Method and system for determining vehicle path in tunnel and electronic equipment

Abstract

The invention discloses a method and system for determining a vehicle path in a tunnel and electronic equipment. The method comprises the steps that identification information corresponding to at least one vehicle in a driving state in a tunnel is obtained, the at least one vehicle in the driving state forms a vehicle set, and the identification information is used for determining vehicle identities; associating the identification information with the moving path of the corresponding vehicle to obtain associated data which is used for representing a mapping relation between the identification information and the moving path of the corresponding vehicle; the associated data is issued to the target vehicle in the vehicle subset, the associated data is used for enabling the target vehicle to determine a moving path corresponding to the identification information of the target vehicle, and the vehicle set comprises the vehicle subset. According to the invention, the technical problem of low accuracy of positioning the vehicle path in the tunnel is solved.

Description

Technical Field

[0001] The present application relates to the field of vehicles, and in particular, to a method, system and electronic device for determining a vehicle path in a tunnel. Background Art

[0002] At present, with the further development of vehicle-road collaboration, the further improvement of infrastructure, and the further enhancement of the level of intelligence, the intelligent identification and accurate positioning of people, vehicles, and objects on highways are of great significance.

[0003] In the related art, due to the disappearance of the positioning signal inside the tunnel, it is impossible to accurately locate the path of the vehicle within an effective range, resulting in a technical problem of low accuracy in positioning the path of the vehicle in the tunnel.

[0004] To address the above-mentioned problems, no effective solution has been proposed yet. Summary of the invention

[0005] According to one aspect of an embodiment of the present application, a method for determining a vehicle path in a tunnel is provided. The method may include: obtaining identification information corresponding to at least one vehicle in a driving state in the tunnel, wherein the at least one vehicle in a driving state constitutes a vehicle set, and the identification information is used to determine the identity of the vehicle; associating the identification information with the moving path of the corresponding vehicle to obtain associated data, wherein the associated data is used to characterize the mapping relationship between the identification information and the moving path of the corresponding vehicle; sending the associated data to a target vehicle in a vehicle subset, wherein the associated data is used to enable the target vehicle to determine the moving path corresponding to the identification information of the target vehicle, and the vehicle set includes the vehicle subset.

[0006] According to another aspect of the embodiment of the present application, another method for determining a vehicle path in a tunnel is provided. The method may include: obtaining association data obtained by associating identification information with a moving path of a corresponding vehicle, wherein the identification information corresponds to at least one vehicle in a driving state in the tunnel, the at least one vehicle in a driving state constitutes a vehicle set, the identification information is used to determine the identity of the vehicle, and the association data is used to characterize the mapping relationship between the identification information and the moving path of the corresponding vehicle; determining target identification information in the association data that matches the identification information of a target vehicle in a vehicle subset, wherein the vehicle set includes the vehicle subset; and determining the moving path corresponding to the target identification information as the moving path of the target vehicle.

[0007] According to another aspect of the embodiment of the present application, another method for determining the path of a vehicle in a tunnel is also provided. The method may include: obtaining association data obtained from a roadside sensing device by associating identification information with the moving path of the corresponding vehicle, wherein the identification information corresponds to at least one vehicle in a driving state in the tunnel, the at least one vehicle in a driving state constitutes a vehicle set, the identification information is used to determine the identity of the vehicle, and the association data is used to characterize the mapping relationship between the identification information and the moving path of the corresponding vehicle; determining the target identification information in the association data that matches the identification information of the target vehicle in the vehicle subset, wherein the vehicle set includes the vehicle subset; determining the moving path corresponding to the target identification information as the moving path of the target vehicle; and predicting the driving path of the target vehicle at a future moment based on the moving path of the target vehicle.

[0008] According to another aspect of the embodiment of the present application, a system for determining a vehicle path in a tunnel is also provided. The system may include: a road end, for obtaining identification information corresponding to at least one vehicle in a driving state in a tunnel, associating the identification information with the moving path of the corresponding vehicle, obtaining associated data, and sending the associated data to a target vehicle in a vehicle subset, wherein at least one vehicle in a driving state constitutes a vehicle set, the identification information is used to determine the identity of the vehicle, and the associated data is used to characterize the mapping relationship between the identification information and the moving path of the corresponding vehicle; a vehicle end, for obtaining associated data from a roadside sensing device in the road end, determining the target identification information in the associated data set that matches the identification information of the target vehicle in the vehicle subset, and determining the moving path corresponding to the target identification information as the moving path of the target vehicle, wherein the vehicle set includes the vehicle subset.

[0009] According to another aspect of an embodiment of the present application, an electronic device is also provided, which may include a memory and a processor; the memory is used to store computer-executable instructions, and the processor is used to execute computer-executable instructions. When the above-mentioned computer-executable instructions are executed by the processor, the above-mentioned method of any one of the above-mentioned items is implemented.

[0010] According to another aspect of an embodiment of the present application, a processor is further provided, the processor being used to run a program, wherein any one of the above methods is executed when the program is running.

[0011] According to another aspect of an embodiment of the present application, a computer-readable storage medium is further provided, the computer-readable storage medium including a stored program, wherein when the program is running, the device where the storage medium is located is controlled to execute any one of the above methods.

[0012] In an embodiment of the present application, identification information corresponding to at least one vehicle in a driving state in a tunnel is obtained, wherein at least one vehicle in a driving state constitutes a vehicle set, and the identification information is used to determine the identity of the vehicle; the identification information is associated with the moving path of the corresponding vehicle to obtain associated data, wherein the associated data is used to characterize the mapping relationship between the identification information and the moving path of the corresponding vehicle; the associated data is sent to a target vehicle in a vehicle subset, wherein the associated data is used to enable the target vehicle to determine the moving path corresponding to the identification information of the target vehicle, and the vehicle set includes the vehicle subset. That is, the identification information corresponding to the vehicle is obtained, the identification information is associated with the moving path of the vehicle, and the moving path of the target vehicle is determined based on the associated data, thereby achieving the technical effect of improving the accuracy of vehicle path positioning in the tunnel, and solving the technical problem of low accuracy of vehicle path positioning in the tunnel.

[0013] It is easy to notice that the above general description and the following detailed description are only for illustrating and explaining the present application, and do not constitute a limitation of the present application. BRIEF DESCRIPTION OF THE DRAWINGS

[0014] The drawings described herein are used to provide a further understanding of the present application and constitute a part of the present application. The illustrative embodiments of the present application and their descriptions are used to explain the present application and do not constitute an improper limitation on the present application. In the drawings:

[0015] Figure 1 It is a hardware structure block diagram of a computer terminal (or mobile device) for implementing a method for determining a vehicle path in a tunnel according to an embodiment of the present application;

[0016] Figure 2 is a structural block diagram of a computing environment according to an embodiment of the present application;

[0017] Figure 3 is a flow chart of a method for determining a vehicle path in a tunnel according to an embodiment of the present application;

[0018] Figure 4 is a flow chart of another method for determining a vehicle path in a tunnel according to an embodiment of the present application;

[0019] Figure 5 is a flow chart of another method for determining a vehicle path in a tunnel according to an embodiment of the present application;

[0020] Figure 6 Schematic diagram of a system for determining a vehicle path in a tunnel according to an embodiment of the present application

[0021] Figure 7 is a schematic diagram of a vehicle and a main vehicle positioning framework in a tunnel according to an embodiment of the present application;

[0022] Figure 8 is a schematic diagram of a tunnel entrance monitoring camera deployment according to an embodiment of the present application;

[0023] Fig. 9 is a schematic diagram of image data and radar data fusion perception according to an embodiment of the present application;

[0024] Fig.10 is a schematic diagram of a host vehicle associated positioning system according to an embodiment of the present application;

[0025] Fig.11 is a structural block diagram of a service grid according to an embodiment of the present application;

[0026] Fig.12 is a schematic diagram of a device for determining a vehicle path in a tunnel according to an embodiment of the present application;

[0027] Fig.13 is a schematic diagram of another device for determining a vehicle path in a tunnel according to an embodiment of the present application;

[0028] Fig.14 is a schematic diagram of another device for determining a vehicle path in a tunnel according to an embodiment of the present application;

[0029] Fig.15 is a structural block diagram of a computer terminal according to an embodiment of the present application;

[0030] Fig.16 It is a block diagram of an electronic device for a method for determining a vehicle path in a tunnel according to an embodiment of the present application. DETAILED DESCRIPTION

[0031] In order to enable those skilled in the art to better understand the solution of the present application, the technical solution in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the present application.

[0032] It should be noted that the terms "first", "second", etc. in the specification of the present application and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchangeable where appropriate, so that the embodiments of the present application described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any of their variations are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device comprising a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0033] First, some nouns or terms that appear in the description of the embodiments of the present application are subject to the following explanations:

[0034] The vehicle positioning system may be composed of a global positioning system and a geographic information system to track and locate the vehicle;

[0035] The main vehicle may refer to a vehicle carrying an On Board Unit (OBU);

[0036] Vehicle to everything (V2X) refers to the communication between vehicles and road facilities, and can be used for vehicles to exchange information with the outside world.

[0037] Global Navigation Satellite System (GNSS) refers to all satellite navigation systems.

[0038] The on-board unit may be a microwave device that uses a dedicated short range communication technology (DSRC) to communicate with the roadside unit;

[0039] Road Side Unit (RSU) can be a device installed on the roadside that uses DSRC to communicate with the vehicle-mounted unit to achieve vehicle identification;

[0040] Full-area vehicle tracking can refer to vehicle target tracking on the entire road section.

[0041] Example 1

[0042] According to one aspect of an embodiment of the present application, a method for determining a vehicle path in a tunnel is provided. As an optional implementation, the method for determining a vehicle path in a tunnel may be applied to, but is not limited to, Figure 1 The application scenario shown. Figure 1 is a schematic diagram of an application scenario of a method for determining a vehicle path in a tunnel according to an embodiment of the present application, such as Figure 1 As shown, in the application scenario, the terminal device 102 may, but is not limited to, communicate with the server 106 via the network 104, and the server 106 may, but is not limited to, perform operations on the database 108, such as write data operations or read data operations. The above-mentioned terminal device 102 may, but is not limited to, include a human-computer interaction screen, a processor, and a memory. The above-mentioned human-computer interaction screen may, but is not limited to, be used to display the identification information of the target vehicle, the moving path of the target vehicle, etc. on the terminal device 102. The above-mentioned processor may, but is not limited to, be used to respond to the above-mentioned human-computer interaction operation, perform corresponding operations, or generate corresponding instructions, and send the generated instructions to the server 106. The above-mentioned memory is used to store relevant processing data, such as the moving path, identification information, and associated data of the vehicles in the vehicle collection.

[0043] As an optional method, the following steps in the method for determining a vehicle path in a tunnel may be executed on the server 106: Step S102, obtaining identification information corresponding to at least one vehicle in a driving state in the tunnel, wherein the at least one vehicle in a driving state constitutes a vehicle set, and the identification information is used to determine the identity of the vehicle; Step S104, associating the identification information with the moving path of the corresponding vehicle to obtain associated data, wherein the associated data is used to characterize a mapping relationship between the identification information and the moving path of the corresponding vehicle; Step S106, sending the associated data to a target vehicle in a vehicle subset, wherein the associated data is used to enable the target vehicle to determine the moving path corresponding to the identification information of the target vehicle, and the vehicle set includes the vehicle subset.

[0044] By adopting the above method, the identification information corresponding to the vehicle is obtained, the identification information is associated with the vehicle's moving path, and the moving path of the target vehicle is determined based on the associated data, thereby achieving the technical effect of improving the accuracy of vehicle path positioning in the tunnel and solving the technical problem of low accuracy of vehicle path positioning in the tunnel.

[0045] Figure 2 is a structural block diagram of a computing environment according to an embodiment of the present application, such as Figure 2 As shown, computing environment 201 includes multiple computing nodes (such as servers) running on a distributed network (shown as 210-1, 210-2, ..., in the figure). The computing nodes all contain local processing and memory resources, and end users 202 can remotely run applications or store data in computing environment 201. Applications can be provided as multiple services 220-1, 220-2, 220-3 and 220-4 in computing environment 201, representing services "A", "D", "E" and "H" respectively.

[0046] The end user 202 can provide and access services through a web browser or other software application on the client, and in some embodiments, the end user 202's provision and / or request can be provided to the entry gateway 230. The entry gateway 230 can include a corresponding agent to handle the provision and / or request for the service (one or more services provided in the computing environment 201).

[0047] Services are provided or deployed based on various virtualization technologies supported by the computing environment 201. In some embodiments, services can be provided based on virtualization based on virtual machines (VMs), container-based virtualization, and / or similar methods. While virtual machines virtualize machines, containers can be started to virtualize the entire operating system (OS) based on container-based virtualization so that multiple workloads can run on a single operating system instance.

[0048] In an embodiment based on container virtualization, several containers of a service can be assembled into a computing unit (e.g., a Kubernetes Pod). Figure 2 As shown, service 220-2 can be equipped with one or more computing units (Pods) Pod240-1, 240-2, ..., 240-N (collectively referred to as Pods). Pods can include agents 245 and one or more containers 242-1, 242-2, ..., 242-M (collectively referred to as containers). Agent 245 generally controls network functions related to the service. Other services can also be equipped with Pods similar to Pods.

[0049] During operation, executing a user request from end user 202 may require invoking one or more services in computing environment 201, and executing one or more functions of a service may require invoking one or more functions of another service. Figure 2 As shown, service "A" 220-1 receives a user request from a terminal user 202 from an entry gateway 230, for example, a request to determine a moving path. Service "A" 220-1 can call service "D" 220-2, and service "D" 220-2 can request service "E" 220-3 to execute step S21 to obtain an identification information corresponding to at least one vehicle in motion in the tunnel; step S22, to associate the identification information with the moving path of the corresponding vehicle to obtain associated data; step S23, to send the associated data to the target vehicle in the vehicle subset, thereby completing the function of sending the moving path corresponding to the target vehicle to the client.

[0050] The computing environment described above can be a cloud computing environment, where the allocation of resources is managed by the cloud service provider, allowing the development of functions without considering the implementation, adjustment or expansion of servers. The computing environment allows developers to execute code in response to events without building or maintaining complex infrastructure. Services can be divided into a set of functions that can be automatically and independently scaled, rather than expanding a single hardware device to handle potential loads.

[0051] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, stored data, displayed data, etc.) involved in this application, such as weather forecast results and other data, are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of relevant data must comply with the relevant laws, regulations and standards of relevant countries and regions, and provide corresponding operation entrances for users to choose to authorize or refuse.

[0052] In the above operating environment, the present application provides a method for determining a vehicle path in a tunnel from the road side. Figure 3 FIG. 1 is a flow chart of a method for determining a vehicle path in a tunnel according to an embodiment of the present application. Figure 3 As shown, the method may include the following steps:

[0053] Step S302, obtaining identification information corresponding to at least one vehicle in a driving state in the tunnel, wherein the at least one vehicle in a driving state constitutes a vehicle set, and the identification information is used to determine the identity of the vehicle.

[0054] In the technical solution provided in the above step S302 of the present application, identification information corresponding to at least one vehicle in a driving state in the tunnel can be obtained. The identification information can be used to determine the identity of the vehicle, and can be license plate information, vehicle identity information (such as vehicle ID), vehicle model information, etc. This is only an example and does not specifically limit the identification information. At least one vehicle in a driving state constitutes a vehicle set.

[0055] Optionally, in the tunnel, there is at least one vehicle in motion, and identification information corresponding to the vehicle can be obtained through an identification device.

[0056] For example, a license plate recognition camera may be used to perform license plate recognition on at least one vehicle traveling in a tunnel to obtain license plate information corresponding to the at least one vehicle traveling in the tunnel.

[0057] Step S304 , associating the identification information with the movement path of the corresponding vehicle to obtain association data, wherein the association data is used to characterize the mapping relationship between the identification information and the movement path of the corresponding vehicle.

[0058] In the technical solution provided in the above step S304 of the present application, the moving path of at least one vehicle is obtained, and the identification information and the moving path of the corresponding vehicle are associated to obtain associated data. The associated data can be used to characterize the mapping relationship between the identification information and the moving path of the corresponding vehicle. The moving path can be the driving path of the vehicle in the tunnel, and can be the roadside sensing vehicle data, which can also be called the vehicle global tracking path.

[0059] Optionally, the movement path of at least one vehicle in the tunnel may be obtained, and the movement path of at least one vehicle may be associated with identification information corresponding to the identified vehicle to obtain associated data.

[0060] For example, the moving paths of vehicles A, B and C in the tunnel can be determined by ultra-wideband technology (UWB) equipment or millimeter wave radar, and the identification information corresponding to vehicles A, B and C can be obtained by a license plate recognition camera, and the identification information of vehicles A, B and C can be associated with the moving paths corresponding to vehicles A, B and C to obtain associated data, wherein the associated data may include the identification information of vehicle A corresponding to the moving path of vehicle A, the identification information of vehicle B corresponding to the moving path of vehicle B, and the identification information of vehicle C corresponding to the moving path of vehicle C.

[0061] Step S306, sending the associated data to the target vehicle in the vehicle subset, wherein the associated data is used to enable the target vehicle to determine a moving path corresponding to the identification information of the target vehicle, and the vehicle set includes the vehicle subset.

[0062] In the technical solution provided in the above step S306 of the present application, the associated data can be sent to a target vehicle in any vehicle subset in the vehicle set, and the target vehicle can determine the corresponding moving path based on the associated data. The vehicle subset can be a collection of vehicles in the vehicle set that are equipped with an on-board unit (OBU).

[0063] Since the signal of the global navigation satellite system in the tunnel is weak, the vehicle cannot be accurately positioned, resulting in a technical problem of low accuracy in positioning the moving path of the vehicle traveling in the tunnel. To solve the above problem, the embodiment of the present application associates the vehicle's identification information with the vehicle's moving path in the tunnel to obtain associated data, and sends the associated data to the target vehicle through the roadside sensing device at the road end. The target vehicle can determine the moving path corresponding to the target vehicle's identification information from the associated data, thereby determining the moving path of the target vehicle in the tunnel.

[0064] Optionally, the associated data may be sent down to a target vehicle in a vehicle subset through a roadside unit (RUS) in a roadside sensing device, so that the target vehicle may determine a corresponding moving path of the target vehicle based on identification information of the target vehicle.

[0065] In an embodiment of the present application, identification information corresponding to the vehicle is obtained, the identification information is associated with the vehicle's moving path, and the moving path of the target vehicle is determined based on the associated data, thereby achieving the technical effect of improving the accuracy of vehicle path positioning in the tunnel and solving the technical problem of low accuracy of vehicle path positioning in the tunnel.

[0066] The above method of this embodiment is further introduced below.

[0067] As an optional implementation, step S304 associates the identification information with the moving path of the corresponding vehicle to obtain associated data, including: determining the monitoring time of the monitored identification information and the monitoring position of the identification information at the monitoring time; in response to the vehicle's moving path being located at the monitoring position at the monitoring time, the identification information and the moving path are associated to obtain associated data.

[0068] In this embodiment, the monitoring time of the monitored identification information and the monitoring position of the identification information at the monitoring time can be determined. It is determined whether the moving path of the vehicle is located at the monitoring position at the monitoring time. In response to the moving path of the vehicle being located at the monitoring time at the monitoring time, the identification information and the moving path can be associated to obtain associated data. The monitoring position can be a certain spatial position in the tunnel. The monitoring time can be the identification time for identifying the identification information of the vehicle.

[0069] Optionally, the monitoring position of the identified identification information at the monitoring time is determined, and the moving path to the monitoring position at the monitoring time is determined. The identification information and the moving path at the same time and at the same position can be associated to obtain associated data, thereby integrating the identification information and the moving path under the premise of unified calibration of time and space. Among them, the moving path of all vehicles can also be called the vehicle global tracking path.

[0070] For example, a license plate recognition camera can recognize the license plates of passing vehicles to obtain the identification information corresponding to each vehicle. Under the premise of unified calibration in time and space, the license plate recognition results can be fused with the vehicle's global tracking path to obtain related data.

[0071] For another example, the identification information of the vehicle and the monitoring time of the identification information can be determined, and the moving path of the vehicle and the corresponding timestamp can be obtained. Time calibration is performed according to the timestamp corresponding to the moving path of the vehicle and the monitoring time of the identification information. The identification information and the path data are spatially calibrated so that the identification information and the moving path correspond to each other in space. For example, an image processing algorithm or a geometric transformation method can be used to match the monitoring position of the identification information with the position information of the moving path. The identification information and the moving path can be matched in time sequence, and the corresponding identification information and the moving path can be associated. For example, the identification information at the monitoring time and the monitoring position corresponding to the identification information can be determined, and the moving path at the monitoring position at the monitoring time can be determined. The identification information can be associated with the determined moving path to obtain associated data. The associated data can be further analyzed and applied. For example, the associated data can be used for vehicle path analysis, path planning, traffic management and other applications.

[0072] As an optional implementation, radar data and multi-frame image data are obtained at at least one position in the tunnel, wherein the image data and radar data are data obtained by a millimeter-wave radar and a monitoring camera deployed at the same position, and the image data is used to characterize the driving environment of the vehicle; image features corresponding to the multi-frame image data and radar features corresponding to the radar data are determined; the image features and the radar features are fused to obtain fused data, wherein the fused data includes the position points of the vehicle at different monitoring times; based on the mapping relationship between the position points in the fused data and the real map, the movement path of the vehicle is determined.

[0073] In this embodiment, radar data acquired by a millimeter-wave radar at at least one position in the tunnel and multiple frames of image data monitored by a monitoring camera can be obtained to determine image features corresponding to the multiple frames of image data and radar features corresponding to the radar data. The image features and radar features can be fused to obtain fused data, and the moving path of the vehicle can be determined based on the mapping relationship between the position points in the fused data and the real map. Among them, the image data and radar data can be data acquired by the millimeter-wave radar and monitoring camera deployed at the same position. The monitoring camera can be a camera, a video camera, or other device that can take pictures. The image data can be used to characterize the driving environment of the vehicle, for example, it can be used to determine the vehicles moving around the vehicle. Multiple frames of image data can form a video. Radar data can be used to measure the distance between the vehicle and the radar, and can provide accurate distance information from the vehicle to the radar, the speed of the vehicle, the driving direction, the size, the outline, and the size of the vehicle. It should be noted that this is only an example, and no specific restrictions are imposed on the data content of millimeter wave monitoring. At least one position can be a position set in the tunnel, for example, it can be a position every 120 meters in the tunnel. This is only an example, and no specific restrictions are imposed on at least one position. The fused data can include the location points of the vehicle at different monitoring times.

[0074] In this embodiment, in order to accurately obtain the precise positioning of vehicles in the tunnel, a set of full coverage monitoring system in the tunnel is designed. A point can be designed and deployed at at least one position in the tunnel (for example, every 120 meters). A camera and a millimeter wave radar are installed in the same direction at each point. The monitoring range of the camera and the millimeter wave radar covers almost the same area. The camera obtains multi-frame image data at at least one position and the millimeter wave radar obtains radar data, thereby realizing video and radar fusion target detection, tracking, and positioning based on video and millimeter wave radar under the condition of full coverage of the tunnel, thereby achieving the purpose of accurately locating the moving path of the vehicle in the tunnel. Among them, the positioning accuracy can reach the lane level. Among them, the camera can be a monitoring camera that meets a certain resolution, frame rate and has a timestamp function.

[0075] For example, radar data and multiple frames of image data at at least one position in the tunnel can be obtained, and target detection and tracking can be performed on the video data to identify the position and movement path of the vehicle. For example, computer vision algorithms (YOLO, Faster R-CNN, etc.) can be used for target detection, and then target tracking can be achieved through methods such as optical flow method or Kalman filtering. At the same time, radar data can be pre-processed and radar features can be extracted to obtain the position and speed information of the vehicle. The image features corresponding to the multiple frames of image data and the radar features corresponding to the radar data are determined. The image features and radar features can be pre-fused, for example, a multi-sensor fusion algorithm (such as Kalman filtering, particle filtering, etc.) can be used to obtain fused data (which can be a more accurate position and movement path of the vehicle). Continuous position points in the fused data can be connected according to the timestamp and position information to determine the movement path of the vehicle from the fused data. The movement path obtained from the fused data can be used to analyze the vehicle's driving path, speed, acceleration, etc., and used for applications such as traffic flow monitoring, vehicle behavior analysis, and intelligent transportation systems. It should be noted that in the process of data fusion, the alignment of the time and space coordinate systems between the data should be considered to ensure the accuracy of the fusion results. At the same time, the characteristics and errors of different sensors also need to be reasonably processed and corrected.

[0076] Optionally, radar data and multi-frame image data at at least one position in the tunnel can be obtained, and the image features of the multi-frame image data and the radar features corresponding to the radar data can be determined. The roadside perception device performs radar and visual target perception fusion analysis on the image features and the corresponding radar features to obtain the corresponding vehicle target. The obtained vehicle target can be associated with the high-precision map, and the vehicle target point can be mapped to obtain the longitude and latitude information in the world coordinate system, so as to determine the actual movement path of the vehicle. Before mapping, calibration between the image and the high-precision map, as well as alignment of the millimeter-wave radar and the visual scene will be performed.

[0077] As an optional implementation, step S306, sending the associated data to the target vehicle in the vehicle subset, includes: controlling the roadside unit to send the associated data to the on-board unit of the target vehicle.

[0078] In this embodiment, the associated data can be sent to the on-board unit of the target vehicle through the roadside unit. Among them, the roadside unit (RoadSideUnit, referred to as RSU) can be installed on the roadside and can be used to communicate with the vehicle end. The on-board unit can be used to communicate with the roadside system. The target vehicle can also be called the main vehicle, which can be a vehicle carrying the on-board unit.

[0079] Optionally, this embodiment can broadcast the moving paths of all vehicles to the OBU of the target vehicle through the RSU. After receiving the data, the OBU can analyze the data to determine the moving path of the target vehicle in the tunnel.

[0080] This embodiment proposes a method for positioning vehicles and the main vehicle in a tunnel from the perspective of vehicle-road collaboration. It can address the problems of weak Global Navigation Satellite System (GNSS) signals in the tunnel, inability to accurately position vehicles, and inability to effectively identify the main vehicle. It can obtain radar data and multi-frame image data at at least one position in the tunnel, and achieve lane-level vehicle positioning with full coverage through radar data and image data. It also has the ability to distinguish between the main vehicle and other perceived vehicles. The roadside unit sends the associated data to the target vehicle with the on-board unit to enable the vehicle-side to realize the roadside perception function, thereby achieving the technical effect of improving the accuracy of vehicle path positioning in the tunnel, and solving the technical problem of low accuracy of vehicle path positioning in the tunnel.

[0081] As an optional implementation, step S302, obtaining identification information corresponding to at least one vehicle in a driving state in a tunnel, includes: obtaining license plate information corresponding to at least one vehicle identified by a monitoring device located at at least one position in the tunnel, wherein the at least one position includes a position within a target range from a tunnel exit of the tunnel, and the monitoring device is used to identify the license plate information of the vehicle.

[0082] In this embodiment, the license plate information corresponding to at least one vehicle identified by the monitoring device at at least one position in the tunnel can be obtained. The at least one position can include a position within a target range from the tunnel exit of the tunnel. The monitoring device can be used to identify the license plate information of the vehicle, and can be a license plate recognition camera.

[0083] For example, a point can be designed and deployed every 120 meters inside the tunnel, and a camera and a millimeter-wave radar can be installed at each point. Each camera and millimeter-wave radar can effectively cover a range of at least 120 meters. A license plate recognition camera can be installed every 20 points to obtain the license plate information corresponding to at least one vehicle identified by the monitoring equipment located at at least one location in the tunnel.

[0084] As an optional implementation, step S304, obtaining identification information corresponding to at least one vehicle in a driving state in the tunnel, includes: obtaining multiple frames of image data at a position within a target range from the tunnel exit and identification information recognized by the monitoring device, and obtaining multiple frames of image data on the opposite side of the position within the target range from the tunnel exit.

[0085] In this embodiment, taking into account the problem of backlight or front light at the tunnel entrance, it involves obtaining multiple frames of image data at a position within the target range of the tunnel exit, identification information recognized by the monitoring equipment, and multiple frames of image data on the opposite side of the position within the target range of the tunnel exit.

[0086] For example, a point a is deployed within the target range (for example, 30 to 50 meters) from the tunnel entrance, an ordinary monitoring camera is installed in both directions of the point, and a license plate recognition camera is installed in the direction of the tunnel entrance at the point. An ordinary monitoring camera is installed in both directions within 60 to 120 meters from point a, and point c is deployed on the opposite side of point a, and an ordinary monitoring camera is deployed at point c. Multi-frame image data at point a and identification information recognized by the monitoring equipment, and multi-frame image data at points b and c can be obtained. The identification information of the vehicle can be accurately identified and the vehicle can be located through the data at points a, b and c, thereby avoiding the problem of inability to accurately locate the vehicle due to backlight or front light at the tunnel entrance.

[0087] As an optional implementation, the method further includes: the associated data is used to enable the target vehicle to determine target identification information that is identical to the identification information of the target vehicle, and to determine a moving path associated with the target identification information as the moving path of the target vehicle.

[0088] In this embodiment, target identification information identical to the identification information of the target vehicle in the associated data may be determined, and a moving path associated with the target identification information may be determined as the moving path of the target vehicle.

[0089] Since the GNSS signal inside the tunnel is weak or absent, it is impossible to ensure that the vehicle equipment equipped with the OBU can accurately locate the main vehicle. Therefore, on the basis of full coverage of vehicle perception and positioning in the tunnel, this embodiment proposes to use license plate information to effectively associate the roadside perception vehicle data with the vehicle equipped with the OBU, and send the associated data to the target vehicle. The vehicle equipped with the OBU can enter the license plate information in advance to obtain the identification information of the target vehicle. When the associated data is obtained, the target identification information in the associated data that is the same as the pre-entered identification information can be determined, and the moving path associated with the target identification information can be determined as the moving path of the target vehicle, thereby solving the technical problem that the moving path of the vehicle cannot be located in the tunnel.

[0090] For example, the license plate recognition camera in the tunnel can recognize the license plates of passing vehicles in the tunnel. Under the premise of unified calibration in time and space, the license plate recognition results can be integrated into the roadside perception equipment and associated (or fused) with the movement path of at least one vehicle obtained to obtain associated data. The associated data of all vehicles can be broadcasted through the RSU. After receiving the associated data, the OBU will parse the associated data and send it to the on-board intelligent device. The on-board intelligent device compares the license plate information input in advance with the license plate information in the associated data of all vehicles. After matching, the moving path of the main vehicle can be determined, so that the moving path can be continuously associated based on the target identification information in the path.

[0091] In an embodiment of the present application, real road information and simulated road information of a real road on which a vehicle to be tested is located are obtained, and the real road information and the simulated road information are fused and processed to obtain fused road information. The fused road information greatly enriches the autonomous driving test scenario, thereby obtaining accurate test results, thereby achieving the technical effect of improving the efficiency of vehicle testing and solving the technical problem of low accuracy in positioning the vehicle path in a tunnel.

[0092] The embodiment of the present application also provides another method for determining a vehicle path in a tunnel from the vehicle side. Figure 4 is a flow chart of another method for determining a vehicle path in a tunnel according to an embodiment of the present application, such as Figure 4 As shown, the method may include the following steps.

[0093] Step S402, obtaining association data obtained by associating the identification information with the moving path of the corresponding vehicle, wherein the identification information corresponds to at least one vehicle in a driving state in the tunnel, the at least one vehicle in a driving state constitutes a vehicle set, the identification information is used to determine the identity of the vehicle, and the association data is used to characterize the mapping relationship between the identification information and the moving path of the corresponding vehicle.

[0094] In the technical solution provided in the above step S402 of the present application, the identification information and the moving path of the corresponding vehicle are associated in the roadside sensing device at the road end to obtain associated data, and the associated data is sent to the vehicle end. The vehicle end can obtain the associated data. Among them, the identification information can correspond to at least one vehicle in a driving state in the tunnel, and can be used to determine the identity of the vehicle. At least one vehicle in a driving state in the tunnel constitutes a vehicle set. The associated data can be used to characterize the mapping relationship between the identification information and the moving path of the corresponding vehicle.

[0095] Optionally, the moving path of a vehicle set consisting of at least one vehicle in the tunnel can be obtained, and identification information obtained by identifying the vehicles in the vehicle set can be obtained. The roadside sensing device can associate the identification information with the moving path of the corresponding vehicle to obtain associated data, and send the associated data to the vehicle end. The vehicle end obtains the associated data.

[0096] In this embodiment, vehicle-road collaboration is utilized to send related data to the vehicle side, so as to realize the use of advanced wireless communication and new generation Internet technologies, implement all-round dynamic real-time information interaction between vehicles and roads, and carry out vehicle active safety control and road collaborative management based on the collection and integration of dynamic traffic information in all time and space, fully realize the effective collaboration between people, vehicles and roads, ensure traffic safety, improve traffic efficiency, and thus form a safe, efficient and environmentally friendly road traffic system.

[0097] Step S404, determining target identification information in the associated data that matches identification information of a target vehicle in the vehicle subset, wherein the vehicle set includes the vehicle subset.

[0098] In the technical solution provided in the above step S404 of the present application, the target vehicle in the vehicle subset obtains the associated data, and the target identification information that matches the identification information of the target vehicle in the associated data can be determined. Among them, the target vehicle can also be called the main vehicle, which can be a vehicle carrying an on-board unit and can communicate with the roadside sensing device through the on-board unit. The vehicle set contains the vehicle subset. The vehicle subset can be a collection of vehicles in the vehicle set that carry the on-board unit.

[0099] Step S406: determine the moving path corresponding to the target identification information as the moving path of the target vehicle.

[0100] In the technical solution provided in the above step S406 of the present application, the moving path corresponding to the target identification information can be determined as the moving path of the target vehicle.

[0101] Optionally, the roadside perception device can send the associated data to the target vehicle in the vehicle subset. The target vehicle determines the target identification information in the associated data that matches the identification information of the target vehicle based on the pre-input identification information, and can determine the moving path corresponding to the target identification information as the moving path of the target vehicle.

[0102] As an optional implementation, step S404, determining target identification information in the associated data set that matches the identification information of the target vehicle in the vehicle subset, includes: determining identification information in the associated data that is the same as the identification information of the target vehicle as the target identification information.

[0103] In this embodiment, the identification information of the target vehicle may be acquired in advance. The identification information identical to the identification information of the target vehicle in the associated data may be determined as the target identification information. The moving path associated with the target identification information may be determined as the moving path of the target vehicle.

[0104] Optionally, this embodiment determines the association between the identification information and the moving path of the vehicle in the vehicle set through the roadside sensing device, obtains the associated data, and sends the associated data to the target vehicle. The target vehicle can determine the moving path of the target vehicle from the associated data based on the identification information of the target vehicle input in advance, thereby solving the problem of being unable to accurately determine the moving path of the vehicle in the tunnel.

[0105] As an optional implementation, the identification information of the target vehicle is obtained from an on-board intelligent device on the vehicle side.

[0106] In this embodiment, the identification information of the target vehicle can be obtained from the vehicle-side in-vehicle intelligent device, wherein the in-vehicle intelligent device is used to determine the target identification information matching the identification information of the target vehicle in the associated data, and the moving path of the target vehicle can be determined based on the target identification information.

[0107] For example, in the roadside sensing device, the license plate recognition camera in the tunnel can recognize the license plates of passing vehicles in the tunnel. Under the premise of unified calibration in time and space, the license plate recognition results can be integrated into the roadside sensing device, and associated (or fused) with the movement path of at least one vehicle obtained to obtain the associated data. The roadside sensing device can broadcast the associated data of all vehicles through the RSU. After the OBU in the vehicle receives the associated data, it will parse the associated data and send it to the on-board intelligent device. The on-board intelligent device compares the license plate information input in advance with the license plate information in the associated data of all vehicles. After matching, the moving path of the main vehicle can be determined, so that the moving path can be continuously associated based on the target identification information in the path.

[0108] In this embodiment, the vehicle itself only needs to be loaded with an OBU device and an intelligent vehicle-mounted device. Through the interaction of information between the OBU device and an intelligent vehicle-mounted device, the lane-level positioning capability of the target vehicle and the ability to perceive surrounding beyond-visual-range vehicles can be achieved. In actual application, the on-board intelligent device can be embedded in the navigation program, and the moving path of the target vehicle can be further analyzed based on the navigation program.

[0109] Optionally, in addition to positioning the vehicle and the main vehicle in the tunnel based on video, radar, high-precision map, license plate, RSU and OBU, vehicle positioning can also be based on ultra-wideband communication, or other vehicle-side positioning methods that rely on roadside sensing equipment (also called roadside equipment). No specific restrictions are made on the device for vehicle positioning here. Methods for positioning the vehicle and determining the vehicle position through identification information should be within the scope of protection of this application.

[0110] In an embodiment of the present application, association data is obtained by associating identification information with a moving path of a corresponding vehicle, wherein the identification information corresponds to at least one vehicle in a driving state in a tunnel, the at least one vehicle in a driving state constitutes a vehicle set, the identification information is used to determine the identity of the vehicle, and the association data is used to characterize the mapping relationship between the identification information and the moving path of the corresponding vehicle; target identification information matching the identification information of a target vehicle in a vehicle subset in the association data is determined; and the moving path corresponding to the target identification information is determined as the moving path of the target vehicle, thereby achieving a technical effect of improving the accuracy of vehicle path positioning in a tunnel, and solving the technical problem of low accuracy of vehicle path positioning in a tunnel.

[0111] The embodiments of the present application are aimed at driving scenarios, such as navigation, vehicle-road collaboration, smart highways, etc., and also provide a method for determining the vehicle path in a tunnel. Figure 5 FIG. 1 is a flow chart of another method for determining a vehicle path in a tunnel according to an embodiment of the present application. Figure 5 As shown, the method may include the following steps:

[0112] Step S502, obtaining association data from a roadside sensing device by associating identification information with a moving path of a corresponding vehicle, wherein the identification information corresponds to at least one vehicle in a driving state in a tunnel, the at least one vehicle in a driving state constitutes a vehicle set, the identification information is used to determine the identity of the vehicle, and the association data is used to characterize a mapping relationship between the identification information and the moving path of the corresponding vehicle.

[0113] In the technical solution provided in the above step S502 of the present application, the roadside sensing device obtains the identification information corresponding to at least one vehicle in a driving state, and associates the identification information with the moving path of the corresponding vehicle to obtain associated data. The terminal can obtain the associated data from the roadside sensing device. Among them, the terminal can be a vehicle terminal, a mobile terminal, such as a mobile phone, a computer terminal, etc. The terminal can be changed according to the actual usage, and no specific limitation is made here on the terminal type.

[0114] Step S504, determining target identification information in the associated data that matches identification information of a target vehicle in the vehicle subset, wherein the vehicle set includes the vehicle subset.

[0115] In the technical solution provided in the above step S504 of the present application, target identification information in the associated data that matches the identification information of the target vehicle in the vehicle subset can be determined.

[0116] Step S506: determine the moving path corresponding to the target identification information as the moving path of the target vehicle.

[0117] In the technical solution provided in the above step S506 of the present application, the target identification information in the associated data that matches the identification information of the target vehicle in the vehicle subset can be determined, and the moving path corresponding to the target identification information can be determined as the moving path of the target vehicle.

[0118] Step S508: predicting the target vehicle's travel path at a future time based on the target vehicle's moving path.

[0119] In the technical solution provided in the above step S508 of the present application, the moving path of the target vehicle at the historical moment is determined, and the moving path of the target vehicle at the historical moment can be predicted to determine the driving path of the target vehicle at the future moment.

[0120] Optionally, the moving path of the target vehicle in the tunnel is determined, and the moving path of the target vehicle at a historical moment can be used to plan the driving path of the target vehicle to obtain the driving path of the target vehicle at a future moment.

[0121] In an embodiment of the present application, associated data is obtained from a roadside sensing device by associating identification information with a moving path of a corresponding vehicle, wherein the identification information corresponds to at least one vehicle in a driving state in a tunnel, the at least one vehicle in a driving state constitutes a vehicle set, the identification information is used to determine the identity of the vehicle, and the associated data is used to characterize a mapping relationship between the identification information and the moving path of the corresponding vehicle; target identification information matching the identification information of a target vehicle in a vehicle subset in the associated data is determined; the moving path corresponding to the target identification information is determined as the moving path of the target vehicle; and the driving path of the target vehicle at a future moment is predicted based on the moving path of the target vehicle, thereby achieving a technical effect of improving the accuracy of vehicle path positioning in a tunnel, and solving the technical problem of low accuracy of vehicle path positioning in a tunnel.

[0122] Example 2

[0123] According to an embodiment of the present application, an embodiment of a system for determining a vehicle path in a tunnel is also provided. Figure 6 is a schematic diagram of a system for determining a vehicle path in a tunnel according to an embodiment of the present application, such as Figure 6 As shown, a system 600 for determining a vehicle path in a tunnel may include: a road end 602 and a vehicle end 604 .

[0124] Road end 602 is used to obtain identification information corresponding to at least one vehicle in a driving state in the tunnel, associate the identification information with the moving path of the corresponding vehicle, obtain associated data, and send the associated data to the target vehicle in the vehicle subset, wherein at least one vehicle in a driving state constitutes the vehicle set, the identification information is used to determine the identity of the vehicle, and the associated data is used to characterize the mapping relationship between the identification information and the moving path of the corresponding vehicle.

[0125] Optionally, the road end 602 may obtain identification information and a driving path corresponding to at least one vehicle in a driving state in the tunnel through a roadside sensing device in the road end, associate the identification information with the driving path, and obtain associated data. The associated data may be sent to a target vehicle in the vehicle subset through the roadside sensing device, wherein the vehicle set includes the vehicle subset.

[0126] For example, the road side 602 may include multiple road side sensing devices A and multiple road side sensing devices B. The multiple road side sensing devices A may parse the vehicle paths within the range of the camera or millimeter wave radar, obtain the driving path corresponding to at least one vehicle in the tunnel, and transmit the driving path to the road side sensing device B for fusion, thereby generating a cross-camera vehicle global tracking path including at least one vehicle in the tunnel. The vehicle global tracking path is sent to the vehicle side 604 for identification of the moving path of the target vehicle.

[0127] The vehicle end 604 is used to obtain the associated data from the roadside sensing device in the road end, determine the target identification information in the associated data set that matches the identification information of the target vehicle in the vehicle subset, and determine the moving path corresponding to the target identification information as the moving path of the target vehicle

[0128] Optionally, the realization of positioning of vehicles and the main vehicle in the tunnel depends on a complete set of road-side 602 and V2X communication systems between the road-side and vehicle-side 604. The road-side 602 uses the camera and the corresponding millimeter-wave radar to perform radar and visual target perception fusion analysis, and after obtaining the corresponding vehicle target, it can be associated with the high-precision map, so as to map the vehicle target point to obtain the longitude and latitude information in the world coordinate system, so as to obtain the moving path of at least one vehicle in the tunnel. At the same time, the road-side 602 can identify the identification information of the vehicle, and associate the identification information of the vehicle with the corresponding moving path to obtain the associated data, which can be sent to the vehicle-side 604.

[0129] Optionally, the vehicle end 604 may also include an onboard unit and an onboard intelligent device, and the associated data may be analyzed by the onboard unit, and the analyzed data obtained after the analysis may be sent to the onboard intelligent device of the vehicle. The onboard intelligent device may determine the target identification information that is the same as the identification information of the target vehicle from the analyzed data, and determine the moving path corresponding to the target identification information as the moving path of the target vehicle.

[0130] Optionally, the road end 602 further includes: at least one millimeter wave radar, at least one monitoring camera and at least one monitoring device. The millimeter wave radar and the monitoring camera can be used to obtain radar data and multi-frame image data at at least one position in the tunnel, and the moving path of the vehicle can be determined based on the radar data and the multi-frame image data. The monitoring camera can be a camera, a video camera or other device that can be used for shooting. The monitoring device can monitor the identification information of the vehicle, and can be a license plate recognition camera.

[0131] In this embodiment, identification information corresponding to at least one vehicle in a driving state in the tunnel is obtained through the road end 602, the identification information and the moving path of the corresponding vehicle are associated to obtain associated data, and the associated data is sent to the target vehicle in the vehicle subset, wherein at least one vehicle in a driving state constitutes a vehicle set, the identification information is used to determine the identity of the vehicle, and the associated data is used to characterize the mapping relationship between the identification information and the moving path of the corresponding vehicle; through the vehicle end 604, associated data from the roadside sensing device is obtained, target identification information matching the identification information of the target vehicle in the vehicle subset in the associated data set is determined, and the moving path corresponding to the target identification information is determined as the moving path of the target vehicle, thereby achieving the technical effect of improving the accuracy of vehicle path positioning in the tunnel, and solving the technical problem of low accuracy of vehicle path positioning in the tunnel.

[0132] Example 3

[0133] With the further development of vehicle-road collaboration, the further improvement of infrastructure, and the further improvement of intelligence, the intelligent identification and accurate positioning of people, vehicles, and objects on highways are of great significance. Accurately locating where there are people, vehicles, and objects on highways can improve the speed of discovering and handling highway accidents and effectively reduce secondary accidents. On the other hand, it can accurately depict the movement path of each vehicle, which can be used for subsequent vehicle driving behavior analysis, path analysis, and a lot of user information.

[0134] At present, the main vehicle assisted driving positioning technology uses GNSS, image sensors, radar and other methods to perceive vehicle position and environmental information. In the highway scenario, the open road of the highway can use GNSS, such as the Global Positioning System, BeiDou Navigation Satellite System (BDS), etc., and can also achieve relatively accurate target positioning, but the positioning signal of GNSS gradually disappears inside the tunnel, and it is impossible to accurately position the vehicle within the effective range, especially the lane-level positioning. Therefore, there are technical shortcomings and positioning blind spots in the whole process of accurately positioning the vehicle in the tunnel area under all-weather and all-terrain conditions, which will affect the safe driving of the vehicle to a certain extent. The gyroscope and accelerometer on the vehicle can achieve inertial positioning, but the accumulated error will gradually increase over time, resulting in the technical problem of low accuracy in positioning the vehicle path.

[0135] As an optional embodiment, a method for positioning vehicles in tunnels based on vision and millimeter-wave radar map features is proposed. The method is based on binocular stereo vision, millimeter-wave radar and high-precision maps, and finally combines the inertial measurement unit (IMU) information to achieve accurate positioning of the vehicle itself. However, this method is limited by the fusion accuracy of the static object perception feature point data set and the high-precision map data and the accuracy of the IMU position data, and is only effective for a single vehicle. Therefore, due to many limiting factors, there is still a technical problem of low accuracy in positioning the vehicle path.

[0136] As another optional embodiment, a vehicle tracking and positioning system and tracking and positioning method in a tunnel based on vehicle-road collaboration is also proposed. This method obtains the received signal strength indication (RSSI) sent by the vehicle-mounted unit on the roadside computing device, calculates the vehicle's positioning information, and sends the vehicle positioning information to the remote center for display. However, this method requires an algorithm for calculating positioning information based on RSSI strength and the RSSI signal itself, and more equipment (for example, 10*30 meters) needs to be deployed in the tunnel to receive the strength to calculate the positioning information. Each vehicle in use needs to be equipped with an RSSI vehicle-mounted device, which results in a limited scope of use of this method and cannot be widely used.

[0137] As another optional embodiment, a method for positioning a vehicle in a tunnel based on lane line mileage matching is proposed. This method uses a wheel speed meter and a lidar to obtain the mileage information of the vehicle in the tunnel, and matches it with the high-precision lane line to complete the precise positioning of the vehicle in a long-distance tunnel environment. However, this method calculates the vehicle position based on the vehicle mileage calculated by the wheel speed meter, which will produce cumulative errors, resulting in the problem of low accuracy in vehicle path positioning.

[0138] As another optional embodiment, a method for positioning a vehicle in a tunnel based on vehicle-road collaboration is proposed. The method determines the moving path of the vehicle based on a vehicle-mounted camera, a vehicle-mounted terminal, vehicle positioning mark points set in the tunnel, and a coordinate database stored in a tunnel monitoring platform. However, the method is a vehicle-mounted vehicle positioning method, which is limited to the positioning of the vehicle itself, and the accuracy is limited by the mark points marked in advance inside the tunnel. Therefore, there is still a problem of low accuracy in positioning the vehicle path.

[0139] As another optional embodiment, a method for positioning vehicles in tunnels based on ultra-wideband technology (Ultra Wide Band, UWB for short) is proposed. The method is based on a multi-point positioning monitoring algorithm (Time Difference Of Arrival, TDOA for short) of a multi-layer feedforward (BP for short) neural network trained by a cuckoo search algorithm to improve the positioning accuracy of ultra-wideband technology-based equipment. However, UWB devices are densely deployed and have a high unit price, and cannot be promoted on a large scale.

[0140] As another optional embodiment, a vehicle-road collaborative positioning method is proposed. This method uses the position of the first vehicle itself and the relative distance to locate the target object, which can improve the positioning accuracy. However, the positioning information of other vehicles or targets calculated from the perspective of this vehicle has a low degree of matching with the global road high-precision map. Therefore, there is still a technical problem of low accuracy in determining the vehicle path.

[0141] The above embodiments are mainly based on the accurate positioning of the vehicle. Some methods are unable to sense and locate vehicles other than the vehicle itself, and the positioning accuracy is questionable. At the same time, due to the strict equipment deployment conditions and the large number of requirements, it does not have the ability to be promoted on a large scale. Therefore, there is still a technical problem of low accuracy in positioning the vehicle path in the tunnel.

[0142] To solve the above problems, the embodiment of the present application proposes a method for positioning vehicles and the main vehicle in the tunnel from the perspective of vehicle-road collaboration. It can achieve full coverage of lane-level vehicle positioning functions for the problems of weak GNSS signals in the tunnel, inability to accurately locate vehicles, and inability to effectively identify the identity of the main vehicle. It also has the ability to distinguish between the main vehicle and other sensing vehicles, realize roadside perception, and empower the vehicle-side functions. In this embodiment, internal vision and millimeter-wave radar perception are fully covered in the tunnel, and the main vehicle path is generated based on the owner's identity associated with license plate recognition, and the roadside perception is fused and the data is transmitted to the on-board intelligent reference. The vehicle itself only needs to be equipped with an OBU device and an intelligent on-board device to achieve the lane-level positioning capability of the vehicle and the ability to perceive surrounding beyond-visual-range vehicles. In actual application, it can be embedded in the navigation APP, thereby achieving the technical effect of improving the accuracy of vehicle path positioning in the tunnel and solving the technical problem of low accuracy of vehicle path positioning in the tunnel.

[0143] The following is a further introduction to a method for positioning a vehicle and a main vehicle in a tunnel proposed in an embodiment of the present application.

[0144] In this embodiment, the positioning of vehicles and the main vehicle in the tunnel depends on a complete set of roadside sensing equipment and a V2X communication system between the roadside and the vehicle. Figure 7 is a schematic diagram of a vehicle and a main vehicle positioning framework in a tunnel according to an embodiment of the present application, such as Figure 7 As shown, the framework may include: a road end 701 and a vehicle end 702. The road end 701 may be deployed in the cloud.

[0145] Optionally, the road end 701 may include multiple roadside sensing devices (e.g., roadside sensing device 7-1, ..., roadside sensing device 7-n, roadside sensing device 703, etc.), multiple cameras, multiple millimeter-wave radars and multiple roadside units (e.g., RUS-701, ..., RUS-70n, etc.).

[0146] Optionally, the roadside sensing devices 7-1, ..., and roadside sensing devices 7-n can perform radar and visual target perception fusion analysis on the camera and the corresponding millimeter-wave radar, obtain the corresponding vehicle target, associate it with the high-precision map, and map the vehicle target point to obtain the longitude and latitude information in the world coordinate system to determine the movement path of the vehicle. Among them, a camera and a millimeter-wave radar can be installed in the same direction at a point, and the camera and the millimeter-wave radar can cover almost the same area.

[0147] Optionally, the vehicle end 702 may carry an on-board unit and an on-board intelligent device to obtain and analyze the data of the road end 701 .

[0148] It should be noted that any calibration between the image and the high-precision map before mapping, as well as the alignment of the millimeter-wave radar and the visual scene should be within the scope of protection of this application. No specific restrictions are made on the punctuation between the image and the high-precision map and the method of aligning the millimeter-wave radar with the visual scene.

[0149] In this embodiment, in order to obtain accurate positioning of vehicles in the tunnel, a full-coverage monitoring system is designed. A point is designed and deployed every 120 meters in the tunnel. A camera and a millimeter-wave radar are installed at each point. Each camera and millimeter-wave radar effectively cover at least 120 meters. A license plate recognition camera is installed every 20 points. In particular, near the tunnel entrance, considering the backlight / frontlight problem at the tunnel entrance, this embodiment proposes a method for deploying monitoring cameras at the tunnel entrance. Figure 8 is a schematic diagram of a tunnel entrance monitoring camera deployment according to an embodiment of the present application, such as Figure 8 As shown, two ordinary monitoring cameras and one license plate recognition camera can be installed within a range of 30 to 50 meters from the cave entrance (for example, at point B), wherein the ordinary monitoring camera can be installed one in each of the left and right directions, and the license plate recognition camera can be installed only one in the direction beyond the cave entrance, and an ordinary camera is installed in both directions within a range of 60 to 120 meters from point B (for example, at point A), and an ordinary monitoring camera is installed on the opposite side of point B (for example, point C), that is, within a range of 30 to 50 meters from the cave entrance.

[0150] Optionally, under the above-mentioned full coverage conditions, the image data in the video monitored by the ordinary camera and the radar data monitored by the millimeter-wave radar are obtained, and the fusion target detection, tracking, and positioning are performed based on the image data and the radar data to identify the movement path of the vehicle. The positioning accuracy in this method can reach the lane level.

[0151] Fig. 9 is a schematic diagram of image data and radar data fusion perception according to an embodiment of the present application, such as Fig. 9 As shown, the image data and radar data are aligned in time and space coordinate systems. The image features of the aligned image data are extracted, and the radar data is filtered and associated and multi-target tracked to obtain tracking results such as the speed and height of the tracked object. The tracking results can be projected into the image, the radar data of the tracking image can be extracted to obtain radar features, the radar features and image features can be pre-fused and monitored to obtain fused monitoring results, the fused monitoring results and tracking results can be post-fused to obtain post-fusion results, wherein the post-fusion results can be used to determine the type, speed, height and other information of the tracked object.

[0152] In this embodiment, since the GNSS signal inside the tunnel is weak or non-existent, it is impossible to ensure that the vehicle equipment equipped with the OBU can accurately locate the main vehicle. Therefore, on the basis of full coverage of vehicle perception and positioning in the tunnel, the license plate information can be used to effectively associate the roadside perception vehicle data with the vehicle equipped with the OBU. Among them, the vehicle equipped with the OBU needs to be able to enter the license plate information in advance.

[0153] Fig.10 is a schematic diagram of a main vehicle associated positioning system according to an embodiment of the present application, such as Fig.10 As shown, the license plate recognition camera 1001 is used to recognize the license plate of the passing vehicle. Under the premise of unified calibration in time and space, the license plate recognition result is integrated into the roadside sensing device 1002, and the roadside sensing device 1002 transmits the fused moving path to the roadside sensing device 1003. The result of the global vehicle tracking path of the roadside sensing device 1003 is sent to the roadside sensing device 1002. In the roadside sensing device 1002, the license plate recognition result is integrated with the global vehicle tracking path, and all vehicle paths can be broadcasted through the roadside unit. After receiving the data, the OBU will send the data to the on-board intelligent device 1004 after the data is parsed. The on-board intelligent device 1004 compares the pre-set license plate information with the license plate information in all vehicle target data. After matching, the path information of the main vehicle can be determined, so that the path can be continuously associated according to the target ID in the path.

[0154] In this embodiment, in addition to positioning the vehicle and the main vehicle in the tunnel based on video, radar, high-precision map, license plate, RSU and OBU, vehicle positioning can also be based on ultra-wideband communication, or other vehicle-side positioning methods that rely on roadside equipment. No specific restrictions are made here on the device for vehicle positioning. Vehicle positioning and methods for determining the vehicle position by license plate should be within the scope of protection of this application.

[0155] This embodiment, from the perspective of vehicle-road collaboration, proposes a method for positioning vehicles and the main vehicle in the tunnel to address the problems of weak GNSS signals in tunnels, inability to accurately position vehicles, and inability to effectively identify the identity of the main vehicle. Based on full coverage of internal vision and millimeter-wave radar in the tunnel, the vehicle's driving path is accurately identified. At the same time, the license plate is associated with the vehicle's driving path, so as to accurately identify the main vehicle's driving path based on the license plate. The embodiment of the present application can achieve a lane-level vehicle positioning function with full coverage, and has the ability to distinguish between the main vehicle and other sensing vehicles, realize roadside perception, and empower the vehicle-side function. The vehicle itself only needs to be equipped with an OBU device and an intelligent on-board device to achieve the lane-level positioning capability of the vehicle and the ability to perceive surrounding beyond-visual-range vehicles. In actual application, it can be embedded in the navigation software to assist in vehicle path planning and driving.

[0156] In another optional embodiment, Fig.11 The block diagram shows the use of the above Figure 1 The computer terminal 10 (or mobile device) is shown as an embodiment of the service grid. Fig.11 is a structural block diagram of a service grid according to an embodiment of the present application, such as Fig.11 As shown, the service grid 1100 is mainly used to facilitate secure and reliable communication between multiple microservices. Microservices refer to decomposing an application into multiple smaller services or instances, which are distributed and run on different clusters / machines.

[0157] like Fig.11 As shown, the microservice may include an application service instance A and an application service instance B, which form a functional application layer of the service grid 1100. In one embodiment, the application service instance A runs in a machine / workload container group 11014 (Pod) in the form of a container / process 1108, and the application service instance B runs in a machine / workload container group 11016 (Pod) in the form of a container / process 11010.

[0158] In one implementation, application service instance A may be a path query service, and application service instance B may be a path planning service.

[0159] like Fig.11 As shown, application service instance A and grid agent (sidecar) 1103 coexist in machine workload container group 11014, and application service instance B and grid agent 1105 coexist in machine workload container 11014. Grid agent 1103 and grid agent 1105 form the data plane layer (data plane) of service grid 1100. Among them, grid agent 1103 and grid agent 1105 run in the form of container / process 1104 and container / process 1106 respectively, and can receive request 11012 for commodity query service, and grid agent 1103 and application service instance A can communicate bidirectionally, and grid agent 1105 and application service instance B can communicate bidirectionally. In addition, grid agent 1103 and grid agent 1105 can also communicate bidirectionally.

[0160] In one implementation, the traffic of application service instance A is routed to a suitable destination through grid proxy 1103, and the network traffic of application service instance B is routed to a suitable destination through grid proxy 1105. It should be noted that the network traffic mentioned here includes but is not limited to Hyper Text Transfer Protocol (HTTP), Representational State Transfer (REST), high-performance, general open source framework (google-Remote Procedure Call, g-RPC), open source in-memory data structure storage system (Redis), etc.

[0161] In one embodiment, the function of extending the data plane layer can be implemented by writing a custom filter for the proxy (Envoy) in the service grid 1100. The service grid proxy configuration can be to enable the service grid to correctly proxy service traffic and achieve service intercommunication and service governance. The grid proxy 1103 and the grid proxy 1105 can be configured to perform at least one of the following functions: service discovery, health checking, routing, load balancing, authentication and authorization, and observability.

[0162] like Fig.11 As shown, the service grid 1100 also includes a control plane layer. The control plane layer can be a group of services running in a dedicated namespace, and these services are hosted by a hosting control plane component 1101 in a machine / workload container group (machine / Pod) 1102. Fig.11 As shown, the managed control plane component 1101 performs two-way communication with the grid agent 1103 and the grid agent 1105. The managed control plane component 1101 is configured to perform some control management functions. For example, the managed control plane component 1101 receives telemetry data transmitted by the grid agent 1103 and the grid agent 1105, and can further aggregate the telemetry data. For these services, the managed control plane component 1101 can also provide a user-oriented application programming interface (Application Programming Interface, API) to more easily manipulate network behavior and provide configuration data to the grid agent 1103 and the grid agent 1105.

[0163] Optionally, you can use programming (e.g., C / C++ programming), combined with computer application framework (e.g., NVIDIA Cuda) programming, and software libraries (e.g., cuDNN, BLAS and other related software development), to combine the two development environments of the central processing unit and the graphics processing unit (Graphics Processing Unit, referred to as GPU) to achieve standard results in terms of speed and performance. In addition, this application relies on deep learning frameworks (e.g., can include caffe, pytorch, Tensorflow, etc.), but the frameworks can be replaced with each other.

[0164] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, stored data, displayed data, etc.) involved in this application, such as weather forecast results and other data, are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of relevant data must comply with the relevant laws, regulations and standards of relevant countries and regions, and provide corresponding operation entrances for users to choose to authorize or refuse.

[0165] It should be noted that, for the aforementioned method embodiments, for the sake of simplicity, they are all expressed as a series of action combinations, but those skilled in the art should be aware that the present application is not limited by the described order of actions, because according to the present application, certain steps can be performed in other orders or simultaneously. Secondly, those skilled in the art should also be aware that the embodiments described in the specification are all preferred embodiments, and the actions and modules involved are not necessarily required by the present application.

[0166] Through the description of the above implementation methods, those skilled in the art can clearly understand that the method according to the above embodiment can be implemented by means of software plus a necessary general hardware platform, and of course, it can also be implemented by hardware. Based on this understanding, the technical solution of the present application, or the part that contributes to the prior art, can be embodied in the form of a software product, which is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk), and includes a number of instructions for a terminal device (which can be a mobile phone, computer, server, or network device, etc.) to execute the methods of each embodiment of the present application.

[0167] Example 4

[0168] According to an embodiment of the present application, there is also provided a method for implementing the above Figure 3 The method for determining a vehicle path in a tunnel and the device for determining a vehicle path in a tunnel are shown.

[0169] Fig.12is a schematic diagram of a device for determining a vehicle path in a tunnel according to an embodiment of the present application, such as Fig.12 As shown, the device 1200 for determining a vehicle path in a tunnel may include: an acquisition unit 1202 , an association unit 1204 , and a sending unit 1206 .

[0170] The first acquisition unit 1202 is used to acquire identification information corresponding to at least one vehicle in a driving state in the tunnel, wherein the at least one vehicle in a driving state constitutes a vehicle set, and the identification information is used to determine the identity of the vehicle.

[0171] The associating unit 1204 is used to associate the identification information with the moving path of the corresponding vehicle to obtain associated data, wherein the associated data is used to represent the mapping relationship between the identification information and the moving path of the corresponding vehicle.

[0172] The sending unit 1206 is used to send the associated data to the target vehicle in the vehicle subset, wherein the associated data is used to enable the target vehicle to determine a moving path corresponding to the identification information of the target vehicle, and the vehicle set includes the vehicle subset.

[0173] It should be noted that the acquisition unit 1202, the association unit 1204 and the issuing unit 1206 correspond to steps S302 to S306 in Example 1, and the three units and the corresponding steps implement the same examples and application scenarios, but are not limited to the contents disclosed in the above-mentioned Example 1. It should be noted that the above-mentioned units can be hardware components or software components stored in a memory (e.g., memory 1204) and processed by one or more processors (e.g., processors 102a, 102b..., 102n), and the above-mentioned units can also be run in the computer terminal 10 provided in Example 1 as part of the device.

[0174] According to an embodiment of the present application, another method for implementing the above Figure 4 The method for determining a vehicle path in a tunnel and the device for determining a vehicle path in a tunnel are shown.

[0175] Fig.13 is a schematic diagram of another device for determining a vehicle path in a tunnel according to an embodiment of the present application, such as Fig.13 As shown, the device 1300 for determining a vehicle path in a tunnel may include: a second acquiring unit 1302 , a first determining unit 1304 , and a second determining unit 1306 .

[0176] The second acquisition unit 1302 is used to acquire association data obtained by associating the identification information with the moving path of the corresponding vehicle, wherein the identification information corresponds to at least one vehicle in a driving state in the tunnel, the at least one vehicle in a driving state constitutes a vehicle set, the identification information is used to determine the identity of the vehicle, and the association data is used to characterize the mapping relationship between the identification information and the moving path of the corresponding vehicle.

[0177] The first determining unit 1304 is configured to determine target identification information in the associated data that matches identification information of a target vehicle in a vehicle subset, wherein the vehicle set includes the vehicle subset.

[0178] The second determining unit 1306 is used to determine the moving path corresponding to the target identification information as the moving path of the target vehicle.

[0179] It should be noted that the second acquisition unit 1302, the first determination unit 1304, and the second determination unit 1306 correspond to steps S402 to S406 in Embodiment 1, and the three units and the corresponding steps implement the same examples and application scenarios, but are not limited to the contents disclosed in Embodiment 1. It should be noted that the above units may be hardware components or software components stored in a memory (e.g., memory 104) and processed by one or more processors (e.g., processors 102a, 102b..., 102n), and the above units may also be part of a device and run in the computer terminal 10 provided in Embodiment 1.

[0180] According to an embodiment of the present application, another method for implementing the above Figure 5 The method for determining a vehicle path in a tunnel and the device for determining a vehicle path in a tunnel are shown.

[0181] Fig.14 is a schematic diagram of another device for determining a vehicle path in a tunnel according to an embodiment of the present application, such as Fig.14 As shown, the device 1400 for determining a vehicle path in a tunnel may include: a third acquiring unit 1402 and a third determining unit 1404 .

[0182] The third acquisition unit 1402 is used to obtain associated data from the roadside sensing device, which is obtained by associating the identification information with the moving path of the corresponding vehicle, wherein the identification information corresponds to at least one vehicle in a driving state in the tunnel, and the at least one vehicle in a driving state constitutes a vehicle set. The identification information is used to determine the identity of the vehicle, and the associated data is used to characterize the mapping relationship between the identification information and the moving path of the corresponding vehicle.

[0183] The third determining unit 1404 is used to determine the target identification information in the associated data that matches the identification information of the target vehicle in the vehicle subset.

[0184] The fourth determining unit 1406 is configured to determine the moving path corresponding to the target identification information as the moving path of the target vehicle, wherein the vehicle set includes a vehicle subset.

[0185] The prediction unit 1408 is used to predict the travel path of the target vehicle at a future time based on the moving path of the target vehicle.

[0186] It should be noted that the third acquisition unit 1402 and the third determination unit 1404 correspond to steps S502 to S504 in Embodiment 1, and the examples and application scenarios implemented by the two units and the corresponding steps are the same, but are not limited to the contents disclosed in Embodiment 1. It should be noted that the above-mentioned units may be hardware components or software components stored in a memory (e.g., memory 104) and processed by one or more processors (e.g., processors 102a, 102b..., 102n), and the above-mentioned units may also be part of the device and may be run in the computer terminal 10 provided in Embodiment 1.

[0187] In the above-mentioned device, the identification information corresponding to the vehicle is obtained, the identification information is associated with the vehicle's moving path, and the moving path of the target vehicle is determined based on the associated data, thereby achieving the technical effect of improving the accuracy of vehicle path positioning in the tunnel and solving the technical problem of low accuracy of vehicle path positioning in the tunnel.

[0188] Example 5

[0189] The embodiment of the present application may provide a computer terminal, which may be any computer terminal device in a computer terminal group. Optionally, in this embodiment, the computer terminal may also be replaced by a terminal device such as a mobile terminal.

[0190] Optionally, in this embodiment, the computer terminal may be located in at least one network device among a plurality of network devices of the computer network.

[0191] In this embodiment, the above-mentioned computer terminal can execute the program code of the following steps in the method for determining the vehicle path in the tunnel: obtaining the identification information corresponding to at least one vehicle in a driving state in the tunnel, wherein the at least one vehicle in a driving state constitutes a vehicle set, and the identification information is used to determine the identity of the vehicle; associating the identification information with the moving path of the corresponding vehicle to obtain associated data, wherein the associated data is used to characterize the mapping relationship between the identification information and the moving path of the corresponding vehicle; sending the associated data to the target vehicle in the vehicle subset, wherein the associated data is used to enable the target vehicle to determine the moving path corresponding to the identification information of the target vehicle, wherein the vehicle set includes the vehicle subset.

[0192] Optionally, Fig.15 is a structural block diagram of a computer terminal according to an embodiment of the present application. Fig.15 As shown, the computer terminal A may include: one or more (only one is shown in the figure) processors 1502 , a memory 1504 and a transmission device 1506 .

[0193] Among them, the memory can be used to store software programs and modules, such as the program instructions / modules corresponding to the method and device for determining the vehicle path in the tunnel in the embodiment of the present application. The processor executes various functional applications and data processing by running the software programs and modules stored in the memory, that is, the above-mentioned method for determining the vehicle path in the tunnel is realized. The memory may include a high-speed random access memory, and may also include a non-volatile memory, such as one or more magnetic storage devices, flash memory, or other non-volatile solid-state memory. In some examples, the memory may further include a memory remotely arranged relative to the processor, and these remote memories can be connected to the computer terminal A via a network. Examples of the above-mentioned network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

[0194] The processor can call the information and application stored in the memory through the transmission device to perform the following steps: obtain the identification information corresponding to at least one vehicle in a driving state in the tunnel, wherein the at least one vehicle in a driving state constitutes a vehicle set, and the identification information is used to determine the identity of the vehicle; associate the identification information with the moving path of the corresponding vehicle to obtain associated data, wherein the associated data is used to characterize the mapping relationship between the identification information and the moving path of the corresponding vehicle; send the associated data to the target vehicle in the vehicle subset, wherein the associated data is used to enable the target vehicle to determine the moving path corresponding to the identification information of the target vehicle, wherein the vehicle set includes the vehicle subset.

[0195] Optionally, the processor may also execute the program code of the following steps: determining the monitoring time when the identification information is detected and the monitoring position where the identification information is located at the monitoring time; in response to the vehicle's moving path being located at the monitoring position at the monitoring time, associating the identification information and the moving path to obtain the associated data.

[0196] Optionally, the processor may also execute program codes of the following steps: obtaining radar data and multi-frame image data at at least one position in the tunnel, wherein the image data and the radar data are data obtained by a millimeter-wave radar and a monitoring camera deployed at the same position, and the image data is used to characterize the driving environment of the vehicle; determining image features corresponding to the multi-frame image data and radar features corresponding to the radar data; fusing the image features and the radar features to obtain fused data, wherein the fused data includes the position points of the vehicle at different monitoring times; determining the moving path of the vehicle based on the mapping relationship between the position points in the fused data and the real map.

[0197] Optionally, the processor may also execute the program code of the following steps: controlling the roadside unit to send the associated data to the on-board unit of the target vehicle.

[0198] Optionally, the processor may also execute program code for the following steps: obtaining license plate information corresponding to at least one vehicle identified by a monitoring device located at at least one position in the tunnel, wherein the at least one position includes a position within a target range from a tunnel exit of the tunnel, and the monitoring device is used to identify the license plate information of the vehicle.

[0199] Optionally, the processor may also execute program code for the following steps: obtaining multiple frames of image data at a position within a target range from a tunnel exit and identification information recognized by a monitoring device, and obtaining multiple frames of image data on the opposite side of the position within a target range from a tunnel exit.

[0200] As an optional example, the processor can call the information and application stored in the memory through the transmission device to perform the following steps: obtain the associated data obtained by associating the identification information with the moving path of the corresponding vehicle, wherein the identification information corresponds to at least one vehicle in a driving state in the tunnel, and the at least one vehicle in a driving state constitutes a vehicle set, the identification information is used to determine the identity of the vehicle, and the associated data is used to characterize the mapping relationship between the identification information and the moving path of the corresponding vehicle; determine the target identification information in the associated data that matches the identification information of the target vehicle in the vehicle subset, wherein the vehicle set includes the vehicle subset; and determine the moving path corresponding to the target identification information as the moving path of the target vehicle.

[0201] Optionally, the processor may also execute the following program code: obtaining identification information of the target vehicle from an on-board smart device at the vehicle end.

[0202] As another optional example, the processor may call the information and application stored in the memory through the transmission device to perform the following steps: obtaining association data from the roadside sensing device, and associating the identification information with the moving path of the corresponding vehicle, wherein the identification information corresponds to at least one vehicle in a driving state in the tunnel, and the at least one vehicle in a driving state constitutes a vehicle set, the identification information is used to determine the identity of the vehicle, and the association data is used to characterize the mapping relationship between the identification information and the moving path of the corresponding vehicle; determining the target identification information in the association data that matches the identification information of the target vehicle in the vehicle subset, wherein the vehicle set includes the vehicle subset; determining the moving path corresponding to the target identification information as the moving path of the target vehicle; and predicting the driving path of the target vehicle at a future moment based on the moving path of the target vehicle.

[0203] By adopting the embodiment of the present application, the identification information corresponding to the vehicle is obtained, the identification information is associated with the vehicle's moving path, and the moving path of the target vehicle is determined based on the associated data, thereby achieving the technical effect of improving the accuracy of vehicle path positioning in the tunnel, and solving the technical problem of low accuracy of vehicle path positioning in the tunnel.

[0204] It can be understood by those skilled in the art that Fig.15 The structure shown is for illustration only, and the computer terminal A may also be a smart phone (such as an Android phone, an iOS phone, etc.), a tablet computer, a PDA, a mobile Internet device (Mobile Internet Devices, MID), a PAD, or other terminal devices. Fig.15 It does not limit the structure of the above-mentioned computer terminal A. For example, the computer terminal A may also include Fig.15 More or fewer components (such as network interfaces, display devices, etc.) shown in, or having Fig.15 Different configurations shown.

[0205] A person of ordinary skill in the art can understand that all or part of the steps in the various methods of the above embodiments can be completed by instructing the hardware related to the terminal device through a program, and the program can be stored in a computer-readable storage medium, and the storage medium may include: a flash drive, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk, etc.

[0206] Example 6

[0207] The embodiment of the present application further provides a computer-readable storage medium. Optionally, in this embodiment, the computer-readable storage medium may be used to store the program code executed by the method for determining a vehicle path in a tunnel provided in the first embodiment.

[0208] Optionally, in this embodiment, the computer-readable storage medium may be located in any one of the computer terminals in a computer terminal group in a computer network, or in any one of the mobile terminals in a mobile terminal group.

[0209] Optionally, in this embodiment, the computer-readable storage medium is configured to store program codes for executing the information stored in the memory and the application program executed by the processor through the transmission device.

[0210] In an embodiment of the present application, identification information corresponding to the vehicle is obtained, the identification information is associated with the vehicle's moving path, and the moving path of the target vehicle is determined based on the associated data, thereby achieving the technical effect of improving the accuracy of vehicle path positioning in the tunnel and solving the technical problem of low accuracy of vehicle path positioning in the tunnel.

[0211] Example 7

[0212] An embodiment of the present application may provide an electronic device, which may include a memory and a processor.

[0213] Fig.16 1 is a block diagram of an electronic device for a method for determining a vehicle path in a tunnel according to an embodiment of the present application. 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 may also represent various forms of mobile devices, such as personal digital processing, cellular phones, smart phones, wearable devices, and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely examples and are not intended to limit the implementation of the present application described and / or claimed herein.

[0214] like Fig.16 As shown, the device 1600 includes a computing unit 1601, which can perform various appropriate actions and processes according to a computer program stored in a read-only memory (ROM) 1602 or a computer program loaded from a storage unit 1608 to a random access memory (RAM) 1603. In RAM 1603, various programs and data required for the operation of the device 1600 can also be stored. The computing unit 1601, ROM 1602, and RAM 1603 are connected to each other via a bus 1604. An input / output (I / O) interface 1605 is also connected to the bus 1604.

[0215] A number of components in the device 1600 are connected to the I / O interface 1605, including: an input unit 1606, such as a keyboard, a mouse, etc.; an output unit 1604, such as various types of displays, speakers, etc.; a storage unit 1608, such as a disk, an optical disk, etc.; and a communication unit 16010, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 16010 allows the device 1600 to exchange information / data with other devices through a computer network such as the Internet and / or various telecommunication networks.

[0216] The computing unit 1601 may be a variety of general and / or special processing components with processing and computing capabilities. Some examples of the computing unit 1601 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various dedicated artificial intelligence (AI) computing chips, various computing units running machine learning model algorithms, a digital signal processor (DSP), and any appropriate processor, controller, microcontroller, etc. The computing unit 1601 performs the various methods and processes described above, such as a method for determining a vehicle path in a tunnel. For example, in some embodiments, the method for determining a vehicle path in a tunnel may be implemented as a computer software program, which is tangibly contained in a machine-readable medium, such as a storage unit 1608. In some embodiments, part or all of the computer program may be loaded and / or installed on the device 1600 via the ROM 1602 and / or the communication unit 16010. When the computer program is loaded into RAM 1603 and executed by the computing unit 1601, one or more steps of the method for determining a vehicle path in a tunnel described above may be performed. Alternatively, in other embodiments, the computing unit 1601 may be configured to execute the method for determining a vehicle path in a tunnel in any other appropriate manner (e.g., by means of firmware).

[0217] Various embodiments of the systems and techniques described above herein may be implemented in digital electronic circuit systems, integrated circuit systems, field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard parts (ASSPs), system on chip systems (SOCs), complex programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various embodiments may include: being implemented 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 programmable processor that can receive data and instructions from a storage system, at least one input device, and at least one output device, and transmit data and instructions to the storage system, the at least one input device, and the at least one output device.

[0218] The program code for implementing the method of the present application can be written in any combination of one or more programming languages. These program codes can be provided to a processor or controller of a general-purpose computer, a special-purpose computer, or other programmable data processing device, so that the program code, when executed by the processor or controller, implements the functions / operations specified in the flow chart and / or block diagram. The program code can be executed entirely on the machine, partially on the machine, partially on the machine and partially on a remote machine as a stand-alone software package, or entirely on a remote machine or server.

[0219] In the context of the present application, a machine-readable medium may be a tangible medium that may contain or store a program for use by or in conjunction with an instruction execution system, device, or equipment. A machine-readable medium may be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium may include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, devices, or equipment, or any suitable combination of the foregoing. A more specific example of a machine-readable storage medium may include an electrical connection based on one or more lines, a portable computer disk, a hard disk, a random access memory, a read-only memory, an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0220] To provide interaction with a user, the systems and techniques described herein may be implemented on a computer having: a display device (e.g., a cathode ray tube or liquid crystal display, monitor) for displaying information to the user; and a keyboard and pointing device (e.g., a mouse or path ball) through which the user can provide input to the computer. Other types of devices may also be used to provide interaction with the user; for example, the feedback provided to the user may be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user may be received in any form (including acoustic input, voice input, or tactile input).

[0221] The systems and techniques described herein may be implemented in a computing system that includes back-end components (e.g., as a data server), or a computing system that includes middleware components (e.g., an application server), or a computing system that includes front-end components (e.g., a user computer with a graphical user interface or a web browser through which a user can interact with implementations of the systems and techniques described herein), or a computing system that includes any combination of such back-end components, middleware components, or front-end components. The components of the system may be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: local area networks, wide area networks, and the Internet.

[0222] A computer system may include a client and a server. The client and the server are generally remote from each other and usually interact through a communication network. The relationship of client and server is generated by computer programs running on respective computers and having a client-server relationship with each other. The server may be a cloud server, a server of a distributed system, or a server combined with a blockchain.

[0223] It should be noted that the serial numbers of the above-mentioned embodiments of the present application are only for description and do not represent the advantages or disadvantages of the embodiments.

[0224] In the above embodiments of the present application, the description of each embodiment has its own emphasis. For parts that are not described in detail in a certain embodiment, please refer to the relevant description of other embodiments.

[0225] In the several embodiments provided in this application, it should be understood that the disclosed technical content can be implemented in other ways. Among them, the device embodiments described above are only schematic, for example, the division of units is only a logical function division, and there may be other division methods in actual implementation, for example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of units or modules, which can be electrical or other forms.

[0226] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0227] In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0228] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application, or the part that contributes to the prior art, or all or part of the technical solution can be embodied in the form of a software product, which is stored in a storage medium and includes several instructions for a computer device (which can be a personal computer, server or network device, etc.) to perform all or part of the steps of the various embodiments of the present application. The aforementioned storage medium includes: various media that can store program codes, such as USB flash drives, read-only memory random access memories, mobile hard disks, magnetic disks or optical disks.

[0229] The above are only preferred implementations of the present application. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principles of the present application. These improvements and modifications should also be regarded as the scope of protection of the present application.

Claims

1. A method for determining a vehicle path in a tunnel, characterized in that: include: Acquire identification information corresponding to at least one vehicle in a driving state in a tunnel, wherein the at least one vehicle in a driving state constitutes a vehicle set, and the identification information is used to determine the identity of the vehicle; Associating the identification information with the movement path of the corresponding vehicle to obtain association data, wherein the association data is used to characterize a mapping relationship between the identification information and the movement path of the corresponding vehicle; The associated data is sent to a target vehicle in a vehicle subset, wherein the associated data is used to enable the target vehicle to determine the moving path corresponding to the identification information of the target vehicle, and the vehicle set includes the vehicle subset.

2. The method according to claim 1, characterized in that Associating the identification information with the movement path of the corresponding vehicle to obtain the associated data includes: Determine a monitoring time at which the identification information is monitored and a monitoring position at which the identification information is located at the monitoring time; In response to the movement path of the vehicle being located at the monitoring position at the monitoring time, the identification information and the movement path are associated to obtain the associated data.

3. The method according to claim 2, characterized in that The method further comprises: Acquire radar data and multiple frames of image data at at least one position in the tunnel, wherein the image data and the radar data are data acquired by a millimeter-wave radar and a monitoring camera deployed at the same position, and the image data is used to characterize the driving environment of the vehicle; Determining image features corresponding to the multiple frames of image data and radar features corresponding to the radar data; The image feature and the radar feature are fused to obtain fused data, wherein the fused data includes the position points of the vehicle at different monitoring times; The moving path of the vehicle is determined based on a mapping relationship between the location points in the fused data and a real map.

4. The method according to claim 1, characterized in that: Sending the associated data to the target vehicle in the vehicle subset includes: The roadside unit is controlled to send the associated data to the on-board unit of the target vehicle.

5. The method according to claim 1, characterized in that Acquiring identification information corresponding to the at least one vehicle in a driving state in the tunnel, including: Acquire license plate information corresponding to the at least one vehicle identified by monitoring equipment at at least one position in the tunnel, wherein the at least one position includes a position within a target range from a tunnel exit of the tunnel.

6. The method according to claim 1, characterized in that Acquiring identification information corresponding to the at least one vehicle in a driving state in the tunnel, including: Acquire multiple frames of image data at a position within the target range from the tunnel exit and the identification information recognized by the monitoring device, and acquire multiple frames of image data on the opposite side of the position within the target range from the tunnel exit.

7. The method according to claim 1, characterized in that The associated data is used to enable the target vehicle to determine target identification information that is identical to the identification information of the target vehicle, and to determine the moving path associated with the target identification information as the moving path of the target vehicle.

8. A method for determining a vehicle path in a tunnel, characterized in that: include: Acquire association data obtained by associating identification information with a moving path of a corresponding vehicle, wherein the identification information corresponds to at least one vehicle in a moving state in the tunnel, the at least one vehicle in a moving state constitutes a vehicle set, the identification information is used to determine the identity of the vehicle, and the association data is used to characterize a mapping relationship between the identification information and the moving path of the corresponding vehicle; Determining target identification information in the associated data that matches identification information of a target vehicle in a vehicle subset, wherein the vehicle set includes the vehicle subset; The moving path corresponding to the target identification information is determined as the moving path of the target vehicle.

9. The method according to claim 8, characterized in that Determining the target identification information in the associated data set that matches the identification information of the target vehicle in the vehicle subset includes: The identification information in the associated data that is identical to the identification information of the target vehicle is determined as the target identification information.

10. The method according to claim 9, characterized in that The method further comprises: The identification information of the target vehicle is obtained from the on-board intelligent device of the vehicle.

11. A method for determining a vehicle path in a tunnel, characterized in that: include: Acquire, from a roadside sensing device, association data obtained by associating identification information with a moving path of a corresponding vehicle, wherein the identification information corresponds to at least one vehicle in a driving state in the tunnel, the at least one vehicle in a driving state constitutes a vehicle set, the identification information is used to determine the identity of the vehicle, and the association data is used to characterize a mapping relationship between the identification information and the moving path of the corresponding vehicle; Determining target identification information in the associated data that matches identification information of a target vehicle in a vehicle subset, wherein the vehicle set includes the vehicle subset; Determine the moving path corresponding to the target identification information as the moving path of the target vehicle; The driving path of the target vehicle at a future time is predicted based on the moving path of the target vehicle.

12. A system for determining a vehicle path in a tunnel, characterized in that: include: A road end, used to obtain identification information corresponding to at least one vehicle in a driving state in the tunnel, associate the identification information with a moving path of the corresponding vehicle, obtain associated data, and send the associated data to a target vehicle in a vehicle subset, wherein the at least one vehicle in a driving state constitutes a vehicle set, the identification information is used to determine the identity of the vehicle, and the associated data is used to characterize a mapping relationship between the identification information and the moving path of the corresponding vehicle; The vehicle end is used to obtain the associated data from the roadside perception device in the road end, determine the target identification information in the associated data set that matches the identification information of the target vehicle in the vehicle subset, and determine the moving path corresponding to the target identification information as the moving path of the target vehicle, wherein the vehicle set includes the vehicle subset.

13. The system according to claim 12, characterized in that The vehicle end also includes: The vehicle-mounted unit is used to analyze the associated data and send the analyzed data to the vehicle-mounted intelligent device of the vehicle; The vehicle-mounted intelligent device is used to determine the target identification information in the associated data that is the same as the identification information of the target vehicle from the analysis data, and determine the moving path corresponding to the target identification information as the moving path of the target vehicle.

14. The system according to claim 12, characterized in that The road end also includes: At least one millimeter wave radar and at least one monitoring camera, used to obtain radar data and multiple frames of image data at at least one position in the tunnel, wherein the radar data and the multiple frames of image data are used to determine the moving path of the vehicle; At least one monitoring device is used to monitor the identification information of the vehicle.

15. An electronic device, characterized in that: include: Memory and processor; The memory is used to store computer-executable instructions, and the processor is used to execute the computer-executable instructions. When the computer-executable instructions are executed by the processor, the steps of the method described in any one of claims 1 to 11 are implemented.

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