A vehicle positioning method, device, electronic equipment and storage medium

Abstract

This invention discloses a vehicle positioning method, device, electronic device, and storage medium. The method includes: determining whether a vehicle is a target vehicle that meets the vehicle position update conditions based on its position; if so, determining a vehicle spacing matching the target vehicle and / or at least one vehicle in the target road segment based on an image captured by the target vehicle and / or at least one vehicle in the target road segment of at least one vehicle in the direction of travel; and updating the current position of at least one vehicle in the target road segment based on the current position of the target vehicle and the vehicle spacing matching the target vehicle and / or at least one vehicle in the target road segment. This invention can solve the problem of weak or no satellite positioning signals in tunnels, mountainous areas, and other road sections, without additional equipment costs, and improves the accuracy of vehicle positioning.

Description

Technical Field

[0001] This invention relates to the field of data processing technology, and in particular to a vehicle positioning method, device, electronic device, and storage medium. Background Technology

[0002] Vehicle navigation systems are typically based on satellite positioning technology, such as GPS (Global Positioning System), to determine the vehicle's current location and perform route planning and real-time navigation guidance based on the destination location provided by the user and the vehicle's current location.

[0003] Taking the determination of a vehicle's current location via GPS signals as an example, since GPS signals rely on wireless communication between satellites and ground receivers, in mountainous areas, tunnels, and other environments, rocks and concrete structures can block or weaken GPS signals. Therefore, in mountainous areas, tunnels, and other environments, GPS signals are usually weak or even disappear completely.

[0004] To address the issue of weak or even completely absent GPS signals in mountainous and tunnel areas, existing technologies typically involve installing additional information collection systems in these areas to assist in determining vehicle location. However, this approach increases the budget and maintenance costs. Other existing technologies employ inertial navigation for relative vehicle positioning, assuming the vehicle is traveling at a constant speed before entering mountainous or tunnel areas, and calculating its current location. However, this method has poor accuracy. Summary of the Invention

[0005] This invention provides a vehicle positioning method, device, electronic device, and storage medium to improve the accuracy of vehicle positioning.

[0006] In a first aspect, embodiments of the present invention provide a vehicle positioning method, the method comprising:

[0007] The vehicle position is used to determine whether the vehicle is the target vehicle that meets the vehicle position update conditions. If so, the vehicle spacing that matches the target vehicle and / or at least one vehicle in the target road segment is determined based on the image taken by the target vehicle and / or at least one vehicle in the target road segment of at least one vehicle in the direction of travel.

[0008] The current position of at least one vehicle in the target road segment is updated based on the current position of the target vehicle and the vehicle spacing that matches the target vehicle and / or at least one vehicle in the target road segment.

[0009] Secondly, embodiments of the present invention also provide a vehicle positioning device, the device comprising:

[0010] The vehicle spacing determination module is used to determine whether a vehicle is a target vehicle that meets the vehicle position update conditions based on the vehicle position. If so, it determines the vehicle spacing that matches the target vehicle and / or at least one vehicle in the target road segment based on the image taken by the target vehicle and / or at least one vehicle in the target road segment of at least one vehicle in the direction of travel.

[0011] The vehicle location update module is used to update the current location of at least one vehicle in the target road segment based on the current location of the target vehicle and the vehicle spacing that matches the target vehicle and / or at least one vehicle in the target road segment.

[0012] Thirdly, embodiments of the present invention also provide an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the vehicle positioning method as described in any of the embodiments of the present invention.

[0013] Fourthly, embodiments of the present invention also provide a storage medium for storing computer-executable instructions, which, when executed by a computer processor, are used to perform the vehicle positioning method as described in any of the embodiments of the present invention.

[0014] The technical solution of this invention determines whether a vehicle meets the vehicle position update conditions based on its location. When the vehicle is a target vehicle that meets the update conditions, the system determines the vehicle spacing matching at least one vehicle in the target vehicle and / or the target road segment based on images captured by the target vehicle and / or vehicles in the target road segment of the vehicles traveling in its direction of travel. Then, based on the current position of the target vehicle and the vehicle spacing matching at least one vehicle in the target road segment, the current position of the vehicles in the target road segment is updated. This invention can solve the problem of weak or no satellite positioning signals in tunnels, mountainous areas, and other road sections, without requiring additional equipment costs, and improves the accuracy of vehicle positioning.

[0015] It should be understood that the description in this section is not intended to identify key or essential features of the embodiments of the present invention, nor is it intended to limit the scope of the invention. Other features of the invention will become readily apparent from the following description. Attached Figure Description

[0016] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0017] Figure 1 This is a flowchart of a vehicle positioning method provided in Embodiment 1 of the present invention;

[0018] Figure 2 This is a schematic diagram of the rear area of ​​a vehicle in front, provided in Embodiment 1 of the present invention;

[0019] Figure 3 This is a schematic diagram of vehicles within a target road segment provided in Embodiment 1 of the present invention;

[0020] Figure 4 This is a schematic diagram of each vehicle when the target vehicle has not entered the target road section or has already left the target road section, as provided in Embodiment 1 of the present invention;

[0021] Figure 5 This is a flowchart of a vehicle positioning method provided in Embodiment 2 of the present invention;

[0022] Figure 6 This is a schematic diagram illustrating the principle of determining vehicle spacing based on the rear area of ​​a vehicle, provided in Embodiment 2 of the present invention.

[0023] Figure 7 This is a schematic diagram of the structure of a vehicle positioning device provided in Embodiment 3 of the present invention;

[0024] Figure 8 This is a schematic diagram of the structure of an electronic device provided in Embodiment 4 of the present invention. Detailed Implementation

[0025] To enable those skilled in the art to better understand the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of the present invention.

[0026] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this invention are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of the invention described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion; for example, a process, method, system, product, or device that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or devices. In the embodiments of this application, certain software, components, models, and other existing industry solutions may be mentioned. These should be considered exemplary, intended only to illustrate the feasibility of implementing the technical solutions of this application, and do not imply that the applicant has already used or necessarily used such solutions.

[0027] The acquisition, transmission, storage, use, and processing of data in this application all comply with the relevant provisions of national laws and regulations.

[0028] Example 1

[0029] Figure 1 The flowchart of a vehicle positioning method is provided in Embodiment 1 of the present invention. This embodiment is applicable to the situation of locating vehicles in road sections with weak or no satellite positioning signals. The method can be executed by a vehicle positioning device, which can be implemented in hardware and / or software. The vehicle positioning device can be configured in a server and used in conjunction with the Internet of Vehicles.

[0030] like Figure 1 As shown, the method includes:

[0031] S110. Determine whether the vehicle is a target vehicle that meets the vehicle position update conditions based on the vehicle position. If so, determine the vehicle spacing that matches the target vehicle and / or at least one vehicle in the target road segment based on the image taken by the target vehicle and / or at least one vehicle in the target road segment of at least one vehicle in the direction of travel.

[0032] The vehicle's position can be determined using satellite positioning technology, and the vehicle must be a vehicle traveling on the road with an accurate current location. Meeting the vehicle position update conditions can mean that the vehicle has just entered or exited the target road segment; or it can mean that the vehicle has not entered the target road segment but the distance between it and the starting point of the target road segment is less than or equal to a preset distance threshold. Based on images taken of the vehicle's direction of travel, the distance between the vehicle and other vehicles traveling in the target road segment can be determined. Alternatively, if the vehicle has left the target road segment but the distance between it and the ending point of the target road segment is less than or equal to a preset distance threshold, the distance between the vehicle and the target vehicle can be determined based on images taken of the vehicle's direction of travel. When a vehicle meets the vehicle position update conditions, it is treated as a target vehicle for subsequent processing.

[0033] The target road segment can be a tunnel, a mountainous area, or other road segment with weak or no satellite positioning signal. The system acquires images of at least one vehicle ahead in the target vehicle's direction of travel using its camera, and / or, while the vehicle is traveling on the target road segment, acquires images of vehicles ahead in the vehicle's direction of travel using its camera. The camera can be a dashcam, a vehicle-mounted action camera, a vehicle-mounted panoramic camera, etc., and this embodiment is not limited to these. The camera uploads the real-time video or images captured at preset shooting intervals to a server. The server identifies the vehicles ahead in the images and, based on the identified vehicles, determines the distance between the target vehicle and / or the vehicles in the target road segment and the vehicles ahead.

[0034] Taking the example of multiple vehicles sequentially entering a target road segment, the process of determining vehicle spacing based on images captured by multiple vehicles is explained. When vehicle A enters the target road segment, there are no vehicles ahead of vehicle A in its direction of travel; therefore, the image of vehicle A is not processed at this time. When vehicle B enters the target road segment, vehicle A is ahead of vehicle B in its direction of travel; therefore, the image of vehicle B is processed to identify vehicle A, and the vehicle spacing between vehicle B and vehicle A is determined based on the image of vehicle B. When vehicle C enters the target road segment, vehicle B is ahead of vehicle C in its direction of travel; the image of vehicle C is processed to identify vehicle B, and the vehicle spacing between vehicle C and vehicle B is determined based on the image of vehicle C. This process continues until the distance between the target vehicle and / or the vehicles in the target road segment and the vehicles ahead of them can be obtained.

[0035] It should be noted that in the above example, after vehicle B enters the target road segment and the distance between vehicle B and vehicle A can be determined based on the images captured by vehicle B, the distance between vehicle B and vehicle A can be updated in real time based on the real-time images captured by vehicle B. Similarly, after vehicle C enters the target road segment and the distance between vehicle C and vehicle B can be determined based on the images captured by vehicle C, the distance between vehicle C and vehicle B can be updated in real time based on the real-time images captured by vehicle C. That is, when vehicles A, B, and C are traveling simultaneously in the target road segment, the distances between vehicle C and vehicle B, and between vehicle B and vehicle A, are updated in real time. Furthermore, the processes of determining the distances between vehicle C and vehicle B, and between vehicle B and vehicle A, are performed simultaneously and independently, regardless of the order in which the vehicles enter the target road segment.

[0036] In an optional embodiment, based on images captured by the target vehicle and / or at least one vehicle in the target road segment of at least one vehicle in the direction of travel, a vehicle spacing matching the target vehicle and / or at least one vehicle in the target road segment is determined. This can involve identifying the vehicle in front of the image and locating the license plate area of ​​the vehicle in front. After determining the type of vehicle in front, the standard size of the license plate corresponding to the type of vehicle in front is determined, and the vehicle spacing is determined based on the area of ​​the license plate area in the image and the standard size of the license plate.

[0037] Understandably, for the same type of vehicle, license plates usually have fixed standard dimensions. For example, motorcycle license plates are 220mm × 95mm, small car license plates are 440mm × 140mm, and trailer license plates are 440mm × 220mm, etc. Depending on the distance between the vehicle and the vehicle in front, the size of the license plate area in the image captured by the vehicle's camera will vary; the greater the distance between the two vehicles, the smaller the license plate area in the image.

[0038] In another optional embodiment, the vehicle spacing matching the target vehicle and / or at least one vehicle in the target road segment is determined based on the image captured by the target vehicle and / or at least one vehicle in the target road segment of at least one vehicle in the direction of travel. Alternatively, the image can be used to identify the vehicle in front and locate the rear region of the vehicle in front. Figure 2 A schematic diagram of the rear area of ​​a vehicle in front is provided, such as... Figure 2 As shown, the rear area can be in the form of the smallest bounding rectangle of the rear of the vehicle in front. After determining the type of vehicle in front, the actual size of the rear area corresponding to the type of vehicle in front is determined, and the vehicle spacing is determined based on the area and actual size of the rear area of ​​the vehicle in front in the image.

[0039] Understandably, for vehicles of the same type, the actual size of their rear end area is usually fixed or not significantly different. For example, different types of vehicles, such as sedans, SUVs, and vans, have different rear end area sizes, while vehicles of the same type usually have similar or nearly identical rear end areas. Depending on the distance between the vehicle and the vehicle in front, the size of the rear end area of ​​the vehicle in front will differ in the image captured by the vehicle's camera. The greater the distance between the two vehicles, the smaller the area of ​​the rear end area in the image. To further improve the accuracy of determining the vehicle distance based on the vehicle's rear end area, the actual size of the rear end area of ​​different vehicle models can be distinguished. The vehicle distance between the two vehicles can be determined based on the actual size of the rear end area corresponding to the model of the vehicle in front and the area of ​​the rear end area of ​​the vehicle in front in the image. Vehicle models include, for example, a sedan of a certain brand and series, or an SUV of a certain brand and class; this embodiment does not limit this.

[0040] In this embodiment, based on images taken by the target vehicle and / or at least one vehicle in the target road segment along its direction of travel, the vehicle ahead is identified. Based on the identified vehicle ahead in the image, the vehicle distance between the target vehicle and / or at least one vehicle in the target road segment and the vehicle ahead is determined. After obtaining the vehicle distance between the target vehicle and / or at least one vehicle in the target road segment and the vehicle ahead, the current position of each vehicle can be iteratively calculated using the vehicle distances between the two vehicles after the current position of the target vehicle is determined, thereby achieving vehicle positioning within the target road segment.

[0041] Furthermore, if forward vehicle identification is performed on the image to identify at least two forward vehicles, the vehicle distance between each identified forward vehicle and the current vehicle is determined. If the at least two forward vehicles have a sequential order in their direction of travel, the vehicle distance between each forward vehicle and the current vehicle, as well as the vehicle distance between forward vehicles determined based on the images captured by the forward vehicles, can be considered when determining the vehicle distance between the at least two forward vehicles.

[0042] For example, taking vehicles A, B, and C sequentially entering a target road segment, the distance between vehicles A and B can be determined based on the image captured by vehicle B. If vehicle C is simultaneously traveling within the target road segment with vehicles A and B, and both vehicles A and B can be identified in the image captured by vehicle C, then the distance between vehicles C and B, as well as the distance between vehicle C and vehicle A, can be determined. In this case, the final distance between vehicles A and B can be determined by combining these three determined distances. For instance, if the distance between vehicles A and B is determined to be 45m based on the image captured by vehicle B, and the distance between vehicles C and A is determined to be 100m and the distance between vehicles C and B is determined to be 60m based on the image captured by vehicle C, then the distance between vehicles A and B can be calculated to be 40m based on the two distances determined from the image captured by vehicle C. The final vehicle distance between vehicles A and B can be calculated by averaging the distance between vehicles A and B determined from the image taken by vehicle B and the distance between vehicles A and B calculated from the image taken by vehicle C.

[0043] Furthermore, since the vehicle spacing determined based on the images captured by the vehicle's camera is essentially the distance between the camera and the vehicle in front, the final vehicle spacing can be obtained by subtracting the distance between the camera and the front of the vehicle from the vehicle spacing determined based on the captured images. The distance between the camera and the front of the vehicle is usually a fixed distance and can be determined based on the type or model of the vehicle; this embodiment does not impose any limitations on this.

[0044] It should be noted that this embodiment uses the example of determining the vehicle spacing to match the target vehicle and / or at least one vehicle in the target road segment after determining that the vehicle is a target vehicle that meets the vehicle location update conditions. Alternatively, throughout the entire process after a vehicle enters the target road segment and before it leaves, regardless of whether a target vehicle meeting the vehicle location update conditions exists, the vehicle spacing between the vehicle traveling in the target road segment and the vehicle in front of it is determined. This setup allows for subsequent location updates based on the target vehicle and / or the vehicle spacing in the target road segment once a target vehicle meeting the vehicle location update conditions is identified, thereby improving the location update speed.

[0045] S120. Update the current position of at least one vehicle in the target road segment based on the current position of the target vehicle and the vehicle spacing that matches the target vehicle and / or at least one vehicle in the target road segment.

[0046] In this embodiment, since the current position of the target vehicle is precise location data, and the vehicle spacing is the distance between the current vehicle and the vehicle in front of it, after knowing the current position of the target vehicle, the current position of the vehicles in the target road segment can be calculated based on the positional relationship between the target vehicle and the vehicles in the target road segment, the current position of the target vehicle, and the vehicle spacing matching the target vehicle and / or the vehicles in the target road segment.

[0047] Furthermore, determining whether a vehicle is a target vehicle that meets the vehicle position update conditions based on its position may include: if the vehicle position indicates that the vehicle has entered the target road segment, then the vehicle is determined to be a target vehicle that meets the vehicle position update conditions. Correspondingly, S120 may include: determining the current position of at least one vehicle ahead of the target vehicle in its direction of travel in the target road segment based on the current position of the target vehicle and the vehicle spacing matching at least one vehicle in the target road segment.

[0048] This embodiment provides an implementation method in which, when a target vehicle enters a target road segment, the current position of each vehicle is calculated sequentially forward based on the vehicle spacing matched with other vehicles in the target road segment.

[0049] In an optional embodiment, determining that a target vehicle has entered a target road segment can be achieved by comparing the target vehicle's position with the starting point of the target road segment using the target vehicle's satellite positioning signal. It is understood that relatively accurate vehicle satellite positioning signals can be obtained outside the target road segment; therefore, vehicle positioning can be performed using satellite positioning technology outside the target road segment, and the vehicle's position can be calculated based on the vehicle spacing after it enters the target road segment.

[0050] In another optional embodiment, determining that a target vehicle has entered the target road segment can be achieved using devices such as cameras or radar sensors positioned at or near the starting point of the target road segment. Specifically, cameras capture images of vehicles at the starting point of the target road segment; when a target vehicle is captured, it is determined that the target vehicle has entered the target road segment. Similarly, radar sensors detect vehicles at the starting point of the target road segment; when a target vehicle is detected, it is determined that the target vehicle has entered the target road segment.

[0051] In this embodiment, the location of the target road segment, including its starting and ending points, can be determined based on road network data. When the target vehicle just enters the target road segment, its current position can be determined based on the starting point of the target road segment or satellite positioning signals. Furthermore, according to S110, the vehicle spacing matching the target vehicle (i.e., the vehicle spacing between the target vehicle and other vehicles in the target road segment) can be determined. If there are multiple vehicles in the target road segment, the vehicle spacing matching the other vehicles in the target road segment can also be determined. The current positions of all other vehicles in the target road segment besides the target vehicle can then be calculated sequentially.

[0052] Figure 3 A schematic diagram of each vehicle within the target road segment is provided, such as... Figure 3 As shown, vehicle A in lane 1 enters the target road segment. The current position of vehicle A can be determined based on the starting position of the target road segment. Simultaneously, according to step S110, the distance between vehicle A and vehicle B in the target road segment can be calculated to be 100m, and the distance between vehicle B and vehicle C in the target road segment can be calculated to be 30m. Based on the current position of vehicle A, the distance between vehicle A and vehicle B, and the distance between vehicle B and vehicle C, the current positions of vehicle B and vehicle C can be calculated sequentially.

[0053] Furthermore, determining whether a vehicle is a target vehicle that meets the vehicle location update conditions based on its location may also include: if it is determined from the vehicle location that the vehicle has left the target road segment, then the vehicle is determined to be a target vehicle that meets the vehicle location update conditions; correspondingly, S120 may include: determining the current location of at least one vehicle in the opposite direction of the target vehicle's travel direction in the target road segment based on the target vehicle's current location and the vehicle spacing that matches at least one vehicle in the target road segment.

[0054] This embodiment provides an implementation method in which, when a target vehicle leaves a target road segment, the current position of each vehicle in the target road segment is sequentially deduced based on the vehicle spacing matched with the vehicles in the target road segment.

[0055] The specific method for determining when a target vehicle leaves a target road segment is similar to the method for determining when a target vehicle enters a target road segment, and will not be described in detail in this embodiment.

[0056] In this embodiment, when the target vehicle has just left the target road segment, the current position of the target vehicle can be determined based on the end position of the target road segment or satellite positioning signal. When there is only one vehicle in the target road segment, the vehicle spacing matching the vehicle (that is, the vehicle spacing between the vehicle and the target vehicle) can be determined according to S110. When there are multiple vehicles in the target road segment, the vehicle spacing matching the vehicles in the target road segment can also be determined according to S110. Thus, the current position of each vehicle in the target road segment can be deduced in reverse order.

[0057] like Figure 3 As shown, vehicle F in lane 2 exits the target road segment. The current position of vehicle F can be determined based on the end point of the target road segment. Simultaneously, according to step S110, the distance between vehicles D and E can be calculated to be 60m, and the distance between vehicles E and F can also be calculated to be 60m. Based on the current position of vehicle F, the distance between vehicles E and F, and the distance between vehicles D and E, the current positions of vehicles E and D can be deduced sequentially.

[0058] In this embodiment, by iteratively calculating the vehicle spacing and / or the spacing between vehicles matching the target vehicle within the target road segment, the precise position of each vehicle within the target road segment is obtained. This solves the problem of poor or even no satellite positioning signal within the target road segment, thereby improving the vehicle navigation accuracy within the target road segment. Especially when the traffic flow on the target road segment is high, the vehicle positioning method in this embodiment performs more accurately and quickly. When the traffic flow on the target road segment is high, the vehicle spacing determined based on the captured vehicle images is highly accurate due to the high vehicle density. Simultaneously, the high frequency of vehicles entering and exiting the target road segment results in a higher frequency of updating the current position of vehicles within the target road segment, leading to more accurate position calculation results and higher vehicle navigation accuracy.

[0059] Furthermore, determining whether a vehicle is a target vehicle meeting the vehicle location update conditions based on its position also includes: if it is determined that the vehicle has not entered the target road segment, the distance between the vehicle and the starting point of the target road segment is less than or equal to a preset distance threshold, and the distance between the vehicle and other vehicles traveling in the target road segment is determined based on an image taken by the vehicle in the direction of travel; then the vehicle is determined to be a target vehicle meeting the vehicle location update conditions. Alternatively, if it is determined that the vehicle has left the target road segment, the distance between the vehicle and the ending point of the target road segment is less than or equal to a preset distance threshold, and the distance between the vehicle and other vehicles traveling in the target road segment is determined based on an image taken by the vehicle in the direction of travel. If the image is used to determine the vehicle distance between the vehicle and other vehicles traveling in the target road segment, then the vehicle is determined to be the target vehicle that meets the vehicle position update conditions. Accordingly, S120 may include: if it is determined that there is only one vehicle traveling in the target road segment, then the current position of the vehicle in the target road segment is determined based on the current position of the target vehicle and the vehicle distance between the target vehicle and other vehicles traveling in the target road segment; if it is determined that there are at least two vehicles traveling in the target road segment, then the current positions of at least two vehicles in the target road segment are determined based on the current position of the target vehicle, the vehicle distance between the target vehicle and other vehicles traveling in the target road segment, and the vehicle distance that matches at least one vehicle in the target road segment.

[0060] This embodiment also provides an implementation method for determining the current position of each vehicle in the target road segment when the target vehicle has not entered the target road segment but meets the vehicle position update conditions, and when the target vehicle has left the target road segment but meets the vehicle position update conditions.

[0061] In this embodiment, when the target vehicle has not entered the target road segment but the distance between it and the starting point of the target road segment is less than or equal to a preset distance threshold, the current position of the target vehicle can be obtained based on the satellite positioning signal. Based on the image taken of the target vehicle in its direction of travel, the vehicle distance between the target vehicle and the vehicle closest to the starting point of the target road segment is determined. Furthermore, when there are multiple vehicles in the target road segment, the vehicle distance matching the vehicles in the target road segment can be obtained according to S110, thereby sequentially calculating the current position of each vehicle in the target road segment.

[0062] Similarly, when the target vehicle has left the target road segment but the distance between it and the end point of the target road segment is less than or equal to a preset distance threshold, the current position of the target vehicle can be obtained based on the satellite positioning signal. According to S110, the vehicle distance between the target vehicle and the vehicle closest to the end point in the target road segment can be obtained. At the same time, when there are multiple vehicles in the target road segment, the vehicle distance matching the vehicles in the target road segment can be obtained according to S110, so that the current position of each vehicle in the target road segment can be deduced in reverse.

[0063] Figure 4 A schematic diagram of each vehicle is provided when the target vehicle has not entered the target road segment or has already left the target road segment, such as... Figure 4 As shown, according to S110, the distance between vehicle B and vehicle C can be determined to be 30m. When the distance between vehicle A in lane 1 and the starting position of the target road segment is less than or equal to a preset distance threshold, based on the image captured by vehicle A, the distance between vehicle A and vehicle B traveling in the target road segment can be determined to be 100m. At this time, vehicle A meets the vehicle position update condition. The current position of vehicle A can be obtained based on the satellite positioning signal. Based on the current position of vehicle A, the distance between vehicle A and vehicle B traveling in the target road segment, and the distance between vehicle B and vehicle C, the current positions of vehicle B and vehicle C in the target road segment can be calculated sequentially.

[0064] like Figure 4 As shown, according to S110, the distance between vehicle D and vehicle E can be determined to be 60m. Although vehicle F has left the target road segment, if the distance between vehicle F and the end point of the target road segment is less than or equal to a preset distance threshold, the distance between vehicle E and vehicle F can be determined to be 60m based on the image of vehicle E traveling in the target road segment. At this time, vehicle F meets the vehicle position update condition. The current position of vehicle F can be obtained based on the satellite positioning signal. Based on the current position of vehicle F, the distance between vehicle E and vehicle F, and the distance between vehicle D and vehicle E, the current positions of vehicle E and vehicle D in the target road segment can be deduced sequentially.

[0065] In this embodiment, for target vehicles that have not entered or have left the target road segment but are relatively close to it, if the distance between the target vehicle and other vehicles within the target road segment can be determined, this situation is considered to meet the vehicle position update condition. The current position of the vehicles within the target road segment is then updated based on the target vehicle's current position, the distance between the target vehicle and other vehicles within the target road segment, and the distance between any two vehicles within the target road segment. The advantage of this setup is that it increases the frequency of current position updates for vehicles within the target road segment, thereby improving vehicle navigation accuracy.

[0066] The technical solution of this invention involves photographing vehicles ahead in the direction of travel of vehicles in a target road segment. The distance between vehicles is determined based on the captured images. When a target vehicle meets the vehicle position update conditions, the current position of all vehicles in the target road segment is updated based on the target vehicle's current position and the corresponding vehicle distance in the target road segment. This invention solves the problem of weak or no satellite positioning signals in tunnels, mountainous areas, and other road sections, without requiring additional equipment costs, and improves the accuracy of vehicle positioning.

[0067] Example 2

[0068] Figure 5 This is a flowchart of a vehicle positioning method provided in Embodiment 2 of the present invention. Based on the above embodiments, the present invention further specifies the process of determining the distance between vehicles in the target road segment and the process of updating the current position of vehicles in the target road segment.

[0069] like Figure 5 As shown, the method includes:

[0070] S210. Determine whether the vehicle is a target vehicle that meets the vehicle location update conditions based on the vehicle location. If yes, execute S220; otherwise, return to execute S210.

[0071] The specific process for determining vehicle location update conditions has been described in the above embodiments, and will not be repeated here.

[0072] S220. Determine the image taken by the first vehicle of at least one second vehicle in front of the first vehicle in the direction of travel of the first vehicle.

[0073] The first vehicle is a vehicle traveling in the target road segment (including vehicles that have just entered the target road segment; in this case, the first vehicle is the target vehicle). The second vehicle ahead of the first vehicle in its direction of travel can be either a vehicle traveling in the target road segment or a vehicle that has already left the target road segment (that is, corresponding to the case in the above embodiment where the target vehicle has left the target road segment but still meets the vehicle position update conditions; in this case, the first vehicle is a vehicle in the target road segment, and the second vehicle is the target vehicle).

[0074] S230. Perform vehicle recognition on the image to obtain the rear region of the second vehicle.

[0075] In this embodiment, image processing algorithms can be used to identify the vehicle in the captured image of the first vehicle. The specific method of vehicle identification is not limited in this embodiment. The rear region of the second vehicle refers to the smallest bounding rectangle of the rear of the second vehicle.

[0076] It should be noted that this embodiment uses the determination of the rear area of ​​a vehicle in an image and the determination of the distance between two vehicles based on the rear area as an example. The above embodiment also provides an implementation method for determining the license plate area in an image and determining the distance between two vehicles based on the license plate area. The method of determining the distance between two vehicles based on the license plate area is similar to the method of determining the distance between two vehicles based on the rear area of ​​the vehicle provided in this embodiment, and will not be repeated here.

[0077] S240. Based on the rear area of ​​the second vehicle, determine the vehicle distance between the first vehicle and the second vehicle, and use the vehicle distance between the first vehicle and the second vehicle as the vehicle distance matched with the first vehicle.

[0078] In an optional embodiment, the vehicle distance between the first and second vehicles is determined based on the rear region of the second vehicle. This can be achieved using a pre-trained vehicle distance determination model. Specifically, using a camera, sample images are pre-captured of the rear of vehicles with different distances and vehicle types (or models), and these sample images are labeled with vehicle distance and vehicle type. A deep learning model is then trained using these sample images to obtain the trained vehicle distance determination model. The captured image of the first vehicle is input into the vehicle distance determination model, which performs second vehicle rear region recognition and feature extraction on the captured image, ultimately outputting the vehicle distance corresponding to the rear region of the second vehicle.

[0079] In another optional embodiment, determining the vehicle distance between the first and second vehicles based on the rear region of the second vehicle can also be achieved through a pre-fitted curve of the vehicle rear region pixel area versus vehicle distance. Specifically, using an imaging device, sample images are pre-captured of the rear of vehicles with different vehicle distances and vehicle types (or models). For sample images of different vehicle types, the rear region is identified, and the pixel area of ​​the rear region is calculated. Curve fitting is performed based on the pixel area of ​​the rear region and the vehicle distance for each sample image to obtain the curve of the vehicle rear region pixel area versus vehicle distance for different vehicle types. Based on the rear region of the second vehicle, the vehicle type of the second vehicle is determined, and the curve of the vehicle rear region pixel area versus vehicle distance corresponding to the vehicle type of the second vehicle is determined. The vehicle distance is then determined based on the pixel area of ​​the rear region of the second vehicle and the curve of the vehicle rear region pixel area versus vehicle distance corresponding to the vehicle type of the second vehicle.

[0080] In this embodiment, the distance between the two vehicles is determined based on the rear area of ​​the vehicle in front. The advantage of this setting is that the rear area of ​​the vehicle usually occupies a certain pixel area in the captured image. Compared with the smaller license plate area, the distance between the vehicles determined by the rear area of ​​the vehicle is more accurate.

[0081] Furthermore, S240 may also include:

[0082] S1. Determine the rear area of ​​the vehicle that matches the rear area of ​​the second vehicle.

[0083] S2. Determine the vehicle distance between the first vehicle and the second vehicle based on the pixel area of ​​the rear region of the second vehicle, the vehicle rear area that matches the rear region of the second vehicle, and the focal length of the shooting device of the first vehicle.

[0084] The vehicle rear area matching the second vehicle's rear region refers to the actual area of ​​the vehicle's rear end corresponding to the vehicle type (or model) of the second vehicle. The pixel area of ​​the second vehicle's rear region can be obtained by multiplying the pixel length and pixel width of the second vehicle's rear region in the captured image.

[0085] Furthermore, S1 may include:

[0086] S11. Based on the second vehicle rear region and at least two types of vehicle rear regions preset, determine the target vehicle rear region that has the highest similarity to the second vehicle rear region in each vehicle rear region.

[0087] S12. The vehicle rear area corresponding to the target vehicle rear area is taken as the vehicle rear area that matches the second vehicle rear area.

[0088] In this embodiment, the distance between the lenses of the cameras of the second vehicle and the first vehicle can be determined according to the imaging principle of the camera. The vehicle spacing between the first vehicle and the second vehicle can be determined according to the distance between the lenses of the cameras of the second vehicle and the first vehicle, and the distance between the camera of the first vehicle and the front of the first vehicle.

[0089] Figure 6 A schematic diagram illustrating the principle of determining vehicle spacing based on the rear area of ​​a vehicle is provided, such as... Figure 6 As shown, the imaging device conforms to the principle of similar triangles. Specifically, the ratio of object distance (the distance between the second vehicle and the lens) to image distance (the distance from the lens to the imaging plane) is equal to the ratio of the actual size of the object (the actual size of the rear area of ​​the second vehicle) to the image size (the pixel size of the rear area of ​​the second vehicle in the captured image). The distance from the lens to the imaging plane, i.e., the focal length, can be determined through the lens parameters of the first vehicle's imaging device. Based on the principle of similar triangles, since the focal length is a one-dimensional parameter, while the pixel area and actual area are two-dimensional parameters, the product of the ratio of the square root of the vehicle's rear area matching the rear area of ​​the second vehicle and the pixel area of ​​the second vehicle's rear area, and the focal length, is used as the distance between the lenses of the second vehicle's and the first vehicle's imaging devices.

[0090] For example, if the focal length of the first vehicle is 50mm, the actual rear area of ​​the second vehicle is 2.25m². 2 The pixel area of ​​the rear region of the second vehicle in the image of the first vehicle is 900 mm². 2 Therefore, the calculated distance between the lenses of the cameras on the second vehicle and the first vehicle is 50mm × (√2.25m). 2 / √900mm 2 = 2.5m.

[0091] S250. Update the current position of at least one vehicle in the target road segment based on the current position of the target vehicle and the vehicle spacing that matches the target vehicle and / or at least one vehicle in the target road segment.

[0092] The process of updating the current location of each vehicle in the target road segment has been described in the above embodiments, and will not be repeated here.

[0093] Furthermore, after S220, the method further includes: if it is determined that the pixel area of ​​the rear region of the second vehicle is greater than or equal to a preset pixel area threshold, then the target speed of the first vehicle is determined based on the vehicle distance between the first vehicle and the second vehicle and the current speed of the first vehicle.

[0094] This embodiment also provides an implementation method for adjusting the current speed of two vehicles when the distance between them is small.

[0095] In this embodiment, if the pixel area of ​​the rear region of the second vehicle is greater than or equal to a preset pixel area threshold, it indicates that the distance between the first vehicle and the second vehicle is small. In this case, the second vehicle has a certain impact on the normal driving of the first vehicle, and the speed of the first vehicle needs to be adjusted according to the distance between the vehicles.

[0096] Specifically, a safe speed can be calculated based on the distance between the first and second vehicles and a pre-set safe following time. If the current speed of the first vehicle exceeds the safe speed, an instruction or prompt is issued to the first vehicle to adjust its speed to below the safe speed. This embodiment improves driving safety by adjusting the speed of the following vehicle when the distance between the two vehicles is small.

[0097] Furthermore, following S220, it also includes:

[0098] If it is determined that the pixel area of ​​the rear region of the second vehicle is less than a preset pixel area threshold, then the driving speed of the first vehicle in the target road segment is determined based on the speed of the first vehicle when it enters the target road segment and the speed threshold, or the driving speed of the second vehicle in the target road segment is determined based on the speed of the second vehicle when it enters the target road segment and the speed threshold.

[0099] This embodiment provides a method for updating the current position of two vehicles when the distance between them is large.

[0100] In this embodiment, if the pixel area of ​​the rear region of the second vehicle is smaller than a preset pixel area threshold, it indicates that the distance between the first and second vehicles is relatively large. In this case, on the one hand, the vehicle distance calculated based on the smaller pixel area of ​​the rear region may be inaccurate, and using the vehicle distance estimation method to determine the current position of each vehicle may also be inaccurate. On the other hand, since the distance between the first and second vehicles is relatively large, the impact between the two vehicles is small. In this case, the speeds of the first and second vehicles can be estimated, thereby enabling the positioning and navigation of the first and second vehicles.

[0101] Specifically, if the speed of the first vehicle when it enters the target road segment is greater than a speed threshold, the position of the first vehicle in the target road segment is determined based on the speed threshold and the travel time of the first vehicle in the target road segment; otherwise, the position of the first vehicle in the target road segment is determined based on its speed and travel time in the target road segment. Similarly, if the speed of the second vehicle when it enters the target road segment is greater than a speed threshold, the position of the second vehicle in the target road segment is determined based on the speed threshold and the travel time of the second vehicle in the target road segment; otherwise, the position of the second vehicle in the target road segment is determined based on its speed and travel time in the target road segment.

[0102] After determining the position of the first vehicle or the second vehicle in the target road segment, the current positions of each vehicle in the target road segment are updated based on the current position of the target vehicle, the distance between at least one vehicle in the target road segment, and the position of the first vehicle or the second vehicle in the target road segment.

[0103] As described in the above embodiments, when updating the current position of each vehicle in the target road segment, if the target vehicle has just entered the target road segment or has not entered the target road segment but meets the vehicle position update conditions, the current position of each vehicle is calculated forward according to the target vehicle's current position and the distance between vehicles in the target road segment, following the target vehicle's travel direction. At this time, if the pixel area of ​​the rear region of the second vehicle in the image of a first vehicle in the target road segment is too small, the calculation of the current position of each vehicle is interrupted at the first vehicle. The position of the second vehicle in the target road segment is determined based on its travel speed and travel time. The current position of the first vehicle and all vehicles from the target vehicle to the first vehicle is calculated based on the target vehicle's current position and the distance between vehicles in the target road segment. The current position of the second vehicle and all vehicles ahead of it in the target road segment's travel direction is calculated based on the second vehicle's position in the target road segment and the distance between vehicles.

[0104] If the target vehicle has just left the target road segment or has left the target road segment but meets the vehicle position update conditions, then based on the target vehicle's current position and the distance between vehicles in the target road segment, the current positions of each vehicle are deduced in the opposite direction of the target vehicle's travel. At this time, if the pixel area of ​​the rear region of a second vehicle in an image of a first vehicle in the target road segment is too small, the calculation of the current positions of each vehicle is interrupted at the second vehicle. The position of the first vehicle in the target road segment is determined based on its travel speed and travel time. For the second vehicle and all vehicles from the second vehicle to the target vehicle, their current positions are deduced in reverse based on the target vehicle's current position and the distance between vehicles. For the first vehicle and all vehicles in the target road segment traveling in the opposite direction of the first vehicle's travel, their current positions are deduced in reverse based on the first vehicle's position in the target road segment and the distance between vehicles.

[0105] In this embodiment, when the distance between the two vehicles is large, the current position is estimated based on the vehicle's speed and travel time, which can improve the accuracy and robustness of vehicle positioning.

[0106] The technical solution of this embodiment, when a target vehicle meeting the vehicle position update conditions is determined, determines the rear area of ​​the second vehicle based on an image captured by the first vehicle of the second vehicle ahead in the direction of travel. Based on this rear area, the distance between the first and second vehicles is determined, improving the accuracy of vehicle spacing. The distance between the target vehicle and the vehicles ahead in the direction of travel, and / or the distance between all vehicles in the target road segment, is determined. Based on the current position of the target vehicle and the aforementioned vehicle spacings, the current positions of the vehicles in the target road segment are calculated. Precise positioning of each vehicle in the target road segment not only improves navigation accuracy within the target road segment but also allows the current positions of each vehicle to be sent to vehicles equipped with vehicle positioning systems after obtaining their precise locations. Alternatively, when the distance between two vehicles is small, speed control commands or prompts can be sent to the following vehicles, enabling the vehicle's autonomous driving system to perform lane changes, obstacle avoidance, or speed adjustments based on the positions of each vehicle, thereby improving driving safety.

[0107] Example 3

[0108] Figure 7 This is a structural schematic diagram of a vehicle positioning device provided in Embodiment 3 of the present invention. Figure 7 As shown, the device includes:

[0109] The vehicle spacing determination module 310 is used to determine whether a vehicle is a target vehicle that meets the vehicle position update conditions based on the vehicle position. If so, it determines the vehicle spacing that matches the target vehicle and / or at least one vehicle in the target road segment based on the image captured by the target vehicle and / or at least one vehicle in the target road segment on at least one vehicle in the direction of travel.

[0110] The vehicle location update module 320 is used to update the current location of at least one vehicle in the target road segment based on the current location of the target vehicle and the vehicle spacing that matches the target vehicle and / or at least one vehicle in the target road segment.

[0111] The technical solution of this invention involves photographing vehicles ahead in the direction of travel of vehicles in a target road segment. The distance between vehicles is determined based on the captured images. When a target vehicle meets the vehicle position update conditions, the current position of all vehicles in the target road segment is updated based on the target vehicle's current position and the corresponding vehicle distance in the target road segment. For vehicle positioning methods relying on satellite positioning signals, this invention solves the problem of weak or no satellite positioning signals in tunnels, mountainous areas, and other road sections, requiring no additional equipment costs and improving the accuracy of vehicle positioning.

[0112] Based on the above embodiments, the vehicle spacing determination module 310 includes:

[0113] An image determination unit is used to determine an image captured by the first vehicle of at least one second vehicle in front of the first vehicle in the direction of travel of the first vehicle;

[0114] Wherein, the first vehicle includes the target vehicle and / or at least one vehicle in the target road segment;

[0115] The second vehicle rear region determination unit is used to perform vehicle recognition on the image to obtain the second vehicle rear region.

[0116] The vehicle spacing determination unit is used to determine the vehicle spacing between the first vehicle and the second vehicle based on the rear area of ​​the second vehicle, and to use the vehicle spacing between the first vehicle and the second vehicle as the vehicle spacing matched with the first vehicle.

[0117] Based on the above embodiments, the vehicle spacing determination unit is specifically used for:

[0118] Determine the vehicle rear area that matches the rear area of ​​the second vehicle;

[0119] The distance between the first and second vehicles is determined based on the pixel area of ​​the rear region of the second vehicle, the rear region of the vehicle that matches the rear region of the second vehicle, and the focal length of the camera device of the first vehicle.

[0120] Based on the above embodiments, the vehicle spacing determination module 310 includes:

[0121] The first vehicle location update condition judgment unit determines that if the vehicle has entered the target road segment based on the vehicle location, the vehicle is a target vehicle that meets the vehicle location update condition.

[0122] Vehicle location update module 320 includes:

[0123] The first vehicle position update unit is used to determine the current position of at least one vehicle ahead of the target vehicle in the target road segment based on the current position of the target vehicle and the vehicle spacing that matches at least one vehicle in the target road segment.

[0124] Based on the above embodiments, the vehicle spacing determination module 310 includes:

[0125] The second vehicle location update condition judgment unit is used to determine that if the vehicle has left the target road segment based on the vehicle location, the vehicle is a target vehicle that meets the vehicle location update condition.

[0126] Vehicle location update module 320 includes:

[0127] The second vehicle position update unit is used to determine the current position of at least one vehicle in the opposite direction of the target vehicle's travel direction in the target road segment, based on the current position of the target vehicle and the vehicle spacing that matches at least one vehicle in the target road segment.

[0128] Based on the above embodiments, the vehicle spacing determination module 310 includes:

[0129] The third vehicle position update condition judgment unit is used to determine that if it is determined that the vehicle has not entered the target road segment, the distance between the vehicle and the starting position of the target road segment is less than or equal to a preset distance threshold, and the vehicle spacing between the vehicle and the vehicles traveling in the target road segment is determined based on the image taken by the vehicle in the direction of travel. If the vehicle is determined to be the target vehicle that meets the vehicle position update condition.

[0130] The fourth vehicle position update condition judgment unit is used to determine that if it is determined that the vehicle has left the target road segment, the distance between the vehicle and the end position of the target road segment is less than or equal to a preset distance threshold, and the vehicle spacing between the vehicle and the vehicle in the target road segment is determined based on the image taken by the vehicle in the target road segment in the direction of travel. If the vehicle is determined to be the target vehicle that meets the vehicle position update condition, then the vehicle is determined to be the target vehicle.

[0131] Vehicle location update module 320 includes:

[0132] The third vehicle location update unit is used to determine the current location of the vehicle in the target road segment based on the current location of the target vehicle and the vehicle distance between the target vehicle and the vehicles in the target road segment if it is determined that there is only one vehicle traveling in the target road segment.

[0133] The fourth vehicle location update unit is used to determine the current location of at least two vehicles in the target road segment if it is determined that there are at least two vehicles traveling in the target road segment, based on the current location of the target vehicle, the vehicle spacing between the target vehicle and the vehicles traveling in the target road segment, and the vehicle spacing that matches at least one vehicle in the target road segment.

[0134] Based on the above embodiments, the device further includes:

[0135] The speed determination module is used to determine the target speed of the first vehicle based on the distance between the first vehicle and the second vehicle and the current speed of the first vehicle if the pixel area of ​​the rear region of the second vehicle is determined to be greater than or equal to a preset pixel area threshold.

[0136] The vehicle positioning device provided in the embodiments of the present invention can execute the vehicle positioning method provided in any embodiment of the present invention, and has the corresponding functional modules and beneficial effects of the method.

[0137] Example 4

[0138] Figure 8 A schematic diagram of an electronic device 10 that can be used to implement embodiments of the present invention is shown. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as personal digital processors, cellular phones, smartphones, wearable devices (e.g., helmets, glasses, watches, etc.), and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely illustrative and are not intended to limit the implementation of the invention described and / or claimed herein.

[0139] like Figure 8As shown, the electronic device 10 includes at least one processor 11 and a memory, such as a read-only memory (ROM) 12 or a random access memory (RAM) 13, communicatively connected to the at least one processor 11. The memory stores computer programs executable by the at least one processor. The processor 11 can perform various appropriate actions and processes based on the computer program stored in the ROM 12 or loaded from storage unit 18 into the RAM 13. The RAM 13 may also store various programs and data required for the operation of the electronic device 10. The processor 11, ROM 12, and RAM 13 are interconnected via a bus 14. An input / output (I / O) interface 15 is also connected to the bus 14.

[0140] Multiple components in electronic device 10 are connected to I / O interface 15, including: input unit 16, such as keyboard, mouse, etc.; output unit 17, such as various types of displays, speakers, etc.; storage unit 18, such as disk, optical disk, etc.; and communication unit 19, such as network card, modem, wireless transceiver, etc. Communication unit 19 allows electronic device 10 to exchange information / data with other devices through computer networks such as the Internet and / or various telecommunications networks.

[0141] Processor 11 can be a variety of general-purpose and / or special-purpose processing components with processing and computing capabilities. Some examples of processor 11 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various special-purpose artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, a digital signal processor (DSP), and any suitable processor, controller, microcontroller, etc. Processor 11 performs the various methods and processes described above, such as vehicle positioning methods.

[0142] In some embodiments, the vehicle positioning method may be implemented as a computer program tangibly contained in a computer-readable storage medium, such as storage unit 18. In some embodiments, part or all of the computer program may be loaded and / or mounted on electronic device 10 via ROM 12 and / or communication unit 19. When the computer program is loaded into RAM 13 and executed by processor 11, one or more steps of the vehicle positioning method described above may be performed. Alternatively, in other embodiments, processor 11 may be configured to perform the vehicle positioning method by any other suitable means (e.g., by means of firmware).

[0143] Various embodiments of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field-programmable gate arrays (FPGAs), application-specific integrated circuits (ASICs), application-specific standard products (ASSPs), systems-on-a-chip (SoCs), payload-programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various embodiments may include implementations in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which may be a dedicated or general-purpose programmable processor, capable of receiving data and instructions from a storage system, at least one input device, and at least one output device, and transmitting data and instructions to the storage system, the at least one input device, and the at least one output device.

[0144] Computer programs used to implement the methods of the present invention may be written in any combination of one or more programming languages. These computer programs may be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, such that when executed by the processor, the computer programs cause the functions / operations specified in the flowcharts and / or block diagrams to be performed. The computer programs may be executed entirely on a machine, partially on a machine, or as a standalone software package, partially on a machine and partially on a remote machine, or entirely on a remote machine or server.

[0145] In the context of this invention, a computer-readable storage medium can be a tangible medium that may contain or store a computer program for use by or in conjunction with an instruction execution system, apparatus, or device. A computer-readable storage medium may include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination thereof. Alternatively, a computer-readable storage medium may be a machine-readable signal medium. More specific examples of machine-readable storage media include electrical connections based on one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fibers, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof.

[0146] To provide interaction with a user, the systems and techniques described herein can be implemented on an electronic device having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and pointing device (e.g., a mouse or trackball) through which the user provides input to the electronic device. Other types of devices can also be used to provide interaction with the user; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including sound input, voice input, or tactile input).

[0147] The systems and technologies described herein can be implemented in computing systems that include backend components (e.g., as data servers), or computing systems that include middleware components (e.g., application servers), or computing systems that include frontend components (e.g., user computers with graphical user interfaces or web browsers through which users can interact with implementations of the systems and technologies described herein), or any combination of such backend, middleware, or frontend components. The components of the system can be interconnected via digital data communication of any form or medium (e.g., communication networks). Examples of communication networks include local area networks (LANs), wide area networks (WANs), blockchain networks, and the Internet.

[0148] A computing system can include clients and servers. Clients and servers are generally located far apart and typically interact through communication networks. The client-server relationship is created by computer programs running on the respective computers and having a client-server relationship with each other. The server can be a cloud server, also known as a cloud computing server or cloud host, which is a hosting product within the cloud computing service system to address the shortcomings of traditional physical hosts and VPS services, such as high management difficulty and weak business scalability.

[0149] It should be understood that the various forms of processes shown above can be used, with steps reordered, added, or deleted. For example, the steps described in this invention can be executed in parallel, sequentially, or in different orders, as long as the desired result of the technical solution of this invention can be achieved, and this is not limited herein.

[0150] The specific embodiments described above do not constitute a limitation on the scope of protection of this invention. Those skilled in the art should understand that various modifications, combinations, sub-combinations, and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this invention should be included within the scope of protection of this invention.

Claims

1. A vehicle positioning method characterized by comprising: include: The vehicle position is used to determine whether the vehicle is the target vehicle that meets the vehicle position update conditions. If so, the vehicle spacing that matches the target vehicle and / or at least one vehicle in the target road segment is determined based on the image taken by the target vehicle and / or at least one vehicle in the target road segment of at least one vehicle in the direction of travel. Among them, meeting the vehicle location update conditions includes: when a vehicle enters the target road segment; when a vehicle has not entered the target road segment but the distance between it and the starting position of the target road segment is less than or equal to a preset distance threshold, the vehicle distance between the vehicle and other vehicles traveling in the target road segment can be determined based on the image taken by the vehicle in the direction of travel; when a vehicle leaves the target road segment; or when a vehicle has left the target road segment but the distance between it and the ending position of the target road segment is less than or equal to a preset distance threshold, the vehicle distance between the vehicle and other vehicles traveling in the target road segment can be determined based on the image taken by the vehicle in the direction of travel. The current position of at least one vehicle in the target road segment is updated based on the current position of the target vehicle and the vehicle spacing that matches the target vehicle and / or at least one vehicle in the target road segment.

2. The method according to claim 1, characterized in that, Based on images taken by at least one vehicle in the target vehicle and / or the target road segment of at least one vehicle in the direction of travel of at least one vehicle ahead, determine the vehicle spacing that matches the target vehicle and / or the target road segment of at least one vehicle, including: The images captured by the first vehicle in relation to at least one second vehicle in front of the first vehicle's direction of travel are determined. Wherein, the first vehicle includes the target vehicle and / or at least one vehicle in the target road segment; Vehicle recognition is performed on the image to obtain the rear region of the second vehicle; Based on the rear area of ​​the second vehicle, the vehicle distance between the first vehicle and the second vehicle is determined, and the vehicle distance between the first vehicle and the second vehicle is used as the vehicle distance matched with the first vehicle.

3. The method according to claim 2, characterized in that, Based on the rear area of ​​the second vehicle, determine the vehicle distance between the first and second vehicles, including: Determine the vehicle rear area that matches the rear area of ​​the second vehicle; The distance between the first and second vehicles is determined based on the pixel area of ​​the rear region of the second vehicle, the rear region of the vehicle that matches the rear region of the second vehicle, and the focal length of the camera device of the first vehicle.

4. The method according to claim 1, characterized in that, Determining whether a vehicle meets the vehicle location update criteria based on its location includes: If the vehicle is determined to have entered the target road segment based on its location, then the vehicle is determined to be the target vehicle that meets the vehicle location update conditions. Based on the current location of the target vehicle and the vehicle spacing matching the target vehicle and / or at least one vehicle in the target road segment, the current location of at least one vehicle in the target road segment is updated, including: Based on the current position of the target vehicle and the vehicle spacing that matches at least one vehicle in the target road segment, determine the current position of at least one vehicle ahead of the target vehicle in the direction of travel of the target vehicle in the target road segment.

5. The method according to claim 1, characterized in that, Determining whether a vehicle is a target vehicle that meets the vehicle location update conditions based on its location also includes: If the vehicle is determined to have left the target road segment based on its location, then the vehicle is determined to be the target vehicle that meets the vehicle location update conditions. Based on the current location of the target vehicle and the vehicle spacing matching the target vehicle and / or at least one vehicle in the target road segment, the current location of at least one vehicle in the target road segment is updated, including: Based on the current position of the target vehicle and the vehicle spacing that matches at least one vehicle in the target road segment, determine the current position of at least one vehicle traveling in the opposite direction to the target vehicle in the target road segment.

6. The method according to claim 1, characterized in that, Determining whether a vehicle is a target vehicle that meets the vehicle location update conditions based on its location also includes: If it is determined that the vehicle has not entered the target road segment, and the distance between the vehicle and the starting position of the target road segment is less than or equal to a preset distance threshold, and the vehicle spacing between the vehicle and the vehicles traveling in the target road segment is determined based on the image taken by the vehicle in the direction of travel, then the vehicle is determined to be the target vehicle that meets the vehicle position update conditions. Alternatively, if it is determined that the vehicle has left the target road segment, the distance between the vehicle and the end point of the target road segment is less than or equal to a preset distance threshold, and the vehicle spacing between the vehicle and the vehicle in the target road segment is determined based on the image taken by the vehicle in the target road segment in the direction of travel, then the vehicle is determined to be the target vehicle that meets the vehicle position update conditions. Based on the current location of the target vehicle and the vehicle spacing matching the target vehicle and / or at least one vehicle in the target road segment, the current location of at least one vehicle in the target road segment is updated, including: If it is determined that there is only one vehicle traveling in the target road segment, then the current position of the vehicle in the target road segment is determined based on the current position of the target vehicle and the distance between the target vehicle and the vehicles traveling in the target road segment. If it is determined that there are at least two vehicles traveling in the target road segment, then the current positions of at least two vehicles in the target road segment are determined based on the current position of the target vehicle, the vehicle spacing between the target vehicle and the vehicles traveling in the target road segment, and the vehicle spacing that matches at least one vehicle in the target road segment.

7. The method according to claim 2, characterized in that, After obtaining the rear area of ​​the second vehicle, it also includes: If it is determined that the pixel area of ​​the rear region of the second vehicle is greater than or equal to a preset pixel area threshold, then the target speed of the first vehicle is determined based on the vehicle distance between the first and second vehicles and the current speed of the first vehicle.

8. A vehicle positioning device, characterized in that, include: The vehicle spacing determination module is used to determine whether a vehicle is a target vehicle that meets the vehicle position update conditions based on the vehicle position. If so, it determines the vehicle spacing that matches the target vehicle and / or at least one vehicle in the target road segment based on the image taken by the target vehicle and / or at least one vehicle in the target road segment of at least one vehicle in the direction of travel. Among them, meeting the vehicle location update conditions includes: when a vehicle enters the target road segment; when a vehicle has not entered the target road segment but the distance between it and the starting position of the target road segment is less than or equal to a preset distance threshold, the vehicle distance between the vehicle and other vehicles traveling in the target road segment can be determined based on the image taken by the vehicle in the direction of travel; when a vehicle leaves the target road segment; or when a vehicle has left the target road segment but the distance between it and the ending position of the target road segment is less than or equal to a preset distance threshold, the vehicle distance between the vehicle and other vehicles traveling in the target road segment can be determined based on the image taken by the vehicle in the direction of travel. The vehicle location update module is used to update the current location of at least one vehicle in the target road segment based on the current location of the target vehicle and the vehicle spacing that matches the target vehicle and / or at least one vehicle in the target road segment.

9. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the program, it implements the vehicle positioning method as described in any one of claims 1-7.

10. A storage medium for storing computer-executable instructions, characterized in that, The computer-executable instructions, when executed by a computer processor, are used to perform the vehicle positioning method as described in any one of claims 1-7.

Images