JP7634176B2 - Speed measurement device and speed measurement method - Google Patents

Description

The present invention relates to a speed measurement device and a speed measurement method that use radar to measure the speed of a moving object moving on a road.

Technology for measuring the speed of vehicles traveling on roads is becoming widespread in order to crack down on speeding violations. A conventional technology for measuring the speed of vehicles on roads is to use a radar to irradiate radio waves onto a moving object on the road, capture the reflected waves, and process the signal (Doppler signal) contained in the reflected waves to measure the speed of the moving object (see Patent Document 1).

Patent No. 6309328

Now, radar devices that detect moving objects on roads (vehicles, people, animals, etc.) are expected to be used as so-called infrastructure radar in future vehicle automatic driving systems and the like. In such cases, the radar devices are installed on traffic light poles at intersections, street light poles on the roadside, and so on. This means that the radar devices will have to be installed at high heights.

However, in the conventional technology, the Doppler velocity is obtained as the velocity of the moving object as is, and if the radar device is installed at a high place, the error in the Doppler velocity from the actual velocity becomes large. In particular, when a large device with low radio frequency is used to detect a moving object at a distance, the influence of the radar installation height is small, but when trying to meet the demand for miniaturization of the device, the influence of the radar installation height becomes large.

The main objective of the present invention is to provide a speed measurement device and a speed measurement method that can accurately measure the speed of a moving object while minimizing the effects of installation height.

The speed measuring device of the present invention is a speed measuring device that is installed around a road and measures the speed of a moving body moving along the road, and is configured to include a radar unit that detects a moving body on the road and outputs a detected value of distance and a detected value of azimuth angle, and a detected value of speed, which is Doppler velocity; a memory unit that stores characteristic information that represents the relationship between a characteristic quantity given by the product of the distance and the speed at a specified speed and the azimuth angle; and a processor that estimates the speed of the moving body based on a measured value of the characteristic quantity obtained by multiplying the detected value of the distance and the detected value of the speed, the characteristic information, and the detected value of the azimuth angle.

The speed measurement method of the present invention is a speed measurement method that causes an information processing device to perform a process of measuring the speed of a moving object moving along a road, in which a processor of the information processing device acquires a distance detection value, an azimuth detection value, and a speed detection value, which is a Doppler velocity, from a radar unit that detects moving objects on the road, multiplies the distance detection value and the speed detection value to calculate a characteristic quantity measurement value, and acquires a speed estimation result based on characteristic information that indicates the relationship between the azimuth angle and the characteristic quantity at a predetermined speed, the characteristic quantity measurement value, and the azimuth angle detection value.

According to the present invention, the characteristic quantity given by the product of distance and speed does not depend on the vertical positional relationship between the radar and the moving object, so by estimating the speed of the moving object based on the characteristic quantity, it is possible to perform speed estimation that is not dependent on the height of the moving object. This makes it possible to accurately measure the speed of the moving object while suppressing the effects of the installation height.

FIG. 1 is a side view showing a state of speed measurement by the speed measurement device 1 according to the first embodiment; FIG. 1 is a side view showing a state of speed measurement by the speed measurement device 1 according to the first embodiment; FIG. 1 is a perspective view showing an overview of a process performed by a speed measurement device 1 according to a first embodiment; FIG. 1 is a plan view showing an overview of a process performed in a speed measurement device 1 according to a first embodiment; FIG. 2 is an explanatory diagram showing an overview of a process performed by the speed measurement device 1 according to the first embodiment; FIG. 2 is an explanatory diagram showing an overview of a process performed by the speed measurement device 1 according to the first embodiment; FIG. 1 is a block diagram showing a schematic configuration of a speed measurement device 1 according to a first embodiment. FIG. 2 is a flowchart showing a procedure of a process performed by the speed measurement device 1 according to the first embodiment. FIG. 11 is an explanatory diagram showing an overview of a process performed by the speed measurement device 1 according to the second embodiment; FIG. 11 is a block diagram showing a schematic configuration of a speed measurement device 1 according to a second embodiment. FIG. 11 is a flowchart showing a procedure of a process performed by the speed measurement device 1 according to the second embodiment. FIG. 13 is an explanatory diagram showing characteristic information according to the third embodiment; FIG. 11 is a block diagram showing a schematic configuration of a speed measurement device 1 according to a third embodiment. FIG. 11 is a flowchart showing a procedure of a process performed by the speed measurement device 1 according to the third embodiment.

The first invention made to solve the above problem is a speed measurement device that is installed around a road and measures the speed of a moving object moving along the road, and is configured to include a radar unit that detects moving objects on the road and outputs a detected value of distance and a detected value of azimuth angle, and a detected value of speed, which is Doppler velocity; a memory unit that stores characteristic information that represents the relationship between a characteristic amount given by the product of the distance and the speed at a specified speed and the azimuth angle; and a processor that estimates the speed of the moving object based on a measured value of the characteristic amount obtained by multiplying the detected value of the distance and the detected value of the speed, the characteristic information, and the detected value of the azimuth angle.

According to this, the characteristic quantity given by the product of distance and speed does not depend on the vertical positional relationship between the radar and the moving object, so by estimating the speed of the moving object based on the characteristic quantity, it is possible to perform a speed estimation that is not dependent on the height of the moving object. This makes it possible to accurately measure the speed of the moving object while minimizing the effects of the installation height.

In a second aspect of the present invention, the processor is configured to obtain an estimated value of a speed as the speed estimation result based on the characteristic information for each of a plurality of speeds.

This allows us to get a highly accurate estimate of speed.

In addition, in a third invention, the processor acquires the position of a measurement point on a plane whose coordinate axes are the azimuth angle and the characteristic quantity based on the detected value of the distance, the detected value of the azimuth angle, and the detected value of the speed, identifies two characteristic curves that are closest to the measurement point among a plurality of characteristic curves corresponding to the characteristic information, and acquires an estimate of the speed by an interpolation method based on the positional relationship between the characteristic curves and the measurement point.

This makes it possible to obtain highly accurate speed estimates without having to set a large number of characteristic information (characteristic curves) for each speed at fine intervals.

In addition, a fourth invention is configured such that the processor statistically processes multiple speed estimates obtained by executing the detection process of the radar unit multiple times, and obtains a final speed estimate.

This makes it possible to further improve the accuracy of the final speed estimate. Note that the statistical processing is, for example, processing such as averaging.

In a fifth aspect of the present invention, the processor acquires, as the speed estimation result, a speed determination result regarding whether or not the speed limit is exceeded, based on the characteristic information for the speed limit.

This allows for highly accurate speed determination results to be obtained.

In addition, a sixth invention is configured such that the processor integrates multiple speed determination results obtained by executing the detection process of the radar unit multiple times, thereby obtaining a final speed determination result.

This will allow for even greater accuracy in the final speed determination results.

In addition, a seventh invention is configured such that the processor determines the type of moving object detected by the radar unit, and obtains the speed estimation result based on the characteristic information corresponding to the type of moving object.

This makes it possible to estimate the speed of various moving objects with high accuracy.

An eighth invention is a speed measurement method that causes an information processing device to perform a process of measuring the speed of a moving body moving along a road, in which a processor of the information processing device acquires a distance detection value, an azimuth detection value, and a speed detection value which is Doppler velocity from a radar unit that detects moving bodies on a road, multiplies the distance detection value and the speed detection value to calculate a measurement value of a characteristic quantity, and acquires a speed estimation result based on characteristic information that indicates the relationship between the azimuth angle and the characteristic quantity at a predetermined speed, the measurement value of the characteristic quantity, and the azimuth detection value.

As with the first invention, this allows the speed of a moving object to be measured accurately while minimizing the effects of installation height.

The following describes an embodiment of the present invention with reference to the drawings.

First Embodiment
Fig. 1 is a side view showing a situation in which a speed is measured by the speed measurement device 1 according to the first embodiment. Fig. 2 is a side view showing a situation in which a speed is measured by the speed measurement device 1 when a moving object is different.

As shown in Figure 1, the speed measurement device 1 uses radar to detect moving objects moving on a road and measures the speed of the moving objects. This speed measurement device 1 is installed at a high location above the road, for example at a height of 5 to 6 m from the ground. Specifically, the speed measurement device 1 is attached to a traffic light pole installed at an intersection, a street light pole installed on the roadside, or a vehicle detector pole installed on the roadside.

In this embodiment, a speed detection value _Vm (Doppler speed) is output as a detection result of the radar of the speed measurement device 1. This speed detection value _Vm is a speed based on the radar of the speed measurement device 1, and differs from the actual speed V of a moving object moving on a road and contains an error. In particular, when the radar is installed at a high position, i.e., when the radar is far away from the road surface, the error in the speed detection value _Vm becomes large.

Furthermore, the error in the detected speed value _Vm (Doppler speed) depends on the height H of the moving object. For example, as shown in Figures 2A and 2B, even if a small two-wheeled vehicle and a large four-wheeled vehicle are traveling at the same speed V, the heights H of the moving objects are different. As a result, the elevation angles α when the moving objects are viewed from the radar of the speed measuring device 1 are different, and the detected speed values _Vm are also different.

On the other hand, if the elevation angle α and the ground position of the moving body can be acquired, the actual speed V of the moving body can be estimated from the detected speed value _Vm (Doppler speed). However, since the elevation angle and the ground position depend on the height H of the moving body, the elevation angle and the ground position cannot be estimated unless the height H of the moving body is known.

However, with a normal two-dimensional radar, although it can obtain the distance and azimuth angle based on the radar as detection results, it cannot obtain information on the elevation angle α or the height H of the moving object. As a result, it is not possible to accurately estimate the speed of the moving object.

In this embodiment, therefore, a speed estimation is performed that is not dependent on the height of the moving body, and the speed V of the moving body can be accurately estimated even when the speed measurement device 1 is installed at a high position. In particular, in this embodiment, a speed estimation that is not dependent on the height of the moving body can be performed using only the detection results of the two-dimensional radar, by estimating the speed of the moving body based on variables that are not dependent on the vertical positional relationship between the radar and the moving body.

The speed measurement method according to this embodiment may be used when the speed measurement device 1 is installed at a height where the elevation angle changes beyond the allowable limit according to the required measurement accuracy, depending on the expected variation in the height of the moving object. That is, when the speed measurement device 1 is located low, the variation in the height of the moving object does not affect the elevation angle very much, but when the speed measurement device 1 is located high, the elevation angle changes significantly depending on the variation in the height of the moving object, and the error in the Doppler velocity becomes noticeable. For this reason, when the speed measurement device 1 is located high, the speed measurement accuracy can be ensured by adopting the speed measurement method according to this embodiment.

As shown in FIG. 1, the elevation angle α is the complement of the angle β (depression angle) in the vertical direction in which the moving object is viewed from the radar of the speed measuring device 1, with the horizontal direction as the reference.

Next, an overview of the processing performed by the speed measurement device 1 according to the first embodiment will be described. FIG. 3 is an overhead view showing an overview of the processing performed by the speed measurement device 1. FIG. 4 is a plan view showing an overview of the processing performed by the speed measurement device 1.

As shown in FIG. 3, in this embodiment, the detection results of the radar of the speed measurement device 1 include a detected distance value r _m and a detected azimuth angle value θ _m based on the radar, and a detected speed value V _m (Doppler speed).

Here, the relationship between the detected distance value r _m based on the radar, the horizontal distance r _g from the radar to the moving object, and the elevation angle α is expressed by the following equation:
r _m =r _g /sin(α) (Formula 1)

Further, the detected velocity value _Vm (Doppler velocity) with respect to the radar, the horizontal velocity _Vg of the moving object with respect to the radar, and the elevation angle α have the following relationship:
V _m =V _g ×sin(α) (Formula 2)

From equations 1 and 2, r _m ×V _m is expressed by the following equation.
r _m ×V _m = r _g /sin (α) × V _g × sin (α) (Formula 3)
r _m ×V _m = r _g ×V _g (Formula 4)

Here, as shown in Equation 4, the rV value ( _rg x _Vg = _rm x _Vm ) (characteristic quantity) is calculated from the detected distance value _rm and the detected speed value _Vm (Doppler speed) which are the radar detection results. The rV value is also independent of the elevation angle α. In other words, the rV value is independent of the height H of the moving body, and is the same for both small two-wheeled vehicles and large four-wheeled vehicles. Therefore, if the speed of the moving body is estimated based on the rV value, it is possible to perform a speed estimation that is independent of the height H of the moving body.

On the other hand, as shown in Fig. 4, when a moving object moves on a road, the detected value _θm of the azimuth angle changes as the position of the moving object changes. In addition, since the radar of the speed measuring device 1 is fixed, the positional relationship between the radar and the road does not change. Therefore, when a moving object moving on a road is detected by the radar, the position of the moving object can be identified based on the detected value _θm of the azimuth angle as a detection result. In addition, the horizontal distance _rg from the radar to the moving object changes according to the detected value _θm of the azimuth angle. Therefore, the rV value is a variable that depends on the detected value _θm of the azimuth angle.

Next, an overview of the processing performed by the speed measurement device 1 according to the first embodiment will be described. Figures 5 and 6 are explanatory diagrams showing an overview of the processing performed by the speed measurement device 1.

In this embodiment, a θ-rV curve (characteristic curve) that represents the relationship between the azimuth angle θ and the rV value is set on a θ-rV plane with the horizontal axis (first coordinate axis) being the azimuth angle θ and the vertical axis (second coordinate axis) being the rV value ( _rg × _Vg = _rm × _Vm ). Here, the rV value changes according to the actual speed of the moving body, but assuming a state in which the moving body is moving at a constant speed, a θ-rV curve (characteristic curve) is set for each predetermined speed.

Furthermore, when the azimuth angle θ is constant, the rV value increases as the actual speed of the moving object increases. Therefore, the θ-rV curve with a faster speed is located on the upper side of the θ-rV plane.
In the example shown in FIG. 5, the actual speed of the moving body is set to 40 km/h, 50 km/h, and 60 km/h, and the θ-rV curve for each speed is drawn on the θ-rV plane.

On the other hand, the speed measuring device 1 obtains the detected distance value r _m , the detected azimuth angle value θ _m , and the detected speed value V _m (Doppler speed) as the detection results of the radar. Therefore, by finding the measured rV value (r _g ×V _g =r _m ×V _m ) from Equation 4 based on the detected distance value r _m and the detected speed value V _m (Doppler speed), it is possible to set a measurement point P _m on the θ-rV plane with the measured rV value and the detected azimuth angle value θ _m as the coordinate values on the horizontal and vertical axes, respectively.

5 shows an example in which the measurement point _Pm overlaps with any of the θ-rV curves for each speed. In this case, the speed of the θ-rV curve with the measurement point _Pm overlapping is obtained as an estimated value of the speed.

6A shows an example in which the measurement point _Pm is between the θ-rV curve of the speed _V1 and the θ-rV curve of the speed _V2 . In this case, the speed estimate is obtained by the interpolation method. At this time, the speed estimate is obtained by the following formula based on the speeds _V1 , _V2 and the interpolation coefficient a.
V=a・V ₁ +(1-a)・V ₂ (Formula 5)
Here, the interpolation coefficient a may be set based on the positional relationship between the measurement point _Pm , point _P1 on the θ-rV curve _of the speed _V1 when the azimuth angle θ is the detected value θm, and point _P2 on the θ-rV curve of the speed _V2 when the azimuth angle θ is the detected value _θm .

Furthermore, when there are three or more θ-rV curves for each speed, the two rV curves immediately above and below the measurement point _Pm may be identified and an interpolation method may be performed.

The example shown in Fig. 6B is a case where radar detection processing is performed multiple times on the same moving object. In this case, multiple measurement points _Pmi (i = 1, ..., n) are obtained by multiple detection processing, and an estimated speed value V _i (i = 1, ..., n) for each time is obtained from the position (coordinate) of the measurement point _Pmi for each time. Then, the estimated speed values V _i for each time are averaged to calculate a final estimated speed value. This makes it possible to improve the accuracy of the estimated speed value.

In addition, since the azimuth angle θ changes as the moving body moves, when the detection process is performed multiple times on the same moving body, the measurement points _Pmi for each time are obtained lined up at intervals corresponding to the measurement timing.

In this embodiment, the average value is calculated as the statistical processing for the estimated value V _i of the speed obtained in each measurement process, but the maximum value (excluding abnormal values) may be obtained. In this embodiment, a speed measurement section is set, and a moving object is detected within the speed measurement section to measure the speed. This speed measurement section is a range of the azimuth angle θ on the θ-rV plane.

Although Figures 3 and 4 are based on the assumption that the road is straight and horizontal, the road is not limited to being straight or horizontal. Even if the road is curved or inclined, the speed can be estimated using the same procedure by generating characteristic information suited to the site.

Next, the general configuration of the speed measurement device 1 according to the first embodiment will be described. Figure 7 is a block diagram showing the general configuration of the speed measurement device 1.

The speed measuring device 1 includes a radar unit 11, a memory unit 12, and a processor 13.

The radar unit 11 includes an antenna 21 and a signal processing unit 22. The antenna 21 emits high-frequency radio waves and captures the reflected waves. The signal processing unit 22 processes the reflected waves captured by the antenna 21, and includes devices such as an ADC (Analog to Digital Converter) and a DSP (Digital Signal Processor). The signal processing unit 22 outputs a detected distance value r _m , a detected azimuth angle value θ _m , and a detected velocity value V _m (Doppler velocity) as detection results.

The storage unit 12 stores programs and the like to be executed by the processor 13. The storage unit 12 also stores characteristic information generated in advance by the characteristic information generating device 2, specifically, information relating to a table or formula corresponding to a θ-rV curve that expresses the relationship between the azimuth angle θ and the rV value ( _rg × _Vg = _rm × _Vm ). The storage unit 12 includes devices such as memory.

The processor 13 executes various processes related to speed measurement by executing the programs stored in the memory unit 12. In this embodiment, the processor 13 performs detection result acquisition processing, measurement point position acquisition processing, speed estimation processing, and the like. The processor 13 includes devices such as a CPU.

In the detection result acquisition process, the processor 13 acquires the detected distance value r _m , the detected azimuth angle value θ _m , and the detected velocity value V _m (Doppler velocity) as detection results from the radar unit 11 .

In the measurement point position acquisition process, the processor 13 acquires the coordinates (θ _{m , r m ×} V _m ) of the measurement point P _m on the θ-rV plane based on the detected distance value r m , the detected azimuth angle value θ _m , and the detected _velocity value V _m .

In the speed estimation process, the processor 13 identifies the upper and lower θ-rV curves immediately adjacent to the measurement point _Pm based on the positional relationship between the coordinates ( _θm , _rm × _Vm ) of the measurement point Pm and the θ-rV curves for each speed. Then, the processor 13 calculates an estimated speed value as a speed estimation result by an interpolation method based on the speeds of the upper and lower θ-rV curves.

The speed measurement device 1 may be configured such that the radar unit 11, memory unit 12, processor 13, etc. are housed in a single housing, but the controller including the memory unit 12, processor 13, etc. and the radar unit 11 may be configured as separate entities.

In addition, the speed measurement device 1 may be configured to be connected to a server (information processing device) (not shown) via a communication path such as a network, so that the processes related to speed measurement executed by the processor 13, specifically, the detection result acquisition process, the measurement point position acquisition process, and the speed estimation process, etc., may be performed by the server.

The function of the speed measuring device 1 may also be incorporated in a roadside device (not shown) that exchanges vehicle driving information, traffic information, and the like with an in-vehicle terminal.

The characteristic information generating device 2 is composed of a PC (information processing device). This characteristic information generating device 2 generates characteristic information, specifically, information on a table or a formula corresponding to a θ-rV curve that represents the relationship between the azimuth angle θ and the rV value ( _rg × _Vg = _rm × _Vm ).

The characteristic information also differs depending on the installation environment of the speed measurement device 1. For this reason, characteristic information is generated for each speed measurement device 1. In other words, the characteristic information generating device 2 uses learning information collected by actually moving a mobile object on the roads at the site where the speed measurement device 1 is installed to generate characteristic information suited to the state of the local roads and the installation state of the speed measurement device 1.

Here, the learning information is a combination of the azimuth angle θ and the rV value ( _rg × _Vg = _rm × _Vm ). In addition, by collecting learning information while changing the speed of the moving body within an expected range, characteristic information for each of a plurality of speeds can be generated. In addition, when road construction is carried out and the road condition changes, learning information is collected again and characteristic information is regenerated.

Next, the processing steps performed by the speed measurement device 1 according to the first embodiment will be described. FIG. 8 is a flow diagram showing the processing steps performed by the speed measurement device 1. Note that FIG. 8 shows an example in which the detection process of the radar unit 11 is performed multiple times on the same moving object, as shown in FIG. 6(B).

First, the processor 13 repeats the measurement process a predetermined number of times (n times) (ST101 to ST106).

In this measurement process, first, the processor 13 acquires the detected distance value r _m , the detected azimuth angle value θ _m , and the detected velocity value V _m (Doppler velocity) as detection results from the radar unit 11 (detection result acquisition process) (ST102).

Next, the processor 13 acquires the coordinates (θ m , r _m ×V _m ) of the measurement point P _m on the θ-rV plane based on the detected distance value r _m , the detected azimuth angle value θ _m , and the detected velocity value _{V m} (measurement point position acquisition process) (ST103).

Next, the processor 13 identifies the upper and lower θ-rV curves immediately adjacent to the measurement point _Pm based on the positional relationship between the coordinates ( _θm , _rm × _Vm ) of the measurement point Pm and the θ-rV curves for each speed (ST104).Then, the processor 13 calculates an estimate of the speed by interpolation based on the speeds of the upper and lower θ-rV curves (speed estimation process) (ST105).

The above measurement process is repeated a predetermined number of times (n times) to obtain the speed estimate V _i (i=1,...,n) for each measurement, and then the processor 13 averages the speed estimate V _i for each measurement to calculate the speed estimate (ST107).Then, the processor 13 outputs the speed estimate (ST108).

Second Embodiment
Next, a second embodiment will be described. Note that points not particularly mentioned here are similar to the above-mentioned embodiment. Fig. 9 is an explanatory diagram showing an overview of the process performed in the speed measurement device 1 according to the second embodiment. Fig. 10 is a block diagram showing a schematic configuration of the speed measurement device 1 according to the second embodiment.

In the first embodiment, the moving speed of the moving object is acquired, but in the present embodiment, it is determined whether the moving object is overspeeding (speeding violation), that is, whether the moving object's speed exceeds the speed limit (threshold value). Specifically, it is determined whether the measurement point P _m is located above or below the θ-rV curve corresponding to the speed limit. That is, if the measurement point P _m is located above the θ-rV curve corresponding to the speed limit, it is determined that the moving object is overspeeding. On the other hand, if the measurement point P _m is located below or directly above the θ-rV curve corresponding to the speed limit, it is determined that the moving object is not overspeeding.

In addition, to improve accuracy, the radar detection process and speeding determination process may be performed multiple times. In this case, the multiple determination results are integrated to obtain a final speeding determination result. At this time, the determination result may be determined by majority vote, for example. In other words, the number of determination results that indicate speeding is occurring is compared with the number of determination results that indicate no speeding, and the determination result with the greater number is determined to be the final determination result.

As shown in FIG. 10, the configuration of the speed measurement device 1 is the same as that of the first embodiment (see FIG. 7). In addition, the memory unit 12 stores characteristic information corresponding to a speed limit that has been created in advance.

The processor 13 also performs detection result acquisition processing and measurement point position acquisition processing, similar to the first embodiment, but instead of speed estimation processing, it performs speeding determination processing.

In the speeding determination process, the processor 13 determines whether or not the speed is exceeded, specifically, whether the measurement point _Pm is located above or below the θ-rV curve corresponding to the speed limit, as a result of the speed estimation.

Next, the processing steps performed by the speed measurement device 1 according to the second embodiment will be described. FIG. 11 is a flow diagram showing the processing steps performed by the speed measurement device 1.

First, the processor 13 repeats the measurement process a predetermined number of times (n times) (ST101 to ST111).

In this measurement process, first, the processor 13 acquires the detected distance value r _m , the detected azimuth angle value θ _m , and the detected velocity value V _m (Doppler velocity) as detection results from the radar unit 11 (ST102).

Next, the processor 13 acquires the coordinates (θ m , r _m ×V _m ) of the measurement point P _m on the θ-rV plane based on the detected distance value r _m , the detected azimuth angle value θ _m , and the detected velocity value _{V m} (measurement point position acquisition process) (ST103).

Next, the processor 13 determines whether the measurement point _Pm is located above or below the θ-rV curve corresponding to the speed limit (ST111).

The above judgment process is repeated a predetermined number of times (n times) to obtain the speeding judgment result for each time. Next, the processor 13 integrates the speeding judgment results for each time to obtain the final speeding judgment result (ST113). The processor 13 then outputs the speeding judgment result (ST114).

When speeding is monitored, the vehicle number is obtained by reading the license plate number, and the vehicle on the road is photographed by a camera to obtain an image of the driver's face. In this case, the camera constantly photographs vehicles on the road and temporarily stores the photographed images for a specified period of time. When the speed measuring device 1 detects a speeding vehicle, the images captured during the period in which the vehicle was photographed are extracted and stored in an appropriate storage device, and are also sent to the monitoring center.

Third Embodiment
Next, a third embodiment will be described. Note that points not specifically mentioned here are the same as those in the above-mentioned embodiments. Fig. 12 is an explanatory diagram showing characteristic information according to the third embodiment. Fig. 13 is a block diagram showing a schematic configuration of a speed measurement device 1 according to the third embodiment.

The moving speed of a moving object varies greatly depending on the type of moving object. For example, the moving speed of a vehicle and a person varies greatly. Therefore, in this embodiment, characteristic information (a table or a formula corresponding to the θ-rV curve) is created in advance for each type of moving object. Then, when measuring the speed, the type of moving object to be measured is identified, and the speed is estimated using the characteristic information corresponding to that type of moving object.

In the example shown in Figures 12(A) and (B), type A of moving object (relatively slow moving object, such as a person or bicycle) and type B of moving object (relatively fast moving object, such as a four-wheeled vehicle or motorcycle) are distinguished, and characteristic information (θ-rV curve) relating to type A and type B is created in advance.

As shown in FIG. 13, the configuration of the speed measurement device 1 is the same as that of the first embodiment (see FIG. 7). In addition, the memory unit 12 stores characteristic information for each type of moving object that has been created in advance.

The processor 13 also performs detection result acquisition processing, measurement point position acquisition processing, and speed estimation processing, as in the first embodiment, but also performs moving object type determination processing, and characteristic information selection processing.

In the moving object type discrimination process, the processor 13 discriminates the type of moving object to be measured (e.g., four-wheeled vehicle, motorcycle, person, bicycle, etc.) based on the detection results of the radar unit 11. Note that the moving object on the road may be photographed by a camera, and the type of moving object may be discriminated based on the captured image.

In the characteristic information selection process, the processor 13 selects characteristic information (θ-rV curve) according to the type of moving object.

Next, the processing steps performed by the speed measurement device 1 according to the third embodiment will be described. FIG. 14 is a flow diagram showing the processing steps performed by the speed measurement device 1.

First, the processor 13 determines the type of moving object to be measured based on the detection results of the radar unit 11 (moving object type determination process) (ST121). The processor 13 then selects characteristic information (θ-rV curve) according to the type of moving object (characteristic information selection process) (ST122). The subsequent steps (ST101 to ST108) are the same as those in the first embodiment.

As described above, the embodiments have been described as examples of the technology disclosed in this application. However, the technology in this disclosure is not limited to this, and can also be applied to embodiments in which modifications, substitutions, additions, omissions, etc. have been made. It is also possible to combine the components described in the above embodiments to create new embodiments.

The speed measurement device and method according to the present invention have the effect of being able to accurately measure the speed of a moving object while minimizing the effects of installation height, and are useful as a speed measurement device and method that uses radar to measure the speed of a moving object moving on a road.

1. Speed measuring device (information processing device)
2 characteristic information generating device 11 radar unit 12 storage unit 13 processor 21 antenna 22 signal processing unit

Claims (8)

A speed measurement device that is installed around a road and measures the speed of a moving object moving along the road,
a radar section for detecting a moving object on a road and outputting a detected value of distance, a detected value of azimuth angle, and a detected value of speed, which is Doppler velocity;
a storage unit that stores characteristic information that indicates a relationship between a characteristic amount given by the product of the distance and the speed at a predetermined speed and the azimuth angle;
a processor that estimates the speed of the moving object based on a measured value of a characteristic amount obtained by multiplying the detected value of the distance and the detected value of the speed, the characteristic information, and the detected value of the azimuth angle;
A speed measuring device comprising: The processor,
2. The speed measurement device according to claim 1, wherein an estimated value of the speed is obtained as the speed estimation result based on the characteristic information for each of a plurality of speeds. The processor,
acquiring a position of a measurement point on a plane having coordinate axes of the azimuth angle and the characteristic amount based on the detected value of the distance, the detected value of the azimuth angle, and the detected value of the velocity;
Identifying two characteristic curves that are closest to the measurement point among a plurality of characteristic curves corresponding to the characteristic information;
3. The speed measuring device according to claim 2 , wherein the estimated value of the speed is obtained by an interpolation method based on a positional relationship between the characteristic curve and the measurement points. The processor,
3. The speed measurement device according to claim 2, wherein a final speed estimate is obtained by performing a statistical process on a plurality of speed estimates obtained by performing the detection process of the radar unit a plurality of times. The processor,
2. The speed measurement device according to claim 1, further comprising: a speed determination result as to whether or not the speed limit is exceeded, as the speed estimation result, based on the characteristic information at the speed limit. The processor,
6. The speed measuring device according to claim 5 , wherein a final speed determination result is obtained by integrating a plurality of speed determination results obtained by executing the detection process of the radar unit a plurality of times. The processor,
Identifying the type of moving object detected by the radar unit;
2. The speed measuring device according to claim 1, wherein the speed estimation result is obtained based on the characteristic information corresponding to a type of moving object. A speed measurement method for causing an information processing device to perform a process for measuring the speed of a moving object moving along a road, comprising:
The processor of the information processing device
A detection value of distance, a detection value of azimuth angle, and a detection value of speed, which is Doppler speed, are obtained from a radar unit that detects a moving object on a road;
multiplying the detected distance value and the detected speed value to calculate a measured value of a characteristic quantity;
A speed measurement method comprising the steps of: obtaining an estimated speed result based on characteristic information representing a relationship between the azimuth angle and the characteristic quantity at a predetermined speed, a measured value of the characteristic quantity, and a detected value of the azimuth angle.

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