Automatic door systems, sensors for automatic doors, traffic flow identification devices, traffic flow identification methods, traffic flow identification programs

Abstract

To provide a technique of an automatic door device capable of comprehending flow lines as detection targets in front and behind when multiple detection targets overlap and then separate.SOLUTION: An automatic door device 100 in a mode includes: an activation sensor 4 that detects a detection target which is a person or thing around an opening in a detection area; an identification unit 5 that identifies the position of the detection target detected by the activation sensor 4; a storage section 3 that stores a piece of transition information regarding positional transitions; and a flow line identification unit 6 that identifies the flow line of the detection target based on the transition information. The flow line identification unit 6 is configured to, when the trajectory of multiple detection targets based on transition information diverges from the confluence state, identify the flow lines of multiple detection targets while associating multiple trajectories based on the transition information before and after branching.SELECTED DRAWING: Figure 2

Description

Technical Field

[0001] The present invention relates to an automatic door device, an automatic door sensor, a traffic flow identification device, a traffic flow identification method, and a traffic flow identification program.

Background Art

[0002] Devices that count the number of people entering and leaving an automatic door using sensors are known. For example, Patent Document 1 describes a device for counting the number of people entering and leaving an automatic door having a motor for opening and closing the door. This device includes a sensor installed inside and outside the building that detects a passing object, and an auxiliary sensor for preventing the passing object from being sandwiched by the door, and controls the drive device based on the signal from the sensor. This device detects the moving direction of the passing object and that the passing object has passed through the door using these sensors, and counts the passing objects from the detection results.

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] The device described in Patent Document 1 can count the number of people entering and leaving by detecting passing objects in time series using the internal and external sensors and the auxiliary sensor. However, when a plurality of detection targets overlap and then separate, it is difficult to grasp the traffic flow of the detection targets before and after that.

[0005] In view of such problems, one object of the present invention is to provide a technology for an automatic door device capable of grasping the traffic flow of detection targets before and after when a plurality of detection targets overlap and then separate.

Means for Solving the Problems

[0006] To solve the above problems, an automatic door device according to one aspect of the present invention includes: an activation sensor that detects a detection target, which is a person or object, around an opening in a detection area; an identification unit that identifies the position of the detection target detected by the activation sensor; a storage unit that stores transition information regarding the change in position; and a movement path identification unit that identifies the movement path of the detection target based on the transition information. When multiple trajectories of multiple detection targets based on the transition information diverge from a merging state, the movement path identification unit identifies the movement paths of multiple detection targets by relating the multiple trajectories before and after the divergence based on the transition information.

[0007] Furthermore, any combination of the above, or any substitution of the components or expressions of the present invention between methods, apparatus, programs, temporary or non-temporary storage media recording programs, systems, etc., are also valid embodiments of the present invention. [Effects of the Invention]

[0008] According to the present invention, it is possible to provide an automatic door system technology that can determine the movement paths of multiple detection targets before and after they overlap and then separate. [Brief explanation of the drawing]

[0009] [Figure 1] This is a schematic front view showing the automatic door device of the embodiment. [Figure 2] Figure 1 is a block diagram illustrating the automatic door system in schematic form. [Figure 3] Figure 1 is a schematic diagram showing an example of the detection area of ​​an automatic door device. [Figure 4] Figure 3 is a schematic diagram showing the trajectory of the detection block corresponding to the movement of the detected object within the detection area. [Figure 5] This is a schematic diagram showing an example of the movement progression of a detected object. [Figure 6] This is a schematic diagram showing the trajectory of the detection block corresponding to the movement of the detected object in Figure 5. [Figure 7] Figure 1 is a schematic diagram showing a first example of the operation of the movement path identification unit of the automatic door system. [Figure 8]It is a schematic diagram showing a second example of the operation of the traffic line identification unit of the automatic door device in FIG. 1. [Figure 9] It is a schematic diagram showing a third example of the operation of the traffic line identification unit of the automatic door device in FIG. 1. [Figure 10] It is a schematic diagram showing a fourth example of the operation of the traffic line identification unit of the automatic door device in FIG. 1. [Figure 11] It is a schematic diagram showing another example of the movement transition of the detection target. [Figure 12] It is a schematic diagram showing the locus of the detection block corresponding to the movement transition of the detection target in FIG. 11. [Figure 13] It is a schematic diagram showing an example of a detection area divided into a plurality of divided areas. [Figure 14] It is a schematic diagram showing a first example of a traffic line pattern. [Figure 15] It is a schematic diagram showing a second example of a traffic line pattern. [Figure 16] It is a schematic diagram showing a third example of a traffic line pattern. [Figure 17] It is a schematic diagram showing a fourth example of a traffic line pattern. [Figure 18] It is a flowchart showing an example of the process of the automatic door device in FIG. 1.

Embodiments for Carrying Out the Invention

[0010] Among the embodiments disclosed in this specification, those composed of a plurality of objects may integrate the plurality of objects, and conversely, those composed of one object can be divided into a plurality of objects. Whether integrated or not, it should be configured so that the object of the invention can be achieved.

[0011] Among the embodiments disclosed in this specification, those in which a plurality of functions are provided dispersedly may provide some or all of the plurality of functions in an aggregated manner, and conversely, those in which a plurality of functions are provided in an aggregated manner can be provided so that some or all of the plurality of functions are dispersed. Whether the functions are aggregated or dispersed, it should be configured so that the object of the invention can be achieved.

[0012] In addition, for separate constituent elements having common points, they are distinguished by attaching "first, second", etc. at the beginning of the name, and these are omitted when they are generically referred to. In addition, terms including ordinal numbers such as first and second are used to describe various constituent elements, but this term is only used for the purpose of distinguishing one constituent element from other constituent elements, and the constituent elements are not limited by this term.

[0013] An automatic door device according to an aspect of the present disclosure includes an activation sensor that detects a detection target that is a person or an object around an opening in a detection area, a specifying unit that specifies the position of the detection target detected by the activation sensor, a storage unit that stores transition information regarding the transition of the position, and a flow line identification unit that identifies the flow line of the detection target based on the transition information. When a plurality of trajectories of a plurality of detection targets based on the transition information branch from a confluent state, the flow line identification unit associates the plurality of trajectories before and after the branch based on the transition information to identify the flow line of the plurality of detection targets.

[0014] According to this configuration, the flow line of the detection target can be grasped from a plurality of trajectories that branch from a confluent state.

[0015] As an example, the flow line identification unit associates a plurality of trajectories based on the moving speed of each of the plurality of detection targets. In this case, the relevance before and after the branch of the trajectories branched by the moving speed of the detection target can be grasped.

[0016] As an example, the flow line identification unit associates a plurality of trajectories based on the positional relationship of each of the plurality of detection targets. In this case, the relevance before and after the branch of the trajectories branched by the positional relationship of the detection target can be grasped.

[0017] For example, a detection area has multiple detection spots, and the identification unit identifies the trajectory of a detection block consisting of one or more detection spots that are in a detected state as the trajectory of the target to be detected. The movement identification unit determines that the multiple trajectories are in a converging state when the distance between the multiple trajectories is less than a threshold. In this case, the chronological position of the target to be detected can be identified from the trajectory of the detection block, and the relationship before and after the branching of the trajectory can be easily estimated based on this chronological change in position.

[0018] As an example, the movement path identification unit identifies the movement paths of multiple detected objects based on the start and end points of multiple trajectories within the detection area. In this case, the movement paths can be easily identified by connecting the start and end points.

[0019] An automatic door sensor in one aspect of the present disclosure includes: a detection unit that detects a person or object in the vicinity of an opening in a detection area provided around the opening; a specification unit that identifies the location of the detection object detected by the detection unit; a storage unit that stores transition information relating to the location; and a movement path identification unit that identifies the movement path of the detection object based on the transition information. When multiple trajectories of multiple detection objects based on the transition information diverge from a merging state, the movement path identification unit identifies the movement paths of multiple detection objects by relating the multiple trajectories before and after the divergence based on the transition information.

[0020] This configuration allows for the identification of the target's movement path from multiple trajectories branching off from a merging point.

[0021] A movement path identification device according to one aspect of the present disclosure includes: a detection unit that detects a detection target, which is a person or object, in a detection area provided around an opening; a specification unit that identifies the location of the detection target detected by the detection unit; a storage unit that stores transition information relating to the location; and a movement path identification unit that identifies the movement path of the detection target based on the transition information. When multiple trajectories of multiple detection targets based on the transition information diverge from a merging state, the movement path identification unit identifies the movement path of multiple detection targets by relating the multiple trajectories before and after the divergence based on the transition information.

[0022] This configuration allows for the identification of the target's movement path from multiple trajectories branching off from a merging point.

[0023] The present invention will be described below with reference to the drawings, based on preferred embodiments. In embodiments and modifications, the same or equivalent components and members will be denoted by the same reference numerals, and redundant explanations will be omitted as appropriate. When there are multiple identical or equivalent elements that are denoted by alphabetical numerals, a number (1, 2, 3, etc.) will be added to the end of the numeral to distinguish them, and the number will be omitted when referring to them collectively. In addition, the dimensions of the members in each drawing will be enlarged or reduced as appropriate to facilitate understanding. Furthermore, some members that are not important for explaining the embodiments will be omitted from the drawings.

[0024] [First Embodiment] Hereinafter, an automatic door device 100 according to the first embodiment of the present invention will be described with reference to the drawings. Figure 1 is a schematic front view showing the automatic door device 100 of the embodiment. The automatic door device 100 shown in Figure 1 is a double sliding door type, in which two doors 9 automatically open and close to the left and right. The doors 9 are a pair, left and right, and are configured to move back and forth along fixed 22 that are fixedly arranged with a gap between them on the left and right sides of the opening 23, thereby opening and closing the opening 23. As an example, the automatic door device 100 is a device that opens and closes doors for openings such as walls that partition spaces in various facilities such as train stations, hotels, department stores, hospitals, and elderly care facilities.

[0025] Hereinafter, the direction along the opening and closing direction of the automatic door device 100 will be referred to as the left-right direction. As shown in Figure 1, when viewing the automatic door device 100 from the front, the left side will be referred to as "left" or "leftward," and the right side will be referred to as "right" or "rightward." The direction along the projection direction of the automatic door device 100 will be referred to as the front-back direction. The area in front of the automatic door device 100 will be referred to as "front" or "forward," and the area beyond the automatic door device 100 in the front-back direction will be referred to as "rear" or "rearward." In Figure 1, the detection area 70 is arranged from the front to the rear of the opening 23 and the fix 22. The dimension in the left-right direction may also be referred to as the "left-right width," and the dimension in the front-back direction may be referred to as the "front-back width." Such directional notations do not restrict the orientation of the automatic door device 100, and the automatic door device 100 can be used in any orientation.

[0026] Door 9 is in a fully closed state when the left and right ends of the door come into contact with each other so that the opening 23 is closed. Door 9 moves so that the ends of the door separate, and the ends of the door move to near the end of the fixed 22 on the opening 23 side and stop, opening the opening 23 to a fully open state. Note that the automatic door device 100 may be a double sliding door type, or a single sliding door type, etc.

[0027] The automatic door device 100 includes an automatic door sensor 10 and an automatic door drive device 90 that drives the door 9 to open and close. The automatic door sensor 10 mainly includes an activation sensor 4 and an information processing unit 20, which will be described later. The activation sensor 4 detects a person or object (hereinafter referred to as "detection target") around the opening 23.

[0028] The activation sensor 4 is positioned, for example, on the transom 16 above the opening 23. It emits and receives infrared light diagonally downward from its position on the transom 16, and detects, for example, an object entering the door 9, and outputs an activation signal. Details of the activation sensor 4 will be described later.

[0029] The auxiliary photoelectric sensor 30 functions as an opening detection unit that detects the object to be detected in the opening 23. By detecting the movement of the object to be detected across the opening 23, the auxiliary photoelectric sensor 30 can complement the movement identification function of the movement identification unit 6 and the movement determination function of the movement determination unit 7, which will be described later. For example, the auxiliary photoelectric sensor 30 can detect whether the object to be detected has passed through the opening 23. For example, the appropriateness of the identification result of the movement identification unit 6 can be determined according to the detection result of the auxiliary photoelectric sensor 30. Also, for example, the appropriateness of the determination result of the movement determination unit 7 can be determined according to the detection result of the auxiliary photoelectric sensor 30. As a result, misrecognition by the movement identification unit 6 or misjudgment by the movement determination unit 7 can be reduced.

[0030] As an example, the auxiliary photoelectric sensor 30 is a photoelectric detection device and has a light emitter 301 and a light receiver 302 positioned near the opening 23 of the fixed 22. The auxiliary photoelectric sensor 30 detects when the light rays passing between the light emitter 301 and the light receiver 302 are blocked, and transmits detection information indicating the presence of a person or object on the track of the door 9 to the control unit 91 via the communication unit 8. In addition to the photoelectric type, the auxiliary photoelectric sensor 30 may also be a light reflection type or ultrasonic type detection device attached to the transom 16.

[0031] As shown in Figure 1, the automatic door drive unit 90 includes a control unit 91 and a door engine 92. The control unit 91 controls the door engine 92 to open and close the door 9 based on control information from the automatic door sensor 10. There are no limitations on the transmission path 96 that transmits the control information from the automatic door sensor 10, but in this example, the transmission path 96 includes an internal bus (e.g., CAN: Controller Area Network). Based on the control of the control unit 91, the door engine 92 rotates a drive motor (not shown) to drive the door 9 to open and close.

[0032] When the control unit 91 receives a start signal from the automatic door sensor 10 to the start sensor 4, it activates the motor (not shown) of the door engine 92 to drive the door 9 until it is fully open. After the door 9 changes to the fully open state, the control unit 91 holds it in the fully open state for a certain period of time, and then operates the door engine 92 in the reverse direction to drive the door 9 until it is fully closed. When the control unit 91 receives detection information from the auxiliary photoelectric sensor 30 while the door 9 is being driven to close, it reverses the direction in which the door engine 92 drives the door 9, bringing the door 9 to the fully open state.

[0033] Figure 2 is a schematic block diagram of the automatic door device 100 according to the present invention. Each block shown in Figure 2 can be realized in hardware terms by components such as a computer processor, CPU, and memory, as well as electronic circuits and mechanical devices, and in software terms by computer programs, etc., but here, the functional blocks realized by the cooperation of these components are depicted. Therefore, it will be understood by those skilled in the art that these functional blocks can be realized in various ways by combinations of hardware and software.

[0034] The automatic door sensor 10 described above can be configured to include an information processing unit 20 that processes the detection results of the activation sensor 4 and the auxiliary photoelectric sensor 30.

[0035] The activation sensor 4 will be explained with reference to Figure 3. Figure 3 is a schematic diagram showing an example of a detection area 70 consisting of multiple detection spots 71. This diagram shows the detection area 70 on the floor surface. The activation sensor 4 detects the object to be detected in the detection area 70 which has multiple detection spots 71. The activation sensor 4 in this example is an infrared reflection type sensor that emits infrared light into the detection area 70 and receives the reflected light from the object to be detected.

[0036] The detection area 70 has a three-dimensional range from the floor to the transom 16 where the activation sensor 4 is located and to the ceiling. The detection area 70 is composed of multiple detection spots 71 arranged in a matrix, with 12 columns in the left-right direction parallel to the direction of movement of the door 9, and 12 rows in the front-back direction perpendicular to the direction of movement of the door 9. Each row is assigned the 1st row, 2nd row, ... 11th row, 12th row from front to back. Each column is assigned the columns A, B, ... K, L from left to right. In this embodiment, an opening 23 is provided between the 6th row and the 7th row, and the door 9 moves between the 6th row and the 7th row.

[0037] Each detection spot 71 is assigned an address 1A, 1B, ..., 12K, 12L corresponding to its position in the matrix. Each assigned address corresponds to the position information of each detection spot 71. The shape of each detection spot 71 and the overall shape of the detection area 70 may be a polygon other than a circle, ellipse, rectangle, or rectangle. As mentioned above, the detection spots 71 may have various shapes, and their shape may also change depending on the sensor method, etc., and they represent individual regions into which the detection area 70 is divided into multiple parts. Conversely, it may also be thought that the detection area 70 as a whole is formed by multiple detection spots.

[0038] The automatic door sensor 10 generates an activation signal to open and close the door 9 when each detection spot 71 in the detection area 70 detects an object.

[0039] The activation sensor 4 may be configured to detect the entire detection area 70 using a single detection unit (for example, an infrared reflective sensor), but the activation sensor 4 in this embodiment has two detection units 41 and 42 and an integration unit 43. The first detection unit 41 is positioned in front of the transom 16 to detect objects in detection spots 71 belonging to rows 1 to 6. The second detection unit 42 is positioned behind the transom 16 to detect objects in detection spots 71 belonging to rows 7 to 12. The integration unit 43 integrates the detection signals from the first detection unit 41 and the second detection unit 42 and outputs them to the information processing unit 20 as a detection signal for the entire detection area 70.

[0040] As shown in Figure 2, the information processing unit 20 includes an input unit 25, an opening / closing processing unit 26, a specific unit 5, a movement path identification unit 6, a movement path determination unit 7, a storage unit 3, and a communication unit 8.

[0041] The input unit 25 sequentially acquires the detection level at each of the multiple detection spots 71, which will be described later, from the activation sensor 4. In this example, the input unit 25 sequentially acquires the detection signal for the entire detection area 70, which has been integrated by the integration unit 43. The input unit 25 also acquires the detection result from the auxiliary photoelectric sensor 30. Based on the results acquired by the input unit 25, the switching processing unit 26 determines that a detection target exists if the detection level at each detection spot 71 is within a predetermined range, and generates an activation signal. The state in which a detection target is determined to exist at each detection spot 71 is called a detection state, and the state in which there is no detection state is called a non-detection state.

[0042] The memory unit 3 stores input information and intermediate processing information in chronological order. In particular, the memory unit 3 stores transition information regarding the position changes of the detection block 72, which will be described later. The trajectory 73 of the detection block 72 corresponds to the movement trajectory of the object being detected. The transition information includes information about the position trajectory 73 that changes over time, and includes chronological position information of the detection block 72, etc. Therefore, the identification unit 5 can identify the trajectory 73 of the detection block 72 based on the transition information. The memory unit 3 also stores the program P100, which will be described later. The communication unit 8 transmits the activation signal of the opening / closing processing unit 26 to the control unit 91 of the automatic door drive device 90.

[0043] See also Figure 4. Figure 4 is a schematic diagram showing the trajectory 73 of the detection block 72 corresponding to the movement of the detection target X in the detection area 70. The hatched area in Figure 4 shows a map of the trajectory 73 of the detection block 72. Figures 3 and 4 show the case in which a single detection spot 71 is detected by a single detection target X. The symbol X-1 indicates the state immediately after the detection target X enters the detection area 70. In particular, the symbol X-1 can be said to be the state in which the detection target X is first detected in the detection area 70. The symbol X-2 indicates the state immediately before the detection target X exits the detection area 70. In particular, the symbol X-2 can be said to be the state in which the detection target X is last detected in the detection area 70. In Figure 3, the symbol Y indicates the contour transition line Y which connects the movement of the detection target X with the change in the position of the contour of the detection target X. The movement of the detection target X may be a line that passes through approximately the center in the width direction of the contour transition line Y.

[0044] A detection block 72 is a block consisting of one or more detection spots 71 in a detection area 70 that are in a detected state. When the object to be detected X moves, the position of the detection block 72 changes along with the movement of the object to be detected X. As a result, the detection block 72 virtually forms a trajectory 73 in the detection area 70. The trajectory 73 has a starting point S and an ending point Q. The starting point S of the trajectory 73 is the detection block 72 consisting of the detection spot 71 that changed to a detected state immediately after the object to be detected X entered the detection area 70. The ending point Q of the trajectory 73 is the detection block 72 consisting of the detection spot 71 that was in a detected state immediately before the object to be detected X left the detection area 70.

[0045] The identification unit 5 identifies the trajectory 73 of the detected object X detected by the activation sensor 4. The identification unit 5 can also identify the starting point S and ending point Q of the trajectory 73. The movement path identification unit 6 identifies the movement path of the detected object X based on the transition information of the detected object X identified by the identification unit 5. The movement path identification unit 6 can identify the movement path of the detected object X based on the trajectory 73 of the detected object X. As shown in Figure 4, the movement path determination unit 7 determines the movement path M of the detected object X based on the starting point S and ending point Q of the movement path recognized by the movement path identification unit 6.

[0046] In addition, depending on the detection target, even with a single detection target X, multiple detection spots 71 may be in a detection state. In this case, a block consisting of multiple detection spots 71 in a detection state is called a detection block 72. A detection block 72 consisting of two or more detection spots 71 is a collection of detection spots 71 that are located closer to each other than a predetermined distance (hereinafter referred to as the "threshold"). In this example, the detection block 72 consists of two or more detection spots 71 that are adjacent to each other. The threshold here is a distance equivalent to the width of a single detection spot 71.

[0047] Figure 5 is a schematic diagram showing an example of the movement transition of multiple detection targets X1 and X2. In this figure, the movement of multiple detection targets X1 and X2 in 70 is shown by contour transition lines Y1 and Y2, which connect the positional changes of the contours of detection targets X1 and X2. The movement lines of the detection targets may also be lines that pass approximately through the center in the width direction of contour transition lines Y1 and Y2.

[0048] In Figure 5, symbols X1-1 and X2-1 indicate the state immediately after the detection targets X1 and X2 enter the detection area 70. In particular, symbols X1-1 and X2-1 can be said to represent the state in which the detection targets X1 and X2 are first detected in the detection area 70. Symbols X1-2 and X2-2 indicate the state in which the detection targets X1 and X2 have moved to the vicinity of the front side of the opening 23, and symbols X1-3 and X2-3 indicate the state in which the detection targets X1 and X2 have moved to the vicinity of the rear side of the opening 23. Symbols X1-4 and X2-4 indicate the state immediately before the detection targets X1 and X2 exit the detection area 70. In particular, symbols X1-4 and X2-4 can be said to represent the state in which the detection targets X1 and X2 are last detected in the detection area 70.

[0049] Thus, when the detection targets X1 and X2 pass through the opening 23 at approximately the same time, as indicated by the symbols X1-2, X2-2 and X1-3, X2-3, the detection targets X1 and X2 approach each other in the vicinity of the opening 23, and the contour transition lines Y1 and Y2 of the detection targets X1 and X2 may also overlap.

[0050] Figure 6 shows the trajectories 73 and 74 of the detection block 72 corresponding to the movement of multiple detection targets X1 and X2 shown in Figure 5. The hatched areas in this figure show a map of the trajectories 73 and 74 of the detection block 72.

[0051] When the trajectory 73 of the detected object X1 and the trajectory 74 of X2 approach each other beyond a threshold, the trajectories 73 and 74 become adjacent to each other, making it difficult to distinguish their boundaries, as shown in the range indicated by addresses 4E-9H. In other words, within this range, the trajectories 73 and 74 merge and become one. This merging of multiple trajectories 73 and 74 when they approach each other beyond a threshold is called the confluence of multiple trajectories 73 and 74, and the state in which multiple trajectories have merged is called the confluence state. The threshold here is the distance corresponding to the width of a single detection spot 71.

[0052] After multiple trajectories 73 and 74 merge, the boundary becomes discernible when the trajectory 73 of the detection target X1 and the trajectory 74 of X2 separate by more than a threshold. This separation of multiple trajectories from a threshold is called branching of multiple trajectories. The threshold here is the distance corresponding to the width of a single detection spot 71.

[0053] When multiple trajectories that were previously merged diverge, it becomes difficult to determine the correspondence between the diverged trajectories 75 and 76 and the detected targets X1 and X2. In other words, when there is merging and diverging, the multiple trajectories 73 and 74 before the merging and the multiple trajectories 75 and 76 after the divergence become disconnected, making their correspondence unclear and making it difficult to handle them continuously.

[0054] In this embodiment, the movement path identification unit 6 determines that multiple trajectories 73 and 74 are in a merged state when the distance between them is less than a threshold (the width of a single detection spot 71). When multiple trajectories of multiple detection targets X1 and X2 branch off from a merged state, the movement path identification unit 6 identifies the movement paths of the multiple detection targets X1 and X2 by relating the multiple trajectories 73 and 74 before the merge and the multiple trajectories 75 and 76 after the branching based on the transition information. As described above, the transition information is stored in the memory unit 3 and is information relating to the transition of trajectories 73 and 74 of the detection block 72 that changes over time, and includes information such as the time-series position information of the detection block 72. For example, the transition information includes a map of trajectories shown in the hatched area of ​​Figure 6.

[0055] Linking multiple trajectories 73, 74, 75, and 76 means estimating the relationships between multiple trajectories 73, 74, 75, and 76 based on predetermined conditions, and then virtually connecting those with relatively high relationships based on the estimation results. As a result, it becomes possible to treat the multiple trajectories 73 and 74 before merging, which are disconnected from each other, and the multiple trajectories 75 and 76 after branching, as continuous. There are no limitations to the process of linking multiple trajectories 73, 74, 75, and 76 based on transition information, but several examples are explained below.

[0056] As an example, the movement path identification unit 6 can associate multiple trajectories based on the movement speed of each of the multiple detection targets. The movement speed of the detection targets can be obtained as the change in position of the detection block per unit time. The following will explain this using the first and second examples.

[0057] (Example 1) Referring to Figure 7, the first example will be explained. In the following explanation, the region between trajectories 73, 74 and trajectories 75, 76 will be referred to as the confluence region. Also, in the figure, multiple trajectories 73, 74, 75, and 76 will be shown with thick lines. In the first example, multiple trajectories are associated based on the movement speeds of multiple detection targets corresponding to multiple trajectories 73, 74, 75, and 76, before and after the confluence. The inventor has found that the ranking of the movement speeds of the detection targets often does not change before and after the confluence. When the movement speeds of multiple detection targets at positions before and after the confluence region (shown as black circles in the figure) are V1, V2, V3, and V4, the movement speeds V1 and V2 before the confluence are ranked in descending order, and the movement speeds V3 and V4 after the branching are ranked in descending order.

[0058] According to this finding, it can be inferred that trajectories with the same ranking of movement speed before merging and the same ranking of movement speed after branching are continuous. In the example in Figure 7, movement speeds V1 and V3 are ranked 1st, and movement speeds V2 and V4 are ranked 2nd. In this case, trajectories 73 and 75, both ranked 1st, are continuous, and trajectories 74 and 76, both ranked 2nd, are also presumed to be continuous. Therefore, trajectories 73 and 75 can be connected as shown by the dashed line and treated as a continuous trajectory 77, and trajectories 74 and 76 can be connected as shown by the dashed line and treated as a continuous trajectory 78.

[0059] (Second example) Referring to Figure 8, a second example will be explained. The inventor has found that the movement speeds before and after the confluence region of the detected object are often close to each other. According to this finding, trajectories with similar movement speeds can be presumed to be continuous. In the example in Figure 8, movement speed V1 is closer to movement speed V3 than to movement speed V4, and movement speed V2 is closer to movement speed V4 than to movement speed V3. In this case, trajectories 73 and 75 are continuous to each other, and trajectories 74 and 76 can be presumed to be continuous to each other. Therefore, trajectories 73 and 75 can be connected as shown by the dashed line and treated as a continuous trajectory 77, and trajectories 74 and 76 can be connected as shown by the dashed line and treated as a continuous trajectory 78.

[0060] As an example, the movement path identification unit 6 can associate multiple trajectories based on the positional relationships of multiple detection targets. The positional relationships of the detection targets can be obtained as the positional relationships of the detection blocks. The third and fourth examples will be explained below.

[0061] (Third example) Referring to Figure 9, a third example of relating multiple trajectories 73, 74, 75, and 76 will be explained. The inventor has found that the positional relationship of multiple detection targets before merging is often maintained after branching. According to this finding, trajectories that are close in position can be presumed to be continuous. In the example in Figure 9, the position U1 of trajectory 73 immediately before merging is closer to the position U3 of trajectory 75 immediately after branching than the position U4 of trajectory 76 immediately after branching. Also, the position U2 of trajectory 74 immediately before merging is closer to the position U4 of trajectory 76 immediately after branching than the position U3 of trajectory 75 immediately after branching. In this case, trajectories 73 and 75 are continuous with each other, and trajectories 74 and 76 can be presumed to be continuous with each other. Therefore, trajectories 73 and 75 can be connected as shown by the dashed line and treated as a continuous trajectory 77, and trajectories 74 and 76 can be connected as shown by the dashed line and treated as a continuous trajectory 78.

[0062] (Fourth example) Referring to Figure 10, a fourth example of linking multiple trajectories 73, 74, 75, and 76 is explained. Insights suggest that when the positional relationship of multiple detection targets is maintained, the positional relationship in the left-right direction is often also maintained. Let W1 and W2 be the distances from one end (in this example, the left end) of the detection area 70 to positions U1 and U2 of trajectories 73 and 74 immediately before merging. Also, let W3 and W4 be the distances from one end of the detection area 70 to positions U3 and U4 of trajectory 75 immediately after branching. In this case, distances W1 and W2 are ranked in ascending order, and distances W3 and W4 are ranked in ascending order.

[0063] When considering distances from one end, trajectories can be presumed to be continuous if their distance ranking immediately before merging and their distance ranking immediately after branching are the same. In the example in Figure 10, distances W1 and W3 are ranked 1st, and distances W2 and W4 are ranked 2nd. In this case, trajectories 73 and 75, both ranked 1st, are presumed to be continuous, and trajectories 75 and 76, both ranked 2nd, are presumed to be continuous. Therefore, trajectories 73 and 75 can be connected as shown by the dashed line and treated as a continuous trajectory 77, and trajectories 74 and 76 can be connected as shown by the dashed line and treated as a continuous trajectory 78.

[0064] Alternatively, another method using the left-right positional relationship can also be employed. For example, just before the merge, position U1 of trajectory 73 is to the left of position U2 of trajectory 74, and immediately after the divergence, position U3 of trajectory 75 is to the left of position U4 of trajectory 76. In this case, it can be assumed that trajectories 73 and 75, both on the left, are continuous with each other, and trajectories 74 and 76, both on the right, are continuous with each other.

[0065] Refer to Figure 6. The movement path identification unit 6 identifies the movement paths M1 and M2 of multiple detection targets based on the starting points S1 and S2 and ending points Q1 and Q2 of the trajectories 77 and 78 in the detection area 70. As mentioned above, the starting point of the trajectory is a detection block consisting of detection spots that changed to a detection state immediately after the detection target entered the detection area. The ending point of the trajectory is a detection block consisting of detection spots that were in a detection state immediately before the detection target left the detection area.

[0066] In the example in Figure 6, the starting point S1 of trajectory 77 is a detection block with address 1D, and the starting point S2 of trajectory 78 is a detection block with address 1I. Also, the ending point Q1 of trajectory 77 is a detection block with address 12D, and the ending point Q2 of trajectory 78 is a detection block with address 12I. The movement path identification unit 6 identifies the movement path M1 connecting the starting point S1 and the ending point Q1, and identifies the movement path M2 connecting the starting point S2 and the ending point Q2.

[0067] Refer to Figures 11 and 12. Figure 11 is a diagram showing another example of the movement transition of multiple detection targets X1 and X2. Figure 12 is a diagram showing the trajectory 73 of the detection block 72 corresponding to the movement transition of the multiple detection targets X1 and X2 shown in Figure 11. The hatched area in this figure shows a map of the trajectory of the detection block 72.

[0068] In the examples shown in Figures 11 and 12, multiple detection targets X1 and X2 enter the detection area 70 in close proximity, and at the time of entry, the trajectories of detection targets X1 and X2 are closer together than the threshold and merged. The trajectories pass through the opening 23 in a merged state and then branch off. In this case, it is difficult to determine whether there is one or multiple detection targets until the branching occurs. Therefore, when the multiple trajectories of multiple detection targets X1 and X2 merge and then branch off, the movement path identification unit 6 of the embodiment can identify the movement paths of multiple detection targets X1 and X2 by relating the multiple trajectories at the time of merging and after branching based on transition information. In particular, when the movement path identification unit 6 detects branching, it estimates multiple trajectories 73, 74, 75, and 76 based on transition information.

[0069] In the example shown in Figure 12, the endpoint Q1 of trajectory 77 corresponding to the detected target X1 is a detection block consisting of addresses 12E and 12F, and the endpoint Q2 of trajectory 78 corresponding to the detected target X2 is a detection block consisting of addresses 12I and 12J. From this result, it can be estimated that the number of detected targets is 2.

[0070] The detection block consisting of addresses 1H-1K at the time of entry is divided by the number of detection targets (=2), and one of the detection blocks consisting of addresses 1H and 1I and the other consisting of addresses 1J and 1K can be estimated to be the starting point S1 and the other the starting point S2. Here, a fourth example that associates multiple trajectories is applied, and the starting point address is estimated using the distance from one end (the left end in this example) of the detection area 70 at the endpoints Q1 and Q2. As a result, the detection block consisting of addresses 1H and 1I, which is the first in terms of distance from the left end, can be estimated to be the starting point S1, and the detection block consisting of addresses 1J and 1K, which is the second in terms of distance from the left end, can be estimated to be the starting point S2. Based on this estimation result, the movement path identification unit 6 identifies the movement path M1 connecting the starting point S1 and the endpoint Q1, and identifies the movement path M2 connecting the starting point S2 and the endpoint Q2.

[0071] In the example shown in Figure 12, the starting points S1 and S2, and the ending points Q1 and Q2, are each detection blocks consisting of multiple detection spots. In such cases, the movement path identification unit 6 can determine, based on predetermined conditions, that at least one of the starting and ending points is a detection block consisting of a single detection spot.

[0072] For example, a detection block consisting of addresses 1H and 1I may be divided, and the detection block furthest from the other detection blocks (addresses 1J and 1K) may be determined as the starting point S1. Alternatively, a detection block consisting of addresses 1J and 1K may be divided, and the detection block furthest from the other detection blocks (addresses 1H and 1I) may be determined as the starting point S2. This process can also be applied when determining the endpoints Q1 and Q2 as detection blocks consisting of a single detection spot.

[0073] The movement path determination unit 7 will be explained with reference to Figures 13-17. The movement path determination unit 7 determines the movement path of the detected object X based on the start point S and end point Q of the movement path M recognized by the movement path identification unit 6. As an example, the detection area 70 is divided into multiple sub-areas, and the movement path determination unit 7 determines the movement path pattern of the movement path M from the start sub-area to which the start point S of the movement path M belongs and the end sub-area to which the end point Q belongs. Each movement path pattern is counted individually and cumulatively, and the count (hereinafter referred to as the "number of determinations") is stored in the storage unit 3.

[0074] Figure 13 shows an example of a detection area 70 divided into multiple sections. In the following explanation, the front side of the automatic door device 100 will be referred to as the indoor side, and the rear side of the automatic door device 100 as the outdoor side. In the example in Figure 13, the detection area 70 is divided into sections D1, P1, A1, L1, and R1 from the 1st to the 6th row on the front side (indoor side), and into sections D2, P2, A2, L2, and R2 from the 7th to the 12th row on the rear side (outdoor side). The number of sections can be two or more.

[0075] Area D1 consists of detection spots 71 with addresses 6A to 6L and detection spots 71 with addresses 5D to 5I. Area P1 consists of detection spots 71 with addresses 3D to 4I. Area A1 consists of detection spots 71 with addresses 1D to 2I. Area L1 consists of detection spots 71 with addresses 1C to 5A. Area R1 consists of detection spots 71 with addresses 1L to 5J.

[0076] Area D2 consists of detection spots 71 with addresses 7A-7L and detection spots 71 with addresses 8D-8I. Area P2 consists of detection spots 71 with addresses 9D-10I. Area A2 consists of detection spots 71 with addresses 11D-12I. Area L2 consists of detection spots 71 with addresses 8A-12C. Area R2 consists of detection spots 71 with addresses 8J-12L.

[0077] Figure 14 is a schematic diagram showing a first example of a movement pattern. If the starting point S of movement M belongs to one of the sectioned areas L1, L2, A1, A2, R1, or R2, and the ending point Q belongs to the same sectioned area as the starting point S, the movement pattern determination unit 7 determines that the movement pattern is a U-turn. Figure 14 shows an example of a movement pattern that is determined to be a U-turn.

[0078] Figure 15 is a schematic diagram showing a second example of a movement pattern. The movement pattern determination unit 7 determines the movement pattern to be a cross-section when the starting point S is in sectioned area L1 and the ending point Q is in sectioned area R1, when the starting point S is in sectioned area R1 and the ending point Q is in sectioned area L1, when the starting point S is in sectioned area L2 and the ending point Q is in sectioned area R2, and when the starting point S is in sectioned area R2 and the ending point Q is in sectioned area L2. Figure 15 shows an example of a movement pattern that is determined to be a cross-section.

[0079] Figure 16 is a schematic diagram showing a third example of a movement pattern. If the starting point S of movement M belongs to one of the sectioned areas L1, L2, R1, or R2, and the ending point Q belongs to one of the sectioned areas A1 or A2, the movement pattern determination unit 7 determines that the movement pattern is a 90° turn. Similarly, if the starting point S of movement M belongs to one of the sectioned areas A1 or A2, and the ending point Q belongs to one of the sectioned areas L1, L2, R1, or R2, the movement pattern determination unit 7 also determines that the movement pattern is a 90° turn. Figure 16 shows an example of a movement pattern that is determined to be a 90° turn.

[0080] Figure 17 is a schematic diagram showing a fourth example of a movement pattern. If the starting point S of movement M belongs to one of the indoor partitioned areas L1, A1, or R1, and the ending point Q belongs to one of the outdoor partitioned areas L2, A2, or R2, the movement pattern determination unit 7 determines that the movement pattern is an exit. If the starting point S of movement M belongs to one of the outdoor partitioned areas L2, A2, or R2, and the ending point Q belongs to one of the indoor partitioned areas L1, A1, or R1, the movement pattern determination unit 7 determines that the movement pattern is an entry. Figure 17 shows an example of a movement pattern that is determined to be either an exit or an entry.

[0081] The memory unit 3 stores the cumulative number of decisions made for each movement pattern. The administrator of the automatic door device 100 can arbitrarily retrieve the cumulative number of decisions for each movement pattern from the memory unit 3. The memory unit 3 resets each cumulative number of decisions when a predetermined timing is reached or when the administrator of the automatic door device 100 performs a predetermined operation.

[0082] Next, we will explain the patterns of movement into and out of the room. In the case of exiting, if the starting point S belongs to area L1, the exit is from the left; if the starting point S belongs to area R1, the exit is from the right; and if the starting point S belongs to area A1, the exit is from the front. Thus, the patterns of movement into the room can be categorized. Similarly, in the case of entering, if the ending point Q belongs to area L1, the entry is made to the left; if the ending point Q belongs to area R1, the entry is made to the right; and if the ending point Q belongs to area A1, the entry is made to the front. Thus, the patterns of movement into the room can be categorized.

[0083] Furthermore, in the case of entry, the entry route can be categorized as follows: if the starting point S belongs to area L2, entry is from the left; if the starting point S belongs to area R2, entry is from the right; and if the starting point S belongs to area A2, entry is from the front. Similarly, in the case of exit, the exit route can be categorized as follows: if the ending point Q belongs to area L2, exit to the left; if the ending point Q belongs to area R2, exit to the right; and if the ending point Q belongs to area A2, exit straight ahead.

[0084] Thus, according to this embodiment, the combination of the starting point S and ending point Q of the movement path M makes it possible to grasp the detailed movement patterns for entering and exiting the room. The memory unit 3 stores the cumulative number of decisions made for the grasped movement patterns. The administrator of the automatic door device 100 can arbitrarily obtain the cumulative number of decisions for the detailed movement patterns for entering and exiting the room from the memory unit 3. The memory unit 3 resets the cumulative number of decisions for entering and exiting the room when a predetermined timing is reached or when the administrator of the automatic door device 100 performs a predetermined operation.

[0085] The aforementioned movement path identification device 50 can be configured to include an activation sensor 4 and an information processing unit 20. In the movement path identification device 50, the activation sensor 4 functions as a detection unit that detects a target object in a detection area having a plurality of detection spots provided around an opening.

[0086] Referring to Figures 6 and 18, an example of the operation process of the automatic door device 100 of this embodiment will be described. This description will show the operation along the trajectory 73 in Figure 6. Figure 18 is a flowchart of process S110 of the automatic door device 100.

[0087] When process S110 starts, the specific unit 5 determines whether the activation sensor 4 has changed from a non-detection state to a detection state (step S111). If the activation sensor 4 remains in a non-detection state and does not change (N in step S111), the process returns to the beginning of step S111 and repeats step S111.

[0088] When the activation sensor 4 changes to a detection state (Y in step S111), the memory unit 3 stores information regarding the progression of the trajectory 73 (step S112).

[0089] After step S112 is executed, the identification unit 5 determines whether the activation sensor 4 has changed from a detected state to a non-detected state (step S113). If the activation sensor 4 remains in the detected state and does not change (N in step S113), the process returns to the beginning of step S112 and repeats steps S112 and S113.

[0090] When the activation sensor 4 changes to a non-detection state (Y in step S113), the process analyzes the transition information to determine whether the trajectory 73 includes a branch (step S114). In this step, the process can determine that the trajectory 73 has branched if the detection block 72 splits into multiple detection blocks 72 that are separated by a threshold. In this case, the threshold is the distance corresponding to the width of a single detection spot 71. In other words, the trajectory 73 can be determined to have branched if an detected detection spot 71 is interposed between multiple detection blocks 72.

[0091] If the trajectory 73 does not include a branch (N in step S114), the identification unit 5 determines that the detection target is singular (step S115) and identifies the singular trajectory 73 (step S116). Once step S116 is executed, the process proceeds to step S120.

[0092] If the trajectory 73 includes a branch (Y in step S114), the identification unit 5 determines that there are multiple detection targets (step S117), identifies multiple trajectories before and after the branch (step S118), and connects the trajectories before and after the branch based on predetermined conditions (step S119).

[0093] Once step S119 is executed, the identification unit 5 identifies the start and end points of the detection block's trajectory (step S120). In this step, the identification unit 5 can identify the detection block that first detected the target (hereinafter referred to as the "first detection area") as the start point of the trajectory, and the detection block that last detected the target (hereinafter referred to as the "last detection area") as the end point of the trajectory. If a single trajectory 73 is identified, the identification unit 5 identifies a single start point S and an end point Q. If multiple trajectories 77 and 78 are identified, the identification unit 5 identifies multiple start points S1 and S2 and end points Q1 and Q2.

[0094] Once step S120 is performed, the movement path identification unit 6 identifies the movement path to be detected based on the start and end points of the trajectory (step S121). If a single trajectory 73 is identified, the movement path identification unit 6 identifies the movement path M connecting the start point S and the end point Q. If multiple trajectories 77, 78 are identified, the movement path identification unit 6 identifies the movement path M1 connecting the start point S1 and the end point Q1, and the movement path M2 connecting the start point S2 and the end point Q2.

[0095] Once step S121 is performed, the movement path determination unit 7 determines the movement path to be detected based on the identified movement path (step S122). In this step, the movement path determination unit 7 determines the movement path patterns of movement path M, movement path M1, and movement path M2.

[0096] Once step S122 is executed, the memory unit 3 cumulatively stores the number of times the movement path determination unit 7 has made a determination for each movement path pattern (step S123). After step S123 is executed, the process returns to the beginning of step S111 and repeats the loop of steps S111 to S123. The steps described above are merely examples, and various modifications are possible.

[0097] The above is a description of the first embodiment.

[0098] The second and third embodiments of the present invention will be described below. In the drawings and descriptions of the second and third embodiments, the same or equivalent components and members as those in the first embodiment will be denoted by the same reference numerals. Descriptions that overlap with those of the first embodiment will be omitted as appropriate, and the descriptions will focus on the configurations that differ from those of the first embodiment.

[0099] [Second Embodiment] A second embodiment of the present invention is a method for identifying movement paths using an automatic door. This method includes a detection step (S111) of detecting a detection target, which is a person or object in the vicinity of an opening, in a detection area 70 provided around the opening 23; a step (S116, S118) of identifying the location of the detection target detected in the detection step; a step (S112) of storing transition information regarding the change in location; and a step of identifying the movement path of the detection target based on the transition information, wherein when multiple trajectories of multiple detection targets diverge from a merging state, the step (S120, S121) of associating the multiple trajectories based on the transition information to identify the movement paths of multiple detection targets.

[0100] According to the second embodiment, the same functions and effects as the first embodiment are achieved.

[0101] [Third Embodiment] A third embodiment of the present invention is a movement path identification program P100 (computer program) using an automatic door. This program P100 causes a computer to execute the following steps: a detection step (S111) in which a detection target, which is a person or object in the vicinity of an opening, is detected in a detection area 70 provided around the opening 23; a step (S116, S118) to identify the position of the detection target detected in the detection step; a step (S112) to store transition information regarding the change in position; and a step (S120, S121) to identify the movement path of the detection target based on the transition information, wherein when multiple trajectories of multiple detection targets diverge from a merging state, the program causes a computer to execute the following steps:

[0102] These functions of program P100 may be installed in the storage (e.g., memory unit 3) of the automatic door sensor 10 as an application program that implements multiple modules corresponding to the functional blocks of the automatic door sensor 10. Program P100 may be read into the main memory of the processor (e.g., CPU) of a computer built into the automatic door sensor 10 and executed.

[0103] According to the third embodiment, the same actions and effects as the first embodiment are achieved.

[0104] The embodiments of the present invention have been described in detail above. The embodiments described above are merely examples of how to implement the present invention. The contents of the embodiments do not limit the technical scope of the present invention, and many design changes, such as changes, additions, and deletions of components, are possible as long as they do not depart from the spirit of the invention as defined in the claims. In the embodiments described above, the contents in which such design changes are possible are described with notations such as "of the embodiments" or "in the embodiments," but this does not mean that design changes are not permitted in contents without such notations.

[0105] [Differentiation] The following describes modified examples. In the drawings and descriptions of the modified examples, the same reference numerals are used for components and members that are identical or equivalent to those in the embodiments. Descriptions that overlap with those in the embodiments will be omitted as appropriate, and the descriptions will focus on the configurations that differ from those in the embodiments.

[0106] In the description of the embodiment, an example was shown in which the detection area 70 has detection spots 71 set on the front and rear sides of the opening 23, but the detection area 70 may have only detection spots 71 set on one side of the opening 23.

[0107] In the description of the embodiment, an example was shown in which both of the multiple detection units 41 and 42 are provided on the transom 16. However, some or all of the multiple detection units 41 and 42 may be provided on surfaces other than the transom 16, such as walls or ceilings.

[0108] In the description of the embodiment, an example was shown in which the activation sensor 4 detects detection spots 71 set on the front and rear sides of the opening 23 using multiple detection units 41 and 42. However, the activation sensor 4 may also be configured to detect the detection spots 71 set on the front and rear sides of the opening 23 using a single detection unit.

[0109] In the description of the embodiment, an example was shown in which the detection area 70 is provided for a single opening 23, but the detection area 70 may be provided for multiple openings 23. For example, part or all of the detection area 70 may be provided between multiple openings 23, each of which is equipped with an automatic door.

[0110] In the description of the embodiment, an example was shown in which the integration unit 43 is provided on the activation sensor 4, but the invention is not limited to this. For example, the integration unit 43 may be provided on the information processing unit 20.

[0111] In the description of the embodiment, an example of the division area of ​​the detection area 70 is shown in Figure 13, but the division area of ​​the detection area is not limited to this and can be modified in various ways.

[0112] In the description of the embodiment, an example was shown in which the movement path identification unit 6 recognizes a movement path from a trajectory where the number of endpoints Q or starting points S is 2, but it is not limited to this. The movement path identification unit 6 may be configured to recognize movement paths from trajectories where the number of endpoints Q is 3 or more, or trajectories where the number of starting points S is 3 or more.

[0113] In the description of the embodiment, an example was shown in which the memory unit 3 is provided in the automatic door sensor 10, but the invention is not limited to this. The memory unit may be provided in the automatic door drive device or outside the automatic door device.

[0114] In the description of the embodiment, an example was shown where the activation sensor 4 is an infrared reflection type sensor, but it is not limited to this. For example, the activation sensor may be a radio wave type sensor, an ultrasonic type sensor, a laser scanning type sensor, or an image type sensor.

[0115] In the description of the embodiment, an example was shown in which all detection spots 71 in the detection area 70 are activation spots that generate an activation signal to open and close the door 9 when an object is detected, but the invention is not limited to this. Some of the detection spots 71 in the detection area 70 may be set as inactive spots that do not generate an activation signal.

[0116] In the description of the embodiment, an example was shown in which the specific unit 5 is mounted on the automatic door sensor 10, but the invention is not limited to this. The specific unit may be mounted on the automatic door drive device or provided on the outside of the automatic door device.

[0117] In the description of the embodiment, examples of movement patterns determined by the movement pattern determination unit 7 are shown in Figures 14 to 17. However, the movement pattern determination unit 7 may be configured to determine movement patterns different from those shown in Figures 14 to 17.

[0118] In the description of the embodiments, an example was shown in which the transmission line 96 includes an internal bus, but the invention is not limited thereto. Known wired or wireless means of information transmission can be used as the transmission line.

[0119] In the description of the embodiment, an example was shown in which detection information from the auxiliary photoelectric sensor 30 is transmitted to the control unit 91 via the information processing unit 20, but the embodiment is not limited to this. The detection information from the auxiliary photoelectric sensor may be transmitted directly to the control unit 91, or it may be transmitted to the control unit 91 via other routes.

[0120] The modifications described above produce the same functions and effects as each embodiment.

[0121] Any combination of the embodiments and modifications described above is also useful as an embodiment of the present invention. The new embodiments resulting from these combinations possess the combined effects of the respective embodiments and modifications. [Explanation of symbols]

[0122] 3 Memory unit, 4 Activation sensor, 5 Identification unit, 6 Movement path identification unit, 7 Movement path determination unit, 10 Sensor for automatic door, 23 Opening, 41 First detection unit, 42 Second detection unit, 50 Movement path identification device, 71 Detection spot, 72 Detection block, 73 Trajectory, 100 Automatic door device.

Claims

1. A start sensor that detects a person or object, which is the target of detection, in the vicinity of the opening within the detection area, A unit for identifying the location of the object detected by the aforementioned activation sensor, A storage unit that stores transition information regarding the transition of the aforementioned position, A movement path identification unit identifies the movement path of the target based on the aforementioned transition information, Equipped with, The aforementioned movement path identification unit identifies the movement paths of the multiple detection targets by relating them when multiple trajectories of multiple detection targets based on the transition information diverge from a merging state, estimating the relationship between the multiple trajectories before and after the divergence based on the transition information, and virtually connecting those with relatively high relationships based on the estimation results.

2. The movement path identification unit uses the movement speed of each of the multiple detection targets before and after the branching point in the estimation. The automatic door device according to claim 1.

3. The aforementioned movement path identification unit uses the positional relationship of each of the multiple detection targets before and after the branching in the estimation. The automatic door device according to claim 1.

4. The aforementioned detection area has multiple detection spots, The identification unit identifies the trajectory of a detection block consisting of one or more detection spots in a detected state from among the plurality of detection spots as the trajectory of the object to be detected. The movement path identification unit determines that the multiple trajectories are in a convergence state when the distance between the multiple trajectories is less than a threshold. The automatic door device according to any one of claims 1 to 3.

5. The movement path identification unit identifies the movement paths of the plurality of detection targets based on the start and end points of the plurality of trajectories in the detection area. The automatic door device according to claim 4.

6. A detection unit that detects a person or object in the vicinity of an opening within a detection area provided around the opening, A unit for identifying the location of the object detected by the detection unit, A storage unit that stores transition information regarding the aforementioned position, A movement path identification unit identifies the movement path of the target based on the aforementioned transition information, Equipped with, The aforementioned movement path identification unit identifies the movement paths of the multiple detection targets by relating them when multiple trajectories of multiple detection targets based on the transition information diverge from a merging state, estimating the relationship between the multiple trajectories before and after the divergence based on the transition information, and virtually connecting those with relatively high relationships based on the estimation results.

7. A detection unit that detects a person or object in the vicinity of an opening within a detection area provided around the opening, A unit for identifying the location of the object detected by the detection unit, A storage unit that stores transition information regarding the aforementioned position, A movement path identification unit identifies the movement path of the target based on the aforementioned transition information, Equipped with, The movement path identification unit identifies the movement paths of the multiple detection targets by relating the multiple trajectories before and after branching when multiple trajectories of multiple detection targets based on the transition information branch off from a merging state, estimating the relationship between the multiple trajectories before and after branching based on the transition information, and virtually connecting those with relatively high relationships based on the estimation results.

8. A detection step in which a computer detects a person or object in the vicinity of an opening in a detection area provided around the opening, The computer then performs the step of identifying the location of the object detected in the detection step, The computer stores information relating to the change in position, The computer identifies the movement path of a target to be detected based on the transition information, and when multiple trajectories of multiple targets to be detected diverge from a merging state, it estimates the relationship between the multiple trajectories before and after the divergence based on the transition information, and identifies the movement path of the multiple targets by relating the multiple trajectories before and after the divergence by combining those with relatively high relationships based on the estimation results, A method for identifying movement patterns, including the method described above.

9. A detection step in which a detection target, which is a person or object in the vicinity of the opening, is detected in a detection area provided around the opening, The step of identifying the location of the object detected in the above detection step, A step of storing transition information regarding the change in the aforementioned position, A step of identifying the movement path of a target to be detected based on the transition information, wherein when multiple trajectories of multiple targets to be detected diverge from a merging state, the relationship between the multiple trajectories before and after the divergence is estimated based on the transition information, and the multiple trajectories before and after the divergence are associated by combining those with relatively high relationships based on the estimation results and virtually connecting them, thereby identifying the movement path of the multiple targets to be detected. A movement path identification program that is executed by a computer.

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