Device for monitoring abnormal situations with a vehicle, vehicle, method

Abstract

The present disclosure relates to an apparatus, a vehicle, a method for monitoring an abnormal situation using a vehicle. An apparatus for monitoring an abnormal situation occurring in an area inside or around a parking lot using a vehicle in the area includes an information acquisition unit that acquires state information indicating a state in the area; an abnormality sensing unit that senses an abnormal situation based on the state information and determines a place of occurrence of the sensed abnormal situation; and an instruction transmission unit that transmits an instruction for starting an outside monitoring sensor of a vehicle parked in a vicinity of the place of occurrence determined by the abnormality sensing unit to the vehicle to cause the outside monitoring sensor to detect the place of occurrence.

Description

Technical Field

[0001] This disclosure relates to devices, vehicles, and methods for using vehicles to monitor abnormal situations. Background Technology

[0002] An anti-theft device for a vehicle is known (e.g., Japanese Patent Application Publication No. 2020-149088).

[0003] Unusual situations such as fires, incidents, or accidents may occur inside or around parking lots. Previously, there was a demand to improve security in the area by effectively monitoring such unusual situations. Summary of the Invention

[0004] The first aspect of this disclosure is an apparatus for monitoring abnormal situations occurring in a parking lot using vehicles within or around the parking lot. The apparatus includes: an information acquisition unit for acquiring status information indicating the status of the area; an anomaly sensing unit for sensing an anomaly based on the status information and determining the location of the detected anomaly; and a command sending unit for sending a command to the parked vehicle to activate an external monitoring sensor located around the location of the anomaly determined by the anomaly sensing unit, thereby enabling the external monitoring sensor to detect the location of the anomaly.

[0005] The second aspect of this disclosure is the apparatus described in the first aspect, wherein the information acquisition unit acquires image data captured by infrastructure sensors installed in the parking lot as status information, and the anomaly sensing unit senses anomalies based on the image data and determines the location of the anomaly.

[0006] The third aspect of this disclosure is the apparatus described in the first or second aspect, which further includes a vehicle determination unit that determines a parked vehicle from the vehicles in the area based on status information or the location information of vehicles in the area, and sends a command to the parked vehicle determined by the vehicle determination unit.

[0007] The fourth aspect of this disclosure is the apparatus described in the third aspect, wherein the vehicle determination unit determines the parking position of the vehicle in the area based on status information or location information, and based on the determined parking position, determines from the vehicles in the area a parked vehicle with an external monitoring sensor that makes the occurrence location fall within the detection range.

[0008] The fifth aspect of this disclosure is the apparatus described in the fourth aspect, wherein the vehicle determination unit further determines the orientation of vehicles in the area based on status information or location information, and further determines the parked vehicle based on the determined orientation.

[0009] The sixth aspect of this disclosure is the apparatus described in any one of the first to fifth aspects, wherein the information acquisition unit further acquires detection data detected by the external monitoring sensor according to the instruction sent by the instruction sending unit as status information.

[0010] The seventh aspect of this disclosure is a vehicle equipped with an external monitoring sensor, which activates the external monitoring sensor according to an instruction sent by the instruction sending unit of the device described in any one of the first to sixth aspects, so that the external monitoring sensor detects the location of the event.

[0011] The eighth aspect of this disclosure is a method for monitoring abnormal situations occurring in a parking lot using vehicles within or around the parking lot. The processor acquires state information representing the state of the area, senses abnormal situations based on the state information, determines the location of the sensed abnormal situation, and sends a command to the parked vehicle to activate an external monitoring sensor located around the determined location of the abnormal situation, enabling the external monitoring sensor to detect the location of the abnormal situation.

[0012] According to this disclosure, external monitoring sensors mounted on surrounding vehicles can be used to monitor abnormal situations occurring in the area. Therefore, abnormal situations can be effectively monitored, thereby improving security in the area. Attached Figure Description

[0013] Hereinafter, with reference to the accompanying drawings, the features, advantages, and technical and industrial significance of exemplary embodiments of the present invention will be described, wherein the same reference numerals denote the same elements, wherein:

[0014] Figure 1 This describes a parking management system implemented in one way.

[0015] Figure 2 yes Figure 1 The diagram shown is a block diagram of a parking management system.

[0016] Figure 3 This is a block diagram of a vehicle according to one implementation method.

[0017] Figure 4 This is a flowchart illustrating an example of a method for monitoring abnormal situations.

[0018] Figure 5 This indicates an unusual situation that occurred inside the parking lot.

[0019] Figure 6 This is a block diagram of another implementation of a parking management system.

[0020] Figure 7 This is a flowchart illustrating another example of a method for monitoring abnormal situations. Detailed Implementation

[0021] Hereinafter, embodiments of the present disclosure will be described in detail based on the accompanying drawings. It should be noted that in the various embodiments described below, the same elements are labeled with the same reference numerals, and repeated descriptions are omitted. First, referring to... Figure 1 and Figure 2 One embodiment of the parking management system 10 will be described. The parking management system 10 is a system for managing vehicles 110 parked in or around area A of the parking lot 100.

[0022] The parking management system 10 includes multiple infrastructure sensors 12, a communicator 14, and a parking management server 16. Each infrastructure sensor 12, including cameras or laser scanners, is installed in the parking lot 100 to capture images within area A. It should be noted that the multiple infrastructure sensors 12 can be distributed across multiple locations within the parking lot 100, enabling them to capture images of any location within area A (e.g., any parking space designated within the parking lot 100). The infrastructure sensors 12 supply the image data IDs of the captured area A to the parking management server 16.

[0023] The communicator 14 can communicate with external devices, including those in vehicles 110 within area A. Specifically, the communicator 14 uses mobile communication networks such as 4G or 5G to wirelessly send and receive data with external devices. It should be noted that multiple communicators 14 can be installed in the parking lot 100, enabling communication with vehicles 110 parked in any location within area A. Furthermore, the communicator 14 can communicate with external devices using any communication protocol.

[0024] The parking management server 16 controls the operation of the infrastructure sensors 12 and communicator 14. Specifically, as... Figure 2 As shown, the parking management server 16 is a computer with a processor 18, a memory 20, and an I / O interface 22. The processor 18 may have a CPU (Central Processing Unit) or a GPU (Graphics Processing Unit), and is communicatively connected to the memory 20 and the I / O interface 22 via a bus 24. The processor 18 performs computational processing to implement the abnormal situation monitoring function described later.

[0025] The memory 20 has RAM (Random Access Memory) or ROM (Read Only Memory), etc., and temporarily or permanently stores various data used in the arithmetic processing executed by the processor 18 and various data generated during the arithmetic processing. The I / O interface 22 has, for example, an Ethernet port, a USB (Universal Serial Bus) port or an HDMI (High Definition Multimedia Interface) terminal. In addition to the infrastructure sensor 12 and the communicator 14 mentioned above, the I / O interface 22 can also be communicatively connected, via wired or wireless means, to peripheral devices such as displays (LCD (Liquid Crystal Display), organic EL (electroluminescence) displays, etc.), input devices (keyboard, mouse, etc.) and speakers.

[0026] Multiple vehicles 110 can be parked within area A (e.g., inside parking lot 100). See below for reference. Figure 3 The configuration of a vehicle 110 according to one embodiment will be described. The vehicle 110 is, for example, a four-wheeled automobile, and includes a body 112, an onboard communicator 114, external monitoring sensors 116, and an electronic control unit (ECU) 118, etc.

[0027] In addition to the vehicle communication device 114, the external monitoring sensor 116, and the ECU 118, the vehicle body 112 also carries various vehicle components such as drive mechanisms (engine or electric motor, etc.), steering mechanisms (power steering devices, etc.), braking mechanisms (electric braking devices, etc.) and various sensors (speed sensors, steering angle sensors, etc.).

[0028] The vehicle-mounted communicator 114 can communicate with external devices, including the communicator 14 of the parking management system 10. The vehicle-mounted communicator 114 includes, for example, a GPS (Global Positioning System) receiver 114A, a vehicle-to-vehicle communicator 114B, and a data communication module (DCM) 114C. The GPS receiver 114A receives GPS signals from GPS satellites. The vehicle-to-vehicle communicator 114B can send and receive data with the vehicle-mounted communicators of other vehicles. The DCM 114C can use mobile communication network systems such as 4G or 5G to send and receive data with the aforementioned communicator 14, the management server of the vehicle manufacturer 110, or the base station of a communication operator.

[0029] The external monitoring sensor 116 detects the surrounding environment of the vehicle 110. For example, the external monitoring sensor 116 has at least one of a camera that detects the surrounding environment by taking pictures of the surrounding environment of the vehicle 110 and a radar (LiDAR, laser scanner, etc.) that detects the surrounding environment by irradiating electromagnetic waves (e.g., laser) around the vehicle 110 and receiving reflected waves from the surrounding environment.

[0030] ECU 118 controls the actions of vehicle 110. Specifically, ECU 118 is a computer with processor 120, memory 122, and I / O interface 124. Processor 120 has CPU or GPU, etc., and is communicatively connected to memory 122 and I / O interface 124 via bus 126.

[0031] The memory 122 has RAM or ROM, etc., which temporarily or permanently stores various data used in the arithmetic processing performed by the processor 120 and various data generated during the arithmetic processing. The I / O interface 124 has, for example, a Controller Area Network (CAN) port, an Ethernet port, a USB port, a fiber optic connector, or an HDMI terminal, for wired or wireless data communication with vehicle components such as the vehicle communicator 114 and the external monitoring sensor 116.

[0032] In this embodiment, the owner D of each vehicle 110 pre-registers for use of the parking lot 100. For example, the owner D operates the human-machine interface (HMI) of the vehicle 110, accesses the parking management server 16 through the vehicle's onboard communicator 114, downloads the application α for user registration of the parking lot 100 from the parking management server 16, and installs it in the ECU 118 of the vehicle 110.

[0033] Then, the owner D operates the HMI of vehicle 110 to start the application α, and enters the owner D's personal information Iv (name, address, phone number, etc.) and the vehicle 110's identification information Is through the user registration screen displayed on the HMI's display, and uploads it to the parking management server 16 through the vehicle communication device 114.

[0034] The identifying information Is includes, for example, the vehicle registration number Is1, chassis number Is2, the manufacturer of vehicle 110 Is3, and the model of vehicle 110 Is4. It should be noted that the vehicle registration number Is1 in the identifying information Is is printed on the license plates mounted on the front and rear of vehicle 110, making it visually identifiable from the outside of vehicle 110.

[0035] The processor 18 of the parking management server 16 obtains personal information Iv and determination information Is sent from the vehicle communicator 114 of the vehicle 110 via the communicator 14, and obtains the communication address AD (e.g., IP address) assigned to the vehicle communicator 114. Then, the processor 18 creates a database DB that associates the obtained personal information Iv, determination information Is, and address AD, and stores this database in advance in the memory 20. Thus, before using the parking lot 100, the determination information Is and address AD of multiple vehicles 110 are stored in the database DB.

[0036] Here, anomalies AS may sometimes occur in area A. Examples of such anomalies AS include fire AS1, theft of vehicle 110 AS2, and accidents between vehicles 110 AS3. In this embodiment, the parking management server 16 performs the function of sensing the occurrence of such anomalies AS and monitoring the anomalies AS using the vehicles 110 in area A.

[0037] The following is for reference Figure 4 The method for monitoring abnormal situations (AS) is explained. Figure 4The process shown begins when the processor 18 of the parking management server 16 receives an action start command (e.g., a power-on command) from an operator, a host controller, or a computer program PG.

[0038] In step S1, the processor 18 begins acquiring state information Ia representing the state within area A. As an example, the processor 18 acquires image data IDs captured by the infrastructure sensors 12 as state information Ia. More specifically, each infrastructure sensor 12 continuously (e.g., periodically) captures images within area A (e.g., the interior of parking lot 100).

[0039] The processor 18 continuously (e.g., periodically) acquires image data IDs captured by each infrastructure sensor 12 via the I / O interface 22. Thus, the processor 18 begins collecting image data IDs captured by multiple infrastructure sensors 12 as the action for status information Ia.

[0040] As another example, processor 18 acquires message data MD that reports the status within area A as status information Ia. Message data MD may include, for example, text or image data of reports published on social networking services (SNS) or web sites (the homepage of the parking lot 100 management company, personal blogs, news websites, etc.).

[0041] For example, when a user of parking lot 100 witnesses an anomaly AS occurring in area A, they can use their portable device (e.g., a smartphone or tablet) to publish a message data MD reporting the anomaly AS on an SNS or webpage. In this way, the message data MD reports the status of area A using text or image data.

[0042] On the other hand, the I / O interface 22 of the parking management server 16 can be communicatively connected to a communication network NW (LAN (Local Area Network) or the Internet, etc.), and the processor 18 can access SNS or websites through this communication network NW. The processor 18 accesses SNS or websites through the communication network NW to retrieve and collect message data MD of the status within reporting area A.

[0043] Thus, in step S1, processor 18 begins the operation of acquiring status information Ia (e.g., image data ID and message data MD). Therefore, in this embodiment, processor 18 serves as the information acquisition unit 32 for acquiring status information Ia. Figure 2 To fulfill its function.

[0044] In this embodiment, the processor 18 determines the vehicle 110 that has entered area A (e.g., the interior of parking lot 100) based on the acquired status information Ia, and determines the parking position PP of the vehicle 110. Specifically, the infrastructure sensor 12 continuously captures images of each vehicle 110 that has entered area A. After step S1 begins, the processor 18 collects the image data ID of the vehicle 110 captured by the infrastructure sensor 12 as the status information Ia.

[0045] For example, set as Figure 5 The vehicle 110E shown has entered the parking lot 100. In this case, the processor 18 reads the vehicle 110E's identification information Is by performing image parsing on the image data ID of vehicle 110E captured by the infrastructure sensor 12. 110E The vehicle registration number Is1 is captured in the image data ID. 110E .

[0046] Processor 18 reads the vehicle registration number Is1 110E The vehicle registration number Is1 of multiple vehicles 110 stored in the aforementioned database DB is compared to determine the vehicle 110E stored in the database DB. It should be noted that the processor 18 can also determine the vehicle company Is3 of vehicle 110E based on its image data ID. 110E And model Is4 110E And based on the car company Is3 110E And model Is4 110E To determine vehicle 110E in database DB.

[0047] Furthermore, the processor 18 determines which parking position PP within area A the vehicle 110E is parked in based on the image data ID of the vehicle 110E captured by the infrastructure sensor 12 after the vehicle 110E enters. Figure 5 In the example, parking space B4). Thus, processor 18 can determine which vehicle 110 stored in database DB is which vehicle 110 has entered area A, and determine the parking position PP of that vehicle 110. Therefore, processor 18 can obtain the address AD of each vehicle 110 in area A from database DB.

[0048] It should be noted that the processor 18 can also determine the parking position PP of the vehicle 110 within area A based on the vehicle 110's location information Ip. Specifically, the processor 120 of the vehicle 110 estimates the vehicle's position based on the GPS signal received from GPS satellites via GPS receiver 114A and the map data MP pre-stored in memory 122.

[0049] After entering area A (e.g., inside parking lot 100), processor 120 sends the estimated vehicle location as location information Ip to parking management system 10 via vehicle-mounted communicator 114 (e.g., DCM 114C). Processor 18 of parking management server 16 determines the parking location PP of vehicle 110 based on the location information Ip received from vehicle-mounted communicator 114 by communicator 14.

[0050] It should be noted that the processor 120 of vehicle 110 can also send, along with location information Ip (i.e., the vehicle's location), behavior information Ib of vehicle 110 after entering the parking lot 100 (e.g., vehicle speed and acceleration, steering wheel angle). Then, the processor 18 of parking management server 16 can determine the parking position PP of vehicle 110 based on the location information Ip and behavior information Ib. In this case, processor 18 can more accurately determine the parking position PP of vehicle 110 within area A.

[0051] Furthermore, the processor 18 of the parking management server 16 can also obtain the vehicle 110's identification information Is (e.g., vehicle registration number Is1) or the vehicle communicator 114's address AD when it receives location information Ip (and behavior information Ib) from the vehicle communicator 114. Then, the processor 18 can also determine which vehicle 110 in the database DB sent the location information Ip by comparing the obtained identification information Is or address AD with the identification information Is or address AD of multiple vehicles 110 stored in the database DB.

[0052] In this case, the processor 18 can determine the vehicle 110 that has entered area A and its parking position PP without using the status information Ia (that is, the image data ID of the vehicle 110 captured by the infrastructure sensor 12). Thus, the processor 18 can determine the parking position PP of each vehicle 110 that has entered area A and obtain the address AD of that vehicle 110.

[0053] In step S2, the processor 18 senses whether an abnormal condition AS has occurred based on the status information Ia. The following is an example of an abnormal condition AS. Figure 5 The following describes the situation where a fire AS1 occurred inside parking lot 100. Figure 5 In the example shown, there are multiple parking spaces Bn (n = 1, 2, 3, 4 ... 11, 12, 13, 14 ...) inside parking lot 100, and a fire AS1 is taking place at parking space B3.

[0054] Such a fire AS1 would be captured in the image data ID taken by the infrastructure sensor 12. Alternatively, a user of the parking lot 100 might operate a portable device to publish a message data MD reporting the occurrence of fire AS1 on an SNS or World Wide Web. Thus, the processor 18 can sense whether a fire AS1 has occurred by parsing the image data ID and message data MD collected after the start of step S1.

[0055] It should be noted that the processor 18 can also use a machine learning model LM (or an algorithm of artificial intelligence: AI) that represents the correlation between status information Ia (that is, image data ID and message data MD) and whether an abnormal situation AS (fire AS1 in this example) has occurred to sense whether an abnormal situation AS has occurred.

[0056] The machine learning model LM can be created, for example, by repeatedly providing state information Ia and decision data indicating whether an anomaly has occurred AS as a learning dataset to a machine learning device (e.g., supervised learning). It should be noted that the processor 18 can be configured to perform the functions of the machine learning device to generate the machine learning model LM. The generated machine learning model LM can be pre-stored in memory 20.

[0057] The processor 18 inputs the status information Ia collected after the start of step S1 into the machine learning model LM. The machine learning model LM outputs a determination result based on the input status information Ia, indicating whether an abnormal situation AS (fire AS1) has occurred. The processor 18 can sense whether an abnormal situation AS has occurred based on the determination result data output by the machine learning model LM.

[0058] Thus, in this embodiment, the processor 18 serves as an anomaly sensing unit 34 that senses an anomaly AS (specifically, a fire AS1) occurring within area A (e.g., inside the parking lot 100) based on status information Ia (specifically, image data ID and message data MD). Figure 2 The processor 18 determines whether an abnormal situation AS has occurred and proceeds to step S3; otherwise, it proceeds to step S9.

[0059] In step S3, the processor 18 functions as an anomaly sensing unit 34, determining the location OL of the anomaly AS based on the status information Ia. As an example, if a fire AS1 is sensed based on image data ID in step S2, the processor 18 determines the location OL of the fire AS1 inside the parking lot 100 based on the location of the infrastructure sensor 12 that captured the image data ID of the fire AS1 and the location of the image of the fire AS1 within that image data ID.

[0060] Instead, processor 18 can also determine the parking space B3 where the fire AS1 is occurring based on the image data ID captured of the fire AS1, and identify the location OL of the fire AS1 as parking space B3. In this case, the marker identifying parking space B3 (e.g., parking space number) can be located in a building (e.g., a wall or driveway) inside the parking lot 100. Then, processor 18 can identify the location OL of the fire AS1 as parking space B3 based on the marker of parking space B3 captured in the image data ID.

[0061] As another example, if fire AS1 is sensed to have occurred based on message data MD in step S2, the processor 18 determines the location OL based on the location information If of fire AS1 included in the message data MD. For example, the location information If of fire AS1 in the message data MD may include coordinates from a map application such as Google Maps (registered trademark) or keywords identifying parking lot 100 and parking space B3.

[0062] The processor 18 can determine the location OL of the fire AS1 based on the location information If included in the message data MD. Thus, in this step S3, the processor 18 functions as an anomaly sensing unit 34, determining the location OL of the abnormal situation AS based on the status information Ia (that is, the image data ID or the message data MD).

[0063] In step S4, the processor 18 generates a warning signal AL1 that notifies the occurrence of an abnormal situation AS. For example, the processor 18 generates a warning signal AL1 indicating that a fire AS1 has occurred as an abnormal situation AS and the location OL identified in step S3, and displays the warning signal AL1 on a display connected to the I / O interface 22 of the parking management server 16, or outputs the warning signal AL1 in voice form through a speaker connected to the I / O interface 22.

[0064] Instead, the processor 18 can also send the generated warning signal AL1 to an external device (e.g., the server of the parking lot management company) via the communicator 14 or the communication network NW. In this way, the operator of the parking management server 16 (or the external device) can immediately identify the occurrence of the abnormal situation AS and its location OL.

[0065] In step S5, the processor 18 sends a detection command C1 to the vehicles 110 parked around the location OL identified in step S3. The detection command C1 is a command to activate the external monitoring sensor 116 of the vehicles 110 parked around the location OL so that the external monitoring sensor 116 can detect the location OL.

[0066] In step S5, the processor 18 retrieves the addresses AD of vehicles 110 parked around the location OL (as determined in step S3) from the database DB. As an example, the processor 18 can retrieve the addresses AD of vehicles 110 parked around the location OL (as determined in step S3). Figure 5 In the example, the address AD is the address of all vehicles 110 parked around parking space B3 and within area A (e.g., inside parking lot 100).

[0067] As another example, processor 18 can also obtain the addresses AD of all vehicles 110 parked around the location OL, specifically those parked on a floor (e.g., the second floor of parking lot 100) of the parking lot 100 where the location OL is located. As yet another example, processor 18 can also, as described later, determine vehicles 110A, 110B, 110C, 110D, and 110E parked around the location OL from the vehicles 110 in region A based on status information Ia or location information Ip. Figure 5 ), and obtain the addresses AD of the identified vehicles 110A, 110B, 110C, 110D, and 110E.

[0068] The processor 18 refers to the acquired address AD and sends a detection command C1 to the vehicle communicator 114 of the vehicle 110 that has the address AD. Thus, in this embodiment, the processor 18 acts as the command sending unit 36 ​​that sends the detection command C1 to vehicles 110 parked around the location OL determined in step S3. Figure 2 To fulfill its function.

[0069] On the other hand, for the processor 120 of vehicle 110, when a detection command C1 is received via the vehicle communicator 114, the external monitoring sensor 116 is activated according to the detection command C1. The external monitoring sensor 116 continuously (e.g., periodically) detects the surrounding environment of vehicle 110. As a result, at least one of the vehicles 110 that has activated the external monitoring sensor 116 (e.g., Figure 5 The vehicles 110A, 110B, 110C, 110D, and 110E shown can detect the location OL using the external monitoring sensor 116. Then, the processor 120 sequentially sends the detection data DD (e.g., image data captured by a camera or radar) detected by the external monitoring sensor 116 to the parking management system 10 via the vehicle communication device 114.

[0070] It should be noted that the detection instruction C1 may include information about the communication address AD' (e.g., IP address) of the communicator 14 of the parking management system 10. In this case, the processor 120 can refer to the address AD' to send the detection data DD from the vehicle communicator 114 to the communicator 14.

[0071] The processor 18 of the parking management server 16 sequentially acquires detection data DD via the communicator 14 as status information Ia. Thus, the processor 18 can also acquire detection data DD as the action of acquiring status information Ia initiated in step S1 above, and continuously monitor the location OL based on the detection data DD.

[0072] In step S6, the processor 18 of the parking management server 16 determines whether the abnormal situation AS has been eliminated based on the status information Ia. For example, the processor 18 analyzes the image data ID captured by the infrastructure sensor 12 after it was determined to be an abnormal situation in step S2 and the detection data DD collected from the vehicle 110 as status information Ia after step S5, and determines whether the fire AS1 sensed in step S2 has been extinguished.

[0073] Instead, processor 18 can also determine whether fire AS1 has been extinguished by parsing the message data MD collected after the determination in step S2. At this time, processor 18 can sense whether fire AS1 has been extinguished by inputting status information Ia (image data ID, detection data DD, or message data MD) into the machine learning model LM.

[0074] Thus, processor 18 determines whether the abnormal condition AS has been eliminated (in this example, whether fire AS1 has been extinguished) based on status information Ia. Processor 18 terminates if it determines that the abnormal condition AS has been eliminated (i.e., yes). Figure 4The process shown, on the other hand, proceeds to step S7 if it is determined that the abnormal situation AS has not been eliminated (i.e., no).

[0075] In step S7, processor 18 generates a warning signal AL2 indicating that the abnormal situation AS is ongoing. For example, processor 18 generates warning signal AL2 and outputs it through the display or speaker of parking management server 16. Alternatively, processor 18 may also send the generated warning signal AL2 to an external device (e.g., the server of the parking lot management company) via communicator 14 or communication network NW.

[0076] In step S8, the processor 18 determines whether an action termination command (e.g., a shutdown command) has been received from the operator, the host controller, or the computer program PG. If the processor 18 has received an action termination command, it determines that it has received one and terminates the operation. Figure 4 The process shown, on the other hand, returns to step S6 if the determination is negative.

[0077] Thus, the processor 18 repeatedly executes the cycle of steps S6 to S8 until it is determined to be true in step S6 or S8, and continuously monitors the abnormal situation AS (fire AS1) based on the status information Ia (image data ID, detection data DD, message data MD).

[0078] On the other hand, if the determination in step S2 is negative, in step S9, the processor 18 determines, in the same manner as in step S8, whether the action end command has been accepted. The processor 18 terminates if the determination is positive. Figure 4 The process shown, on the other hand, returns to step S2 if the determination is negative.

[0079] As described above, in this embodiment, the processor 18 functions as an information acquisition unit 32, an anomaly sensing unit 34, and a command transmission unit 36. It senses an abnormal situation AS and causes the vehicle 110's external monitoring sensor 116 to detect the location OL where the abnormal situation AS occurs, according to the detection command C1, thereby monitoring the abnormal situation AS. Therefore, the information acquisition unit 32, the anomaly sensing unit 34, and the command transmission unit 36 ​​constitute a device 30 that uses the vehicle 110 within area A to monitor an abnormal situation AS occurring within area A. Figure 2 ).

[0080] In the device 30, the information acquisition unit 32 acquires state information Ia representing the state within the region A (step S1), the anomaly sensing unit 34 senses an abnormal situation AS based on the state information Ia (step S2), and determines the location OL where the sensed abnormal situation AS occurs (step S3).

[0081] Then, the command sending unit 36 ​​sends a detection command C1 to the parked vehicle 110 to activate the external monitoring sensor 116 installed in the vicinity of the occurrence location OL determined by the anomaly sensing unit 34 so that the external monitoring sensor 116 detects the occurrence location OL (step S5).

[0082] According to this configuration, an external monitoring sensor 116 mounted on the surrounding vehicle 110 can be used to monitor abnormal situations AS (e.g., fire AS1) occurring in area A. Therefore, abnormal situations AS can be effectively monitored, thereby improving the safety of area A.

[0083] Furthermore, in device 30, information acquisition unit 32 acquires image data ID captured by infrastructure sensor 12 installed in parking lot 100 as status information Ia, and anomaly sensing unit 34 senses anomaly AS based on the image data ID and determines the location OL where the anomaly AS occurs. With this configuration, anomaly AS and its location OL can be sensed with higher accuracy.

[0084] Furthermore, in the device 30, the information acquisition unit 32 also acquires the detection data DD detected by the external monitoring sensor 116 according to the detection command C1 sent by the command transmission unit 36 ​​as status information Ia. Based on this configuration, the processor 18 can continuously monitor abnormal conditions AS using the detection data DD.

[0085] Furthermore, in this embodiment, a vehicle 110 parked near the location OL where the abnormal situation AS occurs activates the external monitoring sensor 116 according to the detection command C1 sent by the command sending unit 36 ​​of the device 30, so that the external monitoring sensor 116 detects the location OL. With such a vehicle 110, the abnormal situation AS can be monitored more effectively by the external monitoring sensor 116.

[0086] Next, refer to Figure 6 and Figure 7 Other functions of the parking management system 10 will be described. In this embodiment, the processor 18 of the parking management server 16 executes... Figure 7 The flowchart illustrates the abnormal situation monitoring method. It should be noted that... Figure 7 In the process shown, for and Figure 5 The same process is labeled with the same step numbers, and repeated descriptions are omitted.

[0087] exist Figure 7In the illustrated process, processor 18 executes step S10 after step S4. In step S10, processor 18 determines, based on status information Ia (specifically, image data ID of vehicle 110) or location information Ip of vehicle 110 within region A, vehicles 110A, 110B, 110C, 110D, and 110E that should activate the external monitoring sensor 116.

[0088] As described above, the processor 18 can determine the parking position PP of each vehicle 110 that has entered area A (e.g., the interior of parking lot 100) based on the image data ID of the vehicle 110 captured by the infrastructure sensor 12 or the location information Ip of the vehicle 110. Based on the determined parking position PP of each vehicle 110, the processor 18 identifies vehicles 110A, 110B, 110C, 110D, and 110E from the vehicles 110 in area A that have external monitoring sensors 116 that allow the location OL of the abnormal situation AS (fire AS1) to fall within the detection range DR.

[0089] Here, each vehicle 110's external monitoring sensor 116 has a defined detection range DR. For example, if a vehicle 110 is equipped with multiple external monitoring sensors 116, the detection range DR of the multiple external monitoring sensors 116 can be the entire surrounding area of ​​the vehicle 110 (that is, the area in front, behind, to the right, and to the left of the vehicle 110) (e.g., the range of a distance δ [m] from the center of the vehicle 110).

[0090] As an example, the detection range DR information (e.g., the distance δ mentioned above) of each vehicle 110 is pre-stored in a database DB in association with personal information Iv, determination information Is, and address AD. The processor 18 can retrieve the detection range DR of each vehicle 110 from the database DB.

[0091] Instead, the processor 18 can also refer to the vehicle 110's determination information Is (e.g., car company Is3 and model Is4) and access the World Wide Web of the car company Is3 of the vehicle 110 through the communication network NW to obtain the detection range DR information of the vehicle 110.

[0092] The processor 18 can estimate the detection range DR of each vehicle 110 within area A based on the determined parking position PP of the vehicle 110 and the detection range DR of the vehicle 110 obtained from the database DB or a web application. For example, in Figure 5 In the example shown, the location OL where fire AS1 occurred falls within the detection range DR of vehicles 110A, 110B, 110C, 110D, and 110E that are parked nearby.

[0093] In this case, based on the estimation result of the detection range DR, the processor 18 identifies vehicles 110A, 110B, 110C, 110D and 110E from vehicles 110 in region A as vehicles 110 having an external monitoring sensor 116 that makes the location OL fall within the detection range DR.

[0094] It should be noted that the processor 18 can also determine the orientation φ of the vehicle 110 in area A (specifically, the forward direction of the vehicle 110) based on the status information Ia or the position information Ip. For example, if a vehicle 110 is equipped with an external monitoring sensor 116 that can only monitor the front of the vehicle 110, its detection range DR can be the range in front of the vehicle 110 (the range of the distance δ [m] in front of the vehicle 110).

[0095] To estimate the detection range DR of such a vehicle 110 within area A, it is necessary to obtain the orientation φ of the vehicle 110 parked within area A. As an example, the processor 18 determines the orientation φ of the vehicle 110 within area A by parsing the image data ID of the vehicle 110 captured by the infrastructure sensor 12, which is considered as state information Ia.

[0096] As another example, processor 18 can also determine the orientation φ of vehicle 110 within area A based on the location information Ip (and behavior information Ib) of vehicle 110. Then, processor 18 infers the detection range DR of vehicle 110 within area A based on the determined parking position PP and orientation φ of vehicle 110, as well as the detection range DR (distance δ) of vehicle 110. Processor 18 can then determine vehicles 110A, 110B, 110C, 110D, and 110E based on the detection range DR inferred from the parking position PP and orientation φ.

[0097] Instead, the processor 18 can also identify a vehicle 110 parked at position PP within a distance Δ (e.g., 5 [m]) from the location OL as the vehicle for which the external monitoring sensor 116 should be activated. This distance Δ can be predefined by the operator of the parking management server 16, taking into account the detection range DR of the vehicle 110.

[0098] For example, in Figure 5In the example shown, vehicles 110A, 110B, 110C, 110D, and 110E are parked within a distance Δ from the location OL. In this case, the processor 18, based on the location OL determined in step S3 above and the predetermined distance Δ, identifies vehicles 110A, 110B, 110C, 110D, and 110E from vehicles 110 in area A as vehicles 110 equipped with an external monitoring sensor 116 that allows the location OL to fall within the detection range DR.

[0099] As described above, the processor 18 determines the parking position PP of the vehicle 110 in area A based on the status information Ia (specifically, image data ID) or the location information Ip, and based on the determined parking position PP, determines vehicles 110A, 110B, 110C, 110D, and 110E from the vehicles 110 in area A that should activate the external monitoring sensor 116. Therefore, in this embodiment, the processor 18 serves as the vehicle determination unit 38 for determining vehicles 110A, 110B, 110C, 110D, and 110E that should activate the external monitoring sensor 116. Figure 6 To fulfill its function.

[0100] After step S10, processor 18 executes step S5, functioning as instruction sending unit 36, and sends detection instruction C1 to vehicles 110A, 110B, 110C, 110D, and 110E identified in step S10. The processors 120 of vehicles 110A, 110B, 110C, 110D, and 110E activate their respective external monitoring sensors 116 to detect the location OL.

[0101] As described above, in this embodiment, the processor 18 of the parking management server 16 functions as an information acquisition unit 32, an anomaly sensing unit 34, a command sending unit 36, and a vehicle determination unit 38, monitoring for anomalies AS using vehicles 110A, 110B, 110C, 110D, and 110E within area A. Therefore, the information acquisition unit 32, the anomaly sensing unit 34, the command sending unit 36, and the vehicle determination unit 38 constitute a device 40 for monitoring anomalies AS using vehicles 110 within area A. Figure 6 ).

[0102] In the device 40, the vehicle determination unit 38 determines, based on the status information Ia (specifically, the image data ID of the vehicle 110) or the location information Ip of the vehicle 110 in area A, the vehicles 110A, 110B, 110C, 110D and 110E that should activate the external monitoring sensor 116 (step S10).

[0103] Then, the command sending unit 36 ​​sends a detection command C1 (step S5) to the vehicles 110A, 110B, 110C, 110D, and 110E identified by the vehicle determination unit 38. According to this configuration, vehicles 110A, 110B, 110C, 110D, and 110E parked around the incident location OL can be effectively screened, and the external monitoring sensors 116 of these vehicles can be activated. Therefore, the incident location OL can be detected more effectively using the external monitoring sensors 116 of vehicles 110A, 110B, 110C, 110D, and 110E.

[0104] Furthermore, in the device 40, the vehicle determination unit 38 determines the parking position PP of the vehicle 110 in area A based on the status information Ia (image data ID of vehicle 110) or the position information Ip, and based on the determined parking position PP, determines vehicles 110A, 110B, 110C, 110D and 110E from the vehicles 110 in area A that have an external monitoring sensor 116 that makes the occurrence location OL fall within the detection range DR.

[0105] Furthermore, the vehicle determination unit 38 determines the orientation φ of the vehicle 110 within area A based on the status information Ia (image data ID of vehicle 110) or the location information Ip, and determines vehicles 110A, 110B, 110C, 110D, and 110E based on the determined parking position PP and orientation φ. According to this configuration, vehicles 110A, 110B, 110C, 110D, and 110E that can reliably detect the location OL can be effectively screened from the vehicles 110 within area A.

[0106] It should be noted that the processor 18 of the parking management server 16 can execute according to the computer program PG pre-stored in the memory 20. Figure 4 or Figure 7 The process is shown. Furthermore, the functions of the devices 30 or 40 (i.e., the information acquisition unit 32, the anomaly sensing unit 34, the command sending unit 36, and the vehicle determination unit 38) executed by the processor 18 can be functional modules implemented by the computer program PG.

[0107] It should be noted that, as a method for monitoring abnormal situations (AS), an example is shown. Figure 4 and Figure 7 The process, but it can also be... Figure 4 and Figure 7 Various changes are applied to the process. For example, in the above embodiment, the processor 18 is modified... Figure 4 (or Figure 7The case where detection data DD is obtained from vehicle 110 (or vehicles 110A, 110B, 110C, 110D, and 110E) after step S5 in the process is described as being used as status information Ia.

[0108] However, it is not limited to this, in Figure 4 (or Figure 7 In the process shown, processor 18 may also choose not to perform the action of acquiring detection data DD from vehicle 110 (or vehicles 110A, 110B, 110C, 110D, and 110E) as status information Ia after step S5. In this case, processor 120 of vehicle 110 (or vehicles 110A, 110B, 110C, 110D, and 110E) can cause the on-board communicator 114 to transmit the detection data DD detected by the external monitoring sensor 116 to an external device different from the parking management server 16.

[0109] For example, processor 120 can activate inter-vehicle communicator 114B to send detection data DD to another vehicle, or it can activate DCM 114C to send detection data DD to external devices such as the car company's management server or base station. This allows notification of an abnormal situation AS (fire AS1) to the outside of parking lot 100. Furthermore, it can also... Figure 4 or Figure 7 Steps S6 to S8 are omitted in the flowchart shown. Furthermore, in Figure 4 or Figure 7 In the process shown, if it is determined in step S2 that it is true, step S4 can be executed, and then step S3 can be executed.

[0110] Furthermore, after step S5, when the detection data DD is detected by the external monitoring sensor 116 within a predetermined period, the processor 120 of vehicle 110 (or vehicles 110A, 110B, 110C, 110D, and 110E) can also automatically control the drive mechanism, steering mechanism, and braking mechanism, thereby enabling vehicle 110 (or vehicles 110A, 110B, 110C, 110D, and 110E) to automatically retreat to a safe parking position PP' isolated from the location OL of the abnormal situation AS (fire AS1).

[0111] In this scenario, the processor 18 of the parking management server 16 can determine a retreat route for vehicle 110 (or vehicles 110A, 110B, 110C, 110D, and 110E) based on the image data ID captured by the infrastructure sensor 12, and send an autonomous driving command to vehicle 110 (or vehicles 110A, 110B, 110C, 110D, and 110E) to perform autonomous driving. As described above, this allows for... Figure 4 or Figure 7 The process shown is subject to various changes.

[0112] It should be noted that, in Figure 5 In the example shown, an abnormal situation AS is described as a fire AS1 occurring inside parking lot 100 (specifically, parking space B3). However, in the event of an incident AS2 or accident AS3 occurring as an abnormal situation AS, or in the case of an abnormal situation AS occurring around parking lot 100, the processor 18 of parking management server 16 executes... Figure 4 or Figure 7 The process shown can also be used to monitor the abnormal situation AS by using vehicles 110 parked around the location OL where the abnormal situation AS occurs.

[0113] In this case, the processor 18 can send a detection command C1 to the vehicles 110 parked around the parking lot 100 in step S5 described above. The present disclosure has been described above through embodiments, but the above embodiments do not limit the invention as defined in the claims.

Claims

1. A device for monitoring abnormal situations occurring in a parking lot area by utilizing vehicles within or around the parking lot, comprising: The information acquisition unit acquires status information representing the state within the area; An anomaly sensing unit senses the anomaly based on the state information and determines the location where the sensed anomaly occurs. The command sending unit sends a command to the parked vehicle to activate the external monitoring sensor of the vehicle located around the location of the incident determined by the anomaly sensing unit, so that the external monitoring sensor detects the location of the incident. as well as The vehicle determination unit, based on the status information or the location information of vehicles within the area, determines from the vehicles within the area the parked vehicle that should trigger the external monitoring sensor. The vehicle determining unit is configured as follows: The parking location of the vehicle in the area is determined based on the status information or the location information; Based on the determined parking location and the detection range of the external monitoring sensors of the vehicles located in the area, the detection range of the vehicles in the area is estimated. as well as Identify, from among the vehicles in the area, the parked vehicle that has the external monitoring sensor that causes the location of the incident to fall within the presumed detection range.

2. The apparatus according to claim 1, wherein, The information acquisition unit acquires image data captured by infrastructure sensors installed in the parking lot as the status information. The anomaly sensing unit senses the anomaly based on the image data and determines the location where it occurs.

3. The apparatus according to claim 1, The instruction sending unit sends the instruction to the vehicle that is currently parked, as determined by the vehicle determining unit.

4. The apparatus according to claim 1, wherein, The vehicle determination unit also determines the orientation of vehicles within the area based on the status information or the location information. The vehicle determination unit also estimates the detection range of vehicles within the area based on the determined orientation.

5. The apparatus according to claim 1, wherein, The information acquisition unit also acquires the detection data detected by the external monitoring sensor according to the instruction sent by the instruction sending unit as the status information.

6. A vehicle equipped with external monitoring sensors, wherein, The vehicle activates the external monitoring sensor according to the instruction sent by the instruction sending unit of the device as described in claim 1, so that the external monitoring sensor detects the location of the occurrence.

7. A method for monitoring abnormal situations occurring within or around a parking lot using vehicles in that area, wherein, The processor acquires state information representing the state within the region. The processor senses the abnormal situation based on the state information and determines the location where the sensed abnormal situation occurred. The processor will activate the external monitoring sensors of the vehicle parked in the vicinity of the determined incident location, so that the external monitoring sensors can detect the incident location and send a command to the parked vehicle. Based on the status information or the location information of vehicles within the area, the processor determines from the vehicles within the area the parked vehicle that should trigger the external monitoring sensor. In order to determine the vehicle that is currently parked, the processor is configured to: The parking location of the vehicle in the area is determined based on the status information or the location information; Based on the determined parking location and the detection range of the external monitoring sensors of the vehicles located in the area, the detection range of the vehicles in the area is estimated. as well as Identify, from among the vehicles in the area, the parked vehicle that has the external monitoring sensor that causes the location of the incident to fall within the presumed detection range.

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