System and method for generating traffic information

Abstract

A system and method for generating traffic information are provided. The system includes a vehicle that acquires its position and surrounding images in real time, and a server that receives the vehicle's position and surrounding images and calculates the time required to pass a specified road section and the average speed of the vehicle passing the specified road section based on the vehicle's position and surrounding images.

Description

[0001] Cross-reference to related applications

[0002] This application claims the benefit of and priority to Korean Patent Application No. 10-2020-0096960, filed on August 3, 2020, which is hereby incorporated by reference herein in its entirety. Technical Field

[0003] The present disclosure relates to a system and method for generating traffic information. Background Art

[0004] Recently, a technology has been developed to provide real-time traffic information for user convenience. For example, this can be generated using a probe vehicle that provides connected car services. When the probe vehicle passes through an intersection, it can provide traffic information by using traffic light information and the time required to pass the intersection.

[0005] However, in the above scheme, traffic information is provided after the probe vehicle has completely passed through the intersection. Passing an intersection takes a considerable amount of time, especially in congested conditions. Therefore, traffic information generated after the probe vehicle has passed through the intersection becomes outdated. For example, if a vehicle enters a 1-kilometer section of road at 8:00 and moves forward at 8:20, traffic information cannot be provided to the vehicle that entered at 8:00. Traffic information is limited to vehicles that entered after 8:20. Summary of the Invention

[0006] One aspect of the present disclosure provides a system and method for generating traffic information, which can provide traffic information based on position information and image information of a vehicle acquired in real time.

[0007] The technical problems to be solved by the present inventive concept are not limited to the aforementioned problems, and any other technical problems not mentioned herein will be clearly understood by those skilled in the art to which the present invention pertains from the following description.

[0008] According to one aspect of the present disclosure, a system for generating traffic information includes: a vehicle, which obtains a position and surrounding images in real time; and a server, which receives the position and surrounding images from the vehicle and calculates the time required to pass through a specified road section and the average speed through the specified road section based on the position and surrounding images from the vehicle.

[0009] The server may determine the location where the vehicle is stopped based on the position of the vehicle, and set a section of the road where a traffic light is installed as a designated section.

[0010] The server may calculate the required time based on the lighting cycle of the traffic light, the moving distance during the lighting cycle, and the waiting time for the green light to be lit at the location of the vehicle.

[0011] The server may calculate and store an average moving distance of a group of the plurality of sample vehicles as the moving distance during the lighting period.

[0012] The server may calculate an average speed for traveling through a specified road segment based on the distance and time required for the specified road segment.

[0013] The server may determine whether a heavy vehicle is detected in front of the vehicle based on a surrounding image of the vehicle, and correct the distance of the designated road section by using the number of heavy vehicles and a correction coefficient for the heavy vehicles when the server determines that a heavy vehicle is detected.

[0014] The server may detect the number of heavy vehicles in a designated road section based on the first surrounding image of the vehicle or the second surrounding image of vehicles traveling around the vehicle.

[0015] The server may generate traffic information based on required time and average speed, and transmit the traffic information to the vehicle.

[0016] According to another aspect of the present disclosure, a method for generating traffic information includes: obtaining a position and surrounding images in real time through a vehicle, and receiving the position and surrounding images from the vehicle through a server, and calculating the time required to pass through a specified road section and the average speed through the specified road section based on the position and surrounding images from the vehicle.

[0017] The method may further include determining, by the server, a location where the vehicle is stopped based on the location of the vehicle, and setting a section of a road equipped with a traffic light as a designated section.

[0018] The method may further include calculating, by the server, a required time based on a lighting cycle of the traffic light, a moving distance during the lighting cycle, and a waiting time for lighting a green light at the location of the vehicle.

[0019] The method may further include calculating and storing, by the server, an average moving distance of a group of the plurality of sample vehicles as the moving distance during the lighting period.

[0020] The method may further include calculating, by the server, an average speed of passing the designated road section based on the distance and time required for the designated road section.

[0021] The method may also include determining, by the server, whether a heavy vehicle is detected in front of the vehicle based on a surrounding image of the vehicle, and when the server determines that a heavy vehicle is detected, correcting the distance of the designated road section by using the number of heavy vehicles and a correction coefficient for the heavy vehicles.

[0022] The method may further include detecting, by the server, the number of heavy vehicles in the designated road section based on the first surrounding image of the vehicle or the second surrounding image of vehicles traveling around the vehicle.

[0023] The method may further include generating, by the server, traffic information based on the required time and the average speed, and transmitting the traffic information to the vehicle. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] Further areas of applicability will become apparent from the description provided herein.It should be understood that the description and specific examples are intended for purposes of illustration only and are not intended to limit the scope of the present disclosure.

[0025] Figure 1 is a diagram showing a configuration of a system for generating traffic information in one form of the present disclosure;

[0026] Figure 2 is a view showing the configuration of a vehicle in one form of the present disclosure;

[0027] Figure 3 is a diagram showing the configuration of a server of one form of the present disclosure;

[0028] Figure 4 is a diagram schematically illustrating a moving distance per traffic signal cycle according to one form of the present disclosure;

[0029] Figure 5 is a diagram schematically illustrating a method for generating traffic information according to one embodiment of the present disclosure;

[0030] Figure 6 is a diagram schematically illustrating a method of generating traffic information by reflecting a heavy vehicle in front of a vehicle according to one form of the present disclosure;

[0031] Figure 7 is a diagram schematically illustrating a configuration for generating traffic information in a plurality of road sections according to one form of the present disclosure;

[0032] Figure 8 is a view illustrating a method of generating traffic information according to one form of the present disclosure. DETAILED DESCRIPTION

[0033] Hereinafter, some embodiments of the present disclosure will be described in detail with reference to the exemplary drawings. When reference numerals are added to the components of each drawing, it should be noted that even when the same or equivalent components are shown on other drawings, they are designated by the same numerals. In addition, when describing the embodiments of the present disclosure, detailed descriptions of well-known features or functions will be excluded in order not to unnecessarily obscure the gist of the present disclosure.

[0034] When describing components according to embodiments of the present 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 the terms do not limit the nature, order, or sequence of the components. Unless otherwise defined, all terms used herein, including technical or scientific terms, have the same meaning as commonly understood by those skilled in the art to which this disclosure relates. Terms such as those defined in commonly used dictionaries should be interpreted as having a meaning equivalent to their contextual meaning in the relevant art, and should not be interpreted as having an ideal or overly formal meaning unless clearly defined as having such a meaning in this application.

[0035] Figure 1 is a diagram illustrating a configuration of a system for generating traffic information in some forms of the present disclosure.

[0036] like Figure 1 As shown, a system 100 for generating traffic information in some forms of the present disclosure may include a vehicle 110 and a server 120 .

[0037] The vehicle 110 can obtain the current position and surrounding images in real time and can send the obtained information to the server 120. In addition, the vehicle 110 can receive traffic information generated from the server 120 and output the received traffic information to guide the user. Figure 2 .

[0038] The server 120 may receive the vehicle position and the surrounding image of the vehicle from the vehicle 110, and may calculate the time required to pass through a designated road section and the average speed of passing through the designated road section based on the vehicle position and the surrounding image of the vehicle. In addition, the server 120 may generate traffic information based on the time required to pass through the designated road section and the average speed of passing through the designated road section, and transmit the generated traffic information to the vehicle 110. Figure 3 Describe the details.

[0039] Figure 2 are views showing the configuration of some forms of vehicles of the present disclosure.

[0040] like Figure 2 As shown, a vehicle 110 in some forms of the present disclosure may include a communication device 111 , a sensor 112 , a camera 113 , a navigation device 114 , an output device 115 , and a controller 116 .

[0041] The communication device 111 may transmit information acquired through the sensor 112, the camera 113, and the navigation device 114 to the server 120 in real time. The communication device 111 may communicate with the server 120 using various communication schemes, such as Wi-Fi, WiBro, Global System for Mobile Communications (GSM), Code Division Multiple Access (CDMA), Wideband Code Division Multiple Access (WCDMA), Universal Mobile Telecommunications System (UMTS), Time Division Multiple Access (TDMA), Long Term Evolution (LTE), etc. In addition, the communication device 111 may perform vehicle-to-vehicle (V2V) communication for transmitting and receiving information to and from surrounding vehicles.

[0042] The sensor 112 can detect obstacles around the vehicle. According to one embodiment, the sensor 112 may include an ultrasonic sensor, a radar, a laser radar, etc., and can detect a vehicle traveling in front of the vehicle.

[0043] The camera 113 can capture images of the vehicle's surroundings. According to one embodiment, the camera 113 can capture images of heavy vehicles, including buses, trucks, etc., traveling in front of the vehicle.

[0044] The navigation device 114 may include a global positioning system receiving device to receive the current position of the vehicle and provide map image information of a specific area based on the current position of the vehicle.

[0045] The output device 115 may include a speaker for outputting the traffic information received from the server 120 as voice, and a display for outputting an image.

[0046] The controller 116 may be implemented using various processing devices, such as a microprocessor including a semiconductor chip capable of executing various commands or operations, and controls the operation of the vehicle according to the present disclosure. According to one embodiment, the controller 116 may control information acquired from the sensor 112 and the navigation device 114 to be transmitted to the server 120, and upon receiving traffic information from the server 120, the controller 116 may control the output of the traffic information via the output device 115.

[0047] Figure 3 is a diagram showing the configuration of a server of some forms of the present disclosure.

[0048] like Figure 3 As shown, the server 120 may include a communication device 121 , a memory 122 , and a controller 123 .

[0049] The communication device 121 can receive vehicle information from the vehicle 110 and transmit traffic information generated by the controller 123 to the vehicle 110. According to one embodiment, the communication device 121 can communicate with the vehicle 110 using various communication schemes, such as Wi-Fi, WiBro, Global System for Mobile Communications (GSM), Code Division Multiple Access (CDMA), Wideband Code Division Multiple Access (WCDMA), Universal Mobile Telecommunications System (UMTS), Time Division Multiple Access (TDMA), Long Term Evolution (LTE), etc. According to an embodiment of the present disclosure, the communication device 121 can communicate not only with the vehicle 110 but also with vehicles around the vehicle 110.

[0050] The memory 122 may store data previously calculated by the server 120. In addition, according to an embodiment of the present disclosure, the memory 122 may store at least one algorithm that performs operations or runs various commands for the operation of the server. The memory 122 may include at least one storage medium selected from a flash memory, a hard disk, a memory card, a read-only memory (ROM), a random access memory (RAM), an electrically erasable programmable read-only memory (EEPROM), a programmable read-only memory (PROM), a magnetic memory, a magnetic disk, and an optical disk.

[0051] The controller 123 can be implemented using various processing devices, such as a microprocessor including a semiconductor chip capable of executing various commands or operations, and controls the operation of the server according to the present disclosure. Specifically, the controller 123 can receive the vehicle position and the surrounding image of the vehicle from the vehicle 110, and calculate the time required to pass through a specified road section and the average speed of passing through the specified road section based on the vehicle position and the surrounding image of the vehicle. In this case, the specified road section may refer to the road section from the current position of the vehicle (where the vehicle is parked) to the road equipped with a traffic light.

[0052] The controller 123 can calculate the time required to pass the specified road section based on the lighting cycle of the traffic light set at the end point of the specified road section, the moving distance during the lighting cycle, and the waiting time for the green light to be lit at the vehicle's location. In this case, the lighting cycle can mean the first time after the green light is turned on until the next green light is turned on, or the second time after the red light is turned on until the next red light is turned on. The moving distance during the lighting cycle can mean the distance the vehicle moves for the first or second time. According to one embodiment, the controller 123 can calculate the moving distance during the lighting cycle by using the average moving distance of a group sampled from multiple sample vehicles. For example, the controller 123 can calculate the average moving distance of the group by using the t distribution (Equation 1) in a 95% confidence interval.

[0053] [Equation 1]

[0054]

[0055] T: Statistics based on t distribution

[0056] E(X): the average value of N moving distance samples

[0057] μ: The average value of the moving distance group

[0058] N: the number of movement distance samples

[0059] S: standard deviation of N moving distance samples

[0060] Will refer to Figure 4 Give a detailed description. Figure 4 is a diagram schematically illustrating a moving distance per traffic signal cycle of some forms of the present disclosure.

[0061] like Figure 4 As shown, the controller 123 may obtain stop points A1, A2, A3, A4, and A5 from a plurality of sample vehicles and calculate the travel distance during the lighting cycle using Equation 1. In some forms of the present disclosure, the controller 123 may calculate a travel distance of 110 meters during the lighting cycle.

[0062] Below, we will refer to Figure 5 The operation of the controller 123 is described in detail, wherein the time required to pass through the designated road section is calculated based on the lighting cycle of the traffic light set at the end point of the designated road section, the moving distance during the lighting cycle, and the waiting time for the green light to be lit at the vehicle's location.

[0063] Figure 5 FIG. 1 is a diagram schematically illustrating a scheme for generating traffic information according to some forms of the present disclosure.

[0064] like Figure 5 As shown, the controller 123 can determine that the distance to the designated road section (the road section from the vehicle's current location to the road section where the traffic light is located) is 250 meters, and that the traffic light 200 has a lighting cycle of three minutes. The travel distance during the lighting period can be calculated as 110 meters. If the remaining time from the vehicle's current location to the green light being illuminated is determined to be 30 seconds, the time required to pass the designated road section can be calculated using the following formula 1.

[0065] <Formula 1>

[0066] Time required = 30 seconds + 3 minutes + 3 minutes + 30 meters / average speed

[0067] Furthermore, the controller 123 may calculate an average speed for passing a designated section by dividing the distance of the designated section by the required time.

[0068] At the same time, the controller 123 can determine whether a heavy vehicle is detected in front of the vehicle based on the surrounding image of the vehicle, and when it is determined that a heavy vehicle is detected, the controller 123 can correct the distance of the designated road section by using the correction coefficient of the heavy vehicle. In this case, heavy vehicles generally refer to large vehicles including buses, trucks, etc., which have lower driving performance than passenger cars and have 6 or more tires in contact with the road surface. Because heavy vehicles have a slower driving speed than ordinary vehicles, when a heavy vehicle is included in the distance of the designated road section, the moving distance during the lighting cycle may be reduced, and thus accurate traffic information may not be calculated. Therefore, the controller 123 can compensate for the distance of the designated road section by applying the moving speed of the heavy vehicle to calculate accurate traffic information.

[0069] Below, we will refer to Figure 6 An operation of correcting the distance of a designated road section by the controller 123 is described.

[0070] Figure 6 is a diagram schematically illustrating a method of generating traffic information by reflecting a heavy vehicle in front of a vehicle in some forms of the present disclosure.

[0071] like Figure 6 As shown, the controller 123 can detect the length of the heavy vehicle 300 in front of the vehicle 110 based on the surrounding image of the vehicle 110, and can correct the distance of the designated road section by using Formula 2 corresponding to the length of the heavy vehicle 300, and applying a correction coefficient for the heavy vehicle to this Formula 2. In this case, the correction coefficient for the heavy vehicle can mean a traffic reduction rate, which can be treated as a value of a ratio of reduction compared to ordinary passenger vehicles when calculating the saturated traffic volume at a signalized intersection, and can be calculated based on the length of the heavy vehicle using a method known in the art.

[0072] <Formula 2>

[0073] Correction distance = distance of designated road section (e.g. 110m) / correction factor for heavy vehicles

[0074] According to one embodiment, the controller 123 can detect the number of heavy vehicles 300 within a specified road section based on the surrounding images acquired by the vehicle 110 and the images received from the surrounding vehicles, and can apply the number of heavy vehicles 300 to correct the distance. For example, when the distance that the vehicle 110 can detect is 'a', the controller 123 can detect the number of heavy vehicles 300 in the surrounding images, and can detect the number of heavy vehicles 300 in the surrounding images in 'a' of the vehicles (surrounding vehicles) stopped within the specified road section. In addition, the controller 123 can correct the distance of the specified road section by applying the number of heavy vehicles 300 detected within the specified road section in the above manner. When the controller 123 detects two heavy vehicles 300 within the specified road section, the corrected distance can be calculated by the following formula 3.

[0075] <Formula 3>

[0076] Approximately 120m = distance of designated road section (e.g. 110m) / correction factor for heavy vehicles (0.96) / correction factor for heavy vehicles (0.96)

[0077] That is, when there are no heavy vehicles in the designated road section, the controller 123 may determine that the distance of the designated road section is 110 meters, but when two heavy vehicles are detected, the distance of the designated road section may be corrected by Formula 3 so that the controller 123 determines the distance to be 120 meters. Therefore, when heavy vehicles are detected, the controller 123 may increase the designated road section by the number of heavy vehicles, thereby more accurately calculating the time and speed required to pass through the designated road section.

[0078] The controller 123 may recalculate the time required to pass through the designated road section and the average speed of passing through the designated road section by using the corrected distance as described above.

[0079] As described above, the controller 123 can generate traffic information based on the time required for the vehicle to pass through the designated road section and the average speed of the designated road section, and send the traffic information to the vehicle 110. In addition, the controller 123 can calculate the required time and average speed by expanding and applying the designated road section set according to the embodiment of the present disclosure on a road with multiple consecutive intersections. Figure 7 The operation of calculating the required time and average speed on a road having a plurality of intersections by the controller 123 will be described.

[0080] Figure 7 FIG. 1 is a diagram schematically illustrating a configuration for generating traffic information in a plurality of road sections according to some forms of the present disclosure.

[0081] like Figure 7As shown, when a plurality of intersections provided with the first to fourth traffic lights 210 to 240 are continuous, the controller 123 may calculate a first expected arrival time based on the required time and the average speed of the designated road section leading to the first traffic light 210. In this scheme, the second to fourth expected arrival times at each intersection may be calculated by calculating the required time and the average speed of each designated road section leading to the second to fourth traffic lights 220 to 240.

[0082] Figure 8 is a diagram illustrating a method of generating traffic information according to some forms of the present disclosure.

[0083] like Figure 8 As shown, in step S110 , the vehicle 110 may obtain its position information and image information, and may transmit the vehicle information obtained in step S110 to the server 120 in step S120 .

[0084] In S130, the server 120 may calculate and store the movement distance during the lighting period by using the average movement distance of the group sampled from the plurality of sample vehicles. According to one embodiment, in S130, the vehicle 110 may calculate the average movement distance of the group by using the t distribution (Equation 1) with a 95% confidence interval as the movement distance during the lighting period. As an example, the average movement distance may be calculated using Equation 1.

[0085] At S140, server 120 may calculate the time required for vehicle 110 to pass through the designated road section and the average speed of the vehicle 110 passing through the designated road section. At S140, server 120 may calculate the required time based on the lighting cycle of the traffic light provided at the end point of the designated road section, the travel distance during the lighting cycle, and the waiting time until the green light at the vehicle's location is illuminated. Additionally, server 120 may calculate the average speed of the vehicle passing through the designated road section by dividing the distance of the designated road section by the required time.

[0086] In S150, the server 120 determines whether a heavy vehicle is detected in front of the vehicle 110. In S150, a heavy vehicle may generally refer to a large vehicle including a bus, a truck, etc., which has lower driving performance than a passenger car and has 6 or more tires in contact with the road surface. When it is determined in S150 that a heavy vehicle is detected in front of the vehicle (yes, Y), in S160, the server 120 may correct the distance of the designated road section by using a correction coefficient for the heavy vehicle. In S160, according to an embodiment, the controller 123 may detect the number of heavy vehicles 300 in the designated road section based on the surrounding images of the vehicle 110 and the images obtained from the vehicles around the vehicle 110, and may apply it to correct the distance of the designated road section.

[0087] When it is determined that a heavy vehicle is detected in front of the vehicle 110, in S170, the server 120 may calculate the time required to pass the designated road section based on the distance of the designated road section corrected in S160, and may generate traffic information based on the average speed of passing the designated road section. In addition, when it is determined that no heavy vehicle is detected in front of the vehicle 110, in S170, the server 120 may generate traffic information based on the required time and average speed calculated in S140.

[0088] In S180 , the server 120 may transmit the traffic information generated in S170 to the vehicle 110 , and although not shown, the vehicle 110 may output the traffic information received from the server 120 through an output device.

[0089] The system and method for generating traffic information according to an embodiment of the present disclosure can calculate the travel speed and required time to an intersection based on position information and image information of a vehicle acquired in real time, so that traffic information with improved accuracy can be provided in real time.

[0090] The above description is a simple example of the technical spirit of the present disclosure, and those skilled in the art to which the present disclosure pertains can make various corrections and modifications to the present disclosure without departing from the basic characteristics of the present disclosure.

[0091] Therefore, the embodiments disclosed in the present disclosure do not limit the technical spirit of the present disclosure, but are illustrative, and the scope of the technical spirit of the present disclosure is not limited by the embodiments of the present disclosure. The scope of the present disclosure should be interpreted by the technical solutions, and it will be understood that all technical spirits within the equivalent scope fall within the scope of the present disclosure.

Claims

1. A system for generating traffic information, the system comprising: A vehicle configured to obtain a position of the vehicle and surrounding images in real time; as well as The server is configured as: receiving the position and the surrounding image from the vehicle; and Calculate the time required to pass through a designated road section and the average speed of passing through the designated road section based on the position and the surrounding image, Wherein, the server is further configured to: determining whether a heavy vehicle is detected in front of the vehicle based on the surrounding image; and When it is determined that the heavy vehicle is detected, the distance of the designated road section is corrected by using the number of heavy vehicles and a correction coefficient for the heavy vehicle, The heavy vehicle includes a large vehicle having more than six tires in contact with the road surface, and The distance of the designated road section is corrected to increase according to the number of heavy vehicles detected.

2. The system according to claim 1, wherein: The server is configured to: determining a location where the vehicle is stopped based on the position; and The road section leading to the road where the traffic light is installed is determined to be the designated road section.

3. The system according to claim 2, wherein: The server is configured to: The required time is calculated based on a lighting cycle of the traffic light, a moving distance during the lighting cycle, and a waiting time for a green light to be lit at the location.

4. The system according to claim 3, wherein: The server is configured to: Calculating the average travel distance of multiple sample vehicles; and The average movement distance is stored as the movement distance during the lighting period.

5. The system according to claim 4, wherein: The server is configured to: The average speed for passing the designated road section is calculated based on the distance of the designated road section and the required time.

6. The system according to claim 1, wherein: The server is configured to: The number of heavy vehicles in the designated road section is detected based on a first surrounding image of the vehicle or a second surrounding image of surrounding vehicles traveling around the vehicle.

7. The system according to claim 1, wherein: The server is configured to: generating the traffic information based on the required time and the average speed; and The traffic information is sent to the vehicle.

8. A method for generating traffic information, the method comprising: Acquiring the position of the vehicle and surrounding images in real time through the vehicle; as well as receiving the position and the surrounding image from the vehicle through a server, and calculating the time required to pass through a designated road section and the average speed of passing through the designated road section based on the position and the surrounding image, Wherein, the method further comprises: determining, by the server based on the surrounding image, whether a heavy vehicle is detected in front of the vehicle; and When it is determined that the heavy vehicle is detected, the server corrects the distance of the designated road section by using the number of heavy vehicles and a correction coefficient for the heavy vehicles. The heavy vehicle includes a large vehicle having more than six tires in contact with the road surface, and The distance of the designated road section is corrected to increase according to the number of heavy vehicles detected.

9. The method according to claim 8, wherein The method further comprises: determining, by the server, a location where the vehicle is stopped based on the location; and The road section leading to the road where the traffic light is installed is determined to be the designated road section.

10. The method according to claim 9, wherein: The method further comprises: The required time is calculated by the server based on a lighting cycle of the traffic light, a moving distance during the lighting cycle, and a waiting time for lighting a green light at the location.

11. The method according to claim 10, wherein: The method further comprises: Calculating, by the server, an average moving distance of a plurality of sample vehicles; and The average movement distance is stored as the movement distance during the lighting period.

12. The method according to claim 11, wherein The method further comprises: The average speed of passing the designated road section is calculated by the server based on the distance of the designated road section and the required time.

13. The method according to claim 8, wherein The method further comprises: The number of heavy vehicles in the designated road section is detected by the server based on a first surrounding image of the vehicle or a second surrounding image of surrounding vehicles traveling around the vehicle.

14. The method according to claim 8, wherein The method further comprises: generating, by the server, the traffic information based on the required time and the average speed; and The traffic information is sent to the vehicle.

Images