RSU antenna switch control method, device, computer equipment and storage medium

Abstract

Embodiments of the present invention disclose a method, apparatus, computer device, and storage medium for controlling the switching of an RSU antenna. The method includes: setting a detection area; employing an artificial intelligence algorithm to detect and track vehicles and obstacles within the detection area to obtain target information; and controlling the switching of the RSU antenna within the detection area based on the target information to wake up or shut down the OBU within the detection area. Implementing the method of the embodiments of the present invention allows for reasonable control of the RSU antenna's switching, reducing the RSU's power consumption and the number of OBU wake-ups, thereby extending the OBU's operating time and saving energy.

Description

Technical Field

[0001] The present invention relates to an RSU antenna, and more specifically to an RSU antenna switch control method, device, computer equipment, and storage medium. Background Art

[0002] With rising living standards and increasing travel demand, my country's vehicle ownership continues to climb. By September 2021, the national motor vehicle ownership reached 390 million, of which 297 million were cars. Traffic congestion has become a pressing challenge in urban management. The Ministry of Transport, in collaboration with various ministries and commissions, is actively promoting ETC (Electronic Toll Collection), aiming to achieve ETC usage for over 90% of vehicles entering expressways by the end of 2019. Data shows that as of July 2021, there were over 26,000 gantries on China's expressways, with a cumulative total of 226 million ETC users. Furthermore, urban roads are also actively exploring the expansion of ETC applications. Currently, the OBU (On-Board Unit), as the on-board unit of ETC, receives timely traffic information, facilitating driver decision-making and enabling timely obstacle avoidance. Ultimately, this ensures the proper diversion of traffic, improves traffic flow, and reduces the occurrence of traffic accidents. Currently, OBU needs to be powered by a battery. If it is in the awake state for a long time, it will cause unnecessary waste of electricity, which will greatly reduce the effective use times of the OBU and shorten the use time of the OBU. How to reasonably switch the RSU (Road Side Unit) is of great significance to the effective use of OBU, the expansion of ETC applications, and energy conservation and emission reduction. The existing method of controlling the switch of the RSU antenna cannot reduce the power consumption of the RSU itself; nor can it reduce the number of times the OBU is awakened.

[0003] Therefore, it is necessary to design a new method to reasonably control the switch of the RSU antenna, reduce the power consumption of the RSU itself, and reduce the number of times the OBU is woken up. Summary of the Invention

[0004] The purpose of the present invention is to overcome the defects of the prior art and provide an RSU antenna switch control method, device, computer equipment and storage medium.

[0005] To achieve the above objectives, the present invention adopts the following technical solution: an RSU antenna switch control method, comprising:

[0006] Set the area to be detected;

[0007] Using artificial intelligence algorithms to detect and track vehicles and obstacles in the area to be detected to obtain target information;

[0008] The RSU antenna in the area to be detected is switched on or off according to the target information to wake up or shut down the OBU in the area to be detected.

[0009] A further technical solution is as follows: setting the area to be detected includes:

[0010] The vehicle detection area is set according to the RSU transaction area of ​​a single gantry or in combination with the lane to obtain the area to be detected.

[0011] A further technical solution is: using an artificial intelligence algorithm to detect and track vehicles and obstacles in the area to be detected to obtain target information, including:

[0012] Using artificial intelligence algorithms to match vehicles and obstacles in the area to be detected with existing tracking targets to obtain matching results;

[0013] Determine whether the matching result is a successful match;

[0014] If the matching result is a successful match, the target ID of the successful match is determined as the target information;

[0015] If the matching result is not a successful match, a target ID is added to obtain target information.

[0016] A further technical solution is: using an artificial intelligence algorithm to match vehicles and obstacles in the area to be detected with existing tracking targets to obtain a matching result, including:

[0017] Matching the vehicles and obstacles in the detection area with the existing tracking targets using a target matching algorithm based on speed and heading angle to obtain a matching result;

[0018] Alternatively, the vehicles and obstacles in the to-be-detected area are matched with existing tracking targets based on an image or point cloud feature matching algorithm to obtain a matching result.

[0019] A further technical solution is: before using an artificial intelligence algorithm to match the vehicles and obstacles in the detection area with the existing tracking targets to obtain a matching result, the method further includes:

[0020] Obtaining surveillance video within the area to be detected;

[0021] Decoding the surveillance video to obtain a decoding result;

[0022] Target detection is performed on the decoding results based on a deep learning algorithm to obtain all targets in the area to be detected.

[0023] A further technical solution is: the switching control of the RSU antenna in the area to be detected is performed according to the target information to wake up or shut down the OBU in the area to be detected, including:

[0024] Set the switch state of the RSU antenna in the area to be detected to off;

[0025] Determine whether the target ID in the target information already exists;

[0026] If the target ID in the target information already exists, then the time when the target ID was last detected is stored and set;

[0027] Delete the target ID whose last detected time exceeds the set time;

[0028] Determine whether the switch state of the RSU antenna in the area to be detected is on;

[0029] If the switch state of the RSU antenna in the area to be detected is on, turning on the RSU antenna to wake up the OBU in the area to be detected;

[0030] If the switch state of the RSU antenna in the area to be detected is not on, the RSU antenna is turned off to turn off the OBU in the area to be detected.

[0031] A further technical solution thereof is: after determining whether the target information contains a target ID, the method further includes:

[0032] If the target ID in the target information does not already exist, the switch state of the RSU antenna in the area to be detected is set to be on, and the storage and setting of the time when the target ID was last detected are performed.

[0033] The present invention also provides an RSU antenna switch control device, comprising:

[0034] An area setting unit, used to set an area to be detected;

[0035] A target detection unit, configured to detect and track vehicles and obstacles in the area to be detected using an artificial intelligence algorithm to obtain target information;

[0036] A switch control unit is used to perform switch control on the RSU antenna in the area to be detected according to the target information, so as to wake up or shut down the OBU in the area to be detected.

[0037] The present invention further provides a computer device, comprising a memory and a processor, wherein a computer program is stored in the memory, and the processor implements the above method when executing the computer program.

[0038] The present invention also provides a storage medium, wherein the storage medium stores a computer program, and the computer program implements the above method when executed by a processor.

[0039] Compared with the prior art, the present invention has the following beneficial effects: the present invention sets a vehicle detection area, adopts an artificial intelligence algorithm to perform target detection and tracking of vehicles and obstacles in the detection area to obtain target information, and performs on-off control of an RSU antenna in the detection area according to the target information to wake up or shut down an OBU in the detection area, thereby realizing reasonable control of the on-off of the RSU antenna, reducing the power consumption of the RSU itself, reducing the number of times the OBU is woken up, extending the use time of the OBU, and saving energy consumption.

[0040] The present invention will be further described below with reference to the accompanying drawings and specific embodiments. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0042] Figure 1 A schematic diagram of an application scenario of the RSU antenna switch control method provided by an embodiment of the present invention;

[0043] Figure 2 A schematic diagram of a flow chart of an RSU antenna switch control method provided in an embodiment of the present invention;

[0044] Figure 3 A schematic diagram of a sub-flow diagram of the RSU antenna switch control method provided by an embodiment of the present invention;

[0045] Figure 4 A schematic diagram of a sub-flow diagram of an RSU antenna switch control method provided by another embodiment of the present invention;

[0046] Figure 5 A schematic diagram of a sub-flow diagram of the RSU antenna switch control method provided by an embodiment of the present invention;

[0047] Figure 6 A schematic block diagram of an RSU antenna switch control device provided in an embodiment of the present invention;

[0048] Figure 7 A schematic block diagram of a target detection unit of an RSU antenna switch control device provided in an embodiment of the present invention;

[0049] Figure 8A schematic block diagram of a target detection unit of an RSU antenna switch control device provided in another embodiment of the present invention;

[0050] Figure 9 A schematic block diagram of a switch control unit of an RSU antenna switch control device provided in an embodiment of the present invention;

[0051] Figure 10 A schematic block diagram of a computer device provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0052] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of them. All other embodiments obtained by ordinary technicians in this field based on the embodiments of the present invention without making any creative efforts shall fall within the scope of protection of the present invention.

[0053] It will be understood that when used in this specification and the appended claims, the terms “comprises” and “comprising” indicate the presence of described features, integers, steps, operations, elements and / or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components and / or groups thereof.

[0054] It should also be understood that the terminology used in this specification is for the purpose of describing particular embodiments only and is not intended to limit the present invention. As used in the specification and appended claims, the singular forms "a," "an," and "the" are intended to include the plural forms unless the context clearly indicates otherwise.

[0055] It should be further understood that the term "and / or" used in the present description and appended claims refers to and includes any and all possible combinations of one or more of the associated listed items.

[0056] See also Figure 1 and Figure 2 , Figure 1 A schematic diagram of an application scenario of the RSU antenna switch control method provided in an embodiment of the present invention. Figure 2This is a schematic flow chart of the RSU antenna switch control method provided in an embodiment of the present invention. The RSU antenna switch control method is applied to a server. The server exchanges data with a sensing device and an RSU antenna. The server uses an artificial intelligence algorithm based on the sensing device to detect and track targets within the range covered by the RSU antenna. The sensing device includes but is not limited to a camera, millimeter-wave radar, and lidar. The range covered by the RSU antenna supports customization, and targets include vehicles and obstacles. When a new vehicle appears in the defined area, the RSU antenna in that area sends a signal to wake up the OBU in that area.

[0057] Figure 2 FIG. 1 is a flow chart of the RSU antenna switch control method provided by an embodiment of the present invention. Figure 2 As shown, the method includes the following steps S110 to S130.

[0058] S110: Set the area to be detected.

[0059] In this embodiment, the area to be detected refers to an area where vehicles and obstacles need to be detected. The area can be defined or set according to actual conditions, and the area to be detected is the range covered by the RSU antenna.

[0060] Specifically, the vehicle detection area is set according to the RSU transaction area of ​​a single gantry or in combination with the lane to obtain the area to be detected. That is, the vehicle detection area is determined according to the range covered by the RSU antenna of a single gantry and / or in combination with the direction of the lane. When determining the area to be detected based on the range covered by the RSU antenna of a single gantry, only the size of the range covered by the RSU antenna needs to be considered. When setting the area to be detected in combination with the lane direction, it is necessary to refine the impact of the dual-lane direction on target detection. The middle boundary of the two-way lane and the boundary of a certain direction can be demarcated and set as the area to be detected.

[0061] S120: Using an artificial intelligence algorithm to detect and track vehicles and obstacles in the area to be detected to obtain target information.

[0062] In this embodiment, the target information refers to the positioning information formed after tracking a target with a target ID.

[0063] In this embodiment, the target ID can be obtained in two ways. The first is that the sensing device has the ability to directly output the target ID. This sensing device can directly access the data of the target detection device to obtain the target ID and then perform target tracking. The other is that the sensing device only has simple target detection capabilities, and target tracking is required to obtain the target ID and location information.

[0064] In one embodiment, see Figure 3 The above-mentioned step S120 may include steps S121~S124.

[0065] S121. Using an artificial intelligence algorithm, the vehicles and obstacles in the to-be-detected area are matched with existing tracking targets to obtain a matching result.

[0066] In this embodiment, the matching result refers to the result of matching the vehicle and obstacle in the current detection area with the existing tracking target. The result can be a target ID or a notification message of unsuccessful matching.

[0067] When target tracking is required, a target matching algorithm based on speed and heading angle can be used to match vehicles and obstacles in the area to be detected with existing tracking targets to obtain a matching result; or an image or point cloud feature matching algorithm can be used to match vehicles and obstacles in the area to be detected with existing tracking targets to obtain a matching result.

[0068] Specifically, a target matching algorithm based on speed and heading angle matches the vehicle and obstacle in the detection area with the existing tracking target to obtain a matching result, including:

[0069] The expected position of the existing tracking target is calculated based on the speed, heading angle, and current time. It is determined whether the deviation between the expected position of the current vehicle and obstacle in the detection area and the existing tracking target is less than a set error threshold. If so, the vehicle and obstacle in the detection area match the existing tracking target, and the ID of the existing tracking target is the target ID of the vehicle and obstacle in the detection area. If not, the vehicle and obstacle in the detection area do not match the existing tracking target.

[0070] In addition, in other embodiments, the existing tracking target may be matched using a short-distance displacement target matching algorithm. Specifically, the position deviation between the position of the vehicle and obstacle in the area to be detected and the position of the existing tracking target is calculated. When the deviation is less than a set error threshold, the vehicle and obstacle in the area to be detected are matched with the existing tracking target, and the ID of the existing tracking target is the target ID of the vehicle and obstacle in the area to be detected; otherwise, the vehicle and obstacle in the area to be detected are not matched with the existing tracking target.

[0071] Specifically, the vehicle and obstacle in the to-be-detected area are matched with the existing tracking target based on an image or point cloud feature matching algorithm to obtain a matching result, including:

[0072] A deep learning-based target feature extraction algorithm is used to extract target features of vehicles and obstacles in the area to be detected. The target features are compared with the target features of existing tracking targets for similarity. When the similarity of the comparison meets the set requirements, the vehicles and obstacles in the area to be detected are matched with the existing tracking target, and the ID of the existing tracking target is used as the target ID of the vehicles and obstacles in the area to be detected; otherwise, the vehicles and obstacles in the area to be detected are not matched with the existing tracking target.

[0073] S122, determining whether the matching result is a successful match;

[0074] S123. If the matching result is a successful match, the target ID of the successful match is determined as the target information;

[0075] S124: If the matching result is not a successful match, a target ID is added to obtain target information.

[0076] In one embodiment, see Figure 4 The above-mentioned step S120 may include steps S121' to S127'. Steps S125' to S127' are similar to steps S121-S124 in the above-mentioned embodiment and are not described in detail here. The following details the additional steps S121' to S123' in this embodiment.

[0077] S121', obtaining the surveillance video within the area to be detected;

[0078] S122': Decode the surveillance video to obtain a decoding result.

[0079] In this embodiment, the decoding result refers to a video formed by decoding the surveillance video.

[0080] S123': Perform target detection on the decoding result based on a deep learning algorithm to obtain all targets in the area to be detected.

[0081] This embodiment is applicable when the sensing device only has the ability to output raw data and needs to perform target detection and target tracking.

[0082] S130 : performing on-off control on the RSU antenna in the area to be detected according to the target information, so as to wake up or shut down the OBU in the area to be detected.

[0083] In one embodiment, see Figure 5 The above-mentioned step S130 may include steps S131~S138.

[0084] S131. Set the switch state of the RSU antenna in the area to be detected to off.

[0085] Initially, the switch state of the RSU antenna in the area to be detected is set to the off state.

[0086] S132: Determine whether the target ID in the target information already exists.

[0087] In this embodiment, when the target ID already exists, it indicates that the switch control of the RSU antenna in the area to be detected has been performed for the detected target ID. It is only necessary to control the time of the target ID, delete the timed target ID, and control the switch of the RSU antenna according to the switch status of the RSU antenna in the area to be detected.

[0088] S133. If the target ID in the target information already exists, store and set the time when the target ID was last detected;

[0089] S134, deleting the target ID whose last detected time exceeds the set time;

[0090] S135. Determine whether the switch state of the RSU antenna in the area to be detected is on;

[0091] S136. If the switch state of the RSU antenna in the area to be detected is on, turn on the RSU antenna to wake up the OBU in the area to be detected;

[0092] S137: If the switch state of the RSU antenna in the area to be detected is not on, turn off the RSU antenna to turn off the OBU in the area to be detected.

[0093] S138. If the target ID in the target information does not already exist, set the switch state of the RSU antenna in the area to be detected to on, and execute step S133.

[0094] When the target ID does not already exist, that is, the target ID has just been detected, and the switch state of the RSU antenna in the area to be detected has not been set and the switch has not been controlled for the target ID, it is necessary to turn on the switch of the RSU antenna in the area to be detected for the target ID.

[0095] The method of this embodiment uses artificial intelligence algorithms based on data collected by sensing devices to detect and track vehicles within an area. Dynamically switching the RSU antenna on and off based on whether there are new vehicles in the area can reduce the power consumption of the RSU itself. Furthermore, it can reduce the number of times the OBU is awakened, extending the OBU's operating time and saving energy. The method of this embodiment can be implemented by adding artificial intelligence processor-side devices based on existing cameras, millimeter-wave radars, and lidars at highway entrances and exits or highway sections, deploying deep learning models and related control software. The method of this embodiment is based on deep learning technology in artificial intelligence and is combined with the current practical application of RSUs to eliminate provincial border toll booths or the urgent need to address the expansion of ETC applications.

[0096] The above-mentioned RUS antenna switch control method sets a vehicle's detection area, uses an artificial intelligence algorithm to detect and track vehicles and obstacles in the detection area to obtain target information, and controls the switching of the RSU antenna in the detection area according to the target information to wake up or shut down the OBU in the detection area, thereby achieving reasonable control of the switching of the RSU antenna, reducing the power consumption of the RSU itself, reducing the number of times the OBU is woken up, extending the use time of the OBU, and saving energy consumption.

[0097] Figure 6 FIG is a schematic block diagram of an RSU antenna switch control device 300 provided by an embodiment of the present invention. Figure 6 As shown, corresponding to the above RSU antenna switch control method, the present invention also provides an RSU antenna switch control device 300. The RSU antenna switch control device 300 includes a unit for executing the above RSU antenna switch control method, and the device can be configured in a server. Figure 6 The RSU antenna switch control device 300 includes an area setting unit 301, a target detection unit 302 and a switch control unit 303.

[0098] The area setting unit 301 is used to set the area to be detected; the target detection unit 302 is used to use an artificial intelligence algorithm to detect and track vehicles and obstacles in the area to be detected to obtain target information; the switch control unit 303 is used to control the RSU antenna in the area to be detected according to the target information to wake up or shut down the OBU in the area to be detected.

[0099] In one embodiment, the area setting unit 301 is used to set the vehicle detection area according to the RSU transaction area of ​​a single gantry or in combination with the lane to obtain the area to be detected.

[0100] In one embodiment, if Figure 7As shown, the target detection unit 302 includes a matching subunit 3024 , a result judgment subunit 3025 , a determination subunit 3026 and a new addition subunit 3027 .

[0101] The matching subunit 3024 is used to use an artificial intelligence algorithm to match the vehicles and obstacles in the area to be detected with the existing tracking targets to obtain a matching result; the result judgment subunit 3025 is used to judge whether the matching result is a successful match; the determination subunit 3026 is used to determine the target ID of the successful match as the target information if the matching result is a successful match; the adding subunit 3027 is used to add a target ID to obtain the target information if the matching result is not a successful match.

[0102] In one embodiment, the matching subunit 3024 is used to match the vehicles and obstacles in the area to be detected with the existing tracking targets based on a target matching algorithm of speed and heading angle to obtain a matching result; or, to match the vehicles and obstacles in the area to be detected with the existing tracking targets based on an image or point cloud feature matching algorithm to obtain a matching result.

[0103] In one embodiment, if Figure 8 As shown, the target detection unit 302 further includes a video acquisition subunit 3021 , a decoding subunit 3022 and a target detection subunit 3023 .

[0104] The video acquisition subunit 3021 is used to acquire the surveillance video within the area to be detected; the decoding subunit 3022 is used to decode the surveillance video to obtain a decoding result; the target detection subunit 3023 is used to perform target detection on the decoding result based on a deep learning algorithm to obtain all targets in the area to be detected.

[0105] In one embodiment, if Figure 9 As shown, the switch control unit 303 includes a first setting subunit 3031, an ID judgment subunit 3032, a storage subunit 3033, a deletion subunit 3034, a state judgment subunit 3035, an opening subunit 3036, a closing subunit 3037 and a second setting subunit 3038.

[0106] The first setting subunit 3031 is used to set the switch state of the RSU antenna in the area to be detected to be off; the ID judgment subunit 3032 is used to judge whether the target ID in the target information already exists; the storage subunit 3033 is used to store and set the last detection time of the target ID if the target ID in the target information already exists; the deletion subunit 3034 is used to delete the target ID whose last detection time exceeds the set time; the state judgment subunit 3035 is used to judge whether the switch state of the RSU antenna in the area to be detected is on; the opening subunit 3036 is used to turn on the RSU antenna in the area to be detected if the switch state of the RSU antenna in the area to be detected is on, so as to wake up the OBU in the area to be detected; the closing subunit 3037 is used to turn off the RSU antenna in the area to be detected if the switch state of the RSU antenna in the area to be detected is not on, so as to turn off the OBU in the area to be detected. The second setting subunit 3038 is used to set the switch state of the RSU antenna in the area to be detected to be on if the target ID in the target information does not already exist, and to perform the storage and set the time when the target ID was last detected.

[0107] It should be noted that those skilled in the art can clearly understand that the specific implementation process of the above-mentioned RSU antenna switch control device 300 and each unit can refer to the corresponding description in the aforementioned method embodiment. For the convenience and brevity of the description, it will not be repeated here.

[0108] The RSU antenna switch control device 300 can be implemented in the form of a computer program. The computer program can be used in Figure 10 Runs on the computer equipment shown.

[0109] See also Figure 10 , Figure 10 1 is a schematic block diagram of a computer device provided in an embodiment of the present application. The computer device 500 may be a server, wherein the server may be an independent server or a server cluster composed of multiple servers.

[0110] See Figure 10 The computer device 500 includes a processor 502 , a memory, and a network interface 505 connected via a system bus 501 , wherein the memory may include a non-volatile storage medium 503 and an internal memory 504 .

[0111] The non-volatile storage medium 503 may store an operating system 5031 and a computer program 5032. The computer program 5032 includes program instructions, which, when executed, may enable the processor 502 to execute a RSU antenna switch control method.

[0112] The processor 502 is used to provide computing and control capabilities to support the operation of the entire computer device 500.

[0113] The internal memory 504 provides an environment for the operation of the computer program 5032 in the non-volatile storage medium 503. When the computer program 5032 is executed by the processor 502, the processor 502 can execute an RSU antenna switch control method.

[0114] The network interface 505 is used to communicate with other devices through the network. Figure 10 The structure shown in the figure is merely a block diagram of a portion of the structure related to the solution of the present application, and does not constitute a limitation on the computer device 500 to which the solution of the present application is applied. The specific computer device 500 may include more or fewer components than shown in the figure, or combine certain components, or have a different component arrangement.

[0115] The processor 502 is configured to execute a computer program 5032 stored in the memory to implement the following steps:

[0116] Set an area to be detected; use an artificial intelligence algorithm to detect and track vehicles and obstacles in the area to be detected to obtain target information; and control the switching of the RSU antenna in the area to be detected according to the target information to wake up or shut down the OBU in the area to be detected.

[0117] In one embodiment, when implementing the step of setting the area to be detected, the processor 502 specifically implements the following steps:

[0118] The vehicle detection area is set according to the RSU transaction area of ​​a single gantry or in combination with the lane to obtain the area to be detected.

[0119] In one embodiment, when the processor 502 implements the step of using an artificial intelligence algorithm to detect and track vehicles and obstacles in the detection area to obtain target information, it specifically implements the following steps:

[0120] An artificial intelligence algorithm is used to match the vehicles and obstacles in the area to be detected with the existing tracking targets to obtain a matching result; it is determined whether the matching result is a successful match; if the matching result is a successful match, the target ID of the successful match is determined as the target information; if the matching result is not a successful match, a new target ID is added to obtain the target information.

[0121] In one embodiment, when implementing the step of using an artificial intelligence algorithm to match the vehicle and obstacle in the to-be-detected area with the existing tracking target to obtain a matching result, the processor 502 specifically implements the following steps:

[0122] The vehicle and obstacles in the area to be detected are matched with the existing tracking targets using a target matching algorithm based on speed and heading angle to obtain a matching result; or the vehicle and obstacles in the area to be detected are matched with the existing tracking targets using an image or point cloud feature matching algorithm to obtain a matching result.

[0123] In one embodiment, before implementing the step of using an artificial intelligence algorithm to match the vehicle and obstacle in the detection area with the existing tracking target to obtain a matching result, the processor 502 further implements the following steps:

[0124] Obtain surveillance video within the area to be detected; decode the surveillance video to obtain a decoding result; perform target detection on the decoding result based on a deep learning algorithm to obtain all targets in the area to be detected.

[0125] In one embodiment, when the processor 502 implements the step of switching the RSU antenna within the to-be-detected area according to the target information to wake up or shut down the OBU within the to-be-detected area, the processor 502 specifically implements the following steps:

[0126] Set the switch state of the RSU antenna in the area to be detected to be off; determine whether the target ID in the target information already exists; if the target ID in the target information already exists, store and set the time when the target ID was last detected; delete the target ID whose last detection time exceeds the set time; determine whether the switch state of the RSU antenna in the area to be detected is on; if the switch state of the RSU antenna in the area to be detected is on, turn on the RSU antenna to wake up the OBU in the area to be detected; if the switch state of the RSU antenna in the area to be detected is not on, turn off the RSU antenna to turn off the OBU in the area to be detected.

[0127] In one embodiment, after implementing the step of determining whether the target information contains a target ID, the processor 502 further implements the following steps:

[0128] If the target ID in the target information does not already exist, the switch state of the RSU antenna in the area to be detected is set to be on, and the storage and setting of the time when the target ID was last detected are performed.

[0129] It should be understood that in the embodiment of the present application, the processor 502 may be a central processing unit (CPU), and the processor 502 may also be other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor may be a microprocessor or any conventional processor, etc.

[0130] Those skilled in the art will appreciate that all or part of the steps in the method of the above-described embodiment can be implemented by instructing the relevant hardware through a computer program. The computer program includes program instructions, which can be stored in a storage medium that is computer-readable. The program instructions are executed by at least one processor in the computer system to implement the steps in the method of the above-described embodiment.

[0131] Therefore, the present invention also provides a storage medium. The storage medium may be a computer-readable storage medium. The storage medium stores a computer program, wherein when the computer program is executed by a processor, the processor performs the following steps:

[0132] Set an area to be detected; use an artificial intelligence algorithm to detect and track vehicles and obstacles in the area to be detected to obtain target information; and control the switching of the RSU antenna in the area to be detected according to the target information to wake up or shut down the OBU in the area to be detected.

[0133] In one embodiment, when the processor executes the computer program to implement the step of setting the area to be detected, the processor specifically implements the following steps:

[0134] The vehicle detection area is set according to the RSU transaction area of ​​a single gantry or in combination with the lane to obtain the area to be detected.

[0135] In one embodiment, when the processor executes the computer program to implement the step of using an artificial intelligence algorithm to detect and track vehicles and obstacles in the detection area to obtain target information, the processor specifically implements the following steps:

[0136] An artificial intelligence algorithm is used to match the vehicles and obstacles in the area to be detected with the existing tracking targets to obtain a matching result; it is determined whether the matching result is a successful match; if the matching result is a successful match, the target ID of the successful match is determined as the target information; if the matching result is not a successful match, a new target ID is added to obtain the target information.

[0137] In one embodiment, when the processor executes the computer program to implement the step of using an artificial intelligence algorithm to match the vehicle and obstacle in the detection area with the existing tracking target to obtain a matching result, the processor specifically implements the following steps:

[0138] The vehicle and obstacles in the area to be detected are matched with the existing tracking targets using a target matching algorithm based on speed and heading angle to obtain a matching result; or the vehicle and obstacles in the area to be detected are matched with the existing tracking targets using an image or point cloud feature matching algorithm to obtain a matching result.

[0139] In one embodiment, before executing the computer program to implement the step of using an artificial intelligence algorithm to match vehicles and obstacles in the detection area with existing tracking targets to obtain a matching result, the processor further implements the following steps:

[0140] Obtain surveillance video within the area to be detected; decode the surveillance video to obtain a decoding result; perform target detection on the decoding result based on a deep learning algorithm to obtain all targets in the area to be detected.

[0141] In one embodiment, when the processor executes the computer program to implement the step of switching the RSU antenna within the to-be-detected area according to the target information to wake up or shut down the OBU within the to-be-detected area, the processor specifically implements the following steps:

[0142] Set the switch state of the RSU antenna in the area to be detected to be off; determine whether the target ID in the target information already exists; if the target ID in the target information already exists, store and set the time when the target ID was last detected; delete the target ID whose last detection time exceeds the set time; determine whether the switch state of the RSU antenna in the area to be detected is on; if the switch state of the RSU antenna in the area to be detected is on, turn on the RSU antenna to wake up the OBU in the area to be detected; if the switch state of the RSU antenna in the area to be detected is not on, turn off the RSU antenna to turn off the OBU in the area to be detected.

[0143] In one embodiment, after executing the computer program to implement the step of determining whether the target information contains a target ID, the processor further implements the following steps:

[0144] If the target ID in the target information does not already exist, the switch state of the RSU antenna in the area to be detected is set to be on, and the storage and setting of the time when the target ID was last detected are performed.

[0145] The storage medium may be any computer-readable storage medium that can store program codes, such as a USB flash drive, a mobile hard disk, a read-only memory (ROM), a magnetic disk, or an optical disk.

[0146] Those skilled in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, computer software, or a combination of the two. In order to clearly illustrate the interchangeability of hardware and software, the above description has generally described the composition and steps of each example according to function. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of the present invention.

[0147] In the several embodiments provided herein, it should be understood that the disclosed devices and methods can be implemented in other ways. For example, the device embodiments described above are merely illustrative. For example, the division of the various units is merely a logical functional division, and actual implementation may employ other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be omitted or not implemented.

[0148] The steps in the methods of the embodiments of the present invention may be adjusted in order, combined, or deleted as needed. The units in the devices of the embodiments of the present invention may be combined, divided, or deleted as needed. Furthermore, the functional units in the various embodiments of the present invention may be integrated into a single processing unit, each unit may exist physically separately, or two or more units may be integrated into a single unit.

[0149] If this integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a storage medium. Based on this understanding, the technical solution of the present invention, or the portion that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product, stored in a storage medium, includes instructions for enabling a computer device (such as a personal computer, terminal, or network device) to execute all or part of the steps of the method described in various embodiments of the present invention.

[0150] The above description is merely a specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any person skilled in the art can easily conceive of various equivalent modifications or substitutions within the technical scope disclosed in the present invention, and such modifications or substitutions are intended to be within the scope of protection of the present invention. Therefore, the scope of protection of the present invention shall be subject to the scope of protection of the claims.

Claims

1. RSU antenna switch control method, characterized in that: include: Set the area to be detected; Set the vehicle detection area according to the RSU transaction area of ​​a single gantry or in combination with the lane to obtain the area to be detected; Using artificial intelligence algorithms to detect and track vehicles and obstacles in the area to be detected to obtain target information; Performing switch control on the RSU antenna in the area to be detected according to the target information to wake up or shut down the OBU in the area to be detected; The switching control of the RSU antenna in the area to be detected according to the target information to wake up or shut down the OBU in the area to be detected includes: Set the switch state of the RSU antenna in the area to be detected to off; Determine whether the target ID in the target information already exists; If the target ID in the target information already exists, then the time when the target ID was last detected is stored and set; Delete the target ID whose last detected time exceeds the set time; Determine whether the switch state of the RSU antenna in the area to be detected is on; If the switch state of the RSU antenna in the area to be detected is on, turning on the RSU antenna to wake up the OBU in the area to be detected; If the switch state of the RSU antenna in the area to be detected is not on, turning off the RSU antenna to turn off the OBU in the area to be detected; The artificial intelligence algorithm is used to detect and track vehicles and obstacles in the detection area to obtain target information, including: Using artificial intelligence algorithms to match vehicles and obstacles in the area to be detected with existing tracking targets to obtain matching results; Determine whether the matching result is a successful match; If the matching result is a successful match, the target ID of the successful match is determined as the target information; If the matching result is not a successful match, then a target ID is added to obtain target information; The artificial intelligence algorithm is used to match the vehicles and obstacles in the detection area with the existing tracking targets to obtain a matching result, including: Matching the vehicles and obstacles in the detection area with the existing tracking targets using a target matching algorithm based on speed and heading angle to obtain a matching result; Alternatively, the vehicles and obstacles in the to-be-detected area are matched with existing tracking targets based on an image or point cloud feature matching algorithm to obtain a matching result.

2. The RSU antenna switch control method according to claim 1, characterized in that: Before using the artificial intelligence algorithm to match the vehicles and obstacles in the to-be-detected area with the existing tracking targets to obtain a matching result, the method further includes: Obtaining surveillance video within the area to be detected; Decoding the surveillance video to obtain a decoding result; Target detection is performed on the decoding results based on a deep learning algorithm to obtain all targets in the area to be detected.

3. The RSU antenna switch control method according to claim 2, characterized in that: After determining whether the target information has a target ID, the method further includes: If the target ID in the target information does not already exist, the switch state of the RSU antenna in the area to be detected is set to be on, and the storage and setting of the time when the target ID was last detected are performed.

4. RSU antenna switch control device, characterized in that: include: An area setting unit, used to set an area to be detected; Set the vehicle detection area according to the RSU transaction area of ​​a single gantry or in combination with the lane to obtain the area to be detected; A target detection unit, configured to detect and track vehicles and obstacles in the area to be detected using an artificial intelligence algorithm to obtain target information; A switch control unit is used to perform switch control on the RSU antenna in the area to be detected according to the target information, so as to wake up or shut down the OBU in the area to be detected; The switch control unit includes: a first setting subunit, configured to set the switch state of the RSU antenna in the area to be detected to be off; an ID judgment subunit, configured to judge whether the target ID in the target information already exists; a storage subunit, configured to store and set the time when the target ID was last detected if the target ID in the target information already exists; a deletion subunit, configured to delete the target ID whose last detection time exceeds the set time; a state judgment subunit, configured to judge whether the switch state of the RSU antenna in the area to be detected is on; a turning on subunit, configured to turn on the RSU antenna if the switch state of the RSU antenna in the area to be detected is on, so as to wake up the OBU in the area to be detected; a turning off subunit, configured to turn off the RSU antenna if the switch state of the RSU antenna in the area to be detected is not on, so as to turn off the OBU in the area to be detected; The target detection unit includes a matching subunit, a result judgment subunit, a determination subunit and a new addition subunit; The matching subunit is used to match the vehicles and obstacles in the detection area with the existing tracking targets using an artificial intelligence algorithm to obtain a matching result; the result judgment subunit is used to judge whether the matching result is a successful match; the determination subunit is used to determine the target ID of the successful match as the target information if the matching result is a successful match; the adding subunit is used to add the target ID to obtain the target information if the matching result is not a successful match; The matching subunit is used to match the vehicles and obstacles in the to-be-detected area with the existing tracking targets based on a target matching algorithm of speed and heading angle to obtain a matching result; or to match the vehicles and obstacles in the to-be-detected area with the existing tracking targets based on an image or point cloud feature matching algorithm to obtain a matching result.

5. A computer device, characterized in that: The computer device includes a memory and a processor, the memory stores a computer program, and the processor implements the method according to any one of claims 1 to 3 when executing the computer program.

6. A storage medium, characterized in that The storage medium stores a computer program, and when the computer program is executed by a processor, the method according to any one of claims 1 to 3 is implemented.

Images