determine whether the three-dimensional shape matching unit 212 uses the type data stored in the three-dimensional shape storage unit 211. The type data associated with the three-dimensional shape determined to be the best match is acquired. The type determination unit 213 outputs the acquired type data as data indicating whether the entrance three-dimensional shape is the shape of the vehicle using the processing device.

FIG. 15 is a diagram illustrating an example of a three-dimensional shape stored in the three-dimensional shape storage unit 211 according to this embodiment.
Solid lines 531a and 532a indicate a part of the three-dimensional shape stored as the track shape by the three-dimensional shape storage unit 211. A solid line 531a indicates a part of a cross section obtained by cutting the three-dimensional shape stored in the three-dimensional shape storage unit 211 along the xy plane (a plane perpendicular to the traveling direction of the vehicle). A solid line 532a indicates a part of a cross section obtained by cutting the three-dimensional shape stored in the three-dimensional shape storage unit 211 along a yz plane (a vertical plane parallel to the traveling direction of the vehicle).

FIG. 16 is a diagram illustrating an example of a three-dimensional shape stored in the three-dimensional shape storage unit 211 according to this embodiment.
Solid lines 531b and 532b indicate a part of the three-dimensional shape stored by the three-dimensional shape storage unit 211 as the shape of the motorcycle.

FIG. 17 is a diagram illustrating an example of a three-dimensional shape stored in the three-dimensional shape storage unit 211 according to this embodiment.
Solid lines 531c and 532c indicate a part of the three-dimensional shape stored as a human shape by the three-dimensional shape storage unit 211.

  In addition, the structure which provides the vehicle determination part 210 in the three-dimensional shape measuring apparatus 100 instead of in the management apparatus 200 may be sufficient. In that case, for example, the three-dimensional shape measurement apparatus 100 outputs the three-dimensional shape only when it is determined that the detected object is a vehicle according to the determination result of the vehicle determination unit 210.

FIG. 18 is a flowchart showing an example of the flow of the vehicle determination process S630 in this embodiment.
In the vehicle determination process S630, the vehicle determination unit 210 determines whether or not the entrance three-dimensional shape is a vehicle shape.
The vehicle determination process S630 includes a three-dimensional shape input step S631, a matching shape selection step S632, a three-dimensional shape matching step S633, and a type determination step S634.

  In the three-dimensional shape input step S631, the three-dimensional shape matching unit 212 uses the input device to input the inlet three-dimensional shape measured by the three-dimensional shape measuring apparatus 100a.

In the matching shape selection step S632, the three-dimensional shape matching unit 212 uses the processing device to select one of the three-dimensional shapes not yet selected from the three-dimensional shapes stored in the three-dimensional shape storage unit 211. .
When all the three-dimensional shapes stored in the three-dimensional shape storage unit 211 have been selected and there is no three-dimensional shape that has not yet been selected, the three-dimensional shape matching unit 212 proceeds to the type determination step S634 using the processing device. move on.
If there is a 3D shape that has not yet been selected, and the 3D shape is selected, the 3D shape matching unit 212 proceeds to the 3D shape matching step S633.

In the three-dimensional shape matching step S633, the three-dimensional shape matching unit 212 uses the processing device to obtain the inlet three-dimensional shape input in the three-dimensional shape input step S631 and the three-dimensional shape selected in the matching shape selection step S632. The degree of coincidence is calculated by comparison. Using the storage device, the three-dimensional shape matching unit 212 stores the calculated degree of matching in association with the three-dimensional shape selected in the matching shape selection step S632.
The three-dimensional shape matching unit 212 returns to the matching shape selection step S632 and selects the next three-dimensional shape.

  In the type determination step S634, the three-dimensional shape matching unit 212 determines the highest matching degree from the matching degrees stored in the three-dimensional shape matching step S633 using the processing device. The three-dimensional shape matching unit 212 uses the processing device to acquire the type data stored in the three-dimensional shape storage unit 211 for the three-dimensional shape associated with the determined degree of coincidence. The three-dimensional shape matching unit 212 outputs the acquired type data using the processing device.

FIG. 19 is a flowchart showing an example of the flow of the entrance management process S640 in this embodiment.
In the entrance management process S640, the management device 200 manages vehicles that pass through the entrance 811 of the management range 810.
The entrance management process S640 includes an entrance 3D shape input step S641, a moving direction determination step S642, a vehicle determination step S643, an object shape storage step S644, an object number increase step S645, an object shape selection step S651 in the passage, a tertiary The original shape matching step S652, the same object determining step S653, the in-passage object shape erasing step S654, and the in-passage object number reducing step S655 are included.

  In the entrance 3D shape input step S641, the vehicle determination unit 210 uses the input device to input the entrance 3D shape measured by the 3D shape measurement apparatus 100a and the moving direction.

In the moving direction determining step S642, the vehicle determining unit 210 uses the processing device to determine the moving direction of the object detected by the three-dimensional shape measuring apparatus 100a based on the moving direction input in the entrance three-dimensional shape input step S641. The direction (z direction) or the reverse direction (−z direction) is determined.
When the moving direction is the forward direction, the vehicle determination unit 210 proceeds to the vehicle determination step S643 using the processing device.
When the moving direction is the reverse direction, the vehicle determination unit 210 proceeds to the in-passage object shape selection step S651 using the processing device.

In vehicle determination process S643, the vehicle determination part 210 performs vehicle determination process S630 using a processing apparatus, and determines whether the object which the three-dimensional shape measuring apparatus 100a detected is a vehicle.
When the object is a vehicle, the vehicle determination unit 210 proceeds to the in-passage object shape storage step S644 using the processing device.
When the object is not a vehicle, the vehicle determination unit 210 ends the entrance management process S640 using the processing device.

  In the object shape storage step S644 in the passage, the object shape storage unit 220 in the passage stores the three-dimensional shape of the entrance input by the vehicle determination unit 210 in the entry three-dimensional shape input step S641 as the object shape in the passage using a storage device. To do.

In the passage object number increasing step S645, the passage object counting unit 250 increases the stored number of objects in the passage by one using the processing device. The in-passage object counting unit 250 stores the increased number of in-passage objects using a storage device.
The in-passage object counting unit 250 ends the entrance management process S640 using the processing device.

In the object shape selection step S651 in the passage, the reverse object determination unit 230 uses the processing device to select the object shape in the passage that has not yet been selected from the object shapes in the passage stored in the object shape storage unit 220 in the passage. Select one.
When all the object shapes in the passage stored in the object shape storage unit 220 in the passage have been selected and there are no object shapes in the passage that have not yet been selected, the reverse object determination unit 230 uses the processing device to It progresses to determination process S653.
If there is an object shape in the passage that has not yet been selected, and the object shape in the passage is selected, the reverse object determination unit 230 proceeds to the three-dimensional shape matching step S652 using the processing device.

In the three-dimensional shape matching step S652, the reverse object determination unit 230 uses the processing device to input the three-dimensional shape of the entrance input by the vehicle determination unit 210 in the entrance three-dimensional shape input step S641 and the in-passage object shape selection step S651. The degree of coincidence is calculated by comparing with the object shape in the passage selected in step (1). Using the storage device, the reverse object determination unit 230 stores the calculated coincidence in association with the in-passage object shape selected in the in-passage object shape selection step S651.
Using the processing device, the reverse object determination unit 230 returns to the object shape selection step S651 in the passage and selects the next object shape in the passage.

In the same object determination step S653, the reverse object determination unit 230 determines the highest matching degree using the processing device based on the matching degree stored in the three-dimensional shape matching step S652. The reverse object determination unit 230 uses the processing device to compare the determined degree of coincidence with a predetermined threshold value.
If the degree of coincidence is less than the threshold value, it is assumed that there is no object shape in the passage that matches the three-dimensional shape of the entrance, and the reverse object determination unit 230 ends the entrance management processing S640 using the processing device.
When the degree of coincidence is equal to or greater than the threshold value, it is assumed that the object shape in the passage associated with the degree of coincidence matches the three-dimensional shape of the entrance, and the reverse object determination unit 230 uses the processing device to detect the object in the passage. Proceed to shape erasing step S654.

  In the intra-passage object shape erasing step S654, the intra-passage object shape storage unit 220 uses the processing device to store the stored intra-passage object based on the degree of coincidence determined by the reverse object determination unit 230 in the same object determination step S653. The object shape in the passage associated with the degree of coincidence is deleted from the shapes.

In the in-passage object number reduction step S655, the in-passage object counting unit 250 decreases the stored number of in-passage objects by 1 using the processing device. The in-passage object counting unit 250 stores the reduced number of in-passage objects using the storage device.
The in-passage object counting unit 250 ends the entrance management process S640 using the processing device.

FIG. 20 is a flowchart showing an example of the flow of the exit management process S660 in this embodiment.
In the exit management process S660, the management device 200 manages vehicles that pass through the exit 812 in the management range 810.
The exit management process S660 includes an exit three-dimensional shape input step S661, a moving direction determination step S662, a vehicle determination step S663, an object shape storage step S664 in the passage, an object number increase step S665 in the passage, an object shape selection step S671 in the passage, a tertiary The original shape matching step S672, the same object determining step S673, the in-passage object shape erasing step S674, and the in-passage object number reducing step S675 are included.

  In the exit three-dimensional shape input step S661, the passing object determination unit 240 uses the input device to input the exit three-dimensional shape and the moving direction measured by the three-dimensional shape measuring apparatus 100b.

In the movement direction determination step S662, the passing object determination unit 240 uses the processing device to determine the movement direction of the object detected by the three-dimensional shape measurement apparatus 100b based on the movement direction input in the outlet three-dimensional shape input step S661. Whether forward direction (z direction) or reverse direction (−z direction) is determined.
When the moving direction is the forward direction, the passing object determination unit 240 proceeds to the in-passage object shape selection step S671 using the processing device.
When the moving direction is the reverse direction, the passing object determination unit 240 proceeds to the vehicle determination step S663 using the processing device.

In vehicle determination process S663, the vehicle determination part 210 performs vehicle determination process S630 using a processing apparatus, and determines whether the object which the three-dimensional shape measuring apparatus 100b detected is a vehicle.
When the object is a vehicle, the vehicle determination unit 210 proceeds to the in-passage object shape storing step S664 using the processing device.
When the object is not a vehicle, the vehicle determination unit 210 ends the exit management process S660 using the processing device.

  In the in-passage object shape storing step S664, the in-passage object shape storing unit 220 uses the storage device as the exit 3D shape input by the passing object determining unit 240 in the exit 3D shape input step S661 as the in-passage object shape. Remember.

In the passage object number increasing step S665, the passage object counting unit 250 increases the stored number of objects in the passage by one using the processing device. The in-passage object counting unit 250 stores the increased number of in-passage objects using a storage device.
The in-passage object counting unit 250 ends the exit management process S660 using the processing device.

  If the vehicle cannot run backward from the exit 812 side, the vehicle determination step S663 to the passage object number increasing step S665 may not be performed. In that case, when it is determined in the movement direction determination step S662 that the movement direction is the reverse direction, the passing object determination unit 240 ends the exit management process S660 using the processing device.

In the object shape selection step S671 in the passage, the passing object determination unit 240 uses the processing device to select an object shape in the passage that has not yet been selected from the object shapes in the passage stored in the object shape storage unit 220 in the passage. Select one.
When all the object shapes in the passage stored in the object shape storage unit 220 in the passage have been selected and there are no object shapes in the passage that have not yet been selected, the passing object determination unit 240 uses the processing device to determine the same object. It progresses to process S673.
If there is an object shape in the passage that has not yet been selected, and the object shape in the passage is selected, the passing object determination unit 240 proceeds to the three-dimensional shape matching step S672 using the processing device.

In the three-dimensional shape collation step S672, the passing object determination unit 240 uses the processing device and the exit three-dimensional shape input by the passing object determination unit 240 in the exit three-dimensional shape input step S661 and the in-passage object shape selection step S671. The degree of coincidence is calculated by comparing with the object shape in the passage selected in step (1). Using the storage device, the passing object determination unit 240 stores the calculated coincidence in association with the in-passage object shape selected in the in-passage object shape selection step S671.
Using the processing device, the passing object determination unit 240 returns to the in-passage object shape selection step S671, and selects the next in-passage object shape.

In the same object determining step S673, the passing object determining unit 240 determines the highest degree of matching using the processing device based on the degree of matching stored in the three-dimensional shape matching step S672. The passing object determination unit 240 compares the determined degree of coincidence with a predetermined threshold using the processing device.
When the degree of coincidence is less than the threshold value, it is assumed that there is no object shape in the passage that matches the three-dimensional shape of the exit, and the passing object determination unit 240 ends the exit management process S660 using the processing device.
When the degree of coincidence is equal to or greater than the threshold, the passage object determination unit 240 determines that the object shape in the passage associated with the degree of coincidence matches the three-dimensional shape of the exit, and the passage object determination unit 240 uses the processing device to Proceed to erasing step S674.

  In the object shape erasing step S674, the object shape storage unit 220 in the passage stores the object shape in the passage stored using the processing device based on the degree of coincidence determined by the passing object determination unit 240 in the same object determination step S673. The object shape in the passage associated with the degree of coincidence is deleted.

In the in-passage object number reduction step S675, the in-passage object counting unit 250 decreases the stored number of in-passage objects by 1 using the processing device. The in-passage object counting unit 250 stores the reduced number of in-passage objects using the storage device.
The in-passage object counting unit 250 ends the exit management process S660 using the processing device.

The traffic vehicle management system 800 described above is installed in, for example, an ETC lane provided at the entrance or exit of a toll road.
Laser type vehicle detectors (three-dimensional shape measuring apparatus 100) are arranged at the inlet (inlet 811) and outlet (outlet 812) of the ETC lane. Laser vehicle detectors measure the three-dimensional shape of an object by measuring the continuous two-dimensional shape of the passing object. The traffic vehicle management system 800 performs vehicle management including the three-dimensional shape pattern information of the passing vehicle using the three-dimensional shape measured by the laser type vehicle detector.

The laser type vehicle detector is disposed in the ETC lane or the like. The laser-type vehicle detector measures a three-dimensional shape pattern of an object entering the lane, and performs vehicle identification of the object.
The three-dimensional shape pattern is calculated by the detection device (object shape calculation device 150) based on the continuous two-dimensional shape measured by the plurality of sensor devices 110 from various angles.
The detection device determines whether the detected object is single or plural from the calculated three-dimensional shape.
The detection device (vehicle determination unit 210) determines whether or not the detected object is a vehicle based on information such as the calculated width, length, and height of the three-dimensional shape. .
The detection device compares the object shape obtained by the sensor with a pattern (three-dimensional shape) stored in advance, and determines whether the object is a passenger car, a two-wheeled vehicle, or a person.

The traffic vehicle management system 800 calculates information such as the position, size, and behavior of the vehicle passing through the ETC lane from the three-dimensional shape pattern measured by the laser vehicle detector. Thereby, accurate vehicle management can be performed.
In addition, unlike a transmissive vehicle detector or the like, a vehicle and an object other than the vehicle, such as a person, animal, garbage, and insect, can be distinguished, so that erroneous detection and vehicle management deviation can be prevented. The laser type vehicle detector can not only measure the three-dimensional shape but also grasp the fine features of the object because the beam is thin. This makes it possible to distinguish vehicles, people, animals, garbage, insects, and the like without depending on the size of the detection target.
Further, even when a plurality of people pass, it can be correctly determined that the vehicle is not a vehicle.
Moreover, even when the two-wheeled vehicle is running in parallel, the vehicle can be counted correctly.
Further, even when a vehicle staying in the ETC lane backs and exits the ETC lane, it is possible to correctly determine this and to count the vehicles correctly.

Embodiment 2. FIG.
The second embodiment will be described with reference to FIGS.
In addition, about the part which is common in Embodiment 1, the same code | symbol is attached | subjected and description is abbreviate | omitted.

FIG. 21 is a perspective view showing an example of the appearance of the passing vehicle management system 800 in this embodiment.
The three-dimensional shape measuring apparatus 100a has two sensor devices 110a and 110b, which are one less than in the first embodiment. Similarly, the three-dimensional shape measuring apparatus 100b includes two sensor devices 110d and 110e. The four sensor devices 110a, 110b, 110d, and 110e are provided at positions higher than those in the first embodiment.

FIG. 22 is a front view showing an example of the arrangement of the sensor devices 110a and 110b of the three-dimensional shape measuring apparatus 100a in this embodiment.
As shown in this figure, the arrangement of the sensor devices 110a and 110b on the xz plane (horizontal plane) is the same as in the first embodiment.

FIG. 23 is a front view showing an example of the arrangement of the sensor devices 110a and 110b of the three-dimensional shape measuring apparatus 100a in this embodiment.
As shown in this figure, the height at which the sensor devices 110a and 110b are installed is substantially the same as the height at which the sensor device 110c described in the first embodiment is installed. Thereby, sensor device 110a, 110b measures not only the shape of the side surface of a vehicle but the shape of the roof of a vehicle.

  The arrangement of the sensor devices 110d and 110e in the three-dimensional shape measuring apparatus 100b is the same as that of the three-dimensional shape measuring apparatus 100a. The configuration of the three-dimensional shape measuring apparatus 100a may be different from the configuration of the three-dimensional shape measuring apparatus 100b.

  Thus, the arrangement positions of the sensor devices 110a and 110b are increased so that one sensor device 110 can measure both the shape of the side surface of the vehicle and the shape of the roof. Thereby, the sensor apparatus 110c becomes unnecessary and the manufacturing cost of the three-dimensional shape measuring apparatus 100 can be suppressed.

  In addition, since the distance between the lower part of the side surface of the vehicle is increased and the resolution is lowered by increasing the arrangement position of the sensor devices 110a and 110b, for example, a configuration may be used in combination with an axle sensor that detects an axle.

Embodiment 3 FIG.
The third embodiment will be described with reference to FIGS.
In addition, about the part which is common in Embodiment 1, the same code | symbol is attached | subjected and description is abbreviate | omitted.

  In this embodiment, a description will be given of a configuration for determining a toll classification of a passing vehicle when the passing vehicle management system 800 is provided at an entrance or exit of a toll road.

FIG. 24 is a system configuration diagram showing an example of the overall configuration of the passing vehicle management system 800 in this embodiment.
The management apparatus 200 includes a charge category calculation unit 260 in addition to the configuration described in the first embodiment.

  The vehicle determination unit 210 not only determines whether the three-dimensional shape of the entrance measured by the three-dimensional shape measuring apparatus 100a is the shape of a vehicle, but if the shape is a vehicle, the vehicle is a passenger car or a truck. Whether the vehicle is a bus or a two-wheeled vehicle.

  When the vehicle determination unit 210 determines that the entrance 3D shape is the shape of the vehicle, the charge category calculation unit 260 determines the entrance 3D shape measured by the 3D shape measurement apparatus 100a and the vehicle determined by the vehicle determination unit 210. Based on the type of the vehicle, the charge category of the vehicle is calculated.

  The in-passage object shape storage unit 220 stores the charge category of the vehicle in association with the stored in-passage object shape of the vehicle.

  The communication device 300 communicates with the vehicle-mounted device mounted on the vehicle, and writes the fee category calculated by the fee category calculation unit 260 in the on-vehicle device. Moreover, the communication apparatus 300 communicates with onboard equipment and acquires the information regarding the vehicle type which the onboard equipment memorize | stored. The communication device 300 collates the acquired information on the vehicle type with the charge category stored in the object shape storage unit 220 in the passage to determine whether there is a contradiction. When it is determined that there is a contradiction, the communication device 300 communicates with the vehicle-mounted device and rewrites information on the vehicle type stored in the vehicle-mounted device.

FIG. 25 is a block configuration diagram showing an example of the configuration of the charge category calculation unit 260 in this embodiment.
The fee category calculation unit 260 includes an axle number counting unit 261, a vehicle width calculation unit 262, a vehicle height calculation unit 263, a vehicle length calculation unit 264, and a fee category determination unit 265.

The axle number counting unit 261 counts the number of axles (number of axles) of the vehicle based on the entrance 3D shape measured by the 3D shape measuring apparatus 100a.
The vehicle width calculation unit 262 calculates the vehicle width (vehicle width) based on the entrance 3D shape measured by the 3D shape measurement apparatus 100a.
The vehicle height calculation unit 263 calculates the height of the vehicle (vehicle height) based on the entrance 3D shape measured by the 3D shape measurement apparatus 100a.
The vehicle length calculation unit 264 calculates the length of the vehicle (vehicle length) based on the entrance 3D shape measured by the 3D shape measurement apparatus 100a.
The charge category determination unit 265 includes the type determined by the vehicle determination unit 210, the number of axles counted by the axle number counting unit 261, the vehicle width calculated by the vehicle width calculation unit 262, and the vehicle calculated by the vehicle height calculation unit 263. Based on the height and the vehicle length calculated by the vehicle length calculation unit 264, the charge category of the vehicle is determined.

  In this way, information necessary for calculating the vehicle charge category, such as the number of axles, the vehicle width, the vehicle height, and the vehicle length, is obtained based on the three-dimensional shape measured by the three-dimensional shape measuring apparatus 100a. Thereby, a charge classification can be correctly determined with a small number of sensors.

  The laser type vehicle detector a (three-dimensional shape measuring apparatus 100a) is disposed at the lane inlet (inlet 811). The laser vehicle detector a measures a three-dimensional shape pattern of an object entering the lane (management range 810). When it is determined that the object is a vehicle, vehicle information (such as a three-dimensional shape pattern and the number of axes) is transmitted to the roadside wireless device (communication device 300). The three-dimensional shape pattern is calculated by the detection device (the object shape calculation device 150) based on the continuous two-dimensional shape measured in a multifaceted manner by the plurality of sensor devices 110. The detection device (vehicle determination unit 210) determines whether the detected object is a vehicle based on the calculated three-dimensional shape. In addition, when the detected object is a vehicle, the charge category calculation unit 260 calculates the number of axes, the vehicle width, the vehicle height, and the vehicle length to obtain vehicle information. Moreover, when the parallel running of the two-wheeled vehicle is detected from the three-dimensional shape, the three-dimensional shape and the number of axes are transmitted to the roadside apparatus as separate vehicles. Further, the laser type vehicle detector a can determine whether the vehicle is moving forward or backward.

When the roadside device (communication device 300) receives the vehicle information, the roadside device (communication device 300) performs communication between the antenna and the vehicle. The vehicle information obtained from the communication result and the vehicle information obtained from the laser type vehicle detector a are associated with each other and registered in the vehicle management table (the object shape storage unit 220 in the passage) of the memory (storage device). When the two-wheeled vehicle is running in parallel, the laser-type vehicle detector a determines that there are two objects, so the communication device 300 reliably communicates with both vehicles and registers them separately in the vehicle management table.
At the entrance toll gate, there is a discrepancy between the vehicle type information obtained from the communication result and the axis number information obtained from the laser type vehicle detector a (when the vehicle type is a light vehicle even though the number of axes is 3 or more). In addition, if other conditions are satisfied, a rank-up process (write the correct vehicle type information on the vehicle-mounted device and process with the correct vehicle type at the exit toll booth) is performed. Further, when the vehicle exits in the reverse direction (−z direction) with the laser type vehicle detector a, the vehicle is determined to be a reverse vehicle (reverse vehicle), and the object counting unit 250 in the passage returns the count of the number of vehicles. . In addition, when it is determined that at least one vehicle has entered the vehicle management area (the vehicle that has returned in the back is considered to have no entry), the exit shut-off device 400 is disposed downstream of the laser vehicle detector b. The blocking bar 420 is raised.

  The laser vehicle detector b (three-dimensional shape measuring apparatus 100b) is disposed at the lane outlet (exit 812). The laser vehicle detector b measures a three-dimensional shape pattern of an object flowing out from the lane. When it is determined that the object is a vehicle, vehicle information (three-dimensional shape pattern and number of axes) is transmitted to the roadside apparatus. The three-dimensional shape pattern is calculated by the detection device (the object shape calculation device 150) based on the continuous two-dimensional shape measured in a multifaceted manner by the plurality of sensor devices 110. The detection device (vehicle determination unit 210) determines whether the detected object is a vehicle based on the calculated three-dimensional shape. If it is a vehicle, the charge category calculation unit 260 calculates the number of axes, the vehicle width, the vehicle height, and the vehicle length, and obtains vehicle information. Moreover, when the parallel running of the two-wheeled vehicle is detected from the three-dimensional shape, the three-dimensional shape and the number of axes are transmitted to the roadside apparatus as separate vehicles.

  Upon receiving the vehicle information, the roadside wireless device (passing object determination unit 240) searches for a vehicle that matches the three-dimensional shape pattern of the vehicle information registered in the table (in-passage object shape storage unit 220) and matches the vehicle information. Remove the vehicle from the table as having passed the lane. In the case of a two-wheeled vehicle, there is a possibility of overtaking on the lane, but since a matching vehicle is determined based on the three-dimensional shape, a vehicle management shift can be prevented. Further, since the vehicle can be identified by pattern matching, it is possible to accurately determine the vehicle that has remained in the vehicle management area after entering the lane. When it is determined that all the vehicles in the vehicle management area (management range 810) in the lane have exited, the exit blocking device 400 lowers the blocking bar 420 disposed downstream of the laser vehicle detector b.

  As described above, based on the three-dimensional shape pattern measured by the laser-type vehicle detector (three-dimensional shape measuring apparatus 100), the vehicle fee classification such as the number of axles, the vehicle width, the vehicle height, and the vehicle length is calculated. You can get the information you need. Therefore, there is no need to provide a road-embedded axle number sensor or the like. Thereby, laying work becomes easy and the cost concerning construction and maintenance can be reduced.

  DESCRIPTION OF SYMBOLS 100 Three-dimensional shape measuring apparatus, 110 Sensor apparatus, 111 Modulation signal generation circuit, 112 CW light source, 113 Scan signal generation circuit, 114 Direction calculation circuit, 115 Long PD, 116 TIA, 117 Phase detection circuit, 118 Distance calculation circuit, DESCRIPTION OF SYMBOLS 120 Radiation optical system, 121 MEMS scanner, 130 Light reception optical system, 131 Convex mirror, 140 Case, 141, 142 Window, 150 Object shape calculation apparatus, 151 Section shape calculation part, 152 Section shape storage part, 153 Section shape comparison part, 154 Movement amount calculation unit, 155 3D shape calculation unit, 200 management device, 210 vehicle determination unit, 211 3D shape storage unit, 212 3D shape verification unit, 213 type determination unit, 220 object shape storage unit in passage, 230 reverse Advance object determination unit, 240 Passing object determination unit, 250 Object in passage Counting unit, 260 toll class calculating unit, 261 axle number counting unit, 262 vehicle width calculating unit, 263 vehicle height calculating unit, 264 vehicle length calculating unit, 265 toll class determining unit, 300 communication device, 400 exit shut-off device, 410 drive Device, 420 blocking bar, 501 passage scanning range, 502 radiation origin, 503 scanning plane, 511 passage width, 513 travel direction position difference, 514 transverse direction position difference, 515 side sensor height, 516 upper sensor height, 521 cross-sectional shape, 531, 532 solid line, 800 traffic vehicle management system, 801 traffic path, 802 island, 803 pillar, 810 management range, 811 entrance, 812 exit.

Claims (5)

In a vehicle determination system for detecting a vehicle passing through a roadway,
The vehicle determination system includes a three-dimensional shape storage unit, a three-dimensional shape measurement device, a vehicle determination unit, an in- passage object shape storage unit, a reverse object determination unit, and an object counting unit,
The three-dimensional shape storage unit stores a three-dimensional shape of each of a plurality of objects including a two-wheeled vehicle, a vehicle that is not a two-wheeled vehicle, and an object that is not a vehicle,
The three-dimensional shape measuring apparatus measures a three-dimensional shape and a traveling direction of an object passing through the entrance of the passage ,
When the traveling direction measured by the three-dimensional shape measurement device is a forward direction toward the exit of the passage , the vehicle determination unit and the three-dimensional shape storage unit measured by the three-dimensional shape measurement device Each of the plurality of three-dimensional shapes stored is determined to determine whether the three-dimensional shape measured by the three-dimensional shape measuring apparatus is a two-wheeled vehicle, a vehicle that is not a two-wheeled vehicle, or an object that is not a vehicle, The object shape storage unit in the passage includes a three-dimensional shape of a two-wheeled vehicle that is a three-dimensional shape determined by the vehicle determination unit among the three-dimensional shapes measured by the three-dimensional shape measuring device, and the vehicle The three-dimensional shape of the vehicle that is a three-dimensional shape determined by the determination unit to be a vehicle that is not a motorcycle is stored,
When the three-dimensional shape measured by the three-dimensional shape measuring apparatus is determined to be a two-wheeled vehicle by the vehicle determining unit, the object counting unit indicates the number of two-wheeled vehicles passing through the passageway. When the three-dimensional shape measured by the three-dimensional shape measuring device is determined to be a vehicle that is not a two-wheeled vehicle by the vehicle determination unit, the number of vehicles that are not two-wheeled vehicles among the vehicles that pass through the passage is calculated . Increase the number of objects in the vehicle's passage shown by 1,
When the traveling direction measured by the three-dimensional shape measuring device is a reverse direction opposite to the exit of the passage, the three-dimensional shape measured by the three-dimensional shape measuring device is Determining whether the three-dimensional shape of the two-wheeled vehicle stored in the object shape storage unit in the passage matches the three-dimensional shape of the vehicle;
When it is determined that the three-dimensional shape measured by the three-dimensional shape measuring apparatus matches the three-dimensional shape of the two-wheeled vehicle stored in the object shape storage unit in the passage, the object counting unit calculates the number of objects in the passage of the two-wheeled vehicle. When the three-dimensional shape measured by the three-dimensional shape measuring apparatus is decreased by 1 and is matched with the three-dimensional shape of the vehicle stored in the object shape storage unit in the passage, the number of objects in the passage of the vehicle is decreased by one. vehicle judgment system according to claim <br/> to make. The vehicle determination unit determines that each two-wheeled motorcycle is a two-wheeled vehicle,
The vehicle determination system according to claim 1, wherein the object counting unit counts the number of two-wheeled vehicles that run in parallel based on the determination result of the vehicle determination unit. The three-dimensional shape measuring device has a plurality of distance measuring devices, a cross-sectional shape calculating device, and a three-dimensional shape calculating device,
The plurality of distance measuring devices are arranged at different positions from each other,
Each of the plurality of distance measuring devices emits laser light, and receives the reflected laser light reflected by the emitted laser light hitting the object, thereby determining the distance to the reflection point where the object reflects the laser light. Measure and measure the distance to multiple reflection points by changing the direction of the emitted laser light within the scanning plane,
The cross-sectional shape calculation device is configured so that, for each of the plurality of distance measurement devices, the distance measurement device emits laser light based on the distances to the plurality of reflection points measured by the distance measurement device. Calculate the cross-sectional shape of the object,
The said three-dimensional shape calculation apparatus calculates the three-dimensional shape of the said object based on the several cross-sectional shape which the said cross-sectional shape calculation apparatus calculated about the said several distance measuring device. Item 3. The vehicle determination system according to Item 2. The first distance measuring device among the plurality of distance measuring devices is installed at a height higher than a vehicle height threshold for measuring the vehicle height of the vehicle traveling on the passage, and scans downward from the horizontal. The vehicle determination system according to claim 3, wherein:   5. The vehicle determination system according to claim 4, wherein the first distance measuring device scans a range of 40 degrees to 80 degrees below the horizontal.

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