Elevator system

Abstract

To provide an elevator system that can prevent users from being pulled into it. [Solution] An elevator system according to one embodiment includes: a camera for photographing users inside the elevator car; setting means for setting a plurality of detection areas on the captured image for detecting users near the elevator car door; detection means for detecting users from the plurality of detection areas; identification means for identifying an entrapment risk value indicating the risk of the user being pulled into the elevator car door when a user is detected by the detection means; determination means for comparing the identified entrapment risk value with a risk threshold value set in advance for the detection area where the user detected by the detection means is located, and determining whether or not there is a risk of the user being pulled into the elevator car door; and control means for announcing to the user inside the elevator car that there is a risk of entrapment when the determination means determines that there is a risk of entrapment.

Description

Technical Field

[0004]

[0001] Embodiments of the present invention relate to an elevator system.

Background Art

[0002] When the door of an elevator car opens, a user's finger or the like inside the car may be drawn into the door pocket. To prevent such accidents, various technologies have been devised, but the realization of a technology that can more accurately prevent the user from being drawn in is desired.

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Patent Document 2

Patent Document 3

Summary of the Invention

Problems to be Solved by the Invention

[0004] The problem to be solved by the present invention is to provide an elevator system capable of preventing a user from being drawn in.

Means for Solving the Problems

[0006] [Figure 1] Figure 1 is a diagram showing a schematic configuration example of an elevator system according to one embodiment. [Figure 2] Figure 2 illustrates an example of a detection area set when the cage door uses a two-door single-leaf opening mechanism. [Figure 3] Figure 3 illustrates another example of the detection area set when the cage door opening and closing mechanism is a two-door single-leaf system. [Figure 4] Figure 4 illustrates an example of a detection area set when the cage door opening and closing mechanism is a central double-opening type. [Figure 5] Figure 5 is a flowchart showing an example of the procedure for setting the detection area according to the same embodiment. [Figure 6] Figure 6 is a diagram illustrating the orientation of the user's body and the position of their hands relative to the car door, as detected by the user detection unit according to the same embodiment. [Figure 7] Figure 7 shows an example of a risk value table according to the same embodiment. [Figure 8]Figure 8 shows another example of a risk value table according to the same embodiment. [Figure 9] Figure 9 is a flowchart showing an example of the procedure for determining the risk of being drawn into a system according to the same embodiment. [Figure 10] Figure 10 is a diagram illustrating the pull-in risk determination process according to the same embodiment. [Figure 11] Figure 11 is another diagram illustrating the entrapment risk determination process according to the same embodiment. [Modes for carrying out the invention]

[0007] The embodiments will be described below with reference to the drawings. It should be noted that the disclosure is merely an example, and the invention is not limited by the contents described in the embodiments below. Modifications that a person skilled in the art can easily conceive are naturally included within the scope of the disclosure. In order to make the explanation clearer, the size, shape, etc. of each part may be schematically represented in the drawings with modifications from the actual embodiments. In some cases, the same reference numerals are used for corresponding elements in multiple drawings, and detailed explanations are omitted.

[0008] Figure 1 shows a schematic example of an elevator system according to one embodiment. While this explanation uses a single elevator car as an example, the configuration is similar for multiple elevator cars.

[0009] The elevator system according to this embodiment has a function to detect a user near the car door inside the elevator car, determine whether there is a risk of the detected user's fingers or hands being pulled into the door pocket (i.e., determine whether there is a risk of an accident occurring), and, if it is determined that there is a risk of an accident occurring, to alert the user inside the elevator car.

[0010] A camera 12 is installed above the entrance and exit of the car 11. Specifically, the camera 12 is installed with its lens part facing downward, or toward the landing side or the car side, inside a curtain board 11a that covers the upper part of the entrance and exit of the car 11. The camera 12 has, for example, a wide-angle lens or a fisheye lens, and continuously captures images at several frames per second (for example, 30 frames / second). The shooting range of the camera 12 only needs to include at least the vicinity of the car door 13. Note that the installation location of the camera 12 may not be above the entrance and exit of the car 11 as long as it is near the car door 13.

[0011] At each floor landing 15, a landing door 14 is installed at the arrival opening of the car 11. The landing door 14 engages with the car door 13 and opens and closes when the car 11 arrives. Note that the power source (door motor) is on the car 11 side, and the landing door 14 only follows the car door 13 to open and close.

[0012] Each image (video) continuously captured by the camera 12 is analyzed and processed in real time by an image processing device 20. Note that in FIG. 1, for the sake of convenience, the image processing device 20 is taken out of the car 11 and shown, but actually, the image processing device 20 is housed together with the camera 12 inside the curtain board 11a.

[0013] The image processing device 20 includes a storage unit 21 and a control unit 22. The storage unit 21 consists of a memory device such as a RAM. The storage unit 21 sequentially stores the images captured by the camera 12. Note that the storage unit 21 has a buffer area for temporarily storing data necessary for the processing of the control unit 22. In the storage unit 21, images subjected to processing such as distortion correction, enlargement / reduction, and partial cutting may be stored as preprocessing for the images captured by the camera 12. The storage unit 21 further stores a risk value table described later.

[0014] The control unit 22 uses the image captured by the camera 12 to detect a user near the cage door 13, determines whether there is a risk that the detected user will be drawn into the cage door 13, and if it is determined that there is a risk of being drawn in, performs various controls to realize a function of alerting the users inside the car 11.

[0015] The control unit 22 includes a detection area setting unit 23, a user detection unit 24, a drawn-in risk value specifying unit 25, a drawn-in risk determination unit 26, and a communication unit 27.

[0016] The detection area setting unit 23 sets a detection area for detecting a user near the cage door 13 on the image captured by the camera 12. In the present embodiment, a plurality of types of detection areas with different risk thresholds described later are set according to the risk of being drawn into the cage door 13. Note that the detection area setting unit 23 sets a plurality of types of detection areas at different positions for each door opening / closing method (door type) of the cage door 13.

[0017] FIG. 2 is a diagram for explaining the detection area set when the door opening / closing method of the cage door 13 is the double-leaf single-opening method.

[0018] The detection area setting unit 23 sets a high-risk detection area E1, a medium-risk detection area E2, and a low-risk detection area E3 near the cage door 13 as areas where there is a risk (drawn-in risk) of a drawn-in accident occurring.

[0019] The high-risk detection area E1 is an area with the highest risk of being drawn in, and is an area where the lowest risk threshold (first risk threshold) is set as the risk threshold described later.

[0020] If the cage door 13 uses a two-door single-leaf opening mechanism, it is expected that entrapment accidents will occur at point P1, which corresponds to the door pocket (or near the door pocket), and at point P2, which corresponds to the overlapping portion of the two doors. For this reason, the detection area setting unit 23 sets the area around points P1 and P2, where entrapment accidents are expected to occur, as a high-risk detection area E1. Specifically, the detection area setting unit 23 sets two areas extending in all directions from points P1 and P2, where entrapment accidents are expected to occur, by, for example, L1 (for example, 10 cm) each (that is, a square area with sides of length 2 × L1 centered on points P1 and P2), as high-risk detection areas E1a and E1b. Hereafter, the point where entrapment accidents are expected to occur (a position where entrapment is likely to occur) will be referred to as the "entrapment point." Also, although the case where L1 is 10 cm is given as an example here, the value of L1 is not limited to this and can be set to any value.

[0021] Medium-risk detection area E2 is an area with a lower risk of being drawn in than high-risk detection area E1, and is an area where a higher risk threshold (second risk threshold) is set than the first risk threshold set for high-risk detection area E1, as described later.

[0022] The detection area setting unit 23 sets the area extending L2 (for example, 30 cm) horizontally from the door-side end e1 of the high-risk detection area E1a set near the entry point P1, and the area extending L2 horizontally from the door-side end e2 of the high-risk detection area E1b set near the entry point P2, as medium-risk detection areas E2a and E2b. Here, L2 is given as an example of 30 cm, but the value of L2 is not limited to this and can be set to any value.

[0023] Low-risk detection area E3 is an area with a lower risk of being drawn in than medium-risk detection area E2, and is an area where a higher risk threshold (third risk threshold) is set than the second risk threshold set for medium-risk detection area E2, as described later.

[0024] The detection area setting unit 23 sets a low-risk detection area E3 around the high-risk detection area E1 and the medium-risk detection area E2, within a distance L3 (for example, 10 cm). Note that the low-risk detection area set around the high-risk detection area E1a and the medium-risk detection area E2a, and the low-risk detection area set around the high-risk detection area E1b and the medium-risk detection area E2b, partially overlap and become one. Therefore, although it is shown as one low-risk detection area E3 in Figure 2 for convenience, in reality, two low-risk detection areas are set. Also, although the case where L3 is 10 cm is given as an example here, the value of L3 is not limited to this and can be set to any value.

[0025] Here, we have shown the case where the detection area shown in Figure 2 is set when the door opening and closing method of the cage door 13 is a two-panel single-leaf system, but it is not limited to this, and when the door opening and closing method of the cage door 13 is a two-panel single-leaf system, for example the detection area shown in Figure 3 may be set. The detection area shown in Figure 3 differs from the detection area shown in Figure 2 in that the range on the cage side of the high-risk detection area E1b set near the retraction point P2 is extended to the same range on the cage side of the high-risk detection area E1a set near the retraction point P1, and extends L1 toward the door pocket side (in other words, the high-risk detection area E1b is set to be in contact with both the medium-risk detection areas E2a and E2b). Accordingly, the medium-risk detection area E2b, which extends L2 in the horizontal direction of the door from the door stop side end e2 of the high-risk detection area E1b, also differs from the detection area shown in Figure 2 in that the range on the cage side is similarly extended.

[0026] Figure 4 is a diagram illustrating the detection area set when the door opening and closing method of the cage door 13 is a central double-opening method.

[0027] If the cage door 13 uses a central double-opening method, it is expected that entrapment accidents will occur at entrapment points P3 and P4, which correspond to the door pockets (or near the door pockets) on both the left and right sides. For this reason, the detection area setting unit 23 sets the area around entrapment points P3 and P4 as a high-risk detection area E1. Specifically, the detection area setting unit 23 sets two areas extending in all four directions from entrapment points P3 and P4 by, for example, L1 (for example, 10 cm) each (that is, a square area with sides of length 2 × L1 centered on points P3 and P4) as high-risk detection areas E1a and E1b.

[0028] Furthermore, the detection area setting unit 23 sets the area extending L2 (for example, 30 cm) horizontally from the center end e1 of the high-risk detection area E1a set near the entry point P3 towards the door, and the area extending L2 horizontally from the center end e2 of the high-risk detection area E1b set near the entry point P4 towards the door, as medium-risk detection areas E2a and E2b.

[0029] Furthermore, the detection area setting unit 23 sets a low-risk detection area E3a around the high-risk detection area E1a and the medium-risk detection area E2a at a distance of L3 (for example, 10 cm), and sets a low-risk detection area E3b around the high-risk detection area E1b and the medium-risk detection area E2b at a distance of L3.

[0030] In the case of Figure 4, L1, L2, and L3 are not limited to the example values, but can be set to any values.

[0031] Furthermore, while Figures 2 to 4 show the positions of each detection area E1, E2, and E3 before the doors are opened (while all doors are closed), the positions of each detection area E1, E2, and E3 may be set to move as the doors open.

[0032] For example, if the door opening and closing mechanism of the cage door 13 is a two-door single-opening type, the position of the high-risk detection area E1b shown in Figure 2 may be moved in the direction of the door pocket as the door opens, while maintaining the same size as the area, and the positions of the medium-risk detection areas E2a, E2b and the low-risk detection area E3 may be moved in the direction of the door pocket as the door opens, while gradually decreasing the size of each area E2a, E2b, and E3.

[0033] Furthermore, if the door opening and closing method of the cage door 13 is a central double-opening method, the positions of the medium-risk detection area E2a and low-risk detection area E3a shown in Figure 4 may be moved towards the door pocket on the left side of the figure as the door opens, while gradually decreasing the size of each area E2a and E3a, and the positions of the medium-risk detection area E2b and low-risk detection area E3b may be moved towards the door pocket on the right side of the figure as the door opens, while gradually decreasing the size of each area E2b and E3b.

[0034] Furthermore, the detection area setting unit 23 may set multiple detection areas with different risk thresholds, rather than setting a detection area according to the door opening and closing method of the cage door 13, depending on the distance from the entry point. For example, the detection area setting unit 23 may set multiple detection areas that are concentric circles around the entry point, each with different risk thresholds. In this case, the risk threshold set for each of the multiple detection areas will be lower for detection areas closer to the entry point and higher for detection areas further from the entry point. Here, as an example, the case where multiple detection areas are set in a concentric circle is shown, but the multiple detection areas can be set in any shape as long as they gradually expand from the entry point.

[0035] Furthermore, the detection area setting unit 23 may set multiple detection areas with different risk thresholds depending on the distance from the entry point in the horizontal direction of the door. For example, the detection area setting unit 23 may set multiple detection areas that are aligned horizontally from the entry point to the door, and each detection area has a different risk threshold. In this case as well, the risk threshold set for each of the multiple detection areas will be lower for detection areas closer to the entry point and higher for detection areas further from the entry point.

[0036] Here, with reference to the flowchart in Figure 5, an example of the procedure for the detection area setting process performed by the detection area setting unit 23 will be described. This process is performed, for example, as part of the initial setup of the image processing device 20.

[0037] First, the detection area setting unit 23 acquires door type information indicating the door opening and closing method of the car door 13 (step S1). Note that the door type information may be acquired from the elevator control device 30 or from a portable terminal (not shown) operated by a maintenance worker.

[0038] Next, the detection area setting unit 23 determines whether the door opening and closing method of the cage door 13, as indicated by the acquired door type information, is a two-door single-opening method or a center double-opening method (step S2).

[0039] When the door opening and closing method of the cage door 13 is a two-door single-leaf system (two-door single-leaf system in step S2), the detection area setting unit 23 detects the retraction point P1 corresponding to the door pocket and the retraction point P2 corresponding to the overlapping portion of the two doors from the captured image (step S3).

[0040] Next, the detection area setting unit 23 sets two areas extending L1 in all directions from the two pull-in points P1 and P2 detected in step S3 as high-risk detection area E1 on the captured image (step S4).

[0041] Next, the detection area setting unit 23 sets the area extending L2 horizontally from the door-side end of the high-risk detection area E1 set near the entry point P1, and the area extending L2 horizontally from the door-side end of the high-risk detection area E1 set near the entry point P2, as the medium-risk detection area E2 on the captured image (step S5).

[0042] Subsequently, the detection area setting unit 23 sets two areas L3 surrounding the two high-risk detection areas and two medium-risk detection areas set on the captured image as a low-risk detection area E3 on the captured image (step S6), and the detection area setting unit 23 completes the series of detection area setting processes.

[0043] On the other hand, if the door opening and closing method of the cage door 13 is a central double-opening method (central double-opening method in step S2), the detection area setting unit 23 detects the retraction point P3 corresponding to the door pocket of the left cage door 13 and the retraction point P4 corresponding to the door pocket of the right cage door 13 from the captured image (step S7).

[0044] Next, the detection area setting unit 23 sets two areas extending L1 in all directions from the two pull-in points P3 and P4 detected in step S7 as high-risk detection areas E1 on the captured image (step S8).

[0045] Next, the detection area setting unit 23 sets the area extending L2 horizontally from the center end of the high-risk detection area E1 set near the entry point P3 towards the door, and the area extending L2 horizontally from the center end of the high-risk detection area E1 set near the entry point P4 towards the door, as the medium-risk detection area E2 on the captured image (step S9).

[0046] Subsequently, the detection area setting unit 23 sets two areas L3 surrounding the two high-risk detection areas and two medium-risk detection areas set on the captured image as a low-risk detection area E3 on the captured image (step S10), and the detection area setting unit 23 completes the series of detection area setting processes.

[0047] According to the series of detection area setting processes described above, each detection area E1 to E3 can be set to an appropriate position according to the door opening and closing method of the cage door 13.

[0048] Let's return to the explanation of Figure 1. The user detection unit 24 uses images captured by the camera 12 to detect users near the elevator car door 13. Specifically, the user detection unit 24 divides the images captured by the camera 12 into numerous blocks, and performs motion detection processing to detect moving blocks (motion blocks) from among the blocks by focusing on changes in color information (for example, changes in brightness values) in each block included in the detection area. According to this motion detection processing, users appearing in the image are detected as a collection of motion blocks.

[0049] Furthermore, the user detection unit 24 may detect users not by the motion detection process described above, but by, for example, SSD (Single Shot Multibox Detector), which is one of the image recognition methods using supervised learning. In this case, the user detection unit 24 can efficiently detect users near the elevator car door 13, including their location, from newly captured images by pre-training images of users near the elevator car door 13 as training data.

[0050] Furthermore, if a user is detected near the elevator car door 13, the user detection unit 24 performs a process to detect the user's attributes (characteristics), the orientation of the user's body relative to the elevator car door 13 (more specifically, the pull-in point), and the position of their hands.

[0051] Examples of user demographics include adults, children, infants, the elderly, and intoxicated individuals.

[0052] Furthermore, the orientation of the user's body relative to the cage door 13 can include, for example, facing forward, to the side, or facing backward.

[0053] Furthermore, the position of the user's hand relative to the cage door 13 is the hand position x, assuming that the pull-in point (closest to the user) is 0°, as shown in Figure 6, for example, and indicates the hand position closer to the cage door 13.

[0054] For example, Figure 6(a) shows the case where the user's body is facing "side" to the car door 13 (retraction point) and the position x of the user's hand (in this case, the position of the right hand) relative to the car door 13 (retraction point) is "x=0°". Also, Figure 6(b) shows the case where the user's body is facing "front" to the car door 13 (retraction point) and the position x of the user's hand (in this case, the positions of both the right and left hands) relative to the car door 13 (retraction point) is "x=90°".

[0055] The user detection unit 24 may detect the user's attributes, the orientation of the user's body relative to the elevator car door 13, and the position of the user's hands relative to the elevator car door 13 simply by image recognition, or it may detect the skeleton of a user near the elevator car door 13 using a known keypoint technique such as Open Pose, and then detect the user's attributes, the orientation of the user's body relative to the elevator car door 13, and the position of the user's hands relative to the elevator car door 13.

[0056] When the user detection unit 24 detects a user near the elevator car door 13, the entrapment risk value identification unit 25 identifies the entrapment risk value based on the user's attributes, body orientation, and hand position. More specifically, the entrapment risk value identification unit 25 refers to a risk value table corresponding to the detected user's attributes from a risk value table pre-stored in the storage unit 21, and identifies the entrapment risk value corresponding to the user's body orientation and hand position.

[0057] Here, we will explain the risk value tables that are pre-stored in the memory unit 21. The memory unit 21 has a risk value table prepared for each user attribute pre-stored in it. Figure 7 shows an example of risk value table t1 indicating that the user attribute is "adult". Figure 8 shows an example of risk value table t2 indicating that the user attribute is "child". Note that the various draw-in risk values ​​defined in the risk value tables t1 and t2 shown in Figures 7 and 8 are just examples and are not limited to these values.

[0058] The entrapment risk value is a value that indicates the risk (danger) of an entrapment accident occurring, and the higher the value, the higher the risk of an entrapment accident occurring.

[0059] The entrapment risk value is set according to whether or not the user can judge for themselves whether or not there is a risk of an entrapment accident, from the perspective of the user's attributes. Specifically, the entrapment risk value is set higher for attributes that are expected to be unable to judge for themselves whether or not there is a risk of an entrapment accident. For this reason, the entrapment risk values ​​defined in risk value table t2, where the user's attribute is "child" as shown in Figure 8, are generally set higher than the entrapment risk values ​​defined in risk value table t1, where the user's attribute is "adult" as shown in Figure 7.

[0060] The risk value table specifies the risk of being pulled in, depending on the orientation of the user's body relative to the elevator car door 13 and the position of the user's hands relative to the elevator car door 13. The risk of being pulled in is set according to the orientation of the user's body relative to the car door 13, depending on whether or not they are looking at the car door 13. The more the user's body orientation is expected to be such that they are not looking at the car door 13, the higher the risk of being pulled in is set.

[0061] For example, it is desirable that the entrapment risk value corresponding to a body orientation "backward" relative to the car door 13 be set to a value greater than or equal to the entrapment risk value corresponding to a body orientation "front" or "side" relative to the car door 13. Similarly, it is desirable that the entrapment risk value corresponding to a body orientation "side" relative to the car door 13 be set to a value greater than or equal to the entrapment risk value corresponding to a body orientation "front" relative to the car door 13.

[0062] The risk of being pulled in is set higher the closer the user's hand is to the car door 13, from the perspective of the user's hand position relative to the car door 13.

[0063] For example, the entrapment risk value corresponding to the user's hand position x relative to the car door 13 being "45°≦x<0°" should preferably be set to a value greater than or equal to the entrapment risk value corresponding to the user's hand position x relative to the car door 13 being "90°≦x<45°", "135°≦x<90°", or "180°≦x<135°". Furthermore, the entrapment risk value corresponding to the user's hand position x relative to the car door 13 being "90°≦x<45°" should preferably be set to a value greater than or equal to the entrapment risk value corresponding to the user's hand position x relative to the car door 13 being "135°≦x<90°" or "180°≦x<135°". In addition, the entrapment risk value corresponding to the user's hand position x relative to the car door 13 being "135°≦x<90°" should preferably be set to a value greater than or equal to the entrapment risk value corresponding to the user's hand position x relative to the car door 13 being "180°≦x<135°".

[0064] However, for the risk of being pulled into the elevator car door 13, which is set in the risk value table t2 indicating that the user's attribute is "child," it is desirable that the risk of being pulled into the elevator car door 13 be set higher when the body is facing "to the side" rather than "facing forward," especially when the hand position x relative to the elevator car door 13 is "45°≦x<0°." This is because, in the case of children, it is assumed that they will approach the elevator car door 13 out of curiosity, and the risk of being pulled into the elevator car door 13 when they are trying to touch it out of curiosity is higher than the risk of being pulled into the elevator car door 13 when they are standing sideways to it and their hands are in a position where they are naturally more likely to be pulled in. This allows for care to be taken even for children who approach the elevator car door 13 out of curiosity, and makes it possible to appropriately determine the risk of being pulled into the elevator car door 13.

[0065] Here, we will explain an example of the process by which the pull-in risk value identification unit 25 identifies the pull-in risk value. For example, if the user detection unit 24 detects an "adult" user whose body is facing "forward" to the car door 13 and whose hands are at a "0°" angle to the car door 13, the entrapment risk value identification unit 25 refers to the risk value table t1 in Figure 7 and identifies the entrapment risk value for that user as "0.9".

[0066] Furthermore, if the user detection unit 24 detects a child user whose body is facing "backward" to the car door 13 and whose hands are positioned at a "90°" angle to the car door 13, the entrapment risk value identification unit 25 refers to the risk value table t2 in Figure 8 and identifies the entrapment risk value for that user as "4.5".

[0067] Let's return to the explanation of Figure 1. The entrapment risk determination unit 26 compares the entrapment risk value of a predetermined user identified by the entrapment risk value identification unit 25 with a pre-set risk threshold for the detection area where the predetermined user was detected, and determines whether the entrapment risk value is equal to or greater than the risk threshold. If the entrapment risk determination unit 26 determines that there is a risk of an entrapment accident occurring (high risk), the entrapment risk determination unit 26 determines that there is no risk of an entrapment accident occurring (low risk), if the entrapment risk value is less than the risk threshold.

[0068] In this embodiment, the entrapment risk determination unit 26 determines that there is a risk of an entrapment accident occurring when the entrapment risk value is equal to or greater than the risk threshold, and determines that there is no risk of an entrapment accident occurring when the entrapment risk value is less than the risk threshold. However, it is not limited to this, and the entrapment risk determination unit 26 may also determine that there is a risk of an entrapment accident occurring when the entrapment risk value is greater than the risk threshold, and determine that there is no risk of an entrapment accident occurring when the entrapment risk value is equal to or less than the risk threshold.

[0069] The communication unit 27 acquires door information from the elevator control device 30 indicating the current open / closed state of the car door 13. Furthermore, if the entrapment risk determination unit 26 determines that there is a risk of an entrapment accident, the communication unit 27 outputs a request signal to the elevator control device 30 corresponding to the current open / closed state of the car door 13.

[0070] Specifically, if the current door opening status of the car door 13 is in the open position, the communication unit 27 outputs a first request signal to the elevator control device 30 to slow down the door opening speed of the car door 13, and a second request signal to announce to users inside the car 11 that there is a risk of an entrapment accident. If the current door opening status of the car door 13 is not in the open position, the communication unit 27 outputs only the second request signal to the elevator control device 30.

[0071] The elevator control device 30 consists of a computer equipped with a CPU, ROM, RAM, etc. The elevator control device 30 controls the raising and lowering of the elevator car 11 and the operation of various equipment installed inside the elevator car 11. The elevator control device 30 stores door type information indicating the door opening and closing method of the car door 13 installed in the elevator car 11 in a memory (not shown) and outputs this information to the image processing device 20 in response to a request from the image processing device 20.

[0072] The elevator control device 30 includes a door opening / closing control unit 31 and a notification control unit 32. The door opening / closing control unit 31 controls the opening and closing of the car door 13 when the elevator car 11 arrives at the landing 15. Specifically, the door opening / closing control unit 31 opens the car door 13 when the elevator car 11 arrives at the landing 15, and closes it after a predetermined time has elapsed.

[0073] Furthermore, the door opening / closing control unit 31 outputs door information indicating the current door opening / closing status of the car door 13 to the image processing device 20 in response to a request from the image processing device 20. In addition, when the door opening / closing control unit 31 receives the above-mentioned first request signal from the image processing device 20, it controls the door opening speed of the car door 13 to be slower than the current speed.

[0074] The notification control unit 32 broadcasts an announcement inside the elevator car 11 via a speaker (not shown) installed inside the elevator car 11 to notify (warn) that there is a risk of an accident occurring due to being pulled into the elevator. Specifically, when the notification control unit 32 receives the above-mentioned second request signal from the image processing device 20, it broadcasts an announcement inside the elevator car 11 to warn passengers that there is a risk of their hands being caught in the door. For example, the announcement may say, "There is a risk of your hands being caught in the door. Please move away from the door."

[0075] Next, with reference to the flowchart in Figure 9, an example of the procedure for the entrapment risk determination process performed by the image processing device 20 will be described. This process is performed, for example, while the elevator car 11 is moving from one floor to another, or when the elevator car arrives at the floor in question.

[0076] First, the user detection unit 24 of the image processing device 20 determines whether or not there is a user near the car door 13 based on the image captured by the camera 12 (in other words, it detects the presence or absence of a user near the car door 13) (step S11).

[0077] In the process of step S11, if it is determined that there are no users near the car door 13 (No. in step S11), the communication unit 27 of the image processing device 20 obtains door information indicating the current door open / closed state of the car door 13 from the elevator control device 30 (step S12), and based on the obtained door information, it determines whether the car door 13 is in a fully open state (in other words, whether the door opening operation of the car door 13 has been completed) (step S13).

[0078] In the process of step S13, if it is determined that the cage door 13 is fully open (in other words, the door opening operation of the cage door 13 has been completed) (Yes in step S13), the image processing device 20 terminates the series of entrapment risk determination processes.

[0079] On the other hand, if it is determined in step S13 that the cage door 13 is not fully open (in other words, the door opening operation of the cage door 13 is not completed) (No. in step S13), the image processing device 20 executes the process of step S11 again.

[0080] Here, if it is determined in step S11 that there is a user near the car door 13 (Yes in step S11), the user detection unit 24 selects one of the detected users as the target user and detects the attributes of that target user, as well as the orientation of that target user's body and the position of their hands relative to the car door 13 (step S14).

[0081] Next, the entrapment risk value identification unit 25 identifies the entrapment risk value corresponding to the target user based on the risk value table corresponding to the attributes of the target user detected in the processing of step S14, and the body orientation and hand position of the target user detected in the processing of step S14, from among the risk value tables stored in the storage unit 21 (step S15).

[0082] Next, the intrusion risk determination unit 26 compares the risk threshold set for the detection area where the target user was detected in step S11 with the intrusion risk value identified in step S15, and determines whether the intrusion risk value is equal to or greater than the risk threshold (step S16).

[0083] In the process of step S16, if it is determined that the entrapment risk value is not equal to or greater than the risk threshold, that is, that the entrapment risk value is less than the risk threshold (No. in step S16), the entrapment risk determination unit 26 determines that there is no risk of the target user being pulled into the car door 13, and determines whether or not all users detected in the process of step S11 were considered target users (step S17).

[0084] If, during the process in step S17, it is determined that not all users are included as target users (No. in step S17), then, among the users detected in the process in step S11 who are not yet included as target users are added as new target users, and the process in step S14 is executed again.

[0085] On the other hand, if it is determined in step S17 that all users are target users (Yes in step S17), the image processing device 20 executes the process in step S12 again.

[0086] In the process of step S16 described above, if it is determined that the entrapment risk value is equal to or greater than the risk threshold (Yes in step S16), the entrapment risk determination unit 26 determines that there is a risk that the target user may be pulled into the car door 13 and that there is a possibility of an entrapment accident occurring, and executes a process to warn the user inside the elevator car 11. Specifically, first, the communication unit 27 obtains door information from the elevator control device 30 (step S18), similar to the process of step S12, and then determines whether the car door 13 is in the process of opening based on the obtained door information (step S19).

[0087] In step S19, if it is determined that the car door 13 is in the process of opening (Yes in step S19), the communication unit 27 outputs a first request signal to the elevator control device 30 to slow down the opening speed of the car door 13 and a second request signal to announce to the users inside the elevator car 11 that there is a risk of an entrapment accident (step S20). In this case, the elevator control device 30 responds to the request from the image processing device 20 by slowing down the opening speed of the car door 13 and broadcasting an announcement from a speaker (not shown) inside the elevator car 11 that there is a risk of an entrapment accident.

[0088] On the other hand, if it is determined in step S19 that the car door 13 is not in the door-opening operation (No. in step S19), the communication unit 27 outputs only the second request signal described above to the elevator control device 30 (step S21). In this case, the elevator control device 30, in response to a request from the image processing device 20, broadcasts an announcement from a speaker (not shown) inside the elevator car 11 that there is a risk of an entrapment accident.

[0089] When the process in step S20 or S21 is executed, the image processing device 20 executes the process in step S12 again. Then, as described above, if the process in step S13 determines that the cage door 13 is fully open (in other words, the opening operation of the cage door 13 has been completed), the image processing device 20 terminates the series of entrapment risk determination processes.

[0090] In this description, if the entrapment risk value is determined to be above the risk threshold, the image processing device 20 determines whether the car door 13 is in the process of opening based on door information obtained from the elevator control device 30, and performs different processing depending on whether the car door 13 is in the process of opening or not. However, the description is not limited to this, and if the image processing device 20 determines that the entrapment risk value is above the risk threshold, it may also perform processing to output to the elevator control device 30 a request signal to announce to users inside the car 11 that there is a risk of an entrapment accident, regardless of the current open / closed state of the car door 13, and a request signal to slow down the opening speed of the car door 13 to a slower speed than normal.

[0091] Figure 10 shows an example where, after the series of entrapment risk determination processes shown in Figure 9 are executed, it is determined that there is no entrapment risk. Figure 11 shows an example where, after the series of entrapment risk determination processes shown in Figure 9 are executed, it is determined that there is an entrapment risk.

[0092] Figure 10 assumes a scenario where a child is detected in the low-risk detection area E3, where a risk threshold of "5" is set, with their body facing "front" to the cage door 13 and their hands positioned at a "90°" angle to the cage door 13, and the entrapment risk value corresponding to this child is identified as "4.5". Also, Figure 10 assumes a scenario where an adult is detected in the high-risk detection area E1, where a risk threshold of "1" is set, with their body facing "front" to the cage door 13 and their hands positioned at a "0°" angle to the cage door 13, and the entrapment risk value corresponding to this adult is identified as "0.9".

[0093] In this case, the entrapment risk determination unit 26 compares the entrapment risk value "4.5" corresponding to the child detected in the low-risk detection area E3 with the risk threshold "5" set for the low-risk detection area E3, in order to determine whether or not there is a risk of the child being pulled into the cage door 13. If the entrapment risk value is not equal to or greater than the risk threshold, it determines that there is no risk of the child being pulled into the cage door 13.

[0094] Furthermore, the entrapment risk determination unit 26 compares the entrapment risk value "0.9" corresponding to the adult detected in the high-risk detection area E1 with the risk threshold "1" set for the high-risk detection area E1, in order to determine whether or not there is a risk of the adult being pulled into the cage door 13. If the entrapment risk value is not equal to or greater than the risk threshold, it determines that there is no risk of the adult being pulled into the cage door 13.

[0095] Figure 11 assumes a scenario where, from the medium-risk detection area E2 with a risk threshold of "3," a "child" is detected with their body facing "front" to the cage door 13 and their hands positioned at a "90°" angle to the cage door 13, and the entrapment risk value corresponding to this child is identified as "4.5." Also, Figure 11 assumes a scenario where, from the high-risk detection area E1 with a risk threshold of "1," an "adult" is detected with their body facing "back" to the cage door 13 and their hands positioned at a "45°" angle to the cage door 13, and the entrapment risk value corresponding to this adult is identified as "1.5."

[0096] In this case, the entrapment risk determination unit 26 compares the entrapment risk value "4.5" corresponding to the child detected in the medium-risk detection area E2 with the risk threshold "3" set in the medium-risk detection area E2 to determine whether or not there is a risk of the child being pulled into the cage door 13. The unit determines that the entrapment risk value is equal to or greater than the risk threshold, that is, that there is a risk of the child being pulled into the cage door 13.

[0097] Furthermore, the entrapment risk determination unit 26 compares the entrapment risk value "1.5" corresponding to the adult detected in the high-risk detection area E1 with the risk threshold "1" set for the high-risk detection area E1, in order to determine whether or not there is a risk of the adult being pulled into the cage door 13. If the entrapment risk value is equal to or greater than the risk threshold, it determines that there is a risk of the adult being pulled into the cage door 13.

[0098] Furthermore, as shown in Figures 10 and 11, if a single user is located across multiple detection areas (i.e., if a single user is detected from multiple detection areas), the entrapment risk determination unit 26 uses the lower of the risk thresholds set for each of the multiple detection areas to determine whether or not there is a risk of the user being pulled into the car door 13. This makes it possible to more reliably prevent the occurrence of entrapment accidents.

[0099] As described above, the elevator system according to this embodiment sets multiple detection areas E1, E2, and E3 on the image captured by the camera 12 to detect users near the car door 13. When a user is detected near the car door 13, the system identifies an entrapment risk value indicating the risk of the user being pulled into the car door 13. The system compares the identified entrapment risk value with a risk threshold value set in advance for the detection area where the user was detected to determine whether or not there is a risk of the user being pulled into the car door 13. If it is determined that there is a risk of the user being pulled into the car door 13, the system announces the risk to the user inside the elevator car 11.

[0100] According to this, it is possible to perform control in accordance with the risk of a user being pulled in, as detected near the car door 13, and while ensuring the safety of users, it is possible to suppress excessive control to prevent accidents caused by being pulled in (for example, by playing a warning announcement or controlling the opening speed of the car door 13). In other words, it is possible to appropriately determine whether or not there is a risk of being pulled in, and while ensuring the safety of users, it is possible to prevent a decrease in the operating efficiency of the elevator car 11.

[0101] In this embodiment, the entrapment risk value is determined based on the user's attributes, the user's body orientation, and the user's hand position, and whether the user is looking at the elevator door 13 is determined solely by the "body orientation." However, the embodiment is not limited to this, and the entrapment risk value may be determined based on the user's attributes, the user's body orientation, the user's face orientation, and the user's hand position, and whether the user is looking at the elevator door 13 may be determined by both the "body orientation" and the "face orientation." This would allow for a more accurate determination of whether the user is looking at the elevator door 13, and thus a more accurate identification of the user's entrapment risk.

[0102] Furthermore, the risk value table pre-stored in the memory unit 21 may be updated based on, for example, data from past (operational) entrapment accidents (for example, data showing the entrapment risk value identified by the entrapment risk value identification unit 25 when an entrapment accident occurs, data showing the determination result by the entrapment risk determination unit 26 using the said entrapment risk value, data showing the output results of various request signals by the communication unit 27, etc.).

[0103] According to this, it is possible to verify whether past entrapment accidents occurred despite appropriate countermeasures being in place, and if the verification results indicate that the countermeasures were insufficient, it is possible to take measures such as updating the entrapment risk value to a higher value than the current value. The above-mentioned update process may be performed, for example, using artificial intelligence installed in the image processing device 20, or it may be performed by a maintenance worker.

[0104] Furthermore, the detection area setting unit 23 may change the size of each detection area E1, E2, and E3, as well as the risk threshold set for each detection area E1, E2, and E3, depending on the type of building and time of day in which the elevator car 11 is installed.

[0105] For example, if the building where the elevator car 11 is installed is a "nursing care facility," the likelihood of an entrapment accident is higher. Therefore, the detection area setting unit 23 may make the size of each detection area E1, E2, and E3 larger than in a typical building, and may also set the risk threshold for each detection area E1, E2, and E3 lower (i.e., it may be set so that the entrapment risk value is more likely to exceed the risk threshold).

[0106] Furthermore, since the likelihood of accidents involving children being pulled into vehicles increases during times when there are many children (for example, during school hours), the detection area setting unit 23 may increase the size of each detection area E1, E2, and E3 compared to normal times, and may also set the risk thresholds set for each detection area E1, E2, and E3 to be lower (that is, it may be set so that the risk value of being pulled into a vehicle is more likely to exceed the risk threshold).

[0107] In this embodiment, it is assumed that a risk value table is prepared for each user attribute, but a risk value table may also be prepared for each user attribute and congestion level. For example, as a risk value table corresponding to the user attribute "child," a risk value table corresponding to congestion level "quiet" and a risk value table corresponding to congestion level "crowded" may be prepared. In this case, it is desirable that the inclusion risk values ​​defined in the risk value table corresponding to congestion level "quiet" are all set higher than the inclusion risk values ​​defined in the risk value table corresponding to congestion level "crowded."

[0108] According to this, even if the elevator car 11 is not crowded, it becomes possible to reliably warn children who approach the car door 13 out of curiosity, thereby preventing accidents in which children are pulled into the elevator.

[0109] In this embodiment, if the entrapment risk determination unit 26 determines that there is a risk of being caught in the car door 13, the communication unit 27 outputs a second request signal to the elevator control device 30 to broadcast an announcement inside the elevator car 11 saying, "There is a risk of your hand being caught in the door. Please move away from the door." However, the communication unit 27 may also output a request signal to the elevator control device 30 to broadcast a special announcement inside the elevator car 11, depending on the current situation near the car door 13.

[0110] For example, if the entrapment risk determination unit 26 determines that there is no entrapment risk for a certain adult user, but that there is an entrapment risk for a child (e.g., an infant) being held by that adult user, the communication unit 27 may output a third request signal, different from the second request signal described above, to the elevator control device 30 in order to broadcast a special announcement inside the elevator car 11, such as "Please be careful of babies being caught in the door." This makes it possible to warn users with more specific information and to more effectively prevent entrapment accidents.

[0111] According to the embodiment described above, it is possible to provide an elevator system that can prevent users from being pulled into it.

[0112] While several embodiments of the present invention have been described, these embodiments are presented as examples only and are not intended to limit the scope of the invention. These novel embodiments can be implemented in various other forms, and various omissions, substitutions, and modifications can be made without departing from the spirit of the invention. These embodiments and their variations are included in the scope and spirit of the invention, as well as in the claims of the invention and its equivalents. [Explanation of Symbols]

[0113] 11... elevator car, 11a... skirting board, 12... camera, 13... car door, 14... landing door, 15... landing, 20... image processing device, 21... memory unit, 22... control unit, 23... detection area setting unit, 24... user detection unit, 25... entrapment risk value identification unit, 26... entrapment risk determination unit, 27... communication unit, 30... elevator control device, 31... door opening / closing control unit, 32... notification control unit.

Claims

1. A camera that photographs passengers inside the elevator car, Setting means for setting multiple detection areas on the image captured by the camera for detecting a user near the door of the elevator car, A detection means for detecting users from the aforementioned multiple detection areas, When a user is detected by the detection means, the identification means identifies an entrapment risk value indicating the risk of the user being pulled into the elevator car door, A determination means compares the identified risk value of being pulled in with a risk threshold set in advance for the detection area where the user detected by the detection means is located, and determines whether or not the user is at risk of being pulled into the elevator car door. If the determination means determines that there is a risk of being pulled in, the control means announces the risk of being pulled in to the user inside the elevator car, An elevator system equipped with [a specific feature / feature].

2. The aforementioned specifying means is, Based on the detected user attributes and the user's body orientation and hand position relative to the elevator car door, the user's risk of being pulled into the elevator car is identified. The elevator system according to claim 1.

3. The determination means is If the identified risk value of being drawn in is equal to or greater than the risk threshold, it is determined that there is a risk of being drawn in. The elevator system according to claim 1.

4. The setting means is used when the door opening and closing method of the elevator car is a two-door single-opening method. A first detection area is set in the vicinity of the door pocket of the elevator car and the vicinity of the overlapping portion of the two doors that make up the elevator car door, where the lowest risk threshold, the first risk threshold, is set. The area extending horizontally from the door-stop side end of the first detection area set near the door pocket, and the area extending horizontally from the door-stop side end of the first detection area set near the overlapping portion of the two doors, are set as a second detection area to which a second risk threshold higher than the first risk threshold is set. A third detection area is set around the first detection area and the second detection area, where a third risk threshold higher than the second risk threshold is set. The elevator system according to claim 3.

5. The setting means is used when the door opening and closing method of the elevator car is a center double-opening method. A first detection area is set near the two door pockets of the aforementioned elevator car, where the lowest risk threshold, the first risk threshold, is set. An area extending horizontally from the door-center end of a first detection area set near one door pocket, and an area extending horizontally from the door-center end of a first detection area set near the other door pocket, are set as a second detection area to which a second risk threshold higher than the first risk threshold is set. A third detection area is set around the first detection area and the second detection area, where a third risk threshold higher than the second risk threshold is set. The elevator system according to claim 3.

6. The setting means sets up multiple detection areas with different risk thresholds depending on the distance from a location where entrapment is likely to occur. The elevator system according to claim 3.

7. The setting means sets a plurality of detection areas with different risk thresholds, depending on the horizontal distance of the door from the position where the entrapment is likely to occur. The elevator system according to claim 6.

8. The risk threshold set for each of the multiple detection areas is set to a lower value the closer it is to the location where the entrapment is likely to occur, and a higher value the further it is from the location where the entrapment is likely to occur. The elevator system according to claim 6.

9. The determination means is If the detected user is located across multiple detection areas, the lower of the risk thresholds set for each of the multiple detection areas is used to determine whether or not the user is at risk of being pulled into the elevator car door. The elevator system according to claim 1.

10. When multiple users are detected by the detection means, the identification means identifies an entrapment risk value for each detected user, indicating the risk of being pulled into the elevator car door. The determination means determines whether there is a risk of being pulled into the elevator car door for each detected user, based on the pull-in risk value identified for each detected user and the risk threshold set for the detection area where each user is located. If the control means determines that at least one of the detected users is at risk of being pulled into the vehicle, it will announce the risk of being pulled into the vehicle inside the vehicle. The elevator system according to claim 1.

11. The control means is If the determination means determines that there is a risk of being pulled in, the control further slows down the opening speed of the elevator car door to a slower speed than usual. The elevator system according to claim 1.

12. The setting means is, The positions of the multiple detection areas are moved in accordance with the opening operation of the elevator car door. The elevator system according to claim 1.

13. The system further includes a storage means for storing multiple risk value tables, each containing a risk value for the user's attributes, based on the user's body orientation and hand position relative to the elevator car door. The elevator system according to claim 1.

14. The determination means determines whether there is a risk of a user detected by the detection means being pulled into the elevator car door while the elevator car is moving from one floor to another, or when it arrives at the floor where the elevator car is located. The elevator system according to claim 1.

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