JP2011096022A - Vehicle detection device and toll charging system - Google Patents

Abstract

An object of the present invention is to reduce the cost of manufacturing, installing and maintaining a vehicle detection device.
A sensor device 110a and a sensor device 110b emit radiation light from a predetermined radiation base point in a predetermined radiation direction, and receive the reflected light reflected by the reflecting object to emit radiation. The distance to the reflecting object that reflected the light is calculated. The radiation base point of the sensor device 110a is located away from the passage 801 in the passage crossing direction across the passage 801. The radiation base point of the sensor device 110b is located at a position away from the traffic path 801 on the side opposite to the radiation base point of the sensor device 110a in the crossing direction of the passage crossing the passage 801, and in the vehicle traveling direction in which the vehicle travels, The sensor device 110a is located away from the radiation base point.
[Selection] Figure 5

Description

  The present invention relates to a vehicle detection device that detects a vehicle passing through a predetermined passage.

There is a system that is installed at a toll gate on a toll road, detects a passing vehicle, determines the type of the detected vehicle, and automatically charges.
In such a system, it is necessary to detect the vehicle length, the vehicle width, the vehicle height, the number of axles, the presence or absence of towing, etc., in order to determine the vehicle charge category. In addition, it is necessary to distinguish between a person such as a toll booth and a vehicle. Further, it is necessary to detect an abnormality such as a parallel running of a motorcycle.

JP 2001-175899 A JP 2000-215382 A JP-A-10-105869 Japanese Patent Application Laid-Open No. 10-105882 JP-A-10-105774 JP-A-11-28896 JP 2002-183881 A JP 2002-74579 A JP 2004-272841 A

Conventional vehicle detection devices use a number of sensors in combination in order to obtain various data as described above. For this reason, the expense concerning manufacture, installation, maintenance management, etc. of a vehicle detection apparatus becomes high.
The present invention has been made, for example, in order to solve the above-described problems, and an object of the present invention is to reduce the cost of manufacturing, installing, maintaining and managing the vehicle detection device.

A vehicle detection device according to the present invention is a vehicle detection device that detects a vehicle passing through a predetermined traffic path.
A plurality of sensor devices, a start detection unit, an end detection unit, a transit time calculation unit, a time difference calculation unit, a vehicle speed calculation unit, a vehicle length calculation unit, and a vehicle width calculation unit;
Each sensor device of the plurality of sensor devices emits radiated light from a predetermined radiation base point in a predetermined radiation direction, and receives the reflected light reflected by the reflecting object existing in the radiation direction. By calculating the distance to the reflecting object reflecting the radiated light,
The first sensor device among the plurality of sensor devices is a position in which the position of the radiation base is separated from the passage in the transverse direction of the passage crossing the passage, and the radial direction in the passage is in the radial direction. Radiate the above radiated light as
The second sensor device among the plurality of sensor devices is a position where the position of the radiation base point is away from the traffic path on the side opposite to the radiation base point of the first sensor device in the crossing direction of the traffic path. , In the vehicle traveling direction in which the vehicle travels, the position of the radiation base point is a position away from the radiation base point of the first sensor device, and the radiation light is emitted with the inside of the passageway as the radiation direction,
The start detection unit detects a reflection start time when the vehicle starts reflecting the radiated light as the reflective object with respect to at least one of the plurality of sensor devices,
The end detection unit detects a reflection end time when the vehicle ends reflection of the radiated light as the reflective object for at least one of the plurality of sensor devices,
The transit time calculation unit is configured to control the vehicle based on the reflection start time detected by the start detection unit and the reflection end time detected by the end detection unit for at least one of the plurality of sensor devices. Calculates the transit time it took to pass in front of the sensor device,
The time difference calculation unit calculates a time difference between a time at which a predetermined part of the vehicle passes in front of the first sensor device and a time at which the predetermined portion of the vehicle passes in front of the second sensor device,
The vehicle speed calculation unit calculates the speed of the vehicle based on the time difference calculated by the time difference calculation unit,
The vehicle length calculation unit calculates the vehicle length of the vehicle based on the passage time calculated by the passage time calculation unit and the speed calculated by the vehicle speed calculation unit,
The vehicle width calculation unit calculates the vehicle width of the vehicle based on the distance calculated by the first sensor device and the second sensor device.

  According to the vehicle detection device of the present invention, since the vehicle length and the vehicle width of the vehicle can be calculated using only two sensor devices, the number of sensor devices can be reduced, and the vehicle detection device can be manufactured, installed, and installed. Costs for maintenance management can be reduced.

1 is a system configuration diagram illustrating an example of an overall configuration of a toll gate system 800 according to Embodiment 1. FIG. 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 perspective view showing an example of an arrangement of three sensor devices 110 in the first embodiment. FIG. 3 is a plan view showing an example of an arrangement of three sensor devices 110 in the first embodiment. FIG. 3 is a front view showing an example of an arrangement of three sensor devices 110 in the first embodiment. FIG. 3 is a block configuration diagram illustrating an example of a functional block configuration of a detection device 150 according to Embodiment 1. FIG. 5 shows an example of a cross-sectional shape detected by a shape detection unit 151 in Embodiment 1. FIG. 5 shows an example of a cross-sectional shape detected by a shape detection unit 151 in Embodiment 1. FIG. 6 is a diagram illustrating an example of a cross-sectional shape detected by a shape detection unit 151 according to the first embodiment. FIG. 6 is a diagram illustrating an example of a cross-sectional shape detected by a shape detection unit 151 according to the first embodiment. FIG. 6 is a diagram illustrating an example of a cross-sectional shape detected by a shape detection unit 151 according to the first embodiment. FIG. 6 is a diagram illustrating an example of a cross-sectional shape detected by a shape detection unit 151 according to the first embodiment. FIG. 6 is a diagram illustrating an example of a cross-sectional shape detected by a shape detection unit 151 according to the first embodiment. FIG. 5 shows an example of a cross-sectional shape detected by a shape detection unit 151 in Embodiment 1. FIG. 3 is a plan view showing an example of a state in which a vehicle passing in front of the sensor device 110 in Embodiment 1 is running obliquely. The flowchart figure which shows an example of the flow of vehicle determination process S610 in Embodiment 1. FIG. FIG. 5 is a flowchart showing an example of a flow of vehicle detection processing S620 in the first embodiment. The flowchart figure which shows an example of the flow of vehicle length calculation process S630 in Embodiment 1. FIG. The flowchart figure which shows an example of the flow of vehicle width calculation process S640 in Embodiment 1. FIG. The flowchart figure which shows an example of the flow of vehicle height calculation process S650 in Embodiment 1. FIG. The flowchart figure which shows an example of the flow of parallel running determination processing S660 in Embodiment 1. FIG.

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

FIG. 1 is a system configuration diagram showing an example of the overall configuration of a toll gate system 800 in this embodiment.
The toll gate system 800 is provided at the entrance and exit of the toll road. The toll gate system 800 detects vehicles that pass through and determines the toll classification of the detected vehicles. The toll booth system 800, for example, stores the determined toll classification and the entrance where the vehicle entered the toll road at the entrance of the toll road by communicating with the onboard equipment, and the toll at the exit of the toll road Is calculated and charged. The toll gate system 800 is, for example, an ETC (Electronic Toll Collection System).

The toll gate system 800 includes, for example, a vehicle detection device 100, a communication antenna 810, a roadside wireless device 820, and a toll collection device 830.
The vehicle detection device 100 detects a passing vehicle and collects data necessary for determining a vehicle charge category, such as the vehicle length, vehicle width, vehicle height, number of axles, presence / absence of traction, and the like of the detected vehicle.
The communication antenna 810 is an antenna for performing wireless communication with the vehicle-mounted device.
The roadside apparatus 820 communicates with the vehicle-mounted device via the communication antenna 810 when the vehicle detection apparatus 100 detects a vehicle.
The toll collection device 830 collects a toll for the vehicle. For example, the toll collection device 830 communicates with a credit company server device based on credit card information acquired by the roadside wireless device 820 communicating with the vehicle-mounted device, and withdraws the toll. In addition, when the vehicle detection device 100 detects an abnormality such as a parallel running of a motorcycle or when the roadside wireless device 820 cannot normally communicate with the vehicle-mounted device, the toll collection device 830 The gate (not shown) is closed to stop the vehicle. In that case, the staff will collect the toll manually.

The vehicle detection device 100 may be described as three sensor devices 110 (in order to distinguish the respective sensor devices 110, with alphabetic lowercase letters added to the sensor devices 110a and 110b. The same applies to other configurations. ) And the detection device 150.
The sensor device 110 radiates light and reflects light (hereinafter referred to as “reflected light”) reflected by an object (hereinafter referred to as “reflection object”) that exists in the direction of radiation (hereinafter referred to as “radiation direction”). ) To measure the distance to the reflecting object. The sensor device 110 can change the direction of light emission within a predetermined range (hereinafter referred to as “scanning direction range”). The sensor device 110 scans the scanning direction range by changing the radiation direction. Thereby, the shape of a reflective object can be measured.
The detection device 150 detects the shape of the reflective object based on the distances measured by the three sensor devices 110, and determines whether or not the reflective object is a vehicle. When it is determined that the reflecting object is a vehicle, the detection device 150 determines the vehicle length, the vehicle width, the vehicle height, the number of axles, the presence or absence of traction, and the like based on the detected vehicle shape. The detection device 150 notifies the roadside device 820 of the determination result.

FIG. 2 is a block configuration diagram showing an example of a block configuration of the sensor device 110 in 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 vehicle detection device 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 is reflected, 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 S _{0 of the} modulation signal and the amplitude R _{0 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. 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 this embodiment.
The vehicle detection apparatus 100 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. 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 this embodiment.
The vehicle detection apparatus 100 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. 5 is a perspective view showing an example of the arrangement of the three sensor devices 110 in this embodiment.
The vehicle travels on a traffic path 801. On both sides of the road 801, an island 802 (referred to as a “vehicle traveling direction” or “downstream direction” hereinafter) is an island 802 on the left side and an “island 802b” on the right side. ") Is provided. The island 802 is slightly higher (for example, 15 centimeters) than the traffic path 801 to prevent the vehicle from entering.
A column 803 is provided on the island 802. Two sensor devices 110a and 110c are fixed to a pillar 803a installed on the left island 802a. The sensor device 110a is installed below the pillar 803a. The sensor device 110c is installed near the tip of the column 803a. The sensor device 110b is fixed to the pillar 803b installed on the right island 802b. The sensor device 110b is installed below the pillar 803b.

FIG. 6 is a plan view showing an example of the arrangement of the three sensor devices 110 in this embodiment.
This figure shows the arrangement shown in FIG. 5 as viewed from above.

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. The traffic path scanning range 501c may be a position close to one of the two traffic path scanning ranges 501a and 501b, or a position that substantially matches either of the two traffic path scanning ranges 501a and 501b. May be. 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. 7 is a front view showing an example of the arrangement of the three sensor devices 110 in this embodiment.
This figure shows the arrangement shown in FIG. 5 viewed from the direction opposite to the vehicle traveling direction (hereinafter referred to as “vehicle backward direction” or “upstream 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 in a direction (hereinafter referred to as “passage direction crossing direction”) perpendicular to the traveling direction of the vehicle (hereinafter referred to as a “traffic direction”) ( Hereinafter, it is referred to as “transverse direction position difference 514”.) Is, for example, 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 503a has an emission base point 502b of the sensor device 110b 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 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. 8 is a block configuration diagram showing an example of a functional block configuration of the detection device 150 in this embodiment.
The functional blocks described below may be realized in software by a computer executing a program, for example, or may be realized in hardware by a dedicated circuit or the like. Below, the case where these functional blocks are implement | achieved with a computer is demonstrated.

  The computer includes, for example, a processing device (hereinafter referred to as “CPU”), a storage device, an input device, an output device, and the like. The CPU executes the program stored in the storage device, thereby processing data stored in the storage device and controlling the entire computer. The storage device stores a program executed by the CPU, data processed by the CPU, and the like. Examples of the storage device include a nonvolatile memory (hereinafter referred to as “ROM”) and a volatile memory (hereinafter referred to as “RAM”). The input device inputs a signal such as a digital signal or an analog signal from the outside of the computer and converts it into a data format that can be processed by the CPU. Examples of the input device include a latch circuit, a serial-parallel conversion circuit (hereinafter referred to as “SPC”), an analog-digital conversion circuit (hereinafter referred to as “ADC”), and the like. The data input by the input device may be processed directly by the CPU or may be temporarily stored by the storage device. The output device converts data processed by the CPU into a signal format such as a digital signal or an analog signal, and outputs the signal to the outside of the computer. Examples of the output device include a latch circuit, a parallel-serial conversion circuit (hereinafter referred to as “PSC”), a digital-analog conversion circuit (hereinafter referred to as “DAC”), and the like.

  The detection device 150 includes three shape detection units 151, two vehicle determination units 152, two start detection units 153, two end detection units 154, two passage time calculation units 155, a passage time estimation unit 156, and two time differences. The calculation unit 157, the time difference estimation unit 158, the vehicle speed calculation unit 159, the vehicle length calculation unit 160, the two axle detection units 161, the axle counting unit 162, the vehicle width calculation unit 163, the vehicle height calculation unit 164, and the parallel running determination unit 165 are provided. Have.

  The shape detection unit 151a receives the direction signal and the distance signal output from the sensor device 110a by controlling the SPC and ADC by the CPU, and can process the data (hereinafter referred to as “direction data” and “distance data”, respectively). "). The shape detection unit 151a detects a cross-sectional shape obtained by cutting the reflective object at the scanning surface 503a when the CPU processes the direction data and the distance data. For example, the ROM stores in advance data representing the position of the radiation base point 502 and the scanning direction range of the sensor device 110, and based on the data, the CPU sets the position of the radiation base point 502a as the origin based on the direction data and the distance data. The cross-sectional shape of the reflective object is reconstructed by converting the coordinates displayed in polar coordinates to orthogonal coordinates having a predetermined point as the origin. The shape detection unit 151 a generates data representing the detected cross-sectional shape (hereinafter referred to as “cross-sectional shape data”) when the CPU processes the data. The cross-sectional shape data generated by the shape detection unit 151a represents, for example, a set of numerical values representing orthogonal coordinates converted by the shape detection unit 151a for a plurality of points or line segments constituting the cross-sectional shape.

  For example, when the interval at which the shape detection unit 151a inputs the distance signal from the sensor device 110a is 2 microseconds, the data rate is 500 kilohertz. If the scanning cycle is 4 milliseconds, the shape detection unit 151a detects 2000 points in one scan. When the scanning direction range is 30 degrees, the radiation direction changes by 60 degrees during one reciprocation, so the angle interval between the points detected by the shape detection unit 151a is 0.03 degrees. This means that the resolution at 6 meters ahead is about 3.1 millimeters, so that it is possible to sufficiently determine whether there is a tow bar having a diameter of 15 millimeters, for example.

  Similarly, the shape detection unit 151b detects a cross-sectional shape obtained by cutting the reflective object at the scanning surface 503b based on the direction signal and the distance signal output from the sensor device 110b, and generates cross-sectional shape data. Based on the direction signal and the distance signal output from the sensor device 110c, the shape detection unit 151c detects a cross-sectional shape obtained by cutting the reflective object at the scanning surface 503c, and generates cross-sectional shape data.

  For example, when the data rate is 500 kilohertz and the scanning cycle is 4 milliseconds, if the scanning direction range of the sensor device 110c is 40 degrees, the angle interval of the points detected by the shape detection unit 151c is 0.04 degrees. The resolution at 7 meters ahead is about 4.9 millimeters.

  Since the cross-sectional shape detected by the shape detection unit 151 has such a high resolution, it is possible to easily determine whether or not the reflecting object is a vehicle, determine the type of vehicle, determine the number of axles, and the like.

The vehicle determination unit 152a determines whether or not the reflective object is a vehicle by causing the CPU to process the cross-sectional shape data generated by the shape detection unit 151a. The vehicle determination unit 152a may be configured to determine the type of the vehicle when the reflective object is a vehicle. When the reflective object is not a vehicle, the vehicle determination unit 152a may be a path 801 or an island 802. It may be configured to determine whether there is a person or a person. The vehicle determination unit 152a generates data representing the determination result (hereinafter referred to as “vehicle determination data”) when the CPU processes the data.
For example, the ROM stores in advance data (hereinafter referred to as “road surface cross-sectional shape data”) representing a cross-sectional shape (hereinafter referred to as “road surface cross-sectional shape”) obtained by cutting the passage 801 and the island 802 along the scanning plane 503a. When the CPU compares the cross-sectional shape represented by the data with the cross-sectional shape represented by the cross-sectional shape data, the vehicle determination unit 152a determines whether there is a reflecting object other than the passage 801 and the island 802 in the scanning surface 503a. Determine whether or not. Further, data representing the characteristics of the cross-sectional shape of some typical vehicles (hereinafter referred to as “profile data”) is stored in advance in the ROM, and the cross-sectional shape represented by the cross-sectional shape data is the characteristic represented by the profile data. When the CPU determines whether or not the vehicle has, the vehicle determination unit 152a calculates an evaluation value. Further, the ROM stores in advance profile data representing features of cross-sectional shapes other than some typical vehicles, and the CPU determines whether the cross-sectional shape represented by the cross-sectional shape data has the features represented by the profile data. The vehicle determination unit 152a calculates an evaluation value. When the CPU compares the calculated evaluation values, the vehicle determination unit 152a determines whether or not the cross-sectional shape is the cross-sectional shape of the vehicle.

  Similarly, the vehicle determination unit 152b determines whether the reflective object is a vehicle based on the cross-sectional shape data generated by the shape detection unit 151b, and generates vehicle determination data.

The start detection unit 153a calculates the time when the vehicle starts to cross the scanning plane 503a (hereinafter referred to as “reflection start time”) by the CPU processing the vehicle determination data generated by the vehicle determination unit 152a. The start detection unit 153a generates data representing the calculated reflection start time (hereinafter referred to as “start time data”) when the CPU processes the data.
When the reflection start time cannot be specified, such as when the vehicle starts to cross the scanning surface 503a while the reflection object other than the vehicle is reflecting the radiated light, the start detection unit 153a displays the start time data. As another example, data may be generated which means that the reflection start time is unknown. Alternatively, when the reflection start time cannot be specified, the start detection unit 153a may be configured to generate data representing a time range that may be the reflection start time.

  Similarly, the start detection unit 153b calculates a reflection start time based on the vehicle determination data generated by the vehicle determination unit 152b, and generates start time data.

The end detection unit 154a calculates the time when the vehicle has crossed the scanning plane 503a (hereinafter referred to as “reflection end time”) by the CPU processing the vehicle determination data generated by the vehicle determination unit 152a. The end detection unit 154a generates data representing the calculated reflection end time (hereinafter referred to as “end time data”) when the CPU processes the data.
As with the start detection unit 153a, when the reflection end time cannot be specified, the end detection unit 154a may be configured to generate data indicating that the reflection end time is unknown as the end time data. A configuration may be used in which data representing a time range that may be the reflection end time is generated.

  Similarly, the end detection unit 154b calculates a reflection end time based on the vehicle determination data generated by the vehicle determination unit 152b, and generates end time data.

The passage time calculation unit 155a processes the start time data generated by the start detection unit 153a and the end time data generated by the end detection unit 154a, so that the time from the reflection start time to the reflection end time, that is, The time required for the vehicle to pass through the scanning surface 503a (hereinafter referred to as “passing time”) is calculated. The passage time calculation unit 155a generates data representing the calculated passage time (hereinafter referred to as “passage time data”) when the CPU processes the data.
When either the reflection start time or the reflection end time is unknown, the passage time calculation unit 155a may generate data indicating that the passage time is unknown as the passage time data. .

  Similarly, the passage time calculation unit 155b calculates passage time based on the start time data generated by the start detection unit 153b and the end time data generated by the end detection unit 154b, and generates passage time data.

The passage time estimation unit 156 is a time (hereinafter referred to as “the time taken for the vehicle to pass in front of the sensor devices 110a and 110b) by the CPU processing the passage time data generated by the two passage time calculation units 155a and 155b. Estimated transit time ”). The passage time estimation unit 156 generates data representing the estimated passage time (hereinafter referred to as “estimated passage time data”).
For example, when the two passage time calculation units 155a and 155b both specify and calculate the passage time, the passage time estimation unit 156 averages the passage times calculated by the two passage time calculation units 155a and 155b. The estimated transit time is calculated. Further, when one of the two passage time calculation units 155a and 155b does not specify the passage time and is unknown, the passage time estimation unit 156 calculates the passage time calculation unit 155 that has specified the passage time. The estimated transit time is taken as the estimated transit time. Accordingly, if the reflection start time and the reflection end time can be detected by either one of the two sensor devices 110a and 110b, the estimated passage time can be estimated. If the reflection start time and the reflection end time can be detected by both of the two sensor devices 110a and 110b, the detection error can be reduced by taking an average.

The time difference calculator 157a processes the start time data generated by the two start detectors 153a and 153b, so that the difference between the reflection start times in the two sensor devices 110a and 110b (hereinafter referred to as “start time difference”). ) Is calculated. The time difference calculation unit 157a generates data representing the calculated start time difference (hereinafter referred to as “start time difference data”) when the CPU processes the data.
When any of the reflection start times is unknown, the time difference calculation unit 157a may be configured to generate data indicating that the start time difference is unknown as the start time difference data.

The time difference calculation unit 157b processes the end time data generated by the two end detection units 154a and 154b by the CPU so that the difference between the reflection end times in the two sensor devices 110a and 110b (hereinafter referred to as “end time difference”). ) Is calculated. The time difference calculation unit 157b generates data representing the calculated end time difference (hereinafter referred to as “end time difference data”) when the CPU processes the data.
When any of the reflection end times is unknown, the time difference calculating unit 157b may generate data indicating that the end time difference is unknown as the end time difference data.

The time difference estimator 158 processes the start time difference data and the end time difference data generated by the two time difference calculators 157a and 157b, so that the time when the vehicle passes in front of the sensor device 110a and the time before the sensor device 110b are processed. The difference from the time of passing through (hereinafter referred to as “estimated time difference”) is estimated. The time difference estimation unit 158 generates data representing the estimated estimated time difference (hereinafter referred to as “estimated time difference data”) as the CPU processes the data.
For example, when the two time difference calculation units 157a and 157b specify and calculate both the start time difference and the end time difference, the CPU processes the start time difference data and the end time difference data, and averages the start time difference and the end time difference. Thus, the time difference estimation unit 158 calculates the estimated time difference. In addition, when one of the two time difference calculation units 157a and 157b does not specify the start time difference or the end time difference and is unknown, the time difference estimation unit 158 determines the specified start time difference or end time difference as the estimated time difference. To do. Thereby, if one of the reflection start time and the reflection end time can be detected by the two sensor devices 110a and 110b, the estimated time difference can be estimated. Further, if both the reflection start time and the reflection end time can be detected by the two sensor devices 110a and 110b, the average when the vehicle speed changes during passage can be calculated by taking the average.

The vehicle speed calculation unit 159 calculates the speed (vehicle speed) of the vehicle that has passed by the CPU processing the estimated time difference data generated by the time difference estimation unit 158. The vehicle speed calculation unit 159 generates data representing the calculated vehicle speed (hereinafter referred to as “vehicle speed data”) when the CPU processes the data.
For example, data representing the traveling direction position difference 513 (hereinafter referred to as “traveling direction position difference data”) is stored in advance in the ROM, and the traveling direction difference data and the estimated time difference data are processed by the CPU to be processed in the traveling direction position. By calculating a quotient obtained by dividing the difference 513 by the estimated time difference, the vehicle speed calculation unit 159 calculates the vehicle speed.

The vehicle length calculation unit 160 processes the estimated passage time data generated by the passage time estimation unit 156 and the vehicle speed data generated by the vehicle speed calculation unit 159, so that the length of the passed vehicle (vehicle length) is obtained. calculate. The vehicle length calculation unit 160 generates data representing the calculated vehicle length (hereinafter referred to as “vehicle length data”) as the CPU processes the data.
For example, the vehicle length calculation unit 160 calculates the vehicle length by processing the estimated passage time data and the vehicle speed data and calculating the product of the estimated passage time and the vehicle speed.
The vehicle detection device 100 notifies the roadside device 820 of the vehicle length data generated by the vehicle length calculation unit 160. The roadside apparatus 820 uses the notified vehicle length data to determine the charge category of the vehicle that has passed.

  As described above, even if one (in some cases, two) of the four time measurement points of the reflection start time and the reflection end time in each of the two sensor devices 110a and 110b cannot be measured, the passing time is exceeded. The estimation unit 156 can estimate the estimated transit time, and the time difference estimation unit 158 can estimate the estimation time difference. Therefore, even if any one of the four time measurement points cannot be measured, the vehicle length calculation unit 160 can calculate the vehicle length if the other three can be measured.

The axle detection unit 161a detects the axle when the CPU processes the cross-sectional shape data generated by the shape detection unit 151a. The axle detection unit 161a generates data representing the detected result (hereinafter referred to as “axle detection data”) when the CPU processes the data.
For example, when the vehicle determination unit 152a determines that the reflective object is a vehicle, the axle detection unit 161a causes the CPU to process the cross-sectional shape data so that the cross-sectional shape of the vehicle is continuous with the cross-sectional shape of the passage 801. It is determined whether or not. When the cross-sectional shape of the vehicle is continuous with the cross-sectional shape of the passage 801, it means that a part of the vehicle is in contact with the passage 801. Therefore, the axle detection unit 161a further determines whether the cross-sectional shape of the portion of the vehicle that is in contact with the passage 801 is a tire by further processing the cross-sectional shape data by the CPU. When it is determined that the cross-sectional shape is a tire, the axle detection unit 161a determines that an axle has been detected.

  Similarly, the axle detection unit 161b detects the axle based on the cross-sectional shape data generated by the shape detection unit 151b, and generates axle detection data.

The axle counting unit 162 counts the number of axles when the CPU processes the axle detection data generated by the two axle detection units 161a and 161b. Axle counting section 162 generates data representing the counted number of axles (hereinafter referred to as “axle number data”) when the CPU processes the data.
For example, the axle counting unit 162 determines whether or not a new vehicle has started to pass by the CPU processing the vehicle determination data generated by the two vehicle determination units 152a and 152b. When it is determined that a new vehicle has started to pass, the RAM stores data representing 0, so that the axle counting unit 162 initializes the number of axles. The axle counting unit 162 performs time difference estimation by processing the estimated time difference data generated by the time difference estimation unit 158, the axle detection data generated by the two axle detection units 161a and 161b, and the data stored in the RAM. The result detected by the two axle detectors 161a and 161b is overlapped by shifting the estimated time difference estimated by the unit 158, and when one of the axle detectors 161 detects the axle, 1 is added to the number of axles. . The axle counting unit 162 determines whether or not the passing vehicle has passed by the CPU processing the vehicle determination data generated by the two vehicle determination units 152a and 152b. When it is determined that the vehicle has passed, the axle counting unit 162 processes the data by the CPU, so that the data stored in the RAM is used as the axle number data.
The vehicle detection device 100 notifies the roadside wireless device 820 of the axle number data generated by the axle counting unit 162. The roadside apparatus 820 determines the toll classification of the vehicle that has passed using the notified axle number data.

The vehicle width calculation unit 163 calculates the width (vehicle width) of the vehicle that has passed by the CPU processing the cross-sectional shape data generated by the two shape detection units 151a and 151b. The vehicle width calculation unit 163 generates data representing the calculated vehicle width (hereinafter referred to as “vehicle width data”) when the CPU processes the data.
For example, in the vehicle width calculation unit 163, the CPU processes the cross-sectional shape data generated by the shape detection unit 151a, so that the distance in the crossing direction of the passage between the radiation base point 502a of the sensor device 110a and the left end of the vehicle that has passed therethrough. (Hereinafter referred to as “left distance”). Similarly, the vehicle width calculation unit 163 processes the cross-sectional shape data generated by the shape detection unit 151b by the CPU, so that the vehicle width calculation unit 163 in the crossing direction of the road between the radiation base point 502b of the sensor device 110b and the right end of the vehicle that has passed. The distance (hereinafter referred to as “right distance”) is calculated. The vehicle width calculation unit 163 calculates the sum of the calculated left distance and right distance when the CPU processes the data. Data representing the cross-direction position difference 514 (hereinafter referred to as “cross-direction position difference data”) is stored in advance in the ROM, and the CPU processes the data so that the vehicle width calculation unit 163 performs the cross-direction position difference. A difference obtained by subtracting the sum of the left distance and the right distance from 514 is calculated as the vehicle width.
The “left end of the vehicle” refers to the portion of the vehicle that protrudes to the leftmost side. However, the left end of the portion where the left tire contacts the passage 801 is regarded as the “left end of the vehicle”. May be. In that case, the CPU processes the axle detection data generated by the axle detection unit 161a, so that the vehicle width calculation unit 163 detects the timing at which the portion where the left tire is in contact with the passage 801 appears in the cross-sectional shape. . When the CPU processes the cross-sectional shape data generated by the shape detection unit 151a, the vehicle width calculation unit 163 detects the left end of the portion where the left tire contacts the passage 801 from the cross-sectional shape at the detected timing, The left side distance is calculated based on the left end of the vehicle.
The same applies to the “right end of the vehicle”.
The vehicle detection device 100 notifies the roadside wireless device 820 of the vehicle width data generated by the vehicle width calculation unit 163. The roadside apparatus 820 determines the fare classification of the vehicle that has passed using the notified vehicle width data.

The vehicle height calculation unit 164 calculates the height (vehicle height) of the vehicle that has passed by the CPU processing the cross-sectional shape data generated by the shape detection unit 151c. The vehicle height calculation unit 164 generates data representing the calculated vehicle height (hereinafter referred to as “vehicle height data”) when the CPU processes the data.
For example, the vehicle height calculation unit 164 determines whether or not a new vehicle has started to pass by the CPU processing the vehicle determination data generated by the two vehicle determination units 152a and 152b. When it is determined that a new vehicle has started to pass, the RAM stores data representing 0, so that the vehicle height calculation unit 164 initializes the vehicle height. The vehicle height calculation part 164 determines the highest part in the cross-sectional shape of a vehicle, when CPU processes the cross-sectional shape data which the shape detection part 151c produced | generated. The vehicle height calculation unit 164 compares the height of the determined highest portion with the numerical value represented by the data stored in the RAM by processing data by the CPU, and the height of the determined highest portion is higher. For example, the vehicle height is updated when the RAM stores data representing the height of the determined highest portion. The vehicle height calculation unit 164 determines whether or not the passing vehicle has passed by the CPU processing the vehicle determination data generated by the two vehicle determination units 152a and 152b. When it is determined that the vehicle has passed, the vehicle height calculation unit 164 causes the data stored in the RAM to be vehicle height data by the CPU processing the data.
The vehicle detection device 100 notifies the roadside wireless device 820 of the vehicle height data generated by the vehicle height calculation unit 164. The roadside apparatus 820 uses the notified vehicle height data to determine the charge category of the vehicle that has passed.

The parallel running determination unit 165 determines whether or not the reflective object is a two-wheeled vehicle running in parallel by the CPU processing the cross-sectional shape data generated by the shape detection unit 151c. The parallel running determination unit 165 generates data representing the determined result (hereinafter referred to as “parallel running determination data”) when the CPU processes the data.
For example, the parallel running determination unit 165 determines whether or not the reflective object is a two-wheeled vehicle running in parallel using the same method as the vehicle determination unit 152 determines whether or not the reflective object is a vehicle. To do.
The vehicle detection device 100 notifies the roadside wireless device 820 of the parallel running determination data generated by the parallel running determination unit 165. The roadside apparatus 820 detects an abnormality based on the notified parallel determination data and takes measures such as closing the gate.

FIG. 9 is a diagram illustrating an example of a cross-sectional shape detected by the shape detection unit 151 according to this embodiment.
The two-dimensional cross-sectional shape 521a is a cross-sectional shape detected by the shape detection unit 151a based on the observation result of the sensor device 110a. The two-dimensional cross-sectional shape 521b is a cross-sectional shape detected by the shape detection unit 151b based on the observation result of the sensor device 110b. The two-dimensional cross-sectional shape 521c is a cross-sectional shape detected by the shape detection unit 151c based on the observation result of the sensor device 110c.
The two-dimensional cross-sectional shape 521 is represented by a solid line. Further, the two-dot chain line indicates the shape of the portion that is not visible from the sensor device 110 due to the reason that it is outside the scanning plane 503 or hidden behind another reflecting object, and is not detected as the two-dimensional cross-sectional shape 521. Represent. The same applies to FIG.

  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. When the ROM stores the cross-sectional shape data representing the cross-sectional shape at this time as road surface cross-sectional shape data, the vehicle determination unit 152 determines whether or not any object is passing. The road surface cross-sectional shape data may be stored in advance in the ROM, or the vehicle determination unit 152 determines the road surface cross-sectional shape from the cross-sectional shapes detected by the shape detection unit 151, and the road surface cross-sectional shape thus determined is determined. The ROM may store road surface cross-sectional shape data. Since the road surface cross-sectional shape has a feature that there is no movement, for example, the vehicle determination unit 152 determines that the cross-sectional shape is a road surface cross-sectional shape when the cross-sectional shape does not move for a time longer than a predetermined time. judge.

FIG. 10 is a diagram illustrating an example of a cross-sectional shape detected by the shape detection unit 151 according to this embodiment.
In this example, how a passenger car passes in front of the sensor device 110 is shown in time series.

At time t _1, passenger cars been entered, the top part comes to scanning surface 503a. The two-dimensional cross-sectional shape 521a is different from the road surface cross-sectional shape. The vehicle determination unit 152a determines that the reflective object is a vehicle. Start detecting unit 153a determines that the time _{t 1} is a reflective start time. The two-dimensional cross-sectional shapes 521b and 521c remain the same as the road surface cross-sectional shape. The vehicle determination unit 152b determines that the reflective object is not a vehicle.
In time _{t 2, the} passenger car is somewhat willing, the head portion comes to the scanning surface 503c. Not only the two-dimensional cross-sectional shape 521a but also the two-dimensional cross-sectional shape 521c are different from the road surface cross-sectional shape. The vehicle determination unit 152a determines that the reflective object is a vehicle. The parallel running determination unit 165 determines that the reflective object is not a two-wheeled vehicle running in parallel. The two-dimensional cross-sectional shape 521b remains the same shape as the road surface cross-sectional shape. The vehicle determination unit 152b determines that the reflective object is not a vehicle.
At time _{t 3,} go further passenger car, the head portion comes to the scanning surface 503b. The two-dimensional cross-sectional shape 521b is also different from the road surface cross-sectional shape. The vehicle determination units 152a and 152b determine that the reflective object is a vehicle. Start detecting unit 153b determines that the time _{t 3} is a reflective start time. Time difference calculating unit 157a computes the difference between the time t ₁ and time t _3, the start time difference.

At time _{t 4,} the ground portion of the front tires of cars approaches the scanning surface 503a. The axle detector 161a detects the axle. The vehicle width calculation unit 163 calculates the left distance 517.
At time t _5, but ground portion of the front wheel tire of passenger car moves past the scanning surface 503a, it has not yet been reached on the scanning surface 503b.
At time _{t 6,} the ground portion of the front tires of cars approaches the scanning surface 503b. The axle detector 161b detects the axle. The vehicle width calculation unit 163 calculates the right distance 518.
At times t ₇ and t ₈ , the middle part of the passenger car passes in front of the sensor device 110.

FIG. 11 is a diagram illustrating an example of a cross-sectional shape detected by the shape detection unit 151 according to this embodiment.
In this example, the state in which the passenger car passes in front of the sensor device 110 is shown in chronological order following FIG.

At time t ₉ , the middle part of the passenger car passes in front of the sensor device 110.
At time _{t 10,} the ground portion of the rear tire of the passenger vehicle approaches the scanning surface 503a. The axle detector 161a detects the axle.
At time t _11, but the ground portion of the rear tire of passenger car past the scanning surface 503a, it has not yet been reached on the scanning surface 503b.
At time _{t 12,} the ground portion of the rear tire of the passenger vehicle approaches the scanning surface 503b. The axle detector 161b detects the axle.

At time _{t 13,} the rearmost portion of the passenger passes by scanning surface 503a. The two-dimensional cross-sectional shape 521a returns to the same shape as the road surface cross-sectional shape. The vehicle determination unit 152a determines that the reflective object is not a vehicle. End detection unit 154a determines that the time _{t 13} is a reflective end time. Passing time calculating unit 155a computes the difference between the time _{t 1} and the time _{t 13,} the transit time.
At time _{t 14,} the end portion of the passenger passes by scanning surface 503c. Not only the two-dimensional cross-sectional shape 521a but also the two-dimensional cross-sectional shape 521c have the same shape as the road surface cross-sectional shape. The parallel running determination unit 165 determines that the reflecting object is not a two-wheeled vehicle running in parallel.

At time _{t 15,} the end portion of the passenger car past the scanning surface 503b, the leading portion of the next passenger approaches the scanning surface 503a. The two-dimensional cross-sectional shape 521a is different from the road surface cross-sectional shape. The vehicle determination unit 152a determines that the reflective object is a vehicle. Start detecting unit 153a, the time t ₁₅ is determined to be a reflection start time of the next vehicle.
The two-dimensional cross-sectional shape 521b is the same shape as the road surface cross-sectional shape. The vehicle determination unit 152b determines that the reflective object is not a vehicle. Completion detecting section 154b determines that the time _{t 15} is a reflective end time. Passing time calculating unit 155b computes the difference between the time _{t 3} and time _{t 15,} the transit time. The passage time estimation unit 156 calculates an average of the passage times calculated by the two passage time calculation units 155a and 155b to obtain an estimated passage time. Time difference calculating unit 157b computes the difference between the time _{t 13} and time _{t 15,} and ends the time difference. The time difference estimation unit 158 calculates an average of the start time difference and the end time difference calculated by the two time difference calculation units 157a and 157b to obtain an estimated time difference.
The vehicle speed calculation unit 159 calculates the product of the estimated time difference calculated by the time difference estimation unit 158 and the traveling direction position difference 513 to obtain the vehicle speed. The vehicle length calculation unit 160 calculates the product of the estimated passage time calculated by the passage time estimation unit 156 and the vehicle speed calculated by the vehicle speed calculation unit 159 as the vehicle length.
The axle counting unit 162 shifts the estimated time difference calculated by the time difference estimating unit 158 and superimposes the determination result by the axle detection unit 161a and the determination result by the axle detection unit 161b. Then, an axle detection by the axle detector 161a at time _{t 4,} since the axle detected by the axle detector 161b at time _{t 6} is one overlapping axle counting unit 162 adds 1 to the number of axles. Similarly, the axle detected by the axle detector 161a at time _{t 10,} since the axle detected by the axle detector 161b at time _{t 12} becomes one overlapping axle counting unit 162 adds 1 to the number of axles 2.

FIG. 12 is a diagram illustrating an example of a cross-sectional shape detected by the shape detection unit 151 in this embodiment.
In this example, a large vehicle such as a bus or a truck passes in front of the sensor device 110.
Thus, if the vehicle height of the passing vehicle is high, the upper portion of the vehicle may protrude from the scanning surface 503c, and the vehicle height calculation unit 164 may not be able to calculate the vehicle height accurately. However, it can be determined that the vehicle height is at least higher than the height that can be calculated. When the vehicle height calculated by the vehicle height calculation unit 164 is used for determination of a charge category, it is often sufficient to know that the vehicle height is higher than the determination threshold of the charge category. Therefore, the sensor device 110c is installed at a position where the height that can be calculated is higher than the determination threshold of the charge category.

FIG. 13 is a diagram illustrating an example of a cross-sectional shape detected by the shape detection unit 151 according to this embodiment.
In this example, a connected vehicle such as a trailer passes in front of the sensor device 110.
Thus, when the passing vehicle is a connected vehicle, the cross-sectional shape of the tow bar is detected as a shape like the two-dimensional cross-sectional shape 521c. For example, the vehicle determination unit 152 determines whether or not the passing vehicle is a connected vehicle by comparing the cross-sectional shape detected by the shape detection unit 151 with the cross-sectional shape of the tow bar.

FIG. 14 is a diagram illustrating an example of a cross-sectional shape detected by the shape detection unit 151 according to this embodiment.
In this example, a motorcycle such as a motorcycle passes in front of the sensor device 110.
Thus, when the passing vehicle is a two-wheeled vehicle, it can be determined from the cross-sectional shape and the vehicle width that it is a two-wheeled vehicle. For example, the vehicle determination unit 152 determines whether or not the passing vehicle is a two-wheeled vehicle by comparing the cross-sectional shape detected by the shape detection unit 151 with the cross-sectional shape of the two-wheeled vehicle. Alternatively, the vehicle detection device 100 does not determine whether or not the passing vehicle is a two-wheeled vehicle, and based on the vehicle width calculated by the vehicle detection device 100, whether or not the passing vehicle is a two-wheeled vehicle. May be determined by the roadside apparatus 820.

FIG. 15 is a diagram illustrating an example of a cross-sectional shape detected by the shape detection unit 151 according to this embodiment.
In this example, a motorcycle such as a motorcycle runs in parallel and passes in front of the sensor device 110.
As described above, when the passing vehicle is a two-wheeled vehicle running in parallel, the determination is based on the cross-sectional shape on the scanning surface 503a detected by the shape detection unit 151a and the cross-sectional shape on the scanning surface 503b detected by the shape detection unit 151b. Although there is a possibility of misidentifying it as a wheeled vehicle or a single two-wheeled vehicle, the parallel running determination unit 165 makes a determination based on the cross-sectional shape of the scanning surface 503c detected by the shape detection unit 151c, so that a parallel running motorcycle can be easily Can be judged.

FIG. 16 is a diagram illustrating an example of a cross-sectional shape detected by the shape detection unit 151 according to this embodiment.
In this example, the passenger car is running extremely close to the left end of the road 801.
As described above, when the passing vehicle is extremely close to the left end of the passage 801, the axle detection unit 161a may not be able to detect the axle correctly, but the axle detection unit 161b detects the axle correctly. Conversely, when the passing vehicle is extremely close to the right end of the traffic path 801, the axle detection unit 161b may not be able to detect the axle correctly, but the axle detection unit 161a correctly detects the axle. The axle counting unit 162 superimposes the detection results of the two axle detection units 161a and 161b, and counts the number of axles when any of the axle detection units 161 detects the axle, so that the number of axles can be counted correctly. .

FIG. 17 is a plan view showing an example of a state in which a vehicle passing in front of the sensor device 110 in this embodiment is running obliquely.
Thus, there are cases where the passing vehicle is not parallel to the vehicle traveling direction but travels obliquely with an angle (hereinafter referred to as “slope running angle 519”). Even in such a case, since the detectable distance of the sensor device 110 is long (for example, 7.5 meters) and the resolution is high even at a position far from the sensor device 110 (for example, 5 millimeters), for example, a position far from the sensor device 110a. In addition, it can be detected that the leading portion of the vehicle (the portion on the right side in this example) has approached the scanning surface 503a. Therefore, the start detection unit 153a determines the time as the reflection start time. The start detection unit 153b determines that the time at which substantially the same position of the vehicle has reached the scanning surface 503b is the reflection start time.
Similarly, with respect to the reflection end time, the two end detection units 154a and 154b use the time at which substantially the same position at the rear end of the vehicle (the portion on the left side in this example) passes the scanning surface 503a or the scanning surface 503b as the reflection end time. judge.
Therefore, the vehicle length calculated by the vehicle length calculation unit 160 is the length of the vehicle as viewed obliquely by the oblique running angle 519. Although it depends on the vehicle speed, the absolute value of the oblique running angle 519 is considered to be approximately 10 degrees or less, so the error in calculating the vehicle length due to the oblique running is slight.

When the vehicle is running obliquely, the timing of crossing the scanning plane 503 differs between the left tire and the right tire. For example, when the vehicle is traveling diagonally to the left as shown in this figure, the left tire passes through the scanning plane 503 more late than the right tire. Utilizing this fact, the vehicle detection device 100 may be configured to determine the oblique running of the vehicle.
For example, an axle time difference calculation unit is provided, and the difference between the time when the axle detection unit 161a detects the axle and the time when the axle detection unit 161b detects the axle (hereinafter referred to as “axle time difference”) is the axle time difference calculation unit. calculate. Furthermore, a skew determination unit is provided, and the skew determination unit calculates a quotient (hereinafter referred to as “slope ratio”) obtained by dividing the axle time difference calculated by the axle time difference calculation unit by the estimated time difference calculated by the time difference estimation unit 158. calculate. When the difference between the calculated oblique running ratio and 1 is greater than a predetermined threshold, the oblique running determination unit determines that the vehicle is running obliquely. Furthermore, it is good also as a structure which provides the oblique running angle calculation part which calculates the oblique running angle 519. FIG. For example, the oblique running angle calculation unit calculates the product of the oblique traveling ratio calculated by the oblique traveling determination unit and the traveling direction position difference 513. The oblique running angle calculation unit calculates a quotient obtained by dividing the calculated product by the vehicle width calculated by the vehicle width calculation unit 163. The oblique running angle calculation unit calculates the oblique running angle 519 by calculating the arc sine of the calculated quotient.

FIG. 18 is a flowchart showing an example of the flow of the vehicle determination process S610 in this embodiment.
In vehicle determination processing S610, the vehicle determination unit 152 determines what the reflective object is. The vehicle determination process S610 includes a road surface determination step S611, a profile selection step S612, an evaluation value calculation step S613, and a maximum evaluation value determination step S614.

In the road surface determination step S611, the vehicle determination unit 152 compares the road surface cross-sectional shape data stored in the ROM with the cross-sectional shape data generated by the shape detection unit 151, so that reflective objects other than the road 801 and the island 802 are detected. It is determined whether or not it exists in the scanning plane 503.
When it is determined that a reflecting object other than the traffic path 801 and the island 802 exists in the scanning plane 503, the vehicle determination unit 152 proceeds to the profile selection step S612.
When it is determined that there is no reflecting object other than the traffic path 801 and the island 802 in the scanning plane 503, the vehicle determination unit 152 ends the vehicle determination process S610.

In profile selection step S612, vehicle determination unit 152 selects one unselected profile data from among a plurality of profile data stored in the ROM.
When all the profile data have been selected, the vehicle determination unit 152 proceeds to the maximum evaluation value determination step S614.
When there is unselected profile data and profile data is selected, the vehicle determination unit 152 proceeds to the evaluation value calculation step S613.

In the evaluation value calculation step S613, the vehicle determination unit 152 represents the feature represented by the profile data in the cross-sectional shape data based on the profile data selected in the profile selection step S612 and the cross-sectional shape data generated by the shape detection unit 151. An evaluation value representing the degree that the cross-sectional shape has is calculated.
Thereafter, the vehicle determination unit 152 returns to the profile selection step S612 and selects the next profile data.

  In the maximum evaluation value determination step S614, the vehicle determination unit 152 determines profile data that has acquired the highest evaluation value among the evaluation values calculated in the evaluation value calculation step S613. The vehicle determination unit 152 determines whether the reflected object is a vehicle by determining whether the determined profile data is profile data representing the characteristics of the vehicle or profile data representing the characteristics of an object other than the vehicle. Determine whether.

FIG. 19 is a flowchart showing an example of the flow of the vehicle detection process S620 in this embodiment.
In the vehicle detection process S620, the vehicle detection device 100 detects a vehicle. The vehicle detection process S620 includes four vehicle determination steps S621, S623, S625, S627, three distance determination steps S622, S626, S628, a start detection step S624, and an end detection step S629.

In vehicle determination process S621, the vehicle determination part 152 performs vehicle determination process S610, and determines what a reflective object is.
When it is determined that there is no reflective object other than the traffic path 801 and the island 802, the vehicle determination unit 152 repeats the vehicle determination step S621 and waits for a reflective object other than the traffic path 801 and the island 802 to be detected.
When there is a reflective object other than the traffic path 801 and the island 802 and it is determined that it is a vehicle, the reflection start time is detected. The vehicle determination unit 152 proceeds to the start detection step S624.
If there is a reflective object other than the traffic path 801 or the island 802, but it is determined that the vehicle is not a vehicle, it is necessary to consider the possibility that the vehicle is hidden behind a reflective object that is not a vehicle. The vehicle determination unit 152 proceeds to the distance determination step S622.

  In the start detection step S624, the start detection unit 153 determines that the time is the reflection start time. The start detection unit 153 proceeds to the vehicle determination step S625.

In the distance determination step S622, the start detection unit 153 calculates a distance to a reflective object that is not a vehicle based on the cross-sectional shape data, and compares it with a predetermined threshold value. This is because when the distance to the reflective object that is not the vehicle is short, the vehicle may be hidden behind it.
When the distance to the reflective object that is not the vehicle is equal to or greater than the threshold, there is no possibility that the vehicle is hidden behind the object. The start detection unit 153 returns to the vehicle determination step S621 and waits for a reflection object other than the traffic path 801 and the island 802 to be detected.
If the distance to the reflective object that is not the vehicle is less than the threshold, the vehicle may be hidden behind it. The start detection unit 153 proceeds to the vehicle determination step S623.

In vehicle determination process S623, the vehicle determination part 152 performs vehicle determination process S610, and determines what a reflective object is.
When it is determined that there is no reflecting object other than the road 801 and the island 802, there is almost no possibility that the vehicle is hidden behind the reflecting object that is not a vehicle. The vehicle determination part 152 returns to vehicle determination process S621, and waits for reflection objects other than the passage 801 and the island 802 to be detected.
When there is a reflective object other than the road 801 and the island 802, but it is determined that the vehicle is not a vehicle, the vehicle determination unit 152 returns to the distance determination step S622, and there is a possibility that the vehicle is hidden behind the reflective object that is not a vehicle. To consider.
When there is a reflective object other than the traffic path 801 and the island 802 and it is determined that the vehicle is a vehicle, there is a possibility that a vehicle hidden behind a reflective object that is not a vehicle may be visible. Could not be detected. The start detection unit 153 determines that the reflection start time is unknown, and proceeds to the vehicle determination step S625.

In vehicle determination process S625, the vehicle determination part 152 performs vehicle determination process S610, and determines what a reflective object is.
When it is determined that there is no reflecting object other than the traffic path 801 and the island 802, the reflection end time is detected. The vehicle determination unit 152 proceeds to the end detection step S629.
When it is determined that there is a reflective object other than the traffic path 801 and the island 802 and it is a vehicle, the vehicle determination unit 152 repeats the vehicle determination step S625 and waits for the vehicle to pass.
If there is a reflective object other than the road 801 or the island 802, but it is determined that the vehicle is not a vehicle, the reflective object that is not the vehicle may have hidden the vehicle, or the vehicle may pass and the reflective object hidden behind it may be seen It is necessary to consider whether it became. The vehicle determination unit 152 proceeds to the distance determination step S626.

In the distance determination step S626, the end detection unit 154 calculates a distance to a reflective object that is not a vehicle based on the cross-sectional shape data, and compares it with a predetermined threshold value.
When the distance to the reflective object that is not the vehicle is equal to or greater than the threshold value, it is considered that the reflective object hidden behind the vehicle can be seen, and thus the reflection end time is detected. The end detection unit 154 proceeds to the end detection step S629.
When the distance to the reflective object that is not the vehicle is less than the threshold value, there is a possibility that the reflective object that is not the vehicle is hiding the vehicle. The end detection unit 154 proceeds to the vehicle determination step S627.
The end detection unit 154 may be configured to use the distance to the vehicle that has been detected before as a threshold value, instead of comparing the distance to a reflective object that is not a vehicle with a predetermined threshold value.

  In the end detection step S629, the end detection unit 154 determines the time as the reflection end time. The end detection part 154 returns to vehicle determination process S621, and waits for reflection objects other than the passage 801 and the island 802 to be detected.

In vehicle determination process S627, the vehicle determination part 152 performs vehicle determination process S610, and determines what a reflective object is.
When it is determined that there is no reflecting object other than the traffic path 801 and the island 802, the vehicle that has been hidden behind the reflecting object that is not a vehicle is no longer present, and thus the reflection end time cannot be detected. The end detection unit 154 determines that the reflection end time is unknown, and returns to the vehicle determination step S621.
If there is a reflective object other than the traffic path 801 and the island 802, but it is determined that the vehicle is not a vehicle, the vehicle determination unit 152 proceeds to the distance determination step S628, and there is a possibility that the vehicle is hidden behind the reflective object that is not a vehicle. To consider.
When a reflecting object other than the traffic path 801 and the island 802 exists and is determined to be a vehicle, it is considered that the vehicle hidden behind the reflecting object that is not a vehicle can be seen again. The vehicle determination unit 152 returns to the vehicle determination step S625 and waits for the vehicle to pass.

In the distance determination step S628, the end detection unit 154 calculates a distance to a reflective object that is not a vehicle based on the cross-sectional shape data, and compares it with a predetermined threshold value.
When the distance to the reflective object that is not the vehicle is equal to or greater than the threshold value, there is almost no possibility that the vehicle is hidden behind the reflective object, and thus the reflection end time cannot be detected. The end detection unit 154 determines that the reflection end time is unknown, and returns to the vehicle determination step S621.
When the distance to the reflective object that is not the vehicle is less than the threshold value, there is a possibility that the reflective object that is not the vehicle is hiding the vehicle. The end detection unit 154 returns to the vehicle determination step S627.

FIG. 20 is a flowchart showing an example of the flow of the vehicle length calculation process S630 in this embodiment.
In the vehicle length calculation process S630, the vehicle length calculation unit 160 calculates the vehicle length of the vehicle. The vehicle length calculation process S630 includes a start time difference calculation step S631, an end time difference calculation step S632, a time difference estimation step S633, a vehicle speed calculation step S634, a first passage time calculation step S635, a second passage time calculation step S636, and a passage time estimation step S637. The vehicle length calculation step S638 is included.

In the start time difference calculation step S631, the time difference calculation unit 157a calculates the difference between the reflection start times detected by the two start detection units 153a and 153b to obtain the start time difference.
In the end time difference calculation step S632, the time difference calculation unit 157b calculates the difference between the reflection end times detected by the two end detection units 154a and 154b to obtain the end time difference.
In the time difference estimation step S633, the time difference estimation unit 158 estimates based on the start time difference calculated by the time difference calculation unit 157a in the start time difference calculation step S631 and the end time difference calculated by the time difference calculation unit 157b in the end time difference calculation step S632. Calculate the time difference.
In the vehicle speed calculation step S634, the vehicle speed calculation unit 159 obtains the vehicle speed by calculating the product of the estimated time difference calculated by the time difference estimation unit 158 in the time difference estimation step S633 and the traveling direction position difference 513.

In the first passage time calculation step S635, the passage time calculation unit 155a calculates the difference between the reflection start time detected by the start detection unit 153a and the reflection end time detected by the end detection unit 154a to obtain the passage time. .
In the second passage time calculation step S636, the passage time calculation unit 155b calculates the difference between the reflection start time detected by the start detection unit 153b and the reflection end time detected by the end detection unit 154b to obtain the passage time. .
In the passage time estimation step S637, the passage time estimation unit 156 calculates the passage time calculated by the passage time calculation unit 155a in the first passage time calculation step S635 and the passage time calculation unit 155b in the second passage time calculation step S636. An estimated passage time is calculated based on the passage time.

  In the vehicle length calculation step S638, the vehicle length calculation unit 160 calculates the product of the vehicle speed calculated by the vehicle speed calculation unit 159 in the vehicle speed calculation step S634 and the estimated passage time calculated by the passage time estimation unit 156 in the passage time estimation step S637. The vehicle length is obtained by calculation.

FIG. 21 is a flowchart showing an example of the flow of the vehicle width calculation process S640 in this embodiment.
In the vehicle width calculation process S640, the vehicle width calculation unit 163 calculates the vehicle width. The vehicle width calculation process S640 includes a left axle detection determination step S641, a left axle distance calculation step S642, a left shortest distance calculation step S643, a right axle detection determination step S644, a right axle distance calculation step S645, a right shortest distance calculation step S646, a vehicle. A width calculation step S647 is included.

In the left axle detection determination step S641, the vehicle width calculation unit 163 determines whether the axle detection unit 161a has detected the left axle based on the axle detection data generated by the axle detection unit 161a.
When it is determined that the axle detection unit 161a has detected the left axle, the vehicle width calculation unit 163 proceeds to the left axle distance calculation step S642.
When it is determined that the axle detection unit 161a has not detected the left axle, the vehicle width calculation unit 163 proceeds to the left shortest distance calculation step S643.

In the left axle distance calculation step S642, the vehicle width calculation unit 163 determines the contact point of the left tire based on the cross-sectional shape data in which the axle detection unit 161a detects the left axle. The vehicle width calculation unit 163 calculates the distance between the determined ground contact point and the radiation base point 502a and sets it as the left distance.
The vehicle width calculation unit 163 proceeds to the right axle detection determination step S644.

  In the left shortest distance calculation step S643, the vehicle width calculation unit 163 determines the position of the vehicle that protrudes most to the left based on the cross-sectional shape data generated by the shape detection unit 151. The vehicle width calculation unit 163 calculates the distance between the determined position and the radiation base point 502a and sets the distance to the left side.

In the right axle detection determination step S644, the vehicle width calculation unit 163 determines whether the axle detection unit 161b has detected the right axle based on the axle detection data generated by the axle detection unit 161b.
When it is determined that the axle detection unit 161b has detected the right axle, the vehicle width calculation unit 163 proceeds to the right axle distance calculation step S645.
When it is determined that the axle detection unit 161a has not detected the right axle, the vehicle width calculation unit 163 proceeds to the right shortest distance calculation step S646.

In the right axle distance calculation step S645, the vehicle width calculation unit 163 determines the contact point of the right tire based on the cross-sectional shape data in which the axle detection unit 161b detects the right axle. The vehicle width calculation unit 163 calculates the distance between the determined ground contact point and the radiation base point 502b and sets it as the right distance.
The vehicle width calculation unit 163 proceeds to the vehicle width calculation step S647.

  In the right shortest distance calculation step S646, the vehicle width calculation unit 163 determines the position of the vehicle that protrudes most to the right based on the cross-sectional shape data generated by the shape detection unit 151. The vehicle width calculation unit 163 calculates the distance between the determined position and the radiation base point 502b and sets it as the right distance.

  In the vehicle width calculation step S647, the vehicle width calculation unit 163 calculates the left distance calculated in the left axle distance calculation step S642 or the left shortest distance calculation step S643, and the right axle distance calculation step S645 or the right shortest distance calculation step S646. Calculate the sum of the right distance and the sum. The vehicle width calculation unit 163 calculates the vehicle width by calculating a difference obtained by subtracting the calculated sum from the crosswise position difference 514.

FIG. 22 is a flowchart showing an example of the flow of the vehicle height calculation process S650 in this embodiment.
In the vehicle height calculation process S650, the vehicle height calculation unit 164 calculates the vehicle height. The vehicle height calculation process S650 includes a vehicle height initialization step S651, a maximum determination step S652, a vehicle height update step S653, and an end determination step S654.

In the vehicle height initialization step S651, the vehicle height calculation unit 164 initializes the vehicle height to zero.
In the highest determination step S652, the vehicle height calculation unit 164 calculates the height of the highest position in the vehicle based on the cross-sectional shape data generated by the shape detection unit 151c. The vehicle height calculation unit 164 compares the calculated height with the vehicle height.
When the calculated height is higher than the vehicle height, the vehicle height calculation unit 164 proceeds to the vehicle height update step S653.
If the calculated height is less than or equal to the vehicle height, the vehicle height calculation unit 164 proceeds to the end determination step S654.

  In the vehicle height update step S653, the vehicle height calculation unit 164 sets the height calculated in the highest determination step S652 as the vehicle height.

In the end determination step S654, the vehicle height calculation unit 164 determines whether or not the vehicle has passed, based on the cross-sectional shape data generated by the shape detection unit 151c.
When it is determined that the vehicle has not yet passed, the vehicle height calculation unit 164 returns to the highest determination step S652.
When it is determined that the vehicle has passed, the vehicle height calculation unit 164 ends the vehicle height calculation process S650.

FIG. 23 is a flowchart showing an example of the flow of parallel running determination processing S660 in this embodiment.
In the parallel running determination process S660, the parallel running determination unit 165 determines the parallel running of the motorcycle. Parallel running determination process S660 has road surface determination process S661, profile selection process S662, evaluation value calculation process S663, and maximum evaluation value determination process S664.

In the road surface determination step S661, the parallel determination unit 165 compares the road surface cross-sectional shape data stored in the ROM with the cross-sectional shape data generated by the shape detection unit 151c, thereby reflecting objects other than the road 801 and the island 802. Is present in the scanning plane 503c.
If it is determined that a reflecting object other than the traffic path 801 and the island 802 exists in the scanning plane 503c, the parallel determination unit 165 proceeds to the profile selection step S662.
When it is determined that there is no reflecting object other than the traffic path 801 and the island 802 in the scanning plane 503c, the parallel determination unit 165 ends the parallel determination processing S660.

In the profile selection step S662, the parallel running determination unit 165 selects one unselected profile data from the plurality of profile data stored in the ROM.
When all the profile data have been selected, the parallel running determination unit 165 proceeds to the maximum evaluation value determination step S664.
When there is unselected profile data and profile data is selected, the parallel determination unit 165 proceeds to the evaluation value calculation step S663.

In the evaluation value calculation step S663, the parallel running determination unit 165 uses the profile data selected from the profile data selected in the profile selection step S662 and the profile shape data generated by the shape detection unit 151c. An evaluation value representing the degree to which the represented cross-sectional shape has is calculated.
Thereafter, the parallel determination unit 165 returns to the profile selection step S662 and selects the next profile data.

  In the maximum evaluation value determination step S664, the parallel determination unit 165 determines profile data that has obtained the highest evaluation value among the evaluation values calculated in the evaluation value calculation step S663. The parallel running determination unit 165 determines whether the determined profile data is profile data that represents the characteristics of a two-wheeled vehicle that is running in parallel or profile data that represents the characteristics of other objects. It is determined whether or not the motorcycle is a running motorcycle.

The vehicle detection apparatus 100 in this embodiment detects a vehicle that passes through a predetermined passage 801.
The vehicle detection device 100 includes a plurality of sensor devices 110, a start detection unit 153, an end detection unit 154, a passage time calculation unit 155 (passage time estimation unit 156), and a time difference calculation unit 157 (time difference estimation unit 158). A vehicle speed calculation unit 159, a vehicle length calculation unit 160, and a vehicle width calculation unit 163.
Each of the sensor devices 110 of the plurality of sensor devices 110 emits radiated light from a predetermined radiation base point 502 in a predetermined radiation direction, and the reflected light is reflected by a reflecting object existing in the radiation direction. Is received to calculate the distance to the reflecting object reflecting the radiated light.
Among the plurality of sensor devices 110, the first sensor device 110a has a position where the radiation base point 502a is separated from the passage 801 in the crossing direction of the passage crossing the passage 801, and the passage The radiated light is radiated in the direction 801 as the radiation direction.
Among the plurality of sensor devices 110, the second sensor device 110b is configured such that the position of the radiation base point 502b is opposite to the radiation base point 502a of the first sensor device 110a in the crossing direction of the passage. In the vehicle traveling direction in which the vehicle travels, the position of the radiation base point 502b is a position away from the radiation base point 502a of the first sensor device 110a, and the radiation path 801 is radiated through the radiation path 801. The radiated light is emitted as a direction.
The start detection unit 153 detects a reflection start time at which the vehicle starts reflecting the radiated light as the reflective object for at least one of the plurality of sensor devices 110.
The end detection unit 154 detects a reflection end time when the vehicle has finished reflecting the radiated light as the reflecting object for at least one of the plurality of sensor devices 110.
The passage time calculation unit 155 (passage time estimation unit 156) includes the reflection start time detected by the start detection unit 153 and the end detection unit 154 for at least one of the plurality of sensor devices 110. Based on the detected reflection end time, a passing time required for the vehicle to pass in front of the sensor device 110 is calculated.
The time difference calculation unit 157 (time difference estimation unit 158) is configured to detect the time at which a predetermined part (leading portion, tail) of the vehicle passes in front of the first sensor device 110a and the front of the second sensor device 110b. The time difference from the time of passing is calculated.
The vehicle speed calculation unit 159 calculates the vehicle speed (vehicle speed) based on the time difference calculated by the time difference calculation unit 157 (time difference estimation unit 158).
The vehicle length calculation unit 160 calculates the vehicle length of the vehicle based on the passage time calculated by the passage time calculation unit 155 (passage time estimation unit 156) and the speed calculated by the vehicle speed calculation unit 159.
The vehicle width calculation unit 163 calculates the vehicle width of the vehicle based on the distance calculated by the first sensor device 110a and the second sensor device 110b.

  Since the vehicle length and vehicle width of the vehicle can be calculated using only the two sensor devices 110a and 110b, the number of sensor devices 110 can be reduced, and the cost required for manufacturing, installation, maintenance management, etc. of the vehicle detection device 100. Can be suppressed.

Each sensor device 110 of the plurality of sensor devices 110 emits radiated light that scans the scanning direction range, with a predetermined scanning direction range as the radiation direction.
The first sensor device 110a scans a direction in which a first scanning line segment (passage scan range 501a) on the pass 801 and substantially parallel to the crossing direction of the pass exists as the scan direction range. Emits synchrotron radiation.
The second sensor device 110b has a direction in which a second scanning line segment (passage path scanning range 501b) exists on the path 801 and is substantially parallel to the first scanning line segment (passage path scanning range 501a). Is emitted as a scanning direction range.

  When the sensor device 110 emits radiation light that scans the range in the scanning direction, the shape of the reflecting object can be detected. Further, since the scanning direction ranges are substantially parallel to each other and substantially parallel to the passage crossing direction, the vehicle speed (and thus the vehicle length) of the vehicle can be calculated with high accuracy.

The sensor devices 110 of the plurality of sensor devices 110 include a radiation device (CW light source 112), a scanning device (radiation optical system 120), a light receiving device (long PD 115), and a distance calculation device (distance calculation circuit 118). And have.
The radiation device (CW light source 112) emits modulated light modulated by a predetermined modulation signal.
The scanning device (radiation optical system 120) bends the modulated light emitted by the radiation device (CW light source 112) to generate radiation light that scans the scanning direction range.
The light receiving device (long PD 115) receives the reflected light that is reflected from the reflecting object by the radiated light bent by the scanning device (radiating optical system 120).
The distance calculation device (distance calculation circuit 118) demodulates the reflected light received by the light receiving device (long PD 115) into a demodulated signal, and calculates a delay time (phase difference) of the demodulated signal with respect to the modulated signal. The distance to the reflecting object is calculated based on the calculated delay time.

  Since the distance to the reflecting object is calculated based on the delay time (phase difference) of the demodulated signal with respect to the modulation signal, the distance to the reflecting object can be calculated with high accuracy.

  The radiation device (CW light source 112) radiates laser light that has been subjected to continuous wave modulation (CW modulation) using a sine wave signal as the modulated light.

  Since a continuous wave modulation method using a sine wave signal is used as the modulation method of the modulated light, the data rate is increased.

  The scanning device (radiation optical system 120) includes a scanning mirror (MEMS scanner 121) constituted by fine electromechanical elements, and the modulated light emitted by the radiation device (CW light source 112) is converted into the scanning mirror (MEMS scanner). 121) reflects and bends the optical path of the modulated light.

  Since the scanning mirror (MEMS scanner 121) is composed of fine electromechanical elements, high-speed scanning is possible and the life is long.

The light receiving device includes a photodiode (long PD115) having a long light receiving surface.
The photodiode (long PD 115) receives the reflected light on the light receiving surface.

  Since the photodiode (long PD115) has a long light-receiving surface, there is no need for mechanical scanning and the lifetime is long.

  The first sensor device 110a and the second sensor device 110b have a distance (side portion) between the surface of the passage 801 and the radiation base points 502a and 502b in a vertical direction perpendicular to the surface of the passage 801. The sensor height 515) is 10 centimeters or more and 2 meters or less, and the distance between the radiation base point 502a of the first sensor device 110a and the radiation base point 502b of the second sensor device 110b in the vehicle traveling direction. (Advancing direction position difference 513) is not less than 10 centimeters and not more than 50 centimeters.

  Since the side sensor height 515 is not less than 10 centimeters and not more than 2 meters, the vehicle tire (axle) can be detected. Further, since the traveling direction position difference 513 is 10 centimeters or more, the vehicle speed can be calculated with high accuracy. Furthermore, since the traveling direction position difference 513 is 50 centimeters or less, it does not take a place to install the sensor device 110.

The vehicle detection device 100 further includes a shape detection unit 151 and a vehicle determination unit 152.
The shape detection unit 151 detects the cross-sectional shape of the reflective object based on the distance calculated by the sensor device 110 for each sensor device 110 of the plurality of sensor devices 110.
The vehicle determination unit 152 determines whether the reflective object is a vehicle based on the cross-sectional shape detected by the shape detection unit 151.

  Since it is determined whether or not the reflective object is a vehicle based on the cross-sectional shape detected by the shape detection unit 151, a highly accurate determination can be made.

The vehicle detection device 100 further includes an axle detection unit 161.
The axle detection unit 161 detects the axle of the vehicle based on the cross-sectional shape detected by the shape detection unit 151.

  Since the axle is detected based on the cross-sectional shape detected by the shape detector 151, highly accurate detection can be performed.

The vehicle detection device 100 further includes a vehicle height calculation unit 164 and a parallel running determination unit 165.
Among the plurality of sensor devices 110, the third sensor device 110c is configured such that the position of the radiation base point 502c is the first sensor device 110a and the second sensor in the vertical direction perpendicular to the plane of the passage 801. The radiation light is emitted above the radiation base points 502a and 502b of the device 110b and the inside of the passage 801 as the radiation direction.
The vehicle height calculation unit 164 calculates the vehicle height of the vehicle based on the distance calculated by the third sensor device 110c.
The parallel running determination unit 165 determines whether or not the reflective object is running in parallel based on the distance calculated by the third sensor device 110c.

  By providing the third sensor device 110c at a position overlooking the passage 801, the vehicle height and parallel running can be detected.

The toll fee charging system (tollgate system 800) in this embodiment includes the vehicle detection device 100 and a toll classification determination unit (roadside radio device 820).
The vehicle detection device 100 is installed at at least one of an entrance and an exit of a toll section.
When the vehicle determination unit 152 determines that the reflecting object is a vehicle, the charge category determination unit (roadside wireless device 820) calculates the vehicle length and the vehicle width calculation unit 163 calculated by the vehicle length calculation unit 160. The charge category of the vehicle is determined based on at least one of the calculated vehicle widths.

  Since the cost for manufacturing / installation / maintenance management of the vehicle detection device 100 can be suppressed, the cost for manufacturing / installation / maintenance management of the entire toll system (tollgate system 800) can be suppressed.

  The shape detection unit 151 is configured to detect the two-dimensional shape of the cross section of the reflecting object based on information obtained by the sensor device 110 performing one-time (one reciprocation or half-reciprocation) scan. Alternatively, the sensor device 110 may be configured to detect the three-dimensional shape of the reflecting object based on information obtained by performing scanning a plurality of times. In this case, scanning in the vehicle traveling direction is performed by movement of the reflecting object itself. Therefore, in the three-dimensional shape of the reflective object detected by the shape detection unit 151, the (pseudo) length in the vehicle traveling direction expands and contracts depending on the moving speed of the reflective object. In order to prevent this, the length in the vehicle traveling direction in the three-dimensional shape of the reflecting object detected by the shape detection unit 151 may be corrected based on the vehicle speed calculated by the vehicle speed calculation unit 159. Conversely, the vehicle speed calculation unit 159 may calculate the vehicle speed based on the distortion of the three-dimensional shape of the reflecting object detected by the shape detection unit 151 (for example, the deviation of the detected tire shape from the perfect circle).

Moreover, the structure which has a reverse detection part which detects the reverse of a vehicle may be sufficient as the vehicle detection apparatus 100.
When the vehicle is moving in the vehicle traveling direction, as shown in FIGS. 10 and 11, the detection of the vehicle starts or ends from the sensor device 110a located in the upstream direction, and proceeds in the order of the sensor devices 110c and 110b. . Therefore, when this order is reversed and detection of the vehicle from the sensor device 110b starts or ends and proceeds in the order of the sensor devices 110c and 110a, the vehicle may be traveling in a direction opposite to the vehicle traveling direction. Recognize. For example, the reverse detection unit detects the reverse of the vehicle in this way.
Alternatively, the reverse detection unit may be configured to detect the reverse of the vehicle based on the distortion of the three-dimensional shape of the reflective object detected by the shape detection unit 151. For example, in the three-dimensional shape of the reflective object detected by the shape detection unit 151, the reverse detection unit determines whether there is a portion where the same shape appears in the reverse order. When it is determined that there is a part where the same shape appears in the reverse order, the reverse detection unit detects that the traveling direction of the vehicle is reversed before and after that.

The vehicle detection device 100 described above is a laser vehicle detection device that detects a vehicle by emitting laser light.
The laser vehicle detection device includes a first side laser sensor (sensor device 110a), a second side laser sensor (sensor device 110b), an upper laser sensor (sensor device 110c), and an information processor (detection device 150). Have.
The first and second side laser sensors scan laser light within a vertical plane (scanning surfaces 503a and 503b), and obtain phase information and intensity information of reflected light by transmitting and receiving laser light.
The upper laser sensor scans the laser beam within the vertical plane (scanning plane 503c), and transmits and receives the laser beam to transmit phase information of the reflected light (phase shift from the transmission wave according to the distance to the laser reflection point) and intensity information. Get.
The information processor obtains vehicle detection information based on information obtained by the first and second side laser sensors and the upper laser sensor.
The first and second side laser sensors are installed such that the scanning center axis faces obliquely downward, and have a predetermined height (side sensor height) lower than the vehicle height on the shoulders (islands 802) on both sides of the passage. 515) and are shifted from each other in the traveling direction of the road by a distance shorter than the tire width (moving direction position difference 513).
The upper laser sensor is installed such that the scanning center axis faces obliquely downward, and is disposed at a position (upper sensor height 516) higher than the vehicle height above the side laser sensor.

  The information processor detects entry or exit of the vehicle based on information from at least one side laser sensor, and detects an axle and a vehicle length. Thereby, even if a vehicle approaches a road shoulder, axle detection robustness becomes high. The information processor detects the vehicle width based on information from the pair of side laser sensors. As a result, the vehicle width can be detected even when the vehicle approaches the shoulder. Further, the information processing device detects the vehicle height based on the distance image information from the upper laser sensor, and transmits the detection data to the vehicle type determination device (roadside wireless device 820).

  In addition, the information processing device detects reverse travel based on information from the pair of side laser sensors, or continuous information on road traveling direction (vehicle traveling direction) based on information from at least one side laser sensor. It is also possible to separate the vehicle from the nature. Thereby, it is possible to detect reverse travel at the time of road-to-vehicle communication even with a short nose vehicle.

  Based on the information from the upper laser sensor, the information processor detects the parallel running of the vehicle from the change in the height information in the road width direction (crossing direction of the road).

  The information processor detects the tow bar based on information from the side laser sensor or the upper laser sensor.

  The side laser sensor transmits CW-modulated laser light, and obtains distance information to the laser reflection position based on phase information obtained by mixing processing of the transmission signal and the reception signal. Thereby, a high data rate can be obtained.

  The side laser sensor further scans the laser transmission light with a MEMS scanner. Thereby, a high data rate can be obtained. The side laser sensor converts the received light into an electrical signal using a long photodiode, and obtains information indicating the direction of the laser reflection position from the scanning angle.

  Thereby, since the resolution of vehicle separation is 50 cm or less, the vehicle can be separated even in a traffic jam. Further, by using an eye-safe laser (for example, a wavelength of 1.48 μm) as a laser beam, a long PD and TIA (Trans Impedance Amplifier) having a high data rate, high sensitivity, and low cost can be used because the wavelength is long. There is no problem for pedestrians. If the data rate is 256 kHz or more (500 kHz or more with a margin), vehicle separation performance of 50 cm or less can be obtained when the vehicle travels at 80 km / h.

  According to the laser vehicle detection device described above, the number of axes of the vehicle can be detected without using a footboard sensor or the like. In addition, the device configuration of the vehicle detection sensor is simple, can be reduced in size, can save time and labor for laying on the road, and can be reduced in cost. Moreover, the parallel running of the two-wheeled vehicle can be detected.

The laser vehicle detection device described above is used by connecting to a vehicle type discrimination device of an ETC system, for example.
The ETC system includes a laser vehicle detection device (hereinafter simply referred to as “vehicle detection device”), an antenna (communication antenna 810), a roadside wireless device (lane server), and a toll collection device (toll gate server). Prepare. Vehicles such as automobiles and motorcycles are equipped with on-vehicle devices.
The vehicle detection device is provided around a road (traffic path 801) passing through the toll gate. The antenna is provided above the road, forms a communication area on the road surface, transmits transmission radio waves to the communication area, and receives communication information from the vehicle-mounted device.
The roadside apparatus transmits / receives communication signals to / from the antenna and performs communication control with the vehicle-mounted device. Moreover, it functions as a vehicle type discriminating device for discriminating the vehicle type based on the vehicle detection data transmitted from the vehicle detection device.
The toll collection device performs toll charge processing based on the on-vehicle device information sent from the on-vehicle device via the roadside wireless device.

The vehicle detection device includes a pair of side laser sensors (sensor devices 110a and 110b), an upper laser sensor (sensor device 110c), and an information processor (detection device 150). One side laser sensor and the upper laser sensor are installed on a pillar 803a erected on the road shoulder. The other side laser sensor is installed on a pillar 803b erected on the road shoulder.
The installation height of the side laser sensor (side sensor height 515) is, for example, 1 m. The installation height of the upper laser sensor (upper sensor height 516) is, for example, 4.7 to 5 m. The distance between the side laser sensors is, for example, 15 to 25 cm in the vehicle traveling direction and 4 to 6 m in the crossing direction of the road.
The laser sensor includes, for example, an oscillator (modulation signal generation circuit 111), a distributor, a CW light source 112, a controller (scanning signal generation circuit 113), a MEMS scanner 121, a mirror (convex mirror 131), a long PD 115, a TIA 116, and a phase detector. (Phase detection circuit 117).
The upper laser sensor may use a pulse laser that measures the transmission / reception time by pulse transmission instead of the CW method.

In addition, the vehicle detection device may be used not for an ETC system but for other systems such as an infrastructure system that provides road information.
Communication between each laser sensor and information processor may be wired connection, or a communication device such as a wireless LAN may be provided to exchange data wirelessly between the two. Further, the information processor may be provided in the side laser sensor. Alternatively, the information processor may be provided in the roadside apparatus.

The information processor (vehicle determination unit 152) detects the onset of the vehicle based on the intensity information of one of the two side laser sensors, and detects the entry or exit of the vehicle.
The information processor (shape detection unit 151) obtains a distance image (cross-sectional shape) from the phase and scanning information of one of the two side laser sensors. The information processor (axle detection unit 161) detects a tire based on a point group having a predetermined length or more continuously from the height of the distance image from the road surface, and detects the axle.
The information processor (vehicle speed calculation unit 159) obtains a distance image from intensity information or phase and scanning information of one of the two side laser sensors, and obtains the vehicle speed from the detection time difference between the pair of side laser sensors. . The information processor (passage time calculation unit 155) obtains the continuous detection time (passage time) of the vehicle from the number of sample data and the sample rate (data rate) while the vehicle is being detected. The information processor (vehicle length calculation unit 160) obtains the vehicle length from the continuous detection time and the vehicle speed.
The information processor (vehicle width calculation unit 163) detects the vehicle width from the distance difference between the two sensors (transverse direction position difference 514) based on information from the pair of side laser sensors. As a result, the vehicle width can be detected even when the vehicle approaches the shoulder.
The information processor (vehicle height calculation unit 164) detects the vehicle height based on the distance image information (cross-sectional shape) from the upper laser sensor.
The vehicle type discriminating device (roadside radio device) discriminates the vehicle type from these detection data.

According to the vehicle detection device described above, the configuration of a large number of vehicle detectors installed in the ETC lane can be reduced and the size can be reduced, so that the device, installation cost, and maintenance cost are reduced. In addition, since there are few facilities to be installed on the island 802, the visibility when viewed from the driver of the vehicle is increased, and the safety is improved. In addition, accidents such as a toll booth staff and equipment maintenance staff tripping to the equipment installed on the island 802 are reduced, and safety is improved.
In addition, a footboard sensor used for an axle sensor is not necessary. In addition, it is possible to detect the parallel running of the motorcycle. Further, since the vehicle shape profile can be measured three-dimensionally, vehicle type determination is facilitated.

The vehicle detection device described above detects the shape of the reflecting object by the CW method. The CW method has a longer continuous time of radiated light and emits and receives light at a higher repetition frequency than the pulse method, so that a high signal-to-noise ratio can be obtained even if the output is small. Further, since a light receiving device having a low response frequency such as a long PD can be used, the manufacturing cost can be reduced.
Further, since there is a possibility that a person enters the scanning plane 503 and sees the emitted light, the output of the laser light is severely limited in order to prevent the occurrence of harm such as retinal damage. Since the vehicle detection apparatus described above uses laser light having a wavelength of 1400 nanometers or more that is safe for the eyes as emitted light, the output can be increased. Thereby, a high signal-to-noise ratio can be obtained.

  DESCRIPTION OF SYMBOLS 100 Vehicle detection 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, 120 Radiation Optical system, 121 MEMS scanner, 130 light receiving optical system, 131 convex mirror, 140 case, 141, 142 window, 150 detection device, 151 shape detection unit, 152 vehicle determination unit, 153 start detection unit, 154 end detection unit, 155 transit time Calculation unit, 156 passage time estimation unit, 157 time difference calculation unit, 158 time difference estimation unit, 159 vehicle speed calculation unit, 160 vehicle length calculation unit, 161 axle detection unit, 162 axle counting unit, 163 vehicle width calculation unit, 164 vehicle height calculation Part, 165 parallel running judgment part, 501 path scanning range, 50 Radiation reference point, 503 scanning plane, 511 passage width, 513 traveling direction position difference, 514 transverse direction position difference, 515 side sensor height, 516 upper sensor height, 517 left distance, 518 right distance, 519 oblique running angle, 521 Two-dimensional sectional shape, 800 toll booth system, 801 toll road, 802 island, 803 pillar, 810 communication antenna, 820 roadside radio device, 830 toll collection device.

Claims (12)

In a vehicle detection device for detecting a vehicle passing through a predetermined passage,
A plurality of sensor devices, a start detection unit, an end detection unit, a transit time calculation unit, a time difference calculation unit, a vehicle speed calculation unit, a vehicle length calculation unit, and a vehicle width calculation unit;
Each sensor device of the plurality of sensor devices emits radiated light from a predetermined radiation base point in a predetermined radiation direction, and receives the reflected light reflected by the reflecting object existing in the radiation direction. By calculating the distance to the reflecting object reflecting the radiated light,
The first sensor device among the plurality of sensor devices is a position in which the position of the radiation base is separated from the passage in the transverse direction of the passage crossing the passage, and the radial direction in the passage is in the radial direction. Radiate the above radiated light as
The second sensor device among the plurality of sensor devices is a position where the position of the radiation base point is away from the traffic path on the side opposite to the radiation base point of the first sensor device in the crossing direction of the traffic path. , In the vehicle traveling direction in which the vehicle travels, the position of the radiation base point is a position away from the radiation base point of the first sensor device, and the radiation light is emitted with the inside of the passageway as the radiation direction,
The start detection unit detects a reflection start time when the vehicle starts reflecting the radiated light as the reflective object with respect to at least one of the plurality of sensor devices,
The end detection unit detects a reflection end time when the vehicle ends reflection of the radiated light as the reflective object for at least one of the plurality of sensor devices,
The transit time calculation unit is configured to control the vehicle based on the reflection start time detected by the start detection unit and the reflection end time detected by the end detection unit for at least one of the plurality of sensor devices. Calculates the transit time it took to pass in front of the sensor device,
The time difference calculation unit calculates a time difference between a time at which a predetermined part of the vehicle passes in front of the first sensor device and a time at which the predetermined portion of the vehicle passes in front of the second sensor device,
The vehicle speed calculation unit calculates the speed of the vehicle based on the time difference calculated by the time difference calculation unit,
The vehicle length calculation unit calculates the vehicle length of the vehicle based on the passage time calculated by the passage time calculation unit and the speed calculated by the vehicle speed calculation unit,
The vehicle width calculation unit calculates the vehicle width of the vehicle based on the distance calculated by the first sensor device and the second sensor device. Each sensor device of the plurality of sensor devices has a predetermined scanning direction range as the radiation direction, emits radiation light that scans the scanning direction range,
The first sensor device emits radiated light that scans the scanning direction range in a direction in which a first scanning line segment exists on the passageway and is substantially parallel to the transverse direction of the passageway,
The second sensor device emits radiated light that scans the scanning direction range in a direction in which the second scanning line segment exists on the passage and is substantially parallel to the first scanning line segment. The vehicle detection device according to claim 1. Each sensor device of the plurality of sensor devices has a radiation device, a scanning device, a light receiving device, and a distance calculation device,
The radiation device radiates modulated light modulated by a predetermined modulation signal,
The scanning device bends the modulated light radiated by the radiation device to be radiated light that scans the scanning direction range,
The light receiving device receives the reflected light reflected by the reflecting object by the radiated light bent by the scanning device;
The distance calculating device demodulates the reflected light received by the light receiving device to obtain a demodulated signal, calculates a delay time of the demodulated signal with respect to the modulated signal, and calculates a distance to the reflecting object based on the calculated delay time. The vehicle detection device according to claim 2, wherein the vehicle detection device calculates the vehicle detection device.   4. The vehicle detection device according to claim 3, wherein the radiation device radiates laser light that is continuously wave-modulated by a sine wave signal as the modulated light.   The scanning device includes a scanning mirror composed of fine electromechanical elements, and the scanning mirror reflects the modulated light emitted by the radiation device, thereby bending the optical path of the modulated light. The vehicle detection device according to claim 3 or 4. The light receiving device has a photodiode having a long light receiving surface,
The vehicle detection device according to claim 3, wherein the photodiode receives the reflected light at the light receiving surface.   In the first sensor device and the second sensor device, a distance between the road surface and the radiation base point is 10 centimeters or more and 2 meters or less in a vertical direction perpendicular to the road surface, The distance between the radiation base point of the first sensor device and the radiation base point of the second sensor device in the vehicle traveling direction is 10 centimeters or more and 50 centimeters or less. Item 7. The vehicle detection device according to any one of Items 6 to 7. The vehicle detection device further includes a shape detection unit and a vehicle determination unit,
The shape detection unit detects the cross-sectional shape of the reflective object based on the distance calculated by the sensor device for each of the plurality of sensor devices,
The said vehicle determination part determines whether the said reflective object is a vehicle based on the cross-sectional shape which the said shape detection part detected, The Claim 1 thru | or 7 characterized by the above-mentioned. Vehicle detection device. The vehicle detection device further includes an axle detection unit,
The vehicle detection device according to claim 8, wherein the axle detection unit detects an axle of the vehicle based on a cross-sectional shape detected by the shape detection unit. The vehicle detection device further includes a vehicle height calculation unit and a parallel running determination unit,
Of the plurality of sensor devices, a third sensor device is configured such that the position of the radiation base point is higher than the radiation base points of the first sensor device and the second sensor device in a vertical direction perpendicular to the road surface. And radiates the radiated light with the radiation direction as the radiation direction,
The vehicle height calculation unit calculates the vehicle height of the vehicle based on the distance calculated by the third sensor device,
The parallel running determination unit determines whether or not the reflective object is running parallel based on the distance calculated by the third sensor device. The vehicle detection device described in 1. In a vehicle detection device for detecting a vehicle passing through a predetermined passage using a plurality of sensor devices,
Each sensor device of the plurality of sensor devices radiates radiated light from a predetermined radiating base point in a predetermined radiating direction, and receives the reflected light reflected by the reflecting object existing in the radiating direction. ,
The first sensor device among the plurality of sensor devices is a position in which the position of the radiation base is separated from the passage in the transverse direction of the passage crossing the passage, and the radial direction in the passage is in the radial direction. Radiate the above radiated light as
The second sensor device among the plurality of sensor devices is a position where the position of the radiation base point is away from the traffic path on the side opposite to the radiation base point of the first sensor device in the crossing direction of the traffic path. , In the vehicle traveling direction in which the vehicle travels, the position of the radiation base point is a position away from the radiation base point of the first sensor device, and the radiated light is emitted with the inside of the passageway as the radiation direction. A vehicle detection device. A vehicle detection device according to any one of claims 1 to 11 and a charge category determination unit,
The vehicle detection device is installed at at least one of an entrance and an exit of a toll section,
When the vehicle determination unit determines that the reflecting object is a vehicle, the charge category determination unit is at least one of a vehicle length calculated by the vehicle length calculation unit and a vehicle width calculated by the vehicle width calculation unit The toll fee charging system according to claim 1, wherein the toll classification of the vehicle is determined.

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