Apparatus and method for generating traffic information, and server

Abstract

The present disclosure relates to an apparatus and a method for generating traffic information configured to generate traffic information based on a vehicle that may or may not include a GPS or a communication device, and a server. An apparatus for generating traffic information includes a memory storing instructions for traffic information generation and a processor executing the instructions. The processor may determine a traveling vehicle by excluding duplicated vehicles from surrounding vehicles based on position information of a relay vehicle traveling on a road and vehicle information of the surrounding vehicles, the surrounding vehicles being detected by the relay vehicle, and generate traffic information based on traveling information of the traveling vehicle.

Description

[0001] Cross-reference to related applications

[0002] This application claims the benefit and priority of Korean Patent Application No. 10-2024-0094484, filed with the Korean Intellectual Property Office on July 17, 2024, the entire contents of which are incorporated herein by reference. Technical Field

[0003] This disclosure relates to apparatus and methods for generating traffic information, and more specifically, to techniques for generating traffic information based on vehicles that may or may not include GPS or communication equipment. Background Technology

[0004] Traffic information can be used to determine traffic flow on roads and can be used for traffic guidance and navigation.

[0005] Traffic information can be generated based on GPS data and direct collection of vehicle speeds on the road. To determine traffic information more accurately, data from a large number of vehicles needs to be collected.

[0006] However, many vehicles are not yet equipped with GPS and communication devices, or have established communication protocols with external servers to generate traffic information.

[0007] To supplement this, GPS information from in-vehicle mobile devices can be used. However, using information from mobile devices conflicts with regulatory requirements because this information is personal data, and traffic information from the vehicle becomes inaccurate when the user with the mobile device temporarily leaves the vehicle.

[0008] Therefore, a more accurate way to determine traffic information is needed. Summary of the Invention

[0009] One aspect of this disclosure provides an apparatus and method for generating traffic information, which is capable of collecting traffic information of vehicles without using personal information.

[0010] One aspect of this disclosure provides an apparatus and method for generating traffic information, which is capable of collecting traffic information from vehicles that are not equipped with GPS devices or communication devices.

[0011] The technical problems to be solved by this disclosure are not limited to those described above, and any other technical problems not mentioned herein will be clearly understood by those skilled in the art from the following description.

[0012] According to an aspect of the disclosure, a device for generating traffic information includes a memory storing instructions for traffic information generation, and a processor executing the instructions. The processor can determine a traveling vehicle by excluding duplicate vehicles from surrounding vehicles based on position information of a relay vehicle traveling on a road and vehicle information of the surrounding vehicles, the surrounding vehicles being detected by the relay vehicle, and generate traffic information based on travel information of the traveling vehicle.

[0013] According to an embodiment, the processor can identify license plate information from the vehicle information of the surrounding vehicles, and determine one of the surrounding vehicles having the same license plate information as the traveling vehicle.

[0014] According to an embodiment, the processor can decrypt the license plate information provided as encrypted data.

[0015] According to an embodiment, the processor can identify relative positions of the surrounding vehicles with respect to the relay vehicle from the vehicle information of the surrounding vehicles, determine absolute positions of the surrounding vehicles based on the position information of the relay vehicle and the relative positions of the surrounding vehicles, and determine one of the surrounding vehicles as the traveling vehicle among the surrounding vehicles having the same absolute position.

[0016] According to an embodiment, the processor can determine the absolute positions of the surrounding vehicles based on route information of the surrounding vehicles.

[0017] According to an embodiment, the processor can determine duplicate vehicles among the surrounding vehicles based on color information or size information of the vehicle information of the surrounding vehicles.

[0018] According to an embodiment, the processor can determine a speed of the traveling vehicle based on speed information of the relay vehicle and an amount of change in the relative position of the traveling vehicle over time, and include the speed information of the traveling vehicle in the traffic information.

[0019] According to an embodiment, the processor can determine a relative position of the traveling vehicle for a predetermined period of time, determine a relative speed of the traveling vehicle based on an amount of change in the relative position of the traveling vehicle for the predetermined period of time, and determine a speed of the traveling vehicle based on speed information of the relay vehicle and the relative speed of the traveling vehicle.

[0020] According to an embodiment, the processor can determine a detection time of the traveling vehicle detected by a side rear detection sensor of the relay vehicle, determine a relative speed of the traveling vehicle based on a detection distance of the side rear detection sensor and the detection time, and determine a speed of the traveling vehicle based on speed information of the relay vehicle and the relative speed of the traveling vehicle.

[0021] According to an embodiment, the processor can match the position information of the traveling vehicle and the speed of the traveling vehicle with a link connecting nodes corresponding to points where a speed change occurs.

[0022] According to an embodiment, the server can include the above-described apparatus, and the server is operatively connected to at least one vehicle.

[0023] According to an aspect of the disclosure, a method for generating traffic information includes receiving, by a server, location information of a relay vehicle on a road and vehicle information of surrounding vehicles detected by the relay vehicle, determining, by the server, a traveling vehicle by excluding duplicate vehicles from the surrounding vehicles based on the location information of the relay vehicle and the vehicle information of the surrounding vehicles, and generating, by the server, traffic information based on travel information of the traveling vehicle.

[0024] According to an embodiment, the determination of the traveling vehicle can include identifying license plate information from the vehicle information of the surrounding vehicles, and determining one of the surrounding vehicles having the same license plate information as the traveling vehicle.

[0025] According to an embodiment, the identifying of the license plate information from the vehicle information can include receiving license plate information recognized by the relay vehicle, the license plate information being encrypted data, and decrypting the encrypted data.

[0026] According to an embodiment, the determination of the traveling vehicle can include identifying relative positions of the surrounding vehicles with respect to the relay vehicle from the vehicle information of the surrounding vehicles, determining absolute positions of the surrounding vehicles based on the location information of the relay vehicle and the relative positions of the surrounding vehicles, and determining one of the surrounding vehicles having the same absolute position as the traveling vehicle among the surrounding vehicles.

[0027] According to an embodiment, the identifying of the relative positions of the surrounding vehicles can include identifying route information of the surrounding vehicles.

[0028] According to an embodiment, the determination of the traveling vehicle can further include using color information or size information of the vehicle information of the surrounding vehicles.

[0029] According to an embodiment, the generating of the traffic information based on the travel information of the traveling vehicle can further include determining a speed of the traveling vehicle based on speed information of the relay vehicle and a change amount of the relative position of the traveling vehicle over time.

[0030] According to an embodiment, the determination of the speed of the traveling vehicle can include determining a relative position of the traveling vehicle over a predetermined period of time, determining a relative speed of the traveling vehicle based on a change amount of the relative position of the traveling vehicle over the predetermined period of time, and determining the speed of the traveling vehicle based on speed information of the relay vehicle and the relative speed of the traveling vehicle.

[0031] According to an embodiment, the determining of the speed of the traveling vehicle can include determining a detection time at which the traveling vehicle is detected by a side rear detection sensor of the relay vehicle, determining a relative speed of the traveling vehicle based on a detection distance of the side rear detection sensor and the detection time, and determining the speed of the traveling vehicle based on the speed information of the relay vehicle and the relative speed of the traveling vehicle.

[0032] According to an embodiment, the generating of the traffic information can include matching the position and the speed of the traveling vehicle with a link, the link connecting nodes corresponding to points where a speed change occurs. BRIEF DESCRIPTION OF DRAWINGS

[0033] The above and other objects, features and advantages of the present disclosure will become more apparent from the following detailed description when taken in conjunction with the accompanying drawings, in which:

[0034] Figure 1 is a diagram for describing a method for generating traffic information according to an embodiment of the present disclosure;

[0035] Figure 2 is a block diagram illustrating a configuration of a system for generating traffic information according to an embodiment of the present disclosure;

[0036] Figure 3 is a diagram for describing a sensor device of a relay vehicle;

[0037] Figure 4 is a flowchart for describing a method for generating traffic information according to an embodiment of the present disclosure;

[0038] Figure 5 is a diagram for describing a method of matching a surrounding vehicle with a link;

[0039] Figure 6 is a flowchart for describing a method for generating traffic information according to another embodiment of the present disclosure;

[0040] Figure 7 is a diagram for describing an embodiment of determining a repeating vehicle;

[0041] Figure 8 is a diagram for describing a method of determining a repeating vehicle according to another embodiment;

[0042] Figure 9 and Figure 10 is a diagram for describing a method for determining speed information of a traveling vehicle according to an embodiment of the present disclosure;

[0043] Figure 11 is a diagram illustrating a computing system according to an embodiment of the present disclosure. DETAILED DESCRIPTION

[0044] It should be understood that the term "vehicle" or "vehicular" or other similar terms as used herein include broad definitions of motor vehicles such as passenger cars, including sport utility vehicles (SUVs), buses, trucks, various commercial vehicles, watercraft (including various boats and ships), aircraft, etc., and includes hybrid vehicles, electric vehicles, plug-in hybrid electric vehicles, hydrogen-powered vehicles, and other alternative fuel vehicles (e.g., fuel driven from resources other than petroleum). As referred to herein, a hybrid vehicle is a vehicle having two or more power sources, for example, a gasoline-powered vehicle and an electric vehicle.

[0045] The terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the present disclosure. As used herein, the singular forms "a," "an" and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise. It will be further understood that the terms "comprises" and / or "comprising," when used in this specification, specify the presence of stated features, integers, steps, operations, elements, and / or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and / or groups thereof. As used herein, the term "and / or" includes any and all combinations of one or more of the associated listed items. Throughout this specification, the word "comprise," and variations of the word, such as "comprising" and "comprises," mean "including but not limited to," and the word "comprise" as used herein is used in the same way. In addition, the terms "unit," "-er," "-meter," and "module" described in the specification mean units for processing at least one function and operation and can be implemented by hardware components or software components and combinations thereof.

[0046] Further, the control logic of the present disclosure can be embodied as non-transitory computer readable media on a computer readable medium containing executable program instructions executed by a processor, controller, or the like. Examples of computer readable media include, but are not limited to, ROM, RAM, compact discs (CDs)-ROM, tape, floppy disks, flash memories, smart cards, and optical data storage devices. The computer readable medium can also be distributed over network-coupled computer systems so that the computer readable medium is stored and executed in a distributed fashion, e.g., as by a remote information processing server or a controller area network (CAN).

[0047] Hereinafter, some embodiments of the present disclosure will be described in detail with reference to exemplary drawings. Also, when reference numerals are duplicated between the drawings, the same or equivalent components will be designated by the same reference numerals even when they are shown in other drawings. Further, in describing embodiments of the present disclosure, detailed descriptions of well-known features or functions will be omitted in order not to unnecessarily obscure the spirit of the present disclosure.

[0048] In describing components according to embodiments of this disclosure, terms such as first, second, "A", "B", (a), (b), etc., may be used. These terms are intended only to distinguish one component from another, and they do not limit the nature, sequence, or order of the constituent components. Unless otherwise defined, all terms used herein (including technical or scientific terms) have the same meaning as commonly understood by one of ordinary skill in the art to which this disclosure pertains. Terms as defined in commonly used dictionaries should be interpreted as having the meaning equivalent to their meaning in the context of the relevant field and should not be interpreted as having an ideal or overly formal meaning unless explicitly defined as having an ideal or overly formal meaning in this application.

[0049] In the following text, reference will be made to Figures 1 to 11 The embodiments of this disclosure are described in detail.

[0050] Figure 1 This is a diagram illustrating a method for generating traffic information according to embodiments of the present disclosure, and Figure 2 This is a block diagram illustrating the configuration of a system for generating traffic information according to an embodiment of the present disclosure. Figure 3 This is a diagram used to describe the sensor equipment used in relay vehicles.

[0051] refer to Figures 1 to 3 The following describes a system for generating traffic information according to embodiments of the present disclosure, and a method for generating traffic information using the system.

[0052] A system for generating traffic information according to embodiments of the present disclosure may include a relay vehicle VEH_r and a server 100.

[0053] The relay vehicle VEH_r can detect surrounding vehicles VEH_s and provide information about the detected surrounding vehicles VEH_s to the server 100. For this purpose, the relay vehicle VEH_r may include sensor device 10, GPS receiver 20, communication module 30, and navigation device 40.

[0054] The sensor device 10 may include a camera 11 for detecting external objects outside the relay vehicle VEH_r, and a proximity warning sensor 12.

[0055] like Figure 3 As shown, camera 11 can be positioned in front of the vehicle to obtain external images of the vehicle, or it can be positioned behind the vehicle, in the right-side mirror, left-side mirror, etc. The camera can be a single-channel camera, a stereo camera, an surround-view monitoring (AVM) camera, or a 360-degree camera.

[0056] The relay vehicle VEH_r can perform artificial intelligence learning to detect surrounding vehicles VEH_s from images obtained by the camera 11. To this end, the relay vehicle VEH_r can include an artificial intelligence (AI) processor. The AI processor can learn a neural network using a pre-stored program. The neural network for detecting target vehicles and dangerous vehicles can be designed to simulate a structure of a human brain on a computer, and can include a plurality of network nodes having weights of neurons simulating neurons exchanging signals via synapses. The plurality of network nodes can exchange data according to a connection relationship to make the neurons simulate synaptic activity of neurons exchanging signals via synapses. The neural network can include a deep learning model developed from a neural network model. In the deep learning model, the plurality of network nodes can be located in different layers to exchange data according to a convolutional connection relationship. Examples of the neural network model can include various deep learning techniques such as a deep neural network (DNN), a convolutional deep neural network (CNN), a recurrent neural network (RNN), a restricted Boltzmann machine (RBM), a deep belief network (DBN), and a deep Q-network.

[0057] The proximity warning sensor 12 can detect an object approaching the relay vehicle VEH_r using a camera or radar, and generate an alert when the object is within a certain distance from the vehicle. The proximity warning sensor 12 can be a blind spot detection (BSD) device for detecting the rear side of the relay vehicle VEH_r.

[0058] In addition, the sensor device 10 can further include a light imaging detection and ranging (LIDAR) 13 and a radio detection and ranging (RADAR) 14.

[0059] The LIDAR 13 can include a laser transmission module and a laser reception module. The LIDAR can be implemented in a TOF (Time of Flight) method or a phase shift method. The LIDAR can be exposed to the outside of the vehicle to detect an object located in front, behind, or at the side of the vehicle.

[0060] The RADAR 14 can include an electromagnetic wave transmission module and an electromagnetic wave reception module, and can detect a position of an object as well as a distance and a relative speed from the detected object. The RADAR can be implemented in a pulse radar method or a continuous wave radar method based on the principle of radio waves. In the continuous wave radar method, the RADAR can be implemented in an FMCW (Frequency Modulated Continuous Wave) method or an FSK (Frequency Shift Keying) method according to a signal waveform.

[0061] Further, the sensor device 10 can include an ultrasonic sensor, an infrared sensor, etc. The ultrasonic sensor can detect an object based on ultrasonic waves, and can detect a position of the detected object, a distance from the detected object, and a relative speed with respect to the detected object. The ultrasonic sensor can be placed at an appropriate position outside the vehicle to detect an object located in front of, behind, or at the side of the vehicle. The infrared sensor can detect an object using infrared light, and can detect a position of the detected object, a distance from the detected object, and a relative speed with respect to the detected object.

[0062] The GPS receiver 20 is used to obtain position information based on a global positioning system, and can obtain position information of the relay vehicle VEH_r by receiving a signal from a satellite.

[0063] The communication module 30 can transmit and receive radio signals to and from the server 100 over a mobile communication network established according to a technical standard or a communication method for mobile communication. The communication module 30 can perform communication based on global system for mobile communications (GSM), code division multiple access (CDMA), code division multiple access 2000 (CDMA 2000), enhanced voice data optimization or enhanced voice-only data (EV-DO), wideband CDMA (WCDMA), high-speed downlink packet access (HSDPA), high-speed uplink packet access (HSUPA), long term evolution (LTE), or LTE-A (long term evolution-advanced).

[0064] The navigation device 40 can provide route guidance based on the position of the relay vehicle VEH_r determined by the map data and the GPS receiver 20.

[0065] The server 100 can include a traffic information generation apparatus, and the traffic information generation apparatus can include a communication device 110, a processor 120, and a memory 130.

[0066] The communication device 110 can perform communication with the relay vehicle VEH_r to receive position information of the relay vehicle VEH_r and vehicle information of the surrounding vehicles VEH_s.

[0067] The processor 120 can select a traveling vehicle by excluding duplicate vehicles from the surrounding vehicles VEH_s by executing instructions (e.g., regarding an algorithm) stored in the memory 130. The processor 120 can generate traffic information based on the traveling vehicle and transmit the generated traffic information to the service vehicle VEH_se. The traffic information can be used to determine a traffic volume on a road.

[0068] The memory 130 can store instructions for operations of the processor 120. The memory 130 can be implemented using a hard disk drive, a flash memory, an electrically erasable programmable read only memory (EEPROM), a static RAM (SRAM), a ferroelectric RAM (FRAM), a phase change RAM (PRAM), a magnetic RAM (MRAM), a dynamic random access memory (DRAM), a synchronous dynamic random access memory (SDRAM), a double data rate-SDRAM (DDR-SDRAM), etc.

[0069] The service vehicle VEH_se can perform route guidance using traffic information provided through the communication module 51 and map data stored in the navigation device 52.

[0070] Hereinafter, a method for generating traffic information in a server according to an embodiment of the disclosure will be described with reference to the accompanying drawings. Figure 4 A method for generating traffic information in a server according to an embodiment of the disclosure will be described.

[0071] Figure 4 is a flowchart for describing a method for generating traffic information according to an embodiment of the disclosure. It will be mainly described with reference to Figure 4 The processing performed by the server shown in Figure 2 will be described.

[0072] In S410, the server 100 can receive position information of the relay vehicle VEH_r and vehicle information of the surrounding vehicles VEH_s from one or more relay vehicles VEH_r using the communication device 110.

[0073] The position information of the relay vehicle VEH_r can be latitude and longitude information acquired by the GPS receiver 20. The vehicle information of the surrounding vehicles VEH_s can include relative position information of the surrounding vehicles VEH_s with respect to the relay vehicle VEH_r, vehicle color information, vehicle size information, etc.

[0074] In S420, the processor 120 of the server 100 can determine a traveling vehicle by excluding duplicate vehicles among the surrounding vehicles VEH_s based on the position information of the relay vehicle VEH_r and the vehicle information of the surrounding vehicles.

[0075] To determine the duplicate vehicle, the processor 120 can determine an absolute position of the surrounding vehicle VEH_s. The processor 120 can determine the absolute position of the surrounding vehicle VEH_s based on the position information of the relay vehicle VEH_r and a relative position of the surrounding vehicle VEH_s with respect to the relay vehicle VEH_r. The relative position of the surrounding vehicle VEH_s can include a distance between the relay vehicle VEH_r and the surrounding vehicle VEH_s, an angle between a straight line connecting the relay vehicle VEH_r and the surrounding vehicle VEH_s and a traveling direction of the relay vehicle VEH_r, and link information of the surrounding vehicle VEH_s.

[0076] When the surrounding vehicle VEH_s is duplicated, the processor 120 can determine that only one vehicle among the duplicated surrounding vehicles VEH_s is the traveling vehicle. The duplicated surrounding vehicles VEH_s can be the same surrounding vehicle VEH_s detected by different relay vehicles VEH_r.

[0077] The processor 120 can determine the duplicate vehicle using color information and size information of the surrounding vehicle VEH_s.

[0078] In addition, the processor 120 can determine the duplicate vehicle based on license plate information of the surrounding vehicle VEH_s. The license plate information can be included in the vehicle information of the surrounding vehicle VEH_s provided by the relay vehicle VEH_r. The relay vehicle VEH_r can detect a license plate from an image acquired through the camera 11 and identify a vehicle number. The relay vehicle VEH_r can encrypt the vehicle number and provide the encrypted vehicle number to the server 100. The server 100 can decrypt the encrypted vehicle number.

[0079] In S430, the processor 120 of the server 100 can generate traffic information based on the travel information of the traveling vehicle.

[0080] The server 100 can generate the traffic information by matching the position and speed of the traveling vehicle with a link. The link can be generated by connecting nodes corresponding to points where a speed change occurs, and can include a plurality of lanes.

[0081] A detailed example of a process for generating traffic information will be described below.

[0082] Figure 5 is a diagram for describing a method of matching a surrounding vehicle with a link.

[0083] Reference Figure 5 The relay vehicle VEH_r traveling on the road can detect the surrounding vehicle VEH_s1, the surrounding vehicle VEH_s2, and the surrounding vehicle VEH_s3 around the relay vehicle VEH_r using the camera 11.

[0084] The relay vehicle VEH_r can provide vehicle information about the first surrounding vehicle VEH_s1, the second surrounding vehicle VEH_s2, and the third surrounding vehicle VEH_s3 together with the position information of the relay vehicle VEH_r to the server 100.

[0085] The vehicle information can include relative position information. The relative position information can include a distance from the relay vehicle VEH_r, lane information, and an angle at which the surrounding vehicle is positioned with respect to a traveling direction of the relay vehicle VEH_r.

[0086] For example, the relative position information of the first surrounding vehicle VEH_s1 can include a relative distance = 10 m, angle information = deg1, and lane information = 1 (first lane). The relative position information of the second surrounding vehicle VEH_s2 can include a relative distance = 20 m, angle information = deg2, and lane information = 2 (second lane), and the relative position information of the third surrounding vehicle VEH_s3 can include a relative distance = 5 m, angle information = deg3, and lane information = 3 (third lane).

[0087] The server 100 can match the position of the relay vehicle VEH_r with a point "r" P_r of the link based on the position information of the relay vehicle VEH_r. In addition, the server 100 can match the second surrounding vehicle VEH_s2 with a first point P1 of the link based on the position information of the relay vehicle VEH_r and the relative position information of the second surrounding vehicle VEH_s2. Similarly, the server 100 can match the first surrounding vehicle VEH_s1 with a second point P2 of the link based on the position information of the relay vehicle VEH_r and the relative position information of the first surrounding vehicle VEH_s1, and can match the third surrounding vehicle VEH_s3 with a third point P3 of the link based on the position information of the relay vehicle VEH_r and the relative position information of the third surrounding vehicle VEH_s3.

[0088] The position information of the point "r" P_r and the first to third points P1, P2, and P3 can include distance information from a node Nd. The node Nd can refer to a point at which a change in a traveling speed of a vehicle on a road can occur, for example, an intersection, an intersection start / end point, an overpass start / end point, a road start / end point, etc.

[0089] Figure 6 is a flowchart for describing a method for generating traffic information according to another embodiment of the disclosure. Figure 7 is a diagram for describing an embodiment of determining a duplicate vehicle.

[0090] Reference Figure 6 and Figure 7A method for generating traffic information according to another embodiment of the present disclosure will be described below.

[0091] In S601, the first relay vehicle VEH_r1 can obtain an image of the surrounding environment via the camera 11.

[0092] The first relay vehicle VEH_r1 can detect the first surrounding vehicle VEH_s1 and the second surrounding vehicle VEH_s2 from the image, and determine vehicle information of the first surrounding vehicle VEH_s1 and the second surrounding vehicle VEH_s2 based on the image. The vehicle information of the first surrounding vehicle VEH_s1 can include a relative position of the first surrounding vehicle VEH_s1 with respect to the first relay vehicle VEH_r1, and color information, size information, and license plate information of the first surrounding vehicle VEH_s1. The vehicle information of the second surrounding vehicle VEH_s2 can include a relative position of the second surrounding vehicle VEH_s2 with respect to the first relay vehicle VEH_r1, and color information, size information, and license plate information of the second surrounding vehicle VEH_s2.

[0093] In S602, the first relay vehicle VEH_r1 can provide the vehicle information of the first surrounding vehicle VEH_s1 and the vehicle information of the second surrounding vehicle VEH_s2 together with position information of the first relay vehicle VEH_r1 to the server 100.

[0094] In S603, the second relay vehicle VEH_r2 can obtain an image of the surrounding environment via the camera 11.

[0095] The second relay vehicle VEH_r2 can detect the first surrounding vehicle VEH_s1, the second surrounding vehicle VEH_s2, and the third surrounding vehicle VEH_s3 from the image, and determine vehicle information of the first surrounding vehicle VEH_s1, the second surrounding vehicle VEH_s2, and the third surrounding vehicle VEH_s3 based on the image. The vehicle information of the third surrounding vehicle VEH_s3 can include a relative position of the third surrounding vehicle VEH_s3 with respect to the second relay vehicle VEH_r2, and color information, size information, and license plate information of the third surrounding vehicle VEH_s3.

[0096] In S604, the second relay vehicle VEH_r2 can provide the vehicle information of the first surrounding vehicle VEH_s1, the vehicle information of the second surrounding vehicle VEH_s2, and the vehicle information of the third surrounding vehicle VEH_s3 together with position information of the second relay vehicle VEH_r2 to the server 100.

[0097] In S605, the server 100 can determine a duplicate vehicle among the surrounding vehicles, and determine one of the duplicate vehicles as a traveling vehicle.

[0098] According to an embodiment, the server 100 can match the surrounding vehicles VEH_s1, VEH_s2, and VEH_s3 with the link and determine the repeating vehicle based on the positions of the surrounding vehicles VEH_s1, VEH_s2, and VEH_s3 matched with the link.

[0099] For example, the server 100 can match the position of the first relay vehicle VEH_r1 with the point r1 P_r1 of the link based on the position information of the first relay vehicle VEH_r1. Also, the server 100 can match the second surrounding vehicle VEH_s2 with the (1-1)th point P1-1 of the link based on the position information of the first relay vehicle VEH_r1 and the relative position information of the second surrounding vehicle VEH_s2. Similarly, the server 100 can match the first surrounding vehicle VEH_s1 with the (1-2)th point P1-2 of the link based on the position information of the first relay vehicle VEH_r1 and the relative position information of the first surrounding vehicle VEH_s1.

[0100] The server 100 can match the position of the second relay vehicle VEH_r2 with the point r2 P_r2 of the link based on the position information of the second relay vehicle VEH_r2. Also, the server 100 can match the second surrounding vehicle VEH_s2 with the (2-1)th point P2-1 of the link based on the position information of the second relay vehicle VEH_r2 and the relative position information of the second surrounding vehicle VEH_s2. Similarly, the server 100 can match the first surrounding vehicle VEH_s1 with the (2-2)th point P2-2 of the link based on the position information of the second relay vehicle VEH_r2 and the relative position information of the first surrounding vehicle VEH_s1, and can match the third surrounding vehicle VEH_s3 with the (2-3)th point P2-3 of the link based on the position information of the second relay vehicle VEH_r2 and the relative position information of the third surrounding vehicle VEH_s3.

[0101] The position information of the (1-1)th point P1-1 and the (1-2)th point P1-2 can include distance information from the node Nd.

[0102] The (2-1)th point P2-1, the (2-2)th point P2-2, and the (2-3)th point P2-3 can include distance information from the node Nd.

[0103] The server 100 can determine whether the position information of the surrounding vehicles generated using the vehicle information provided by the first relay vehicle VEH_r1 and the position information of the surrounding vehicles generated using the vehicle information provided by the second relay vehicle VEH_r2 are identical to each other. For example, when the first (1-1) point P1-1 and the second (2-1) point P2-1 include identical distance information, the server 100 can determine that the second surrounding vehicle VEH_s2 is repeatedly detected by the first relay vehicle VEH_r1 and the second relay vehicle VEH_r2.

[0104] According to another embodiment, S605 can be performed based on the positions of the surrounding vehicles designated in the lane.

[0105] To this end, the server 100 can determine the absolute position of the vehicle based on the position information of the first relay vehicle VEH_r1 and the vehicle information of the surrounding vehicles VEH_s1 and VEH_s2 provided by the first relay vehicle VEH_r1. The following [Table 1] is a table showing an example of the position information of the first relay vehicle VEH_r1 and the vehicle information of the surrounding vehicles VEH_s1 and VEH_s2 provided by the first relay vehicle VEH_r1.

[0106] [Table 1]

[0107]

[0108] In addition, the server 100 can determine the absolute position of the vehicle based on the position information of the second relay vehicle VEH_r2 and the vehicle information of the surrounding vehicles VEH_s1, VEH_s2, and VEH_s3 provided by the second relay vehicle VEH_r2. The following [Table 2] is a table showing an example of the position information of the second relay vehicle VEH_r2 and the vehicle information of the surrounding vehicles VEH_s1, VEH_s2, and VEH_s3 provided by the second relay vehicle VEH_r2.

[0109] [Table 2]

[0110]

[0111] In [Table 1] and [Table 2], the link ID can be a unique link of a road on which the relay vehicle VEH_r1 and the relay vehicle VEH_r2 travel. The vehicle number can be a unique number encrypted and transmitted to the server 100. The line information can be expressed together with information (-, +) indicating the direction of the line with respect to the relay vehicle VEH_r1 and the relay vehicle VEH_r2. The azimuth angle can be expressed in degrees together with information (-, +) indicating the direction of the detected vehicle with respect to the traveling direction of the relay vehicle VEH_r1 and the relay vehicle VEH_r2.

[0112] The server 100 can determine the position of the first surrounding vehicle VEH_s1 on the road including the plurality of lanes based on the distance between the first relay vehicle VEH_r1 and the first surrounding vehicle VEH_s1, the azimuth angle of the first surrounding vehicle VEH_s1, and the link information of the first surrounding vehicle VEH_s1. In addition, the server 100 can specifically determine the second relay vehicle VEH_r2 and the position of the second relay vehicle VEH_r2 on the road.

[0113] Similarly, the server 100 can specifically determine the positions of the first surrounding vehicle VEH_s1, the second surrounding vehicle VEH_s2, and the third surrounding vehicle VEH_s3 on the road.

[0114] The server 100 can determine a duplicate vehicle by determining whether the positions of the surrounding vehicles determined based on the vehicle information provided by the first relay vehicle VEH_r1 and the positions of the surrounding vehicles determined based on the vehicle information provided by the second relay vehicle VEH_r2 are the same.

[0115] In the process of determining the duplicate vehicle, the server 100 can additionally use the color information and the size information of the surrounding vehicles.

[0116] In S606, the server 100 can determine one of the duplicate vehicles as a traveling vehicle.

[0117] For example, when the surrounding vehicle matched with the first (1-1) point P1-1 and the surrounding vehicle matched with the second (2-1) point P2-1 are the same vehicle, the server 100 can determine that the first surrounding vehicle matched with the first (1-1) point P1-1 is the traveling vehicle. In addition, the server 100 can ignore the vehicle information of the first surrounding vehicle VEH_s1 provided by the second relay vehicle VEH_r2.

[0118] In S607, the server 100 can generate traffic information related to the traveling vehicle.

[0119] The traffic information can include position information of the traveling vehicle matched with the link and speed information of the traveling vehicle. The position information of the traveling vehicle can include distance information from the node.

[0120] Figure 8 is a diagram for describing a method of determining a duplicate vehicle according to another embodiment. Referring to Figure 8 , a method of determining a duplicate vehicle according to another embodiment of the disclosure will be described below in detail.

[0121] In S801, the relay vehicle VEH_r can recognize a license plate of a vehicle based on an image.

[0122] In S802, the relay vehicle VEH_r can recognize the vehicle number from the license plate of the vehicle and encrypt the vehicle number.

[0123] In S803, the relay vehicle VEH_r can transmit the encrypted vehicle number to the server 100.

[0124] In S804, the server 100 can decrypt the encrypted vehicle number to obtain the vehicle number. Then, the server 100 can determine whether the vehicle number is a duplicate of the vehicle number provided by another relay vehicle.

[0125] In S805, the server 100 can transmit a message indicating that the vehicle number is duplicated to the relay vehicle VEH_r when the vehicle number provided by the relay vehicle VEH_r is the same as the vehicle number provided by another relay vehicle.

[0126] In S806, the relay vehicle VEH_r can provide vehicle information of surrounding vehicles other than the duplicate vehicle to the server 100 without transmitting the vehicle information of the duplicate surrounding vehicle to the server 100.

[0127] In Figure 8 , S805 can be performed even when a duplicate vehicle is determined based on another embodiment. For example, even when the server 100 determines a duplicate vehicle based on the location information of the surrounding vehicles, the server 100 can provide information about the duplicate vehicle to the relay vehicle.

[0128] Figure 9 and Figure 10 are diagrams for describing a method for determining speed information of a traveling vehicle according to an embodiment of the disclosure. Figure 9 and Figure 10 are diagrams for determining speed information of a surrounding vehicle determined as a traveling vehicle by removing a duplicate vehicle from the surrounding vehicles.

[0129] Figure 9 is a diagram for describing a method for determining a speed of a traveling vehicle based on an image.

[0130] Referring to Figure 9 , the relay vehicle VEH_r can determine a distance d1 from the traveling vehicle VEH_d based on an image acquired at a first time t1.

[0131] Then, the relay vehicle VEH_r can determine a distance d2 from the traveling vehicle VEH_d based on an image acquired at a second time t2.

[0132] The relay vehicle VEH_r can determine Δt corresponding to a time interval between the first time t1 and the second time t2, and determine Δd corresponding to a distance difference between d2 and d1. Then, the relay vehicle VEH_r can determine a relative speed of the running vehicle VEH_d based on Δt and Δd.

[0133] The relay vehicle VEH_r can determine a speed of the running vehicle VEH_d based on a speed of the relay vehicle VEH_r and the relative speed of the running vehicle VEH_d.

[0134] Figure 10 is a diagram for describing a method for determining a speed of a running vehicle using a proximity warning sensor.

[0135] Reference Figure 10 When the running vehicle VEH_d is detected by the proximity warning sensor 12, the relay vehicle VEH_r can identify a time t1 at which an alarm starts.

[0136] When the running vehicle VEH_d deviates from a detection distance d3 of the proximity warning sensor 12, the relay vehicle VEH_r can identify a time t2 at which the alarm ends.

[0137] The detection distance d3 of the proximity warning sensor 12 can be a pre-designed value.

[0138] The relay vehicle VEH_r can determine a relative speed of the running vehicle VEH_d based on a time interval between the first time t1 and the second time t2 at which the alarm is transmitted and the detection distance d3.

[0139] The relay vehicle VEH_r can determine a speed of the running vehicle VEH_d based on a speed of the relay vehicle VEH_r and the relative speed of the running vehicle VEH_d.

[0140] Figure 9 and 10 The embodiment illustrated in the middle can be performed by a server. The relay vehicle VEH_r can provide the server 100 with speed information of the relay vehicle VEH_r and detection distance information of the proximity warning sensor, and provide the server 100 with image information of the running vehicle VEH_d, detection time information of the proximity warning sensor 12, etc. Then, the server 100 can determine a speed of the running vehicle VEH_d based on the information provided by the relay vehicle VEH_r.

[0141] Figure 11 A computing system according to an embodiment of the disclosure is illustrated.

[0142] Reference Figure 11The computing system 1000 can include at least one processor 1100, a memory 1300, a user interface input device 1400, a user interface output device 1500, a storage 1600, and a network interface 1700 connected to each other via a bus 1200.

[0143] The processor 1100 can be a central processing unit (CPU) or a semiconductor device that processes instructions stored in the memory 1300 and / or the storage 1600. The memory 1300 and the storage 1600 can include various types of volatile or non-volatile storage media. For example, the memory 1300 can include read-only memory (ROM) 1310 and random access memory (RAM) 1320.

[0144] Accordingly, the operations of the methods described in connection with the embodiments disclosed herein or the instructions (for example, of the algorithm) can be directly embodied in hardware or software modules executed by the processor 1100, or a combination of hardware and software modules. The software modules can reside on a storage medium (that is, the memory 1300 and / or the storage 1600) such as RAM, flash memory, ROM, EPROM, EEPROM, registers, hard disk, a removable disk, and CD-ROM.

[0145] An exemplary storage medium can be coupled to the processor 1100, and the processor 1100 can read information from the storage medium and can record information in the storage medium. Alternatively, the storage medium can be integrated with the processor 1100. The processor and the storage medium can reside in an application-specific integrated circuit (ASIC). The ASIC can reside within a user terminal. In another case, the processor and the storage medium can reside in the user terminal as separate components. The user terminal can further include a communication interface 1700 for establishing communication with another device or server.

[0146] The above description is merely illustrative of the technical concept of the present disclosure, and those skilled in the art to which the present disclosure pertains can make various modifications and changes without departing from the essential characteristics of the present disclosure.

[0147] Therefore, the embodiments disclosed in the present disclosure are not intended to limit the technical concept of the present disclosure, but are for describing the present disclosure, and the scope of the technical concept of the present disclosure is not limited by the embodiments. The scope of protection of the present disclosure should be interpreted by the appended claims, and all technical concepts within the scope equivalent to the appended claims should be interpreted as included in the scope of the present disclosure.

[0148] According to the embodiments of the present disclosure, in addition to the relay vehicle equipped with a GPS device and a communication device, position information and speed information of other vehicles can also be obtained, so that traffic information can be generated based on a larger amount of data.

[0149] Further, according to the embodiment of the present disclosure, by determining the positions and speeds of other vehicles based on images acquired by vehicles traveling on a road, it is possible to obtain position information and speed information of vehicles that are actually traveling on the road.

[0150] Further, various effects directly or indirectly understood by the present disclosure can be provided.

[0151] In the foregoing, while the present disclosure has been described with reference to the example embodiments and the accompanying drawings, the present disclosure is not limited thereto, but various modifications and changes can be made thereto by those skilled in the art to which the present disclosure pertains without departing from the spirit and scope of the present disclosure as claimed in the appended claims.

Claims

1. An apparatus for generating traffic information, comprising: The memory is configured to store instructions for generating the traffic information used to determine the traffic volume on the road; A processor is configured to execute the instructions, wherein, when executing the instructions, the processor is configured to: The vehicle being traveled is determined by excluding duplicate vehicles from the surrounding vehicles based on the location information of the relay vehicle traveling on the road and the vehicle information of surrounding vehicles; the surrounding vehicles are detected by the relay vehicle. The traffic information is generated based on the driving information of the vehicles.

2. The apparatus for generating traffic information according to claim 1, wherein, The processor is configured to: Identify license plate information from the vehicle information of the surrounding vehicles; and The vehicle with the same license plate information among the surrounding vehicles is identified as the driving vehicle.

3. The apparatus for generating traffic information according to claim 2, wherein, The processor is configured to decrypt the license information provided as encrypted data.

4. The apparatus for generating traffic information according to claim 1, wherein, The processor is configured to: The relative positions of the surrounding vehicles with respect to the relay vehicle are identified from the vehicle information of the surrounding vehicles. Based on the location information of the relay vehicle and the relative positions of the surrounding vehicles, the absolute positions of the surrounding vehicles are determined; and Among the surrounding vehicles with the same absolute position, one of the surrounding vehicles is identified as the driving vehicle.

5. The apparatus for generating traffic information according to claim 4, wherein, The processor is configured to determine the absolute position of the surrounding vehicles based on the route information of the surrounding vehicles.

6. The apparatus for generating traffic information according to claim 4, wherein, The processor is configured to determine the duplicate vehicle among the surrounding vehicles based on the color information or size information of the vehicle information of the surrounding vehicles.

7. The apparatus for generating traffic information according to claim 4, wherein, The processor is configured to: Based on the speed information of the relay vehicle and the change in the relative position of the traveling vehicle over time, the speed of the traveling vehicle is determined; and The speed information of the vehicles is included in the traffic information.

8. The apparatus for generating traffic information according to claim 7, wherein, The processor is configured to: Determine the relative position of the vehicle during a predetermined time period; The relative speed of the vehicle is determined based on the change in its relative position over the predetermined time period; and The speed of the traveling vehicle is determined based on the speed information of the relay vehicle and the relative speed of the traveling vehicle.

9. The apparatus for generating traffic information according to claim 7, wherein, The processor is configured to: Determine the detection time of the traveling vehicle detected by the side and rear detection sensors of the relay vehicle; The relative speed of the vehicle is determined based on the detection distance and detection time of the rear-side detection sensor. and The speed of the traveling vehicle is determined based on the speed information of the relay vehicle and the relative speed of the traveling vehicle.

10. A server comprising the means for generating traffic information according to claim 1, the server being operatively connected to at least one vehicle.

11. A method for generating traffic information, comprising: The server receives the location information of the relay vehicle on the road, as well as the vehicle information of surrounding vehicles detected by the relay vehicle. The server determines the driving vehicle by excluding duplicate vehicles from the surrounding vehicles based on the location information of the relay vehicle and the vehicle information of the surrounding vehicles. and The server generates traffic information to determine the traffic volume on the road based on the driving information of the vehicles.

12. The method for generating traffic information according to claim 11, wherein, The vehicle being driven includes: Identify license plate information from the vehicle information of the surrounding vehicles; and The vehicle with the same license plate information among the surrounding vehicles is identified as the driving vehicle.

13. The method for generating traffic information according to claim 12, wherein, Identifying the license plate information from the vehicle information includes: Receive the license plate information identified by the relay vehicle, wherein the license plate information is encrypted data; and Decrypt the encrypted data.

14. The method for generating traffic information according to claim 11, wherein, The vehicle being driven includes: Identify the relative positions of the surrounding vehicles with respect to the relay vehicle from the vehicle information of the surrounding vehicles; Based on the location information of the relay vehicle and the relative positions of the surrounding vehicles, the absolute positions of the surrounding vehicles are determined; and Among the surrounding vehicles with the same absolute position, one of the surrounding vehicles is identified as the driving vehicle.

15. The method for generating traffic information according to claim 14, wherein, Identifying the relative positions of the surrounding vehicles includes identifying the route information of the surrounding vehicles.

16. The method for generating traffic information according to claim 14, wherein, Determining the driving vehicle also includes using the color information or size information of the vehicle information of the surrounding vehicles.

17. The method for generating traffic information according to claim 14, wherein, Generating the traffic information based on the driving information of the vehicle further includes: determining the speed of the vehicle based on the speed information of the relay vehicle and the change in the relative position of the vehicle over time.

18. The method for generating traffic information according to claim 17, wherein, Determining the speed of the vehicle includes: Determine the relative position of the vehicle during a predetermined time period; The relative speed of the vehicle is determined based on the change in its relative position over the predetermined time period; and The speed of the traveling vehicle is determined based on the speed information of the relay vehicle and the relative speed of the traveling vehicle.

19. The method for generating traffic information according to claim 17, wherein, Determining the speed of the vehicle includes: Determine the detection time of the traveling vehicle detected by the side and rear detection sensors of the relay vehicle; Based on the detection distance and detection time of the rear-side detection sensor, the relative speed of the vehicle is determined; and The speed of the traveling vehicle is determined based on the speed information of the relay vehicle and the relative speed of the traveling vehicle.

20. The method for generating traffic information according to claim 11, wherein, Generating the traffic information includes matching the position and speed of the moving vehicle with links, the links connecting nodes corresponding to points where speed changes occur.

Images