Driving assistance processing method, device, computer readable medium and electronic device

Abstract

The embodiments of the present application provide a driving assistance processing method, device, computer-readable medium and electronic device. The driving assistance processing method includes: obtaining the position information, driving status information and road condition information of the road section on which the vehicle is traveling, and obtaining the blind spot monitoring capability information of the vehicle; determining the potential blind spots of the vehicle during driving according to the position information, driving status information and road condition information of the vehicle, and obtaining the blind spot monitoring results; generating a blind spot supplementary reminder message according to the blind spot monitoring results and the blind spot monitoring capability information of the vehicle; and sending the blind spot supplementary reminder message to the vehicle. The technical solution of the embodiments of the present application can reduce the possibility of missed detection and missed warning of blind spots, and effectively enhance the safety of ADAS.

Description

Technical Field

[0001] The present application relates to the field of computer and communication technology, and more specifically, to a driving assistance processing method, device, computer-readable medium and electronic device. Background Art

[0002] ADAS (Advanced Driving Assistance System) uses a variety of sensors installed on the vehicle (millimeter wave radar, lidar, monocular or binocular cameras, satellite navigation, etc.) to sense the surrounding environment in real time during vehicle driving, collect data, identify, detect and track static and dynamic objects, and combine navigation map data to perform systematic calculations and analysis, so as to allow drivers to be aware of possible dangers in advance, effectively increasing the comfort and safety of car driving.

[0003] However, traditional ADAS has the problem of limited perception range. When driving safety risks arise, there is a lack of more effective coordination mechanism between multiple vehicles, so there are limitations in safety. Summary of the invention

[0004] The embodiments of the present application provide a driving assistance processing method, device, computer-readable medium and electronic device, which can reduce the possibility of missed detection and missed warning in blind spots at least to a certain extent, and effectively enhance the safety of ADAS.

[0005] Other features and advantages of the present application will become apparent from the following detailed description, or may be learned in part by the practice of the present application.

[0006] According to one aspect of an embodiment of the present application, a driving assistance processing method is provided, including: obtaining a vehicle's position information, driving status information, and road condition information of a road section on which the vehicle is traveling, and obtaining blind spot monitoring capability information of the vehicle; determining potential blind spots of the vehicle during driving based on the vehicle's position information, driving status information, and road condition information, and obtaining blind spot monitoring results; generating a blind spot supplementary reminder message based on the blind spot monitoring results and the blind spot monitoring capability information of the vehicle; and sending the blind spot supplementary reminder message to the vehicle.

[0007] According to one aspect of an embodiment of the present application, a driving assistance processing device is provided, including: an acquisition unit, configured to acquire a vehicle's position information, driving status information, and road condition information of a road section on which the vehicle is traveling, and acquire blind spot monitoring capability information of the vehicle; a processing unit, configured to determine potential blind spots of the vehicle during driving based on the vehicle's position information, driving status information, and road condition information, and obtain blind spot monitoring results; a generation unit, configured to generate a blind spot supplementary reminder message based on the blind spot monitoring results and the blind spot monitoring capability information of the vehicle; and a sending unit, configured to send the blind spot supplementary reminder message to the vehicle.

[0008] In some embodiments of the present application, based on the aforementioned scheme, the processing unit is configured as follows: if it is determined that there is a visual obstruction at the location of the vehicle end based on the position information, driving status information and road condition information of the vehicle end, a potential blind spot of the vehicle end is generated based on the location where the visual obstruction exists.

[0009] In some embodiments of the present application, based on the aforementioned scheme, the processing unit is configured as follows: if it is determined that the vehicle end meets at least one of the following conditions based on the position information, driving status information and road condition information of the vehicle end, then it is determined that there is a visual obstruction at the position of the vehicle end: the position of the vehicle end is a curve area, the vehicle end is in a tunnel, the vehicle end is in an uphill state, and there is an obstacle blocking the vicinity of the vehicle end.

[0010] In some embodiments of the present application, based on the aforementioned scheme, the acquisition unit is configured to: obtain advanced driving assistance system ADAS capability information sent by the vehicle end, the ADAS capability information including identification information of the vehicle end, and at least one of the following information of the vehicle end: vehicle end support information for various ADAS functions and sensor information equipped by the vehicle end; determine the blind spot monitoring capability information of the vehicle end based on the ADAS capability information.

[0011] In some embodiments of the present application, based on the aforementioned scheme, the acquisition unit is configured to: acquire the blind spot monitoring history records reported by the vehicle end; and determine the blind spot monitoring capability information of the vehicle end according to the blind spot monitoring history records.

[0012] In some embodiments of the present application, based on the aforementioned scheme, the acquisition unit is configured to: obtain the blind spot monitoring history records reported by the vehicle end and the feedback information of the driver of the vehicle end on the blind spot warning; determine the blind spot monitoring capability information of the vehicle end based on the blind spot monitoring history records and the feedback information of the driver on the blind spot warning.

[0013] In some embodiments of the present application, based on the aforementioned solution, the processing unit is further configured to: perform time synchronization with the vehicle end, so that the vehicle end processes the blind spot supplementary reminder message based on the synchronized time.

[0014] In some embodiments of the present application, based on the aforementioned scheme, the processing unit is configured to perform time synchronization with the vehicle end in at least one of the following ways: adding explicit timestamp information in the blind spot supplementary reminder message to perform time synchronization with the vehicle end; performing time synchronization with the vehicle end in an implicit indication manner, and the implicit indication manner includes implicitly indicating the timestamp information of other data packets based on the explicit timestamp information of some data packets in the data packets transmitted through the same transmission channel.

[0015] In some embodiments of the present application, based on the aforementioned scheme, the sending unit is also configured as follows: if it is difficult to determine the potential blind spot of the vehicle during driving based on the position information, driving status information and road condition information of the vehicle, then a blind spot reminder message is sent to all vehicle ends on the road section where the vehicle end is traveling.

[0016] In some embodiments of the present application, based on the aforementioned scheme, the sending unit is also configured as follows: if it is predicted that the network status of the area that the vehicle is about to enter is insufficient to support blind spot warning based on the location information, driving status information of the vehicle and the road condition information of the road section on which the vehicle is traveling, then a warning message is sent to the vehicle before the vehicle enters the area; wherein the warning information includes at least one of the following: potential blind spot information within the area, and prompt information that a blind spot warning cannot be provided within the area.

[0017] In some embodiments of the present application, based on the aforementioned scheme, the processing unit is also configured to: if the area is not within the network coverage or the network quality in the area is lower than a set value, determine that the network status of the area is insufficient to support blind spot warning.

[0018] In some embodiments of the present application, based on the aforementioned scheme, the generation unit is also configured to: determine whether it is necessary to send a blind spot supplementary reminder message to the vehicle according to the blind spot monitoring results and the blind spot monitoring capability information of the vehicle end; if it is determined that it is necessary to send a blind spot supplementary reminder message to the vehicle according to the blind spot monitoring results and the blind spot monitoring capability information of the vehicle end, then generate the blind spot supplementary reminder message.

[0019] According to one aspect of an embodiment of the present application, a computer-readable medium is provided, on which a computer program is stored. When the computer program is executed by a processor, the driving assistance processing method as described in the above embodiment is implemented.

[0020] According to one aspect of an embodiment of the present application, an electronic device is provided, comprising: one or more processors; a storage device for storing one or more programs, wherein when the one or more programs are executed by the one or more processors, the one or more processors implement the driving assistance processing method as described in the above embodiments.

[0021] According to one aspect of the embodiments of the present application, a computer program product or a computer program is provided, the computer program product or the computer program includes computer instructions, and the computer instructions are stored in a computer-readable storage medium. A processor of a computer device reads the computer instructions from the computer-readable storage medium, and the processor executes the computer instructions, so that the computer device executes the driving assistance processing method provided in the above various optional embodiments.

[0022] In the technical solutions provided in some embodiments of the present application, the cloud platform determines the potential blind spots of the vehicle during driving based on the vehicle's position information, driving status information and road condition information of the road section on which the vehicle is traveling, obtains blind spot monitoring results, and then generates blind spot supplementary reminder messages based on the blind spot monitoring results and the blind spot monitoring capability information of the vehicle, and sends the blind spot supplementary reminder messages to the vehicle, so that the cloud platform can assist the vehicle in blind spot monitoring, reduce the possibility of missed blind spot detection and missed warning, solve the problem of limited perception range of traditional single-vehicle ADAS, and effectively enhance the safety of ADAS.

[0023] It should be understood that the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the present application. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] The drawings herein are incorporated into the specification and constitute a part of the specification, showing embodiments consistent with the present application, and together with the specification, are used to explain the principles of the present application. Obviously, the drawings described below are only some embodiments of the present application, and for ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work. In the drawings:

[0025] Figure 1 A schematic diagram of an application scenario of an embodiment of the present application is shown;

[0026] Figure 2 A flowchart of a driving assistance processing method according to an embodiment of the present application is shown;

[0027] Figure 3 A schematic diagram showing ADAS capability information according to an embodiment of the present application is shown;

[0028] Figure 4A flowchart of a driving assistance processing method according to an embodiment of the present application is shown;

[0029] Figure 5 A block diagram of a driving assistance processing device according to an embodiment of the present application is shown;

[0030] Figure 6 A schematic diagram of the structure of a computer system suitable for implementing an electronic device of an embodiment of the present application is shown. DETAILED DESCRIPTION

[0031] Example embodiments will now be described more fully with reference to the accompanying drawings. However, example embodiments can be implemented in a variety of forms and should not be construed as limited to the examples set forth herein; rather, these embodiments are provided so that this application will be more comprehensive and complete and fully convey the concept of the example embodiments to those skilled in the art.

[0032] In addition, described feature, structure or characteristic can be combined in one or more embodiments in any suitable manner. In the following description, many specific details are provided to provide a full understanding of the embodiments of the present application. However, those skilled in the art will appreciate that the technical scheme of the present application can be put into practice without one or more of the specific details, or other methods, components, devices, steps, etc. can be adopted. In other cases, known methods, devices, realizations or operations are not shown or described in detail to avoid blurring the various aspects of the application.

[0033] The block diagrams shown in the accompanying drawings are merely functional entities and do not necessarily correspond to physically independent entities. That is, these functional entities may be implemented in software form, or in one or more hardware modules or integrated circuits, or in different networks and / or processor devices and / or microcontroller devices.

[0034] The flowcharts shown in the accompanying drawings are only exemplary and do not necessarily include all the contents and operations / steps, nor must they be executed in the order described. For example, some operations / steps can be decomposed, and some operations / steps can be combined or partially combined, so the actual execution order may change according to actual conditions.

[0035] It should be noted that the "multiple" mentioned in this article refers to two or more. "And / or" describes the association relationship of the associated objects, indicating that there can be three relationships. For example, A and / or B can mean: A exists alone, A and B exist at the same time, and B exists alone. The character " / " generally indicates that the associated objects before and after are in an "or" relationship.

[0036] Figure 1 A schematic diagram of an application scenario of an embodiment of the present application is shown.

[0037] like Figure 1 As shown, in an application scenario of the present application, the vehicle side can communicate with the cloud platform through the base station 101, and the cloud platform can communicate with the high-precision positioning system 102 and achieve high-precision positioning of the vehicle side by cooperating with the vehicle side. Base station 101 can be a 5G base station, or a 3G or 4G base station, or a next-generation mobile communication base station. The cloud platform can be a roadside cloud platform or a central cloud platform. The roadside cloud platform is a cloud platform that is set up near the road and only serves a small number of road sections; relative to the roadside cloud platform, the central cloud platform is a cloud platform that serves multiple road sections or the entire road section, and its service scope is much larger than the roadside cloud platform, and the central cloud platform can be set up at the back end of the core network.

[0038] Optionally, the vehicle side can also Figure 1 In addition to interacting with the cloud platform (including the central cloud platform and the roadside cloud platform) through the base station 101 (i.e., the mobile communication network) as shown in the figure, it is also possible to interact with the roadside cloud platform through V2X (vehicle to Everything) communication.

[0039] In one embodiment of the present application, Figure 1The vehicle end shown in the figure can be equipped with ADAS functions, and the ADAS functions specifically include warning systems and control systems. The warning system includes forward collision warning (FCW), lane departure warning (LDW), blind spot detection (BSD), driver fatigue warning (DFW), and tire pressure monitoring (TPMS); the control system includes lane keeping assist (LKA), automatic parking assist (APS), automatic emergency braking (AEB), adaptive cruise control (ACC), pedestrian protection system (PPS), downhill control system (DAC), etc. Of course, in the embodiments of the present application, not all vehicles have ADAS functions, and vehicles with ADAS functions do not have all of the above functions, and they may only have some ADAS functions.

[0040] In one embodiment of the present application, the vehicle can report its own location information, driving status information, and road condition information of the driving section to the cloud platform (e.g. Figure 1 ), and can upload its own blind spot monitoring capability information to the cloud platform. The cloud platform can determine the potential blind spots of the vehicle during driving based on the location information, driving status information and road condition information of the vehicle, and obtain blind spot monitoring results. The cloud platform can then generate a blind spot supplementary reminder message based on the blind spot monitoring results and the blind spot monitoring capability information of the vehicle, and then send the blind spot supplementary reminder message to the vehicle. It can be seen that the technical solution of the embodiment of the present application enables the cloud platform to assist the vehicle in blind spot monitoring, reduces the possibility of missed detection and missed warning of blind spots, solves the problem of limited perception range of traditional single-vehicle ADAS, and effectively enhances the safety of ADAS.

[0041] In one embodiment of the present application, the cloud platform can use artificial intelligence (AI) technology when determining potential blind spots during vehicle driving. Artificial intelligence technology is the theory, method, technology and application system that uses digital computers or machines controlled by digital computers to simulate, extend and expand human intelligence, perceive the environment, acquire knowledge and use knowledge to obtain the best results. In other words, artificial intelligence is a comprehensive technology in computer science that attempts to understand the essence of intelligence and produce a new intelligent machine that can respond in a similar way to human intelligence. Artificial intelligence is to study the design principles and implementation methods of various intelligent machines so that machines have the functions of perception, reasoning and decision-making.

[0042] At the same time, artificial intelligence technology is a comprehensive discipline that covers a wide range of fields, including both hardware-level and software-level technologies. The basic technologies of artificial intelligence generally include sensors, dedicated artificial intelligence chips, cloud computing, distributed storage, big data processing technology, operation / interaction systems, mechatronics and other technologies. Artificial intelligence software technology mainly includes computer vision technology, speech processing technology, natural language processing technology, and machine learning / deep learning.

[0043] Computer vision (CV) is a science that studies how to make machines "see". To put it more specifically, it refers to the use of cameras and computers to replace human eyes to identify, track and measure targets, and further perform image processing to make computer processing into images that are more suitable for human eye observation or transmission to instruments for detection. As a scientific discipline, computer vision studies related theories and technologies, and attempts to establish an artificial intelligence system that can obtain information from images or multi-dimensional data. Computer vision technology usually includes image processing, image recognition, image semantic understanding, image retrieval, OCR (Optical Character Recognition), video processing, video semantic understanding, video content / behavior recognition, three-dimensional object reconstruction, 3D technology, virtual reality, augmented reality, simultaneous positioning and mapping, and other technologies, as well as common biometric recognition technologies such as face recognition and fingerprint recognition.

[0044] In conjunction with this application, both the vehicle side and the cloud platform can adopt computer vision, machine learning and other technologies in artificial intelligence technology to improve the accuracy of driving assistance, and the vehicle side can also realize autonomous driving based on this.

[0045] The implementation details of the technical solution of the embodiment of the present application are described in detail below:

[0046] Figure 2A flowchart of a driving assistance processing method according to an embodiment of the present application is shown. The driving assistance processing method can be executed by a cloud platform, which can be a central cloud platform or a roadside cloud platform. Figure 2 As shown, the driving assistance processing method at least includes steps S210 to S240, which are described in detail as follows:

[0047] In step S210, the location information, driving status information and road condition information of the road section on which the vehicle is traveling are obtained, and the blind spot monitoring capability information of the vehicle is obtained.

[0048] In one embodiment of the present application, if the cloud platform is a central cloud platform, the vehicle side can send the location information, driving status information and road condition information of the road section being traveled to the central cloud platform through the mobile communication network; if the cloud platform is a roadside cloud platform, the vehicle side can send the location information, driving status information and road condition information of the road section being traveled to the roadside cloud platform through the mobile communication network or vehicle network communication.

[0049] Optionally, the location information of the vehicle can be sent by the vehicle to the cloud platform, or the cloud platform can communicate with the high-precision positioning system and cooperate with the vehicle to achieve high-precision positioning of the vehicle. The driving status information of the vehicle includes the speed information, acceleration information, etc. of the vehicle. The road condition information of the section where the vehicle is traveling includes the potential safety risks of the section where the vehicle is located (such as whether there is a landslide, whether the road surface is slippery, whether there is a crosswind, whether it is a tunnel, etc.), and may also include the vehicle conditions in the section (for example, whether there are safety hazards of other vehicles, etc.).

[0050] In one embodiment of the present application, the process of the cloud platform obtaining the blind spot monitoring capability information of the vehicle side may be to obtain the ADAS capability information sent by the vehicle side, and the ADAS capability information includes the identification information of the vehicle side, and at least one of the following information of the vehicle side: the vehicle side's support information for various ADAS functions and the sensor information equipped by the vehicle side. Then, the blind spot monitoring capability information of the vehicle side can be determined according to the ADAS capability information.

[0051] Optionally, the format of the ADAS capability information sent by the vehicle side can be as follows: Figure 3 As shown, the ADAS capability information includes the identification information of the vehicle side, and at least one of the following information: the vehicle side's support information for various ADAS functions (such as whether it supports ACC, whether it supports FCW, whether it supports LDW, whether it supports BSD, whether it supports TPMS, etc.); the sensor information equipped by the vehicle side (such as camera, radar and other sensor performance parameters, etc.).

[0052] In one embodiment of the present application, the process of the cloud platform obtaining the blind spot monitoring capability information of the vehicle side can also be to obtain the blind spot monitoring history records reported by the vehicle side, and then determine the blind spot monitoring capability information of the vehicle side according to the blind spot monitoring history records. For example, the vehicle side monitors and records the blind spot information through the sensor information carried by itself during driving, then the cloud platform can determine the blind spot monitoring capability information of the vehicle side by analyzing the blind spot monitoring history records of the vehicle side, such as whether the vehicle side has the blind spot monitoring capability, and the strength of the blind spot monitoring capability of the vehicle side.

[0053] In one embodiment of the present application, the process of the cloud platform obtaining the blind spot monitoring capability information of the vehicle side may be to obtain the blind spot monitoring history records reported by the vehicle side and the feedback information of the driver on the blind spot warning of the vehicle side, and then determine the blind spot monitoring capability information of the vehicle side based on the blind spot monitoring history records and the feedback information of the driver on the blind spot warning. For example, the vehicle side detects a blind spot during driving and issues a blind spot warning. If the driver chooses to ignore the blind spot warning, it means that the blind spot warning of the vehicle side may be a false alarm. If the driver accepts the blind spot warning, or feedback that the blind spot warning is accurate, it means that the blind spot warning of the vehicle side is accurate. In this case, the cloud platform can analyze the strength and weakness information of the blind spot monitoring capability of the vehicle side.

[0054] In step S220, based on the position information, driving status information and road condition information of the vehicle, the potential blind spots of the vehicle during driving are determined to obtain blind spot monitoring results.

[0055] In one embodiment of the present application, the process of the cloud platform determining the potential blind spot of the vehicle during driving may be: if it is determined that the position of the vehicle has visual impairment according to the position information, driving status information and road condition information of the vehicle, then the potential blind spot of the vehicle is generated based on the position of the visual impairment. Optionally, if it is determined that the vehicle meets at least one of the following conditions according to the position information, driving status information and road condition information of the vehicle, then it is determined that the position of the vehicle has visual impairment: the position of the vehicle is a curve area (for example, when the angle of the curve is large, visual impairment will occur), the vehicle is in a tunnel, the vehicle is in an uphill state (for example, when the slope is steep, visual impairment will occur), and there is an obstacle blocking the adjacent position of the vehicle.

[0056] In step S230, a blind spot supplementary reminder message is generated based on the blind spot monitoring result and the blind spot monitoring capability information of the vehicle.

[0057] In one embodiment of the present application, before generating a blind spot supplementary reminder message, it can also be determined whether it is necessary to send a blind spot supplementary reminder message to the vehicle based on the blind spot monitoring results and the blind spot monitoring capability information of the vehicle end. If it is determined that it is necessary to send a blind spot supplementary reminder message to the vehicle based on the blind spot monitoring results and the blind spot monitoring capability information of the vehicle end, a blind spot supplementary reminder message is generated.

[0058] In step S240, a blind spot supplementary reminder message is sent to the vehicle end.

[0059] In one embodiment of the present application, in order to ensure that the vehicle side can process the blind spot supplement reminder message in a timely manner, the cloud platform can also synchronize time with the vehicle side so that the vehicle side processes the blind spot supplement reminder message based on the synchronized time.

[0060] In one embodiment of the present application, the cloud platform may add explicit timestamp information in the blind spot supplementary reminder message to synchronize time with the vehicle side.

[0061] In one embodiment of the present application, the cloud platform can also synchronize time with the vehicle end by implicit indication, and the implicit indication method includes implicitly indicating the timestamp information of other data packets based on the explicit timestamp information of some data packets in the data packets transmitted through the same transmission channel. For example, if the cloud platform transmits several data packets through a certain transmission channel, then some of the data packets can carry explicit timestamp information to implicitly indicate the time information of other data packets that do not carry timestamp information.

[0062] In one embodiment of the present application, if the cloud platform finds it difficult to determine the potential blind spots of the vehicle during driving based on the vehicle's location information, driving status information, and road condition information, a blind spot reminder message can be sent to all vehicles on the road section where the vehicle is traveling to remind the vehicles on that road section to pay attention to driving safety.

[0063] In one embodiment of the present application, if the cloud platform predicts that the network status of the area that the vehicle is about to enter is insufficient to support blind spot warning based on the vehicle's location information, driving status information, and road condition information of the road section on which the vehicle is traveling, then the cloud platform can send warning information to the vehicle before the vehicle enters the area. Optionally, the warning information sent by the cloud platform to the vehicle before the vehicle enters the area includes at least one of the following: potential blind spot information in the area that the vehicle is about to enter, and prompt information that blind spot warning cannot be provided in the area that the vehicle is about to enter.

[0064] In one embodiment of the present application, if the area that the vehicle is about to enter is not within the network coverage or the network quality in the area that the vehicle is about to enter is lower than a set value, it is determined that the network status of the area that the vehicle is about to enter is insufficient to support blind spot warning. Optionally, the network quality may be a network signal value, a network transmission rate value, etc.

[0065] In summary, the technical solution of the embodiment of the present application is mainly that the cloud platform (central cloud platform or edge cloud platform) obtains the vehicle's location information, driving status information and road condition information, and analyzes the location and speed of the surrounding vehicles to determine the vehicle's potential blind spot, and then determines whether it is necessary to send a blind spot supplementary reminder message to the vehicle based on the vehicle's own blind spot monitoring capability information. Figure 4 For detailed explanation:

[0066] Figure 4 FIG. 1 is a flowchart of a driving assistance processing method according to an embodiment of the present application. Figure 4 As shown, the driving assistance processing method at least includes steps S410 to S460, which are described in detail as follows:

[0067] Step S410: The cloud platform obtains the vehicle's location, driving status information, and road condition information.

[0068] In one embodiment of the present application, the cloud platform may be a central cloud platform or a roadside cloud platform. The central cloud platform provides a large-scale coverage through a mobile communication network (such as a 5G network), and the roadside cloud platform provides a small-scale coverage through a 5G small station or a V2X (vehicle to Everything) RSU (Road Side Unit).

[0069] In one embodiment of the present application, the road condition information may be the potential safety risks of the road section on which the vehicle is traveling (such as landslides, slippery roads, crosswinds, tunnels, etc.), or it may be the vehicle conditions within a specific road section, such as blind spots caused by sharp turns, tunnels, slopes and other visual obstacles, and the appearance of these blind spots is also related to the location of the vehicle.

[0070] In one embodiment of the present application, the location and status information of the vehicle is very important for blind spot detection. In order to provide accuracy and pertinence of blind spot detection and reduce unnecessary false alarms, the location and driving status information of the vehicle needs to be transmitted to the cloud platform in real time through the 5G network or V2X network. At the same time, due to the existence of communication transmission delay and processing delay, time synchronization is required between the vehicle and the cloud platform, and the ADAS module on the vehicle side needs to support compensation function, that is, it can process the reminder of the cloud platform according to the explicit timestamp information in the reminder message or the implicit delay estimation.

[0071] In step S420, the cloud platform combines historical data and vehicle information to characterize the blind spot monitoring capability information of the vehicle.

[0072] In one embodiment of the present application, the configuration of the vehicle itself may or may not support blind spot monitoring, and the specific capabilities of the vehicle to support blind spot monitoring are also different. Therefore, the vehicle side can transmit historical data of blind spot monitoring to the cloud to assist the cloud in providing personalized blind spot monitoring services for the vehicle. In this embodiment, the cloud platform also needs to know the vehicle's identification, the vehicle's ADAS-related capabilities, and the vehicle's own sensor functions and performance indicators, as well as communication capabilities and other information. Optionally, the vehicle's communication capabilities include Uu networking capabilities, PC5 networking capabilities, etc.

[0073] In one embodiment of the present application, each vehicle will have blind spot monitoring behavior and driving records during driving, and the cloud platform can analyze the vehicle and its driver's judgment of potential blind spots based on this information. Optionally, this information includes safety warning information that has already appeared, as well as traffic hazard information that may appear due to blind spot monitoring errors. For example, different road conditions such as sharp turns, tunnels, slopes and other visual obstacles may cause blind spots. Even if the vehicle has not had an accident, its driving data can still be used to judge the blind spot monitoring capability.

[0074] In step S430, the cloud platform evaluates potential blind spots based on road conditions and full viewing angles.

[0075] In one embodiment of the present application, the cloud platform can combine the road condition information of the road section where the vehicle is traveling and the blind spot monitoring capability of the vehicle itself to determine whether there is a blind spot that the vehicle cannot perceive. Optionally, the road condition information can be the potential safety risks of the road section where the vehicle is traveling (such as landslides, slippery roads, crosswinds, tunnels, etc.), or it can be the vehicle conditions in a specific road section, such as nearby large trucks blocking the line of sight, sharp bends causing temporary failure of vehicle camera monitoring, and slopes causing incomplete front and rear vision of the vehicle.

[0076] In one embodiment of the present application, the cloud platform can also determine whether there is a blind spot in combination with the relative position distribution of the vehicle. This is because for blind spot detection, sharp turns, tunnels, slopes and other visual obstacles may cause blind spots, and the appearance of these blind spots is also related to the position of the vehicle.

[0077] In one embodiment of the present application, if the cloud platform cannot accurately analyze and determine the blind spot relationship between vehicles based on the positional relationship between vehicles, a regional warning can be issued to send the blind spot information to all vehicles on the road section.

[0078] In one embodiment of the present application, if the cloud platform can accurately analyze and determine the blind spot relationship between vehicles based on the positional relationship between the vehicles, it can also perform selective warnings and send blind spot information to vehicles with specific blind spots.

[0079] In one embodiment of the present application, for vehicles with lower perception capabilities (especially vehicles that are not equipped with blind spot monitoring capabilities), that is, vehicles that need to rely on network assistance or even control, if the 5G network itself has limited coverage in a certain area or the network quality is low, resulting in the cloud platform being unable to continue the blind spot warning function, the cloud platform can also notify the vehicle in advance before the vehicle enters the weak network area.

[0080] In step S440, the cloud platform analyzes and determines the blind spot information based on the road conditions and the vehicle's own blind spot monitoring capability information.

[0081] Step S450: Whether it is necessary to push blind spot supplementary reminder information.

[0082] In one embodiment of the present application, the cloud platform can determine whether to send a blind spot supplementary reminder to the vehicle-side ADAS based on the blind spot obtained by the full-view analysis and the vehicle's own blind spot monitoring capabilities mastered by the cloud platform.

[0083] Step S460, sending blind spot supplementary reminder information to the vehicle.

[0084] Optionally, the cloud platform can notify the vehicle's ADAS module of the blind spot supplementary reminder information through the 5G network or V2X network.

[0085] The technical solutions of the above-mentioned embodiments of the present application enable the cloud platform to assist vehicles in blind spot monitoring, reduce the possibility of missed detection and missed warning of blind spots, solve the problem of limited perception range of traditional single-vehicle ADAS, and effectively enhance the safety of ADAS.

[0086] The following describes an embodiment of the device of the present application, which can be used to execute the driving assistance processing method in the above embodiment of the present application. For details not disclosed in the embodiment of the device of the present application, please refer to the embodiment of the driving assistance processing method in the above embodiment of the present application.

[0087] Figure 5 A block diagram of a driving assistance processing device according to an embodiment of the present application is shown.

[0088] Reference Figure 5 As shown, a driving assistance processing device 500 according to an embodiment of the present application includes: an acquisition unit 502 , a processing unit 504 , a generation unit 506 and a sending unit 508 .

[0089] Among them, the acquisition unit 502 is configured to acquire the vehicle's position information, driving status information and road condition information of the road section on which the vehicle is traveling, and acquire the blind spot monitoring capability information of the vehicle; the processing unit 504 is configured to determine the potential blind spots of the vehicle during driving based on the vehicle's position information, driving status information and the road condition information, and obtain the blind spot monitoring results; the generation unit 506 is configured to generate a blind spot supplementary reminder message based on the blind spot monitoring results and the blind spot monitoring capability information of the vehicle; the sending unit 508 is configured to send the blind spot supplementary reminder message to the vehicle.

[0090] In some embodiments of the present application, based on the aforementioned scheme, the processing unit 504 is configured as follows: if it is determined that there is a visual obstruction at the location of the vehicle end according to the location information, driving status information and road condition information of the vehicle end, then a potential blind spot of the vehicle end is generated based on the location where the visual obstruction exists.

[0091] In some embodiments of the present application, based on the aforementioned scheme, the processing unit 504 is configured as follows: if it is determined that the vehicle end meets at least one of the following conditions based on the position information, driving status information and road condition information of the vehicle end, then it is determined that there is a visual obstruction at the position of the vehicle end: the position of the vehicle end is a curve area, the vehicle end is in a tunnel, the vehicle end is in an uphill state, and there is an obstacle blocking the vicinity of the vehicle end.

[0092] In some embodiments of the present application, based on the aforementioned scheme, the acquisition unit 502 is configured to: obtain advanced driving assistance system ADAS capability information sent by the vehicle end, the ADAS capability information including identification information of the vehicle end, and at least one of the following information of the vehicle end: vehicle end support information for various ADAS functions and sensor information equipped by the vehicle end; determine the blind spot monitoring capability information of the vehicle end based on the ADAS capability information.

[0093] In some embodiments of the present application, based on the aforementioned scheme, the acquisition unit 502 is configured to: acquire the blind spot monitoring history records reported by the vehicle end; and determine the blind spot monitoring capability information of the vehicle end according to the blind spot monitoring history records.

[0094] In some embodiments of the present application, based on the aforementioned scheme, the acquisition unit 502 is configured to: obtain the blind spot monitoring history records reported by the vehicle end and the feedback information of the driver of the vehicle end on the blind spot warning; determine the blind spot monitoring capability information of the vehicle end based on the blind spot monitoring history records and the feedback information of the driver on the blind spot warning.

[0095] In some embodiments of the present application, based on the aforementioned solution, the processing unit 504 is further configured to: perform time synchronization with the vehicle end, so that the vehicle end processes the blind spot supplementary reminder message based on the synchronized time.

[0096] In some embodiments of the present application, based on the aforementioned scheme, the processing unit 504 is configured to perform time synchronization with the vehicle end in at least one of the following ways: adding explicit timestamp information in the blind spot supplementary reminder message to perform time synchronization with the vehicle end; performing time synchronization with the vehicle end in an implicit indication manner, and the implicit indication manner includes implicitly indicating the timestamp information of other data packets based on the explicit timestamp information of some data packets in the data packets transmitted through the same transmission channel.

[0097] In some embodiments of the present application, based on the aforementioned scheme, the sending unit 508 is also configured as follows: if it is difficult to determine the potential blind spot of the vehicle during driving based on the position information, driving status information and road condition information of the vehicle, a blind spot reminder message is sent to all vehicle ends on the road section where the vehicle end is traveling.

[0098] In some embodiments of the present application, based on the aforementioned scheme, the sending unit 508 is also configured as follows: if it is predicted that the network status of the area that the vehicle is about to enter is insufficient to support blind spot warning based on the location information, driving status information of the vehicle and the road condition information of the road section on which the vehicle is traveling, then a warning message is sent to the vehicle before the vehicle enters the area; wherein the warning information includes at least one of the following: potential blind spot information in the area, and prompt information that a blind spot warning cannot be provided in the area.

[0099] In some embodiments of the present application, based on the aforementioned scheme, the processing unit 504 is also configured to: if the area is not within the network coverage or the network quality in the area is lower than a set value, determine that the network status of the area is insufficient to support blind spot warning.

[0100] In some embodiments of the present application, based on the aforementioned scheme, the generation unit 506 is also configured to: determine whether it is necessary to send a blind spot supplementary reminder message to the vehicle according to the blind spot monitoring results and the blind spot monitoring capability information of the vehicle end; if it is determined that it is necessary to send a blind spot supplementary reminder message to the vehicle according to the blind spot monitoring results and the blind spot monitoring capability information of the vehicle end, then generate the blind spot supplementary reminder message.

[0101] Figure 6 A schematic diagram of the structure of a computer system suitable for implementing an electronic device of an embodiment of the present application is shown.

[0102] It should be noted that Figure 6 The computer system 600 of the electronic device shown is only an example and should not bring any limitation to the functions and scope of use of the embodiments of the present application.

[0103] like Figure 6 As shown, the computer system 600 includes a central processing unit (CPU) 601, which can perform various appropriate actions and processes according to the program stored in the read-only memory (ROM) 602 or the program loaded from the storage part 608 to the random access memory (RAM) 603, such as executing the method described in the above embodiment. In the RAM 603, various programs and data required for system operation are also stored. The CPU 601, ROM 602 and RAM 603 are connected to each other through a bus 604. An input / output (I / O) interface 605 is also connected to the bus 604.

[0104] The following components are connected to the I / O interface 605: an input section 606 including a keyboard, a mouse, etc.; an output section 607 including a cathode ray tube (CRT), a liquid crystal display (LCD), etc., and a speaker, etc.; a storage section 608 including a hard disk, etc.; and a communication section 609 including a network interface card such as a LAN (Local Area Network) card, a modem, etc. The communication section 609 performs communication processing via a network such as the Internet. A drive 610 is also connected to the I / O interface 605 as needed. A removable medium 611, such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, etc., is installed on the drive 610 as needed so that a computer program read therefrom is installed into the storage section 608 as needed.

[0105] In particular, according to an embodiment of the present application, the process described above with reference to the flowchart can be implemented as a computer software program. For example, an embodiment of the present application includes a computer program product, which includes a computer program carried on a computer-readable medium, and the computer program includes a computer program for executing the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from a network through a communication section 609, and / or installed from a removable medium 611. When the computer program is executed by a central processing unit (CPU) 601, various functions defined in the system of the present application are executed.

[0106] It should be noted that the computer-readable medium shown in the embodiment of the present application may be a computer-readable signal medium or a computer-readable storage medium or any combination of the above two. The computer-readable storage medium may be, for example, - but not limited to - an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device or device, or any combination of the above. More specific examples of computer-readable storage media may include, but are not limited to: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM), a flash memory, an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In the present application, a computer-readable storage medium may be any tangible medium containing or storing a program, which may be used by an instruction execution system, device or device or used in combination with it. In the present application, a computer-readable signal medium may include a data signal propagated in a baseband or as part of a carrier wave, wherein a computer-readable computer program is carried. Such propagated data signals may take a variety of forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination of the above. Computer-readable signal media may also be any computer-readable medium other than computer-readable storage media, which may send, propagate, or transmit programs for use by or in conjunction with an instruction execution system, apparatus, or device. The computer program contained on the computer-readable medium may be transmitted using any appropriate medium, including but not limited to: wireless, wired, etc., or any suitable combination of the above.

[0107] The flowchart and block diagram in the accompanying drawings illustrate the possible architecture, functions and operations of the system, method and computer program product according to various embodiments of the present application. Wherein, each box in the flowchart or block diagram can represent a module, a program segment, or a part of the code, and the above-mentioned module, program segment, or a part of the code contains one or more executable instructions for realizing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the box can also occur in a different order from the order marked in the accompanying drawings. For example, two boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the block diagram or flowchart, and the combination of boxes in the block diagram or flowchart can be implemented with a dedicated hardware-based system that performs a specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions.

[0108] The units involved in the embodiments described in this application may be implemented by software or hardware, and the units described may also be set in a processor. The names of these units do not, in some cases, constitute limitations on the units themselves.

[0109] As another aspect, the present application also provides a computer-readable medium, which may be included in the electronic device described in the above embodiment; or may exist independently without being assembled into the electronic device. The above computer-readable medium carries one or more programs, and when the above one or more programs are executed by an electronic device, the electronic device implements the method described in the above embodiment.

[0110] It should be noted that, although several modules or units of the equipment for action execution are mentioned in the above detailed description, this division is not mandatory. In fact, according to the embodiments of the present application, the features and functions of two or more modules or units described above can be embodied in one module or unit. On the contrary, the features and functions of one module or unit described above can be further divided into being embodied by multiple modules or units.

[0111] Through the description of the above implementation methods, it is easy for those skilled in the art to understand that the example implementation methods described here can be implemented by software or by combining software with necessary hardware. Therefore, the technical solution according to the implementation methods of the present application can be embodied in the form of a software product, which can be stored in a non-volatile storage medium (which can be a CD-ROM, a USB flash drive, a mobile hard disk, etc.) or on a network, and includes several instructions to enable a computing device (which can be a personal computer, a server, a touch terminal, or a network device, etc.) to execute the method according to the implementation methods of the present application.

[0112] Those skilled in the art will readily appreciate other embodiments of the present application after considering the specification and practicing the embodiments disclosed herein. The present application is intended to cover any variations, uses or adaptations of the present application, which follow the general principles of the present application and include common knowledge or customary technical means in the art that are not disclosed in the present application.

[0113] It should be understood that the present application is not limited to the precise structures that have been described above and shown in the drawings, and that various modifications and changes may be made without departing from the scope thereof. The scope of the present application is limited only by the appended claims.

Claims

1. A driving assistance processing method, characterized in that: The driving assistance processing method is executed by a cloud platform, and the driving assistance processing method includes: Acquire the location information, driving status information and road condition information of the road section on which the vehicle is traveling, and acquire the blind spot monitoring capability information of the vehicle; the blind spot monitoring capability information of the vehicle is used to indicate whether the vehicle has blind spot monitoring capability and the strength of the blind spot monitoring capability of the vehicle; Determine the potential blind spot of the vehicle during driving according to the location information, driving state information and road condition information of the vehicle, and obtain a blind spot monitoring result; Generating a blind spot supplementary reminder message for assisting the vehicle in blind spot monitoring according to the blind spot monitoring result and the blind spot monitoring capability information of the vehicle end; The blind spot supplement reminder message is sent to the vehicle end.

2. The driving assistance processing method according to claim 1, characterized in that: Determining a potential blind spot of the vehicle during driving according to the location information, driving state information and road condition information of the vehicle, including: If it is determined that there is a visual obstruction at the location of the vehicle end according to the location information, driving status information and the road condition information of the vehicle end, a potential blind spot of the vehicle end is generated based on the location where the visual obstruction exists.

3. The driving assistance processing method according to claim 2, characterized in that: The driving assistance processing method further includes: If it is determined based on the position information, driving status information and road condition information of the vehicle end that the vehicle end meets at least one of the following conditions, it is determined that there is a visual obstruction at the position of the vehicle end: the position of the vehicle end is a curve area, the vehicle end is in a tunnel, the vehicle end is in an uphill state, and there is an obstacle blocking the vicinity of the vehicle end.

4. The driving assistance processing method according to claim 1, characterized in that: Obtaining the blind spot monitoring capability information of the vehicle, including: Acquire advanced driving assistance system ADAS capability information sent by the vehicle end, wherein the ADAS capability information includes identification information of the vehicle end and at least one of the following information of the vehicle end: support information of the vehicle end for various ADAS functions and sensor information equipped by the vehicle end; The blind spot monitoring capability information of the vehicle is determined according to the ADAS capability information.

5. The driving assistance processing method according to claim 1, characterized in that: Obtaining the blind spot monitoring capability information of the vehicle, including: Obtaining the blind spot monitoring history records reported by the vehicle end; The blind spot monitoring capability information of the vehicle end is determined according to the blind spot monitoring history records.

6. The driving assistance processing method according to claim 1, characterized in that: Obtaining the blind spot monitoring capability information of the vehicle, including: Obtaining the blind spot monitoring history records reported by the vehicle end and the feedback information of the driver of the vehicle end on the blind spot warning; The blind spot monitoring capability information of the vehicle end is determined according to the blind spot monitoring history records and the driver's feedback information on the blind spot warning.

7. The driving assistance processing method according to claim 1, characterized in that: The driving assistance processing method further includes: Time synchronization is performed with the vehicle end so that the vehicle end processes the blind spot supplementary reminder message based on the synchronized time.

8. The driving assistance processing method according to claim 7, characterized in that: Time synchronization with the vehicle terminal includes at least one of the following methods: Adding explicit timestamp information to the blind spot supplementary reminder message to synchronize time with the vehicle end; Time synchronization is performed with the vehicle end by implicit indication, wherein the implicit indication includes implicitly indicating the timestamp information of other data packets based on the explicit timestamp information of some data packets in the data packets transmitted through the same transmission channel.

9. The driving assistance processing method according to claim 1, characterized in that: The driving assistance processing method further includes: If it is difficult to determine the potential blind spot of the vehicle during driving based on the location information, driving status information and road condition information of the vehicle, a blind spot reminder message is sent to all vehicles on the road section where the vehicle is traveling.

10. The driving assistance processing method according to claim 1, characterized in that: The driving assistance processing method further includes: If it is predicted based on the location information, driving status information of the vehicle and the road condition information of the road section on which the vehicle is traveling that the network status of the area that the vehicle is about to enter is insufficient to support blind spot warning, then a warning message is sent to the vehicle before the vehicle enters the area; The warning information includes at least one of the following: potential blind spot information in the area, and prompt information that a blind spot warning cannot be provided in the area.

11. The driving assistance processing method according to claim 10, characterized in that: The driving assistance processing method further includes: If the area is not within the network coverage or the network quality in the area is lower than a set value, it is determined that the network status of the area is insufficient to support blind spot warning.

12. The driving assistance processing method according to any one of claims 1 to 11, characterized in that: Before generating a blind spot supplementary reminder message according to the blind spot monitoring result and the blind spot monitoring capability information of the vehicle, the driving assistance processing method further includes: Determining whether it is necessary to send a blind spot supplementary reminder message to the vehicle according to the blind spot monitoring result and the blind spot monitoring capability information of the vehicle end; If it is determined that a blind spot supplementary reminder message needs to be sent to the vehicle based on the blind spot monitoring result and the blind spot monitoring capability information of the vehicle, the blind spot supplementary reminder message is generated.

13. A driving assistance processing device, characterized in that: The driving assistance processing device is applied to a cloud platform, and the driving assistance processing device includes: an acquisition unit configured to acquire the position information, driving state information and road condition information of the road section on which the vehicle is traveling, and acquire the blind spot monitoring capability information of the vehicle; the blind spot monitoring capability information of the vehicle is used to indicate whether the vehicle has the blind spot monitoring capability and the strength of the blind spot monitoring capability of the vehicle; A processing unit configured to determine a potential blind spot of the vehicle during driving according to the location information, driving state information and road condition information of the vehicle, and obtain a blind spot monitoring result; A generating unit configured to generate a blind spot supplementary reminder message for assisting the vehicle end in blind spot monitoring according to the blind spot monitoring result and the blind spot monitoring capability information of the vehicle end; The sending unit is configured to send the blind spot supplementary reminder message to the vehicle end.

14. A computer readable medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the driving assistance processing method according to any one of claims 1 to 12 is implemented.

15. An electronic device, characterized in that: include: one or more processors; A storage device for storing one or more programs, when the one or more programs are executed by the one or more processors, enables the one or more processors to implement the driving assistance processing method as described in any one of claims 1 to 12.

16. A computer program product, characterized in that The computer program product includes a computer program, which is stored in a computer-readable storage medium. A processor of a computer device reads and executes the computer program from the computer-readable storage medium, so that the computer device executes the driving assistance processing method according to any one of claims 1 to 12.

Images