Method for determining abnormal driving behavior and reference information and electronic equipment

Abstract

The embodiment of the invention provides a method for determining abnormal driving behaviors and reference information and electronic equipment. The method for determining the abnormal driving behavior comprises the following steps: acquiring geographic position information indicating the geographic position of a vehicle and driving angle information indicating the driving angle of the vehicle; determining a reference vehicle type and a reference driving angle corresponding to a grid region matched with the geographic position from the reference information based on the geographic position information; determining whether the type and the driving angle of the vehicle are consistent with a reference vehicle type and a reference driving angle respectively; and in response to determining that at least one of the type of the vehicle and the driving angle information is inconsistent with the corresponding reference vehicle type or the reference driving angle, enabling a warning component of the vehicle to provide warning information. Therefore, whether the vehicle has an abnormal driving behavior or not can be judged, and the abnormal driving behavior is reported to a driver in time.

Description

Technical Field

[0001] Embodiments of the present disclosure relate to the field of vehicle driving, and more specifically, to a method for determining abnormal driving behavior, a method for determining reference information, an electronic device, and a computer-readable storage medium. Background Art

[0002] In modern transportation systems, vehicles (such as bicycles, motorcycles, cars or electric cars, etc.) may have abnormal driving behaviors when driving on the road due to driver negligence, lack of driving experience, cognitive errors, etc. For example, vehicles occupy the road or drive in the opposite direction. These abnormal driving behaviors are not easy to correct in time, which not only increases the risk of accidents, but also brings troubles and dangers to other road users. Summary of the invention

[0003] The purpose of the present disclosure is to provide a method for determining abnormal driving behavior, an electronic device and a machine storage medium to at least partially solve the above-mentioned problems and / or other potential problems existing in the traditional determination of abnormal driving behavior of a mobile vehicle.

[0004] The first aspect of the present disclosure provides a method for determining abnormal driving behavior. The method includes: obtaining geographic location information indicating the geographic location of a vehicle and driving angle information indicating the driving angle of the vehicle; determining a reference vehicle type and a reference driving angle corresponding to a grid area matching the geographic location from reference information based on the geographic location information; determining whether the type and driving angle of the vehicle are consistent with the reference vehicle type and reference driving angle, respectively; and in response to determining that at least one of the type and driving angle information of the vehicle is inconsistent with the corresponding reference vehicle type or reference driving angle, causing a warning component of the vehicle to provide warning information.

[0005] In some embodiments, reference information is determined in the following manner: determining multiple grid areas in a target area to be detected, the multiple grid areas being indicated by range information representing multiple geographic ranges; determining a correspondence relationship between multiple vehicles and multiple grid areas based on a comparison of corresponding geographic locations of multiple vehicles during a predetermined period with the multiple geographic ranges; determining a reference vehicle type and a reference driving angle corresponding to each grid area in the multiple grid areas based on the correspondence relationship; and determining reference information based on the reference vehicle type and the reference driving angle.

[0006] In some embodiments, determining the correspondence relationship includes: determining corresponding geographic locations and corresponding driving angles of multiple vehicles; and for each grid area among multiple grid areas, determining at least one vehicle located in the grid area from the multiple vehicles based on the corresponding geographic locations of the multiple vehicles.

[0007] In some embodiments, determining a reference vehicle type and a reference driving angle includes: determining a reference driving angle of the grid area based on a driving angle of at least one vehicle located within the grid area; and determining a reference vehicle type based on a type of at least one vehicle located within the grid area.

[0008] In some embodiments, determining a reference vehicle type includes: determining whether the number of vehicles of the same predetermined type among at least one vehicle located within the grid area is greater than a predetermined number; and in response to determining whether the number of vehicles of the same predetermined type is greater than the predetermined number, determining the predetermined type as the reference vehicle type.

[0009] In some embodiments, determining the reference driving angle includes: determining the driving direction of at least one vehicle of the same predetermined type located in the grid area; and determining the reference driving angle corresponding to the predetermined grid area according to the driving direction of the vehicle of the same predetermined type.

[0010] In some embodiments, the range information includes latitude and longitude information or geocoding information.

[0011] In some embodiments, providing warning information includes at least one of the following: in response to determining that the type of the vehicle is inconsistent with the corresponding reference vehicle type, causing a warning component of the vehicle to provide lane-occupying warning information; and in response to determining that the driving angle of the vehicle is inconsistent with the corresponding reference driving angle, causing a warning component of the vehicle to provide wrong-way warning information.

[0012] In some embodiments, determining whether the driving angle of the vehicle is consistent with a reference driving angle includes: determining a deviation value between the driving angle and the reference driving angle; in response to determining that the deviation value is greater than a threshold deviation, determining that the driving angle of the vehicle is inconsistent with the reference driving angle.

[0013] A second aspect of the present disclosure provides a method for determining reference information. The method includes: determining a plurality of grid areas in a target area to be detected, the plurality of grid areas being indicated by range information representing a plurality of geographic ranges; determining a correspondence relationship between a plurality of vehicles and a plurality of grid areas based on a comparison of corresponding geographic locations of a plurality of vehicles with the plurality of geographic ranges during a predetermined period; determining a reference vehicle type and a reference driving angle corresponding to each of the plurality of grid areas based on the correspondence relationship; and determining reference information based on the reference vehicle type and the reference driving angle.

[0014] The third aspect of the present disclosure provides an electronic device, which includes: at least one processing unit; and at least one memory coupled to the at least one processing unit and storing machine executable instructions, which, when executed by the at least one processing unit, causes the device to execute the method according to the first aspect or the second aspect.

[0015] A fourth aspect of the present disclosure provides a computer-readable storage medium. A computer program product stored on the computer-readable storage medium includes machine-executable instructions, which, when executed, cause a machine to perform the steps of the method of the first aspect of the present disclosure. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] The above and other objects, features and advantages of the present disclosure will become more apparent through a more detailed description of exemplary embodiments of the present disclosure in conjunction with the accompanying drawings, wherein like reference numerals generally represent like components throughout the exemplary embodiments of the present disclosure.

[0017] Figure 1 shows a simplified schematic diagram of a portion of a vehicle according to an embodiment of the present disclosure;

[0018] Figure 2 A flow chart showing a method for determining abnormal driving behavior according to an embodiment of the present disclosure is shown;

[0019] Figure 3 A schematic diagram showing the distribution of types of vehicles in a grid area according to an embodiment of the present disclosure;

[0020] Figure 4 A schematic diagram showing the distribution of various types of transportation tools in a grid area according to an embodiment of the present disclosure;

[0021] Figure 5 A schematic diagram showing the distribution of vehicle types and driving angle information in a grid area according to an embodiment of the present disclosure;

[0022] Figure 6 A flowchart showing a method for determining reference information according to an embodiment of the present disclosure; and

[0023] Figure 7 A schematic block diagram of an electronic device suitable for implementing an embodiment of the present disclosure is shown. DETAILED DESCRIPTION

[0024] Embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. Although certain embodiments of the present disclosure are shown in the accompanying drawings, it should be understood that the present disclosure can be implemented in various forms and should not be construed as being limited to the embodiments described herein, which are instead provided for a more thorough and complete understanding of the present disclosure. It should be understood that the drawings and embodiments of the present disclosure are only for exemplary purposes and are not intended to limit the scope of protection of the present disclosure.

[0025] In the description of the embodiments of the present disclosure, the term "including" and similar terms should be understood as open inclusion, that is, "including but not limited to". The term "based on" should be understood as "based at least in part on". The term "one embodiment" or "the embodiment" should be understood as "at least one embodiment". The terms "first", "second", etc. may refer to different or the same objects. Other explicit and implicit definitions may also be included below.

[0026] The principles of the present disclosure will be described below with reference to several example embodiments shown in the accompanying drawings. Although preferred embodiments of the present disclosure are shown in the accompanying drawings, it should be understood that these embodiments are described only to enable those skilled in the art to better understand and implement the present disclosure, and are not intended to limit the scope of the present disclosure in any way.

[0027] In addition, the term "in response to" as used herein refers to a state in which a corresponding event occurs or a condition is satisfied. It will be understood that the timing of executing a subsequent action executed in response to the event or condition is not necessarily strongly related to the time when the event occurs or the condition is satisfied. For example, in some cases, the subsequent action may be executed immediately when the event occurs or the condition is satisfied; while in other cases, the subsequent action may be executed after a period of time after the event occurs or the condition is satisfied.

[0028] The embodiments of the present disclosure may involve user data, data acquisition and / or use, etc. These aspects are subject to the corresponding laws, regulations and relevant provisions. In the embodiments of the present disclosure, all data collection, acquisition, processing, processing, forwarding, use, etc. are carried out on the premise that the user knows and confirms. Accordingly, when implementing each embodiment of the present disclosure, the type, scope of use, usage scenario, etc. of the data or information that may be involved should be informed to the user and the user's authorization should be obtained in an appropriate manner in accordance with the relevant laws and regulations. The specific notification and / or authorization method can vary according to the actual situation and application scenario, and the scope of the present disclosure is not limited in this respect.

[0029] The solutions described in this specification and in the examples, if they involve the processing of personal information, will be processed on the premise of having a legal basis (such as obtaining the consent of the subject of personal information, or being necessary for the performance of a contract, etc.), and will only be processed within the scope of regulations or agreements. If a user refuses to process personal information other than the necessary information for basic functions, it will not affect the user's use of basic functions.

[0030] As mentioned above, in modern transportation systems, abnormal driving behaviors (e.g., occupying the road, driving against the traffic, etc.) of mobile vehicles (hereinafter referred to as vehicles, which can be bicycles, motorcycles, cars, electric cars, etc.) are very dangerous and illegal. And due to the driver's negligence, lack of driving experience, cognitive errors, etc., these abnormal driving behaviors are not easy to be corrected in time, which not only increases the risk of accidents, but also brings troubles and dangers to other road users.

[0031] At present, the existing technology mainly uses traffic cameras on the road to monitor vehicles or cameras on vehicles to make real-time judgments on road signs ahead. Installing a large number of cameras on roads or vehicles has the problems of high cost and difficult maintenance. At the same time, in the case of complex road topology, dense traffic or at night, the method of monitoring the driving behavior of vehicles through cameras on the road and / or on vehicles may not provide accurate identification results of occupying the lane and driving against the traffic.

[0032] In order to solve or at least partially solve the above-mentioned problems or other potential problems in determining abnormal driving behavior of mobile vehicles in traditional technologies, the embodiments of the present disclosure provide a method for determining abnormal driving behavior, which uses the correspondence between multiple vehicles and multiple grid areas within a predetermined period to determine the reference information of multiple grid areas, and then matches the reference vehicle type and reference driving angle of the corresponding reference information according to the geographical location information indicating the geographical location of the vehicle, and finally compares the type of the vehicle and the current driving angle information with the reference vehicle type and reference driving angle of the reference information, and when there is at least one inconsistency in the comparison between the type and driving angle information of the vehicle and the reference vehicle type and reference driving angle, a warning message is sent to the warning component of the vehicle. In this way, when the vehicle has abnormal driving behavior, it can be reported to the driver to assist the driver to calibrate the driving behavior in time and improve driving safety.

[0033] Figure 1 A simplified schematic diagram of a vehicle according to an embodiment of the present disclosure is shown. Figure 1As shown, the vehicle of the embodiment of the present disclosure includes a positioning module 105 and a vehicle computer 101. The positioning module 105 can send geographic location information (such as latitude and longitude coordinates or geocoding information) indicating the current geographic location of the vehicle and driving angle information (such as heading angle data) indicating the driving angle of the vehicle to the vehicle computer 101. The vehicle computer 101 includes a processing module 104, a communication module 103 and a storage module 102. After receiving the geographic location information and driving angle information sent by the positioning module 105, the processing module 104 sends the type of the vehicle where the vehicle computer 101 is located to the communication module 103 as driving data, and the communication module 103 reports it to the server.

[0034] In some embodiments, the vehicle further includes a warning component 106. The vehicle computer 101 can control the warning component 106 to operate after the vehicle has abnormal behavior, so as to issue at least one of a visual warning, an auditory warning, and a tactile warning to remind the driver. For example, the warning component 106 can include a display screen, and the display screen can remind the driver that the vehicle is currently in an abnormal driving state through images, text, etc. The warning component 106 can also be a speaker or a buzzer, etc., which reminds the driver that the vehicle is currently in an abnormal driving state through sound. The warning component 106 can also be a vibrator, which contacts and vibrates the driver to remind the driver that the vehicle is currently in an abnormal driving state.

[0035] The above vehicle computer 101, positioning module 105 and warning component 106 can be controlled and exchange information data through a bus 107, wherein the bus 107 includes but is not limited to a serial port, SPI, CAN, etc.

[0036] Figure 2 FIG. 2 is a flow chart showing a method 200 for determining abnormal driving behavior according to an embodiment of the present disclosure. The method may be executed by a control unit of a cloud server that communicates with a vehicle. Figure 2 As shown, in block 210, the control unit of the cloud server obtains geographic location information indicating the geographic location of the vehicle and driving angle information indicating the driving angle of the vehicle. For example, the control unit can obtain the geographic location information and driving angle information of the corresponding vehicle from the vehicle.

[0037] Specifically, when a vehicle is traveling on a road, the processing module of the vehicle periodically obtains the driving data of the vehicle at a predetermined interval, and reports the driving data to a remote server (i.e., a cloud server) in real time. The driving data includes at least geographic location information indicating the current geographic location of the vehicle, driving angle information indicating the driving angle of the vehicle, and the type of the vehicle.

[0038] In some alternative embodiments, the control unit may also obtain the above information from other devices such as a roadside high-precision image capture device. The embodiments of the present disclosure mainly take the control unit obtaining the geographic location information and driving angle information of the corresponding vehicle from the vehicle as an example to describe the concept of the present disclosure. It should be understood that the situation of obtaining from other devices is similar and will not be described separately below.

[0039] In box 220, the cloud server determines the reference vehicle type and reference driving angle corresponding to the grid area matching the geographical location from the reference information based on the geographical location information. In some embodiments, the reference information here can be a database stored in a memory coupled to the control unit of the server. Specifically, after the server receives multiple sets of driving data reported by multiple vehicles in different periods, it can construct reference information based on these driving data. The reference information is stored in the form of a database in the server or the vehicle computer so that it can be called when detecting the driving behavior of the vehicle. The construction and storage method of the reference information (i.e., the database) will be further explained below.

[0040] In block 230, the cloud server determines whether the type and driving angle of the vehicle are consistent with the reference vehicle type and reference driving angle in the reference information, respectively. That is, when it is necessary to detect the driving behavior of the vehicle, the server or the vehicle computer calls the reference information in the corresponding grid area according to the current geographical location information of the vehicle, and compares the type and driving angle information of the vehicle with the reference vehicle type and reference driving angle in the reference information, respectively.

[0041] In block 240, if the cloud server determines that at least one of the vehicle type and the driving angle information is inconsistent with the corresponding reference vehicle type or reference driving angle, the warning component of the vehicle will be caused to provide warning information. That is, according to the comparison result, when at least one of the items is inconsistent, the vehicle computer controls the warning component of the vehicle to issue a warning message (when the comparison occurs in the vehicle computer, the vehicle computer can directly control the warning component to issue a warning message according to the comparison result. When the comparison occurs inside the server, the server sends a command to the vehicle computer, which in turn causes the vehicle computer to control the warning component to issue a warning message).

[0042] In some embodiments, the reference information can be determined by the server in the following manner. First, the server determines a plurality of grid areas in the target area to be detected, and the plurality of grid areas are indicated by range information representing a plurality of geographical ranges. Next, the server determines the correspondence relationship between the plurality of vehicles and the plurality of grid areas based on a comparison of the corresponding positions of the plurality of vehicles with the plurality of geographical ranges during a predetermined period. Then, the server determines the reference vehicle type and the reference driving angle corresponding to each of the plurality of grid areas based on the correspondence relationship. Finally, the server determines the reference information based on the reference vehicle type and the reference driving angle, and stores it in a memory.

[0043] In some embodiments, the server may determine the corresponding geographic locations and corresponding travel angles of the plurality of vehicles. Then, for each grid area in the plurality of grid areas, the server determines at least one vehicle located in the grid area from the plurality of vehicles based on the corresponding geographic locations of the plurality of vehicles.

[0044] In some embodiments, the server determines a reference driving angle of the grid area based on a driving angle of at least one vehicle located in the grid area. The server also determines a reference vehicle type based on a type of at least one vehicle located in the grid area.

[0045] In some embodiments, when determining the reference vehicle type, the server determines whether the number of vehicles of the same predetermined type among the at least one vehicle located in the grid area is greater than a predetermined number. If it is determined whether the number of vehicles of the same predetermined type is greater than a predetermined number, the server determines the predetermined type as the reference vehicle type.

[0046] In some embodiments, when determining the reference driving angle, the server determines the driving direction of a vehicle of the same predetermined type as at least one vehicle located in the grid area, and determines the reference driving angle corresponding to the predetermined grid area based on the driving direction of the vehicle of the same predetermined type.

[0047] The following will combine Figures 3 to 5 The example scenarios shown respectively specifically introduce the construction of reference information and the use of the reference information to detect the driving behavior of the vehicle.

[0048] Building reference information mainly includes the following aspects: acquiring driving data, determining the target area to be detected, dividing the area grid, and setting the reference information in each area grid.

[0049] Acquiring driving data mainly includes: the server filters out driving data related to abnormal driving of the detected vehicle from all heartbeat packet data reported by various vehicles in the historical period. The historical period can be set as needed, for example, the historical period can be set to 7 days, 10 days or 15 days.

[0050] The driving data may include the type of vehicle, geographic location information, and driving angle information. The type of vehicle is used to indicate the type of vehicle, such as indicating that the vehicle is a bicycle, a motorcycle, a car, an electric car, etc. In some embodiments, the type of vehicle may also include whether the vehicle is a passenger vehicle or a cargo vehicle, such as indicating that the vehicle is a bus, a truck, etc. The geographic location information may be longitude and latitude coordinates. In order to improve the recognition accuracy, the positioning unit of the vehicle may adopt an RTK algorithm. The driving angle information may include the heading angle information of the vehicle (also referred to as driving angle information).

[0051] In some embodiments, the target area to be detected can be automatically defined based on the obtained driving data. The server traverses the geographical location information of the obtained driving data, and filters out the geographical location information located at the boundary (hereinafter also referred to as boundary geographical location information) from all the geographical location information, and then defines the area surrounded by all boundary geographical locations as the target area to be detected. In some embodiments, the target area to be detected can be rectangular, and the target area to be detected can be located by at least two sets of boundary location information, for example, it can be located by two sets of boundary location information located at opposite corners of the target area to be detected. In other embodiments, the target area to be detected can also be an arbitrary polygon, and the target area to be detected can also be located by more than two sets of boundary location information.

[0052] In some embodiments, the target area to be detected can also be defined manually. The user can manually input boundary geographical location information indicating the boundary of the target area to be detected. The server determines the target area to be detected through the boundary location information.

[0053] The server divides the target area to be detected into multiple rectangular grids according to the accuracy requirements. For example, in some embodiments, the target area to be detected can be divided into n×n square grids as required, and the side lengths of these square grids can be 1m, 2m, etc. according to the accuracy requirements.

[0054] In some embodiments, the server may also use geohash encoding to perform geohash encoding on the latitude and longitude coordinates of the mobile carrier, set the geohash encoding accuracy, and use the encoded value as the grid ID. As long as the encoding after coordinate conversion is consistent, they can be considered to belong to the same grid.

[0055] After the regional grids are divided, the server distributes multiple groups of driving data to corresponding regional grids according to the geographical location information, and the driving data in each regional grid is grouped according to the type of transportation tool.

[0056] Reference information matching each grid is constructed according to the driving data in each grid.

[0057] 1) Determine the reference vehicle type in each regional grid. Specifically, the server counts the number of data of various vehicle types in each grid area, and compares the number of data with a predetermined number. When the number of data of one or some vehicle types is greater than the predetermined number, the vehicle type is added to the reference vehicle type of this regional grid.

[0058] Figure 3 FIG. 1 is a schematic diagram showing the distribution of types of vehicles in a grid area according to an embodiment of the present disclosure. Figure 3 As shown, for example, the predetermined number of vehicles of type automobile in the regional grid is set to 1, and in the regional grid B3, there is one driving data of the vehicle type automobile. In the grid D4, there are three driving data of the vehicle type automobile. According to the above judgment rules, it is considered that there is no reference vehicle type of automobile in the B3 grid, that is, the B3 grid does not belong to the driving area of ​​the car. There is a reference vehicle type of automobile in the D4 grid, that is, the D4 grid belongs to the driving area of ​​the car.

[0059] Figure 4 FIG. 1 is a schematic diagram showing the distribution of various types of transportation vehicles in a grid area according to an embodiment of the present disclosure. Figure 4 As shown, in some embodiments, the same grid area may have multiple types of vehicles. For example, in some embodiments, the C3 grid may have both the reference vehicle type of cars and the reference vehicle type of bicycles, and the reference vehicle type of cars and the reference vehicle type of bicycles are greater than their respective predetermined number requirements. Therefore, the C3 grid can be considered as a driving area belonging to both cars and bicycles.

[0060] 2) Determine the reference driving angle within each regional grid.

[0061] The server counts the driving angle information of the same type of vehicle in each grid area, and performs mean processing on the driving angle information, such as performing arithmetic mean, truncated mean or reciprocal mean on multiple driving angle information (heading angles), etc. The reference driving angle is obtained through mean processing.

[0062] Figure 5FIG. 1 shows a schematic diagram of the distribution of vehicle types and driving angle information in a grid area according to an embodiment of the present disclosure. Figure 5 As shown, for example, grid C5 includes four sets of driving angle information of the same vehicle type. By taking the average of the four sets of driving angle information, the reference driving angle of grid C5 can be obtained.

[0063] In order to improve the accuracy of detection and eliminate interference caused by vehicles changing lanes during detection, a threshold deviation is also predetermined based on the reference driving angle. For example, when the reference driving angle is from south to north and the threshold deviation is 45°, the driving angle range allowed in this grid area is 45° north by west to 45° north by east.

[0064] In some embodiments, the reference transportation type and reference driving angle of the grid area may change with different time periods of the day. Specifically, each set of driving data also includes time information for recording the time when the current driving data occurs. The reference information in each grid area can be grouped according to the time period. The reference information of the same grid area in different time periods may be different. For example, in the time period of 7:00-9:00, the reference transportation type of the grid area D3 is a bus, and in the time period of 9:00-15:00, the reference transportation type of the grid area D3 is a car. In different time periods, the reference driving angle corresponding to the grid area may also change. For example, for the E3 grid, in the time period of 7:00-9:00, the reference driving angle in the grid may be from south to north, and in the time period of 17:00-19:00, the reference driving angle in the grid may be from north to south.

[0065] The server can detect the driving behavior of the vehicle based on the above reference information and report abnormal driving behavior. When the vehicle is driving, the vehicle computer reports the driving data to the server, and the server matches the driving data with the grid area based on the geographic location information in the driving data. The server then compares the type of vehicle and driving angle information in the driving data with the reference vehicle type and reference driving angle of the reference information of the grid area.

[0066] When the type of the vehicle is consistent with the reference vehicle type and the vehicle's driving angle information is within the threshold deviation range of the reference driving angle, the current driving behavior of the vehicle is considered to be normal. If at least one of the two comparisons does not match (for example, the type of the vehicle is inconsistent with the reference vehicle type and / or the vehicle's driving angle information is not within the threshold deviation range of the reference driving angle), the current driving behavior of the vehicle is considered to be abnormal. At this time, the server sends information indicating the abnormal driving behavior of the vehicle to the vehicle computer, and the vehicle computer sends a warning message to the warning component of the vehicle. After receiving the warning message, the warning component takes action and reminds the driver.

[0067] In some embodiments, if the computing performance of the vehicle computer allows, the detection of the driving behavior of the vehicle can also be performed by the vehicle computer, and the vehicle computer downloads the grid area data and corresponding reference information in the server to the local computer. After obtaining the driving data, the vehicle computer can complete the comparison locally, so that it can detect whether the driving behavior of the vehicle is normal in a more timely manner and report it to the driver. In this way, the impact of factors such as network signals on the timeliness of detection can be reduced, and when the vehicle has abnormal driving behavior, the driver can be reminded to calibrate more quickly.

[0068] As mentioned above, there may be multiple reference vehicle types in the reference information corresponding to each grid area. Therefore, in some embodiments, when the type of vehicle is compared with the reference vehicle type, the type of vehicle only needs to be the same as any one of the reference vehicle types to be considered consistent with the reference vehicle type.

[0069] The embodiment of the present disclosure also proposes a method 600 for determining the above-mentioned reference information. Figure 6 The method can be executed by a control unit of a cloud server communicating with a vehicle. Figure 6 As shown, in box 610, the control unit determines a plurality of grid areas in the target area to be detected. These plurality of grid areas are indicated by range information representing a plurality of geographical ranges. In box 620, the control unit determines the correspondence relationship between the plurality of vehicles and the plurality of grid areas based on a comparison of the corresponding geographical locations of the plurality of vehicles with the plurality of geographical ranges during a predetermined period. The predetermined period refers to a previous (i.e., historical) predetermined period, such as a month or other appropriate period.

[0070] In block 630, the control unit determines a reference vehicle type and a reference driving angle corresponding to each of the plurality of grid areas based on the correspondence relationship. In block 640, the control unit determines reference information based on the reference vehicle type and the reference driving angle.

[0071] In some embodiments, the control unit may obtain at least geographical locations during a predetermined period from each of the plurality of vehicles, and compare the obtained geographical locations with the plurality of geographical ranges to determine a correspondence relationship.

[0072] In some implementations, the control unit may also determine corresponding geographic locations and corresponding driving angles of multiple vehicles, and for each grid area among the multiple grid areas, determine at least one vehicle located in the grid area from the multiple vehicles based on the corresponding geographic locations of the multiple vehicles.

[0073] In some embodiments, the control unit may also determine a reference driving angle of the grid area based on a driving angle of at least one vehicle located in the grid area, and determine a reference vehicle type based on a type of at least one vehicle located in the grid area.

[0074] In some embodiments, the control unit may also determine whether the number of vehicles of the same predetermined type among at least one vehicle located in the grid area is greater than a predetermined number. If it is determined whether the number of vehicles of the same predetermined type is greater than a predetermined number, the control unit may determine the predetermined type as the reference vehicle type.

[0075] In some embodiments, the control unit may also determine the driving direction of at least one vehicle of the same predetermined type located in the grid area, and determine a reference driving angle corresponding to the predetermined grid area according to the driving direction of the vehicle of the same predetermined type.

[0076] Figure 7 FIG. 7 is a schematic block diagram of an electronic device 700 suitable for implementing an embodiment of the present disclosure. The electronic device 700 may be a server for communicating with a vehicle as mentioned above, or a control system of the vehicle itself, or other appropriate device. Figure 7 As shown, the electronic device 700 includes at least one processing unit and at least one memory, and at least one processing unit can use a central processing unit (CPU) 701, which can perform various appropriate actions and processes according to computer program instructions stored in a read-only memory (ROM) 702 or computer program instructions loaded from a storage unit to a random access memory (RAM) 703. In RAM 703, various programs and data required for device operation can also be stored. CPU 701, ROM 702 and RAM 703 are connected to each other via a bus 704. An input / output (I / O) interface 705 is also connected to the bus 704.

[0077] Multiple components in the electronic device 700 are connected to the I / O interface 705, including: an input unit 706, such as a touch screen, buttons, etc.; an output unit 707, such as various types of displays, speakers, etc.; a storage unit 708, such as a disk, an optical disk, etc.; and a communication unit 709, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 709 allows the electronic device 700 to exchange information / data with other devices through a computer network such as the Internet and / or various telecommunication networks.

[0078] The various processes and processing described above, such as the processes mentioned above, can be performed by the processing unit 701. For example, in some embodiments, the processes 210-240 or the processes 610-640 can be implemented as a computer software program, which is tangibly contained in a machine-readable medium, such as the storage unit 708. In some embodiments, part or all of the computer program can be loaded and / or installed on the electronic device 700 via the ROM 702 and / or the communication unit 709. When the computer program is loaded into the RAM 703 and executed by the CPU 701, one or more actions of the processes 210-240 or the processes 610-640 described above can be performed.

[0079] Embodiments of the present disclosure relate to methods, electronic devices, and / or computer program products. The computer program product may include a computer-readable storage medium carrying computer-readable program instructions for executing various aspects of the present disclosure.

[0080] Computer readable storage medium can be a tangible device that can hold and store instructions used by an instruction execution device. Computer readable storage medium can be, for example, (but not limited to) an electrical storage device, a magnetic storage device, an optical storage device, an electromagnetic storage device, a semiconductor storage device, or any suitable combination thereof. More specific examples (non-exhaustive list) of computer readable storage medium include: 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), a static random access memory (SRAM), a portable compact disk read-only memory (CD-ROM), a digital versatile disk (DVD), a memory stick, a floppy disk, a mechanical encoding device, for example, a punch card or a convex structure in a groove on which instructions are stored, and any suitable combination thereof. The computer readable storage medium used here is not interpreted as a transient signal itself, such as a radio wave or other freely propagating electromagnetic wave, an electromagnetic wave propagated by a waveguide or other transmission medium (for example, a light pulse by an optical fiber cable), or an electrical signal transmitted by a wire.

[0081] The computer-readable program instructions described herein can be downloaded from a computer-readable storage medium to each computing / processing device, or downloaded to an external computer or external storage device via a network, such as the Internet, a local area network, a wide area network, and / or a wireless network. The network can include copper transmission cables, optical fiber transmissions, wireless transmissions, routers, firewalls, switches, gateway computers, and / or edge servers. The network adapter card or network interface in each computing / processing device receives the computer-readable program instructions from the network and forwards the computer-readable program instructions for storage in the computer-readable storage medium in each computing / processing device.

[0082] The computer program instructions for performing the operations of the present disclosure may be assembly instructions, instruction set architecture (ISA) instructions, machine instructions, machine-dependent instructions, microcode, firmware instructions, state setting data, or source code or object code written in any combination of one or more programming languages, including object-oriented programming languages, such as Smalltalk, C++, etc., and conventional procedural programming languages, such as "C" language or similar programming languages. The computer-readable program instructions may be executed entirely on the user's computer, partially on the user's computer, as an independent software package, partially on the user's computer, partially on the remote computer, or entirely on the remote computer or server 130. In the case of 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., using an Internet service provider to connect through the Internet). In some embodiments, by using the state information of the computer-readable program instructions to personalize an electronic circuit, such as a programmable logic circuit, a field programmable gate array (FPGA), or a programmable logic array (PLA), the electronic circuit may execute the computer-readable program instructions, thereby implementing various aspects of the present disclosure.

[0083] Various aspects of the present disclosure are described herein with reference to the flowcharts and / or block diagrams of the methods, devices (systems) and computer program products according to the embodiments of the present disclosure. It should be understood that each box in the flowchart and / or block diagram and the combination of each box in the flowchart and / or block diagram can be implemented by computer-readable program instructions.

[0084] These computer-readable program instructions can be provided to a processing unit of a general-purpose computer, a special-purpose computer, or other programmable data processing device, thereby producing a machine, so that when these instructions are executed by the processing unit of the computer or other programmable data processing device, a device that implements the functions / actions specified in one or more boxes in the flowchart and / or block diagram is generated. These computer-readable program instructions can also be stored in a computer-readable storage medium, and these instructions cause the computer, programmable data processing device, and / or other equipment to work in a specific manner, so that the computer-readable medium storing the instructions includes a manufactured product, which includes instructions for implementing various aspects of the functions / actions specified in one or more boxes in the flowchart and / or block diagram.

[0085] Computer-readable program instructions may also be loaded onto a computer, other programmable data processing apparatus, or other device so that a series of operating steps are performed on the computer, other programmable data processing apparatus, or other device to produce a computer-implemented process, thereby causing the instructions executed on the computer, other programmable data processing apparatus, or other device to implement the functions / actions specified in one or more boxes in the flowchart and / or block diagram.

[0086] The flow chart and block diagram in the accompanying drawings show the possible architecture, function and operation of the system, method and computer program product according to multiple embodiments of the present disclosure. In this regard, each square box in the flow chart or block diagram can represent a part of a module, program segment or instruction, and a part of the module, program segment or instruction includes one or more executable instructions for realizing the specified logical function. In some alternative implementations, the function marked in the square box can also occur in a sequence different from that marked in the accompanying drawings. For example, two continuous square boxes can actually be executed substantially in parallel, and they can sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each square box in the block diagram and / or flow chart, and the combination of the square boxes in the block diagram and / or flow chart can be implemented with a dedicated hardware-based system that performs the specified function or action, or can be implemented with a combination of special hardware and computer instructions.

[0087] The embodiments of the present disclosure have been described above, and the above description is exemplary, not exhaustive, and is not limited to the disclosed embodiments. Many modifications and variations will be apparent to those of ordinary skill in the art without departing from the scope and spirit of the described embodiments. The selection of terms used herein is intended to best explain the principles of the embodiments, practical applications, or technical improvements to the technology in the market, or to enable other persons of ordinary skill in the art to understand the embodiments disclosed herein.

Claims

1. A method for determining abnormal driving behavior, comprising: Acquiring geographical location information indicating a geographical location of a vehicle and driving angle information indicating a driving angle of the vehicle; Determining, from the reference information based on the geographic location information, a reference transportation vehicle type and a reference driving angle corresponding to a grid area matching the geographic location; determining whether the type of the vehicle and the driving angle are consistent with the reference vehicle type and the reference driving angle, respectively; as well as In response to determining that at least one of the type of the vehicle and the driving angle information is inconsistent with the corresponding reference vehicle type or the reference driving angle, a warning component of the vehicle is enabled to provide warning information.

2. The method according to claim 1, wherein the reference information is determined in the following manner: Determine a plurality of grid areas in the target area to be detected, the plurality of grid areas being indicated by range information representing a plurality of geographical ranges; determining a correspondence relationship between the plurality of vehicles and the plurality of grid areas based on a comparison of the respective geographic locations of the plurality of vehicles with the plurality of geographic ranges during a predetermined period; Determining a reference vehicle type and a reference driving angle corresponding to each grid area in the plurality of grid areas based on the corresponding relationship; as well as The reference information is determined based on the reference vehicle type and the reference driving angle.

3. The method according to claim 2, wherein determining the correspondence relationship comprises: Determine the corresponding geographic locations and corresponding travel angles of multiple vehicles; as well as For each grid area of ​​the plurality of grid areas, at least one vehicle located in the grid area is determined from the plurality of vehicles based on the corresponding geographical locations of the plurality of vehicles.

4. The method according to claim 3, wherein determining the reference vehicle type and the reference driving angle comprises: Determining a reference driving angle of the grid area based on the driving angle of the at least one vehicle located within the grid area; as well as A reference vehicle type is determined based on the type of the at least one vehicle located within the grid area.

5. The method of claim 4, wherein determining the reference vehicle type comprises: Determining whether the number of vehicles of the same predetermined type among the at least one vehicle located in the grid area is greater than a predetermined number; as well as In response to determining whether the number of vehicles of the same predetermined type is greater than a predetermined number, the predetermined type is determined as the reference vehicle type.

6. The method according to claim 4, wherein determining the reference driving angle comprises: Determining a travel direction of a vehicle of the same predetermined type as the at least one vehicle located within the grid area; The reference driving angle corresponding to the predetermined grid area is determined according to the driving direction of the vehicles of the same predetermined type.

7. The method according to any one of claims 2-6, wherein the range information comprises latitude and longitude information or geocoding information.

8. According to the method of any one of claims 1 to 6, providing warning information comprises at least one of the following: In response to determining that the type of the vehicle is inconsistent with the corresponding reference vehicle type, causing a warning component of the vehicle to provide lane occupation warning information; and In response to determining that the travel angle of the vehicle is inconsistent with the corresponding reference travel angle, a warning component of the vehicle is enabled to provide wrong-way warning information.

9. The method according to any one of claims 1 to 6, determining whether the driving angle of the vehicle is consistent with the reference driving angle comprises: determining a deviation value between the driving angle and the reference driving angle; In response to determining that the deviation value is greater than a threshold deviation, it is determined that the driving angle of the vehicle is inconsistent with the reference driving angle.

10. A method for determining reference information, comprising: Determine a plurality of grid areas in the target area to be detected, the plurality of grid areas being indicated by range information representing a plurality of geographical ranges; determining a correspondence relationship between the plurality of vehicles and the plurality of grid areas based on a comparison of the respective geographic locations of the plurality of vehicles with the plurality of geographic ranges during a predetermined period; Determining a reference vehicle type and a reference driving angle corresponding to each grid area in the plurality of grid areas based on the corresponding relationship; as well as The reference information is determined based on the reference vehicle type and the reference driving angle.

11. The method according to claim 10, wherein determining the correspondence relationship comprises: acquiring at least the geographical location during the predetermined period from each of the plurality of transportation vehicles; as well as The acquired geographic location is compared with the plurality of geographic ranges to determine the correspondence relationship.

12. The method according to claim 10 or 11, wherein determining the correspondence relationship further comprises: Determine the corresponding geographic locations and corresponding travel angles of multiple vehicles; as well as For each grid area of ​​the plurality of grid areas, at least one vehicle located in the grid area is determined from the plurality of vehicles based on the corresponding geographical locations of the plurality of vehicles.

13. The method according to claim 12, wherein determining the reference vehicle type and the reference driving angle comprises: Determining a reference driving angle of the grid area based on the driving angle of the at least one vehicle located within the grid area; as well as A reference vehicle type is determined based on the type of the at least one vehicle located within the grid area.

14. The method of claim 13, wherein determining the reference vehicle type comprises: Determining whether the number of vehicles of the same predetermined type among the at least one vehicle located in the grid area is greater than a predetermined number; as well as In response to determining whether the number of vehicles of the same predetermined type is greater than a predetermined number, the predetermined type is determined as the reference vehicle type.

15. The method according to claim 13, wherein determining the reference driving angle comprises: Determining a travel direction of a vehicle of the same predetermined type as the at least one vehicle located within the grid area; The reference driving angle corresponding to the predetermined grid area is determined according to the driving direction of the vehicles of the same predetermined type.

16. An electronic device, at least one processing unit; and At least one memory coupled to the at least one processing unit and storing machine executable instructions, which, when executed by the at least one processing unit, cause the device to perform the method according to any one of claims 1-9 or any one of claims 10-15.

17. A computer-readable storage medium comprising a computer program product stored thereon comprising machine-executable instructions, which when executed cause a machine to perform the steps of the method according to any one of claims 1 to 9 or any one of claims 10 to 15.

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