KR102678602B1 - Apparatus and method for guiding the optimal route to transport vehicles in a port cooperation autonomous cargo transportation system using hybrid v2x communication system - Google Patents

Abstract

A step of obtaining information about the road environment of the port and destination information of the vehicle by starting work, and generating movement route information of the vehicle. If the vehicle is located in the V2X communication service area, using the V2X communication service in the first order. optimal for vehicles in the hybrid V2X-based port cooperation autonomous cargo transportation system, which includes transmitting the movement route information to the vehicle, and transmitting the movement route information to the vehicle using a mobile communication service in the second order. A method of guiding the operation route can be provided.

Description

Device and method for guiding the optimal route to vehicles in the hybrid V2X-based port cooperation autonomous cargo transportation system

With the launch, an optimal route guidance device and method is provided that can safely deliver destination information and movement routes to cargo transport vehicles operating in a port management system equipped with CCTV and V2X communication systems.

Recently, vehicles have become the result of complex industrial technology that combines electrical, electronic, and communication technologies with a focus on mechanical engineering, and in this respect, vehicles are also called smart cars. Smart cars connect drivers, vehicles, and transportation infrastructure to provide not only traditional vehicle technologies such as traffic safety/complexity relief, but also a variety of customized mobility services. This connectivity can be implemented using Vehicle to Everything (V2X) communication technology.

C-ITS is an abbreviation for Cooperative-Intelligent Transport Systems and is also called a cooperative intelligent transport system and a next-generation intelligent transport system. C-ITS refers to a system in which vehicles cooperate through communication with infrastructure or other vehicles. C-ITS is a system that prevents traffic accidents and improves the convenience of using highways by providing forward dangerous situation information and convenience information to drivers driving on the road in advance through V2X communication between the center (server), roadside base station, and vehicles. am.

Unlike existing one-way transportation services, C-ITS, which is being actively built around the world, provides more diverse and rich transportation and transportation services through interaction between devices using V2X (Vehicle-to-Everything) communication technology and end-to-end information exchange protocols. Safety services can be provided in real time.

V2X (Vehicle to Everything) technology overcomes the sensor limitations (distance, blind spots) of autonomous vehicles through cooperation between vehicle and road infrastructure to create a road environment where autonomous cooperative driving is possible, and regular vehicles use terminals mounted on the vehicle. It is a technology that prevents traffic accidents by collecting, analyzing and processing road situation information such as accidents, congestion, and other vehicles or infrastructure installed on the road. The hybrid V2X communication system can be installed on the ground on the roadside or on various structures installed on the roadside, and the installation location and method can be determined by considering various factors such as the type of communication function supported by the multimodal communication system and operational efficiency.

As shown in Figure 1, in the wireless communication (Wireless Access in Vehicular Environments, hereinafter referred to as "WAVE") technology used in V2X communication, one control channel (CCH) and a plurality of service channels (service channels, SCH) is used to adopt a multi-channel switching method, and GPS signals are used for synchronization between the roadside base station and the vehicle terminal. Vehicle-to-vehicle and vehicle-to-road side unit (RSU) communication is direct communication between devices (D2D). Meanwhile, not only can traffic information be transmitted in real time between the vehicle and the base station, and between the RSU and the base station using LTE mobile communication (V2N: Vehicle-to-Network) technology, but also provide real-time information on traffic conditions several kilometers ahead.

In the existing port management system, destination information or travel route information was delivered to autonomous vehicles using the WIFI network within the port. In this case, it was difficult to safely transmit the information provided by the port management system because the WIFI communication distance was short and the communication success rate decreased as the vehicle moved.

On the other hand, when using the mobile communication network installed in the port, problems with connection delays occurred because mobile communication base stations that anyone can access were used, problems with communication quality deterioration occurred, and there was a burden of the cost of using the mobile communication network. did.

Japanese Patent Publication No. 2011-240816 (2011.12.01) Republic of Korea Patent Registration No. 2599024 (2023.11.01)

The purpose of the technical task initiated by the port management system is to increase the efficiency of cargo transport vehicles by providing an optimal operation route that can safely convey destination information and movement routes to cargo transport vehicles operating in the port management system.

According to the first embodiment, obtaining information about the road environment of the port and destination information of the vehicle, generating movement route information of the vehicle, determining whether the vehicle is located in the V2X communication service area, and determining whether the vehicle is located in the V2X communication service area. When located in a communication service area, it includes transmitting movement route information to the vehicle using a V2X communication service in a first order, and transmitting movement route information to the vehicle using a mobile communication service in a second order. It is possible to provide a method of guiding the optimal operation route to vehicles of a hybrid V2X-based port cooperative autonomous cargo transportation system. By starting the work, a step of displaying real-time vehicle status information on a context map, and the vehicle's It can display real-time traffic information to the destination and provide steps to create and display the most appropriate route for the task assigned to the vehicle using an artificial intelligence learning model.

By starting the work, noise data, vibration data, and combustion pressure measurement data are acquired using sensors included in the vehicle, and noise data, vibration data, combustion pressure measurement data, and vehicle operation are obtained using an artificial intelligence learning model. Diagnosing the driving state of the vehicle by learning information about the purpose, determining the driving mode of the vehicle in real time based on the driving state of the vehicle, and generating vehicle control information based on the determined driving mode of the vehicle. can be provided.

According to a second embodiment, it includes a communication unit that communicates with an external device, a memory that stores at least one instruction, and a processor that executes at least one instruction, and the processor includes information about the road environment in the port and vehicle Obtain destination information, generate vehicle movement path information, determine whether the vehicle is located in the V2X communication service area, and if the vehicle is located in the V2X communication service area, use the V2X communication service in the first order. transmits the movement route information to the vehicle, and transmits the movement route information to the vehicle using a mobile communication service in the second order. A guidance device can be provided.

In the computer program stored in a non-transitory computer-readable recording medium according to the third embodiment, obtaining information about the road environment of the port and destination information of the vehicle and generating movement route information of the vehicle, the vehicle is V2X Determining whether the vehicle is located in the communication service area, if the vehicle is located in the V2X communication service area, transmitting movement route information to the vehicle using the V2X communication service in the first order, and mobile communication in the second order A computer program stored in a recording medium that performs the step of transmitting movement route information to a vehicle using the service may be provided.

Other specific details of the invention are included in the detailed description and drawings.

By using the characteristics of V2X communication and mobile communication networks appropriately for the communication environment within the port, various information to be sent from the port control center to the port autonomous yard tractor can be safely transmitted.

In particular, by simultaneously operating a hybrid V2X communication device that integrates V2X communication and a mobile communication network, stable communication can be attempted even when the port autonomous yard tractor is operating in a poor communication environment within the port.

According to the disclosure, if control information is generated only from information obtained from existing autonomous vehicles, there is a high possibility of serial traffic accidents due to the lack of information sharing with surrounding vehicles. However, using CCTV and V2X infrastructure facilities, the port road Safety accidents in the port can be prevented by directly checking the status.

According to the disclosure, a hybrid V2X communication device is used to collect the location of the vehicle using V2X communication in areas where a V2X base station is installed, and the location of the vehicle is collected using a mobile communication network only in areas where there is no V2X base station. Communication network usage fees can be minimized.

According to the present invention, data via V2X RSU can be used as real-time data due to low delay time in data collection and transmission, thereby providing real-time location tracking service for autonomous port tractors.

By starting the work, safety accidents within the port can be prevented by informing surrounding vehicles of dangerous situations such as potholes, road work sections, illegally parked vehicles, reverse-running vehicles, and low-speed vehicles that occur on the road to self-driving tractors.

With the launch, it is possible to provide real-time information on dangerous situations that may occur in autonomous port tractors using V2X base stations densely built within the port.

Figure 1 is a diagram illustrating a technology in which a vehicle communicates with an external server through a roadside unit (RSU) and a V2X server according to an disclosure.
Figure 2 is a diagram schematically illustrating a method of guiding the optimal driving route to vehicles in a hybrid V2X-based port cooperative autonomous driving cargo transportation system.
Figure 3 is a diagram illustrating the configuration of a device that guides the optimal driving route to vehicles in a hybrid V2X-based port cooperative autonomous driving cargo transportation system by one disclosure.
FIG. 4 is a diagram illustrating a configuration in which a device that guides the optimal driving path to a vehicle in a hybrid V2X-based port cooperative autonomous cargo transportation system communicates with an external device and an external server.
Figure 5 is a diagram illustrating the flow of a service that guides the optimal driving route to vehicles in a hybrid V2X-based port cooperative autonomous driving cargo transportation system by one start.
FIG. 6 is a diagram illustrating technical features for creating an optimal driving path for a vehicle according to an exemplary embodiment of the present disclosure.
Figure 7 is a diagram showing the configuration of a processor including an artificial intelligence learning model according to an disclosure.

Hereinafter, the present disclosure will be described in detail with reference to the accompanying drawings.

Terms used in this specification will be briefly described, and the present disclosure will be described in detail.

The terms used in the embodiments of the present disclosure have selected general terms that are currently widely used as much as possible while considering the functions in the present disclosure, but this may vary depending on the intention or precedent of a person working in the art, the emergence of new technology, etc. . In addition, in certain cases, there are terms arbitrarily selected by the applicant, and in this case, the meaning will be described in detail in the description part of the relevant disclosure. Therefore, the terms used in this disclosure should be defined based on the meaning of the term and the overall content of this disclosure, rather than simply the name of the term.

In this specification, expressions such as “have,” “may have,” “includes,” or “may include” refer to the presence of the corresponding feature (e.g., a numerical value, function, operation, or component such as a part). , and does not rule out the existence of additional features.

The expression at least one of A or/and B should be understood as referring to either “A” or “B” or “A and B”.

As used herein, expressions such as “first,” “second,” “first,” or “second,” can be used to express various components regardless of order and/or importance, and can represent one component. It is only used to distinguish from other components and does not limit the components.

A component (e.g., a first component) is “(operatively or communicatively) coupled with/to” another component (e.g., a second component). When referred to as “connected to,” it should be understood that a certain component can be connected directly to another component or connected through another component (e.g., a third component).

Singular expressions include plural expressions unless the context clearly dictates otherwise. In this application, terms such as “comprise” or “consist of” are intended to designate the presence of features, numbers, steps, operations, components, parts, or combinations thereof described in the specification, but are intended to indicate the presence of one or more other It should be understood that this does not exclude in advance the presence or addition of features, numbers, steps, operations, components, parts, or combinations thereof.

In the present disclosure, a “module” or “unit” performs at least one function or operation, and may be implemented as hardware or software, or as a combination of hardware and software. In addition, a plurality of “modules” or a plurality of “units” are integrated into at least one module and implemented by at least one processor (not shown), except for “modules” or “units” that need to be implemented with specific hardware. It can be.

Hereinafter, the device 10 that guides the optimal driving route to vehicles in the hybrid V2X-based port cooperative autonomous cargo transportation system will be abbreviated as the driving route guidance device 10.

Figure 2 is a diagram schematically illustrating a method of guiding the optimal driving route to vehicles in a hybrid V2X-based port cooperative autonomous driving cargo transportation system.

By way of disclosure, the driving route guidance device 10 may be included in a vehicle or may be included in an external server.

By way of disclosure, the driving route guidance device 10 may obtain information on the road environment of the port and destination information of the vehicle, and generate movement route information of the vehicle. As a start, the travel route guidance device 10 can determine the vehicle's travel route information using an artificial intelligence model.

By way of disclosure, the driving route guidance device 10 may determine whether the vehicle is located in the V2X communication service area.

By way of disclosure, when the vehicle is located in the V2X communication service area, the travel route guidance device 10 may transmit travel route information to the vehicle using the V2X communication service in the first order. Here, the first sequence number has priority over the second sequence number.

As a result of the disclosure, the route guidance device 10 may transmit the route information to the vehicle using a mobile communication service in a second order.

By way of disclosure, when the vehicle is not located in the V2X communication service area, the travel route guidance device 10 may transmit travel route information to the vehicle using the mobile communication device in the first order. Next, by the start of the operation, the route guidance device 10 may attempt to transmit the route information to the vehicle using the V2X communication service in the second turn.

By the start, the driving route guidance device 10 continuously attempts to provide information using the V2X communication service even in situations where the vehicle must use a mobile communication network, and immediately provides information using the V2X communication service when the vehicle enters the V2X communication service area. By receiving based movement route information, movement route information can be transmitted without interruption of communication.

By the start of the operation, the route guidance device 10 first determines whether the vehicle is located in the V2X service area or the mobile communication service area in order to transmit information indicating that the vehicle's movement route has changed from A to B. You can judge. In addition, by way of disclosure, the driving route guidance device 10 may attempt to communicate using a V2X communication service and a mobile communication service at the same time in order to safely and quickly transmit the vehicle's travel route information.

According to another embodiment, the driving route guidance device 10 may simultaneously transmit the minimum identification information of the vehicle to the vehicle using a V2X communication service and a mobile communication service.

If the vehicle first receives the minimum identification information through the V2X communication service, the driving route guidance device 10 determines that the vehicle is located in the V2X communication service area and transmits the movement route information to the vehicle by preferentially using the V2X communication service. You can. On the other hand, when the vehicle first receives the minimum identification information through the mobile communication service, the driving route guidance device 10 determines that the vehicle is not located in the V2X communication service area and uses the mobile communication service and the V2X communication service simultaneously. Thus, movement route information can be transmitted to the vehicle.

The driving route guidance device 10 by one start may transmit vehicle location information, vehicle status information, and vehicle movement path information to the V2X server 300 through the V2X RSU (roadside base station, 200). Vehicle status information may include, for example, vehicle-related sensing information, remaining battery capacity, operation mode, operation destination, current speed, current location, etc., and vehicle movement path information may include vehicle movement speed, direction of movement, and destination. may include information.

The driving route guidance device 10 by one start may transmit vehicle status information to the port control server (FMS, 600) through the V2X server 300. However, in order for the driving route guidance device 10 by one start to use the V2X communication system, the vehicle must be included in the V2X service area.

Communication technology in the V2X field is largely divided into V2X Wave (WAVE: Wireless Access Vehicular Environment, Wi-Fi-based vehicle communication) and C-V2X. What they have in common is that vehicles can communicate over short distances, but the differences appear in the communication method. C-V2X uses existing mobile carrier base stations. On the other hand, Wi-Fi-based V2X Wave requires a dedicated roadside base station (RSU: Roadside Unit) to be able to communicate. V2X wave technology is advantageous for smooth real-time communication in an environment with high information processing.

Therefore, when the driving route guidance device 10 is not in an area without a V2X RSU 200 or a V2X communication service area, the route information device 10 uses the mobile communication network 400 to communicate with the port control server 600 through the mobile communication server 500. Information about the vehicle and travel route information can be transmitted.

The driving route guidance device 10 collects message information and traffic information including the current location and time information from the driving route guidance device 10 through the mobile communication network 400 through PVD communication in real time and sends it to the port control server 600. ), and the control information and surrounding traffic information transmitted from the port control server 600 can be provided to other vehicles in the area.

By the start of the operation, the route guidance device 10 can communicate with the V2X RSU 200 in JSON format, and the V2X RSU 200 and the V2X server 300 can communicate with the port control server (FMS, 600) and international standards. By applying ISO 15784 (including TIC4.0), information can be exchanged according to the communication environment suitable for the domestic environment.

Figure 3 is a diagram illustrating the configuration of a device that guides the optimal driving route to vehicles in a hybrid V2X-based port cooperative autonomous driving cargo transportation system by one disclosure.

The driving route guidance device 10 according to one disclosure may include a processor 20, a memory 30, and a communication unit 40. The driving route guidance device 10 by way of example may be included in a vehicle, or may be included in an external server or external device outside the vehicle.

Here, the external server and external device may include devices capable of communication, for example, a desktop computer, a laptop computer, a laptop, a smart phone, and a tablet PC. (tablet PC), mobile phone, smart watch, smart glass, e-book reader, PMP (portable multimedia player), portable game console, navigation device, digital camera ( digital camera), DMB (digital multimedia broadcasting) player, digital audio recorder, digital audio player, digital video recorder, digital video player, PDA ( Personal Digital Assistant), etc.

The processor 20 according to one disclosure typically controls the overall operation of the navigation route guidance device 10. For example, the processor 20 can generally control other components included in the driving route guidance device 10 by executing programs stored in the memory 30. Additionally, the processor 20 may perform the function of the driving route guidance device 10 by executing programs stored in the memory 30. Processor 20 may include at least one processor. Depending on its function and role, the processor 20 may include a plurality of processors or may include one processor in an integrated form. In one embodiment, the processor 20 may include at least one processor configured to provide a notification message by executing at least one program stored in the memory 30.

The memory 30 may store programs for processing and control of the processor 20, and may also store data input to the driving route guidance device 10 or output from the solar power generation facility monitoring device 100. .

The memory 30 may be a flash memory type, hard disk type, multimedia card micro type, card type memory (for example, SD or XD memory 30, etc.). ), RAM (Random Access Memory), SRAM (Static Random Access Memory), ROM (Read-Only Memory), EEPROM (Electrically Erasable Programmable Read-Only Memory), PROM (Programmable Read-Only Memory), magnetic memory , may include at least one type of storage medium among a magnetic disk and an optical disk.

Programs stored in the memory 30 can be classified into a plurality of modules according to their functions. Here, the plurality of modules refers to functionally operating modules that are software rather than hardware.

The memory 30 may store a program for processing and controlling the processor 20, and may also store images input to the driving route guidance device 10 or guide information output from the driving route guidance device 10. . Additionally, the memory 30 may store specific information for determining whether to output guide information.

Additionally, the processor 20 can communicate with other devices and other servers using the communication unit 40. The communication unit may include one or more components that allow the driving route guidance device 10 to communicate with other devices (not shown) and servers (not shown). Other devices (not shown) may be computing devices such as the solar power plant monitoring device 100 or sensing devices, but are not limited thereto. For example, the communication unit may include a short-range communication unit, a mobile communication unit, and a broadcast reception unit.

The short-range wireless communication unit includes a Bluetooth communication unit, BLE (Bluetooth Low Energy) communication unit, Near Field Communication unit, WLAN (Wi-Fi) communication unit, Zigbee communication unit, and infrared (IrDA) communication unit. Data Association) communication department, WFD (Wi-Fi Direct) communication department, UWB (ultra wideband) communication department, Ant+ communication department, etc., but is not limited thereto.

The mobile communication unit transmits and receives wireless signals to at least one of a base station, an external terminal, and a server on a mobile communication network. Here, the wireless signal may include various types of data according to voice call signals, video call signals, or text/multimedia message transmission and reception.

As a start, the driving route guidance device 10 may identify the type of event using an event type identification model based on the acquired image information of the event.

The event type identification model is created based on the results of pre-learning image/video information for each event type classified according to preset criteria using a preset artificial intelligence algorithm, and is a convolutional neural network (CNN). This may be included. In addition to convolutional neural networks, event type identification models can also be combined with recurrent neural networks (RNNs) and created according to the learned results.

Here, events may include vehicles, people, dynamic objects, and static objects. Dynamic objects may include all objects and living things that move on the road, and static objects may include various objects, including falling objects and stones that have fallen on the road. Events can be classified in detail according to the current state of the event, and the number is not limited.

For example, vehicle-related events include high-speed vehicles (2004), slow-moving vehicles (2005), illegally stopped vehicles (2006), vehicles traveling in reverse (2007), objects falling from vehicles (2008), and traffic accidents (2003). It may include, but is not limited to.

By the start, the route guidance device 10 predicts at least one of a change in the distance between the event and the autonomous vehicle, a change in the relative speed of the event, and a change in the location of the event using a collision prediction model based on information about the event. After that, the predicted collision time between the event and the autonomous vehicle can be calculated.

The collision prediction model is learned based on information about vehicles and objects on the road. The collision prediction model can be learned using a machine learning algorithm. Here, the machine learning algorithms are Gradient Descent, Artificial Neural Network, Naive Bayes Classifier (NBC), Hidden Markov Model (HMM), K-Means Clustering, k-Nearest Neighbors (k-NN), and Support Vector. It can be at least one of Machine (SVM).

By way of example, the driving path guidance device 10 may obtain information about other vehicles and obstacles around the vehicle from various sensors included in the vehicle.

Sensors included in a vehicle according to an disclosure must be equipped with a plurality of various types of sensors to detect various objects on the road and surrounding vehicles. For example, radar (Radio Detection And Ranging, RADAR), LiDAR sensors, image sensors, and ultrasonic sensors are used.

In particular, LiDAR sensors can detect surrounding vehicles in all directions around an autonomous vehicle in real time. The LiDAR included in the vehicle is installed at a preset location on the self-driving vehicle and rotates in a preset direction to irradiate pulse lasers in all directions around the self-driving vehicle. Lidar can obtain information about the vehicle's surroundings by receiving reflected pulse lasers from all directions around the autonomous vehicle. LiDAR sensors can be installed to detect information in areas corresponding to different ranges of azimuths among the 360-degree azimuths around the autonomous vehicle.

In addition, by the start of the operation, the route guidance device 10 can obtain image information about the road and the surrounding situation from CCTV installed in the port.

The driving route guidance device 10 receives images captured through the CCTV 220. CCTV (220) can be installed on multiple V2X RSUs (200) installed in the port, and its installation location is not limited. The video captured by the CCTV 220 can be transmitted to the port control server 600 using the V2X communication system, thereby achieving economic benefits.

The driving route guidance device 10 by way of example can recognize a dynamic object and confirm its location in an image frame obtained from a CCTV video. Here, the recognition of dynamic objects can utilize artificial intelligence. In identifying dynamic objects such as vehicles, people, bicycles, etc. included in a video frame, it is possible to recognize multiple objects in one image at a speed close to real-time. At this time, artificial intelligence is used to learn the object to be recognized, and then , A model that tracks the objects in the frame of the CCTV video is applied. Meanwhile, the artificial intelligence technology for analyzing video information in the present invention is Faster RCNN and YOLO. , any one of SSDs can be used and is not limited to this. Faster RCNN is a model that has been improved from the initial RCNN to Fast RCNN with the goal of real-time processing speed, but has a very small region proposal. By using a regression network called network for selective search, YOLO shows processing speed performance of 250 times that of RCNN and 25 times that of Fast RCNN, not in the pixel unit of the image but in the grid unit corresponding to n boxes. It is a method of tracking objects by dividing them into two parts, and SSD is a model suitable for a real-time detection system with close real-time distance performance. It is a model suitable for various target objects in one image based on feature maps of various sizes. It is a model that shows balanced accuracy and processing speed by tracking .

Next, the driving path guidance device 10 by one start can convert the location of the recognized dynamic object into a global coordinate system. In the embodiment of the present invention, the CCTV image used as input information has horizontal (X) and vertical (Y) resolutions of 1920 and 1080, respectively, while visualization using precision, aerial, and general maps has latitude -19 to 90 , uses the WGS84 coordinate system, which ranges from -180 to 180 longitude. Therefore, in order to map the exact position of the object tracked in the input image, a transformation matrix that can explain the differences (translate, rotation, scale) between coordinate systems is required. The dimension of CCTV video and visualization is to convert the location defined in the video coordinate system to the map coordinate system through a transformation matrix in which the coordinate system conversion relationship between the CCTV coordinate system and the map is established, and the present invention used the H calculation method in terms of usability verification. H is a method mainly used for coordinate system conversion between 2D-2D and 2D-3D.

More specifically, when looking at the same point x from cameras in two different directions, a 3*3 matrix defining the movement, rotation, etc. between the point Coordinate transformation is possible through the definition of the transformation relationship.

For example, by using the WGS coordinate system corresponding points for the invariant feature points of the CCTV image, invariant feature points (lanes, road markings, crosswalks, etc.) in the CCTV image are defined, and the road information is measured and produced in WGS84 coordinates. By defining points corresponding to image feature points on the map with high precision, the location of the object can be converted through a manual method.

Equation 1 below is used to transform the position of an object, and 25 invariant feature points can be defined for each image to calculate the transformation relationship between coordinate systems.

[Equation 1]

here, represents the position of the dynamic object in the WGS84 coordinate system, represents the object location within the video image.

And the dynamic object information converted to a coordinate system can be output for use. At this time, dynamic object information is output as object type, location, ID, etc., and as properties of one dynamic object, a process of bundling them into one data set is required for easy transmission and use, and the formats that can be applied for this purpose are It can vary. For example, by adopting the json format, which is fast and stable in encoding and decoding, you can define the attribute information output as a result of identification and tracking of dynamic objects.

The dynamic object information defined in this way can be visualized and provided on a web-based basis by mapping the dynamic object information to the context map after the visualization module receives the dynamic object information and performs decoding.

FIG. 4 is a diagram illustrating a configuration in which a device that guides the optimal driving path to a vehicle in a hybrid V2X-based port cooperative autonomous cargo transportation system communicates with an external device and an external server.

As a start, the driving route guidance device 10 can acquire vehicle surrounding environment sensing information 4001 from vehicles in the port, CCTVs installed in the port, external servers, and sensors installed in the port. The driving route guidance device 10 can send the vehicle surrounding environment sensing information 4001 to the port control server and use it as basic information for controlling the vehicle.

By way of disclosure, when the vehicle is located in a V2X communication service area, the route guidance device 10 may receive destination and/or movement route information from the external server 600 using the vehicle's V2X receiver 130. . At this time, if the vehicle is not located in the V2X communication service area, the channel switch 150 can be controlled to receive movement route information from an external server using the vehicle's mobile communication device 110.

By way of disclosure, the central processing unit 140 of the hybrid V2X terminal 100 may determine whether a vehicle including a hybrid V2X communication system is located in the V2X communication service area.

For example, if the driving route guidance device 10 can continuously receive V2I through the V2X receiver 130, it may determine that a vehicle including a hybrid V2X communication system is located in the V2X communication service area, and the V2X receiver If the V2I signal is not received through (130), it may be determined that the vehicle including the hybrid V2X communication system is not located in the V2X communication service area.

The mobile communication device 110 displays real-time vehicle status information on a context map, displays real-time traffic information to the vehicle's destination, and uses a first artificial intelligence learning model to determine the most appropriate task for the vehicle. You can create and display a route.

The first artificial intelligence learning model by one disclosure includes vehicle status information including the type of vehicle, vehicle transportation purpose, destination, vehicle speed, and vehicle status, and surrounding environment information including road information and weather information. You can create a suitable path generation model by learning. The mobile communication device 110 according to one disclosure may determine the most suitable travel path for the current vehicle using a suitable path creation model.

By way of disclosure, the driving route guidance device 10 may acquire the location information of the V2X base station installed on the road on which the vehicle passes and the communication service area of the V2X base station in order to determine whether the vehicle is located in the V2X communication service area. Multiple V2X base stations can be installed to provide V2X communication services to surrounding areas.

By way of disclosure, the driving route guidance device 10 can determine in real time whether the current location of the vehicle corresponds to the V2X communication service area based on road information, vehicle location information, and vehicle speed information.

The driving route guidance device 10 generates vehicle status information based on vehicle control information and then determines whether the vehicle is located in the V2X communication service area. If the vehicle is located in the V2X communication service area, the vehicle's V2X transmitter Vehicle status information can be transmitted to an external server using (120).

By way of disclosure, when the vehicle leaves the V2X communication service area, the driving route guidance device 10 may transmit vehicle status information to an external server using the mobile communication device 110 rather than the V2X transmitter 120.

The mobile communication device 110 according to one disclosure is a communication network aimed at performing communication between moving objects or between a moving object and the outside of the moving object, and is capable of providing unique functions targeting a moving object, such as tracking the location of a moving object, setting a base station, and setting a route. It may include functions and may include communication methods such as LTE, 5G, and 6G. There are no restrictions on the type of communication method.

The vehicle control unit 101 is responsible for overall control of the vehicle, and in particular, can control autonomous driving of the vehicle based on control information received from the external server 600.

For example, control information is provided to each moving object such as a yard truck or crane traveling on a port, considering the current location of the moving object, destination, port facilities, and the amount of change in the position of other moving objects. A safe driving route can be included, and various routes such as a safe driving route, a route that improves work efficiency, and the shortest route can be created according to user options.

By starting, the port control server 600 can determine whether the vehicle is located in an area where V2X communication is possible. For example, when the port control server 600 receives a V2I communication message from a vehicle, it may determine that the vehicle is in a V2X communication capable area, and when it receives a PVD communication message, it may determine that the vehicle is in a V2X communication unavailable area. .

When the port control server 600 determines that the vehicle is located in an area where V2X communication is possible, destination information and movement route are sent to the vehicle's V2X receiver 130 through the V2X server 300 and the V2X base station (RSU, 200). Information can be transmitted. Additionally, vehicle control information for changing the travel route can also be transmitted.

Figure 5 is a diagram illustrating the flow of a service that guides the optimal operation route to vehicles in a hybrid V2X-based port cooperative autonomous driving cargo transportation system by one start.

By way of example, the port control server 600 may receive the vehicle's destination and/or movement path information from an external server and an external device. Here, the movement path information may be the optimal movement route for the vehicle to move to the destination. Here, the optimal travel route is created based on the driving mode (safe mode, high-speed mode, etc.) according to the vehicle's driving purpose, and can change in real time depending on the surrounding environment of the road, presence of obstacles, presence of other vehicles, etc.

By way of disclosure, the port control server 600 can transmit the vehicle movement path to the vehicle by simultaneously using V2X communication and mobile communication servers, as discussed above. When using V2X communication, the V2X server 300 is used, and when using mobile communication, the mobile communication network 400 can be used to communicate with the vehicle's hybrid V2X terminal 100.

FIG. 6 is a diagram illustrating technical features for creating an optimal driving path for a vehicle according to an exemplary embodiment of the present disclosure.

The driving route guidance device 10 by way of example may obtain driving information of vehicles surrounding the vehicle in order to generate movement route information of the vehicle.

As shown in (a) of FIG. 6, the driving route guidance device 10 by one start can determine the first vehicle 6001 having the same driving direction as the vehicle 6000 using the driving information of surrounding vehicles. there is.

By way of disclosure, the driving path guidance device 10 may determine vehicles having the same road and the same driving direction based on path history and path prediction based on a Global Positioning System (GPS).

By way of disclosure, the driving route guidance device 10 may receive the direction value of another vehicle through vehicle-to-vehicle (V2V) communication. Additionally, the communication unit 120 can perform communication between the vehicle and the infrastructure already built around the road on which the vehicle is driving through vehicle-to-infrastructure (V2I) communication. The driving route guidance device 10 may include all communication methods with low delay and high efficiency for information exchange between vehicles and between vehicles and infrastructure.

By starting, the driving path guidance device 10 measures the direction value of the vehicle. At this time, the direction value includes heading, yaw rate, steering angle, etc. Heading refers to the deviation between true north, which is the direction of Polaris, which is always unchanging, and the vehicle's direction. The yaw rate refers to the angular velocity of the yaw value that occurs around the vertical axis of the vehicle when the vehicle's direction of travel is toward the left or right. Additionally, the steering angle refers to the angle at which the spindle of the steering wheel turns when the vehicle changes direction.

The driving route guidance device 10 by way of example may determine the second vehicle 6003 located in the lane in which the vehicle is traveling and the third vehicle 6002 located in the lane in which the first vehicle 6001 is traveling.

The driving path guidance device 10 by one start calculates the probability of collision with the vehicle based on the speed of the first vehicle 6001, the second vehicle 6003, and the third vehicle 6002 and the distance to the vehicle, , lane change information of the vehicle can be generated based on the calculated value and the driving mode of the vehicle.

In addition, the travel route guidance device 10 by one start provides the travel route of the vehicle 6000.

The driving path guidance device 10 by way of example may obtain information on obstacles located in the vehicle's travel path, and may use the obstacle information to determine whether the vehicle will collide with the obstacle if it maintains its current travel path.

The travel route guidance device 10 by one start can create a new travel route to avoid obstacles.

When the travel route of the vehicle changes, the travel route guidance device 10 by one disclosure may transmit information about the changed travel route of the vehicle to vehicles surrounding the vehicle.

The driving route guidance device 10 receives information such as the curvature radius of the vehicle 6000, GPS-based route history and predicted route, and direction values of the vehicle 6000 and other vehicles. Here, the radius of curvature can be used to check whether surrounding vehicles are in the same lane as the vehicle. Additionally, route history and predicted routes can be used to limit communicating vehicles to vehicles on the same road and with the same direction of travel, as described above.

Meanwhile, (b) of FIG. 6 shows a situation where the fourth vehicle 6004 is within the photographable range of the vehicle 6000 and is entering a curved road, and the vehicle 6000 is driving in a straight line. In this case, if the driving route guidance device 10 uses only the direction value to determine a lane change, it may determine that the fourth vehicle 6004 has changed lanes even though it has not actually changed lanes. Accordingly, if the fourth vehicle 6004 is within the photographable range of the vehicle 6000, but the road on which it is traveling is a curved road, the image captured by the vehicle's camera can be used to determine lane change. In this way, a lane change decision can be made using the captured image acquired by the imaging unit in addition to the direction value.

By way of example, the driving route guidance device 10 may generate step-by-step warning notification information based on the result of calculating the possibility of collision with the vehicle according to the characteristics of the vehicle's surrounding vehicles. For example, if a nearby vehicle driving in front of the vehicle attempts to change lanes suddenly, the possibility of collision can be calculated based on the current moving speeds of the vehicle and the surrounding vehicle, and a warning notification level can be set accordingly.

As a start, when a lane change of a surrounding vehicle is confirmed, the driving route guidance device 10 may calculate a stopping distance to avoid collision between the vehicle and the surrounding vehicle. Here, the stopping distance is calculated as the product of the vehicle's speed and stopping time. At this time, the stopping time can be expressed as the sum of the reaction time and braking time. Here, the reaction time is the time from when the vehicle recognizes the obstacle and starts braking, which is about 2 seconds or less. Additionally, the braking time is the time from when braking begins until the vehicle stops. The braking time may vary depending on the current speed of the vehicle and the vehicle's brake performance.

By starting, the route guidance device 10 calculates the required speed for maintaining a safe distance between the lane-changing vehicles based on the stopping time, and controls the speed of the own vehicle at the calculated required speed to separate the own vehicle from the lane-changing vehicle. Collisions between vehicles can be avoided, or new movement paths can be created to avoid collisions with vehicles.

Figure 7 is a diagram showing the configuration of a processor including an artificial intelligence learning model according to an disclosure.

The central processing unit 140 of the driving route guidance device 10 according to one disclosure may include at least one of a data learning unit 21 and a control information generating unit 22.

By way of disclosure, the driving route guidance device 10 may acquire noise data, vibration data, and combustion pressure measurement data obtained using sensors included in the vehicle.

By the start, the driving route guidance device 10 can diagnose the driving condition of the vehicle by learning noise data, vibration data, combustion pressure measurement data, and information about the purpose of vehicle operation using a second artificial intelligence learning model. .

By way of example, the driving route guidance device 10 may determine the driving mode of the vehicle in real time based on the driving state of the vehicle. Additionally, vehicle control information may be generated based on the determined driving mode of the vehicle and transmitted to the vehicle.

The second artificial intelligence learning model refers to a deep learning model learned to generate control data and driving paths for autonomous driving by analyzing preprocessed sensor data, or a processor that executes it.

The data learning unit 21 by one start can learn noise data, vibration data, combustion pressure measurement data, and information about the purpose of vehicle operation. Specifically, the data learning unit 21 may learn criteria for diagnosing the driving state of the vehicle from noise data, vibration data, combustion pressure measurement data, and information on the purpose of vehicle operation. Additionally, the data learning unit 21 may learn control information according to the driving state of the vehicle according to the driving state of the vehicle. That is, the data learning unit 21 can generate, learn, or update new vehicle control information based on the accumulated driving status of the vehicle.

The processor 140 may determine the driving mode of the vehicle by analyzing the driving state of the vehicle according to the learned criteria. Additionally, the processor 140 can extract data necessary for learning from the vehicle's driving information, status information, and road surrounding environment information. From this, the data learning unit 21 can create and update the vehicle control information generation model.

The control information generator 22 can recognize the situation from predetermined data using the learned vehicle control generation model. The control information generator 22 may acquire predetermined data according to a preset standard through learning and use a data recognition model using the acquired data as an input value. For example, using the learned context model, etc. to analyze the vehicle's status information, driving history, destination information, vehicle operation purpose information, traffic information, previously stored map information, and vehicle's surrounding environment information, etc., and create a driving route. Data can be extracted for Additionally, using the learned model, the control information generator 22 can obtain information about the current surrounding situation from an external server and generate the most appropriate driving mode for the vehicle. Here, the driving mode may include a driving time reduction mode, a stable driving mode, an obstacle detection mode, a driving mode according to vehicle defects, etc., and there is no limit to the number of modes.

At least a portion of the data learning unit 21 and at least a portion of the control information generating unit 22 may be implemented as a software module or may be manufactured in the form of at least one hardware chip and mounted on an electronic device. For example, at least one of the data learning unit 21 and the control information generating unit 22 may be manufactured in the form of a dedicated hardware chip for artificial intelligence (AI), or an existing general-purpose processor (e.g. It may be manufactured as part of a CPU or application processor) or a graphics-specific processor (e.g., GPU) and installed in the various electronic devices or content data playback devices described above. At this time, the dedicated hardware chip for artificial intelligence is a dedicated processor specialized in probability calculations, and has higher parallel processing performance than existing general-purpose processors, so it can quickly process computational tasks in the field of artificial intelligence such as machine learning. If the data learning unit 21 and the control information generating unit 22 are implemented as a software module (or a program module including instructions), the software module is a non-transitory readable recording medium that can be read by a computer. It can be stored on (non-transitory computer readable media). In this case, the software module may be provided by an OS (Operating System) or a predetermined application. Alternatively, some of the software modules may be provided by an operating system (OS), and others may be provided by a predetermined application.

In the computer program stored in a computer-readable non-transitory recording medium, obtaining information about the road environment of the port and destination information of the vehicle, generating movement route information of the vehicle, determining whether the vehicle is located in the V2X communication service area Determining whether the vehicle is located in the V2X communication service area, transmitting movement route information to the vehicle using the V2X communication service in the first order, and moving route information using the mobile communication service in the second order A computer program stored on a recording medium that performs the steps of transmitting information to a vehicle may be provided.

Additionally, the computer program may be provided stored in a recording medium that performs all the method steps provided by the present invention.

The steps of the method or algorithm described in connection with embodiments of the present invention may be implemented directly in hardware, implemented as a software module executed by hardware, or a combination thereof. The software module may be RAM (Random Access Memory), ROM (Read Only Memory), EPROM (Erasable Programmable ROM), EEPROM (Electrically Erasable Programmable ROM), Flash Memory, hard disk, removable disk, CD-ROM, or It may reside on any type of computer-readable recording medium well known in the art to which the present invention pertains.

The components of the present invention may be implemented as a program (or application) and stored in a medium in order to be executed in conjunction with a hardware computer. Components of the invention may be implemented as software programming or software elements, and similarly, embodiments may include various algorithms implemented as combinations of data structures, processes, routines or other programming constructs, such as C, C++, , may be implemented in a programming or scripting language such as Java, assembler, etc. Functional aspects may be implemented as algorithms running on one or more processors.

Above, embodiments of the present invention have been described with reference to the attached drawings, but those skilled in the art will understand that the present invention can be implemented in other specific forms without changing its technical idea or essential features. You will be able to understand it. Therefore, the embodiments described above should be understood in all respects as illustrative and not restrictive.

Claims (10)

Generate a suitable route generation model by learning vehicle status information including the type of vehicle, vehicle operation purpose, destination, vehicle speed, and vehicle status, and surrounding environment information including road information and weather information, generating movement path information of the vehicle using the appropriate path creation model;
Using driving information of vehicles surrounding the vehicle, determining a first vehicle having the same driving direction as the vehicle;
determining a second vehicle located in the lane in which the vehicle is traveling and a third vehicle located in the lane in which the first vehicle is traveling;
Calculate the probability of colliding with the vehicle based on the speed of the first vehicle, second vehicle, and third vehicle and the distance to the vehicle, and calculate the probability of collision with the vehicle based on the calculated collision probability value and the driving mode of the vehicle. Modifying movement path information of the vehicle including lane change information;
Based on the results of acquiring noise data, vibration data, and combustion pressure measurement data obtained from the vehicle, and learning the noise data, vibration data, combustion pressure measurement data, and information about the purpose of vehicle operation using an artificial intelligence learning model. diagnosing the driving state of the vehicle and modifying vehicle movement path information based on the driving mode of the vehicle determined based on the driving state of the vehicle;
When the vehicle is located in a V2X communication service area, transmitting the movement path information to the vehicle using the V2X communication service in a first order; and
A method of guiding the optimal driving route to a vehicle in a hybrid V2X-based port cooperation autonomous cargo transportation system, comprising transmitting the movement route information to the vehicle using a mobile communication service in a second turn. delete According to claim 1,
When the vehicle is not located in a V2X communication service area, preferentially transmitting the movement route information to the vehicle using a mobile communication device; and
A method of guiding the optimal driving route to a vehicle in a hybrid V2X-based port cooperative autonomous cargo transportation system, including the step of continuously attempting to transmit the movement route information to the vehicle using the V2X communication service. . According to claim 1,
Simultaneously transmitting the minimum identification information of the vehicle to the vehicle using a V2X communication service and a mobile communication service;
When the vehicle first receives the minimum identification information through the V2X communication service, it is determined that the vehicle is located in the V2X communication service area and the movement path information is transmitted to the vehicle by preferentially using the V2X communication service,
When the vehicle first receives the minimum identification information through the mobile communication service, it is determined that the vehicle is not located in the V2X communication service area, and the movement path information is provided by using the mobile communication service and the V2X communication service simultaneously. A method of guiding the optimal driving route to vehicles in a hybrid V2X-based port cooperative autonomous driving cargo transportation system, including the step of transmitting to the vehicle. According to claim 1,
Information on the road environment of the above port,
It includes images obtained from CCTV installed in the port and sensing information obtained from a plurality of vehicles located in the port,
The destination information of the vehicle is,
A method of guiding the optimal operation route to a vehicle of a hybrid V2X-based port cooperative autonomous cargo transportation system, which includes destination information determined according to the purpose of operation of the vehicle and destination information changed during operation of the vehicle. delete delete According to claim 1,
If the movement route of the vehicle changes,
A method of guiding the optimal driving route to a vehicle in a hybrid V2X-based port cooperative autonomous cargo transportation system, comprising the step of transmitting information on the changed movement path of the vehicle in real time to vehicles surrounding the vehicle. A communication unit that communicates with an external device;
a memory storing at least one instruction; and
Comprising a processor executing the at least one instruction,
The processor,
Generate a suitable route generation model by learning vehicle status information including the type of vehicle, vehicle operation purpose, destination, vehicle speed, and vehicle status, and surrounding environment information including road information and weather information, Generate movement path information of the vehicle using the appropriate path generation model,
Using driving information of vehicles surrounding the vehicle, determine a first vehicle having the same driving direction as the vehicle,
Determining a second vehicle located in the lane in which the vehicle is traveling and a third vehicle located in the lane in which the first vehicle is traveling,
Calculate the probability of colliding with the vehicle based on the speed of the first vehicle, second vehicle, and third vehicle and the distance to the vehicle, and calculate the probability of collision with the vehicle based on the calculated collision probability value and the driving mode of the vehicle. Modify the vehicle's movement path information, including lane change information,
Based on the results of acquiring noise data, vibration data, and combustion pressure measurement data obtained from the vehicle, and learning the noise data, vibration data, combustion pressure measurement data, and information about the purpose of vehicle operation using an artificial intelligence learning model. Diagnose the driving state of the vehicle, and modify vehicle movement path information based on the driving mode of the vehicle determined based on the driving state of the vehicle,
If the vehicle is located in the V2X communication service area, the movement path information is transmitted to the vehicle using the V2X communication service in the first order,
A device that guides the optimal driving route to the vehicle of the hybrid V2X-based port cooperation autonomous cargo transportation system, which transmits the movement route information to the vehicle using a mobile communication service in the second order. In a computer program stored on a non-transitory computer-readable recording medium,
Generate a suitable route generation model by learning vehicle status information including the type of vehicle, vehicle operation purpose, destination, vehicle speed, and vehicle status, and surrounding environment information including road information and weather information, generating movement path information of the vehicle using the appropriate path creation model;
Using driving information of vehicles surrounding the vehicle, determining a first vehicle having the same driving direction as the vehicle;
determining a second vehicle located in the lane in which the vehicle is traveling and a third vehicle located in the lane in which the first vehicle is traveling;
Calculate the probability of colliding with the vehicle based on the speed of the first vehicle, second vehicle, and third vehicle and the distance to the vehicle, and calculate the probability of collision with the vehicle based on the calculated collision probability value and the driving mode of the vehicle. Modifying movement path information of the vehicle including lane change information;
Based on the results of acquiring noise data, vibration data, and combustion pressure measurement data obtained from the vehicle, and learning the noise data, vibration data, combustion pressure measurement data, and information about the purpose of vehicle operation using an artificial intelligence learning model. diagnosing the driving state of the vehicle and modifying vehicle movement path information based on the driving mode of the vehicle determined based on the driving state of the vehicle;
When the vehicle is located in a V2X communication service area, transmitting the movement path information to the vehicle using the V2X communication service in a first order; and
A computer program stored in a recording medium that performs a second step of transmitting the movement route information to the vehicle using a mobile communication service.