JP7615903B2 - Biological detection device - Google Patents

Description

The present invention relates to a biological detection device.

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 adults and children seated in child seats inside a vehicle based on the image features of an object (presence or absence of a head or shoulders, etc.) acquired using a range image sensor.

JP 2018-202921 A JP 2012-127811 A

However, if highly penetrating radio waves are used as the radio waves transmitted and received to detect people, etc., the transmitted waves will 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 will increase, 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 seated in a child seat, etc.) from image features, there is a high possibility that accurate determination will not be possible if the person in question is covered with a blanket, for example.

Therefore, the problem that the present invention aims to solve is to provide a live body detection device that can determine the type and state of a person present inside a vehicle with high accuracy.

One embodiment of the present invention relates to a living body detection device, which includes a sensor that transmits frequency-modulated laser light into the vehicle interior as a transmission wave and receives a reflected wave generated when the transmission wave is reflected by an object in the interior, a first generation unit that generates three-dimensional map information of the interior based on the intensity distribution of the reflected wave, a second generation unit that generates speed information related to the speed of the object in the interior based on the Doppler shift of the reflected wave, a first detection unit that detects a child in the interior based on the three-dimensional map information and the speed information, a second detection unit that detects the position of a seat in the interior, 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.

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 a 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 present in the vehicle's cabin with high accuracy.

The determination unit may also determine that the child is seated in the child seat when the position of a specific part of the child is shifted forward and upward by more than a threshold value relative to the position of a specific part of the seat.

When a child is seated in a child seat, the child's position shifts forward and upward compared to when the child is seated in a normal seat. Therefore, by making the above determination, it is possible to accurately determine whether or not a child is seated in a child seat.

The position of the specified part of the child may also be the center of gravity of the area in which the child is present in the three-dimensional map information.

This allows the child's position to be accurately estimated without using an image sensor or the like, and makes it possible to accurately determine whether the child is seated in a child seat.

The biological detection device may further include a third generation unit that generates information about the heart rate of a person in the room based on the Doppler shift of the reflected wave.

This makes it possible to generate biometric information that takes into account a person's type and condition.

FIG. 1 is a diagram illustrating an example of a configuration of a vehicle according to an embodiment. FIG. 2 is a block diagram showing an example of the functional configuration of a LiDAR sensor and a control device of an embodiment. FIG. 3 is a diagram showing an outline of signal processing by the FMCW method in the embodiment. 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. FIG. 5 is a diagram illustrating an example of a seat position in the embodiment. FIG. 6 is a diagram showing an example of a state in which a child is directly seated on the seat in the embodiment. FIG. 7 is a diagram showing an example of a state in which a child is seated in a child seat in the embodiment. FIG. 8 is a flowchart illustrating an example of a process performed by the biological detection device according to the embodiment. FIG. 9 is a diagram showing an example of a vehicle in the first modified example. FIG. 10 is a diagram showing an example of how to use a LiDAR sensor in the second modified example.

Below, exemplary embodiments of the present invention are disclosed. The configurations of the embodiments shown below, and the actions, results, and effects brought about by said 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 the various effects and derivative effects based on the basic configuration.

Figure 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 in the ceiling part of the interior. The control device 3 is installed, for example, in a dashboard provided at the front end of the interior.

An occupant M (person) is sitting in the seat S. Below, we will explain how the living body detection device 1 detects the presence of the occupant M and determines the type and condition of the occupant M.

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

The transmitter 21 transmits (irradiates) frequency-modulated laser light as a transmission wave over a wide area 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.

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

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

The storage unit 33 is, for example, a storage device such as a RAM (Random Access Memory), a ROM (Read Only Memory), an SSD (Solid State Drive), or an HDD (Hard Disk Drive). The storage unit 33 stores the programs executed by the processing unit 32, data required for the execution of the programs, data generated by the execution of the programs, etc. In this embodiment, the storage unit 33 stores setting information 331, three-dimensional map information 332, speed information 333, seat position information 334, biological information 335, seating information 336, etc.

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 adults and children, a threshold for determining whether a child is seated in a child seat, a threshold for determining whether a biological signal is from a person, etc.

The three-dimensional map information 332 is information that indicates the three-dimensional object arrangement state in the room, and is generated by the map information generation unit 321 based on the intensity distribution of the reflected waves. The intensity distribution is information that indicates the correspondence between the position of the reflection source in three-dimensional space (the interior of the vehicle C) and the intensity of the reflected waves.

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

The seat position information 334 is information indicating the position of the seats (rear seat, passenger seat, driver's seat, etc.) installed in the vehicle C, detected by the seat position detection unit 423.

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

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 or not a child is seated in a child seat, etc.

Here, an overview of signal processing using the FMCW method will be described. FIG. 3 is a diagram showing an overview of signal processing using 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 into the interior of the vehicle C. Then, the receiver 22 of the LiDAR sensor 2 receives the reflected wave.

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 within the vehicle. This three-dimensional map information includes a labeling area D that indicates the position and size of objects (occupant M, seat S, etc.) present within the vehicle.

Next, as shown in (C), 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 cabin, an object having a predetermined speed (movement) can be determined to be occupant M. In addition, biometric information (heart rate, etc.) of occupant M can also be calculated based on the Doppler shift of the reflected wave.

The details of the processing performed by the processing unit 32 are described below with reference to FIG. 2.

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 memory unit 33 and executes calculation 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 person detecting unit 323 (first detecting unit), a seat position detecting unit 324 (second detecting unit), a determining unit 325, and a biometric information generating unit 326 (third generating unit). Note that some or all of the units 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).

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 it in the memory unit 33.

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 memory unit 33.

The person 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 person 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 area D included in the three-dimensional map information 332.

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 can be detected based on a detection signal of a sensor installed in the slide mechanism of the seat S, three-dimensional map information 332, etc. Seat position information 334 indicating the position of the seat S is stored in the memory unit 33.

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. The specific method of determination by the determination unit 325 will be described later.

The biometric information generating unit 326 generates biometric information (heart rate, etc.) of the occupant M detected by the person detecting unit 323 based on the reflected wave information acquired from the ADC 31. The generated biometric information is stored in the memory unit 33.

Figure 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 an embodiment. For example, the physical size of the person can be estimated based on the size of the labeling area D (see Figure 2) corresponding to the person, and if the physical size is equal to or smaller than a threshold, the person can be estimated to be a child Mc.

Figure 5 is a diagram showing an example of a seat position Ps in an embodiment. Figure 5 illustrates an example of 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 the position of a specific part of the seat S, and in this case, is the position of the center of the seating portion of the seat S (excluding the backrest portion). The seat position Ps is not limited to this, and may be the 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.

Figure 6 shows an example of a state in which a child Mc is seated directly on a seat S in an embodiment. Figure 7 shows an example of a state in which a child Mc is seated in a child seat Sc in an embodiment.

Figures 6 and 7 show examples of the seat position Ps and the child position Pm. The child position Pm is the position of a specific part of the child Mc, and may be, for example, the center of gravity of the area in which the child Mc is present (labeling area D) 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, for example. Figures 6 and 7 also show examples of the forward shift amount Df of the child position Pm relative to the seat position Ps, and the upward shift amount Du of the child position Pm relative to the seat position Ps.

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

Figure 8 is a flowchart showing an example of processing by the living body detection device 1 in an embodiment. When reflected wave information from within 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 waves (S102), and the speed information generating unit 322 generates speed information 333 based on the Doppler shift of the reflected waves (S103).

The person 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 person 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.

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 judgment unit 325 judges whether the deviation amounts Df, Du between the child position Pm and the seat position Ps are equal to or greater than a threshold (S107). If both deviation amounts Df, Du are equal to or greater than a threshold (S107: Yes), the judgment unit 325 judges 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 both or either of the deviation amounts Df, Du are not equal to or greater than the threshold (S107: No), the judgment unit 325 judges 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, etc. (S111), and this routine ends. The biometric information and seating information generated as described above can be output to a specified system (e.g., a driving assistance system for vehicle C, etc.) and used.

According to the above embodiment, a child Mc in the vehicle is detected based on the three-dimensional map information 332 and speed information 333 acquired by the LiDAR sensor 2, and it is determined whether or not 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.

(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, the LiDAR sensor 2 may be installed in the front part instead of the ceiling, and processing for detecting the type and state of the occupant M may be performed.

Figure 10 is a diagram showing an example of how to use 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 movements, etc.

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

Although an 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.

1...biological detection device, 2...LiDAR sensor, 3...control device, 21...transmitter, 22...receiver, 31...ADC, 32...processor, 33...storage unit, 321...map information generator, 322...speed information generator, 323...person detector, 324...seat position detector, 325...determiner, 326...biological information generator, 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...deviation amount, M...occupant (bathing person), Ma...adult, Mc...child, Pm...child position, Ps...seat position, S...seat, Sc...child seat

Claims (4)

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: 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 . 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 . 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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