KR102149175B1 - Vehicle accident detection and emergency call service system based on data and method for processing thereof - Google Patents

Abstract

The present invention relates to a data-based accident detection and emergency response service system and a processing method thereof. The accident detection and emergency response service system of the present invention detects and collects various information such as location information in accordance with vehicle operation, driver status information, and vehicle operation information in real time using a high-precision location-based IoT agent installed in the vehicle, analyzes and learns the same to predict the occurrence of events, and induces safe driving and prevents traffic accidents by alerting a driver to prepare for an accident when an even is predicted.

Description

Data-based accident detection and emergency response service system and its handling method {VEHICLE ACCIDENT DETECTION AND EMERGENCY CALL SERVICE SYSTEM BASED ON DATA AND METHOD FOR PROCESSING THEREOF}

The present invention relates to an accident detection and emergency response service system, and more specifically, by using a high-precision location-based platform, various information such as driver status and vehicle operation status according to vehicle operation are collected and collected in real time or periodically based on sensors. And, it relates to a data-based accident detection and emergency response service system that analyzes and learns the collected information to predict the occurrence of an event while driving a vehicle, and provides an emergency response service to a driver in advance in response to the event, and a processing method thereof. .

In recent years, due to the rapidly increasing number of automobiles, the incidence of traffic accidents is rapidly increasing. Traffic accidents are causing serious social and economic damage. In particular, the incidence of traffic accidents due to drowsy driving is higher than that of general traffic accidents, and since most of the situations in which the driver is not aware of the occurrence of the accident at the time of the accident, the probability of a large accident is higher.

In general, when a traffic accident occurs while a vehicle is operating, in order to minimize the damage to the driver and passengers in the vehicle in the accident, rapid accident handling and rescue work must be performed after the accident.

Accordingly, with the development of ICT technology, research on the establishment of an accident emergency response system to promptly deal with the use of ICT technology such as vehicle emergency call service (e-Call service) in case of a traffic accident is actively conducted. It is a situation in progress. For example, the Ministry of Land, Infrastructure and Transport and the Road Traffic Safety Authority are seeking various measures to secure a golden time for vehicle accidents. Accordingly, technologies such as installing an e-Call terminal to detect an accident in a vehicle and analyzing a threshold value due to an impact to establish an emergency response system for a traffic accident in a physical environment are being developed.

Korean Patent Application Publication No. 10-2018-0077671 (published on July 09, 2018) Korean Patent Registration No. 10-1711027 (announced on March 13, 2017) Korean Registered Patent Publication No. 10-1993537 (announced on June 26, 2019) Korean Patent Application Publication No. 10-2019-0072077 (published on June 25, 2019)

An object of the present invention is to detect and collect information on driver status and vehicle operation status in real time using sensors installed in a vehicle and an IoT agent, and to analyze and learn this to detect accidents such as drowsy driving and traffic accidents. And a data-based accident detection and emergency response service system that predicts, provides an emergency response service for the detected or predicted accident, and a processing method thereof.

Another object of the present invention is to measure and correct the location information according to the operation of the vehicle in real time using a high-precision GNSS platform, and when an event occurring during the operation of the vehicle is predicted, the driver is notified or alerted about the event It is to provide a data-based accident detection and emergency response service system and a processing method that prevents accidents by generating them.

Another object of the present invention is to detect various information according to vehicle operation, analyze and learn the detected information, and detect and predict the occurrence of an event using an accident prediction algorithm and spatial analysis to respond to a detected or predicted event in an emergency. It is to provide a data-based accident detection and emergency response service system that provides a service, and a method of processing the same.

In order to achieve the above objects, the data-based accident detection and emergency response service system according to the present invention detects various information according to vehicle operation in real time based on a sensor, collects and aggregates through an IoT agent, and collects the collected information. One feature is to provide drivers with emergency response services corresponding to various events occurring during vehicle operation by analyzing and learning. The accident detection and emergency response service system of the present invention predicts an accident based on a variety of sensed data, and provides an emergency response service through accident prevention and predictive learning, thereby preventing an accident that occurs during vehicle operation.

The data-based accident detection and emergency response service system of the present invention according to this feature includes: a smart band worn by a driver of a vehicle in operation and detecting heart rate information of the driver and acceleration information according to movement; A driver condition monitoring device installed inside the vehicle, having a first camera module, and detecting driver condition information by acquiring an image including the driver's iris and face; It is installed in the vehicle, a second camera module is provided to acquire surrounding images while the vehicle is running, and a radar module is provided to detect the presence or absence of an object in the surrounding situation of the vehicle and the distance to the object, and the second camera A state-of-the-art driver assistance device for generating driver assistance information by receiving vehicle driving information according to vehicle operation in real time from a module, the radar module, and the vehicle driving record self-diagnosis device; It is installed on the vehicle and is connected to a plurality of base stations through an artificial satellite to obtain the location information of the vehicle in real time, and receive heart rate information, acceleration information, and driver status information from the smart band and the driver condition monitoring device, and the A satellite navigation terminal that receives driver assistance information from a state-of-the-art driver assistance device and transmits location information, driver status information, and vehicle operation information of the vehicle; And collecting and collecting the vehicle location information, driver state information, and vehicle operation information transmitted from the satellite navigation terminal provided in each of a plurality of vehicles, and analyzing and learning the collected information to detect or predict an event occurrence. And an emergency response service server that provides an emergency response service for transmitting notification information according to the occurrence of the event to a driver terminal when an event occurrence is detected or predicted.

In this feature, the accident detection and emergency response service system generates emergency braking information when the driving record self-diagnosis device receives a notification command according to an event occurrence from the advanced driver assistance device and operates the brake actuator to generate emergency braking information. Further comprising an automatic emergency braking device for transmitting to the support device; The advanced driver assistance device includes the transmitted emergency provision information in driver assistance information and transmits it to the satellite navigation terminal.

In this feature, the emergency response service server sets a certain range of geo-fence areas in response to the location information transmitted from the satellite navigation terminal, and sets an area setting value corresponding to each of the set geo-fence areas to cause an accident. Set to have the highest value in the order of the highest region.

In this feature, the emergency response service server sets priorities in stages for events that may occur during vehicle operation through the collected information using an accident prediction algorithm, and determines the possibility of event occurrence according to the set priority. It detects and predicts events by discriminating step by step.

In this feature, the emergency response service server comprises: a first event detected by the automatic emergency braking device, a second event detected by the advanced driver assistance device, and a third event detected by the driver condition monitoring device. , A fourth event sensed by the smart band and a fifth event sensed by the satellite navigation terminal; The priority is set to five levels, a first priority is when the first event to the third event and the fifth event are simultaneously detected, and a second priority is the first event and the second event And the fourth event and the fifth event are simultaneously detected, and a third priority is when the second event, the third event, the fourth event, and the fifth event are simultaneously detected, and a fourth The priority is when the second event, the third event, and the fifth event are detected at the same time in consideration of the state in which the smart band is not worn, and the fifth priority is the case where the smart band is stopped for no reason while driving. It is set as a case where the fifth event is detected.

As described above, the data-based accident detection and emergency response service system according to the present invention acquires GNSS-based location information of each vehicle, and provides information on the driver status and vehicle operation status of the vehicle in real time through various sensors. It is possible to collect and collect various information to build big data, analyze and learn it repeatedly to detect and predict an accident, and provide emergency response services before an accident to the driver.

In addition, the data-based accident detection and emergency response service system according to the present invention can increase the accuracy of accident detection and prediction by combining various sensor information to detect and predict an accident step by step, and apply a zone setting value through spatial analysis. have.

In addition, the data-based accident detection and emergency response service system according to the present invention acquires short-period driving information using the GNSS platform and analyzes it to apply to traffic safety and accident prevention activities, or to various fields such as guidance and guidance services. By establishing a data operation platform that can provide relevant information so that it is possible, various organizations that can reduce traffic accidents are provided not only to related organizations such as the National Police Agency, Road Traffic Authority, and local governments, but also to the private sector such as navigation companies and public data portals. It can lay the foundation for providing services.

In addition, the data-based accident detection and emergency response service system according to the present invention is open to be applied to various applications as public data to secure data quality and standards, support various data volumes and formats, and provide them in various forms and uses. , Continuous management is possible.

In addition, the data-based accident detection and emergency response service system according to the present invention provides information related to emergency response services to an incident support system such as the Road Traffic Authority, etc., traffic fatal accident information, traffic weakness, and accident characteristics. Information on the location of traffic fatal accidents through traffic accident analysis systems and public data portals at the National Police Agency and Road Traffic Authority in real time by fusion analysis with data on accident-prone area information, past traffic accidents, weather, and accidents, etc. By opening information such as traffic accident information, accident location information, and road risk index, it is possible to provide various services that can reduce traffic accidents in various industries.

In addition, when the data-based accident detection and emergency response service system according to the present invention is provided to private industries such as navigation companies, a differentiated road risk index according to the road type and driver vehicle type is provided through a more three-dimensional map guidance service. It can improve the accuracy of guidance and expand the diversity of guidance content. For example, when a vehicle passes a specific area at a specific time, the area is notified that it is a high-risk area where fatal accidents are concentrated between 00:00 and 00:00, or when passing through an area with frequent fatal accidents, an automatic notification service to the driver It can be expected to preemptively reduce accidents.

In addition, when the data-based accident detection and emergency response service system according to the present invention is used in the insurance industry, it is possible to increase the satisfaction of insurance contractors through various special contracts and premium option products using open data.

In addition, the data-based accident detection and emergency response service system according to the present invention can secure diversity of research by utilizing traffic accident information in existing traffic communication information when researching for traffic safety in research institutes, It is expected to be able to improve the accuracy of accident analysis and statistical data.

In addition, the data-based accident detection and emergency response service system according to the present invention can be applied to revitalization of public service projects such as road structure reorganization and signal system improvement in areas with frequent traffic accidents in local governments. The use of accident location information is expected to improve the stability and convenience of the public through the effect of reducing social costs by reducing the incidence of traffic accidents and increasing job creation through the development of the data industry.

1 is a block diagram showing a network configuration of a data-based accident detection and emergency response service system according to the present invention;
FIG. 2 is a block diagram showing a partial configuration of the vehicle shown in FIG. 1;
3 is a block diagram showing the configuration of the server shown in FIG. 1;
4 is a flow chart showing the processing procedure of the data-based accident detection and emergency response service system according to the present invention, and
5 is a flowchart showing a procedure of the accident detection and prediction routine shown in FIG. 4.

The embodiments of the present invention may be modified in various forms, and the scope of the present invention should not be construed as being limited by the embodiments described below. This embodiment is provided to more completely explain the present invention to those of ordinary skill in the art. Therefore, the shape of the constituent elements in the drawings is exaggerated in order to emphasize a more clear description.

Hereinafter, exemplary embodiments of the present invention will be described in detail with reference to FIGS. 1 to 5.

1 is a block diagram showing a network configuration of a data-based accident detection and emergency response service system according to the present invention, FIG. 2 is a block diagram showing a partial configuration of the vehicle shown in FIG. 1, and FIG. It is a block diagram showing the configuration of the server shown in 1.

1 to 3, the accident detection and emergency response service system 2 of the present invention collects various information according to vehicle operation using an IoT agent, and combines the collected information to provide data. In order to provide an e-Call service that responds to an emergency based on an emergency, it detects various information according to the location of the vehicle, the driver's state, and the vehicle operation state while the vehicle is driving, collects and collects it, and sleeps in advance. It monitors and predicts the occurrence of events such as driving and traffic accidents, analyzes and learns collected information, and provides emergency response services to predicted events. Here, the events include, for example, a driver's drowsy driving, a sudden change in mental and physical condition, speeding, sudden start, sudden stop, sudden lane change, collision with a vehicle ahead, and a road hazard situation.

The accident detection and emergency response service system 2 of the present invention uses a high-precision location-based IoT agent installed in the vehicle in real time, such as location information according to vehicle operation, driver status information, and vehicle operation information. It detects and collects information, analyzes and learns it, and predicts the occurrence of an event, and when an event is predicted, it is possible to prevent safety driving and traffic accidents by alarming a driver in preparation for an accident.

In addition, the accident detection and emergency response service system 2 of the present invention can be applied to various fields such as traffic safety and accident prevention activities by acquiring and analyzing driving information of a short cycle using a GNSS platform, or guidance and guidance services. By constructing a data operation platform that can provide relevant information, various services that can reduce traffic accidents are provided to the private sector, such as navigation companies, insurance companies, and public data portals, as well as related organizations such as the National Police Agency and Road Traffic Authority. You can lay the groundwork to provide.

To this end, the accident detection and emergency response service system 2 of the present invention includes a communication network 4, a smart band 110 worn by a driver, a DSM device 120 installed in the vehicle 100, and an ADAS device 130. , AEBS device 140, GNSS terminal 150, driver terminal 300, and an emergency response service server 200. In addition, the accident detection and emergency response service system 2 of the present invention may further include an accident support system 400.

Specifically, the communication network 4 includes, for example, a wireless communication network such as Wi-Fi and Bluetooth, a mobile communication network such as LTE and 5G, and a dedicated communication network such as a LoRa network, and each of them is a single communication network or a mixed network. It can be provided as a complex network. The communication network 4 is connected to enable data communication between the GNSS terminal 150 of the vehicle and the emergency response service server 200. In addition, the communication network 4 may be connected to enable data communication between the driver terminal 300 and each of the accident support systems 300 and the emergency response service servers 200.

The vehicle 100 includes a plurality of sensors, a camera, a radar, and the like in order to detect a driver's state and a vehicle's driving state during vehicle operation based on a sensor. In this embodiment, the vehicle 100 includes a smart band 110 and a DSM device 120 for detecting a driver's state, and an ADAS device 130 and an AEBS device 140 for detecting a vehicle driving state. In addition, the vehicle 100 includes a GNSS terminal 150 for real-time tracking of the vehicle location and data communication with the emergency response service server 200.

The smart band 110 is a wearable device worn on a driver's wrist, etc., and includes driver information, and senses heart rate information of the driver and acceleration information according to movement in order to detect the driver's health state, mental and physical state, and the like. The smart band 110 transmits the detected heart rate information and acceleration information to the GNSS terminal 150. To this end, the smart band 110 includes a heart rate sensor 116, an acceleration sensor 118, a communication module 114, and a controller 112, as shown in FIG. 2.

The heart rate sensor 116 detects, for example, the driver's heart rate in real time or periodically (seconds, minutes), and detects the detected heart rate information in order to determine the driver's mental and physical state or physical state. To pass. The acceleration sensor 118 measures acceleration information according to the driver's movement and transmits it to the controller 112 in order to determine the driver's drowsy driving. The communication module 114 transmits driver information, heart rate information, and acceleration information to the GNSS terminal 150 through, for example, a wireless communication network such as Wi-Fi and Bluetooth, or a mobile communication network such as LTE and 5G. Further, the controller 112 controls the heart rate sensor 116, the acceleration sensor 118, and the communication module 114 to process the functions of the smart band 110.

Driver Status Monitoring (DSM) device 120 is installed inside the vehicle 100 to detect driver status information to determine whether the driver is drowsy driving, looking ahead, and driving fatigue. The state information is transmitted to the GNSS terminal 150. The DSM device 120 of this embodiment includes a camera module 126, a communication module 124, and a controller 122, as shown in FIG. 2.

The camera module 126 acquires an image including the driver's iris and face by recognizing the driver's iris and face, and transmits the acquired image to the controller 122. The communication module 124 transmits the acquired image, that is, driver status information, to the GNSS terminal 150 through a wired interface such as, for example, a USB port or a serial port. In addition, the controller 122 controls the camera module 126 and the communication module 124 to process the functions of the DSM device 120.

This DSM device 120 not only recognizes the iris and face using the camera module 126, but also various sensors that detect the driver's biological and health status, for example, a seat of a vehicle, a steering wheel, a seat belt, a gear transmission, etc. Equipped with an electrocardiogram sensor, a pulse wave sensor, an electroencephalogram sensor, etc., through this, it detects the driver's heart diagram, pulse wave, and biometric information such as electroencephalogram to monitor the driver's health and physical condition, and the driver's drowsy driving condition and fatigue condition , It is also possible to determine whether an event such as an attention-lowering state has occurred. Accordingly, the present invention detects driver state information so that the driver's drowsy driving state, mental and physical state, etc. can be determined through the smart band 110 and the DSM device 120.

The Advanced Driver Assistance Systems (ADAS) device 130 is connected to the On-Board Diagnostics-II (OBD2) device 142 of the vehicle 100 through CAN communication, OBD2 port, etc. , ADAS information is generated by receiving various vehicle operation information according to vehicle operation from the OBD2 device 142 in real time. The ADAS device 130 transmits the generated ADAS information to the GNSS terminal 150. Here, the vehicle operation information includes various information related to vehicle operation, such as vehicle information, vehicle speed, RPM, turn signal status, accelerator operation status, brake actuator operation status, digital driving record, emergency braking information, etc. ADAS information includes information determined through vehicle operation information, such as lane recognition, lane departure, front vehicle recognition, pedestrian recognition, front object detection and distance measurement, vehicle collision time (Time To Collision: TTC), etc. Information and emergency braking information transmitted from the OBD2 device 142 are included. The ADAS device 130 of this embodiment includes a camera module 136, a radar module 138, a communication module 134, and a controller 132, as shown in FIG. 2.

The camera module 136 acquires an image around the vehicle while driving the vehicle and transmits it to the controller 132. The radar module 138 detects the presence of a front and rear vehicle according to the movement of the vehicle 100, a distance between the front and rear vehicles, and the presence of a pedestrian, and transmits the detection to the controller 132. The communication module 134 transmits ADAS information to the GNSS terminal 150 through a wired interface such as, for example, a USB port or a serial port. And the controller 132 controls the camera module 136, the radar module 138, and the communication module 134 to process the functions of the ADAS device 130. The controller 132 processes and analyzes the image transmitted from the camera module 136 or detects an object detected from the radar module 138 to recognize lanes, whether to leave the lane, recognize the vehicle ahead, recognize the pedestrian, detect the object in front, and ADAS information is generated according to distance measurement, vehicle collision time required, and emergency braking information. The controller 132 controls to transmit the generated ADAS information to the GNSS terminal 150 through the communication module 134. In addition, when an event occurs in ADAS information, the controller 132 transmits a notification command according to the occurrence of the event to the OBD2 device 142 of the vehicle 100 through a universal asynchronous transceiver (UART).

The ADAS device 130 is a device that assists the driver's safe driving, and uses a radar module 138 and a camera module 136 to avoid a front collision, a lane departure warning, a blind spot monitoring, a driver's drowsiness detection, and a rear monitoring. Etc. When it is necessary to transmit the event occurrence state to the driver, the ADAS device 130 may alert the driver with a sound, visually display a rearview mirror, or shake the seat or steering wheel so that the driver can perceive it tactilely. I can.

The automatic emergency braking system (AEBS) device 140 includes an OBD2 device 142 and a brake actuator (B/A) 144, and an event from the ADAS device 130, such as a frontal collision , Lane departure, pedestrian recognition, etc. are detected and the notification command is transmitted to the OBD2 device 142, the OBD2 device 142 controls the brake actuator (B/A) 144 to be automatically operated. Accordingly, the OBD2 device 142 transmits emergency braking information related to the AEBS device 140 to the controller 132 of the ADAS device 130.

The Global Navigation Satellite System (GNSS) terminal 150 is an Internet of Things (IoT) agent, installed on the vehicle 100, and connected to a plurality of base stations for higher-precision information collection than general GPS to operate the vehicle. The location information according to is acquired in real time (eg, in units of 1 second). The GNSS terminal 150 automatically switches channel connections with adjacent base stations to correct position information between adjacent base stations while the vehicle is running. For example, the GNSS terminal 150 covers a plurality of base stations having a radius of about 10 km in a corresponding area while the vehicle is being operated, and acquires and corrects location information in real time in both directions through this. In addition, the GNSS terminal 150 is connected to the smart band 110 and the emergency response service server 200 through a wireless communication network, a mobile communication network, etc., in order to collect data based on a high-precision location during vehicle operation, and through a wired interface. It is connected to the DSM device 120 and the ADAS device 130. To this end, the GNSS terminal 150 includes a GNSS antenna 154, a GNSS module 156, a communication module 158, a memory 159, and a controller 152, as shown in FIG. 2.

The GNSS antenna 154 is connected to a plurality of base stations through an artificial satellite. The GNSS module 156 acquires high-precision position information from the GNSS antenna 154 in real time or periodically (eg, in seconds) during vehicle operation, and transmits the obtained position information to the controller 152. Here, the location information transmitted to the controller 152 is transmitted as NMEA (National Marine Electronics Association) data including information such as time, longitude and latitude location, azimuth, number of satellites, speed, direction, and GNSS quality. The communication module 158 is connected to the smart band 110, the DSM device 120, and the ADAS device 130 through a wireless communication network, a mobile communication network, a wired interface, etc., and a communication network such as a wireless communication network, a mobile communication network, a dedicated communication network, etc. It is connected to the emergency response service server 200 through (4). The memory 159 receives location information, such as NMEA data, from the controller 152, temporarily stores it, and updates it in real time. In addition, the controller 152 controls the GNSS module 156, the communication module 158, and the memory 159 to process functions of the GNSS terminal 150. The controller 152 is synchronized with time information transmitted from the smart band 110, the DSM device 120, the ADAS device 130, and the AEBS device 140, and the location information obtained through the GNSS module 156 and , Control to transmit vehicle information, driver information, driver status information, vehicle operation information, and images collected through the communication module 158 to the emergency response service server 200 through the communication network 4.

The GNSS terminal 150 acquires and corrects location information according to the movement of the vehicle 100 in real time, and driver status information and vehicle operation detected in real time from various sensors installed on the vehicle 100 and worn by the driver. By receiving information, etc., various information is transmitted in real time to the emergency response service server 200 so as to quickly respond to an emergency accident such as a traffic accident.

Referring back to FIG. 1, the emergency response service server 200 collects and collects various information according to the location, driver state, and vehicle operation state according to the vehicle operation from each of the plurality of vehicles 100 to enable the vehicle operation in real time. A standardized system related to the safe operation of the vehicle 100 is implemented by producing mobile IoT-based driving data according to this, and providing notifications and alarms according to event occurrence predictions such as prevention of drowsy driving and traffic accidents to the driver through this. That is, the emergency response service server 200 collects and collects various information such as location information transmitted from each of the plurality of GNSS terminals 150, the driver's state according to the vehicle operation, and the vehicle operation state, and analyzes and learns it. By predicting the occurrence of an accident, that is, an event, detecting the driver's drowsy driving, or when any one of the events occurring while driving is predicted, an emergency response to promptly prevent a traffic accident by notifying or warning the driver in advance Provide service.

The emergency response service server 200 provides various data related to emergency response services to related organizations, for example, the Police Agency, the Road Management Authority, and the accident support system 400 of local governments online in real time or periodically, or It can be provided offline or online to private companies such as insurance companies and navigation companies, so that they can be used for various purposes.

Specifically, the emergency response service server 200 includes a server 210 and a database 250, as shown in FIG. 3. The server 210 is provided as a web server, an app server, etc., and transmits a standard RTCM (Radio Technical Committee for Maritime Service) signal by correcting location information based on the Internet using, for example, an IoT platform to authenticate users. NTRIP server for, an interface server for time synchronization and data processing, a connection server for managing IoT devices, and the like, and the database 250 includes, for example, vehicle information DB, sensor collection DB, accident response DB, etc. do.

The server 210 of this embodiment includes a control unit 212, a communication unit 214, a location determination unit 216, an information collection unit 218, an analysis unit 220, a big data learning unit 222, and a spatial area setting unit. (224), an accident prediction unit 226, a monitoring unit 228 and a notification unit 230.

The control unit 212 is a communication unit 214, a location determination unit 216, and an information collection unit to process all functions of the emergency response service server 200 in connection with the GNSS terminals 150 of each of the plurality of vehicles 100. 218, analysis unit 220, big data learning unit 222, spatial area setting unit 224, accident prediction unit 226, monitoring unit 228, notification unit 230, and databases 250 Each function is controlled to be processed organically.

The communication unit 214 is connected to the communication network 4 and receives location information, driver status information, vehicle operation information, and images from the GNSS terminal 150 of the vehicle 100 in real time. The communication unit 214 transmits notification information to the driver terminal 300 through the communication network 4 when an event is predicted. In addition, the communication unit 214 may provide various information related to emergency response services to the accident support system 400 or the like through the communication network 4.

The location determination unit 216 determines the location information transmitted from the GNSS terminal 150 in real time while the vehicle is running, and monitors the location of the vehicle 100 in real time. The location determination unit 216 corrects the location information of the vehicle in correspondence with adjacent base stations while the vehicle is running. The location determination unit 216 determines the current position of the vehicle as an area set by the spatial area setting unit 224.

The information collection unit 218 collects and collects location information, driver status information, vehicle operation information, and images transmitted from the GNSS terminal 150 of each of the plurality of vehicles 100, and stores them in the database 250. To build big data. The government collection unit 218 collects, for example, GNSS information, OBD2 information, smart band information, DSM information, ADAS information, emergency braking information, driver information, vehicle information, vehicle location information, and vehicle operation information in real time during vehicle operation. Or, collect and collect repeatedly. The information collection unit 218 stores the collected information in the database 250. In this embodiment, the information collection unit 218 collects various pieces of information according to vehicle operation through the GNSS terminal 150 in real time (eg, once per second, etc.).

The analysis unit 220 analyzes whether an event occurs according to a driver's state and a vehicle driving state by statistically analyzing and patterning the information collected by the information collecting unit 218. The analysis unit 220, for example, analyzes the driver's mental and physical state, health state, and drowsy driving state through information detected from the heart rate sensor 116 and the acceleration sensor 118 of the smart band 110, or The images acquired from the camera module 126 of 120 are analyzed and processed to analyze the drowsy driving state. The analysis unit 220 generates response information for providing an emergency response service by analyzing a pattern according to a driver state and a vehicle operation state.

The big data learning unit 222 uses the collected information, analysis processing results, and response information to determine driver status, vehicle driving status, accident type, road environment status, etc. through artificial intelligence (AI) and deep learning learning. Build big data to provide emergency response services through repeated learning. Therefore, analysis and learning are repeatedly processed through the analysis unit 220 and the big data learning unit 222 to establish an emergency response service corresponding to each event. For example, when an event that is in a drowsy driving state is predicted, the emergency response service informs or warns the driver of dangers due to the possibility of occurrence of the event as the response information, and generates a warning about emergency braking in the second order. The device 140 is activated. Thereafter, when an accident occurs, the emergency response service transfers the event occurrence situation to the accident support system 400 and processes to take rapid action.

The spatial area setting unit 224 sets a geofence area of a certain range in response to the location information of the current vehicle 100 and sets an area setting value corresponding to each of the set geofence areas. Geo-fence zones are assigned different zone settings according to areas with high probability of accidents, such as school zones around schools, around residential areas, around shopping malls, and areas with frequent accidents. It is set to have the highest value in the order of regions with the highest probability of occurrence.

The accident prediction unit 226 is equipped with an accident prediction algorithm and determines a geo-fence area according to the location of the vehicle. The accident prediction unit 226 combines location information, driver status information, and vehicle operation information to apply a corresponding area setting value corresponding to the geo-fence area determined according to the location information of the vehicle 100, and use an accident prediction algorithm. It detects and predicts the event by determining the possibility of occurrence of the event step by step.

The accident prediction unit 226 sets priorities for possible events in stages by using an accident prediction algorithm, and determines whether an event occurs according to the set priority to predict an accident. In this embodiment, the accident prediction unit 226 uses the location information of the GNSS terminal 150 as a criterion for determining a final accident to predict an event. The accident prediction unit 226, for example, is set to prioritize the possibility of an event in five stages. That is, the event is an AEBS event detected by the AEBS device 140, an ADAS event detected by the ADAS device 130, a DSM event detected by the DSM device 120, and the SB detected by the smart band 110. Events are classified into GNSS events according to movement information (ie, speed) detected by the GNSS terminal 150. In addition, the first priority event is when an AEBS event, ADAS event, DSM event, and GNSS event are simultaneously detected, and the second priority is when an AEBS event, DSM event, SB event, and GNSS event are simultaneously detected. 3 Priority is when ADAS event, DSM event, SB event, and GNSS event are detected at the same time, and the fourth priority is ADAS event, DSM event, and GNSS event detection at the same time considering the state in which the smart band 110 is not worn. This is the case, and the fifth priority is the case that the GNSS event corresponding to the case of stopping for no reason while driving is detected. Therefore, the accident prediction unit 226 predicts the possibility of event occurrence step by step according to the collected information by applying the priority set through the location information of the vehicle 100 and the area setting value allocated by the spatial area setting unit 224 do.

The monitoring unit 228 monitors whether an event occurs during vehicle operation in real time by displaying driver status information, vehicle operation information, and images. The monitoring unit 228 displays a geo-fence area on the electronic map, displays the location and movement path of the vehicle 100 in operation, and displays the road situation or the location of the vehicle 100 according to the operation of the vehicle 100 Road conditions can also be guided in real time by applying the road risk index according to.

The notification unit 230 predicts an event according to a drowsy driving state, vehicle driving state, and road risk during the operation of the vehicle from the accident predicting unit 226, by the analysis unit 220 and the big data learning unit 222. Notification information notifying or alarming an emergency response service for an event is generated and transmitted to the driver terminal 300.

In addition, the database 250 stores and manages various pieces of information collected and generated according to a process of processing all functions of the emergency response service server 200 under the control of the controller 212. The database 250 of this embodiment includes driver information 252, vehicle information 254, driver status information 256, vehicle location information 258, vehicle operation information 260, ADAS information 262, emergency braking information. 264, analysis information 266, correspondence information 268, and notification information 270 are at least stored. The database 250 is included in the emergency response service server 200, but may be provided independently.

The above-described emergency response service server 200 acquires GNSS-based location information of each of the vehicles 100, and collects and collects various information on the driver status and vehicle operation status of the vehicle running in real time to build big data. And, by analyzing and repetitive learning, emergency response services such as preventing drowsy driving and preventing traffic accidents can be provided to the driver before an accident occurs.

Referring back to FIG. 1, the driver terminal 300 is provided with, for example, a smart phone or a navigation device, and is provided inside a vehicle. The driver terminal 300 provides driver information to the emergency response service server 200. The driver terminal 300 guides or alerts the emergency response service by receiving notification information from the emergency response service server 200.

In addition, the accident support system 400 is provided with related organizations that urgently provide support for accident response in the event of an accident, for example, the National Police Agency, the fire department, medical institutions, the Road Traffic Authority and local governments, etc., through the communication network 4 It is connected to the corresponding service server 200. The accident support system 400 receives accident-related information from the emergency response service server 200 in real time or periodically to provide information such as location information of a traffic fatal accident, traffic accident information, accident location information, and road risk index to the general public. It is open and can provide a variety of services that can reduce accidents.

Therefore, the data-based accident detection and emergency response service system 2 of the present invention opens the data generated by the processing process so that it can be applied to various applications to secure data quality and standards, support various data volumes and formats, and support various forms. And it can be processed and provided for use.

The following describes in detail the procedure of the accident detection and emergency response service system according to the present invention.

FIG. 4 is a flowchart illustrating a processing procedure of the data-based accident detection and emergency response service system according to the present invention, and FIG. 5 is a flowchart illustrating the processing procedure of the accident detection and prediction routine shown in FIG. 4.

4 and 5, the accident detection and emergency response service system 2 of the present invention includes various sensors installed in the vehicle 100 or installed on the driver in step S500, such as the heart rate sensor of the smart band 110. The heart rate and acceleration of the driver according to vehicle operation from 116 and the acceleration sensor 118, the camera module 126 of the DSM device 120, the camera module 136 of the ADAS device 130, and the radar module 138, etc. , Driver status information such as DSM information, and various information including vehicle operation information such as ADAS information and emergency braking information are detected in real time, and various types of information detected in step S502 are connected to a wireless communication network, a mobile communication network, a wired interface, etc. It is transmitted to the GNSS terminal 150 through.

In step S504, the GNSS terminal 150 acquires the location information of the vehicle 100 in real time while the vehicle is running, and in step S506, various information including driver status information and vehicle operation information and the location information of the vehicle 100 are stored. It is transmitted to the emergency response service server 200 through the communication network 4.

In step S508, the emergency response service server 200 determines the location information transmitted from the GNSS terminal 150 of each of the plurality of vehicles 100, and automatically transmits the location information of each of the vehicles 100 in operation between the base stations. The location information is corrected in real time by switching channels.

In step S510, the emergency response service server 200 collects and collects various pieces of information transmitted from the GNSS terminals 150 to build big data, and in step S512, to generate an event occurrence prediction and a response plan for the predicted event. In order to perform statistical analysis and pattern analysis, the collected information is repeatedly learned so that driver status, vehicle driving status, accident type, and road environment status can be determined through artificial intelligence (AI) and deep learning learning. The emergency response service server 200 repeats analysis and learning to generate a response plan for providing an emergency response service corresponding to each of the events to the driver.

In step S514, the emergency response service server 200 detects and predicts whether an event occurs from the collected information. At this time, the emergency response service server 200 combines the location information, driver status information, and vehicle operation information, applies a corresponding area setting value in response to the geo-fence area set according to the location information of the vehicle, and prioritizes the set event. It detects and predicts an event step by step according to.

Specifically, the event detection and prediction routine S514 analyzes a space using the location information of the vehicle 100 in step S550, as shown in FIG. 5. That is, it is determined whether the current vehicle location is in the set geo-fence area, and the area setting value corresponding to the determined geo-fence area is applied. In this case, the region setting value is set higher in the order of regions with high probability of event occurrence.

In addition, the event detection and prediction routine (S514) sets priorities for event prediction in 5 steps through the collected detection information to predict the possibility of event occurrence. That is, events are classified into AEBS events, ADAS events, DSM events, SB events, and GNSS events, and the events of the first priority are cases where AEBS events, ADAS events, DSM events, and GNSS events are simultaneously detected, and the second priority. The priority is when AEBS events, DSM events, SB events, and GNSS events are detected at the same time, the third priority is when ADAS events, DSM events, SB events, and GNSS events are simultaneously detected, and the fourth priority is smart band. In consideration of the state in which (110) is not worn, the ADAS event, the DSM event, and the GNSS event are detected at the same time, and the fifth priority is the case where the GNSS event corresponding to the case of stopping for no reason while driving is detected.

Therefore, according to the information collected in steps S552 to S570, the possibility of event occurrence is determined step by step to detect and predict the event. That is, priorities are set for possible events step by step, it is determined whether any one of the first to fifth priority events occurs according to the set priority, and then the occurrence of the corresponding event is determined in step 572.

Referring back to FIG. 4, when an event is predicted in step S516, the procedure proceeds to step S518 to generate notification information providing a response plan for the predicted event and transmit it to the driver terminal 300. Subsequently, in step S520, the driver terminal 300 receives notification information from the emergency response service server 200 to guide or alert the driver of the emergency response service.

In the above, the configuration and operation of the data-based accident detection and emergency response service system according to the present invention are illustrated in accordance with the detailed description and drawings, but this is only described by way of example, and the scope does not depart from the technical idea of the present invention. Various changes and changes are possible within.

2: Accident detection and emergency response service system
4: communication network
100: vehicle
110: smart band
120: DSM device
130: ADAS device
140: AEBS device
150: GNSS terminal
200: emergency response service server
300: driver terminal
400: accident support system

Claims (5)

In a data-based incident detection and emergency response service system:
A smart band worn by a driver of a vehicle in operation and sensing heart rate information of the driver and acceleration information according to movement;
A driver condition monitoring device installed inside the vehicle, having a first camera module, and detecting driver condition information by acquiring an image including a driver's iris and face;
It is installed in the vehicle, a second camera module is provided to acquire surrounding images while the vehicle is running, and a radar module is provided to detect the presence or absence of an object in the surrounding situation of the vehicle and the distance to the object, and the second camera A state-of-the-art driver assistance device for generating driver assistance information by receiving vehicle driving information according to vehicle operation in real time from a module, the radar module, and the vehicle driving record self-diagnosis device;
An automatic emergency braking device generating emergency braking information and transmitting the information to the advanced driver assistance device when the driving record self-diagnosis device receives a notification command according to an event occurrence from the advanced driver assistance device and operates the brake actuator;
It is installed in the vehicle and is connected to a plurality of base stations through an artificial satellite to obtain location information of the vehicle in real time, and receive heart rate information, acceleration information, and driver status information from the smart band and the driver condition monitoring device, and receive the A satellite navigation terminal that receives driver assistance information from a state-of-the-art driver assistance device and transmits location information, driver status information, and vehicle operation information of the vehicle; And
Collect and collect the vehicle location information, driver status information, and vehicle operation information transmitted from the satellite navigation terminal provided in each of a plurality of vehicles, analyze and learn the collected information to detect or predict the occurrence of an event, When the occurrence of an event is detected or predicted, an emergency response service server that provides an emergency response service for transmitting notification information according to the occurrence of the event to the driver terminal; includes,
The advanced driver assistance device includes the transmitted emergency provision information in driver assistance information and transmits it to the satellite navigation terminal;
The emergency response service server,
Setting a geo-fence area of a certain range in response to the location information transmitted from the satellite navigation terminal, and setting an area setting value corresponding to each of the set geo-fence areas to have a higher value in the order of areas with a high probability of an accident;
Detecting and predicting an event by step-by-step determining the likelihood of occurrence of an event according to the set priority, setting a priority for events that may occur during vehicle operation through the collected information using an accident prediction algorithm;
A first event detected by the automatic emergency braking device, a second event detected by the advanced driver assistance device, a third event detected by the driver condition monitoring device, a fourth event detected by the smart band, Classified into a fifth event detected by the satellite navigation terminal;
The priority is set to five levels, a first priority is when the first event to the third event and the fifth event are simultaneously detected, and a second priority is the first event and the second event And the fourth event and the fifth event are simultaneously detected, and a third priority is a case that the second event, the third event, the fourth event, and the fifth event are simultaneously detected, and a fourth The priority is a case where the second event, the third event, and the fifth event are detected at the same time in consideration of the state in which the smart band is not worn, and the fifth priority is the case of stopping without a reason while driving. Data-based accident detection and emergency response service system, characterized in that set to a case in which the fifth event is detected. delete delete delete delete

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