JP2008309533A - Method and apparatus for measuring vehicle shape - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To provide a method and an apparatus for measuring a vehicle shape, capable of measuring a vehicle being at rest with an arbitrary attitude (orientation) in a prescribed parking area, from a remote position, and of metering dimensions (vehicle height, vehicle length and vehicle width), the position and the attitude of the vehicle based on above measured data. <P>SOLUTION: The vehicle shape measuring method for measuring the vehicle height and the vehicle width of the vehicle being at rest in the prescribed parking area, at the position remote from the vehicle comprises: a three-dimensional coordinate value measuring step S1 of using a plurality of three-dimensional laser radars for emitting pulse laser light in a three-dimensional fashion toward both sides of the vehicle in the parking area, and measuring three-dimensional coordinate values of the both sides based on pulse laser light reflected by the both sides; a data processing step S2 of using a computer for applying a data processing to the three-dimensional coordinate values and determining vehicle data including the vehicle height and the vehicle width of the vehicle; and a vehicle data outputting step S3 of outputting the determined vehicle data. <P>COPYRIGHT: (C)2009,JPO&INPIT

Description

  The present invention relates to a vehicle shape measuring method and apparatus for measuring a stationary vehicle shape from a plurality of measurement positions and measuring the dimensions (vehicle length and width), position, and posture of the vehicle from the distance data.

  In a parking facility such as a passenger car, Patent Documents 1 to 5 have already been disclosed as means for measuring a vehicle body such as the width of a parked vehicle in a non-contact manner.

Patent Document 1 can automatically measure the vehicle width with high accuracy of the order of several millimeters without stopping the passing vehicle, and does not require large equipment such as a gantry or incidental equipment such as a reflector, and with a small number of detection devices. The vehicle width can be automatically measured, even if it is a streamlined vehicle body or even if it detects the arm of the passenger from the door mirror or window, the maximum vehicle width of the vehicle body can be measured accurately, even when the vehicle passes diagonally, The purpose is to accurately measure the vehicle width.
Therefore, as shown in FIG. 13, this means controls a pair of laser radars 52a and 52b provided opposite to each other on the both sides of the roadway through which the vehicle passes with a horizontal interval D, and each laser radar. A control processing unit 54 for processing the obtained data, and each laser radar scans a laser beam in a predetermined angle range up and down with respect to the passing vehicle to obtain cross-sectional data of both side surfaces of the vehicle body. The horizontal distances L1 and L2 from each laser radar to both side surfaces of the vehicle body are measured, the difference W (= D−L1−L2) is stored over the entire length of the vehicle, and the maximum value is used as the vehicle width.

Patent Document 2 aims to simplify the configuration to reduce the cost and facilitate the installation work.
Therefore, as shown in FIG. 14, this means has one scanning type distance measuring means L that scans in the width direction from above the traveling path R, and is installed above one side of the traveling path R. In the data processing unit 61 that processes the distance measurement data obtained by the scanning distance measuring means L to obtain the vehicle width and height, the data corresponding to the shape of the side surface of the vehicle to be scanned is the data. The vehicle width is obtained by performing an operation to supplement the data corresponding to the side shape on the opposite side.

Patent Document 3 aims to enable accurate vehicle width measurement even when the ceiling is low and the CCD camera cannot be installed at a sufficient height, and to enable vehicle width measurement even in the case of a high roof vehicle. To do.
Therefore, as shown in FIG. 15, this means simultaneously detects a vehicle 91 passing through the measurement position by a plurality of CCD cameras 72, a pair of non-contact distance meters 74, and a photoelectric sensor 76. Next, when the vehicle is classified as a normal vehicle by the photoelectric sensor 76, the position La and Lb on both sides of the vehicle is simultaneously detected by the non-contact distance meter, and a pair of CCD cameras 72b and 72c closest to the detected vehicle side surface are detected. The vehicle width is measured by image processing based on the image from. In addition, when the vehicle is classified as a high roof vehicle by the photoelectric sensor, the side surface positions La and Lb of the vehicle are simultaneously detected by the non-contact distance meter, and the distance between the side surface positions is set as the vehicle width.

Patent Document 4 aims to reliably measure an accurate vehicle width regardless of the vehicle body color or its concentration and even when the vehicle passes through the measurement unit obliquely.
Therefore, this means includes a measurement floor surface having a striped pattern extending linearly in the width direction of the vehicle, a CCD camera installed vertically downward on the measurement floor surface, and an image processing device for processing captured images. As shown in FIG. 16, (A) a CCD camera is used to capture images of both sides of the vehicle against the measurement floor, and (C) the difference between the vehicle density on the image and the stripe pattern density is calculated. (D) Among the sudden change line segments, a line segment extending substantially more than a predetermined length in the front-rear direction and spaced most apart in the width direction is used as an extraction segment. E) A pair of parallel lines is obtained by connecting extracted segments located substantially on the same line, and the interval between the parallel lines is defined as the vehicle width.

Patent document 5 aims at being able to measure the vehicle width including the mirror in a state where the vehicle under measurement is normally passing through a road without stopping.
Therefore, as shown in FIG. 17, this means arranges semiconductor laser groups 81A and 81B that irradiate light beams B at equal intervals perpendicular to the road M at an upper position perpendicular to the traveling direction of the vehicle 82 to be measured. The CCD linear sensors 83A and 83B for detecting the light spot are provided at the parallel positions of the laser groups 81A and 81B, and the input light beam B is opposed to the laser groups 81A and 81B on the road M, and the linear sensors 83A and 83B. Reflecting plates 84A and 84B are provided, and a vehicle width determining device 86 for determining the vehicle width of the vehicle 2 to be measured from the number of reflected light spots detected by the linear sensors 83A and 83B is provided.

JP 2000-298007 A, “Vehicle width measuring method and apparatus” Japanese Patent Application Laid-Open No. 11-28896, “Vehicle Shape Measuring Device and Vehicle Width Measuring Method” Japanese Patent Laid-Open No. 10-21490, “Vehicle Width Measurement Method” JP 09-54892 A, “Vehicle width measuring method and apparatus” Japanese Patent Application Laid-Open No. 07-167622, “Vehicle width measurement method and apparatus”

In Patent Documents 3 and 4 described above, a CCD camera is placed on the ceiling of a vehicle's traffic path, and an image obtained by photographing the vehicle from above is image-processed to extract the left and right contour lines of the vehicle and measure the vehicle width. is doing.
However, when a CCD camera is used, there is a drawback that stability is required unless the contrast difference between the background floor and the vehicle is high.
Thus, Patent Document 4 devises a contrast by drawing a striped pattern on the floor surface, but it is generally difficult to obtain the understanding of the parking lot owner to craft a floor surface such as a parking lot. Moreover, it is generally difficult to detect protrusions such as door mirrors.

Further, in Patent Documents 1 and 2 described above, the vehicle width is measured by arranging a scanning two-dimensional laser radar on the traffic path of the vehicle and obtaining the distance to the left and right contour lines of the vehicle while the vehicle passes. is doing. That is, the position where the laser beam hits is represented as a point, and the vehicle width is obtained by reconstructing the side surface of the vehicle with these point groups.
However, as in Patent Documents 1 and 2, with a means for measuring a vehicle while passing through a two-dimensional laser radar placed on the vehicle's passage, information on the overall shape of the vehicle can be obtained. Since the vehicle length (the traveling direction of the vehicle) varies depending on the vehicle speed, a reliable value cannot be obtained.
Further, since the vehicle is moving, the same part of the side surface portion of the vehicle can be measured only once with the laser beam, and the error is generally large depending on the distance accuracy of the laser radar, and noise and noise It is also difficult to distinguish.
In addition, since the influence of errors is not taken into consideration, the actual vehicle width range cannot be estimated from the obtained measurement result.
Furthermore, since the vehicle side surface is reconstructed with the measurement point group, it is difficult to distinguish between the boundary between the projection such as the door mirror and the side surface part and noise from the influence of the error.

In Patent Document 5 using the semiconductor laser group, the vehicle length (the traveling direction of the vehicle) varies depending on the speed of the vehicle, and thus a reliable value cannot be obtained.
Further, since the vehicle is moving, the same part of the side surface portion of the vehicle can be measured only once with the laser beam.

  Further, since the conventional means described above is based on the premise that the vehicle passes through a predetermined position in a predetermined posture (orientation), the vehicle stops at an arbitrary position (orientation) in an arbitrary region. In such a case, the dimensions (vehicle length and width), position, and posture of the vehicle could not be measured.

  The present invention has been developed to solve the above-described problems. That is, an object of the present invention is to measure a vehicle stationary in an arbitrary posture (orientation) within a predetermined parking area from a remote position, and measure the vehicle dimensions (vehicle height, vehicle length, vehicle The object is to provide a vehicle shape measuring method and apparatus capable of measuring a width), a position, and an attitude.

According to the present invention, there is provided a vehicle shape measuring method for measuring a vehicle length and a vehicle width of a vehicle stationary in a predetermined parking area from a position away from the vehicle,
A plurality of three-dimensional laser radars irradiate three-dimensionally with a pulse laser beam toward both sides of the vehicle in the parking area, and the three-dimensional coordinate values of both sides are obtained from the pulse laser beam reflected on the both sides. A three-dimensional coordinate value measuring step for measuring;
A data processing step of performing data processing on the three-dimensional coordinate value by a computer and determining vehicle data including a vehicle length and a vehicle width of the vehicle;
And a vehicle data output step of outputting the determined vehicle data. A vehicle shape measuring method is provided.

According to a preferred embodiment of the present invention, the data processing step includes a data input step of inputting the three-dimensional coordinate value measured in the three-dimensional coordinate value measurement step to a computer;
A model construction step of constructing an environment model that divides the space area where the parking area exists into a plurality of voxels made of rectangular parallelepipeds whose boundary surfaces are orthogonal to each other, and stores each voxel position;
A matching step of setting and storing a representative point and its error distribution inside the voxel corresponding to the coordinate value;
A surface reconstruction step of reconstructing the surface of the vehicle body based on the position of the representative point of each voxel;
A vehicle data determining step for determining a vehicle length and a vehicle width from the obtained three-dimensional data of voxels.

  In the vehicle data determination step, the three-dimensional data of the voxel obtained in the surface reconstruction step is projected onto the floor surface to obtain two-dimensional plane information, and the inclusion figure of the two-dimensional shape is obtained. Determine the width.

  In the model building step, when a maximum voxel is set to a size corresponding to the minimum necessary resolution and there are a plurality of measurement points in a single voxel, a single voxel is single. The voxel is further divided into a plurality of voxels hierarchically so that only the measured point exists.

After the matching step, a model update step for updating the environmental model is performed, and in the model update step, a voxel corresponding to a coordinate value of a newly input measurement point is searched,
The error distribution held by the voxel is sufficiently converged and the part where a certain voxel with a representative point exists in a small voxel is connected to a certain side is regarded as the side part of the vehicle. Isolate.

After the matching step, a model update step for updating the environmental model is performed, and in the model update step, a voxel corresponding to a coordinate value of a newly input measurement point is searched,
When there is no representative point in the voxel, the coordinate value and error distribution are set as the coordinate value and error distribution of the representative point.

After the matching step, a model update step for updating the environmental model is performed, and in the model update step, a voxel corresponding to a coordinate value of a newly input measurement point is searched,
When there is a representative point already set in the voxel, the newly acquired error distribution is compared with the already set error distribution in the voxel,
If the error distributions overlap each other, reset a new error distribution and a new representative point from both error distributions,
When the error distributions do not overlap with each other, the voxel is further divided into a plurality of voxels hierarchically so that only a single representative point exists within a single voxel.

  It is preferable to have a probability value in addition to the representative point and its error distribution inside the voxel.

Moreover, according to the present invention, there is provided a vehicle shape measuring device that measures the vehicle length and the vehicle width of a vehicle stationary within a predetermined parking area from a position away from the vehicle,
A plurality of three-dimensional laser radars that three-dimensionally irradiate a pulse laser beam toward both sides of the vehicle in the parking area and measure a three-dimensional coordinate value on both sides from the pulse laser beam reflected on the both sides When,
A data processing device that processes the three-dimensional coordinate values to determine vehicle data including a vehicle length and a vehicle width;
There is provided a vehicle shape measuring device comprising a vehicle data output device for outputting the determined vehicle data.

According to a preferred embodiment of the present invention, the data processing device includes a data input device that inputs a three-dimensional coordinate value measured by a three-dimensional laser radar to a computer;
A model construction device that divides a spatial region existing in the parking area into a plurality of voxels made of rectangular parallelepipeds whose boundary surfaces are orthogonal to each other, and constructs an environmental model that stores each voxel position;
A matching device for setting and storing a representative point and its error distribution inside a voxel corresponding to the coordinate value;
A surface reconstruction device that reconstructs the surface of the vehicle body based on the position of the representative point of each voxel;
A vehicle data determination device that determines the vehicle length and vehicle width from the obtained three-dimensional data of voxels.

  Further, the vehicle data determination device projects the three-dimensional data of the voxels obtained by the surface reconstruction device onto the floor surface to obtain two-dimensional plane information, and obtains an inclusion figure of the two-dimensional shape, thereby And determine the vehicle width.

According to the method and apparatus of the present invention described above, in the three-dimensional coordinate value measurement step using a plurality of three-dimensional laser radars, the pulse laser beam is three-dimensionally directed toward both sides of the vehicle in a predetermined parking area. Irradiate and measure the three-dimensional coordinate values of both sides from the pulsed laser light reflected on both sides,
In the data processing step using a computer, the three-dimensional coordinate value is data-processed to determine vehicle data including the vehicle length and vehicle width, so that not only the vehicle width but also the vehicle overall shape including the vehicle length is determined. Can be grasped.

Furthermore, according to the present invention, the following effects can be obtained.
(1) The same part of the vehicle can be measured several times, and the accuracy can be improved by statistical processing.
(2) The measurement results of a plurality of sensors with different viewpoints can be integrated, and the accuracy can be improved.
(3) By taking into account the error model of the sensor, it is possible to improve the measurement error and estimate the measurement error, and to ensure safety when allocating parking spaces according to the size of the vehicle and for automatic / manual guidance of the vehicle. It becomes possible to consider.
(4) It becomes possible to distinguish between noise and the other, and an improvement in accuracy can be expected.
(5) Since it is possible to distinguish the protruding portion such as the door mirror and the side surface portion of the vehicle by improving the accuracy, the vehicle width including the door mirror and the vehicle width not including the door mirror can be properly used depending on the application.
(6) By obtaining the two-dimensional plane information and obtaining the inclusion graphic, the vehicle length, the vehicle width, and the posture can be obtained stably.

  Hereinafter, preferred embodiments of the present invention will be described with reference to the drawings. In each figure, common portions are denoted by the same reference numerals, and redundant description is omitted.

FIG. 1 is a configuration diagram of a three-dimensional laser radar.
As shown in this figure, the three-dimensional laser radar 10 includes a radar head 12 and a controller 20. The pulsed laser light 1 oscillated from the laser diode 13 is shaped into parallel light 2 by the light projecting lens 14, scanned in a two-dimensional direction by the mirrors 18a and 18b and the polygon mirror 15 that rotates and swings, and is applied to the measurement object. Irradiated. The pulsed laser light 3 reflected from the measurement object is collected by the light receiving lens 16 via the polygon mirror 15 and converted into an electric signal by the photodetector 17.

The time interval counter 21 in the controller 20 measures the time interval between the start pulse 4 synchronized with the pulse oscillation timing of the laser diode 13 and the stop pulse 5 output from the photodetector 17. The signal processing board 22 outputs the time interval t when the reflected light is detected, the rotation angle θ of the polygon mirror, and the swing angle φ as polar coordinate data (r, θ, φ).
r is a distance with the measurement position (radar head installation position) as the origin, and is obtained by the equation r = c × t / 2. Here, c is the speed of light.
The determination processing unit 23 performs detection processing by converting polar coordinate data from the signal processing board into three-dimensional space data (x, y, z) having the radar head installation position as the origin. In this figure, reference numeral 24 denotes a drive unit.

The measurement range of the three-dimensional laser radar 10 described above is, for example, a horizontal field angle of 60 °, a vertical field angle of 30 °, and a maximum measurement distance of 50 m. The position detection accuracy is about 20 cm, for example.
Further, when displaying the measurement data as a distance image having a distance value in the depth direction for each pixel, if the number of measurement points in one frame is 166 points in the horizontal direction and 50 points in the scan direction, 166 × 50 per frame. = 8300 points are displayed. In this case, the frame rate is, for example, about 2 frames / second.

The points to be measured on the three-dimensional shape measured by the three-dimensional laser radar 10 are a group of discrete points, Δθ × r in the horizontal direction and Δφ × r in the vertical direction. For example, when Δθ = 60/166 × π / 180 = 6.3 × 10 ⁻³ radians, Δφ = 30/50 × π / 180 = 10.5 × 10 ⁻³ radians, r = 5.0 m, the closest proximity In this case, the distance between the measurement points is about 31.5 mm in the horizontal direction and about 52.5 mm in the vertical direction.

FIG. 2 is a diagram illustrating a relationship between polar coordinate data measured by the distance sensor and an error.
As shown in FIG. 2A, polar coordinate values (r, θ, φ) having an arbitrary measurement position as the origin are measured as measurement results. An error distribution as shown in the figure normally exists in the measurement result by the distance sensor.
This error distribution is normalized in the directions of measurement axes r, θ, and φ when the existence probability of the error distribution at r _s , θ _s , and φ _s is P (r _s , θ _s , φ _s ). For example, it can be expressed by the formula (1). Here, r, θ, φ are measured values from the sensor, σ _r , σ _θ , σ _φ are standard deviations, and A is a normalization constant.
As shown in FIG. 2B, the error distribution is a distribution that is normally included in a truncated cone shape (left figure) that is long in the r direction, but the difference between a and b is small in the distance. Therefore, this error distribution can be approximated to the safe side as an ellipsoid included in a rectangular parallelepiped.

FIG. 3 is an overall configuration diagram of the vehicle shape measuring apparatus of the present invention.
As shown in this figure, the vehicle shape measuring device of the present invention includes a plurality of three-dimensional laser radars 10, a data processing device 30, and a vehicle data output device 40.
A plurality (two in this example) of three-dimensional laser radars 10 three-dimensionally irradiate pulse laser light toward both side surfaces of the vehicle 9 in a predetermined parking area 11 and are reflected on both side surfaces of the vehicle 9. The three-dimensional coordinate values on both sides are measured from the pulsed laser beam.
The data processing device 30 performs data processing on the three-dimensional coordinate values obtained by the three-dimensional laser radar 10 and determines vehicle data including the vehicle length and the vehicle width of the vehicle 9.
The vehicle data output device 40 outputs the vehicle data determined by the data processing device 30 to another device 50.

  FIG. 4 is a configuration diagram of the data processing device 30. As shown in this figure, the data processing device 30 is a computer and includes a data input device 32, an external storage device 33, an internal storage device 34, a central processing device 35 and an output device 36.

The data input device 32 inputs the three-dimensional coordinate value of the vehicle 9 obtained by the three-dimensional laser radar 10 to the storage device. The data input device 32 may also have normal input means such as a keyboard.
The external storage device 33 is a hard disk, a floppy (registered trademark) disk, a magnetic tape, a compact disk, or the like. The external storage device 33 stores the inputted three-dimensional coordinate value of the vehicle 9, the voxel position, the representative point, its error distribution, and a program for executing the method of the present invention.
The internal storage device 34 is, for example, a RAM, a ROM, etc., and stores calculation information.
The central processing unit 35 (CPU) functions as a model construction device and a matching device, centrally processes operations and input / output, and executes a program together with the internal storage device 34.
The output device 36 is, for example, a display device and a printer, and outputs data stored in the external storage device 33 and the execution result of the program.

FIG. 5 is a flow chart illustrating the method of the present invention.
The method of the present invention is a vehicle shape measuring method for measuring the vehicle length and the vehicle width of a vehicle 9 stationary in a predetermined parking area 11 from a position away from the vehicle 9, and a three-dimensional coordinate value measuring step S1, It has a data processing step S2 and a vehicle data output step S3.

In the three-dimensional coordinate value measurement step S <b> 1, a plurality of three-dimensional laser radars irradiate pulse laser light three-dimensionally toward both side surfaces of the vehicle 9 in the parking area 11, and are reflected on both side surfaces of the vehicle 9. The three-dimensional coordinate values on both sides are measured from the pulse laser beam.
In the data processing step S2, the three-dimensional coordinate value of the vehicle 9 is data-processed by a computer (the data processing device 30 described above), and vehicle data including the vehicle length and the vehicle width of the vehicle 9 is determined.

  The data processing step S2 includes a data input step S21, a data correction step S22, a model construction step S23, a matching step S24, a surface reconstruction step S25, and a vehicle data determination step S26.

In the data input step S21, the three-dimensional coordinate value measured in the three-dimensional coordinate value measuring step S1 is input to the storage device of the computer (the data processing device 30 described above).
The three-dimensional coordinate value obtained by the three-dimensional laser radar 10 is distance data having a predetermined measurement position as the origin, and is represented by polar coordinate values (r, θ, φ). Further, the error distribution of each coordinate value is obtained by calculation from polar coordinate values (r, θ, φ), or is input in advance by another input means (for example, a keyboard).

In the data correction step S22, distance data correction processing is performed to improve the accuracy of the distance data. Further, the polar coordinate data and the position data of the three-dimensional laser radar 10 may be converted into three-dimensional space data (x, y, z) having an arbitrary fixed position as the origin.
In the distance data correction processing, isolated point removal, statistical processing, and the like are performed. An isolated point is a point that is isolated from surrounding points, and the measurement data is composed of a plurality of adjacent points. Therefore, the isolated point can be removed on the assumption of an erroneous measurement. The statistical process corrects the distance by statistically processing a plurality of measurements (for example, an average value) in consideration of the error distribution included in the measurement data.
Further, when the target three-dimensional shape can be linearly approximated or planarly approximated, these are preferably performed.

  FIG. 6 is a schematic diagram of model building steps when an octree is used for voxel division.

In the model construction step S23, as shown in this figure, an environment model in which a space area where a predetermined parking area 11 exists is divided into a plurality of voxels 6 made of rectangular parallelepipeds whose boundary surfaces are orthogonal to each other, and each voxel position is stored. Build up.
The shape of the voxel 6 may be a cube having the same length on each side or a rectangular parallelepiped having a different length on each side.
The length of each side of the voxel 6 is preferably set to a size corresponding to the minimum necessary resolution of the maximum voxel 6. Hereinafter, the largest voxel 6 is referred to as a level 1 voxel.
In addition, when there are a plurality of measured points in a single voxel, the voxel is further divided into eight and divided hierarchically so that only a single measured point exists in a single voxel. Divide into voxels. Hereinafter, a spatial region in which the largest voxel 6 is divided into eight is referred to as a level 2 voxel, and a spatial region in which k is performed k times is referred to as a level k + 1 voxel.

FIG. 7 is a schematic diagram of the constructed environmental model.
In the matching step S24, the representative point 7 and its error distribution 8 are set and stored inside the voxel 6 corresponding to the coordinate value on the three-dimensional shape, as shown in FIG. The terminal voxel can have only one representative point of measurement. Each voxel has a representative point of the measurement value and its error distribution, thereby representing the shape of the object.

In the matching step S24, the absolute position of the representative point is given by equation (2). Here, (x, y, z) is the relative coordinates of the voxels of the representative points, Sx, Sy, Sz is the side of the voxel at level 1 _{size, n x (k), n} y (k), n _z (k) is the address of the voxel at level k, and L is the level at which the representative point to be found exists.

FIG. 8 is a diagram showing a data structure of voxel data in the present invention.
In this figure, FIG. 8A is an example of a memory layout of each voxel data. In this figure, an arrow represents a link to data, and a pointer to the data is held as a value.
FIG. 8B shows an example in which a voxel at level 2 (1, 1, 0) has a representative point. In this figure, null represents an empty set.

The environmental model of the data structure described above has the following characteristics.
(1) Contents: A space is divided into small rectangular parallelepipeds, and representative points of measurement points and error distribution are held in each voxel.
(2) Accuracy: Equivalent to the representative value of the measurement points for each voxel.
(3) Presence: The presence or absence of an object can be expressed.
(4) Data amount: A memory is required in proportion to the number of voxels, but the size is fixed.
(5) Conversion from a point cloud: Suitable and less computational complexity.
(6) Access speed: Since the structure is simple, access to elements is fast.

Moreover, from this characteristic, the environmental model mentioned above satisfy | fills all the following effects AC.
Effect A: It is possible to express in consideration of errors.
Effect B: Necessary memory amount and calculation amount are below a certain amount.
Effect C: Not only the presence of an object but also the absence of an object can be expressed.

  Further, in FIG. 5, the surface reconstruction step S25 is performed after the matching step S24, and the environment model constructed in the model construction step S23 is updated.

FIG. 9 is a data processing flowchart in the surface reconstruction step S25. As shown in this figure, a search is made for a voxel corresponding to the coordinate value of the measured point newly input in step ST1, and if there is no representative point in the corresponding voxel in step ST2 (the voxel is empty). Sets (newly registers) the coordinate value and error distribution of the measurement point newly input in step ST3 as the coordinate value and error distribution of the representative point.
In step ST3, no object should exist in principle between the new measurement position (origin) and the measured point. Accordingly, the representative point in the voxel located between the new measurement position (origin) and the measurement point and the error distribution are reset or deleted.

FIG. 10 is a schematic diagram when there is a representative point already set in the corresponding voxel.
If there is a representative point already set in the corresponding voxel in step ST2 in FIG. 9, the error distribution newly acquired in step ST4 is compared with the error distribution in the already set voxel (that is, the difference points are the same). Judge whether it is one point).
If the error distributions overlap each other in this comparison (FIG. 10A), a new error distribution and a new error distribution center are reset from both error distributions in step ST5 (that is, the error distribution is synthesized).
In this comparison, if the error distributions do not overlap with each other (FIG. 10B), the voxel is further divided into eight so that only a single representative point exists in a single voxel in steps ST6 and ST7. Newly register by dividing into multiple voxels hierarchically.
The criteria for division and synthesis are determined from, for example, the degree of coincidence of error distributions. For example, a distance scale such as Mahalanobis distance can be used for the degree of coincidence of error distributions. Further, based on the two error distributions, it may be determined by a statistical test whether both represent the same point.

  FIG. 11 is another schematic diagram when error distributions overlap each other (FIG. 10A). In step ST5 of FIG. 9, a Kalman filter can be used as means for setting a new representative point and error distribution by combining the error distribution with two representative points. For example, in the case of two dimensions, as shown in this figure, the two representative points are x (1) and x ′ (2), the two error distributions are Σ (1) and Σ ′ (2), respectively. 11 is a schematic diagram for calculating the representative point x (2) and the error distribution Σ (2), where x (2) and the error distribution are Σ (2).

  Further, in FIG. 5, the vehicle data determination step S26 is performed after the surface reconstruction step S25, and the obtained three-dimensional data of the voxel is projected onto the floor surface to obtain two-dimensional plane information, and the inclusion of the two-dimensional shape is performed. The vehicle length and vehicle width are determined by determining the figure.

  In the vehicle data determination step S <b> 26, the voxel position, the representative point, and its error distribution may be output to the output device 36. When the output device 36 is a display device (for example, a CRT), it is preferable to perform stereoscopic display on a three-dimensional image. These data may be transferred to another device (for example, a control device or a computer) or may be output by a printer.

  The processing procedure shown in FIG. 5 repeats the processing each time new measurement data is obtained at a new measurement position, and stores the result in the external storage device 33.

In FIG. 5, in the vehicle data output step S <b> 3, the vehicle data determined in the data processing step S <b> 2 is output to another device 50.
Another device 50 includes, for example, (1) means for selecting a parking area according to the shape or dimensions of the vehicle, (2) fee calculation means according to the shape or dimensions of the vehicle, and (3) the shape or dimensions of the vehicle. Corresponding means for guiding the moving method of the vehicle to the corresponding parking space, and (4) guiding / transporting means for automatically guiding / transporting the vehicle to the parking space by the automatic transport device.
By using these means (another device 50) in combination, a parking area can be selected according to the shape or dimensions of the vehicle by means of (1), and the shape or shape of the vehicle by means of charge calculation means of (2). Charges can be calculated according to the dimensions, and the guide means of (3) can guide the vehicle movement method to the corresponding parking space according to the shape or dimensions of the vehicle. The vehicle can be guided / transported automatically to the parking space by the automatic transport device by the transport means.

FIG. 12 is a diagram showing an embodiment of the present invention. In this figure, (A) is the first measurement data, (B) is an integration result of a plurality of measurement data, and (C) is an enlarged view of the integration result of a plurality of measurement data.
From this figure, it can be seen that the accuracy can be improved by integrating the measurement data of a plurality of times.

According to the method and apparatus of the present invention described above, in the three-dimensional coordinate value measurement step using a plurality of three-dimensional laser radars, the pulse laser beam is three-dimensionally directed toward both sides of the vehicle in a predetermined parking area. Irradiate and measure the three-dimensional coordinate values of both sides from the pulsed laser light reflected on both sides,
In the data processing step using a computer, the three-dimensional coordinate value is data-processed to determine vehicle data including the vehicle length and vehicle width, so that not only the vehicle width but also the vehicle overall shape including the vehicle length is determined. Can be grasped.

Furthermore, according to the present invention, the following effects can be obtained.
(1) The same part of the vehicle can be measured several times, and the accuracy can be improved by statistical processing.
(2) The measurement results of a plurality of sensors with different viewpoints can be integrated, and the accuracy can be improved.
(3) By taking into account the error model of the sensor, it is possible to improve the measurement error and estimate the measurement error, and to ensure safety when allocating parking spaces according to the size of the vehicle and for automatic / manual guidance of the vehicle. It becomes possible to consider.
(4) It becomes possible to distinguish between noise and the other, and an improvement in accuracy can be expected.
(5) Since it is possible to distinguish the protruding portion such as the door mirror and the side surface portion of the vehicle by improving the accuracy, the vehicle width including the door mirror and the vehicle width not including the door mirror can be properly used depending on the application.
(6) By obtaining the two-dimensional plane information and obtaining the inclusion graphic, the vehicle length, the vehicle width, and the posture can be obtained stably.

  In addition, this invention is not limited to embodiment mentioned above, Of course, it can change variously in the range which does not deviate from the summary of this invention.

It is a block diagram of a three-dimensional laser radar. It is a figure which shows the relationship between polar coordinate data measured with the distance sensor, and an error. 1 is an overall configuration diagram of a vehicle shape measuring device of the present invention. 2 is a configuration diagram of a data processing device 30. FIG. 3 is a flowchart illustrating the method of the present invention. It is a schematic diagram of a model construction step when an octree is used for voxel division. It is a schematic diagram of the constructed environmental model. It is a figure which shows the data structure of the voxel data in this invention. It is a data processing flow figure in surface reconstruction step S25. 1 is an overall configuration diagram of a laser distance measuring device according to the present invention. It is another schematic diagram when error distributions mutually overlap. It is a figure which shows the Example of this invention. It is a schematic diagram of the apparatus of patent document 1. FIG. It is a schematic diagram of the apparatus of patent document 2. FIG. It is a schematic diagram of the apparatus of patent document 3. FIG. It is a schematic diagram of the apparatus of patent document 4. FIG. 11 is a schematic diagram of an apparatus disclosed in Patent Document 5.

Explanation of symbols

1 pulse laser light, 2 parallel light, 3 pulse laser light,
4 start pulse, 5 stop pulse,
6 voxels, 7 representative points, 8 error distribution,
10 3D laser radar, 12 radar head, 13 laser diode,
14 projection lens, 15 polygon mirror, 16 light receiving lens,
17 photo detector, 18a, 18b mirror,
20 controller, 21 time interval counter, 22 signal processing board,
23 judgment processing unit, 24 drive unit,
32 data input device, 33 external storage device, 34 internal storage device,
35 Central processing unit, 36 Output unit

Claims (11)

A vehicle shape measuring method for measuring a vehicle length and a vehicle width of a vehicle stationary in a predetermined parking area from a position away from the vehicle,
A plurality of three-dimensional laser radars irradiate three-dimensionally with a pulse laser beam toward both sides of the vehicle in the parking area, and the three-dimensional coordinate values of both sides are obtained from the pulse laser beam reflected on the both sides. A three-dimensional coordinate value measuring step for measuring;
A data processing step of performing data processing on the three-dimensional coordinate value by a computer and determining vehicle data including a vehicle length and a vehicle width of the vehicle;
And a vehicle data output step of outputting the determined vehicle data. The data processing step includes a data input step of inputting the three-dimensional coordinate value measured in the three-dimensional coordinate value measuring step to a computer;
A model construction step of constructing an environment model that divides the space area where the parking area exists into a plurality of voxels made of rectangular parallelepipeds whose boundary surfaces are orthogonal to each other, and stores each voxel position;
A matching step of setting and storing a representative point and its error distribution inside the voxel corresponding to the coordinate value;
A surface reconstruction step of reconstructing the surface of the vehicle body based on the position of the representative point of each voxel;
The vehicle shape measuring method according to claim 1, further comprising a vehicle data determining step for determining a vehicle length and a vehicle width from the obtained three-dimensional data of voxels.   In the vehicle data determination step, the three-dimensional data of the voxel obtained in the surface reconstruction step is projected onto the floor surface to obtain two-dimensional plane information, and the inclusion figure of the two-dimensional shape is obtained. The vehicle shape measuring method according to claim 1, wherein a width is determined.   In the model building step, when a maximum voxel is set to a size corresponding to the minimum necessary resolution and there are a plurality of measurement points in a single voxel, a single voxel is single. 4. The vehicle shape measuring method according to claim 2, wherein the voxel is further divided and divided into a plurality of voxels hierarchically so that only the measured point is present. 5. After the matching step, a model update step for updating the environmental model is performed, and in the model update step, a voxel corresponding to a coordinate value of a newly input measurement point is searched,
The error distribution held by the voxel is sufficiently converged and the part where a certain voxel with a representative point exists in a small voxel is connected to a certain side is regarded as the side part of the vehicle. The vehicle shape measuring method according to claim 2, wherein the vehicle shape measuring method is separated. After the matching step, a model update step for updating the environmental model is performed, and in the model update step, a voxel corresponding to a coordinate value of a newly input measurement point is searched,
6. The vehicle shape measurement method according to claim 2, wherein when there is no representative point in the voxel, the coordinate value and the error distribution are set as the coordinate value and the error distribution of the representative point. . After the matching step, a model update step for updating the environmental model is performed, and in the model update step, a voxel corresponding to a coordinate value of a newly input measurement point is searched,
When there is a representative point already set in the voxel, the newly acquired error distribution is compared with the already set error distribution in the voxel,
If the error distributions overlap each other, reset a new error distribution and a new representative point from both error distributions,
The voxel is further divided into a plurality of voxels hierarchically so that only a single representative point exists in a single voxel when error distributions do not overlap each other. Item 7. A vehicle shape measuring method according to any one of Items 2 to 6.   7. The vehicle shape measuring method according to claim 2, further comprising a probability value in addition to the representative point and its error distribution inside the voxel. A vehicle shape measuring device that measures the length and width of a vehicle stationary within a predetermined parking area from a position away from the vehicle,
A plurality of three-dimensional laser radars that three-dimensionally irradiate a pulse laser beam toward both sides of the vehicle in the parking area and measure a three-dimensional coordinate value on both sides from the pulse laser beam reflected on the both sides When,
A data processing device that processes the three-dimensional coordinate values to determine vehicle data including a vehicle length and a vehicle width;
A vehicle shape measuring device comprising: a vehicle data output device for outputting the determined vehicle data. The data processing device includes a data input device that inputs a three-dimensional coordinate value measured by a three-dimensional laser radar to a computer;
A model construction device that divides a spatial region existing in the parking area into a plurality of voxels made of rectangular parallelepipeds whose boundary surfaces are orthogonal to each other, and constructs an environmental model that stores each voxel position;
A matching device for setting and storing a representative point and its error distribution inside a voxel corresponding to the coordinate value;
A surface reconstruction device that reconstructs the surface of the vehicle body based on the position of the representative point of each voxel;
The vehicle shape measuring device according to claim 9, further comprising a vehicle data determining device that determines a vehicle length and a vehicle width from the obtained three-dimensional data of voxels.   By the vehicle data determination device, the three-dimensional data of the voxel obtained by the surface reconstruction device is projected onto the floor surface to obtain two-dimensional plane information, and the inclusion figure of the two-dimensional shape is obtained, so that the vehicle length and the vehicle The vehicle shape measuring device according to claim 9 or 10, wherein a width is determined.

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