Streetlight control method, device, equipment and medium based on roadside perception system

Abstract

The present application discloses a streetlight control method, device, electronic device, and readable storage medium based on a roadside sensing system, which are applied to the field of roadside sensing technology. The streetlight control method based on the roadside sensing system includes: if the vehicle identification information broadcast by the target vehicle is received, then the actual distance information corresponding to the target vehicle is obtained, wherein the actual distance information is used to represent the actual distance between the target vehicle and the streetlight to be controlled; based on the vehicle identification information and the actual distance information, determining whether the target vehicle is a light control reference vehicle; if so, obtaining streetlight control information by fusing the vehicle identification information and the actual distance information; and controlling the streetlight to be controlled based on the streetlight control information. The present application solves the technical problem of low streetlight utilization on the road sections where unmanned logistics vehicles travel.

Description

Technical Field

[0001] The present application relates to the field of roadside perception technology, and in particular to a streetlight control method, device, electronic device and readable storage medium based on a roadside perception system. Background Art

[0002] With the continuous development of science and technology, unmanned logistics vehicles in specific scenarios are being used more and more widely. At the same time, how to improve the utilization of resources in the driving scenarios of unmanned logistics vehicles has become an urgent problem to be solved. At present, the street lights on the road sections where unmanned logistics vehicles are driving are usually set with specific opening and closing time periods to assist the driving of unmanned logistics vehicles. For example, they are set to be in a normally open state from 9 pm to 5 am. However, unmanned logistics vehicles do not pass through this road section at all times. Therefore, there is a waste of resources in the street lights on the road sections where unmanned logistics vehicles are driving, that is, the utilization rate of street lights on the road sections where unmanned logistics vehicles are driving is low. Summary of the Invention

[0003] The main purpose of this application is to provide a street light control method, device, electronic device and readable storage medium based on a roadside perception system, aiming to solve the technical problem of low street light utilization rate on the road sections where unmanned logistics vehicles travel in the existing technology.

[0004] To achieve the above objectives, the present application provides a streetlight control method based on a roadside perception system, the streetlight control method based on a roadside perception system comprising:

[0005] If the vehicle identification information broadcast by the target vehicle is received, the actual distance information corresponding to the target vehicle is obtained, wherein the actual distance information is used to represent the actual distance between the target vehicle and the streetlight to be controlled;

[0006] Determining whether the target vehicle is a light-controlled reference vehicle based on the vehicle identification information and the actual distance information;

[0007] If yes, then obtaining streetlight control information by fusing the vehicle identification information and the actual distance information;

[0008] The streetlight to be controlled is controlled according to the streetlight control information.

[0009] To achieve the above objectives, the present application further provides a streetlight control device based on a roadside sensing system, the streetlight control device based on a roadside sensing system comprising:

[0010] An acquisition module is configured to acquire actual distance information corresponding to a target vehicle upon receiving vehicle identification information broadcast by the target vehicle, wherein the actual distance information is used to represent the actual distance between the target vehicle and the streetlight to be controlled;

[0011] a determination module, configured to determine whether the target vehicle is a light-controlled reference vehicle based on the vehicle identification information and the actual distance information;

[0012] a fusion module, configured to obtain streetlight control information by fusing the vehicle identification information and the actual distance information;

[0013] A control module is used to control the streetlight to be controlled according to the streetlight control information.

[0014] The present application also provides an electronic device, which includes: a memory, a processor, and a program of the street light control method based on the roadside perception system stored in the memory and runnable on the processor. When the program of the street light control method based on the roadside perception system is executed by the processor, the steps of the street light control method based on the roadside perception system as described above can be implemented.

[0015] The present application also provides a computer-readable storage medium, on which is stored a program for implementing a street light control method based on a roadside perception system. When the program for the street light control method based on a roadside perception system is executed by a processor, the steps of the street light control method based on a roadside perception system as described above are implemented.

[0016] The present application also provides a computer program product, including a computer program, which, when executed by a processor, implements the steps of the above-mentioned street light control method based on the roadside perception system.

[0017] The present application provides a street light control method, device, electronic device and readable storage medium based on a roadside perception system, that is, if vehicle identification information broadcast by a target vehicle is received, the actual distance information corresponding to the target vehicle is obtained, wherein the actual distance information is used to characterize the actual distance between the target vehicle and the street light to be controlled; based on the vehicle identification information and the actual distance information, it is determined whether the target vehicle is a light control reference vehicle; if so, street light control information is obtained by fusing the vehicle identification information and the actual distance information; and based on the street light control information, the street light to be controlled is controlled. Since the target vehicle will broadcast vehicle identification information while driving, and the roadside perception system can perceive the actual distance between the target vehicle and the street light to be controlled, the vehicle identification information and actual distance information can be used to accurately determine whether the target vehicle is a reference vehicle for controlling the switch status of the street light, that is, a light-controlled reference vehicle. When the target vehicle is a light-controlled reference vehicle, the vehicle identification information and the actual distance information are fused to generate street light control information to control the street light to be controlled. This can achieve the purpose of real-time control of the switch status of the street light to be controlled based on the light-controlled reference vehicle, rather than keeping the street light in a normally on or normally off state within a set time period. Therefore, the technical defect of wasting street light resources caused by no vehicles driving on the road section when the street light is in a normally on state is overcome. Therefore, the control flexibility of street light control is improved, thereby improving the utilization rate of street lights on the road section where unmanned logistics vehicles are driving. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present application and, together with the description, serve to explain the principles of the present application.

[0019] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, for ordinary technicians in this field, other drawings can be obtained based on these drawings without any creative work.

[0020] Figure 1 This is a flowchart of the first embodiment of the streetlight control method based on the roadside perception system of this application;

[0021] Figure 2 This is a schematic diagram of information interaction of the roadside perception system based on the roadside perception system of the streetlight control method of the present application;

[0022] Figure 3 This is a flowchart of the second embodiment of the street light control method based on the roadside perception system of this application;

[0023] Figure 4This is a schematic diagram of an embodiment of a streetlight control device based on a roadside sensing system of the present application;

[0024] Figure 5 This is a schematic diagram of the device structure of the hardware operating environment involved in the street light control method based on the roadside perception system in the embodiment of the present application.

[0025] The purpose, features and advantages of this application will be further explained in conjunction with the embodiments and with reference to the accompanying drawings. DETAILED DESCRIPTION

[0026] To make the above-mentioned objects, features, and advantages of the present invention more clearly understood, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some of the embodiments of the present invention, not all of them. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making any creative efforts shall fall within the scope of protection of the present invention.

[0027] Example 1

[0028] First of all, it should be understood that in the context of industrial digitalization and backgroundization, roadside perception systems are usually deployed on driving roads. Among them, the roadside perception system uses roadside perception technology to obtain real-time information about road traffic participants and road conditions, and feeds back the surrounding conditions to the vehicle-mounted system. That is, through a variety of sensors such as visual sensors, millimeter-wave radars and lidars, combined with edge computing units, real-time acquisition of road traffic participants and road condition information is achieved, and then handed over to the software system for analysis and decision-making. At the same time, due to V2I (Vehicle to The widespread application of vehicle and infrastructure (V2I) technology has made it possible to control road resources by relying on information interaction between roadside perception systems and on-board systems. For example, in the field of logistics and transportation, streetlight resource control is usually carried out on unmanned vehicle transportation sections. At present, logistics, transportation and distribution of goods are usually carried out on closed or semi-closed roads. Since unmanned logistics vehicles need to capture road condition information ahead through cameras, unmanned logistics vehicles need to rely on streetlights on both sides of the road for night operations. This means that roadside streetlights are always on during certain fixed time periods. However, unmanned logistics vehicles do not pass through this section at all times, resulting in a waste of streetlight resources. Therefore, there is an urgent need for a method to improve the utilization rate of streetlights on sections where unmanned logistics vehicles are traveling.

[0029] The present application provides a method for controlling streetlights based on a roadside sensing system. In the first embodiment of the method for controlling streetlights based on a roadside sensing system, Figure 1 , the streetlight control method based on the roadside perception system includes:

[0030] Step S10: If the vehicle identification information broadcast by the target vehicle is received, then the actual distance information corresponding to the target vehicle is obtained, wherein the actual distance information is used to represent the actual distance between the target vehicle and the streetlight to be controlled;

[0031] Step S20, determining whether the target vehicle is a light-controlled reference vehicle based on the vehicle identification information and the actual distance information;

[0032] Step S30: If yes, obtain streetlight control information by fusing the vehicle identification information and the actual distance information;

[0033] Step S40: controlling the streetlight to be controlled according to the streetlight control information.

[0034] In this embodiment, it should be noted that since V2I technology can establish a communication frequency band for the on-board intelligent transportation system through wireless, and then the vehicle can broadcast its own vehicle information through the on-board unit through the communication frequency band during driving, the target vehicle is used to represent the vehicle that communicates with the roadside perception system through the target communication frequency band, which can specifically be an unmanned logistics vehicle, etc. For example, in one feasible method, the target communication frequency band of the roadside perception system is A, but within a preset time period, communication frequency bands A, B and C all broadcast vehicle identification information, then the vehicle identification information broadcast by communication frequency band A is the vehicle identification information of the target vehicle, wherein the vehicle identification information is used to identify the target vehicle, and can specifically be a license plate number or vehicle identification, etc.

[0035] In addition, it should be noted that in order to improve the clarity of roadside monitoring, a roadside sensing system is usually installed on a roadside lamp post. That is, the roadside sensing system can accurately locate the actual distance between the target vehicle and the street light to be controlled, and then analyze and decide the opening and closing of the street light through information interaction. Figure 2 , Figure 2Schematic diagram of information interaction of a roadside perception system, the roadside perception system includes a roadside perception module, an edge computing unit, a V2I roadside unit, a routing device, and a streetlight control module, wherein the V2I roadside unit is used to collect relevant information between the target vehicle and the roadside perception system for controlling the streetlight to be controlled, specifically including a positioning module and a first V2I communication module, the first V2I communication module receives the vehicle identification information broadcast by the target vehicle, the positioning module is used to locate the actual distance between the target vehicle and the streetlight to be controlled, the roadside perception module is used to detect the accuracy of the relevant information obtained by the V2I roadside unit, specifically including a comparison module, an information collection module, and a second V2I communication module, the information collection module includes a high-definition camera and a laser radar, the second V2I communication module is used to receive the information from the V2I roadside unit The relevant information transmitted is that the comparison module is used to compare whether there is a target vehicle corresponding to the vehicle identification information in the picture frame captured by the high-definition camera, and to compare whether the perceived distance between the target vehicle and the street lamp to be controlled located by the laser radar is consistent with the actual distance corresponding to the reagent distance information. The edge computing unit is used to receive the vehicle identification information and the corresponding actual distance information corresponding to the street lamp reference vehicle and perform information fusion to generate street lamp control information, and then feed back the street lamp control information to the V2I roadside unit, so that the V2I roadside unit will send the street lamp control information to the street lamp control module through a preset communication segment. The street lamp control module is used to flexibly control the street lamp to be controlled. The routing device is used to transmit information between the modules of the roadside perception system, wherein the vehicle information in the figure includes vehicle identification information and actual distance information.

[0036] Additionally, it should be noted that the actual distance information is used to represent the actual distance between the target vehicle and the streetlight to be controlled. The light-controlled reference vehicle is used to represent the target vehicle that provides reference information for streetlight control. The reference information is the vehicle identification information and actual distance information of the vehicle. The streetlight information is used to represent the streetlight control signal that controls the streetlight to be controlled. The streetlight control signal can control the streetlight to be turned on or off, etc. The streetlights to be controlled and the roadside sensing system can have a one-to-one correspondence, or a relationship where one roadside sensing system corresponds to multiple streetlights to be controlled. Since the roadside sensing system has a receivable range for receiving broadcast information, only streetlights within the preset monitoring range of the roadside sensing system are streetlights to be controlled. The road section corresponding to the farthest communication distance between the streetlight to be controlled and the target vehicle is the communicable road section. For example, in one practicable embodiment, assuming that the target vehicle is an unmanned logistics vehicle, and there are 10 streetlights on the roadside of the communicable road section corresponding to the unmanned logistics vehicle, a roadside sensing system can be installed on each streetlight to control the streetlight.

[0037] As an example, steps S10 to S40 include: if vehicle identification information broadcast by the target vehicle on the communicative road section is received, then obtaining the actual distance information corresponding to the target vehicle; based on the vehicle identification information and the actual distance information, determining whether the target vehicle is a light-controlled reference vehicle; if it is determined that the target vehicle is a light-controlled reference vehicle, obtaining street light control information by fusing the vehicle identification information and the actual distance information; and controlling the street light to be controlled based on the street light control information.

[0038] The step of determining whether the target vehicle is a light-controlled reference vehicle based on the vehicle identification information and the actual distance information includes:

[0039] Step A10, obtaining the current picture frame;

[0040] Step A20, detecting whether the target vehicle exists in the current image frame according to the vehicle identification information;

[0041] Step A30: If yes, then obtain the perceived distance information between the target vehicle and the street lamp to be controlled in the current image frame, and determine whether the target vehicle is the street lamp control reference vehicle based on the correspondence between the actual distance information and the perceived distance information;

[0042] Step A40: If not, the next picture frame is used as the current picture frame, and the process returns to the step of detecting whether the target vehicle exists in the current picture frame according to the vehicle identification information.

[0043] In this embodiment, it should be noted that the current image frame is the image frame of the streetlight-controlled section captured by the roadside perception module when receiving the relevant information sent by the V2I roadside unit. Since there are multiple traffic participants in the streetlight-controlled section and the communication frequency band has a long communication distance, if the positioning information obtained directly through the V2I roadside unit is fused, it will lead to inaccurate streetlight control. If the target vehicle appears in the streetlight-controlled section, it indicates that the target vehicle will require streetlights to provide lighting. Therefore, it is possible to determine whether the target vehicle exists in the current image frame to determine whether the target vehicle is the light-controlled reference vehicle. That is, it is possible to determine whether the target vehicle corresponding to the vehicle identification information obtained by the V2I roadside unit is the light-controlled reference vehicle and whether the positioning is accurate.

[0044] As an example, steps A10 to A40 include: when the roadside perception module receives the vehicle identification information and actual distance information of the target vehicle sent by the V2I roadside unit, intercepting the current picture frame in the video stream captured by the camera; detecting whether the target vehicle exists in the current picture frame based on the vehicle identification information; if the target vehicle exists in the current picture frame, obtaining the perceived distance information between the target vehicle and the street lamp to be controlled in the current picture frame, and determining whether the target vehicle is the light control reference vehicle based on the correspondence between the actual distance information and the perceived distance information; if the target vehicle does not exist in the current picture frame, intercepting the next picture frame of the current picture frame in the video stream, using the next picture frame as the current picture frame, and returning to the execution step of detecting whether the target vehicle exists in the current picture frame based on the vehicle identification information.

[0045] The step of detecting whether the target vehicle exists in the current frame based on the vehicle identification information includes:

[0046] Step B10, matching the vehicle identification information with a standard vehicle image of the target vehicle;

[0047] Step B20 , determining whether the target vehicle exists in the current image frame by performing image recognition on the current image frame and the standard vehicle image.

[0048] As an example, steps B10 to B20 include: using the vehicle identification information as an index, matching the standard vehicle image of the target vehicle in a preset vehicle mapping library, wherein the preset vehicle mapping library is used to store the mapping relationship between the vehicle identification information and the standard vehicle image; performing image classification on the current picture frame to obtain a first image classification label, and performing image classification on the standard vehicle image to obtain a second image classification label. If the first image classification label and the second image classification label are consistent, it is determined that the target vehicle exists in the current picture frame. If the first image classification label and the second image classification label are inconsistent, it is determined that the target vehicle does not exist in the current picture frame. The first image classification label and the second image classification label are both image classification labels, and the image classification label is used to identify the category of the image, which can specifically be 0 or 1.

[0049] The step of obtaining the perceived distance information between the target vehicle and the street lamp to be controlled in the current picture frame includes:

[0050] Step C10, obtaining the point cloud information of the driving section corresponding to the current image frame;

[0051] Step C20, performing structured processing on the driving section point cloud information to obtain structured point cloud information;

[0052] Step C30: clustering the structured point cloud information into a preset number of point cloud clusters, and determining a target point cloud cluster in each of the point cloud clusters;

[0053] In step C40 , the target point cloud cluster feature vector corresponding to the target point cloud cluster is input into a preset distance recognition model to obtain the perceived distance information between the target vehicle and the street lamp to be controlled.

[0054] In this embodiment, it should be noted that the driving section point cloud information is used to characterize the point cloud of the street light controlled section, which can be specifically any frame point cloud fed back by the laser radar during the working process under the current picture frame, that is, the original data fed back by the laser radar of the roadside perception module. Since there are usually multiple traffic participants in the street light controlled section, the point cloud to be processed needs to be sorted, so the structured point cloud information is used to characterize the point cloud after the laser points in each point cloud are sorted according to the preset sorting index. In order to reduce the amount of calculation, the laser points corresponding to the ground points will be invalidated during the sorting process, and different types of structured point cloud information are clustered to obtain a preset number of point cloud clusters of different types.

[0055] In addition, it should be noted that the preset distance recognition model is used to identify the perceived distance information between the target vehicle and the street lamp to be controlled. The perceived distance information is used to characterize the perceived distance between the target vehicle and the street lamp to be controlled. The perceived distance is the distance measured by the roadside perception module through the lidar. The perceived distance and the actual distance positioned by the V2I roadside unit can reduce the error of the information that needs to be fused, thereby achieving precise control of the street lamps on the street lamp control section.

[0056] As an example, steps C10 to C40 include: obtaining the driving section point cloud information corresponding to the current picture frame through a laser radar, wherein the driving section point cloud information includes the driving section point cloud information of ground points and the driving section point cloud information of non-ground points; performing invalid processing on the driving section point cloud information of ground points, and performing structured processing on the driving section point cloud information of non-ground points to obtain the structured point cloud information; clustering the structured point cloud information into a preset number of point cloud clusters, and determining a target point cloud cluster in each of the point cloud clusters; inputting the target point cloud cluster feature vector corresponding to the target point cloud cluster into a preset distance recognition model to obtain the perceived distance information between the target vehicle and the street lamp to be controlled.

[0057] The step of determining whether the target vehicle is the light control reference vehicle based on the correspondence between the actual distance information and the perceived distance information includes:

[0058] Step D10, detecting whether the actual distance information is consistent with the perceived distance information;

[0059] Step D20: If yes, then determine that the target vehicle is the light-controlled reference vehicle;

[0060] Step D30: If not, it is determined that the target vehicle is not the light control reference vehicle.

[0061] As an example, steps D10 to D40 include: detecting whether the actual distance information and the perceived distance information are consistent; if the actual distance corresponding to the actual distance information and the perceived information corresponding to the perceived distance information are consistent, determining that the target vehicle is the lighting control reference vehicle; if the actual vehicle corresponding to the actual distance information and the perceived information corresponding to the perceived distance information are inconsistent, determining that the target vehicle is not the lighting control reference vehicle.

[0062] The step of obtaining the streetlight control information by fusing the vehicle identification information and the actual distance information includes:

[0063] Step E10, detecting whether the actual distance corresponding to the actual distance information is not greater than a preset light control distance threshold;

[0064] Step E20: If yes, perform information fusion on the vehicle identification information and the actual distance information to obtain the street light control information.

[0065] In this embodiment, it should be noted that the target vehicle uses the V2I communication module to transmit the vehicle identification information to the V2I roadside unit, and then the V2I roadside unit will send the information to the roadside perception module and the edge computing unit respectively after obtaining the actual distance information through the positioning module. The edge computing unit not only serves the street light control, but also the roadside perception module verifies the accuracy of the relevant information before the edge computing unit fuses the information to improve the resource utilization of the edge computing unit. However, if the information is accurate, the information fusion will be started, which involves the control distance factor for controlling the street light. The preset light control distance threshold is used to characterize the distance for controlling the street light. Therefore, information fusion is performed when entering the preset light control distance, which can maximize the utilization of the computing resources of the edge computing unit.

[0066] As an example, steps E10 to E20 include: detecting whether the actual distance corresponding to the actual distance information is not greater than a preset light control distance threshold; if the actual distance is not greater than the preset light control distance threshold, fusing the vehicle identification information and the actual distance information to obtain the street light control information.

[0067] An embodiment of the present application provides a street light control method based on a roadside perception system, that is, if vehicle identification information broadcast by a target vehicle is received, actual distance information corresponding to the target vehicle is obtained, wherein the actual distance information is used to characterize the actual distance between the target vehicle and the street light to be controlled; based on the vehicle identification information and the actual distance information, it is determined whether the target vehicle is a light control reference vehicle; if so, street light control information is obtained by fusing the vehicle identification information and the actual distance information; and based on the street light control information, the street light to be controlled is controlled. Since the target vehicle will broadcast vehicle identification information while driving, and the roadside perception system can perceive the actual distance between the target vehicle and the street light to be controlled, the vehicle identification information and actual distance information can be used to accurately determine whether the target vehicle is a reference vehicle for controlling the switch status of the street light, that is, a light-controlled reference vehicle. When the target vehicle is a light-controlled reference vehicle, the vehicle identification information and the actual distance information are fused to generate street light control information to control the street light to be controlled. This can achieve the purpose of real-time control of the switch status of the street light to be controlled based on the light-controlled reference vehicle, rather than keeping the street light in a normally on or normally off state within a set time period. Therefore, the technical defect of wasting street light resources caused by no vehicles driving on the road section when the street light is in a normally on state is overcome. Therefore, the control flexibility of street light control is improved, thereby improving the utilization rate of street lights on the road section where unmanned logistics vehicles are driving.

[0068] Example 2

[0069] Further, refer to Figure 3 In another embodiment of the present application, the same or similar contents as those in the above-mentioned embodiment 1 can be referred to the above description and will not be described in detail. On this basis, the step of determining whether the current image frame contains the target vehicle by performing image recognition on the current image frame and the standard vehicle image includes:

[0070] Step F10, performing image feature extraction on the current image frame using a first image feature extraction model to obtain at least one first image feature corresponding to the current image frame;

[0071] Step F20, performing image feature extraction on the standard vehicle image using a second image feature extraction model to obtain a second image feature corresponding to the standard vehicle image;

[0072] Step F30 : judging whether the target vehicle exists in the current image frame based on the feature similarity between each of the first image features and the second image features.

[0073] As an example, steps F10 to F30 include: inputting the current picture frame into a first image feature extraction model, performing feature extraction on different picture frame areas of the current picture frame, and obtaining at least one first image feature corresponding to the current picture frame; inputting the standard vehicle image into a second image feature extraction model, performing feature extraction on the entire image area of ​​the standard vehicle image, and obtaining a second image feature corresponding to the standard vehicle image; respectively calculating the feature similarity between each of the first image features and the second image features, and if at least one feature similarity among the feature similarities is greater than a preset feature similarity threshold, it is determined that the target vehicle exists in the current picture frame; if none of the feature similarities is greater than the preset feature similarity threshold, it is determined that the target vehicle does not exist in the current picture frame, wherein the feature similarity can be calculated based on Manhattan distance, Minkowski distance, and Euclidean distance representation.

[0074] The embodiment of the present application provides a vehicle image recognition method, namely, performing image feature extraction on the current image frame using a first image feature extraction model to obtain at least one first image feature corresponding to the current image frame; performing image feature extraction on the standard vehicle image using a second image feature extraction model to obtain a second image feature corresponding to the standard vehicle image; and determining whether the current image frame contains the target vehicle based on the feature similarity between each of the first image features and the second image features. Compared to an image recognition method that only uses an image classification model to identify whether the current image frame contains the target vehicle, the embodiment of the present application compares the feature similarity between image features in different image regions of the current image frame and image features corresponding to the standard vehicle image to further identify whether the current image frame contains the target vehicle, thereby achieving the purpose of accurately identifying the target vehicle and avoiding the situation where a vehicle in the current image frame that is too similar to the target vehicle is mistakenly identified as the target vehicle, thereby improving the accuracy of target vehicle recognition.

[0075] Example 3

[0076] The embodiment of the present application also provides a street light control device based on a roadside sensing system, referring to Figure 4 , the street light control device based on the roadside perception system includes:

[0077] An acquisition module 101 is configured to acquire actual distance information corresponding to a target vehicle upon receiving vehicle identification information broadcast by the target vehicle, wherein the actual distance information is used to represent the actual distance between the target vehicle and the streetlight to be controlled;

[0078] A determination module 102 is configured to determine whether the target vehicle is a light-controlled reference vehicle based on the vehicle identification information and the actual distance information;

[0079] A fusion module 103 is configured to obtain streetlight control information by fusing the vehicle identification information and the actual distance information.

[0080] The control module 104 is configured to control the streetlight to be controlled according to the streetlight control information.

[0081] Optionally, the determining module 102 is further configured to:

[0082] Get the current frame;

[0083] Detecting whether the target vehicle exists in the current image frame according to the vehicle identification information;

[0084] If so, obtaining the perceived distance information between the target vehicle and the street lamp to be controlled in the current image frame, and determining whether the target vehicle is the light control reference vehicle based on the correspondence between the actual distance information and the perceived distance information;

[0085] If not, the next picture frame is used as the current picture frame, and the process returns to the step of detecting whether the target vehicle exists in the current picture frame according to the vehicle identification information.

[0086] Optionally, the determining module 102 is further configured to:

[0087] Matching the vehicle identification information with a standard vehicle image of the target vehicle;

[0088] By performing image recognition on the current image frame and the standard vehicle image, it is determined whether the target vehicle exists in the current image frame.

[0089] Optionally, the determining module 102 is further configured to:

[0090] Performing image feature extraction on the current picture frame using a first image feature extraction model to obtain at least one first image feature corresponding to the current picture frame;

[0091] performing image feature extraction on the standard vehicle image using a second image feature extraction model to obtain a second image feature corresponding to the standard vehicle image;

[0092] Based on the feature similarity between each of the first image features and the second image features, it is determined whether the target vehicle exists in the current image frame.

[0093] Optionally, the determining module 102 is further configured to:

[0094] Obtaining point cloud information of the driving section corresponding to the current picture frame;

[0095] Performing structured processing on the driving section point cloud information to obtain structured point cloud information;

[0096] Clustering the structured point cloud information into a preset number of point cloud clusters, and determining a target point cloud cluster in each of the point cloud clusters;

[0097] The target point cloud cluster feature vector corresponding to the target point cloud cluster is input into a preset distance recognition model to obtain the perceived distance information between the target vehicle and the street lamp to be controlled.

[0098] Optionally, the determining module 102 is further configured to:

[0099] detecting whether the actual distance information is consistent with the perceived distance information;

[0100] If so, determining that the target vehicle is the light-controlled reference vehicle;

[0101] If not, it is determined that the target vehicle is not the light control reference vehicle.

[0102] Optionally, the fusion module 103 is further configured to:

[0103] Detecting whether the actual distance corresponding to the actual distance information is not greater than a preset light control distance threshold;

[0104] If so, the vehicle identification information and the actual distance information are fused to obtain the street light control information.

[0105] The roadside sensing system-based streetlight control device provided by the present invention utilizes the roadside sensing system-based streetlight control method described in the aforementioned embodiments to address the technical issue of low streetlight utilization on roads traveled by unmanned logistics vehicles. Compared to the prior art, the beneficial effects of the roadside sensing system-based streetlight control device provided by the embodiments of the present invention are the same as those of the roadside sensing system-based streetlight control method described in the aforementioned embodiments. Other technical features of the roadside sensing system-based streetlight control device are the same as those disclosed in the aforementioned embodiments and are not further elaborated here.

[0106] Example 4

[0107] An embodiment of the present invention provides an electronic device, which includes: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions that can be executed by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can execute the street light control method based on the roadside perception system in the above-mentioned embodiment one.

[0108] Reference below Figure 5 , which shows a schematic diagram of the structure of an electronic device suitable for implementing the embodiments of the present disclosure. The electronic devices in the embodiments of the present disclosure may include, but are not limited to, mobile terminals such as mobile phones, laptop computers, digital broadcast receivers, PDAs (personal digital assistants), PADs (tablet computers), PMPs (portable multimedia players), in-vehicle terminals (e.g., in-vehicle navigation terminals), and fixed terminals such as digital TVs and desktop computers. Figure 5 The electronic device shown is only an example and should not limit the functions and scope of use of the embodiments of the present disclosure.

[0109] like Figure 5 As shown, the electronic device may include a processing device 1001 (e.g., a central processing unit, a graphics processing unit, etc.), which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM) 1002 or a program loaded from a storage device 1003 into a random access memory (RAM) 1004. Various programs and data required for the operation of the electronic device are also stored in the RAM 1004. The processing device 1001, the ROM 1002, and the RAM 1004 are connected to each other via a bus 1005. An input / output (I / O) interface 1006 is also connected to the bus.

[0110] Typically, the following systems can be connected to the I / O interface 1006: input devices 1007 including, for example, a touch screen, touchpad, keyboard, mouse, image sensor, microphone, accelerometer, gyroscope, etc.; output devices 1008 including, for example, a liquid crystal display (LCD), speaker, vibrator, etc.; storage devices 1003 including, for example, a magnetic tape, hard disk, etc.; and communication devices 1009. The communication devices can allow the electronic device to communicate with other devices wirelessly or by wire to exchange data. Although the figure shows an electronic device with various systems, it should be understood that it is not required to implement or have all of the systems shown. More or fewer systems may be implemented or have instead.

[0111] In particular, according to an embodiment of the present disclosure, the process described above with reference to the flowchart can be implemented as a computer software program. For example, an embodiment of the present disclosure includes a computer program product, which includes a computer program carried on a computer-readable medium, and the computer program includes program code for executing the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from the network via the communication device 1009, or installed from the storage device 1003, or installed from the ROM 1002. When the computer program is executed by the processing device 1001, the above-mentioned functions defined in the method of the embodiment of the present disclosure are performed.

[0112] The electronic device provided by the present invention utilizes the roadside sensing system-based streetlight control method described in the aforementioned embodiment to address the technical issue of low streetlight utilization on roads traveled by unmanned logistics vehicles. Compared to the prior art, the electronic device provided by the present invention achieves the same beneficial effects as the roadside sensing system-based streetlight control method described in the aforementioned embodiment. Other technical features of the electronic device are the same as those disclosed in the aforementioned embodiment and are not further elaborated here.

[0113] It should be understood that various parts of the present disclosure can be implemented with hardware, software, firmware or a combination thereof. In the description of the above embodiments, specific features, structures, materials or characteristics can be combined in any one or more embodiments or examples in an appropriate manner.

[0114] 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 modifications or substitutions that can be easily conceived by a person skilled in the art within the technical scope disclosed in the present invention should be included in the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be based on the scope of protection of the claims.

[0115] Example 5

[0116] This embodiment provides a computer-readable storage medium having computer-readable program instructions stored thereon, and the computer-readable program instructions are used to execute the street light control method based on the roadside perception system in the above embodiment.

[0117] The computer-readable storage medium provided in the embodiment of the present invention can be, for example, a USB flash drive, but is not limited to electrical, magnetic, optical, electromagnetic, infrared, or semiconductor systems, systems or devices, or any combination thereof. More specific examples of computer-readable storage media can include, but are not limited to: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), 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 thereof. In this embodiment, the computer-readable storage medium can be any tangible medium that contains or stores a program that can be used by or in combination with an instruction execution system, system or device. The program code contained on the computer-readable storage medium can be transmitted using any appropriate medium, including but not limited to: wires, optical cables, RF (radio frequency), etc., or any suitable combination thereof.

[0118] The computer-readable storage medium may be included in the electronic device, or may exist independently without being incorporated into the electronic device.

[0119] The above-mentioned computer-readable storage medium carries one or more programs. When the above-mentioned one or more programs are executed by an electronic device, the electronic device: if vehicle identification information broadcast by a target vehicle is received, obtains actual distance information corresponding to the target vehicle, wherein the actual distance information is used to characterize the actual distance between the target vehicle and the street light to be controlled; determines whether the target vehicle is a light control reference vehicle based on the vehicle identification information and the actual distance information; if so, obtains street light control information by fusing the vehicle identification information and the actual distance information; and controls the street light to be controlled based on the street light control information.

[0120] Computer program code for performing the operations of the present disclosure may be written in one or more programming languages, or a combination thereof, including object-oriented programming languages ​​such as Java, Smalltalk, C++, and conventional procedural programming languages ​​such as "C" or similar programming languages. The program code may be executed entirely on the user's computer, partially on the user's computer, as a stand-alone software package, partially on the user's computer and partially on a remote computer, or entirely on the remote computer or server. In cases involving a remote computer, the remote computer may be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computer (e.g., through the Internet using an Internet service provider).

[0121] The flow charts and block diagrams in the accompanying drawings illustrate the possible implementation architecture, functions and operations of the system, method and computer program product according to various embodiments of the present invention. In this regard, each box in the flow chart or block diagram can represent a module, program segment, or a part of code, and the module, program segment, or a part of code contains one or more executable instructions for realizing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the box can also occur in a different order than that marked in the accompanying drawings. For example, two boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the block diagram and / or flow chart, and the combination of the boxes in the block diagram and / or flow chart, can be implemented with a dedicated hardware-based system that performs the specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions.

[0122] The modules involved in the embodiments described in this disclosure may be implemented in software or hardware, wherein the name of a module does not necessarily limit the unit itself.

[0123] The computer-readable storage medium provided by the present invention stores computer-readable program instructions for executing the aforementioned roadside sensing system-based streetlight control method, addressing the technical issue of low streetlight utilization on roads traveled by unmanned logistics vehicles. Compared to the prior art, the beneficial effects of the computer-readable storage medium provided by the present invention are similar to those of the roadside sensing system-based streetlight control method provided by the aforementioned embodiment, and are not further elaborated here.

[0124] Example 6

[0125] The present application also provides a computer program product, including a computer program, which, when executed by a processor, implements the steps of the above-mentioned street light control method based on the roadside perception system.

[0126] The computer program product provided in this application solves the technical problem of low streetlight utilization on roads traveled by unmanned logistics vehicles. Compared with the prior art, the beneficial effects of the computer program product provided by the embodiments of the present invention are the same as those of the roadside sensing system-based streetlight control method provided in the above embodiments, and are not further elaborated here.

[0127] The above are only preferred embodiments of the present application and do not limit the patent scope of the present application. Any equivalent structure or equivalent process transformation made using the contents of the present application specification and drawings, or directly or indirectly applied in other related technical fields, are also included in the patent processing scope of the present application.

Claims

1. A streetlight control method based on a roadside perception system, characterized in that: The streetlight control method based on the roadside perception system includes: If the vehicle identification information broadcast by the target vehicle is received, the actual distance information corresponding to the target vehicle is obtained, wherein the actual distance information is used to represent the actual distance between the target vehicle and the streetlight to be controlled; Get the current frame; Detecting whether the target vehicle exists in the current image frame according to the vehicle identification information; If the target vehicle exists in the current image frame, acquiring the perceived distance information between the target vehicle and the street lamp to be controlled in the current image frame, and determining whether the target vehicle is a light control reference vehicle based on the correspondence between the actual distance information and the perceived distance information; If the target vehicle does not exist in the current picture frame, the next picture frame is used as the current picture frame, and the process returns to the step of detecting whether the target vehicle exists in the current picture frame according to the vehicle identification information; If it is determined that the target vehicle is the light control reference vehicle, street light control information is obtained by fusing the vehicle identification information and the actual distance information; The streetlight to be controlled is controlled according to the streetlight control information.

2. The streetlight control method based on the roadside perception system according to claim 1, characterized in that: The step of detecting whether the target vehicle exists in the current picture frame based on the vehicle identification information includes: Matching the vehicle identification information with a standard vehicle image of the target vehicle; By performing image recognition on the current image frame and the standard vehicle image, it is determined whether the target vehicle exists in the current image frame.

3. The streetlight control method based on the roadside perception system according to claim 2, characterized in that: The step of determining whether the target vehicle exists in the current picture frame by performing image recognition on the current picture frame and the standard vehicle image comprises: Performing image feature extraction on the current picture frame using a first image feature extraction model to obtain at least one first image feature corresponding to the current picture frame; Performing image feature extraction on the standard vehicle image using a second image feature extraction model to obtain a second image feature corresponding to the standard vehicle image; Based on the feature similarity between each of the first image features and the second image features, it is determined whether the target vehicle exists in the current image frame.

4. The streetlight control method based on the roadside perception system according to claim 1, characterized in that: The step of obtaining the perceived distance information between the target vehicle and the street lamp to be controlled in the current picture frame includes: Obtaining point cloud information of the driving section corresponding to the current picture frame; Performing structured processing on the driving section point cloud information to obtain structured point cloud information; Clustering the structured point cloud information into a preset number of point cloud clusters, and determining a target point cloud cluster in each of the point cloud clusters; The target point cloud cluster feature vector corresponding to the target point cloud cluster is input into a preset distance recognition model to obtain the perceived distance information between the target vehicle and the street lamp to be controlled.

5. The streetlight control method based on the roadside perception system according to claim 1, characterized in that: The step of determining whether the target vehicle is a light control reference vehicle based on the correspondence between the actual distance information and the perceived distance information includes: detecting whether the actual distance information is consistent with the perceived distance information; If so, determining that the target vehicle is the light-controlled reference vehicle; If not, it is determined that the target vehicle is not the light control reference vehicle.

6. The streetlight control method based on the roadside perception system according to claim 1, characterized in that: The step of obtaining street light control information by fusing the vehicle identification information and the actual distance information includes: Detecting whether the actual distance corresponding to the actual distance information is not greater than a preset light control distance threshold; If so, the vehicle identification information and the actual distance information are fused to obtain the street light control information.

7. A streetlight control device based on a roadside sensing system, characterized in that: The street light control device based on the roadside perception system includes: An acquisition module is configured to acquire actual distance information corresponding to a target vehicle upon receiving vehicle identification information broadcast by the target vehicle, wherein the actual distance information is used to represent the actual distance between the target vehicle and the streetlight to be controlled; A determination module is configured to obtain a current picture frame; detect whether the target vehicle exists in the current picture frame based on the vehicle identification information; if the target vehicle exists in the current picture frame, obtain the perceived distance information between the target vehicle and the street lamp to be controlled in the current picture frame, and determine whether the target vehicle is a light control reference vehicle based on the correspondence between the actual distance information and the perceived distance information; if the target vehicle does not exist in the current picture frame, use the next picture frame as the current picture frame, and return to the step of detecting whether the target vehicle exists in the current picture frame based on the vehicle identification information; a fusion module, configured to obtain streetlight control information by fusing the vehicle identification information and the actual distance information if the target vehicle is determined to be the streetlight control reference vehicle; A control module is used to control the streetlight to be controlled according to the streetlight control information.

8. An electronic device, characterized in that: The electronic device comprises: at least one processor; and, a memory communicatively connected to the at least one processor; wherein, The memory stores instructions that can be executed by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to perform the steps of the street light control method based on the roadside perception system according to any one of claims 1 to 6.

9. A computer-readable storage medium, characterized in that The computer-readable storage medium stores a program for implementing a street light control method based on a roadside perception system, and the program for implementing a street light control method based on a roadside perception system is executed by a processor to implement the steps of the street light control method based on a roadside perception system as described in any one of claims 1 to 6.

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