KR102588456B1 - Method for determining whether there is any emergency in autonomous vehicle and responding against the emergency and server using the same - Google Patents

Abstract

In a method of supporting response by determining whether an emergency exists in an autonomous vehicle, (a) a control server collects distribution information of passengers inside the autonomous vehicle obtained by a predetermined sensor, and Determining whether an emergency situation has occurred in the autonomous vehicle by referring to distribution information of passengers inside; and (b) when it is determined that an emergency situation has occurred in the self-driving vehicle, supporting the control server to determine and respond to an emergency situation in the self-driving vehicle by referring to the location information of the self-driving vehicle; Disclosed is a method comprising:

Description

Method for determining whether an emergency exists in an autonomous vehicle and supporting response, and a server using the same

The present invention relates to a method for determining whether an emergency exists in an autonomous vehicle and supporting response, and a server using the same.

Recently, the market for autonomous vehicles has been developing significantly. As a result, buses, trains, and taxis can now operate autonomously, and the safety of passengers riding in self-driving vehicles has become more important.

However, various emergencies that can occur inside an autonomous vehicle can occur inside and outside the vehicle. In particular, emergency situations that occur inside an autonomous vehicle are difficult to recognize and deal with quickly, so the safety of passengers in the vehicle may be a problem. You can.

Therefore, improvement measures to solve the above problems are required.

The purpose of the present invention is to solve all of the above-mentioned problems.

In addition, another purpose of the present invention is to recognize emergency situations within the vehicle and support corresponding follow-up processing by referring to the distribution information of passengers inside the autonomous vehicle obtained by a predetermined sensor.

In order to achieve the object of the present invention as described above and realize the characteristic effects of the present invention described later, the characteristic configuration of the present invention is as follows.

According to one aspect of the present invention, in a method for determining whether an emergency exists in an autonomous vehicle and supporting response, (a) the control server provides distribution information of passengers inside the autonomous vehicle obtained by a predetermined sensor; collecting and determining whether an emergency situation has occurred in the autonomous vehicle by referring to distribution information of passengers inside the autonomous vehicle; and (b) when it is determined that an emergency situation has occurred in the self-driving vehicle, supporting the control server to determine and respond to an emergency situation in the self-driving vehicle by referring to the location information of the self-driving vehicle; A method comprising:

As an example, in step (a), if it is determined that the emergency situation has occurred, the control server refers to the distribution information of passengers inside the autonomous vehicle and selects one of the plurality of categories corresponding to the emergency situation. It is determined whether it corresponds to a category, and in step (b), if it is determined that it corresponds to a specific category among the plurality of categories corresponding to the emergency situation, the control server provides information about a plurality of facilities corresponding to the specific category. Using information about a specific facility determined with reference to the location of the autonomous vehicle, information about the specific category of the emergency situation of the autonomous vehicle and location information of the autonomous vehicle are provided to the specific facility. A method characterized by transmitting about.

As an example, in step (a), the control server collects distribution information of the passengers inside the autonomous vehicle, at least one of an image sensor, an audio sensor, a pressure sensor, and a fire sensor inside the autonomous vehicle. The distribution information is collected by some, wherein the number of at least one passenger of the autonomous vehicle captured by the image sensor, the ratio of the passenger occupying the seat, and the ratio of the passenger occupying the seat are selected. 1 Determination of whether the number of unseated passengers is greater than the second critical factor even though it is less than the critical factor, and whether the number of passengers greater than the third critical factor is concentrated within a predetermined detailed space compared to the area of the interior space of the autonomous vehicle and the number of passengers. Determining whether the distribution information corresponds to an abnormal distribution with reference to at least one of the determinations as to whether the distribution information corresponds to an abnormal distribution, and determining whether the voice of the passenger of the autonomous vehicle obtained by the audio sensor is fast, pitched, and profane; Determination of whether a specific passenger of the self-driving vehicle is talking to himself, whether the self-talk continues for a predetermined period of time, determination of whether a specific passenger of the self-driving vehicle is talking to other passengers, and determination of whether the specific passenger of the self-driving vehicle is talking to other passengers. When talking to a passenger, it is determined whether the distribution information corresponds to an abnormal distribution by referring to at least one of the abnormality judgments about the gesture based on the information of the image sensor, and the autonomous driving detected by the pressure sensor Determination of whether the force applied to the floor or wall of the vehicle is higher than a high critical pressure, and when the force applied to the floor or wall of the autonomous vehicle is higher than the low critical pressure, the image sensor or the It is determined whether the distribution corresponds to an abnormality by referring to at least one of the gestures or voices of other passengers based on the audio sensor, and the smoke inside the autonomous vehicle detected by the fire sensor is higher than or equal to a high critical density. Determination of recognition, distribution of abnormality with reference to at least one of the gestures or voices of other passengers based on the image sensor or the audio sensor while the smoke inside the autonomous vehicle is above a low critical density A method characterized by determining whether a method is applicable.

As an example, in step (a), determining at least one cause point among the passengers whose risk probability determined by a predetermined sensor is greater than or equal to a predetermined risk probability, and determining distribution information of passengers centered on the cause point; , If the cause point is a specific passenger whose risk probability is greater than or equal to the predetermined risk, and the distribution information of the other passengers is determined to be concentrated at a location greater than a preset first distance from the specific passenger, a plurality of categories corresponding to the emergency situation are provided. If it is determined that it falls under the first category, which is a category related to the occurrence of a serious crime, and the distribution information of the other passengers is determined to be around the specific passenger by clustering in a close location less than the preset second distance from the specific passenger, Characterized in that it is determined to fall into a second category, which is a category related to patient occurrence, among the plurality of categories corresponding to the emergency situation, and when the cause point is a specific point in the autonomous vehicle that is more than the predetermined risk probability, the passenger If it is determined that the distribution information is concentrated at a location greater than the preset third distance from the specific point, it is judged to fall into the third category, which is the category related to breakdown/fire occurrence, among the plurality of categories corresponding to the emergency situation. How to feature.

As an example, in step (a), the control server additionally collects driving data of the autonomous vehicle and provides information on the speed, direction, and acceleration of the autonomous vehicle included in the specific driving data corresponding to a specific time. Critical distribution information for distinguishing between normal distribution information and abnormal distribution information, which is a standard for obtaining information and determining whether an emergency situation has occurred in the self-driving vehicle by the control server with reference to the distribution information, A method characterized in that adjustment is made with reference to information about the speed, direction, and acceleration of the autonomous vehicle.

As an example, the control server refers to the history information of the passengers inside the autonomous vehicle - the history information includes at least part of the medical history information and crime information of the passengers - and provides the normal distribution information and the A method characterized by determining the critical distribution information that distinguishes abnormal distribution information, and lowering at least some of the standards corresponding to location data and movement data of passengers corresponding to the critical distribution information.

According to another aspect of the present invention, a server that determines whether an emergency exists in an autonomous vehicle and supports response, comprising: at least one memory storing instructions; and at least one processor configured to execute the instructions, wherein the processor: (I) collects distribution information of passengers inside the autonomous vehicle obtained by a predetermined sensor, and A process for determining whether an emergency situation has occurred in the autonomous vehicle, with reference to passenger distribution information; and (II) when it is determined that an emergency situation has occurred in the autonomous vehicle, a process for determining and responding to an emergency situation in the autonomous vehicle by referring to the location information of the autonomous vehicle. A server with .

As an example, if the processor determines that the emergency situation has occurred in the (I) process, one of the plurality of categories corresponding to the emergency situation is selected with reference to the distribution information of passengers inside the autonomous vehicle. and, in the process (II), if it is determined that it falls under a specific category among the plurality of categories corresponding to the emergency situation, the autonomous vehicle's information on the plurality of facilities corresponding to the specific category is determined. Characterized by transmitting information about the specific category of the emergency situation of the autonomous vehicle and location information of the autonomous vehicle to the specific facility using information about the specific facility determined with reference to the location. A server that does.

As an example, in the process (I), the processor collects distribution information of the passengers inside the autonomous vehicle, at least some of the image sensor, audio sensor, pressure sensor, and fire sensor inside the autonomous vehicle. The distribution information is collected by, wherein the number of at least one passenger of the autonomous vehicle captured by the image sensor, the ratio of seats occupied by the passengers, and the ratio of seats occupied by the passengers are first Determination of whether the number of unseated passengers is more than the second critical factor even though it is less than the critical number, and whether the number of passengers is more than the third critical number crowded within a predetermined detailed space compared to the area of the interior space of the self-driving vehicle and the number of passengers. Determining whether the distribution information corresponds to an abnormal distribution with reference to at least one of the determinations, determining the speed, pitch, and profanity of the voice of the passenger of the autonomous vehicle acquired by the audio sensor, and Determination of whether a specific passenger of the self-driving vehicle is talking to himself, whether the self-talk continues for a predetermined period of time, determination of whether a specific passenger of the self-driving vehicle is talking to other passengers, whether a specific passenger of the self-driving vehicle is talking to other passengers When talking with the user, the autonomous vehicle determines whether the distribution information corresponds to an abnormal distribution by referring to at least one of the abnormality determinations for the gesture based on the information of the image sensor, and detecting the autonomous vehicle using the pressure sensor. Determination of whether the force applied to the floor or wall of the autonomous vehicle is higher than a high threshold pressure, and the image sensor or the audio in a state where the force applied to the floor or wall of the autonomous vehicle is higher than the low threshold pressure Determine whether it corresponds to an abnormal distribution by referring to at least one of the gestures or voices of other passengers based on the sensor, and determine whether the smoke inside the autonomous vehicle detected by the fire sensor is higher than a high critical density. Determination of whether or not, in a state where the smoke inside the autonomous vehicle is above a low critical density, an abnormality distribution is determined by referring to at least one of the gestures or voices of other passengers based on the image sensor or the audio sensor. A server characterized in that it determines whether it is applicable.

As an example, in the process (I), determining at least one cause point among the passengers whose risk probability determined by a predetermined sensor is greater than or equal to a predetermined risk probability, and determining distribution information of passengers centered on the cause point; , If the cause point is a specific passenger whose risk probability is greater than or equal to the predetermined risk, and the distribution information of the other passengers is determined to be concentrated at a location greater than a preset first distance from the specific passenger, a plurality of categories corresponding to the emergency situation are provided. If it is determined that it falls under the first category, which is a category related to the occurrence of a serious crime, and the distribution information of the other passengers is determined to be around the specific passenger by clustering in a close location less than the preset second distance from the specific passenger, Characterized in that it is determined to fall into a second category, which is a category related to patient occurrence, among the plurality of categories corresponding to the emergency situation, and when the cause point is a specific point in the autonomous vehicle that is more than the predetermined risk probability, the passenger If it is determined that the distribution information is concentrated at a location greater than the preset third distance from the specific point, it is judged to fall into the third category, which is the category related to breakdown/fire occurrence, among the plurality of categories corresponding to the emergency situation. Featured server.

As an example, in the process (I), the processor additionally collects driving data of the autonomous vehicle, and information about the speed, direction, and acceleration of the autonomous vehicle included in the specific driving data corresponding to a specific time. Obtains, and the processor determines whether an emergency situation has occurred in the autonomous vehicle with reference to the distribution information, threshold distribution information that distinguishes between normal distribution information and abnormal distribution information, which serves as a standard for determining whether an emergency situation has occurred in the autonomous vehicle. A server that makes adjustments based on information about the speed, direction, and acceleration of the driving vehicle.

As an example, the processor may refer to history information of the passengers inside the autonomous vehicle - the history information includes at least part of the medical history information and crime information of the passengers - to determine the normal distribution information and the abnormality. A server that determines the critical distribution information for classifying distribution information, and lowers at least some of the standards corresponding to location data and movement data of passengers corresponding to the critical distribution information.

In addition, a computer-readable recording medium for recording a computer program for executing the method of the present invention is further provided.

The present invention has the effect of recognizing emergency situations within a vehicle and supporting follow-up processing corresponding thereto, by referring to information on the distribution of passengers inside an autonomous vehicle obtained by a predetermined sensor.

The following drawings attached for use in explaining embodiments of the present invention are only some of the embodiments of the present invention, and to those skilled in the art (hereinafter “those skilled in the art”), the invention Other drawings can be obtained based on these drawings without further work being done.
Figure 1 is a diagram schematically showing a server for determining whether an emergency exists in an autonomous vehicle and supporting response, according to an embodiment of the present invention.
Figure 2 is a flowchart schematically showing the process performed in a method for determining whether an emergency situation exists in an autonomous vehicle and supporting response, according to an embodiment of the present invention.
FIG. 3A is a diagram schematically showing a case of a patient among examples of the existence of an emergency situation in an autonomous vehicle, according to an embodiment of the present invention.
FIG. 3B is a diagram schematically showing a case of a crime occurring among examples of an emergency situation in an autonomous vehicle according to an embodiment of the present invention.

The detailed description of the present invention described below refers to the accompanying drawings, which show by way of example specific embodiments in which the present invention may be practiced to make clear the objectives, technical solutions and advantages of the present invention. These embodiments are described in sufficient detail to enable those skilled in the art to practice the invention.

Additionally, throughout the description and claims, the word “comprise” and variations thereof are not intended to exclude other technical features, attachments, components or steps. Other objects, advantages and features of the invention will appear to those skilled in the art, partly from this description and partly from practice of the invention. The examples and drawings below are provided by way of example and are not intended to limit the invention.

Moreover, the present invention encompasses all possible combinations of the embodiments shown herein. It should be understood that the various embodiments of the present invention are different from one another but are not necessarily mutually exclusive. For example, specific shapes, structures and characteristics described herein with respect to one embodiment may be implemented in other embodiments without departing from the spirit and scope of the invention. Additionally, it should be understood that the location or arrangement of individual components within each disclosed embodiment may be changed without departing from the spirit and scope of the invention. Accordingly, the detailed description that follows is not intended to be taken in a limiting sense, and the scope of the invention is limited only by the appended claims, together with all equivalents to what those claims assert, if properly described. Similar reference numbers in the drawings refer to identical or similar functions across various aspects.

Hereinafter, in order to enable those skilled in the art to easily practice the present invention, preferred embodiments of the present invention will be described in detail with reference to the attached drawings.

Figure 1 is a diagram schematically showing a server for determining whether an emergency exists in an autonomous vehicle and supporting response, according to an embodiment of the present invention.

As shown in FIG. 1, the control server 100 for determining whether an emergency exists in an autonomous vehicle of the present invention and supporting response may include a memory 110 and a processor 120.

Here, self-driving vehicles may include means of transportation that can operate autonomously, such as public buses, trains, and taxis.

The memory 110 of the control server 100 may store instructions to be executed by the processor 120. Specifically, the instructions are code generated for the purpose of allowing the control server 100 to function in a specific manner. As such, it may be stored in a computer-usable or computer-readable memory capable of being directed to a computer or other programmable data processing equipment. Instructions may perform processes to execute functions described in the specification of the present invention.

Additionally, the processor 120 of the control server 100 may include hardware components such as a Micro Processing Unit (MPU) or Central Processing Unit (CPU), cache memory, and data bus. In addition, it may further include an operating system and software configuration of an application that performs a specific purpose.

Additionally, the control server 100 may be linked to a database (not shown). Here, the database (not shown) is a flash memory type, hard disk type, multimedia card micro type, or card type memory (for example, SD or XD memory). , RAM (Random Access Memory), SRAM (Static Random Access Memory), ROM (ReadOnly Memory, ROM), EEPROM (Electrically Erasable Programmable ReadOnly Memory), PROM (Programmable ReadOnly Memory), magnetic memory, magnetic disk, and optical disk. It may include at least one type of storage medium, but is not limited to this and may include any medium capable of storing data. In addition, the database (not shown) may be installed separately from the control server 100, or alternatively, may be installed inside the control server 100 to transmit data or record received data, and, unlike shown, may have more than one database (not shown). It may be implemented separately, and this may vary depending on the implementation conditions of the invention.

Meanwhile, the control server 100 may be a server operated separately outside the self-driving vehicle, but is not limited to this, and in some cases, the control server 100 may be mounted inside the self-driving vehicle.

A method for determining whether an emergency exists in an autonomous vehicle and supporting response according to an embodiment of the present invention configured as described above will be described with reference to FIGS. 2 to 3B as follows.

First, Figure 2 is a flowchart schematically showing the process performed in a method for determining whether an emergency situation exists in an autonomous vehicle and supporting response, according to an embodiment of the present invention.

Referring to FIG. 2, the processor 120 collects distribution information of passengers inside the self-driving vehicle obtained by a predetermined sensor, and determines an emergency situation within the self-driving vehicle by referring to the distribution information of passengers inside the self-driving vehicle. It is determined whether an emergency has occurred in the autonomous vehicle (S201), and if it is determined that an emergency has occurred in the autonomous vehicle, the emergency situation in the autonomous vehicle can be determined and supported by referring to the location information of the autonomous vehicle (S202). .

Here, determining that an emergency situation has occurred means that the processor 120 refers to the distribution information of passengers inside the autonomous vehicle and determines which category among the plurality of categories corresponding to the emergency situation falls.

Here, the plurality of categories can be divided into categories such as criminal acts such as wielding a knife or committing violence, equipment defects due to engine failure, fires, and patients suddenly collapsing.

In addition, if it is determined that the emergency situation falls under a specific category among the plurality of categories, the processor 120 refers to the location of the autonomous vehicle where the emergency situation occurred among the information on the plurality of facilities corresponding to the specific category. Using the information about the specific facility determined, information within the autonomous vehicle and location information of the autonomous vehicle can be transmitted to the specific facility.

Here, a specific facility may be a police station or police car located near an autonomous vehicle in the event of a criminal act, a nearby police station or repair shop in case of a defect in the device in case traffic is paralyzed, or in case of a fire. If smoke is detected, the system can be connected to a nearby fire station, and if a patient complains of pain occurs inside the self-driving vehicle, the system can be connected to a nearby hospital or 119.

Additionally, the occurrence of a crime, a fire, a patient, etc. can be determined by a certain sensor installed inside the autonomous vehicle.

Here, the predetermined sensor may be an image sensor, an audio sensor, a pressure sensor, a fire sensor, etc.

Additionally, although the image sensor 301 is not shown here, it may be replaced or added with at least one of an audio sensor, a pressure sensor, and a fire sensor.

More specifically, the image sensor 301 detects the number of passengers in the autonomous vehicle 300, the percentage of seats occupied by passengers, and passengers who are not seated even though the percentage of seats occupied by passengers is less than 50%. It is possible to determine whether the distribution is abnormal by determining whether the number of passengers is more than

In addition, determination of the speed, pitch, and profanity of the voice of the passenger of the self-driving vehicle acquired by an audio sensor, determination of whether a specific passenger of the self-driving vehicle is talking to himself, and whether the self-talk continues for a predetermined period of time. , determining whether a specific passenger of the self-driving vehicle is talking to another passenger, determining that the specific passenger of the self-driving vehicle is talking to another passenger, potentially determining that the passenger is a high-risk passenger, and image sensor 301 ), it will be possible to determine whether the distribution information corresponds to an abnormal distribution with reference to at least one of the determinations of whether the gesture of the passenger with a potentially high risk probability is abnormal. Here, the distribution information may be distribution information about all passengers boarding the autonomous vehicle, but may also be information about the distribution between the specific passenger and the other passengers. Here, in the case of high-threshold voice or higher, the probability of risk corresponding to a specific passenger will increase, so by adjusting the critical distribution information to be a little closer to the normal distribution, even if the distribution of passengers identified by the image sensor, etc. deviates slightly from the normal distribution, It can be judged to correspond to an abnormal distribution, and on the other hand, if it is a low-threshold voice abnormality, the risk probability corresponding to a specific passenger will be somewhat lower, so by adjusting the critical distribution information to be a little further away from the normal distribution, the distribution of passengers If it deviates only a little from the normal distribution, it can be treated as a normal distribution, and only if it deviates a lot from the normal distribution, it can be judged to be an abnormal distribution.

Meanwhile, the pressure sensor determines whether the force applied to the floor or wall of the autonomous vehicle 300 is higher than a high critical pressure and determines whether the force applied to the floor or wall of the autonomous vehicle 300 is low (低) It is possible to determine whether the pressure is above the critical pressure, and accordingly adjust the critical distribution information that serves as a standard for determining whether the pressure is abnormal. In other words, if the pressure is above a high critical pressure, the probability of risk corresponding to a specific passenger will increase, so by adjusting the critical distribution information to be a little closer to the normal distribution, it is recognized that even if the distribution of passengers slightly deviates from the normal distribution, it is an abnormal distribution. Conversely, if the pressure is above the low critical pressure, the risk probability corresponding to a specific passenger will be somewhat lower, so by adjusting the critical distribution information to be a little further away from the normal distribution, if the distribution of passengers is slightly outside the normal distribution, is treated as a normal distribution, and only when it deviates significantly from the normal distribution can it be judged to be an abnormal distribution.

In this example, the risk probability can be adjusted by additionally referring to the image sensor or audio sensor, and the critical distribution information can also be adjusted accordingly.

In addition, the fire sensor determines whether the smoke inside the autonomous vehicle is above a high critical density and whether the smoke inside the autonomous vehicle 300 is above a low critical density. , Similar to what was mentioned above, it will be possible to determine whether there is an abnormal distribution by adjusting the critical distribution information, and detailed description will be omitted.

In the above, we did not mention an example of adjusting the critical distribution information for the image sensor, but of course the critical distribution information can be adjusted for the image sensor as well. As will be explained later, when a criminal or patient is on board, the critical distribution information can be adjusted. By adjusting the information, it will be possible to determine the abnormal distribution.

Below, a method for determining and responding to an emergency in an autonomous vehicle according to an embodiment of the present invention will be explained in more detail with an example.

FIG. 3A is a diagram schematically showing a case of a crime occurring among examples of an emergency situation in an autonomous vehicle, according to an embodiment of the present invention.

Referring to FIG. 3A, when the risk probability determined by a predetermined sensor is greater than or equal to a predetermined risk probability, at least one cause point may be determined, and the degree of distribution of passengers may be determined centered on the cause point.

For example, when the probability of risk for a specific passenger (310-1) is 90% through the image sensor 301 in the autonomous vehicle 300, the distribution of other passengers (320-1) becomes the causal point. If it is determined that the passenger is crowded at a location of 2 m or more from a specific passenger (310-1), it can be determined that it falls into the crime-related category among the plurality of categories corresponding to an emergency situation. Here, the risk probability can be determined by determining how far the passenger's gestures, voice volume, etc. deviate from the standard gesture and voice using a predetermined algorithm.

Here, the cause point may be the location where a specific passenger 310-1 who commits a criminal act is standing.

Figure 3b is a diagram schematically showing the case of a patient among examples of the existence of an emergency situation in an autonomous vehicle, according to an embodiment of the present invention.

Referring to FIG. 3B, when the risk probability determined by a predetermined sensor is greater than or equal to a predetermined risk probability, at least one cause point may be determined, and the degree of distribution of passengers may be determined centered on the cause point.

For example, when the probability of risk is 70% through the image sensor 301 in the autonomous vehicle 300, the distribution of other passengers is concentrated at a close distance of less than 40 cm from the specific passenger (310-2), which is the cause point. If it is determined that a specific passenger (310-2) is around, it may be determined that it falls into the category related to the occurrence of a patient among the plurality of categories corresponding to an emergency situation.

Here, the cause point may be the location where a specific passenger 310-2 complaining of pain is lying down.

Although not shown, as another example, when the cause point is a fire occurrence point within the autonomous vehicle 300, if it is determined that the distribution information of passengers is concentrated at a location greater than a preset distance from the fire occurrence point, an emergency situation occurs. Among the plurality of categories, it can be determined that it falls into the category related to device failure/fire occurrence.

Although not shown, the processor 120 additionally collects driving data of the autonomous vehicle 300 and calculates the speed, direction, and acceleration of the autonomous vehicle 300 included in the specific driving data corresponding to a specific time. You can obtain information about

Here, the driving data may include the movement route.

In addition, in the driving data, passengers may be concentrated to one side due to centrifugal force, inertia, etc. during at least one direction of movement among left turn, right turn, and U-turn, so in this case, the critical distribution information, which is the standard for determining abnormal distribution, is used in the driving data. It can be adjusted with reference to .

That is, the processor 120 uses the distribution information as a reference to determine whether an emergency situation has occurred in the autonomous vehicle 300 by providing critical distribution information that distinguishes between normal distribution information and abnormal distribution information, which serves as a standard for autonomous driving. It can be adjusted by referring to information about the speed, direction, and acceleration of the vehicle 300.

In addition, the processor 120 refers to the history information (medical history information, crime information) of the passengers inside the autonomous vehicle 300, determines critical distribution information that distinguishes the normal distribution and the abnormal distribution, and corresponds to the critical distribution information. The standards corresponding to the location data and movement data of the passengers can be set to be a little closer to the normal distribution.

For example, if a specific passenger (310-1) has a criminal record, the risk rate for other passengers (320-1) becomes higher, so the critical distribution information can be adjusted so that even a single step backwards is included in the abnormal distribution area. There will be.

Additionally, the embodiments according to the present invention described above may be implemented in the form of program instructions that can be executed through various computer components and recorded on a computer-readable recording medium. The computer-readable recording medium may include program instructions, data files, data structures, etc., singly or in combination. Program instructions recorded on the computer-readable recording medium may be specially designed and configured for the present invention, or may be known and usable by those skilled in the computer software field. Examples of computer-readable recording media include hard disks, magnetic media such as floppy disks and magnetic tapes, optical recording media such as CD-ROMs and DVDs, and magneto-optical media such as floptical disks. , and hardware devices specifically configured to store and perform program instructions, such as ROM, RAM, flash memory, etc. Examples of program instructions include not only machine language code such as that created by a compiler, but also high-level language code that can be executed by a computer using an interpreter or the like. The hardware device may be configured to operate as one or more software modules to perform processing according to the invention and vice versa.

In the above, the present invention has been described with specific details such as specific components and limited embodiments and drawings, but this is only provided to facilitate a more general understanding of the present invention, and the present invention is not limited to the above embodiments. , a person skilled in the art to which the present invention pertains can make various modifications and variations from this description.

Therefore, the spirit of the present invention should not be limited to the above-described embodiments, and the scope of the patent claims described below as well as all modifications equivalent to or equivalent to the scope of the claims fall within the scope of the spirit of the present invention. They will say they do it.

Claims (12)

In a method of determining whether an emergency exists in an autonomous vehicle and supporting response,
(a) The control server collects distribution information of passengers inside the autonomous vehicle obtained by a predetermined sensor, and refers to the distribution information of passengers inside the autonomous vehicle, and detects an emergency situation within the autonomous vehicle. determining whether something has occurred; and
(b) when it is determined that an emergency situation has occurred within the autonomous vehicle, assisting the control server to determine and respond to an emergency situation within the autonomous vehicle by referring to the location information of the autonomous vehicle; Including,
In step (a) above,
When it is determined that the emergency situation has occurred, the control server determines which category among the plurality of categories corresponding to the emergency situation falls, with reference to the distribution information of passengers inside the self-driving vehicle,
In step (b) above,
If it is determined that the emergency situation falls under a specific category among the plurality of categories, the control server determines a specific location of the self-driving vehicle among the information on the plurality of facilities corresponding to the specific category. Characterized by transmitting information about the specific category of the emergency situation of the autonomous vehicle and location information of the autonomous vehicle to the specific facility using information about the facility,
In step (a) above,
When the control server collects distribution information of the passengers inside the autonomous vehicle, the distribution information is collected by at least some of an image sensor, an audio sensor, a pressure sensor, and a fire sensor inside the autonomous vehicle,
The number of at least one passenger of the autonomous vehicle captured by the image sensor, the percentage of seats occupied by the passengers, and the percentage of seats occupied by the passengers are less than or equal to a first threshold factor. With reference to at least one of the following: a judgment as to whether the number of passengers is more than a second critical factor, and a judgment as to whether the number of passengers more than a third critical factor is concentrated in a predetermined detailed space compared to the area of the interior space of the autonomous vehicle and the number of passengers. Determine whether the distribution information corresponds to an ideal distribution,
Determination of the speed, pitch, and profanity of the voice of the passenger of the autonomous vehicle acquired by the audio sensor, determination of whether a specific passenger of the autonomous vehicle is talking to himself, and whether the self-talk continues for a predetermined period of time; At least one of determining whether a specific passenger of the self-driving vehicle is talking to another passenger, or determining whether a gesture is abnormal based on information from the image sensor when a specific passenger of the self-driving vehicle is talking to another passenger. Determine whether the distribution information corresponds to an ideal distribution by referring to one,
Determination of whether the force applied to the floor or wall of the autonomous vehicle detected by the pressure sensor is higher than a high critical pressure, and whether the force applied to the floor or wall of the autonomous vehicle is low. In a state where the pressure is above the critical pressure, determine whether it corresponds to an abnormal distribution by referring to at least one of the gestures or voices of other passengers based on the image sensor or the audio sensor,
Determination of whether the smoke inside the autonomous vehicle detected by the fire sensor is above a high critical density, and the image sensor in a state where the smoke inside the autonomous vehicle is above a low critical density Or, a method characterized in that it determines whether it corresponds to an abnormal distribution by referring to at least one of other passengers' gestures or voices based on the audio sensor. delete delete In a method of determining whether an emergency exists in an autonomous vehicle and supporting response,
(a) The control server collects distribution information of passengers inside the autonomous vehicle obtained by a predetermined sensor, and refers to the distribution information of passengers inside the autonomous vehicle, and detects an emergency situation within the autonomous vehicle. determining whether something has occurred; and
(b) when it is determined that an emergency situation has occurred within the autonomous vehicle, assisting the control server to determine and respond to an emergency situation within the autonomous vehicle by referring to location information of the autonomous vehicle;
Including,
In step (a) above,
When it is determined that the emergency situation has occurred, the control server determines which category among the plurality of categories corresponding to the emergency situation falls, with reference to the distribution information of passengers inside the self-driving vehicle,
In step (b) above,
If it is determined that the emergency situation falls under a specific category among the plurality of categories, the control server determines a specific location of the self-driving vehicle among the information on the plurality of facilities corresponding to the specific category. Characterized by transmitting information about the specific category of the emergency situation of the autonomous vehicle and location information of the autonomous vehicle to the specific facility using information about the facility,
In step (a) above,
Among the passengers, determine at least one cause point whose risk probability determined by a predetermined sensor is greater than or equal to a predetermined risk probability, and determine distribution information of passengers centered on the cause point,
If the cause point is a specific passenger whose probability of risk is greater than or equal to the predetermined risk probability,
If the distribution information of the other passengers is determined to be concentrated at a location greater than the first preset distance from the specific passenger, it is determined that the first category, which is the category related to the occurrence of a crime, is determined among the plurality of categories corresponding to the emergency situation, and , If the distribution information of other passengers is determined to be around the specific passenger by clustering in a close location less than the preset second distance from the specific passenger, the patient occurrence-related category among the plurality of categories corresponding to the emergency situation It is characterized by being judged to fall into the second category,
If the cause point is a specific point within the autonomous vehicle that is greater than or equal to the predetermined risk probability,
If the distribution information of the passengers is determined to be concentrated at a location greater than the preset third distance from the specific point, it is determined that the emergency situation falls into the third category, which is the category related to breakdown/fire occurrence, among the plurality of categories corresponding to the emergency situation. A method characterized by: According to paragraph 1,
In step (a) above,
The control server additionally collects driving data of the autonomous vehicle and obtains information on the speed, direction, and acceleration of the autonomous vehicle included in specific driving data corresponding to a specific time,
The control server provides critical distribution information that distinguishes between normal distribution information and abnormal distribution information, which serves as a standard for determining whether an emergency situation has occurred in the autonomous vehicle with reference to the distribution information, of the autonomous vehicle. A method characterized in that adjustment is made with reference to information on speed, direction, and acceleration. According to clause 5,
The control server refers to the history information of the passengers inside the autonomous vehicle - the history information includes at least part of the medical history information and crime information of the passengers - and provides the normal distribution information and the abnormal distribution information. Determining the critical distribution information that distinguishes, and lowering at least some of the criteria corresponding to the location data and movement data of passengers corresponding to the critical distribution information. In the server that determines whether an emergency exists in an autonomous vehicle and supports response,
at least one memory storing instructions; and
At least one processor configured to execute the instructions;
The processor (I) collects distribution information of passengers inside the autonomous vehicle obtained by a predetermined sensor, and refers to the distribution information of passengers inside the autonomous vehicle, and detects an emergency situation within the autonomous vehicle. The process of determining whether something has occurred; and (II) when it is determined that an emergency situation has occurred in the autonomous vehicle, a process for determining and responding to an emergency situation in the autonomous vehicle with reference to the location information of the autonomous vehicle;
The processor,
In process (I) above,
If it is determined that the emergency situation has occurred, it is determined which of the plurality of categories corresponding to the emergency situation falls into, with reference to the distribution information of passengers inside the self-driving vehicle,
In process (II) above,
If it is determined that the emergency situation falls under a specific category among the plurality of categories, information on the specific facility determined with reference to the location of the self-driving vehicle is provided among the information on the plurality of facilities corresponding to the specific category. Characterized by transmitting information about the specific category of the emergency situation of the autonomous vehicle and location information of the autonomous vehicle to the specific facility,
In process (I) above,
When the processor collects distribution information of the passengers inside the autonomous vehicle, the distribution information is collected by at least some of an image sensor, an audio sensor, a pressure sensor, and a fire sensor inside the autonomous vehicle,
The number of at least one passenger of the autonomous vehicle captured by the image sensor, the percentage of seats occupied by the passengers, and the percentage of seats occupied by the passengers are less than or equal to a first threshold factor. With reference to at least one of the following: a judgment as to whether the number of passengers is more than a second critical factor, and a judgment as to whether the number of passengers more than a third critical factor is concentrated in a predetermined detailed space compared to the area of the interior space of the autonomous vehicle and the number of passengers. Determine whether the distribution information corresponds to an ideal distribution,
Determination of the speed, pitch, and profanity of the voice of the passenger of the autonomous vehicle acquired by the audio sensor, determination of whether a specific passenger of the autonomous vehicle is talking to himself, and whether the self-talk continues for a predetermined period of time; At least one of determining whether a specific passenger of the self-driving vehicle is talking to another passenger, or determining whether a gesture is abnormal based on information from the image sensor when a specific passenger of the self-driving vehicle is talking to another passenger. Determine whether the distribution information corresponds to an ideal distribution by referring to one,
Determination of whether the force applied to the floor or wall of the autonomous vehicle detected by the pressure sensor is higher than a high critical pressure, and whether the force applied to the floor or wall of the autonomous vehicle is low. In a state where the pressure is above the critical pressure, determine whether it corresponds to an abnormal distribution by referring to at least one of the gestures or voices of other passengers based on the image sensor or the audio sensor,
Determination of whether the smoke inside the autonomous vehicle detected by the fire sensor is above a high critical density, and the image sensor in a state where the smoke inside the autonomous vehicle is above a low critical density Or, a control server that determines whether the distribution corresponds to an abnormality by referring to at least one of other passengers' gestures or voices based on the audio sensor. delete delete In the server that determines whether an emergency exists in an autonomous vehicle and supports response,
at least one memory storing instructions; and
At least one processor configured to execute the instructions;
The processor (I) collects distribution information of passengers inside the autonomous vehicle obtained by a predetermined sensor, and refers to the distribution information of passengers inside the autonomous vehicle, and detects an emergency situation within the autonomous vehicle. The process of determining whether something has occurred; and (II) when it is determined that an emergency situation has occurred in the autonomous vehicle, a process for determining and responding to an emergency situation in the autonomous vehicle with reference to the location information of the autonomous vehicle;
The processor,
In process (I) above,
If it is determined that the emergency situation has occurred, it is determined which of the plurality of categories corresponding to the emergency situation falls into, with reference to the distribution information of passengers inside the self-driving vehicle,
In process (II) above,
If it is determined that the emergency situation falls under a specific category among the plurality of categories, information on the specific facility determined with reference to the location of the self-driving vehicle is provided among the information on the plurality of facilities corresponding to the specific category. Characterized by transmitting information about the specific category of the emergency situation of the autonomous vehicle and location information of the autonomous vehicle to the specific facility,
In process (I) above,
Among the passengers, determine at least one cause point whose risk probability determined by a predetermined sensor is greater than or equal to a predetermined risk probability, and determine distribution information of passengers centered on the cause point,
If the cause point is a specific passenger whose probability of risk is greater than or equal to the predetermined risk probability,
If the distribution information of the other passengers is determined to be concentrated at a location greater than the first preset distance from the specific passenger, it is determined that the first category, which is the category related to the occurrence of a crime, is determined among the plurality of categories corresponding to the emergency situation, and , If the distribution information of other passengers is determined to be around the specific passenger by clustering in a close location less than the preset second distance from the specific passenger, the patient occurrence-related category among the plurality of categories corresponding to the emergency situation It is characterized by being judged to fall into the second category,
If the cause point is a specific point within the autonomous vehicle that is greater than or equal to the predetermined risk probability,
If the distribution information of the passengers is determined to be concentrated at a location greater than the preset third distance from the specific point, it is determined that the emergency situation falls into the third category, which is the category related to breakdown/fire occurrence, among the plurality of categories corresponding to the emergency situation. A control server characterized in that. In clause 7,
In process (I) above,
The processor additionally collects driving data of the autonomous vehicle and obtains information about the speed, direction, and acceleration of the autonomous vehicle included in specific driving data corresponding to a specific time,
The processor, with reference to the distribution information, determines whether an emergency situation has occurred in the self-driving vehicle by providing critical distribution information that distinguishes between normal distribution information and abnormal distribution information, which serves as a standard for determining the speed of the self-driving vehicle. A control server characterized in that it adjusts by referring to information on direction and acceleration. According to clause 11,
The processor determines the normal distribution information and the abnormal distribution information with reference to the history information of the passengers inside the autonomous vehicle - the history information includes at least part of the medical history information and crime information of the passengers. A control server that determines the critical distribution information for classification, but lowers at least some of the criteria corresponding to the location data and movement data of passengers corresponding to the critical distribution information.