Vehicle abnormal behavior early warning method and device, electronic equipment and storage medium

Abstract

The invention relates to the technical field of traffic early warning, and provides a vehicle abnormal behavior early warning method and device, electronic equipment and a storage medium. The method comprises the following steps: acquiring attribute information and state information of each vehicle in a target area; determining a current traffic road condition of the target area according to the attribute information and the state information of each vehicle; if it is monitored that there is an abnormal behavior vehicle in each vehicle, predicting a future traffic road condition of the target area according to the abnormal behavior of the abnormal behavior vehicle and the current traffic road condition; and determining whether to execute early warning operation or not according to the future traffic road condition. Through the setting, when the vehicle with the abnormal behavior is monitored, the future traffic road condition is predicted according to the abnormal behavior of the vehicle with the abnormal behavior and the current traffic road condition, and then whether the early warning operation is executed or not is evaluated according to the predicted future traffic road condition, so that the early warning can be prevented from being excessive; and the rationality of early warning the abnormal behaviors of the vehicle is improved.

Description

Technical Field

[0001] This application relates to the technical field of traffic warning, and particularly to a warning method, device, electronic device and storage medium for abnormal vehicle behaviors. Background Art

[0002] The safety and efficiency of vehicle passing are the core research directions in the field of public transportation. Abnormal vehicle behaviors, such as fatigue driving, speeding, slow driving, dangerous following, sudden braking, illegal parking, abnormal driving trajectories, reverse driving and U-turns, etc., are the main reasons affecting the safe and efficient passing of vehicles. Therefore, it is of great significance to detect and warn against abnormal vehicle behaviors. Existing technologies generally use video data of roads and detect and judge vehicle trajectories with the help of other vehicle detection devices to identify abnormal behavior vehicles, and then warnings can be issued to abnormal behavior vehicles and surrounding vehicles by means of telephone, alarm, etc. However, in some cases, the abnormal behaviors of vehicles do not actually affect the safe and efficient passing of vehicles, but warnings are still issued at this time, that is, there is a problem of over-warning. Summary of the Invention

[0003] In view of this, the embodiments of this application provide a warning method, device, electronic device and storage medium for abnormal vehicle behaviors, which can prevent over-warning and improve the rationality of warning against abnormal vehicle behaviors.

[0004] The first aspect of the embodiments of this application provides a warning method for abnormal vehicle behaviors, including:

[0005] Obtain the attribute information and status information of each vehicle in the target area;

[0006] Determine the current traffic conditions of the target area according to the attribute information and status information of each vehicle;

[0007] If an abnormal behavior vehicle is detected among the vehicles, predict the future traffic conditions of the target area according to the abnormal behavior of the abnormal behavior vehicle and the current traffic conditions;

[0008] Determine whether to perform a warning operation according to the future traffic conditions.

[0009] In the embodiment of the present application, first, obtain the attribute information and status information of each vehicle in the target area, such as information on the type, size, position, speed, and heading angle of the vehicle; then, determine the current traffic conditions in the target area according to the attribute information and status information of each vehicle, such as traffic flow, the proportion and quantity of various vehicle types, etc.; during the process of monitoring abnormal vehicle behaviors, if an abnormal behavior vehicle is found, predict the future traffic conditions in the target area according to the abnormal behavior of the abnormal behavior vehicle and the current traffic conditions; finally, determine whether to execute a warning operation according to the future traffic conditions. By setting it in this way, when an abnormal behavior vehicle is monitored, the future traffic conditions will be predicted first according to the abnormal behavior of the abnormal behavior vehicle and the current traffic conditions, and then it will be evaluated whether to execute a warning operation according to the predicted future traffic conditions, that is, a warning will be issued only when it is evaluated that the abnormal behavior of the vehicle will actually affect the traffic conditions, so as to prevent over-warning and improve the rationality of warning against abnormal vehicle behaviors.

[0010] In one implementation manner of the embodiment of the present application, obtaining the attribute information and status information of each vehicle in the target area includes:

[0011] Obtain the attribute information and status information of each vehicle in the target area sensed by the roadside sensing system;

[0012] According to the attribute information and status information of each vehicle, determining the current traffic conditions in the target area includes:

[0013] Map the attribute information and status information of each vehicle to the traffic simulation system in real time for traffic condition simulation calculation to obtain the current traffic conditions in the target area; wherein, the roadside sensing system and the traffic simulation system use the same high-precision map and clock source.

[0014] In one implementation manner of the embodiment of the present application, predicting the future traffic conditions in the target area according to the abnormal behavior of the abnormal behavior vehicle and the current traffic conditions includes:

[0015] Execute acceleration simulation by the traffic simulation system according to the current traffic conditions, and deduce the impact of the abnormal behavior of the abnormal behavior vehicle on the traffic conditions in the target area after the simulation duration, so as to obtain the future traffic conditions in the target area; wherein, the simulation duration is determined according to the type of the abnormal behavior.

[0016] In one implementation manner of the embodiment of the present application, determining whether to execute a warning operation according to the future traffic conditions includes:

[0017] Determine whether an abnormal traffic event will occur in the target area according to the future traffic conditions;

[0018] If an abnormal traffic event will occur in the target area, determine the type and relevant parameters of the abnormal traffic event;

[0019] Determine whether to execute a warning operation according to the type and relevant parameters of the abnormal traffic event.

[0020] In one implementation manner of the embodiment of the present application, determining whether to execute a warning operation according to the type and relevant parameters of the abnormal traffic event includes:

[0021] If the type of the abnormal traffic event is a specified type, or the relevant parameters of the abnormal traffic event exceed a set threshold, determine to execute a warning operation.

[0022] In one implementation manner of the embodiment of the present application, after determining whether to execute a warning operation according to the future traffic conditions, it further includes:

[0023] If it is determined to execute a warning operation, send a warning message to the abnormal behavior vehicle and the vehicles in the surrounding and upstream areas of the abnormal behavior vehicle among each vehicle through the roadside induction device.

[0024] In one implementation manner of the embodiment of the present application, whether any vehicle among each vehicle is an abnormal behavior vehicle is monitored by the following method:

[0025] Obtain the driving trajectory and driving behavior information of the any vehicle;

[0026] Input the driving trajectory and driving behavior information into a pre-constructed vehicle abnormal behavior recognition model for matching processing, and determine whether the any vehicle is an abnormal behavior vehicle according to the result of the matching processing.

[0027] The second aspect of the embodiment of the present application provides a warning device for vehicle abnormal behavior, including:

[0028] An information acquisition module, configured to acquire the attribute information and status information of each vehicle in the target area;

[0029] A current traffic condition determination module, configured to determine the current traffic condition of the target area according to the attribute information and status information of each vehicle;

[0030] A future traffic condition prediction module, configured to predict the future traffic condition of the target area according to the abnormal behavior of the abnormal behavior vehicle and the current traffic condition if it is monitored that there is an abnormal behavior vehicle among each vehicle;

[0031] A warning judgment module, configured to determine whether to execute a warning operation according to the future traffic condition.

[0032] A third aspect of the embodiments of the present application provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it implements the warning method for abnormal vehicle behaviors provided in the first aspect of the embodiments of the present application.

[0033] A fourth aspect of the embodiments of the present application provides a computer-readable storage medium storing a computer program, which, when executed by a processor, implements the warning method for abnormal vehicle behaviors provided in the first aspect of the embodiments of the present application.

[0034] A fifth aspect of the embodiments of the present application provides a computer program product, which, when running on an electronic device, causes the electronic device to execute the warning method for abnormal vehicle behaviors provided in the first aspect of the embodiments of the present application.

[0035] It can be understood that the beneficial effects of the above second to fifth aspects can be referred to the relevant descriptions in the first aspect above, and will not be elaborated here. BRIEF DESCRIPTION OF THE DRAWINGS

[0036] Figure 1 is a flowchart of a warning method for abnormal vehicle behaviors provided by an embodiment of the present application;

[0037] Figure 2 is an operation schematic diagram of the warning method for abnormal vehicle behaviors provided by an embodiment of the present application in an actual application scenario;

[0038] Figure 3 is a schematic structural diagram of a warning device for abnormal vehicle behaviors provided by an embodiment of the present application;

[0039] Figure 4 is a schematic diagram of an electronic device provided by an embodiment of the present application. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0040] In the following description, specific details such as specific system structures and technologies are presented for the purpose of illustration rather than limitation, so as to thoroughly understand the embodiments of the present application. However, those skilled in the art should clearly understand that the present application can also be implemented in other embodiments without these specific details. In other cases, detailed descriptions of well-known systems, devices, circuits, and methods are omitted to avoid unnecessary details from interfering with the description of the present application. Additionally, in the description of the specification and claims of the present application, the terms "first", "second", "third", etc. are only used for distinguishing descriptions and cannot be understood as indicating or implying relative importance.

[0041] The detection and early warning of abnormal vehicle behaviors are of great significance. However, in the existing technologies, when an abnormal vehicle is detected, an immediate early warning is issued, and there is a problem of over-early warning in some cases. In view of this, the embodiments of the present application provide a method, device, electronic device, and storage medium for early warning of abnormal vehicle behaviors, which can prevent over-early warning and improve the rationality of early warning of abnormal vehicle behaviors. For more specific technical implementation details of the embodiments of the present application, please refer to the method embodiments described below.

[0042] It should be understood that the execution subject of each method embodiment of the present application is various types of electronic devices. For example, it can be a mobile phone, a tablet computer, a wearable device, a vehicle-mounted device, an augmented reality (AR) / virtual reality (VR) device, a laptop computer, an ultra-mobile personal computer (UMPC), a netbook, a personal digital assistant (PDA), a large-screen TV, etc. The specific type of the electronic device is not limited in the embodiments of the present application.

[0043] Please refer to Figure 1 , which shows a method for early warning of abnormal vehicle behaviors provided by the embodiments of the present application, including:

[0044] 101. Obtain the attribute information and status information of each vehicle in the target area;

[0045] It should be understood that the execution subject of this method embodiment can be an electronic device used to early warn of abnormal vehicle behaviors. This electronic device can be connected to a roadside perception system in a road scene to obtain vehicle information within a certain range area (i.e., the target area) sensed by the roadside perception system. Here, the vehicle information can include the attribute information and status information of each vehicle. Among them, the attribute information can include the type and size of the vehicle, etc.; the status information can include the real-time position, longitude and latitude, speed, and heading angle of the vehicle, etc.

[0046] In an implementation manner of the embodiments of the present application, obtaining the attribute information and status information of each vehicle in the target area includes:

[0047] Obtain the attribute information and status information of each vehicle in the target area sensed by the roadside perception system.

[0048] The roadside perception system generally includes lidar, high-definition cameras, and various other types of sensors. Using the roadside perception system, the attribute information and status information of each vehicle within a certain range can be perceived in real time. After establishing a communication connection with the roadside perception system, this electronic device can obtain the attribute information and status information of each vehicle in the target area perceived by the roadside perception system.

[0049] 102. Determine the current traffic conditions of the target area based on the attribute information and status information of each vehicle;

[0050] After obtaining the attribute information and status information of each vehicle in the target area, this electronic device can determine the current traffic conditions of the target area based on the attribute information and status information of each vehicle. This step can be understood as determining the current traffic situation and conditions of the target area based on information such as the type, size, real-time position, speed, and heading angle of each vehicle in the target area, such as cross-sectional traffic flow, the proportion of various vehicle types, the number of various vehicle types, and driving speed, and so on.

[0051] In one implementation manner of the embodiments of the present application, determining the current traffic conditions of the target area based on the attribute information and status information of each vehicle includes:

[0052] Real-time map the attribute information and status information of each vehicle to a traffic simulation system for traffic condition simulation calculation to obtain the current traffic conditions of the target area; wherein, the roadside perception system and the traffic simulation system use the same high-precision map and clock source.

[0053] A traffic simulation system based on microscopic traffic simulation technology can be installed in this electronic device. Microscopic traffic simulation technology is a technology that uses mathematical models to replicate and analyze actual traffic systems. When simulating, it focuses on the behaviors of individual vehicles and pedestrians and can simulate various driving behaviors of vehicles, such as vehicle acceleration, deceleration, turning, and lane changing. In specific operations, the simulation range of the traffic simulation system can be made consistent with the perception range of the roadside perception system, and the attribute information and status information of each vehicle perceived by the roadside perception system are real-time mapped to the traffic simulation system for traffic condition simulation calculation, thereby obtaining the current traffic conditions of the target area. In addition, to improve the synchronization of simulation data and real vehicle data, the roadside perception system and the traffic simulation system use the same high-precision map and clock source, thereby ensuring the time and space alignment of simulation data and real vehicle data.

[0054] 103. If an abnormal behavior vehicle is detected among the vehicles, predict the future traffic conditions of the target area based on the abnormal behavior of the abnormal behavior vehicle and the current traffic conditions;

[0055] The electronic device also monitors each vehicle in the target area in real time to identify vehicles with abnormal behaviors. If a vehicle with an abnormal behavior is detected among the vehicles, the future traffic conditions of the target area will be predicted based on the abnormal behavior of the vehicle with the abnormal behavior and the current traffic conditions, that is, the impact of the abnormal behavior of the vehicle with the abnormal behavior on the traffic conditions of the target area will be predicted.

[0056] In one implementation manner of the embodiment of the present application, whether any one of the vehicles is a vehicle with an abnormal behavior is monitored in the following manner:

[0057] (1) Obtain the driving trajectory and driving behavior information of the any one vehicle;

[0058] (2) Input the driving trajectory and driving behavior information into a pre-constructed vehicle abnormal behavior recognition model for matching processing, and determine whether the any one vehicle is a vehicle with an abnormal behavior according to the result of the matching processing.

[0059] When the electronic device identifies whether a certain vehicle is a vehicle with an abnormal behavior, it can obtain the driving trajectory and driving behavior information of the vehicle. Among them, the driving trajectory can be sensed by a roadside sensing system and sent to the electronic device; the driving behavior information can be collected by an on-vehicle terminal of the vehicle and sent to the electronic device. The driving behavior information can include, but is not limited to: steering wheel control information, throttle and brake control information, and driver status information. In specific operations, various different vehicle abnormal behavior recognition models can be pre-constructed, and the driving trajectory and driving behavior information of the vehicle are respectively input into each vehicle abnormal behavior recognition model for matching processing. According to the result of the matching processing, it can be determined whether the vehicle has an abnormal behavior and what type of abnormal behavior exists. Various different vehicle abnormal behavior recognition models can include, but are not limited to: a recognition model for fatigue driving behavior, a recognition model for dangerous following behavior, a recognition model for sudden braking behavior, a recognition model for illegal parking behavior, a recognition model for U-turn behavior, and a recognition model for reverse driving behavior, etc. The training methods and working principles of these vehicle abnormal behavior recognition models can refer to the prior art and will not be elaborated here.

[0060] In one implementation manner of the embodiment of the present application, predicting the future traffic conditions of the target area based on the abnormal behavior of the vehicle with the abnormal behavior and the current traffic conditions includes:

[0061] Execute acceleration simulation according to the current traffic conditions through a traffic simulation system, and deduce the impact of the abnormal behavior of the vehicle with the abnormal behavior on the traffic conditions of the target area after the simulation duration, so as to obtain the future traffic conditions of the target area; wherein, the simulation duration is determined according to the type of the abnormal behavior.

[0062] If an abnormal behavior vehicle is detected, the traffic simulation system performs an acceleration simulation according to the current traffic conditions, predicts the states of each vehicle in the target area after a set simulation duration, and deduces the impact of the abnormal behavior of the abnormal behavior vehicle on the traffic conditions in the target area after this simulation duration, such as whether it will cause vehicle conflicts, whether it will cause vehicle collisions, whether it will cause vehicle congestion, the time and length of congestion, the change in interval vehicle speed, etc. Finally, the future traffic conditions in the target area are obtained. Among them, the simulation duration can be determined according to the type of abnormal behavior, that is, different types of abnormal behavior can be set with different simulation durations respectively, which can improve the accuracy of predicting future traffic conditions. For example, if the abnormal behavior of the abnormal behavior vehicle is a sudden brake, the impact it generates will be presented in a short time, so a shorter simulation duration can be set; if the abnormal behavior of the abnormal behavior vehicle is a U-turn or a reverse, the impact it generates may take some time to be presented, so a longer simulation duration can be set, and so on.

[0063] 104. Determine whether to perform a warning operation according to the future traffic conditions.

[0064] After predicting the future traffic conditions in the target area, determine whether to perform a warning operation according to this future traffic condition. Specifically, according to this future traffic condition, it can be judged whether the abnormal behavior of the vehicle will have an actual impact on the safe and efficient passage of each vehicle in the target area. If it will have an actual impact, a warning operation is performed; otherwise, no warning operation is performed, so as to avoid over-warning.

[0065] In an implementation manner of the embodiment of the present application, determining whether to perform a warning operation according to the future traffic conditions includes:

[0066] (1) According to the future traffic conditions, determine whether an abnormal traffic event will occur in the target area;

[0067] (2) If an abnormal traffic event will occur in the target area, determine the type and relevant parameters of the abnormal traffic event;

[0068] (3) According to the type and relevant parameters of the abnormal traffic event, determine whether to perform a warning operation.

[0069] Based on the predicted future traffic conditions, it is possible to predict whether abnormal traffic events will occur in the target area, such as whether vehicle conflicts, vehicle collisions, road congestion, or slow driving will occur. If it is determined that an abnormal traffic event will occur, the type and related parameters of the abnormal traffic event are obtained. Among them, the type can include vehicle conflicts, vehicle collisions, road congestion, or slow driving, etc.; the related parameters can include the severity of the conflict, the severity of the collision, the length of the road congestion, the duration of the road congestion, the average driving speed, etc. According to the type and related parameters of the abnormal traffic event, the severity of the impact brought by the abnormal vehicle behavior can be evaluated, so as to decide whether to issue a warning.

[0070] In one implementation manner of the embodiment of the present application, determining whether to perform a warning operation according to the type and related parameters of the abnormal traffic event includes:

[0071] If the type of the abnormal traffic event is a specified type, or the related parameters of the abnormal traffic event exceed the set threshold, it is determined to perform a warning operation.

[0072] If the type of the predicted abnormal traffic event is a relatively serious specified type, such as a vehicle collision, there is no need to consider other related parameters, and the warning operation is directly performed. If the predicted abnormal traffic event does not belong to a serious type, such as road congestion or slow driving, it is possible to further determine whether the related parameters of the abnormal traffic event exceed the set threshold, and the warning operation is performed only when the threshold is exceeded, otherwise the warning operation is not performed. For example, if the abnormal traffic event is road congestion, it is further determined whether the length of the road congestion or the duration of the road congestion exceeds the set threshold. If the threshold is exceeded, it means that the road congestion is serious and a warning operation needs to be performed, otherwise it means that the road is slightly congested and the warning operation may not be performed. Another example is that if the abnormal traffic event is slow driving, it is further determined whether the average driving speed is too small, or whether the average driving time within the section is too long. If so, it means that a serious slow driving event has occurred and a warning operation needs to be performed, otherwise the warning operation may not be performed.

[0073] In one implementation manner of the embodiment of the present application, after determining whether to perform a warning operation according to the future traffic conditions, it further includes:

[0074] If it is determined to perform a warning operation, warning information is sent to the abnormal behavior vehicle and the vehicles in the surrounding and upstream areas of the abnormal behavior vehicle among each vehicle through the roadside induction device.

[0075] If it is determined to execute the early warning operation, the electronic device may send relevant early warning information to the vehicle with abnormal behavior and the vehicles in the surrounding and upstream areas of the vehicle with abnormal behavior among all vehicles through the roadside induction device, so as to remind the driver of the vehicle with abnormal behavior and other affected vehicles in the surrounding area to pay attention to the possible abnormal traffic events, and decelerate and avoid in time to avoid danger. It should be noted that in addition to sending early warning information to relevant vehicles through the roadside induction device, the electronic device may also output early warning information through various other methods, and the embodiments of the present application do not make any limitations on this.

[0076] For ease of understanding, the following lists a practical application scenario. As Figure 2 shown, it is an operation schematic diagram of the early warning method for vehicle abnormal behavior provided by the embodiments of the present application in a practical application scenario.

[0077] Figure 2 Above shows the state data of each real vehicle sensed by the roadside perception system within a section of road, among which a certain vehicle A has an abnormal behavior of sudden braking. Figure 2 In the middle shows the state data of each simulated vehicle obtained after the state data of each real vehicle is mapped to the traffic simulation system in real time for traffic condition simulation calculation. Each simulated vehicle corresponds to each real vehicle one by one, and the current traffic condition of this section of road can be determined according to the state data of each simulated vehicle. In addition, through the sudden braking behavior recognition model, it can be recognized that vehicle A with the abnormal behavior of sudden braking appears. At this time, the traffic simulation system will perform acceleration simulation according to the current traffic condition, and deduce the impact of the sudden braking behavior of vehicle A on the traffic condition of this section of road after the set simulation duration, so as to obtain the future traffic condition of this section of road. Figure 2 Below shows the future traffic condition of this section of road. It can be seen that due to the sudden braking behavior of vehicle A, it may cause multiple vehicles upstream to drive slowly or traffic jams and other phenomena. If the phenomenon of slow driving or traffic jam is relatively serious, early warning information may be sent to vehicle A and multiple vehicles upstream through the roadside induction device to remind the drivers of each vehicle to pay attention to the upcoming traffic jam and other phenomena.

[0078] In the embodiments of the present application, first, obtain the attribute information and status information of each vehicle in the target area, such as information on the type, size, position, speed, and heading angle of the vehicle; then, determine the current traffic conditions in the target area according to the attribute information and status information of each vehicle, such as traffic flow, the proportion and quantity of various vehicle types, etc.; during the process of monitoring abnormal vehicle behaviors, if an abnormal behavior vehicle is found, predict the future traffic conditions in the target area according to the abnormal behavior of the abnormal behavior vehicle and the current traffic conditions; finally, determine whether to execute a warning operation according to the future traffic conditions. By setting it in this way, when an abnormal behavior vehicle is detected, the future traffic conditions will be predicted first according to the abnormal behavior of the abnormal behavior vehicle and the current traffic conditions, and then it will be evaluated whether to execute a warning operation according to the predicted future traffic conditions, that is, a warning will be issued only when it is evaluated that the abnormal behavior of the vehicle will actually affect the traffic conditions, so as to prevent over-warning and improve the rationality of warning against abnormal vehicle behaviors.

[0079] It should be understood that the magnitudes of the sequence numbers of the steps in the above various embodiments do not mean the order of execution. The execution order of each process should be determined according to its function and internal logic, and should not constitute any limitation to the implementation process of the embodiments of the present application.

[0080] The above mainly describes a warning method for abnormal vehicle behaviors. Next, a warning device for abnormal vehicle behaviors will be described.

[0081] Please refer to Figure 3 , an embodiment of a warning device for abnormal vehicle behaviors in the embodiments of the present application includes:

[0082] An information acquisition module 301, configured to acquire the attribute information and status information of each vehicle in the target area;

[0083] A current traffic condition determination module 302, configured to determine the current traffic conditions in the target area according to the attribute information and status information of each vehicle;

[0084] A future traffic condition prediction module 303, configured to predict the future traffic conditions in the target area according to the abnormal behavior of the abnormal behavior vehicle and the current traffic conditions if an abnormal behavior vehicle is detected among each vehicle;

[0085] A warning judgment module 304, configured to determine whether to execute a warning operation according to the future traffic conditions.

[0086] In an implementation manner of the embodiments of the present application, the information acquisition module includes:

[0087] An information acquisition unit, configured to acquire the attribute information and status information of each vehicle in the target area sensed by the roadside perception system;

[0088] The current traffic condition determination module includes:

[0089] A traffic condition simulation calculation unit, configured to map the attribute information and status information of each vehicle to a traffic simulation system in real time for traffic condition simulation calculation, so as to obtain the current traffic condition of the target area; wherein, the roadside perception system and the traffic simulation system use the same high-precision map and clock source.

[0090] In an implementation manner of the embodiment of the present application, the future traffic condition prediction module includes:

[0091] An acceleration simulation unit, configured to perform acceleration simulation through the traffic simulation system according to the current traffic condition, and deduce the influence of the abnormal behavior of the abnormal behavior vehicle on the traffic condition of the target area after the simulation duration, so as to obtain the future traffic condition of the target area; wherein, the simulation duration is determined according to the type of the abnormal behavior.

[0092] In an implementation manner of the embodiment of the present application, the warning judgment module includes:

[0093] A traffic event determination unit, configured to determine whether an abnormal traffic event will occur in the target area according to the future traffic condition;

[0094] A traffic event parameter determination unit, configured to determine the type and related parameters of the abnormal traffic event if an abnormal traffic event will occur in the target area;

[0095] A warning judgment unit, configured to determine whether to perform a warning operation according to the type and related parameters of the abnormal traffic event.

[0096] In an implementation manner of the embodiment of the present application, the warning judgment unit includes:

[0097] A warning subunit, configured to determine to perform a warning operation if the type of the abnormal traffic event is a specified type, or the related parameters of the abnormal traffic event exceed a set threshold.

[0098] In an implementation manner of the embodiment of the present application, the warning device for vehicle abnormal behavior further includes:

[0099] A warning module, configured to send a warning message to the abnormal behavior vehicle and the vehicles in the surrounding and upstream areas of the abnormal behavior vehicle among each vehicle if it is determined to perform a warning operation through a roadside induction device.

[0100] In an implementation manner of the embodiment of the present application, the warning device for vehicle abnormal behavior further includes:

[0101] A vehicle information acquisition module, configured to acquire the driving trajectory and driving behavior information of any one of the vehicles;

[0102] An abnormal vehicle recognition module is configured to input driving trajectory and driving behavior information into a pre-constructed vehicle abnormal behavior recognition model for matching processing, and determine whether any one of the vehicles is an abnormal behavior vehicle according to the result of the matching processing.

[0103] The embodiment of the present application further provides a computer-readable storage medium, which stores a computer program. When the computer program is executed by a processor, it implements the warning method for vehicle abnormal behavior as described in any one of the above embodiments.

[0104] The embodiment of the present application further provides a computer program product. When the computer program product runs on an electronic device, it causes the electronic device to execute the warning method for vehicle abnormal behavior as described in any one of the above embodiments.

[0105] Figure 4 is a schematic diagram of an electronic device provided by an embodiment of the present application. As Figure 4 shown, the electronic device 4 of this embodiment includes: a processor 40, a memory 41, and a computer program 42 stored in the memory 41 and executable on the processor 40. When the processor 40 executes the computer program 42, it implements the steps in the embodiments of the above warning methods for various vehicle abnormal behaviors, such as Figure 1 the steps 101 to 104 shown. Alternatively, when the processor 40 executes the computer program 42, it implements the functions of each module / unit in the above device embodiments, such as Figure 3 the functions of the modules 301 to 304 shown.

[0106] The computer program 42 can be divided into one or more modules / units. The one or more modules / units are stored in the memory 41 and executed by the processor 40 to complete the present application. The one or more modules / units can be a series of computer program instruction segments capable of performing specific functions, and these instruction segments are used to describe the execution process of the computer program 42 in the electronic device 4.

[0107] The so-called processor 40 may be a Central Processing Unit (CPU), or may also be other general-purpose processors, Digital Signal Processors (DSPs), Application Specific Integrated Circuits (ASICs), Field-Programmable Gate Arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor may be a microprocessor or the processor may also be any conventional processor, etc.

[0108] The memory 41 may be an internal storage unit of the electronic device 4, such as the hard disk or memory of the electronic device 4. The memory 41 may also be an external storage device of the electronic device 4, such as a plug-in hard disk equipped on the electronic device 4, a Smart Media Card (SMC), a Secure Digital (SD) card, a Flash Card, etc. Further, the memory 41 may also include both the internal storage unit of the electronic device 4 and the external storage device. The memory 41 is used to store the computer program and other programs and data required by the electronic device. The memory 41 may also be used to temporarily store data that has been output or is to be output.

[0109] Those skilled in the art can clearly understand that, for the convenience and simplicity of description, only the above division of each functional unit and module is used as an example. In actual applications, the above functions can be allocated to different functional units and modules according to needs, that is, the internal structure of the device is divided into different functional units or modules to complete all or part of the functions described above. Each functional unit and module in the embodiment may be integrated into one processing unit, or each unit may exist physically alone, or two or more units may be integrated into one unit. The above integrated unit may be implemented in the form of hardware or in the form of a software functional unit. In addition, the specific names of each functional unit and module are only for the convenience of mutual distinction and do not limit the protection scope of the present application. The specific working processes of the units and modules in the above system may refer to the corresponding processes in the foregoing method embodiments and will not be elaborated herein.

[0110] Those skilled in the art can clearly understand that, for the convenience and simplicity of description, the specific working processes of the system, device, and unit described above may refer to the corresponding processes in the foregoing method embodiments and will not be elaborated herein.

[0111] In the above embodiments, the descriptions of the various embodiments each have their own emphasis. For parts not described in detail or recorded in a certain embodiment, reference may be made to the relevant descriptions of other embodiments.

[0112] Those of ordinary skill in the art can realize that the units and algorithm steps of each example described in combination with the embodiments disclosed herein can be implemented by electronic hardware, or by a combination of computer software and electronic hardware. Whether these functions are executed in a hardware or software manner depends on the specific application and design constraints of the technical solution. Professional technicians can use different methods to implement the described functions for each specific application, but such implementation should not be considered to exceed the scope of this application.

[0113] In the embodiments provided in this application, it should be understood that the disclosed devices and methods can be implemented in other ways. For example, the system embodiments described above are merely illustrative. For example, the division of the modules or units is only a logical function division, and there may be other division methods in actual implementation. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the couplings or direct couplings or communication connections shown or discussed with each other can be through some interfaces, and the indirect couplings or communication connections of the devices or units can be in electrical, mechanical or other forms.

[0114] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place, or may be distributed to multiple network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiments of this application.

[0115] In addition, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically alone, or two or more units can be integrated into one unit. The above integrated units can be implemented in the form of hardware or in the form of software functional units.

[0116] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, to implement all or part of the processes in the above-mentioned embodiment methods of this application, it can also be completed by instructing relevant hardware through a computer program. The computer program can be stored in a computer-readable storage medium. When the computer program is executed by a processor, the steps of the above-mentioned various method embodiments can be implemented. Among them, the computer program includes computer program code, and the computer program code can be in the form of source code, object code, executable file, or some intermediate form, etc. The computer-readable medium can include: any entity or device that can carry the computer program code, recording medium, USB flash drive, mobile hard disk, magnetic disk, optical disc, computer memory, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), electrical carrier signal, telecommunication signal, and software distribution medium, etc. It should be noted that the content included in the computer-readable medium can be appropriately increased or decreased according to the requirements of legislation and patent practice in the jurisdiction. For example, in some jurisdictions, according to legislation and patent practice, the computer-readable medium does not include electrical carrier signals and telecommunication signals.

[0117] The above-mentioned embodiments are only used to illustrate the technical solutions of this application, rather than to limit it; although this application has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that: they can still modify the technical solutions recorded in the foregoing embodiments, or perform equivalent replacements on some of the technical features; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the various embodiments of this application, and should all be included in the protection scope of this application.

Claims

1. A warning method for abnormal vehicle behavior, characterized in that, Including: Obtain the attribute information and status information of each vehicle in the target area; Determine the current traffic condition of the target area according to the attribute information and status information of each vehicle; If an abnormal behavior vehicle is detected among the vehicles, predict the future traffic condition of the target area according to the abnormal behavior of the abnormal behavior vehicle and the current traffic condition; Determine whether to perform a warning operation according to the future traffic condition.

2. The method according to claim 1, wherein The obtaining of the attribute information and status information of each vehicle in the target area includes: Obtain the attribute information and status information of each vehicle in the target area sensed by the roadside perception system; The determining of the current traffic condition of the target area according to the attribute information and status information of each vehicle includes: Real-time map the attribute information and status information of each vehicle to a traffic simulation system for traffic condition simulation calculation to obtain the current traffic condition of the target area; wherein, the roadside perception system and the traffic simulation system use the same high-precision map and clock source.

3. The method according to claim 2, wherein The predicting of the future traffic condition of the target area according to the abnormal behavior of the abnormal behavior vehicle and the current traffic condition includes: Execute acceleration simulation through the traffic simulation system according to the current traffic condition, and deduce the impact of the abnormal behavior of the abnormal behavior vehicle on the traffic condition of the target area after the simulation duration, so as to obtain the future traffic condition of the target area; wherein, the simulation duration is determined according to the type of the abnormal behavior.

4. The method according to claim 1, wherein The determining of whether to perform a warning operation according to the future traffic condition includes: Determine whether an abnormal traffic event will occur in the target area according to the future traffic condition; If an abnormal traffic event will occur in the target area, determine the type and related parameters of the abnormal traffic event; Determine whether to perform a warning operation according to the type and related parameters of the abnormal traffic event.

5. The method according to claim 4, wherein The determining of whether to perform a warning operation according to the type and related parameters of the abnormal traffic event includes: If the type of the abnormal traffic event is a specified type, or the related parameters of the abnormal traffic event exceed the set threshold, determine to perform a warning operation.

6. The method according to claim 1, wherein After the determining of whether to perform a warning operation according to the future traffic condition, it further includes: If it is determined to perform a warning operation, send a warning message to the abnormal behavior vehicle and the vehicles in the surrounding and upstream areas of the abnormal behavior vehicle among the vehicles through roadside induction devices.

7. The method according to any one of claims 1 to 6, characterized in that Whether any vehicle among the vehicles is an abnormal behavior vehicle is monitored in the following manner: Obtain the driving trajectory and driving behavior information of the any vehicle; Input the driving trajectory and the driving behavior information into a pre-constructed vehicle abnormal behavior recognition model for matching processing, and determine whether the any vehicle is an abnormal behavior vehicle according to the result of the matching processing.

8. An early warning device for abnormal vehicle behavior, characterized in that, Including: An information acquisition module, configured to obtain the attribute information and status information of each vehicle in the target area; A current traffic condition determination module, configured to determine the current traffic condition of the target area according to the attribute information and status information of each vehicle; A future traffic condition prediction module, which is used to predict the future traffic conditions of the target area according to the abnormal behaviors of the abnormal behavior vehicles and the current traffic conditions if abnormal behavior vehicles are detected among the various vehicles; An early warning judgment module, which is used to determine whether to execute an early warning operation according to the future traffic conditions.

9. An electronic device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the early warning method for vehicle abnormal behaviors according to any one of claims 1 to 7.

10. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by the processor, it implements the early warning method for vehicle abnormal behaviors according to any one of claims 1 to 7.

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