Biological detection device

Abstract

To highly accurately determine a type and a state of a person existing in a cabin of a vehicle.SOLUTION: A living body detection device comprises: a sensor which transmits a laser beam whose frequency is modulated to a cabin of a vehicle as a transmission wave and receives a reflection wave generated by a reflection of the transmission wave by an object in the cabin; a first generation unit which generates three-dimensional map information in the cabin on the basis of intensity distribution of the reflection wave; a second generation unit which generates speed information about a speed of the object in the cabin on the basis of Doppler shift of the reflection wave; a first detection unit which detects a child in the cabin on the basis of the three-dimensional map information and the speed information; a second detection unit which detects a position of a seat in the cabin; and a determination unit which determines whether or not the child is seated on a child seat on the basis of a position of the child detected by the first detection unit and the position of the seat detected by the second detection unit.SELECTED DRAWING: Figure 2

Description

[Technical field]

[0001] The present invention relates to a biological detection device. [Background technology]

[0002] Conventionally, there is a technology that calculates biometric information (heart rate, etc.) by irradiating a person with radio waves and performing frequency analysis of the Doppler shift of the reflected waves. There is also a technology that determines the presence or absence of a person (occupant) inside a vehicle (passenger car, etc.) based on the transmission and reception of radio waves using the FMCW (Frequency Modulated Continuous Wave) method. With the FMCW method, radio waves are irradiated and the position where the reflected wave is reflected and the speed at that position can be obtained from the Doppler shift. By combining these technologies, it is possible to detect people inside a vehicle and their biometric information. There is also a technology that distinguishes between an adult present inside a vehicle and a child seated in a child car seat based on the image features of an object (presence or absence of a head or shoulders, etc.) acquired using a range image sensor. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] JP 2018-202921 A [Patent Document 2] JP 2012-127811 A Summary of the Invention [Problem to be solved by the invention]

[0004] However, if highly penetrating radio waves are used as the radio waves transmitted and received to detect people, etc., the transmitted waves penetrate all the way to the metal structural parts of the vehicle, and the signal level of the waves reflected from the metal structural parts increases, which may reduce the accuracy of detecting people, etc. Also, when trying to determine the type and state of a person (whether or not they are a child, whether or not they are sitting in a child seat, etc.) from image features, there is a high possibility that accurate determination will not be possible if the person is covered with a blanket, for example.

[0005] Therefore, an object of the present invention is to provide a living body detection device capable of determining the type and state of a person present inside a vehicle with high accuracy. [Means for solving the problem]

[0006] One embodiment of the present invention relates to a living body detection device, and includes a sensor that transmits frequency-modulated laser light into a vehicle cabin as a transmission wave and receives a reflected wave generated when the transmission wave is reflected by an object in the cabin, a first generation unit that generates three-dimensional map information of the cabin based on the intensity distribution of the reflected wave, a second generation unit that generates speed information regarding the speed of objects in the cabin based on the Doppler shift of the reflected wave, a first detection unit that detects a child in the cabin based on the three-dimensional map information and the speed information, a second detection unit that detects the position of a seat in the cabin, and a determination unit that determines whether or not a child is seated in a child seat based on the position of the child detected by the first detection unit and the position of the seat detected by the second detection unit.

[0007] According to the above configuration, a child in the vehicle is detected based on three-dimensional map information and speed information acquired by a sensor (such as a LiDAR sensor) that transmits and receives frequency-modulated laser light, and it is determined whether the child is seated in the child seat based on the positional relationship between the child and the seat. This makes it possible to determine the type and state of a person in the vehicle with high accuracy.

[0008] The determination unit may determine that the child is seated in the child seat when the position of a predetermined part of the child is shifted forward and upward from the position of a predetermined part of the seat by more than a threshold value.

[0009] When a child is seated in a child seat, the child's position is shifted forward and upward compared to when the child is seated in a normal seat, so by performing the above-mentioned determination, it is possible to accurately determine whether or not a child is seated in a child seat.

[0010] The position of the predetermined part of the child may be the center of gravity of the area in which the child is present in the three-dimensional map information.

[0011] This makes it possible to accurately estimate the child's position without using an image sensor or the like, and to accurately determine whether or not the child is seated in a child seat.

[0012] The living body detection device may further include a third generator configured to generate information relating to the heartbeat of a person in the room based on the Doppler shift of the reflected wave.

[0013] This makes it possible to generate biometric information that takes into account the type and condition of a person. [Brief description of the drawings]

[0014] [Figure 1] FIG. 1 is a diagram illustrating an example of a configuration of a vehicle according to an embodiment. [Diagram 2] FIG. 2 is a block diagram illustrating an example of a functional configuration of a LiDAR sensor and a control device according to an embodiment. [Diagram 3] FIG. 3 is a diagram showing an outline of signal processing by the FMCW method in the embodiment. [Figure 4] FIG. 4 is a diagram illustrating an example of a state in which an adult and a child are detected by the human detection unit in the embodiment. [Diagram 5] FIG. 5 is a diagram showing an example of a seat position in the embodiment. [Figure 6] FIG. 6 is a diagram showing an example of a state in which a child is directly seated on the seat in the embodiment. [Figure 7] FIG. 7 is a diagram showing an example of a state in which a child is seated in a child seat in the embodiment. [Figure 8] FIG. 8 is a flowchart illustrating an example of a process performed by the biological detection device according to the embodiment. [Figure 9] FIG. 9 is a diagram showing an example of a vehicle in the first modified example. [Figure 10]FIG. 10 is a diagram showing an example of a method of using a LiDAR sensor in the second modified example. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0015] Exemplary embodiments of the present invention are disclosed below. The configurations of the embodiments described below, and the actions, results, and effects brought about by the configurations are merely examples. The present invention can be realized with configurations other than those disclosed in the following embodiments, and it is possible to obtain at least one of various effects and derivative effects based on the basic configuration.

[0016] 1 is a diagram showing an example of the configuration of a vehicle C in an embodiment. A LiDAR sensor 2 (sensor) and a control device 3 constituting a living body detection device 1 are arranged in the interior of the vehicle C. The LiDAR sensor 2 is installed on the ceiling of the interior. The control device 3 is installed, for example, in a dashboard provided at the front end of the interior.

[0017] An occupant M (person) is seated in the seat S. In the following, detection of the presence of the occupant M by the living body detection device 1 and determination of the type and state of the occupant M will be described.

[0018] 2 is a block diagram showing an example of a functional configuration of the LiDAR sensor 2 and the control device 3 according to the embodiment. The LiDAR sensor 2 includes a transmitter 21 and a receiver 22.

[0019] The transmitter 21 transmits (irradiates) a frequency-modulated laser beam as a transmission wave over a wide range within the interior of the vehicle C. The receiver 22 receives a reflected wave that is generated when the transmission wave is reflected by an object within the interior.

[0020] The control device 3 is configured with, for example, an MCU (Micro Controller Unit) having an integrated circuit equipped with a hardware processor, a memory, etc. The control device 3 includes an ADC (Analog-to-Digital Converter) 31, a processing unit 32, and a storage unit 33.

[0021] The ADC 31 converts the analog signal acquired from the receiving unit 22 of the LiDAR sensor 2 into a digital signal and outputs the digital signal to the processing unit 32.

[0022] The storage unit 33 is, for example, a storage device such as a random access memory (RAM), a read only memory (ROM), a solid state drive (SSD), or a hard disk drive (HDD). The storage unit 33 stores the program executed by the processing unit 32, data required for executing the program, data generated by executing the program, etc. The storage unit 33 in this embodiment stores setting information 331, three-dimensional map information 332, speed information 333, seat position information 334, biological information 335, seating information 336, etc.

[0023] The setting information 331 includes various thresholds for implementing the functions of the biological detection device 1. The thresholds may be, for example, a threshold for detecting a person, a threshold for distinguishing between an adult and a child, a threshold for determining whether or not a child is seated in a child seat, a threshold for determining whether or not a biological signal is from a person, and the like.

[0024] The three-dimensional map information 332 is information indicating a three-dimensional object arrangement state in the room, which is generated based on the intensity distribution of the reflected wave by the map information generating unit 321. The intensity distribution is information indicating the correspondence relationship between the position of the reflection source in the three-dimensional space (the room of the vehicle C) and the intensity of the reflected wave.

[0025] The speed information 333 is information indicating the speed (movement) of an object present in the room, which is generated based on the Doppler shift of the reflected wave by the speed information generating unit 322. The speed information 333 may include information indicating the direction of the object's movement.

[0026] The seat position information 334 is information that indicates the positions of the seats (rear seats, passenger seats, driver seats, etc.) installed in the vehicle C, which is detected by the seat position detection unit 423.

[0027] The biometric information 335 is biometric information of a person (occupant M) generated by the biometric information generating unit 326. The biometric information may be, for example, a heart rate or a person's condition (physical condition, mental state, etc. estimated from the heart rate, etc.).

[0028] The seating information 336 is information that indicates the seating state of a person in the seat S, as determined by the determination unit 325. The seating information 336 includes information that indicates whether a child is seated in a child seat, and the like.

[0029] Here, an overview of signal processing by the FMCW method will be described. Fig. 3 is a diagram showing an overview of signal processing by the FMCW method in an embodiment. As shown in (A), first, FMCW-modulated laser light is transmitted from the transmitter 21 of the LiDAR sensor 2 to the interior of the vehicle C. Then, the receiver 22 of the LiDAR sensor 2 receives the reflected wave.

[0030] Next, as shown in (B), three-dimensional map information of the interior of the vehicle is created based on the intensity distribution of the reflected waves in the vehicle. This three-dimensional map information includes a labeling area D that indicates the positions and sizes of objects (occupant M, seat S, etc.) present in the vehicle.

[0031] Next, as shown in (C), the occupant M is detected based on the above-mentioned three-dimensional map information and speed information based on the Doppler shift of the reflected wave. For example, among multiple objects present in the vehicle cabin, an object having a predetermined speed (movement) can be determined to be the occupant M. In addition, the biological information (heart rate, etc.) of the occupant M can also be calculated based on the Doppler shift of the reflected wave.

[0032] The process performed by the processing unit 32 will be described in detail below with reference to FIG.

[0033] The processing unit 32 is configured by a hardware processor such as a CPU (Central Processing Unit). The processing unit 32 reads a program stored in the storage unit 33 and executes arithmetic processing. The processing unit 32 includes, as functional units, a map information generating unit 321 (first generating unit), a speed information generating unit 322 (second generating unit), a human detection unit 323 (first detecting unit), a seat position detection unit 324 (second detecting unit), a determination unit 325, and a biometric information generating unit 326 (third generating unit). Note that a part or all of each unit 321 to 326 may be configured by hardware such as a circuit including an ASIC (Application Specific Integrated Circuit) or an FPGA (Field-Programmable Gate Array).

[0034] The map information generating unit 321 generates three-dimensional map information 332 of the room based on the reflected wave information acquired from the ADC 31 , and stores the information in the storage unit 33 .

[0035] The speed information generating unit 322 generates speed information 333 indicating the speed of an object present in the room based on the reflected wave information acquired from the ADC 31 , and stores the information in the storage unit 33 .

[0036] The human detection unit 323 detects an occupant M present in the cabin of the vehicle C based on the setting information 331, the three-dimensional map information 332, the speed information 333, etc. The human detection unit 323 also detects whether the occupant M is a child or not. Whether the occupant M is a child or not can be detected, for example, by comparing the setting information 331 with information indicating the size of the labeling region D included in the three-dimensional map information 332.

[0037] The seat position detection unit 324 detects the position of the seat S. The method of detecting the position of the seat S is not particularly limited, but for example, the position of the seat S can be detected based on a detection signal of a sensor installed in a slide mechanism of the seat S, three-dimensional map information 332, or the like. Seat position information 334 indicating the position of the seat S is stored in the storage unit 33.

[0038] The determination unit 325 determines whether or not the child is seated in the child seat based on the position of the child detected by the person detection unit 323 and the seat position information 334. A specific method of determination by the determination unit 325 will be described later.

[0039] The biometric information generating unit 326 generates biometric information (heart rate, etc.) of the occupant M detected by the human detection unit 323 based on the reflected wave information acquired from the ADC 31. The generated biometric information is stored in the storage unit 33.

[0040] 4 is a diagram showing an example of a state in which an adult Ma and a child Mc are detected by the person detection unit 323 in the embodiment. For example, the physical build of the person is estimated based on the size of the labeling area D (see FIG. 2) corresponding to the person, and if the physical build is equal to or smaller than a threshold, the person can be estimated to be a child Mc.

[0041] FIG. 5 is a diagram showing an example of a seat position Ps in the embodiment. FIG. 5 illustrates the seat S in a default position and the seat S in a state where it has been slid forward. The seat position Ps is a position of a predetermined part of the seat S, and in this case, is a position of the center part of the seating portion of the seat S (excluding the backrest portion). The seat position Ps is not limited to this, and may be a position of another part of the seat S. The seat position Ps is displaced according to the movement of the seat S. The movement of the seat S may be not only a horizontal slide, but also a vertical or diagonal movement.

[0042] Fig. 6 is a diagram showing an example of a state in which a child Mc is directly seated on a seat S in the embodiment. Fig. 7 is a diagram showing an example of a state in which a child Mc is seated in a child seat Sc in the embodiment.

[0043] 6 and 7 show an example of a seat position Ps and a child position Pm. The child position Pm is the position of a predetermined part of the child Mc, and may be, for example, the center of gravity of the presence area (labeling area D) of the child Mc in the three-dimensional map information 332. By using such a child position Pm, the position of the child Mc can be estimated without using image analysis or the like. The child position Pm may be the position of the child Mc's head, or the like. Also, in FIGS. 6 and 7, a forward displacement amount Df of the child position Pm relative to the seat position Ps and an upward displacement amount Du of the child position Pm relative to the seat position Ps are shown as examples.

[0044] The displacement amounts Df, Du shown in Fig. 7 are larger than the displacement amounts Df, Du shown in Fig. 6. That is, the displacement amounts Df, Du when the child Mc is seated in the child seat Sc are larger than the displacement amounts Df, Du when the child Mc is seated in a normal seat S, because the child Mc moves forward and upward due to the child seat Sc. Therefore, when the displacement amounts Df, Du are each equal to or larger than a threshold value, it can be determined that the child Mc is seated in the child seat Sc.

[0045] 8 is a flowchart showing an example of processing by the living body detection device 1 in the embodiment. When reflected wave information of the interior of the vehicle C is acquired by driving the LiDAR sensor 2 (S101), the map information generating unit 321 generates three-dimensional map information 332 based on the intensity distribution of the reflected wave (S102), and the speed information generating unit 322 generates speed information 333 based on the Doppler shift of the reflected wave (S103).

[0046] The human detection unit 323 detects whether or not a child Mc is present inside the vehicle C based on the three-dimensional map information 332 and the speed information 333 (S104). If a child Mc is not present (S104: No), the human detection unit 323 determines whether or not a person (adult Ma) is present (S105). If no person is present (S105: No), this routine ends, and if a person (only adult Ma) is present (S105: Yes), the biometric information generation unit 326 generates biometric information of the person based on the Doppler shift of the reflected wave, etc. (S111), and this routine ends.

[0047] If a child Mc is present (S104: Yes), the seat position detection unit 324 detects the seat position Ps of the seat S corresponding to the position of the child Mc (S106), and the determination unit 325 determines whether the deviations Df, Du between the child position Pm and the seat position Ps are equal to or greater than a threshold (S107). If both the deviations Df, Du are equal to or greater than a threshold (S107: Yes), the determination unit 325 determines that the child Mc is seated in a child seat Sc (S108), and generates seating information indicating that the child Mc is seated in a child seat Sc (S110). On the other hand, if either or both of the deviations Df, Du are not equal to or greater than the threshold (S107: No), the determination unit 325 determines that the child Mc is seated in a normal seat S (S109), and generates seating information indicating that the child Mc is seated in a normal seat S (S110). After the seating information is generated, the biometric information generating unit 326 generates biometric information of the person based on the Doppler shift of the reflected wave or the like (S111), and this routine ends. The biometric information and seating information generated as described above can be output to a predetermined system (for example, a driving assistance system of the vehicle C) and used.

[0048] According to the above embodiment, the child Mc in the vehicle is detected based on the three-dimensional map information 332 and the speed information 333 acquired by the LiDAR sensor 2, and it is determined whether the child Mc is seated in the child seat Sc based on the positional relationship between the child Mc and the seat S. This makes it possible to determine the type and state of a person present in the vehicle C with high accuracy.

[0049] (Modification) Fig. 9 is a diagram showing an example of a vehicle C in the first modified example. As shown in Fig. 9, in the interior of the vehicle C, a LiDAR sensor 2 may be installed in the front part instead of the ceiling, and a process for detecting the type and state of an occupant M may be performed.

[0050] 10 is a diagram showing an example of a method of using the LiDAR sensor 2 in the second modified example. The LiDAR sensor 2 may be installed on the ceiling above the bathtub B in the bathroom, and processing may be performed to detect the type and condition of the bather M. In this way, for example, if an elderly person suddenly falls ill while taking a bath, the sudden illness can be detected with high accuracy if there are certain changes in the elderly person's pulse wave, breathing, body movement, etc.

[0051] The program executed by the control device 3 may be provided as a computer program product by being stored in a computer-readable storage medium such as a CD-ROM, CD-R, memory card, DVD (Digital Versatile Disk), or flexible disk (FD) in an installable or executable format file. The program may be provided by being stored on a computer connected to a network such as the Internet and downloaded via the network. The program may be provided or distributed via a network such as the Internet.

[0052] Although the embodiment of the present invention has been described above, the above embodiment is presented as an example and is not intended to limit the scope of the invention. This new embodiment can be implemented in various other forms, and various omissions, substitutions, and modifications can be made without departing from the gist of the invention. This embodiment and its modifications are included in the scope and gist of the invention, and are included in the scope of the invention and its equivalents described in the claims. [Explanation of symbols]

[0053] 1...biological detection device, 2...LiDAR sensor, 3...control device, 21...transmission unit, 22...reception unit, 31...ADC, 32...processing unit, 33...storage unit, 321...map information generation unit, 322...speed information generation unit, 323...person detection unit, 324...seat position detection unit, 325...determination unit, 326...biological information generation unit, 331...setting information, 332...three-dimensional map information, 333...speed information, 334...seat position information, 335...biological information, 336...seating information, C...vehicle, D...labeling area, Df, Du...displacement amount, M...occupant (bathing person), Ma...adult, Mc...child, Pm...child position, Ps...seat position, S...seat, Sc...child seat

Claims

1. a sensor that transmits a frequency-modulated laser beam as a transmission wave into a vehicle interior and receives a reflected wave generated when the transmission wave is reflected by an object in the interior; a first generating unit that generates three-dimensional map information of the room based on the intensity distribution of the reflected waves; a second generating unit that generates velocity information regarding a velocity of an object in the room based on a Doppler shift of the reflected wave; a first detection unit that detects a child in the room based on the three-dimensional map information and the speed information; A second detection unit that detects the position of the seat in the vehicle interior; a determination unit that determines whether or not the child is seated in the child seat based on the position of the child detected by the first detection unit and the position of the seat detected by the second detection unit; A biological detection device comprising:

2. the determination unit determines that the child is seated in the child seat when a position of a predetermined part of the child is shifted forward and upward from a position of a predetermined part of the seat by a threshold value or more, respectively. The biological detection device according to claim 1 .

3. The position of the predetermined part of the child is a center of gravity of the presence area of ​​the child in the three-dimensional map information. The biological detection device according to claim 1 .

4. a third generating unit that generates information about the heartbeat of the person in the room based on the Doppler shift of the reflected wave; The biological detection device according to any one of claims 1 to 3, further comprising:

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