JP6941404B2 - Railroad crossing obstacle detection device - Google Patents

Description

The present invention relates to a railroad crossing obstacle detection device that irradiates an aerial propagating wave such as infrared rays into a railroad crossing to detect a railroad crossing passage (obstacle) such as a person or a vehicle on the railroad crossing. Regarding a level crossing obstacle detection device of the level crossing radar type that receives the reflected wave and measures the position while sweeping the level crossing, more specifically, a computer determines the existence of obstacles based on the measurement data obtained by such a method. Regarding the railroad crossing obstacle detection device performed at.

The level crossing obstacle detection device of the plane sweep radar type (see, for example, Patent Document 1) covers the area of the railroad crossing crossing the railroad track located between the blocking rods on both sides of the railroad track and the surface area above the railroad crossing. As a detection area, a plane sweep measurement unit (laser radar, etc.) that receives reflected waves while sweeping and transmitting airborne waves toward the obstacle detection area and measures the distance and direction, and the measurement can be obtained. It is equipped with a determination unit that determines the presence or absence of an obstacle in the obstacle detection area based on the measured data.

Among them, the plane sweep measurement unit (see, for example, Patent Documents 1 and 2) includes an aerial propagating wave transmitter / receiver that transmits an aerial propagating wave and a reflected wave toward an obstacle detection region, and an aerial propagating wave transmitter / receiver. A rotation mechanism that normally rotates within a predetermined angle, a rotation control unit that controls the rotational movement and measures or enables direction measurement of transmission / reception of airborne waves, and transmission / reception signals of the airborne wave transmission / reception unit. It is equipped with a signal processing unit that measures the distance from the transmission position to the reflection position based on.

Further, the determination unit is provided with a computer as a means for executing software for determining the contents of the data processing and the determination processing of determining the presence or absence of an obstacle based on the measurement data.
When it is necessary to ensure high reliability, a fail-safe computer capable of manifesting a hardware failure is adopted as this computer (see, for example, Patent Documents 3 to 5).
Further, in the software processing, after tracing the sequence of data to grasp the object shape, the object shape is collated with the storage shape to determine whether or not the object is an obstacle (). For example, see Patent Document 1).

Since the aerial propagating wave transmitter / receiver is installed at the same height as the blocking rod at the time of descent in such a level crossing obstacle detection device of the plane sweep radar type, it is installed at a much higher place to cross the railroad crossing. Compared to a three-dimensional railroad crossing obstacle detection device that gives a bird's-eye view, it is easier to reduce costs.
In addition, compared to the beam type that has been used for a long time, the number of installations can be reduced because the transmitter / receiver can be integrated, and the resolution is good, so not only large ones such as automobiles but also small ones such as individual passers-by and wheelchairs. It has the advantage of being able to detect even things.

Further, in the data processing and the discrimination processing, each time a set of plane sweeps is performed, the object shape is grasped by tracing the sequence of measurement point data (pair of distance and direction) included in the measurement data. Along with the processing, if even a part of the detected object is between the blocking rods on the crossing path, it is determined that there is an obstacle in the crossing (see, for example, Patent Document 1). .. Such processing in the image (that is, processing related to the measurement data obtained by the above-mentioned collective plane sweep) avoids undesired false detection by the measurement data related to low-density disturbance such as snowfall and rainfall. , Since the original detection target such as a car or a passerby is detected based on high-density measurement data, it is useful for improving the detection accuracy.

Japanese Unexamined Patent Publication No. 2006-007818 Japanese Unexamined Patent Publication No. 2006-214961 Japanese Unexamined Patent Publication No. 2006-338094 Japanese Patent Application No. 2016-163579 (application) Japanese Patent Application No. 2017-010727 (application)

However, in the plane sweep radar type crossing obstacle detection device, the measurement point data is neither Cartesian coordinates nor matrix shape unlike the camera image, and the sequence of the distance and direction represented by polar coordinates or the direction is known. As the expansion data, if it can be omitted, it can be obtained by a series of distances under polar coordinates. For this reason, when processing data to detect obstacles in railroad crossings from measurement point data, it is possible to identify obstacle candidates by simple in-image tracking that can be called a trace, and to continue for a short predetermined time related to the obstacle candidates. Tracking that tracks obstacle candidates across multiple images over a relatively long period of time until the obstacle candidates advance to the railroad crossing, even if confirmed, can also be called grouping suitable for such tracking. Such processing was not performed by the level crossing obstacle detection device of the plane sweep radar type.
Therefore, the first technical issue is to realize a level crossing obstacle detection device of a plane sweep radar type that can track an obstacle candidate until it advances to the railroad crossing road.

In addition, although it partially overlaps with the above-mentioned one, in detail, as described above, the plane sweep radar type crossing obstacle detection device irradiates an object with an aerial propagating wave such as an infrared pulse laser beam and bounces off. By measuring the time until, the measurement point data (set of distance and direction) obtained by measuring one AF point of the object is obtained. Then, by repeating such measurement at a fine sweep angle while performing a horizontal sweep, a series of measurement data (a series of pairs of distance and direction) is acquired.
Therefore, if there is a solid object such as a car or a person to be detected, measurement data related to a highly continuous and high-density point cloud can be obtained, but for disturbing objects such as snow and raindrops that are not to be detected. Obtains measurement data relating to a low-density point cloud with low continuity.

Moreover, during rainfall and snowfall, solid objects and disturbance objects coexist, and especially when a disturbance object exists in front of the solid object, the distance measurement (distance measurement) for the solid object behind is disturbed, and the solid object is disturbed. Measurement data point group density decreases.
Practical crossing obstacle detection devices are required to reliably detect objects that should be detected and reliably eliminate objects that should not be detected, and distance measurement points (distance measurement points) due to disturbance objects. Does not specify / recognize as the measurement point data group of the obstacle candidate, but identifies / recognizes only the distance measurement point group of the solid object to be detected as the distance measurement point group (measurement point data group) of the obstacle candidate. is important.
Therefore, it is a second technical problem to realize a level crossing obstacle detection device of a plane sweep radar type that can accurately perform grouping processing without being disturbed even if there is a disturbance such as snow or rain.

Furthermore, in the tracking process following such grouping process, position estimation and position prediction using a Kalman filter or the like are easy to use, but in such position estimation or the like, the data of the measurement point data group of the obstacle candidate is used as it is. A representative point is determined and an estimation calculation related to the representative point position (grouping coordinates), which is the point coordinate, is performed.
Therefore, it is a third technical issue to realize a level crossing obstacle detection device of a plane sweep radar type that performs a grouping process suitable for such a tracking process.

Further, it is further mentioned that tracking of a plurality of objects is useful for a level crossing obstacle detection device of a plane sweep radar type.
The railroad crossing obstacle detection device is based on the premise that if "one or more" objects continue to exist on the railroad crossing for a specified time, it should be determined that there is an obstacle, and the representative point position (grouping coordinates). ) Is present in the obstacle detection area of the railroad crossing, it is judged that there is an object first, and then if the object is present in the obstacle detection area for a specified time, it is judged that there is an obstacle. Logic is conceivable, but this is not practical for the following three reasons.

The first reason is that when multiple objects exist in the monitoring area (obstacle detection area), the time is measured if there is one or more, so if there are many passing objects, the obstacle is detected immediately. It ends up. As a countermeasure, a method of setting a plurality of monitoring areas (obstacle detection areas) in a strip shape and assuming that there is an obstacle if one or more grouping coordinates (representative points) exist for a specified time is also conceivable. However, dissatisfaction remains, such as the time and effort required to set a large number of strip-shaped areas, the spatial resolution tends to be coarse, and the detection process near the strip boundary may cause non-detection.

The second reason is that even if disturbing objects such as snowfall are eliminated as much as possible by grouping processing, it is inevitable that a situation will occur in which they cannot be completely eliminated. Therefore, the final judgment is made by processing up to grouping without tracking. This is because false positives cannot be sufficiently suppressed if the above is given.
The third reason is that when the speed of an object is high, the object quickly jumps out of the monitoring area (obstacle detection area), so the over-detection prevention function of excluding the high-speed object from the target of obstacle detection. Is useful, but when realizing the function to prevent over-detection, the measurement point data group (distance measurement point group) and representative point position (grouping coordinates) of the object to be tracked and the obstacle candidate are limited to a single one. Then, it becomes difficult to realize. For example, even with the strip-shaped area setting described above, over-detection prevention can be achieved to some extent, but for an object traveling in the same direction as the long side of the strip, the object will continue to exist in the same strip for a long time. It becomes over-detection.

Furthermore, if the grouping process is performed appropriately and it is found that "one or more" objects exist, tracking can be performed, and if there is one representative point position (grouping coordinates), the minimum judgment can be made. It also mentions the reason why it is desirable that even if there are a plurality of measurement point data groups (distance measurement point groups) and representative point positions (grouping coordinates) of obstacle candidates, which are the objects to be tracked, they can be processed appropriately.

The first reason is that the object to be tracked and thus the measurement point data group of the obstacle candidate is limited to one, and the elapsed time from the start of the extinction certification to the completion of the extinction certification when the measurement point data group of the obstacle candidate disappears. Assuming that the disappearance of the tracking target is confirmed using a predetermined extinction element, when another object invades immediately after one object exits the crossroads, the disappearance of the tracking target is confirmed. Therefore, tracking of another object is performed after waiting for the passage of the element at the time of extinction, which is inconvenient because the obstacle determination is delayed.

The second reason is that the number of representative point positions (grouping coordinates) of one object is ideally one point, but due to factors such as surface shape and reflectance, a single object is divided into multiple objects for grouping. This is because even if there is only one object on the crossroads, there may be a plurality of obstacle candidate measurement point data groups (distance measurement point groups), and thus a plurality of objects to be tracked.
The third reason is that even if an undesired measurement point (distance measuring point) due to a disturbance factor such as a measurement point (distance measuring point) due to snowfall or interference from an oncoming radar cannot be eliminated by the grouping process, it is subject to tracking. This is because there may be multiple objects.

For this reason, in order to perform highly reliable detection, a plurality of tracking numbers (the number of measurement point data groups and representative point positions of the object to be tracked and thus the obstacle candidate) are prepared and appropriately processed. However, since tracking resources are limited, it is also necessary to prevent / avoid unnecessary tracking.
Therefore, a fourth technical issue is to realize a level crossing obstacle detection device of a plane sweep radar type that can perform effective tracking using a finite number of tracking resources.

Further, in addition to the grouping process in the image related to the obstacle candidate as described above, the tracking process over time between a plurality of images related to the obstacle candidate described above is also executed by the software. It requires a lot of processing power in the hardware.
However, as described above, a fail-safe computer may be adopted as the hardware of the railroad crossing obstacle detection device, and since ensuring high reliability is prioritized for the fail-safe computer, many consumer devices, etc. Compared to the general computer used in, it is powerless because it sacrifices cost performance.
Therefore, it is a fifth technical issue to realize a railroad crossing obstacle detection device of a plane sweep radar type that requires a light load of software processing.

The crossing obstacle detection device of the present invention (Solution 1) was devised to contribute to the solution of the above-mentioned first technical problem, and the airborne propagating wave is swept in a plane to acquire the measurement data of the reflection position. In a crossing obstacle detection device including a plane sweep measurement unit and a computer equipped with a determination means for determining the presence or absence of an obstacle based on the measurement data, the determination means determines an obstacle based on the measurement data. It is characterized in that a grouping process for specifying a candidate measurement point data group is performed, and the presence or absence of an obstacle is determined according to the presence or absence of the measurement point data group.

Further, the crossing obstacle detection device of the present invention (Solution 2) was devised to solve the above-mentioned first technical problem, and the airborne propagating wave is swept in a plane to acquire the measurement data of the reflection position. In a crossing obstacle detection device including a plane sweep measurement unit and a computer equipped with a determination means for determining the presence or absence of an obstacle based on the measurement data, the determination means determines an obstacle based on the measurement data. Grouping processing that can identify multiple candidate measurement point data groups, and tracking the position of the representative point when there is one measurement point data group, and individually the position of those representative points when there are multiple measurement point data groups. It is characterized in that a tracking process for tracking is performed, and the presence or absence of an obstacle is determined according to the presence or absence of a tracking target in the tracking process.

Further, the crossing obstacle detection device of the present invention (Solution 3) was devised to solve the above-mentioned second technical problem, and the airborne propagating wave is swept in a plane to acquire the measurement data of the reflection position. In a crossing obstacle detection device including a plane sweep measurement unit and a computer equipped with a determination means for determining the presence or absence of an obstacle based on the measurement data, the determination means determines an obstacle based on the measurement data. A grouping process for specifying a candidate measurement point data group is performed, and in the grouping process, the traced measurement point and the destination measurement point are traced while tracing a series of measurement point data included in the measurement data. The group area count value is increased or decreased according to the magnitude of the distance, and when the group area count value reaches the grouping confirmation specified value, the measurement point data group being traced is determined as related to the obstacle candidate, and the group area is determined. When the count value reaches the grouping completion specified value, the identification of the measurement point data group being traced is completed.

Further, the railroad crossing obstacle detection device of the present invention (solution 4) is the railroad crossing obstacle detection device of the solution 3, and the absolute value of the increase unit of the group area count value is a decrease of the group area count value. It is characterized by being larger than the absolute value of the unit.

Further, the railroad crossing obstacle detecting device of the present invention (solving means 5) is a railroad crossing obstacle detecting device of the solving means 3 and 4, and the determining means increases or decreases the group area count value when the grouping process is performed. Is performed only between the grouping completion designated value and the grouping finalized designated value.

Further, the railroad crossing obstacle detection device of the present invention (solution 6) was devised to solve the above-mentioned third technical problem, and is the railroad crossing obstacle detection device of the above-mentioned solutions 3 to 5. The determination means is characterized in that, for the measurement point data group identified as an obstacle candidate in the grouping process, a representative point is determined one by one (at the time of the grouping process or at the time of the subsequent tracking process). And.

Further, the railroad crossing obstacle detection device of the present invention (solving means 7) is a railroad crossing obstacle detecting device of the solving means 3 to 6, and the determination means keeps the measured data in polar coordinates when performing the grouping process. The feature is that it is designed to be handled.

Further, the railroad crossing obstacle detecting device of the present invention (solving means 8) is a railroad crossing obstacle detecting device of the solving means 3 to 7, and the determining means is included in the measurement data at the time of the grouping process. It is characterized in that it follows in one direction when tracing a series of measurement point data.

Further, the railroad crossing obstacle detection device of the present invention (solving means 9) is the railroad crossing obstacle detecting device of the solving means 7 and 8, and the difference between the grouping confirmation designated value and the grouping completion designated value is the said. It is characterized in that the magnitude changes depending on the perspective of the position of the measurement point data group during the tracing of.

Further, the crossing obstacle detecting device of the present invention (solving means 10) is the crossing obstacle detecting device of the solving means 3 to 9, and the value is effective for the portion of the determining means for which the grouping process is performed. The unreached state when the measurement point data has not been reached yet, the pre-determination reflex state when the value is reached to the valid measurement point data before the obstacle candidate is confirmed, and before the obstacle candidate is confirmed. There is no reflex before confirmation when the measurement point data with invalid value is reached, the state with reflex after confirmation when the measurement point data with valid value is reached after the obstacle candidate is confirmed, and the obstacle candidate. It is characterized by incorporating a state machine having no reflection after confirmation when it reaches invalid measurement point data of the value after confirmation.

Further, the railroad crossing obstacle detection device of the present invention (solving means 11) is a railroad crossing obstacle detecting device of the solving means 3 to 10, and the measuring point being traced when the determining means performs the grouping process. It is characterized in that it is possible to switch between an increase unit and a decrease unit of the group area count value before and after the data group is determined as relating to the obstacle candidate.

In such a railroad crossing obstacle detection device of the present invention (solutions 1 and 2), at the time of grouping, not only one measurement point data group of obstacle candidates but also a plurality of measurement point data groups can be specified. In the subsequent tracking, the position of each representative point is individually tracked not only when there is only one measurement point data group but also when there are multiple measurement point data groups, so that an object that can be a candidate for an obstacle becomes a railroad crossing. Even if it takes a long time from entering to advancing, it is possible to track obstacle candidates over a plurality of images.
Therefore, according to the present invention, it is possible to realize a level crossing obstacle detection device of a plane sweep radar type that can track an obstacle candidate until it advances to the railroad crossing road, and as a result, the first technical problem is solved. NS. Further, in the invention (solving means 2) in which the representative point of the measurement point data group is used as the tracking target of the tracking process, the above-mentioned third technical problem is also solved.

Further, in the crossing obstacle detection device of the present invention (Solution 3), the grouping process for specifying the measurement point data group of the obstacle candidate included in the measurement data consisting of a series of measurement point data is embodied. At that time, after adopting a method of measuring the magnitude of the continuity of obstacle candidates with the group area count value while tracing the sequence of measurement point data as the heading method prior to identification, the traced measurement points that have already been traced and the future Find the distance from the measurement point of the destination you are trying to follow, and count the group area according to the magnitude of the distance (for example, whether it is larger or smaller than a predetermined fixed value), that is, according to the proximity state of both measurement points. By increasing or decreasing the value, the group area count value steadily increases (or decreases) for the measurement point data group with large continuity, while the group area count is performed for the measurement point data group with low continuity. On the contrary, the value decreases (or increases).

Therefore, when the group area count value reaches the grouping confirmation specified value, the measuring point data group being traced is determined as related to the obstacle candidate, and when the group area count value reaches the grouping completion specified value, the measuring point being traced is determined. By completing the identification of the data group, it is possible to accurately eliminate undesired effects such as snow and rain with low continuity, and measure desired objects such as vehicles and passersby with high continuity as obstacle candidates. The point data group can be specified.
Therefore, according to the present invention (Solution 3), it is possible to realize a level crossing obstacle detection device of a plane sweep radar type that can accurately perform grouping processing without being disturbed even if there is a disturbance such as snow or rain. As a result, the second technical problem is solved.

Moreover, if such an accurate grouping process is performed, the number of measurement point data groups of obstacle candidates, and thus the unreasonable increase in the number of tracking numbers, can be suppressed or avoided. Therefore, according to the present invention (Solution 3), a fourth technical problem of realizing a level crossing obstacle detection device of a plane sweep radar type capable of performing effective tracking using a finite number of tracking resources is solved. Also useful.
In addition, in the plane sweep radar method, since a series of distance data can be obtained by sweeping the measurement data once, it is possible to easily trace the sequence of measurement point data by changing the direction value or the direction data. The load of data processing and counting calculation is relatively light. Therefore, according to the present invention (Solution 3), it also contributes to solving the fifth technical problem of realizing a level crossing obstacle detection device of a plane sweep radar type in which the load of software processing is light.

Further, in the crossing obstacle detection device of the present invention (Solution 4), the absolute value of the increasing unit of the group area count value is made larger than the absolute value of the decreasing unit of the group area count value, so that the measurement point is obtained. Since continuity is evaluated higher than discontinuity in terms of data, objects with high continuity such as vehicles and passersby that should not be overlooked are identified with high accuracy as obstacle candidates. It will contribute to high-level solutions to the second and fourth technical issues.

Further, in the railroad crossing obstacle detection device of the present invention (Solution 5), the range of increase / decrease of the group area count value is limited between the grouping completion specified value and the grouping confirmed specified value, so that it is easy and accurate. , Overestimation of continuity and discontinuity can be avoided.

Further, in the crossing obstacle detection device of the present invention (Solution 6), one representative grouping coordinate is selected for the measurement point data group specified as the obstacle candidate, and further specified as the obstacle candidate. When there are multiple measurement point data groups, one representative grouping coordinate is selected for each measurement point data group, and the coordinates of the measurement point data group after grouping are narrowed down to one point. , It becomes easy to track the subsequent processing. Therefore, according to the present invention, it is possible to realize a level crossing obstacle detection device of a plane sweep radar type that performs grouping processing suitable for tracking processing that performs position estimation and position prediction using a Kalman filter or the like. The third technical problem is also solved.

Further, in the crossing obstacle detection device of the present invention (Solution 7), the measurement data is handled in polar coordinates in the grouping process, so that the measurement data includes a large number of measurement point data. Since the calculation of coordinate conversion is omitted, the load of software processing is greatly reduced. On the other hand, since the grouping process is performed using a series of distance data as described above, since the directional pitch is fine, there is no inconvenience even if a simple calculation ignoring the directional component is adopted when calculating the separation distance. It can be said that. Therefore, handling the measurement data in polar coordinates does not significantly increase the burden of software processing.
Therefore, according to the present invention, it is possible to realize a level crossing obstacle detection device of a plane sweep radar type in which the load of software processing is light, and the fifth technical problem is also solved.

Further, in the crossing obstacle detection device of the present invention (Solution 8), when tracing the sequence of measurement point data included in the measurement data, it is traced in one direction, so that the traced location is reached. Since there is no return, the maximum number of processing targets, and thus the number of times the processing is repeated, does not exceed the number of measurement point data included in the measurement data, so that a state in which the load of data processing, counting calculation, etc. is light is always maintained.
Therefore, according to the present invention, it is possible to realize a level crossing obstacle detection device of a plane sweep radar type in which the load of software processing is light, and the fifth technical problem is also solved.

Further, in the crossing obstacle detection device of the present invention (solution 9), when the position of the measurement point data group being traced is far, that is, when the distance from the plane sweep measurement unit to the reflection position is long, the grouping is confirmed. The difference between the specified value and the grouping completion specified value becomes small, and when the positions of the measurement point data groups being traced are close, that is, when the distance from the plane sweep measurement unit to the reflection position is short, the above difference becomes large. As a result, the relationship between the above difference and the position of the measuring point data group being traced is inversely proportional, in other words, the product of the above difference at the time of grouping confirmation and the position of the measuring point data group being traced does not change much. Since the relationship holds, the length of the object part corresponding to the measurement point data group when it is determined to be related to the obstacle candidate is stable, so the minimum length of the object detected as an obstacle (minimum object detection length). ) Is almost constant.

When the measurement data is handled in polar coordinates during the grouping process, the distance measurement points (distance measurement points) become dense in the vicinity but coarse in the distance. If the difference between the above and is fixed, even if the nearby object is too small, it will be an obstacle candidate, and even if the distant object is large, it will leak from the obstacle candidate. By making it variable, the harmful effects can be easily eliminated.
In the normal embodiment, the grouping completion designated value is set to "0", so that the above difference is simply the grouping final designated value.
Therefore, according to the present invention (Solution 9), it is possible to easily realize a level crossing obstacle detection device of a plane sweep radar type that requires a light load of software processing, and as a result, a fifth technical problem is solved. It is solved in a practical manner.

Further, in the crossing obstacle detection device of the present invention (solution 10), a number of sets are set based on the division of obstacle candidates, before and after the determination of obstacle candidates, and the validity / invalidity of measurement point data. By adopting a state machine that includes the transition state and incorporating it into the part that searches for obstacle candidates while tracing the sequence of measurement point data included in the measurement data in the grouping process, grouping is performed. Since the program structure and the like when the processing is embodied by software are simplified and clarified, the burden of mounting on a computer is reduced.

Further, in the railroad crossing obstacle detection device of the present invention (solution 11), it is possible to switch between the increase unit and the decrease unit of the group area count value before and after the determination of the obstacle candidate during the grouping process. As described above, it is desirable to identify objects with high continuity with high accuracy before confirmation, so both units are set as such, but after confirmation, the objects are accurately classified. Since it becomes easy to adopt a fine-grained grouping process such as switching between the two units, it is possible to improve the accuracy of the grouping process.
Therefore, it is possible to realize a plane sweep radar type railroad crossing obstacle detection device that can perform grouping processing more accurately without being disturbed even if there is a disturbance such as snow or rain, and as a result, the second technical problem is solved at a high level. Will be done.

Regarding Example 1 of the present invention, the structure of the railroad crossing obstacle detection device is shown, (a) is a schematic plan view of the railroad crossing at the installation destination, (b) is a schematic block diagram of the hardware of the railroad crossing obstacle detection device, ( c) is an outline block diagram of the software of the railroad crossing obstacle detection device. (A) is a schematic view of sweeping the airborne wave in a plane, (b) is an image diagram of the measurement data before the limitation, and (c) is an image diagram of the measurement data after the limitation. (A) is an image diagram of data for a grouping program, and (b) is a schematic diagram of a state machine incorporated in the grouping program. It is a partially enlarged schematic view of a plane sweeping of airborne waves during rainfall and snowfall. (A) is an image diagram of the measurement data before the limitation, (b) is an image diagram of the measurement data after the limitation, and (c) is an image image diagram of the measurement point data group. (A) is an image diagram of tracking information, (b) is an image diagram of measurement point data group, (c) is an image diagram of tracking information, (d) is an image diagram of measurement point data group, and (e) is an image diagram of tracking information. Is.

The first embodiment suitable for carrying out such a railroad crossing obstacle detection device of the present invention is the railroad crossing obstacle detection device of the above-mentioned solution means, and the determination means determines the railroad crossing obstacle detection area. A data limiting process that holds the specified detection area specified data and narrows down the measurement data to the data related to the position belonging to the obstacle detection area based on the detection area specified data for the grouping process. It is characterized by being designed to do.

In this case, a series of measurement data relating to a railroad crossing passerby or the like can be obtained each time the plane of the airborne wave is swept, but the determination means does not perform the grouping process or the like using the measurement data as it is, but the grouping process or the like. Prior to this, the raw measurement data (before limitation) is narrowed down to the obstacle detection area, and then the measurement data (after limitation) is used for grouping processing and the like. Then, by narrowing down the data, the distribution range of the measurement point data group of the obstacle candidate is reduced, the amount of data processing is reduced / reduced, and the number of tracking is also reduced or at least the increase is prevented, while the obstacle. Since the data related to the position belonging to the object detection area is used for subsequent processing such as grouping without being removed, the increase in the number of tracking is suppressed without sacrificing the tracking performance.

Moreover, it also exerts the further effects described below. That is, since the image data to be processed is narrowed down to those related to the obstacle detection area prior to the grouping process or the like, when the obstacle enters or advances into the obstacle detection area, it is in the middle of the process. Since the measurement point data group of the obstacle candidate is limited to the part belonging to the obstacle detection area instead of the entire obstacle, the measurement point data group is expanded or contracted while sticking to the boundary line of the obstacle detection area. Looking at the moving speed of each part of the image, the part farthest from the boundary line moves at the speed of the obstacle or a speed close to it, while the part along the boundary line almost keeps stopping, so it is an obstacle candidate. Internal points such as the center point in the measurement point data group of the above move at a slower speed than the obstacle.

On the other hand, position estimation and position prediction using a Kalman filter or the like calculate the next position from the previous position and velocity, and are generally vulnerable to discontinuous jumping velocity changes. The slower the speed change, the more accurately it can be tracked. Therefore, by adopting the inner point of the measurement point data group as the representative point of the measurement point data group of the obstacle candidate to be tracked by the tracking process using the representative point, it is easy to calculate the center position and the center of gravity of the inner points. By adopting the center point obtained by position calculation or the like, it is possible to easily and accurately enhance the tracking ability in the tracking process.

Further, the railroad crossing obstacle detection device of the second embodiment is the railroad crossing obstacle detection device of the first embodiment, and the measurement point data group specified by the determination means as an obstacle candidate in the grouping process. Is performed for a period of time when the tracking disappears, and in the tracking process, the tracking disappearing element is increased or decreased depending on whether the speed related to the measurement point data group is slow or fast. It is characterized by that.
In this case, when tracking the measurement point data group by the tracking process, when the speed of the measurement point data group is slow, the time of the tracking disappearance becomes long, and when the speed of the measurement point data group is high, the tracking disappears. By shortening the raw time, for example, for elderly people who move slowly and take time to cross the crossing, it is closely tracked to ensure safety, while for example, automobiles. For items that move quickly and do not have the risk of staying inside the railroad crossing, tracking can be quickly rounded up to reduce the burden of data processing.

Further, the railroad crossing obstacle detection device of the third embodiment is the railroad crossing obstacle detection device of the first and second embodiments, and when the speed related to the measurement point data group in the tracking process is faster than the predetermined speed, the above. It is characterized in that the element at the time of tracking disappearance is set to zero time or ignored.
Further, the railroad crossing obstacle detection device of the fourth embodiment is the railroad crossing obstacle detection device of the third embodiment, and the predetermined speed is set to a value corresponding to the average walking speed of a healthy person. It is a feature.
In such a railroad crossing obstacle detection device of the third and fourth embodiments, for safety, for slow railroad crossing passages such as elderly people, tracking is extended based on the time when tracking disappears, but the speed of automobiles and the like is high. For railroad crossing passages, the safety of railroad crossing passage and the reduction of data processing burden can be achieved at a high level by omitting the tracking extension based on the tracking disappearance.
Moreover, it is simplified by setting the tracking extinction element to zero time or ignoring the tracking extinction element.

Regarding the railroad crossing obstacle detection device of the present invention and the railroad crossing obstacle detection device of the embodiment, specific embodiments for carrying out the same will be described with reference to the following Examples 1 to 4.
The first embodiment shown in FIGS. 1 to 6 embodies the above-mentioned solutions 1 to 10 (claims 1 to 10 at the time of filing) and the first embodiment. , The above-mentioned solution 11 (claim 11 at the time of filing) is embodied, and Examples 3 and 4, which are also omitted from the illustration, embody the above-described embodiments 2 to 4.
For the sake of simplicity, these illustrations include housings, frames, fasteners such as bolts, drive sources such as electric motors, transmission members such as gears, electric circuits such as motor drivers, and electronic devices such as controllers. Circuits and the like are omitted from the illustrations, and block diagrams and the like are shown focusing on those necessary for explaining the invention and related ones.

The specific configuration of the first embodiment of the railroad crossing obstacle detection device of the present invention will be described with reference to the drawings.
1A is a schematic plan view showing the installation status of the railroad crossing obstacle detection device 10 on the railroad crossing road 4, and FIG. 1B is a schematic block diagram showing the hardware configuration of the railroad crossing obstacle detection device 10; ) Is a schematic block diagram showing a software configuration of the railroad crossing obstacle detection device 10.

Further, FIG. 2 is a schematic plan view in which the airborne wave is swept in a plane, (b) is an image diagram of the measurement data before the limitation, and (c) is an image diagram of the measurement data after the limitation. be.
Further, FIGS. 3A and 3B are an image diagram of the main data used for the grouping process of the grouping program 23, and FIG. 3B is a schematic diagram of the grouping process state machine incorporated in the grouping program 23.
Further, FIG. 4 is a partially enlarged view of a schematic plan view in which airborne waves are swept in a plane when it is snowing or raining.

Further, FIG. 5 is an image diagram showing measurement data in (a) after being acquired by the data input program 21 while sweeping the airborne wave in a plane and before performing the limitation processing of the data limitation program 22. (B) is an image diagram of the measurement data after the limited processing of the data limiting program 22 is performed.
Further, FIGS. 5 (c), 6 (b), and 6 (d) are image images of the measurement point data group, and FIGS. 6 (a), 6 (c), and 6 (e) are. It is an image diagram of the tracking information.

The railroad crossing obstacle detection device 10 (see FIGS. 1 (a) and 1 (b), Patent Documents 4 and 5) first describes a hardware configuration. A plane sweep radar type plane sweep measurement unit that receives reflected waves and measures the distance and direction while sweeping and transmitting airborne waves such as infrared rays (see the two-point chain line) toward the obstacle detection area 7 It includes 11 to 13 and a fail-safe computer 14 in which a determination program 20 for determining the presence or absence of an obstacle in the obstacle detection area 7 is installed from the measurement data obtained by the measurement.

The plane sweep measurement units 11 to 13 set the transmission direction of the air-propagated wave transmission / reception unit 12 that transmits the air-propagated wave and the reflected wave toward the obstacle detection region 7 and the transmission direction of the air-propagated wave transmission / reception unit 12, for example, 130. For the transmission / reception signals of the rotation control unit 11 and the airborne wave transmission / reception unit 12 that control the rotational movement of the rotation mechanism that sweeps within an angle range such as ° or 190 ° and measure or enable the direction measurement of the transmission / reception of airborne waves. It is provided with a signal processing unit 13 that measures the distance from the transmission position to the reflection position based on the signal processing unit 13. In this example, in order to measure the entire area of the obstacle detection area 7 by dividing the area, or to measure the entire area of the obstacle detection area 7 in duplicate (see, for example, Patent Document 4), two sets (plurality). The plane sweep measuring units 11 to 13 are provided.

Since a known product is sufficient for the fail-safe computer 14 (see, for example, Patent Documents 3 and 4), it is adopted, and the data memory (see FIG. 1 (c)) is a preset constant. The detection area definition data and the tracking disappearance element, the measurement data (before and after limitation) which are variables and arrays changed with the execution of the determination program 20, the data of the measurement point data group, and the tracking information are retained. ing. Tracking information (tracking data, etc.) for tracking processing, which includes variables, etc., when tracking disappears, and grouping processing data, which also includes variables, etc. in addition to constants, are now retained in the data memory. There is.

The determination program 20 (see FIG. 1C), in short, determines the presence or absence of an obstacle based on measurement data, detection area definition data, grouping processing data, and tracking information such as when tracking disappears. For that purpose, a data input program 21, a data limiting program 22, a grouping program 23, a tracking program 24, and a final determination program 25 are provided, and these are repeatedly executed in that order, for example, at a predetermined cycle or each time a predetermined event occurs. It is designed to be executed.

Of the data (see FIG. 1 (c)), the detection area defining data defines the obstacle detection area 7 related to the crossing road 4, and is, for example, two positions over the entire circumference of the obstacle detection area 7. The dimensional coordinates or at least the two-dimensional coordinates of the positions of each corner are arranged in the order of orbit, and the coordinates may be orthogonal coordinates, but the polar coordinates are more compatible with the plane sweep radar method.
The grouping processing data (see FIG. 1 (c)) will be described in detail later (see FIG. 3 (a)), but the measurement data is traced in the same direction as or in the opposite direction to the plane sweep of the airborne wave. A counter that holds a group area count value for evaluating the continuity and discontinuity that appears in a series of data (distance measuring points), data that holds the increase / decrease value used for updating the counter, and tracing of the measurement data. It includes data that holds some pointers related to the above.

The pointer pair that identifies the measurement point data group that is related to the obstacle candidate based on the group area count value may be retained in the grouping processing data, but there is a possibility of a large number of pointer pairs. In order to avoid securing the data holding area in the grouping processing data, in this embodiment, the pointer pair that identifies the measurement point data group is immediately or temporarily without being held in the grouping processing data. Even when it is held, it is quickly handed over to the tracking process without continuing to hold it.

The tracking disappearance time element (see FIG. 1 (c)) is a predetermined time during which tracking information and the like are retained after the measurement point data group of the obstacle candidate to be tracked disappears, and a plurality of crossing passages are passed. It is decided in consideration of the time from the union to the separation of the measurement point data group due to the movement of the body. When tracking disappears, it is necessary to temporarily interrupt tracking, for example, when another object passes in front of the object being tracked or the aerial propagating wave reflected from the object being tracked weakens. This is so that tracking can be resumed promptly after the temporary factor disappears even in such a case. An appropriate time as the restart waiting time is predetermined as the tracking extinction time element, and the data is held in a state where it can be referred to during the tracking process. Then, even after the measurement point data group disappears, the tracking information is maintained without being deleted until the elapse of the element at the time of tracking disappearance.

In the data input program 21, the polar coordinate values of the reflection positions obtained by the plane sweep measurement units 11 to 13 each time the plane sweep measurement units 11 to 13 perform the measurement by the plane sweep (see FIGS. 1 (a), 2 (a), and 4). Is input from the plane sweep measurement units 11 to 13 to obtain the measurement data before limitation (see FIGS. 1 (c), 2 (b), and 5 (a)), but in this example, For the sake of simplification of the explanation, a series of data obtained from one of the two sets of plane sweep measuring units 11 to 13 (see FIGS. 1 (a) and 1 (b)) is used as the measurement data (see FIGS. 1 (a) and 1 (b)). It is assumed that it is adopted before the limitation) and only that is processed (see FIGS. 2 (b) and 5 (a)).

The measurement data before this limitation includes the three vehicles of the crossing passage (three vehicles of FIG. 2 (a)) in the obstacle detection area 7 (see the alternate long and short dash line of FIGS. 2 (a) and 5 (a)). , One vehicle in FIG. 4, see three vehicles in FIG. 5 (a)), but not only that, but also the part of them that protrudes from the obstacle detection area 7. Although not shown in the figure, even equipment outside the obstacle detection area 7 can include image data of its contour as long as it is within the plane sweep range (FIGS. 2 (b), 4 and 5 (FIG. 2 (b)). See the black dot in a)).

In this embodiment, for the sake of simplification of the explanation, since the plane sweep and the reflection measurement in the plane sweep measurement units 11 to 13 are always performed at the same angle and with the same angle difference, the direction waits for the measurement. Since it is a fixed value that can be understood without need, and only the distance is the fluctuation value obtained by the measurement, the measurement data (before limitation) is a series of the distance values measured for reflection in many directions of equal pitch. For example, it is held in the array area of one row and N columns (N is a positive integer). For example (see FIG. 2B), each item in the above array includes "148", "147", "146", "146", if the item corresponds to the direction reflected from the vehicle on the railroad crossing. Positive distance values such as "147" are retained, but non-positive distance values such as "0", "0", and "0" are retained for items that correspond to directions with no reflection, such as between vehicles. It has become so.

The data limiting program 22 executes the data limiting process and creates the measurement data after the limitation from the measurement data before the limitation based on the detection area definition data (see FIG. 1C). Of the points of the image data included in the measurement data before the limitation (see the black dots in FIGS. 2 (b) and 5 (a)), the obstacle detection area 7 (see the one-point chain line in the same figure). By excluding those located outside the limit, those that are narrowed down to the data related to the position belonging to the obstacle detection area 7 among the points of the measurement data before the limitation are adopted as the measurement data after the limitation. (See the black dots in FIGS. 2 (c) and 5 (b)).

In the case of an object straddling the boundary of the obstacle detection region 7, the measurement data (after limitation) includes only the image data of the portion inside the region, and the image data of the portion outside the region is deleted. Specifically (see FIG. 2C), the value "0" when there is no reflection is forcibly adopted even for the item related to the direction in which the distance can be measured due to the reflection. It has become.
In the above example, those that were "148", "147", "146", "146", "147", and "0" before the limitation (see FIG. 2B) are the obstacle detection areas 7. The two outer left ends "148" and "147" are forced to "0" and "0", and after the limitation, "0", "0", "146", "146", "147" and "0" (See Fig. 2 (c)).

In short, the grouping program 23 executes an in-image grouping process for creating a measurement point data group of obstacle candidates from measurement data (after limitation) (see FIG. 1C), and measurement data (after limitation). For each point of the image data (see the black points in FIGS. 2 (c), 4 and 5 (b)), the measurement point data groups that can be obstacle candidates are specified by grouping the short-distance ones one after another. (See the three solid lines in FIG. 5 (c) and the two solid lines in FIG. 6 (b)). If there is no railroad crossing passerby that can be an obstacle candidate, the measurement point data group disappears immediately (see FIG. 6 (d)).

Specifically (see FIG. 3A), the grouping processing data is a pointer that points to any data item of a series of measurement data (after limitation), and is a pointer to the measurement point data group of the obstacle candidate. A traced measurement point that points to the start point, a traced measurement point that points to the data item that has been traced from that start point, and a pointer that points to the next data item that is going to be traced from this traced measurement point. The measurement points of are secured in the data memory.
In the grouping process of the grouping program 23, the measurement data is handled as polar coordinates, and when tracing the sequence of measurement point data included in the measurement data, the measurement data is traced in one direction, for example, from left to right in the illustrated example. Therefore, one set of the measurement point to start tracing, the measurement point to be traced, and the measurement point to be traced to is sufficient.

In the illustrated example, the distance between the traced measurement point and the destination measurement point is about one measurement point data, because the distance between the traced measurement point and the destination measurement point is small. When the traced measurement point is advanced only when both points are close to each other, the measurement point next to the traced measurement point is far apart, so only the traced measurement point is advanced by one more point. Because it shows.
Further, in the case of this example, the pointer pair pointing to the beginning and the end of the continuous portion specified as the measurement point data group is quickly handed over to the tracking process as described above, so that it does not appear in the grouping process data. Although not, two dashed lines are shown to make it easier to imagine the already identified measurement point data group.

Further (see FIG. 3A), in addition to those data areas, a counter that holds a group area count value that counts the degree of continuity of the measurement point data and a group area count value thereof are further used as grouping processing data. A grouping fixed specified value that specifies the data area that holds the increase unit used when increasing, the data area that holds the decrease unit used when decreasing the group area count value, and the limit value when the group area count value increases. The data area that holds the grouping completion specified value that specifies the limit value when the group area count value decreases is also secured in the data memory.

Then, in the grouping process of the grouping program 23, when the group area count value exceeds the grouping confirmation specified value when the increase unit is added to the group area count value, the group area count value is limited to the grouping confirmation specified value. , When the grouping area count value exceeds the grouping completion specified value when the reduction unit is subtracted from the grouping area count value, the grouping area count value is limited to the grouping completion specified value, and the increase or decrease of the grouping area count value is specified as grouping completion. It is designed to be performed only between the value and the specified grouping confirmation value.
In this example, the grouping completion designation value is fixed to zero "0" for simplification and simplification, and the absolute unit of increase of the group area count value is given priority from the viewpoint of prioritizing the detection of railroad crossing passages with high continuity. The set value of the increase unit is set to "2" and the set value of the decrease unit is set to "1" so that the value becomes larger than the absolute value of the decrease unit of the group area count value.

Therefore, when the group area count value exceeds the grouping confirmation specified value, it corresponds to the group area count value exceeding the grouping confirmation specified value, and when the group area count value exceeds the grouping completion specified value, it corresponds to the group area count value. Corresponds to being less than the grouping completion specified value. On the other hand, when the set value of the increase unit is set to "-2" and the set value of the decrease unit is set to "-1", if the group area count value exceeds the grouping confirmation specified value, the group area count value is grouped. It corresponds to falling below the definite designated value, and when the group area count value exceeds the grouping completion specified value, it corresponds to the group area count value exceeding the grouping completion designated value.

As described above, when the group area count value exceeds the grouping confirmed specified value or the grouping completed specified value, it is reset to the corresponding specified value. Therefore, in the explanation of this example, the grouping confirmed specified value or the grouping completed is set for easy understanding. We often use the expression that the specified value is reached.
Further, as described above, not only a positive value but also a negative value can be set for the increase unit and the decrease unit, so the meaning of the increase or decrease is not a mere increase or decrease of a numerical value but a continuity evaluation. The value is increased or decreased. Similarly, addition or subtraction related to an increase unit or a decrease unit also means an operation related to addition or decrease of a continuity evaluation value, not a simple addition or subtraction operation of a numerical value.

Further (see FIG. 3A), a table for changing the grouping specified value is also held in the data memory. This table holds a series of approximate values G that have been calculated in advance so that the approximate value G of the calculated value of the formula [L / D] can be easily obtained by using D as an index or a key. doing. Here, D is a distance value held in the measurement point data pointed to by the traced measurement point, and is a value of the most recently traced measurement point data in the measurement data. Further, L is the minimum object detection length which is the minimum object length to be detected by the railroad crossing obstacle detection device as an obstacle candidate, and is equivalent to, for example, about 200 mm when trying to detect even a small passerby. It becomes a fixed value.

Then, in the grouping process of the grouping program 23, after fixing the grouping completion specified value to zero “0” as described above, the grouping final specified value is referred to the above-mentioned table for changing the grouping specified value. By substituting the obtained approximate value G and appropriately changing the grouping confirmation specified value, the difference between the grouping confirmation specified value and the grouping completion specified value (that is, in this example where the grouping completion specified value is zero, the grouping is confirmed). The magnitude of the specified value G as it is (as it is) changes contrary to the magnitude (that is, approximately inversely proportional) of the perspective (that is, the distance value D) of the position of the measurement point data group being traced.

In this way, in the grouping process of the grouping program 23, the measurement data after limitation is handled as the polar coordinates, and the sequence of measurement point data included in the measurement data is traced in one direction. Is embodied by advancing the destination pointed to by the measurement point of the destination one by one, whereby the data items belonging to the measurement data (after limitation) are referred to one by one. Then, while tracing the measurement data in this way, the group area count value is increased or decreased according to the size of the distance between the traced measurement point and the destination measurement point, and the group area count value reaches the grouping confirmation specified value. Then, the measurement point data group being traced is determined as related to the obstacle candidate, and when the group area count value reaches the grouping completion specified value, the identification of the measurement point data group being traced is completed, but the processing is grouping processing. It is embodied in a state machine.

The state machine that forms the core of this grouping program 23 (see FIG. 3B) shows the unreached state when the valid measurement point data of the value has not been reached yet and the value before the obstacle candidate is determined. Pre-confirmation reflex state when reaching valid measurement point data, pre-confirmation no reflex state when reaching invalid measurement point data before confirmation of obstacle candidates, and confirmation of obstacle candidates There are five states: a post-confirmation reflex state when the value is valid at the measurement point data, and a post-confirmation non-reflex state when the value invalid measurement point data is reached after the obstacle candidate is confirmed. It is equipped and is designed to start from the unachieved state.

In this grouping processing state machine (see FIG. 3B), “with reflection” and “without reflection” indicate whether the value of the measurement point data pointed to by the measurement point to be traced is valid or invalid, that is, in the obstacle detection area 7. It is an abbreviation of whether or not it belongs to the distance value. In this example, as described above, when the reflected wave cannot be received in the measurement by the plane sweep measuring units 11 to 13, or even if the reflected wave can be received, it is an obstacle. When the reflection is from the outside of the detection area 7, the value of the measurement point data is set to "0" by the data limitation program 22, so that the value of the measurement point data pointed to by the destination measurement point is "0". If so, it becomes "no reflection". Next, even if the value of the measurement point data pointed to by the traced measurement point is other than "0", it is investigated whether or not the difference between that value and the value of the measurement point data pointed to by the traced measurement point is in a close state. If they are not close to each other, that is, if the distance between the two measurement points is large, then there is no reflection. The value of the point data is finally considered valid and becomes "with reflection".

In addition, it is necessary to distinguish whether or not the traced measurement point and the traced measurement point are close to each other, that is, to determine the size of the distance between the two measurement points in order to avoid a complicated calculation with a heavy load under the polar coordinates. The distance between the measurement points is approximated by the difference between the distance values of both measurement points, and the difference is determined by whether or not the difference exceeds a preset predetermined value. As the predetermined value, the above-mentioned minimum object detection length or a fixed value obtained by multiplying it by an appropriate constant is easy to use.
Further, in the figure (see FIG. 3B), the "confirmed designated value" is an abbreviation that the group area count value has reached the grouping confirmed specified value, and the "completion specified value" is the group area count value. Is an abbreviation that the grouping completion specified value has been reached, and the "intermediate value" is an abbreviation that the group area count value is a value between the grouping confirmation specified value and the grouping completion specified value. It should be noted that the illustration of the state transition related to the detailed case classification is omitted.

The unreached state is a state in which the obstacle candidate has not been reached at all since the measurement data is started, or a state after the obstacle candidate that has already been encountered has been traced, and the grouping processing state machine changes the state from this state. Is supposed to start. Further, in this unreached state, the grouping completion designated value "0" is set as the initial value in the group area count value. Then, when there is reflection in this unreached state, that is, when the measurement point data with a valid value is reached, the measurement point data pointed to by the measurement point to be traced at that time has been traced in order to start the search for obstacle candidates. It is omitted because it is usually unnecessary to check the group area count value after updating the traced measurement point and the traced start measurement point so that the measurement point and the start measurement point are also pointed to, and adding the increase unit to the group area count value. Therefore, the state transitions to the pre-determined reflex state.

The pre-confirmation reflex state and the pre-confirmation non-reflex state are for determining whether or not the effective measurement point data or measurement point data group reached can be determined as an obstacle candidate having a minimum object detection length L or more. If there is no reflection, that is, when the measurement point data with an invalid value is reached, the reduction unit is subtracted from the group area count value, and the state transitions to the pre-determination no reflection state, while if there is reflection, then The traced measurement point is updated so that the traced measurement point also points to the traced measurement point data pointed to by the traced measurement point, and the increment unit is added to the group area count value to enter the pre-determined reflection state. It is designed to transition.

However, such mutual transition is also performed only while the group area count value is in the median value, and when the group area count value reaches the grouping completion specified value, the search for obstacle candidates is performed. In order to start over from the beginning, the state transitions to the unachieved state.
On the other hand, when the group area count value reaches the grouping confirmation specified value, the measurement point data group being traced at that time is confirmed as an obstacle candidate, and then confirmed so as to finish the search for the obstacle candidate. The state transitions to the post-reflex state. Moreover, at that time, as a specific process of determination, a pointer pair for specifying the measurement point data group is added to the grouping processing data, and the value of the pointer pair starts to be traced, and the pointer value of the measurement point and the traced measurement point are traced. The pointer pair is also updated so that the pointer value of is paired.

The post-confirmation reflection state and the post-confirmation non-reflection state are states for confirming the end of the measurement point data group confirmed as an obstacle candidate having the minimum object detection length L or more, and if there is reflection, at that time. The traced measurement point is updated so that the traced measurement point also points to the traced measurement point data pointed to by the traced measurement point, and the grouping confirmation value is added to the grouping count value with the specified value as the limit to confirm. While the state transitions to the state with post-reflection, if there is no reflection, the reduction unit is subtracted from the group area count value, and the state transitions to the state without reflection after confirmation.
However, such a mutual transition is performed only while the group area count value is the intermediate value or the grouping confirmation specified value, and when the group area count value reaches the grouping completion specified value, the end of the confirmed obstacle candidate. Is confirmed, the state transitions to the unreachable state in order to search for new obstacle candidates.

The tracking program 24 executes a tracking process of tracking the measurement point data group obtained by the in-image grouping process over a plurality of images over time (see FIG. 1C), and the measurement point data group. If there are a plurality of measurement point data groups, the same number of tracking information is generated and held and assigned to each measurement point data group, so that each measurement point data group is individually tracked. Moreover, one representative point is determined for each measurement point data group related to the obstacle candidate (see the black dots in FIGS. 6 (a) and 6 (c)). It is desirable to determine the representative point by calculating the average value of all the coordinate values of the valid measurement point data belonging to the measurement point data group, but since the calculation load of the computer is heavy, the first one belonging to the measurement point data group. It is performed by calculating intermediate values for two points, the measurement point data and the last measurement point data.

Further, the tracking program 24 performs time-dependent tracking processing between a plurality of images related to obstacle candidates by estimating the next representative point position from the previous representative point position or the like by an estimation calculation of a known Kalman filter or the like. Specifically, for each tracking information, the next predicted position is calculated from the position and speed of the previous representative point by, for example, a linear Kalman filter, and the representative point is entered in a predetermined range from the predicted position. Group-specific information such as the position of the representative point of the measurement point data group is included in the corresponding tracking information.

Here, the above-mentioned predetermined range is determined by a predicted radius or the like in which a value is set in advance, but in the frequently used constant velocity linear motion model, the advantage that the traceable maximum speed also increases as the predicted radius increases. On the other hand, there is a disadvantage that the separation performance of the tracking target deteriorates when there are multiple tracking targets, and there is a possibility that even those that should not be tracked get inside the predicted radius and mistracking occurs. Since there is also the inconvenience of increasing the number of predicted radii, the set value of the predicted radius is determined in advance in consideration of the balance between them.

Further, when the tracking program 24 performs such a tracking process, the tracking program 24 refers to a preset tracking extinction time element (see FIG. 1 (c)), and tracks over the time of the time element. It has become. Specifically, when the measurement point data group to be tracked disappears by the grouping process, the tracking information related to the measurement point data group is not deleted immediately, but is kept until the tracking disappearance time elapses. There is. For example, even when the three measurement point data groups to be tracked move to the right (see FIGS. 5 (c) and 6 (a)) and the rightmost measurement point data group disappears (FIG. 6). (Refer to (b)), before the elapse of the tracking extinction element, the tracking information related to the representative point of the measurement point data group at the right end continues to exist (see FIG. 6C), and the deletion of the tracking information is the tracking extinction element. It is supposed to be done after the passage of.

The final determination program 25 determines the presence or absence of an obstacle in the obstacle detection area 7, and the determination process is performed according to the presence or absence of the tracking target of the tracking process (FIG. 1 (c)). reference). Specifically, if there is at least one tracking information created by the tracking program 24 (see FIGS. 6A and 6C, three in the figure), it is determined that an obstacle exists in the obstacle detection area 7. However, if there is no such tracking information (see FIG. 6E), it is determined that there is no obstacle in the obstacle detection area 7.

The usage mode and operation of the railroad crossing obstacle detection device 10 of the first embodiment will be described with reference to the drawings. 2 and 4 show a state in which the aerial propagating wave transmission / reception unit 12 sweeps the aerial propagating wave in a plane toward the obstacle detection area 7 above the crossing road 4, and FIG. 5A shows a state in which the aerial propagating wave is swept in a plane. It is an image diagram of the measurement data before the limitation, FIG. 5 (b) is an image diagram of the measurement data after the limitation, and FIGS. 5 (c) and 6 (a) are image diagrams of the initial measurement point data group and the tracking information. 6 (b) and 6 (c) are image diagrams of the subsequent measurement point data group and tracking information, and FIGS. 6 (d) and 6 (e) are image diagrams of the last measurement point data group and tracking information. Is.

When using the railroad crossing obstacle detection device 10, preferably (see FIG. 1A), an appropriate number (two in the figure) of aerial propagating wave transmission / reception units 12 and 12 are installed facing the railroad crossing road 4. , The area wider than the entire area of the obstacle detection area 7 is swept in a plane from a plurality of directions (two opposite directions in the figure), but here, for the sake of simplification of the explanation, only one aerial propagating wave transmission / reception unit 12 is used. (See FIG. 2) Then, in the railroad crossing obstacle detection device 10, the plane sweep measurement units 11 to 13 repeatedly perform the plane sweep (see the two-point chain line in FIG. 2), and each time the railroad crossing road 4 is passed. If there is (three vehicles in the figure), the reflected wave is detected, the reflected position is acquired by the polar coordinate value, and obstacle detection is performed as a one-dimensional array-like aggregate data consisting of a series of the polar coordinate values. Measurement data (before limitation) for a region wider than region 7 is completed (see FIG. 2 (b) and black dots for almost all of the three vehicles in FIG. 5 (a)).

Then, every time a set or a set of measurement data is obtained by such a plane sweep, the fail-safe computer 14 executes the determination program 20.
To outline the determination procedure, first, the measurement data before limitation is taken into the fail-safe computer 14 by executing the data input program 21 (see FIGS. 2B and 5A), and then the data limitation program 22 By the execution, the measurement data after the limitation is created from the measurement data before the limitation, and the image data to be processed after that is narrowed down to those belonging to the obstacle detection area 7 (FIGS. 2 (c) and 5 (b)). See the black dots on the rear end of the vehicle on the right, the right half of the vehicle in the center, and the front end of the vehicle on the left).

As described above, since the image data including the obstacle candidate is limited at the initial stage of the determination process, the load of the subsequent data processing is reduced.
Then, the grouping program 23 is executed, the grouping process is performed, and the data of the measurement point data group of the obstacle candidate is created from the measurement data after the limitation by the in-image tracking (in FIG. 5C). A vertically long L-shaped solid line related to the lower part of the rear end of the vehicle on the right side, a horizontally long L-shaped solid line related to the lower part of the central vehicle, and a-shaped solid line related to the lower part of the front end of the vehicle on the left side. See the solid line and the corresponding three measurement point data groups).

Here, the process of creating the measurement point data group of the obstacle candidate related to one object by the grouping process will be described in detail (see FIG. 4).
Rain or snow that disturbs the reflection is falling on the crossroads (see the white circle in Fig. 4), and a vehicle is crossing the crossroads (see the dotted line pattern on the upper side of Fig. 4). The measured data is obtained under the condition that the airborne wave is swept in a plane (see the two-dot chain line in Fig. 4) and the airborne wave that hits them is reflected not only by the vehicle but also by rain and snow (see the black dot in Fig. 4). Suppose it was acquired.

Then, since there was no reflection of the airborne waves in the sweeping of the airborne waves A1 to A2, the grouping processing state machine remained in the unreached state when tracing the corresponding part of the measurement data by the grouping processing, and the group area count value. Remains "0".
Then, since the airborne wave was reflected for the first time in the next sweep of the airborne wave A3, the pointer to the corresponding point / measurement point data in the measurement data starts to be traced and is set to the measurement point and the traced measurement point. , For example, “9” is obtained as the corresponding value G by referring to the grouping specified value change table from the distance value D at that time, and it is set as the grouping confirmed specified value. The grouping completion specified value remains "0" at all times. The group area count value becomes "2" by adding the increment unit. Then, the grouping processing state machine transitions to the pre-determined reflection state.

Then, the destination pointed to by the destination measurement point is advanced by one, and the next measurement point data is examined, but since there was no reflection of the aerial propagating wave A4 in the corresponding sweep, the measurement of the destination at that time was performed. Since the distance value D of the measurement point data pointed to by the point is "0", the traced measurement point is not updated, and the group area count value that was "2" is decremented by the decrease unit "1" to "1". , And the grouping processing state machine transitions to the pre-determination no reflection state.

Furthermore, the destination pointed to by the measurement point to be traced is advanced by one, the measurement point data there is examined, there is reflection of the airborne wave in the corresponding sweep, and the distance value D of the corresponding measurement point data. Since is not "0", the perspective between the traced measurement point and the traced measurement point can be further checked. Then, here, it is assumed that it is determined to be on the proximity side. Then, the traced measurement point is updated at the traced measurement point, that is, the pointer to the corresponding point / corresponding measurement point data in the measurement data is set to the traced measurement point. Further, the corresponding value G of the distance value D at that time, for example, "7" is set as the grouping confirmation specified value, the group area count value becomes "3" by adding the increasing unit, and the grouping processing state machine reflects before confirmation. Transition to the state.

Then, to briefly explain below, the measurement point of the destination moves forward, and the proximity state between the traced measurement point and the traced measurement point is recognized based on the distance value D of the corresponding measurement point data, and the traced measurement point has been traced. The measurement point is updated at the measurement point to be traced, the grouping confirmation specified value is set to, for example, "9", the group area count value is increased to "5", and the grouping processing state machine remains in the pre-confirmation reflection state.

Then, the traced measurement point advances, and the traced measurement point and the grouping confirmation specified value are not updated according to the distance value D of the corresponding measurement point data being "0", and the group area count value is reduced by the decreasing unit. It becomes "3", and the grouping processing state machine transitions to the pre-determination no reflection state.

Then, the destination measurement point advances, and the proximity state between the traced measurement point and the destination measurement point is recognized based on the distance value D of the measurement point data corresponding to the sweep of the aerial propagating wave A5, and the trace is performed. The completed measurement point is updated at the measurement point to be traced, the grouping confirmation specified value is set to, for example, "8", the group area count value is increased to "7", and the grouping processing state machine transitions to the pre-confirmation reflection state. do.

Then, the destination measurement point advances, and the proximity state between the traced measurement point and the destination measurement point is recognized based on the distance value D of the measurement point data corresponding to the sweep of the aerial propagating wave A6, and the trace is performed. The completed measurement point is updated at the measurement point to be traced, and the grouping confirmation specified value is set to, for example, "8". Then, since the group area count value becomes "9" by adding the increasing unit and exceeds the grouping confirmation specified value, it is suppressed to "8", which is the grouping confirmation specified value. Now that the obstacle candidates are confirmed, a new pointer pair that identifies the measurement point data group is secured in the grouping data, and the pointer value of the measurement point and the pointer value of the traced measurement point are set. Will be done. Then, the grouping processing state machine transitions to the state with reflection after being confirmed.

After that, more simply, when the measurement point to be traced is advanced, and each time there is reflection and proximity is recognized based on the distance value D, the traced measurement point and the grouping confirmed specified value are recognized. And the pointer pair of the measurement point data group are updated, the group area count value is added up to the grouping confirmation specified value, and the grouping processing state machine transitions to the no reflection state after confirmation. On the other hand, when there is no reflection and the distance value D is "0", the traced measurement point, the grouping confirmation specified value, and the pointer pair of the measurement point data group are not updated, and the reduction unit is subtracted from the group area count value. , Grouping processing The state machine transitions to the no reflection state after confirmation.

Such a state transition is repeated to search for the end of the obstacle candidate, but at that time, for example, there is no reflection in the sweep of the aerial propagating wave A7, and the distance value D of the corresponding measurement point data becomes “0”. Even so, the group area count value remains at the value obtained by subtracting the reduction unit "1" from the grouping confirmation specified value of, for example, "7" to "10", so that the grouping is immediately disrupted by sporadic disturbance. There is no such thing. For example, even if there is no reflection in the subsequent sweep in addition to the sweep of the aerial propagating wave A8, the grouping is not broken because the decrease unit is set smaller than the increase unit.

Then, after the traced measurement point, the grouping confirmed specified value, and the pointer pair of the measurement point data group are updated based on the measurement point data corresponding to the sweep of the last aerial propagating wave A9 that hits the vehicle, the reflection Since the distance value of the value "0" is lined up in the corresponding part of the measurement data continuously in the absence state, the group area count value continues to decrease accordingly, and when the group area count value reaches the grouping completion specified value, grouping is performed. The processing state machine transitions to the unreachable state. Then, since the content of the pointer pair that identifies the measurement point data group is maintained, the obstacle candidate is determined.
In this way, the identified obstacle candidates are not lost or shredded by disturbances even during rainfall or snowfall, and often correspond to an accurate group of objects.

When the grouping process is completed in this way, further, by executing the tracking program 24, a representative point is selected for tracking over time for each measurement point data group, and tracking used for tracking over time is performed. Information is created one by one (one set) (see three black dots and three sets of tracking information blocks in FIG. 6A).
Tracking information is added each time a new measurement point data group is added to the tracking target, and each tracking information includes, for example, position data of a representative point of the measurement point data group of the tracking target and speed data calculated from the change. Can be included. When the tracked object disappears, the corresponding tracking information is deleted. Therefore, when there is no tracking target at all, the tracking information is completely lost (see FIG. 6E).

Then, by executing the final determination program 25, if there is even one (one set) of tracking information, it is determined that an obstacle exists on the railroad crossing 4. The presence or absence of tracking information can be confirmed quickly and accurately by simply referring to any one of the information for managing the tracking information, such as the number of tracking information data and the presence / absence mark of the first tracking information. be able to.
Therefore, for all the tracking information, it is necessary to determine whether or not the measurement point data group to be tracked and its representative point belong to the obstacle detection area 7, and then the determination of the absence of obstacles can be made. The railroad crossing obstacle detection device 10 is quickly put out with a light load. Then, this determination result is sent to a railroad crossing control device or the like and used for alarm output to a special signal light emitter or the like.

In this way, every time the plane sweep measurement units 11 to 13 perform plane sweep and reflected wave measurement on the railroad crossing 4, data limiting processing, grouping processing, tracking processing, and obstacles to the obstacle detection area 7 related to the measurement data are performed. The existence / non-existence determination process is performed by the fail-safe computer 14, and the process is repeated at a predetermined cycle or the like. Then, among those processes, from the plane sweeping process to the grouping process, the measurement point data group of the processing result is uniquely determined by the traffic state and the image data at that time, but in the subsequent tracking process, the time lapse between a plurality of images is determined. Since the position of the representative point of the measurement point data group is tracked over the time when the tracking disappears, the tracking information remains for a while even after the measurement point data group disappears.

For example, when tracking three measurement point data groups for three vehicles (see the black dots in the image on the right side of FIGS. 5 (c) and 6 (a)), the data of the measurement point data groups is also tracked. Information data is also held in three sets each (see the block on the left side in Fig. 5 (c) and Fig. 6 (a)), but three vehicles move from left to right and the vehicle on the right is in trouble. When the object detection area 7 is exited, the measurement point data group immediately becomes two for the central vehicle remaining in the obstacle detection area 7 and the left vehicle on which at least a part is hung (FIG. 6). (Refer to the solid line in the image on the right side of (b)), as for the tracking information, the one related to the vehicle on the right side is maintained until the time when the tracking disappears (the black dot in the image on the right side in FIG. 6C). And the block on the left).

Then, when the tracking disappearance time elapses for the tracking, the tracking information also becomes two related to the two vehicles related to the obstacle detection area 7 (not shown).
In this way, it is carefully confirmed that the railroad crossing passerby has left the obstacle detection area 7. In addition, although not shown, the time from merger to separation is tracked even when a merger or separation occurs in a plurality of measurement point data groups related to a plurality of railroad crossing passages depending on the traffic of the railroad crossing passages. If it is shorter than the extinction time element, the time-dependent tracking between a plurality of images related to the obstacle candidate can be accurately performed without being disturbed by a large change in the image due to the merger.
After that, when all the railroad crossing passersby exit the obstacle detection area 7, the measurement point data group disappears (see FIG. 6D), and when the tracking disappearance time elapses, the tracking information also disappears (Fig. 6). 6 (e)), it is found that there is no obstacle in the obstacle detection area 7.

Although a new illustration is omitted, the railroad crossing obstacle detection device of the second embodiment differs from the railroad crossing obstacle detection device 10 described above in that the increase unit and the decrease unit of the group area count value are changed from fixed to variable. It is a point. That is, a part of the grouping program 23 has been modified so that in the new grouping process, the unit of increase and the unit of decrease of the group area count value can be switched, and the measurement point data group being traced can be an obstacle candidate. The unit of increase and the unit of decrease of the group area count value are different before and after the determination as related to.

Specifically, in the first embodiment, only a pair of an increase unit and a decrease unit is provided, but in this embodiment 2, the increase unit and the decrease unit are referred to before the obstacle candidate is determined. In addition to this, there is also an additional pair that is referred to after the obstacle candidate is confirmed, so that a total of four units can set the value individually. These values may be changed dynamically at any time, but the initial values may be used continuously. For example, for the sake of simplicity, to give an example of continuous use of the latter initial value, the increase unit and decrease unit for reference before confirmation emphasize continuity as in the case of Example 1 described above. Although it is set to "2" and "1" (see FIG. 3A), the increase unit and decrease unit for reference after confirmation are different from those in the above-mentioned Example 1, and the increase unit and decrease unit emphasize separability. For example, it is set to "1" and "2" (not shown).

Then, when the state machine of the grouping program 23 is transitioning to any of the unreached state, the pre-determined reflection non-confirmed state, and the pre-determined reflection present state (see FIG. 3B), the case of the above-described first embodiment. As with the above, the increase unit and decrease unit are set to "2" and "1" for continuity, which is referred to for pre-confirmation reference (see Fig. 3 (a)), but the grouping processing state machine is confirmed. When transitioning to either the state with post-reflection or the state without post-reflection (see FIG. 3B), the increase unit and decrease unit emphasize separability, unlike the case of Example 1 described above. The one for reference after confirmation, which is set to "" and "2", is referred to (not shown).

In this way, in the grouping process, the absolute value of the increasing unit is made larger than the absolute value of the decreasing unit before the obstacle candidates are determined, and the continuity of the AF points is highly evaluated. The detection accuracy is improved, but on the other hand, after the obstacle candidate is confirmed, the absolute value of the increasing unit is made smaller than the absolute value of the decreasing unit, and the separability of the distance measuring point (distance measuring point) is highly evaluated. Even if there are multiple bodies, the objects are accurately separated from each other, so the smaller railroad crossing passerby is not missed, and the smaller railroad crossing passerby is accurately detected without being confused with the larger railroad crossing passerby. The accuracy can be increased.

To specify the switching between the increase unit and the decrease unit of the group area count value, as described above, two pairs of the increase unit and the decrease unit, that is, a total of four units are set in the data area together with the group area count value. It is not limited to the method of holding in the same data format, and the data held together with the group area count value and referred to by the state machine is a pair of increase unit and decrease unit as in Example 1, that is, There are two units in total, and when the state machine of the grouping program 23 is transitioning to either the unreached state, the pre-determined reflex non-confirmed state, or the pre-confirmed reflexed state, the increase unit and the decrease unit are set to ". When the grouping processing state machine is transitioning to either the confirmed post-reflection state or the post-confirmed non-reflection state by resetting to "2" and "1", the increase unit and the decrease unit are set to "1" and "1". You may set it again to 2 ”.

Although the illustration is omitted, the railroad crossing obstacle detection device of the third embodiment is different from the railroad crossing obstacle detection device 10 described above in that the part of the processing of the tracking program 24 that uses the element at the time of disappearance of tracking is changed. It is a point.
Specifically, a value obtained by converting the moving speed of an object on a cutway at or near 4 km / h, which is generally regarded as the average walking speed of a healthy person, into the moving speed of a representative point of a measurement point data group in the measurement data is set in advance as a predetermined speed. At the same time, when the speed related to the measurement point data group is slower than the above-mentioned predetermined speed during the tracking process, the tracking disappearance element even after the disappearance of the measurement point data group to be tracked in the grouping process is the same as in the first embodiment. The tracking information is retained before the lapse, but when the speed related to the measurement point data group is faster than the above-mentioned predetermined speed, unlike the case of Example 1, the measurement point data group to be tracked is ignored, ignoring the element at the time of tracking disappearance. When is deleted by the grouping process, the corresponding tracking information is promptly deleted.

Similarly, although the illustration is omitted, the railroad crossing obstacle detection device of the fourth embodiment is different from the railroad crossing obstacle detection device 10 described above in that the tracking processing portion using the tracking extinction element is also changed.
Specifically, not only one element at the time of tracking extinction but also a plurality of elements can be associated with each measurement point data group one by one. In addition, during the tracking process, the tracking extinction time element is changed individually for each measurement point data group to be tracked, but in the change process, the movement speed of the representative point of the corresponding measurement point data group is changed. If it becomes slower, the value of the element at the time of tracking disappearance will increase or at least maintain the current status, and if the movement speed of the representative point of the corresponding measurement point data group increases, the value of the element at the time of tracking disappearance will decrease or at least maintain the current status. Will be done. Further, for each measurement point data group, when the moving speed of the representative point is faster than the predetermined speed of Example 2, the value of the corresponding tracking extinction element is cleared to zero time, so that it can be easily and quickly. It is also designed to omit the tracking extension based on the tracking disappearance.

[others]
In the above embodiment, a plurality of sets of plane sweep measurement units 11 to 13 that sweep the airborne wave in a plane and receive the reflected wave are mounted, whereas the crossing passerby is used as an obstacle based on the measurement data. Where only one set of fail-safe computer 14 and judgment program 20 embodying the determination means to detect is mounted, a series of measurements obtained from one of the two sets of plane sweep measurement units 11 to 13 mounted. Although only an example in which data is processed by a single determination means has been described, when there are a plurality of plane sweep measurement units 11 to 13, a series of measurement data becomes a plurality of sequences, and as an acquisition mode thereof, a plurality of measurement data are time-divided. It is assumed that the first aspect is acquired at different timings and the second aspect is acquired in parallel with a plurality of measurement data.

Therefore, if the coping methods are divided according to these aspects, in the case of the first aspect, the determination means are also executed in a time-division manner to OR the determination results, so that a set of determination means can be easily used. Can be dealt with. Further, also in the case of the second aspect, it can be easily dealt with by combining the buffering of the measurement data, the time-division execution of the determination means, and the logical sum of the determination results.
In addition, it is also easy to perform tracking up to the grouping that you want to process in polar coordinates by time division, and after the representative point of the measurement point data group is decided, switch to Cartesian coordinates that are easy to integrate and perform tracking while integrating the representative points. With a light load, the measurement data from a plurality of sets of plane sweep measuring units 11 to 13 can be processed by a single determination means.

In the above embodiment, only one obstacle detection area 7 is defined, but when the number of parallel running tracks is large and the obstacle detection area related to one railroad crossing is very long, the obstacle detection area may be defined. It may be divided into several subregions that do not overlap or overlap.
In that case, for example, by dividing the final determination program 25 into an intermediate determination program and a determination integration program, it is possible to deal with it relatively easily by software.

In the above embodiment, the grouping confirmation specified value changes positively and the grouping completion specification value is fixed to zero, but the zero may be another value for the sake of simplicity, and the grouping confirmation specification may be used. The value may be a fixed value and the grouping completion specified value may be changed, or both the grouping confirmed specified value and the grouping completed specified value may be changed, and may not be a positive number. It suffices if the difference between the grouping confirmation specified value and the grouping completion specified value changes in magnitude against the perspective of the position of the measurement point data group being traced. Positive numbers are not required for group counts, increasing units, or even decreasing units.

In the above embodiment, the situation where one measurement point data group is selected for one railroad crossing passage is described, but it is not rare that a plurality of measurement point data groups are selected for one railroad crossing passage. For example, when the front and rear parts of the railroad crossing passage are clearly detected but the middle part is unclear, or when the left and right sides of the railroad crossing passage are swept in a plane by different aerial propagating wave transmission / reception units 12 and 12, both images of the railroad crossing passage are obtained. It is easy to have multiple measurement point data groups, such as when they are separated from each other in front of and behind the body. In addition, there are cases where only one measurement point data group is selected for a plurality of railroad crossing passages, such as when two railroad crossing passages approach each other. In any case, if there is even one measurement point data group, it is judged on the safe side that an obstacle exists, so there is no inconvenience apart from the amount of data processing.

In the above embodiment, it is assumed that the directions for sweep measurement by the plane sweep measurement units 11 to 13 are predetermined, for example, the measurement start direction is a known fixed direction and the subsequent direction difference is also known, and the direction of the measurement data. For the part of the known data related to, a series of data retention was omitted, and only the part of the fluctuation data related to the distance was retained in the array area of 1 row and N columns, but the distance of the measurement point data. When both the direction and the direction are variable values, the paired data of the distance value and the direction value may be connected to form the measurement data, which may be held in the array area of 2 rows and N columns, for example.

In the above embodiment, when the grouping confirmation specified value is determined by the table lookup of the grouping specified value change table, the distance value D related to the latest one point called the traced measurement point is used. This is because priority is given to reducing the computing load of the computer, and if the computing power of the computer is sufficient, for example, the distance value related to one point between the starting measurement point and the traced measurement point, or the traced from the traced measurement point The average value or the median value of the distance values related to multiple points up to the measurement point may be used.

The application of the railroad crossing obstacle detection device of the present invention is not limited to those that detect only obstacles, and in addition to obstacles such as detection of railroad crossing passages in situations where they do not cause obstacles and detection of trains. It can also be applied to those that detect other things.

4 ... Railroad crossing, 7 ... Obstacle detection area (monitoring area),
10 ... Railroad crossing obstacle detection device,
11-13 ... Plane sweep measurement unit, 11 ... Rotation control unit,
12 ... Airborne wave transmitter / receiver, 13 ... Signal processing unit, 14 ... Fail-safe computer,
20 ... Judgment program,
21 ... Data input program, 22 ... Data limited program,
23 ... Grouping program (grouping process in image),
24 ... Tracking program (tracking process over time),
25 ... Final judgment program

Claims (9)

A crossing obstacle detection device equipped with a plane sweep measurement unit that sweeps an aerial propagating wave in a plane and acquires measurement data of a reflection position, and a computer equipped with a determination means for determining the presence or absence of an obstacle based on the measurement data. In the determination means, the grouping process for specifying the measurement point data group of the obstacle candidate is performed based on the measurement data, and the measurement point data included in the measurement data is included in the grouping process. The group area count value is increased or decreased according to the size of the distance between the traced measurement point and the destination measurement point while tracing the sequence, and when the group area count value reaches the grouping confirmation specified value, the measurement point data being traced. A crossing obstacle characterized in that the group is determined to be related to an obstacle candidate, and when the group area count value reaches the grouping completion specified value, the identification of the measurement point data group being traced is completed. Detection device. The railroad crossing obstacle detection device according to claim 1, wherein the absolute value of the increasing unit of the group area count value is larger than the absolute value of the decreasing unit of the group area count value. Claim 1 or claim 1, wherein the determination means increases or decreases the group area count value only between the grouping completion designated value and the grouping finalized designated value in the grouping process. The railroad crossing obstacle detection device according to claim 2. The present invention according to any one of claims 1 to 3 , wherein the determination means determines a representative point one by one for the measurement point data group identified as an obstacle candidate in the grouping process. The described railroad crossing obstacle detection device. It said determination means, upon the grouping process, have been crossing obstacle detection device according to any one of claims 1 to 4, characterized in that is adapted to handle the measurement data remains polar. It said determination means, upon the grouping process, any one of claims 1 to 5, characterized in that is adapted to follow in one direction while traversing a series of measurement point data contained in the measurement data Railroad crossing obstacle detection device described in. The difference between the grouping definite specified value and the grouping completion specified value, according to claim 5 or claims characterized in that it is as to the magnitude change against the distance of the position of the measurement point data group in follow the Item 6. The railroad crossing obstacle detection device according to item 6. The unreached state when the valid measurement point data of the value has not yet been reached and the valid measurement point data of the value are reached before the obstacle candidate is determined in the portion of the determination means to be subjected to the grouping process. Pre-confirmed reflex state when there is, pre-confirmation no reflex state when reaching invalid measurement point data before the obstacle candidate is confirmed, and valid measurement point data of the value after the obstacle candidate is confirmed A state machine with a post-confirmation reflex state when arriving at and a post-confirmation non-reflective state when arriving at invalid measurement point data of the value after the obstacle candidate is confirmed is incorporated. It has been crossing obstacle detection device according to any one of claims 1 to 7, characterized. In the grouping process, the determination means may switch between an increase unit and a decrease unit of the group area count value before and after determining the measurement point data group being traced as relating to an obstacle candidate. crossing obstacle detection device according to any one of claims 1 to 8, characterized in that it is so possible.

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