A driving safety assistance method and device based on vehicle positioning and an intelligent terminal

Abstract

The application discloses a kind of driving safety auxiliary method, device and intelligent terminal based on vehicle positioning, the method includes: obtaining vehicle driving information, when identifying vehicle safety accident or safety risk event occurs, the event type of vehicle safety accident or safety risk event is obtained;According to event type, vehicle driving information is compared with the historical vehicle driving information corresponding to event type, and similarity is obtained;According to the similarity, the historical similar scene matched with the similarity is obtained, and vehicle driving is controlled based on the intervention timing and intervention intensity of the historical similar scene.The application classifies and marks the safety risk of driving scene based on vehicle environmental information in combination with historical vehicle stability control process or safety accident information, and then makes sufficient and effective safety information prompt and vehicle stability control to current similar driving scene when vehicle safety accident or safety risk event occurs, to realize the goal of driving safety auxiliary.

Description

Technical Field

[0001] This invention relates to the field of vehicle active safety, specifically to a driving safety assistance method, device, and intelligent terminal based on vehicle positioning. Background Technology

[0002] As road transport has become the most important mode of ground transportation, it plays a crucial role in social progress and economic development. In recent years, the number of vehicles and drivers in my country has grown rapidly, leading to frequent traffic accidents. Accidents caused by driver cognitive and decision-making errors are a major component of these tragedies. Therefore, active safety assistance systems for vehicles have been proposed and have been rapidly developed and widely applied.

[0003] Vehicle active safety assistance utilizes big data analytics and intelligent assistance to enable vehicles to perform better driving maneuvers based on shared driving data, thereby fully ensuring driving safety and speed. However, current technologies do not consider the correlation between environmental factors and vehicle stability, and do not categorize safety incidents by type, resulting in low accuracy in handling safety incidents.

[0004] Therefore, existing technologies still need to be improved and developed. Summary of the Invention

[0005] The technical problem to be solved by the present invention is to provide a driving safety assistance method, device and intelligent terminal based on vehicle positioning, which addresses the above-mentioned defects of the prior art. The aim is to solve the problem that the prior art does not take into account the correlation between environmental factors and vehicle stability, and does not subdivide the event types of safety events, resulting in low accuracy in handling safety events.

[0006] The technical solution adopted by this invention to solve the technical problem is as follows: In a first aspect, the present invention provides a driving safety assistance method based on vehicle positioning, wherein the method includes: Obtain vehicle driving information, wherein the vehicle driving information includes vehicle information and environmental information; When a vehicle safety accident or safety risk event is detected, the event type of the vehicle safety accident or safety risk event is obtained; Based on the event type, the vehicle driving information is compared with the historical vehicle driving information corresponding to the event type to obtain the similarity. Based on the similarity, historical similar scenes matched by the similarity are obtained, and vehicle driving is controlled based on the intervention timing and intensity of the historical similar scenes.

[0007] In one implementation, the vehicle information includes vehicle speed, acceleration, yaw rate, steering wheel angle, drive torque, and braking torque.

[0008] In one implementation, the environmental information includes location, time, temperature, and rainfall.

[0009] In one implementation, when a vehicle safety accident or safety risk event is detected, obtaining the event type of the vehicle safety accident or safety risk event includes: Real-time monitoring of vehicle driving status; when the vehicle stability control system begins to intervene in driving, it determines that a vehicle safety accident or safety risk event has occurred. The event type of the vehicle safety accident or safety risk event is obtained. The event type of the vehicle safety accident includes the collision location and collision intensity, and the event type of the safety risk event includes the intervention flag position and intensity of the anti-lock braking system, traction control system, yaw stability system, and automatic emergency braking.

[0010] In one implementation, the step of comparing the vehicle driving information with historical vehicle driving information corresponding to the event type to obtain a similarity score includes: The historical vehicle driving information is classified according to the event type to obtain several historical vehicle driving information categories under each event type. Based on the event type at the time of the vehicle safety accident or safety risk event, the vehicle information and environmental information are compared with the historical vehicle driving information corresponding to each event type to obtain the single similarity with each historical vehicle driving information. The similarity of each historical category of vehicle driving information is obtained by weighting the individual similarities of each item according to a preset weight. The weights of location, rainfall, vehicle speed, and yaw rate are greater than the weights of acceleration, steering wheel angle, drive torque, braking torque, time, and temperature.

[0011] In one implementation, obtaining the historical similar scenes matched by the similarity based on the similarity includes: If the maximum value of the similarity among the vehicle driving information of each historical category is greater than or equal to a preset similarity threshold, then the historical similar scene is obtained based on the historical vehicle driving information corresponding to the maximum value.

[0012] In one implementation, controlling vehicle driving based on the intervention timing and intensity of the historical similar scenarios includes: Obtain the timing and intensity of interventions in the aforementioned historically similar scenarios; Based on the timing and intensity of intervention in the aforementioned historically similar scenarios, vehicle stability control measures are derived. Based on the aforementioned vehicle stability control measures, adjust the vehicle stability control threshold and limit the maximum vehicle speed; Based on the vehicle safety accident or safety risk event, send a safety information alert.

[0013] Secondly, embodiments of the present invention also provide a driving safety assistance device based on vehicle positioning, wherein the device includes: A vehicle driving information acquisition module is used to acquire vehicle driving information, wherein the vehicle driving information includes vehicle information and environmental information; The event type acquisition module is used to acquire the event type of a vehicle safety accident or safety risk event when it is identified that a vehicle safety accident or safety risk event has occurred. The comparison module is used to compare the vehicle driving information with the historical vehicle driving information corresponding to the event type according to the event type, and obtain the similarity. An intervention control module is used to obtain historical similar scenes matched by the similarity based on the similarity, and control vehicle driving based on the intervention timing and intensity of the historical similar scenes.

[0014] Thirdly, embodiments of the present invention also provide a smart terminal, wherein the smart terminal includes a memory, a processor, and a vehicle positioning-based driving safety assistance program stored in the memory and executable on the processor, wherein when the processor executes the vehicle positioning-based driving safety assistance program, it implements the steps of the vehicle positioning-based driving safety assistance method as described in any of the above claims.

[0015] Fourthly, embodiments of the present invention also provide a computer-readable storage medium, wherein the computer-readable storage medium stores a vehicle positioning-based driving safety assistance program, and when the vehicle positioning-based driving safety assistance program is executed by a processor, it implements the steps of the vehicle positioning-based driving safety assistance method as described in any of the preceding claims.

[0016] Beneficial Effects: Compared with existing technologies, this invention provides a vehicle positioning-based driving safety assistance method. First, it acquires vehicle driving information, including vehicle information and environmental information. By combining vehicle information with environmental information, internal and external environmental parameters of the vehicle can be obtained simultaneously, making subsequent classification and identification processes more accurate. When a vehicle safety accident or safety risk event is identified, the event type is acquired, and the driving scenario is classified and labeled for safety risk, which helps in accurate matching. Then, based on the event type, the vehicle driving information is compared with historical vehicle driving information corresponding to the event type to obtain a similarity score. By comparing with the classified historical information, the handling methods and timing of historical safety events can be accurately matched. Next, based on the similarity score, historical similar scenarios are obtained. By determining the historical scenario with the highest similarity, the degree of similarity can be quantified, accurately locating historical similar scenarios. Finally, based on the intervention timing and intensity of the historical similar scenarios, vehicle driving is controlled, achieving sufficient and effective safety information prompts and vehicle stability control for current similar driving scenarios, thus achieving the goal of driving safety assistance. Attached Figure Description

[0017] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments recorded in the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0018] Figure 1 This is a schematic diagram of the driving safety assistance method based on vehicle positioning provided in an embodiment of the present invention.

[0019] Figure 2 This is a schematic diagram of the functional module architecture provided in an embodiment of the present invention.

[0020] Figure 3 This is a schematic diagram of the functional modules provided in an embodiment of the present invention.

[0021] Figure 4 This is a flowchart illustrating the driving safety assistance method based on vehicle positioning provided in an embodiment of the present invention.

[0022] Figure 5 This is a schematic diagram of the driving safety assistance device based on vehicle positioning provided in an embodiment of the present invention.

[0023] Figure 6 This is a block diagram illustrating the internal structure of a smart terminal provided in an embodiment of the present invention. Detailed Implementation

[0024] To make the objectives, technical solutions, and effects of this invention clearer and more explicit, the invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.

[0025] Those skilled in the art will understand that, unless specifically stated otherwise, the singular forms “a,” “an,” “the,” and “the” used herein may also include the plural forms. It should be further understood that the term “comprising” as used in this specification means the presence of the stated features, integers, steps, operations, elements, and / or components, but does not exclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and / or groups thereof. It should be understood that when we say an element is “connected” or “coupled” to another element, it can be directly connected or coupled to the other element, or there may be intermediate elements. Furthermore, “connected” or “coupled” as used herein can include wireless connections or wireless coupling. The term “and / or” as used herein includes all or any units and all combinations of one or more associated listed items.

[0026] It will be understood by those skilled in the art that, unless otherwise defined, all terms used herein (including technical and scientific terms) have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains. It should also be understood that terms such as those defined in general dictionaries should be understood to have the same meaning as in the context of the prior art, and should not be interpreted in an idealized or overly formal sense unless specifically defined as herein.

[0027] With the rapid growth of vehicles and drivers in my country, traffic accidents are frequent, and accidents caused by driver cognitive and decision-making errors constitute a major component of these tragedies. In response, active safety assistance systems for vehicles have been proposed and have rapidly developed and been widely applied. These systems utilize big data analysis and intelligent assistance to enable vehicles to perform better driving operations based on shared driving data, thereby fully ensuring driving safety and speed. However, current technologies do not consider the correlation between environmental factors and vehicle stability, and they do not segment safety incidents into different types, resulting in low accuracy in handling safety incidents.

[0028] To address the aforementioned deficiencies in existing technologies, this invention provides a vehicle positioning-based driving safety assistance method. This invention first identifies the occurrence of a vehicle safety accident or safety risk event, obtains the event type of the accident or risk event, and matches it with historical vehicle driving information to determine the event type. Then, it identifies the most similar historical scenarios from the historical vehicle driving information of the same event type. This allows for accurate matching of the processing method and timing of the most similar historical safety event, thereby achieving the goal of driving safety assistance.

[0029] Exemplary methods This embodiment provides a driving safety assistance method based on vehicle positioning. For example... Figure 1 As shown, the method includes the following steps: Step S100: Obtain vehicle driving information, which includes vehicle information and environmental information; vehicle information includes vehicle speed, acceleration, yaw rate, steering wheel angle, drive torque and braking torque; environmental information includes location, time, temperature and rainfall.

[0030] Specifically, such as Figure 2 As shown, during vehicle operation, environmental information can be collected via a GPS receiver, and vehicle information can be obtained via a vehicle stability control unit. Figure 3 As shown, vehicle driving information includes vehicle information that reflects the control parameters and vehicle status during vehicle operation, as well as environmental information that reflects geographical and weather conditions in the environment. Vehicle information and environmental information together constitute vehicle driving information.

[0031] GPS positioning information is geographic information provided by the Global Positioning System (GPS). GPS is a high-precision radio navigation positioning system based on artificial Earth satellites. It can provide accurate geographic location, vehicle speed, and precise time information anywhere in the world and in near-Earth space. By locating the vehicle's position and time, combined with meteorological information, the temperature and rainfall of the vehicle's environment can be obtained. Temperature affects tire hardness, and rainfall affects road surface friction. GPS positioning information can effectively predict the vehicle's driving status.

[0032] In this embodiment, by referencing the vehicle's GPS positioning information to obtain environmental information, the vehicle's driving information is effectively supplemented, which helps to accurately predict the danger the vehicle is in, so as to provide the driver with effective guidance to correct the dangerous situation as soon as possible.

[0033] Step S200: When a vehicle safety accident or safety risk event is identified, obtain the event type of the vehicle safety accident or safety risk event; Specifically, such as Figure 2 The identification of vehicle safety accidents or safety risk events is handled by the driving scenario safety risk labeling module, which is responsible for information collection, labeling, classification, and recording. When a safety accident or safety risk event is detected, i.e., when vehicle stability control begins to intervene, this module needs to label and differentiate the event type and the vehicle and environmental information at the time of the event to determine the event type of the vehicle safety accident or safety risk event.

[0034] For example, when ESC (Electronic Stability Control) intervenes in vehicle movement, it is considered that a safety risk event has occurred. The event type is determined by the intervention flag and intensity of the yaw stability system. When a collision with the front bumper is detected, and the collision intensity is severe, a safety accident is considered to have occurred.

[0035] In one implementation, step S200 of this embodiment specifically includes: Step S201: Monitor the vehicle's driving status in real time. When the vehicle stability control system is detected to begin intervening in driving, determine that a vehicle safety accident or safety risk event has occurred. Step S202: Obtain the event type of vehicle safety accident or safety risk event. The event type of vehicle safety accident includes collision location and collision intensity, and the event type of safety risk event includes the intervention flag position and intensity of anti-lock braking system, traction control system, yaw stability system and automatic emergency braking.

[0036] Specifically, the Vehicle Stability Control (VSC) system is a new generation of active safety control device for automobiles, developed on the basis of ABS / ASR, with more complete control functions. Through independent automatic braking control of all four wheels and engine torque control, it suppresses rear wheel slippage, front wheel slippage, and brake folding of the tractor unit during sudden events such as sharp steering or abrupt changes in road conditions, thus ensuring vehicle stability. When the VSC system intervenes in driving, it indicates a danger has occurred, requiring the auxiliary system to control the vehicle for smooth driving. In this embodiment, when the VSC system intervenes in driving, it determines that a vehicle safety accident or safety risk event has occurred and needs to determine the event type. By determining the event type, the subsequent matching range can be narrowed down, thereby achieving precise matching.

[0037] For example, by monitoring vehicle driving conditions in real time, when the ABS (Antilock Braking System) is detected to be intervening in driving, a safety risk event is determined to have occurred. The event type is determined by the obtained intervention flag and intensity of the ABS. When a collision is detected, a safety accident is determined to have occurred. The event type of the safety accident is determined by the collision location and collision intensity.

[0038] Step S300: Based on the event type, compare the vehicle driving information with the historical vehicle driving information corresponding to the event type to obtain the similarity. Specifically, historical vehicle driving information—that is, historical traffic safety accident data—involves vehicle driving information under different regions, environments, and events. By classifying this historical vehicle driving information according to event type, we can obtain the historical vehicle driving information corresponding to a specific event type. Then, by comparing this vehicle driving information with the historical vehicle driving information corresponding to the event type and accurately describing it using similarity, we can evaluate which historical scenario the current vehicle's driving state is most similar to, and thus take similar intervention measures.

[0039] In one implementation, step S300 of this embodiment specifically includes: Step S301: Classify the historical vehicle driving information according to the event type to obtain several historical vehicle driving information corresponding to each event type; Step S302: Based on the event type when the vehicle safety accident or safety risk event occurs, compare the vehicle information and environmental information with the historical vehicle driving information corresponding to each event type to obtain the single similarity with each historical vehicle driving information. Step S303: The single similarity of each historical category vehicle driving information is weighted and averaged according to the preset weights to obtain the similarity of each historical category vehicle driving information. Among them, the weights of location, rainfall, vehicle speed, and yaw rate are greater than the weights of acceleration, steering wheel angle, driving torque, braking torque, time, and temperature.

[0040] Specifically, vehicle safety accidents are categorized by event type, including collision location and intensity. Safety risk events are categorized by event type, including intervention flags and intensity for anti-lock braking systems (ABS), traction control systems, yaw stability systems, and automatic emergency braking. Historical vehicle driving information is classified according to these event types, and this information also includes the timing and intensity of interventions to be taken after each safety accident and safety risk event. Individual similarity scores are obtained by comparing vehicle driving information under the same event type with historically categorized vehicle driving information. Indicators that directly affect vehicle stability, such as location, rainfall, vehicle speed, and yaw rate, are given higher weights. A weighted average of these individual similarity scores yields the similarity scores for multiple historically categorized vehicle driving information.

[0041] For example, when the intervention flag and intensity of a vehicle's anti-lock braking system (ABS) are identified, the event type can be determined as ABS under the same intervention flag and intensity. Under the same ABS event type with the same intervention flag and intensity, there are two historical vehicle driving information sets, A and B. Comparing the vehicle and environmental information in the current vehicle driving information with those in A and B yields the following similarities: speed similarity 2, acceleration similarity 2, yaw rate similarity 4, steering wheel angle similarity 6, drive torque similarity 4, position similarity 3, time similarity 6, temperature similarity 5, and rainfall similarity 2. Similarly, the current vehicle driving information and historical vehicle driving information B show similarities: speed similarity 4, acceleration similarity 4, yaw rate similarity 1, steering wheel angle similarity 2, drive torque similarity 1, and position similarity 2. Given that the time similarity is 1, temperature similarity is 1, and rainfall similarity is 1, with preset weights of vehicle speed (0.2), acceleration (0.05), yaw rate (0.2), steering wheel angle (0.05), drive torque (0.05), position (0.05), time (0.05), temperature (0.1), and rainfall (0.15), the similarity between the current vehicle's driving information and historical vehicle driving information A is calculated as: 2*0.2 + 2*0.05 + 4*0.2 + 6*0.05 + 4*0.05 + 3*0.05 + 6*0.05 + 5*0.1 + 2*0.15 = 3.05. The similarity between the current vehicle driving information and the historical vehicle driving information B is: 4*0.2+4*0.05+1*0.2+2*0.05+1*0.05+2*0.05+1*0.05+1*0.1+1*0.15=1.75.

[0042] Step S400: Obtain historical similar scenes based on similarity. Specifically, by selecting the historical vehicle driving information with the highest similarity in each scenario category as the historical similar scenario, the intervention measures and intensity of the historical similar scenario can be used as the basis for dealing with the current driving risks.

[0043] In one implementation, step S400 of this embodiment specifically includes: Step S401: If the maximum value of the similarity of each historical category vehicle driving information is greater than or equal to the preset similarity threshold, then the historical similar scene is obtained based on the historical category vehicle driving information corresponding to the maximum value. Step S402: Obtain the intervention timing and intensity of similar historical scenarios.

[0044] Specifically, such as Figure 4 As shown, a preset similarity threshold is used to determine whether there are scenarios in the historical vehicle driving information of the same category that are sufficiently similar to the current vehicle driving information. As in the example above, if the similarity threshold is 1, then the similarity of historical vehicle driving information A and B both exceed the similarity threshold. Since the similarity of historical vehicle driving information A is greater than that of historical vehicle driving information B, historical vehicle driving information A is used as the historical similar scenario.

[0045] Step S500: Control vehicle driving based on the timing and intensity of intervention in the historical similar scenarios.

[0046] Specifically, since historical similar scenarios are the scenarios with the highest similarity to current driving information, intervention methods from historical scenarios can be used to control vehicle driving. By sending safety information prompts, human-computer interaction can be carried out with the driver to notify the driver of the risk events that have occurred to the vehicle and the intervention measures that the vehicle control system has taken, thereby improving driving safety.

[0047] In one implementation, step S500 of this embodiment specifically includes: Step S501: Based on the intervention timing and intensity based on historical similar scenarios, obtain vehicle stability control measures; Step S502: Adjust the vehicle stability control threshold and limit the maximum vehicle speed according to the vehicle stability control measures; Step S503: Send a safety information alert based on a vehicle safety accident or safety risk event.

[0048] Specifically, when Figure 3As shown, the control request processing module is responsible for arbitrating and outputting control quantities to relevant actuators after scene recognition. These control quantities are categorized into two types based on the actuator: human-machine interaction and vehicle stability control. These are used for safety information prompts and vehicle stability prediction control, respectively. Vehicle stability prediction control includes, but is not limited to, adjusting vehicle stability control thresholds and limiting maximum speed. Simultaneously, based on the intervention timing and intensity of similar historical scenarios, it predicts and controls the optimal intervention timing and intensity for the current scenario.

[0049] For example, the timing of ABS intervention (manifested as vehicle speed, master cylinder pressure, wheel slip ratio, etc.) and the intensity of intervention (target wheel cylinder pressure) in similar historical scenarios can be directly applied to the control in the current scenario, improving control performance and helping the vehicle return to a safe state as quickly as possible. Simultaneously, the in-vehicle screen will notify the user of the occurrence of ABS anti-lock braking and indicate the intervention method, timing, and intensity employed by the control system.

[0050] Exemplary device like Figure 5 As shown in the illustration, this embodiment also provides a driving safety assistance device based on vehicle positioning, the device comprising: The vehicle driving information acquisition module 10 is used to acquire vehicle driving information, which includes vehicle information and environmental information. The vehicle information includes vehicle speed, acceleration, yaw rate, steering wheel angle, drive torque and braking torque. The environmental information includes location, time, temperature and rainfall.

[0051] The event type acquisition module 20 is used to acquire the event type of a vehicle safety accident or safety risk event when a vehicle safety accident or safety risk event is identified. The comparison module 30 is used to compare the vehicle driving information with the historical vehicle driving information corresponding to the event type according to the event type to obtain the similarity. The intervention control module 40 is used to obtain historical similar scenes matched by the similarity based on the similarity, and control the vehicle driving based on the intervention timing and intensity of the historical similar scenes.

[0052] In one implementation, the event type acquisition module 20 of this embodiment specifically includes: The risk assessment unit is used to monitor the vehicle's driving status in real time. When it detects that the vehicle stability control system has begun to intervene in driving, it determines that a vehicle safety accident or safety risk event has occurred. The event type acquisition unit is used to acquire the event type of vehicle safety accidents or safety risk events. The event type of vehicle safety accidents includes the collision location and collision intensity, while the event type of safety risk events includes the intervention flag position and intensity of the anti-lock braking system, traction control system, yaw stability system, and automatic emergency braking.

[0053] In one implementation, the comparison module 30 of this embodiment specifically includes: The classification unit is used to classify historical vehicle driving information according to event type, resulting in several historical vehicle driving information categories under each event type; The single-item similarity acquisition unit is used to compare the vehicle information and environmental information with the historical classification vehicle driving information corresponding to each event type according to the event type when the vehicle safety accident or safety risk event occurs, and obtain the single-item similarity with each historical classification vehicle driving information. The weighted average unit is used to perform a weighted average of the individual similarities corresponding to the driving information of each historical category of vehicles according to preset weights, so as to obtain the similarity of the driving information of each historical category of vehicles. Among them, the weights of location, rainfall, vehicle speed, and yaw rate are greater than the weights of acceleration, steering wheel angle, driving torque, braking torque, time, and temperature.

[0054] In one implementation, the intervention control module 40 of this embodiment includes: The historical similar scene acquisition unit is used to obtain historical similar scenes based on the historical vehicle driving information corresponding to the maximum value in the similarity of each historical category of vehicle driving information if the maximum value is greater than or equal to a preset similarity threshold. The intervention timing and intensity acquisition unit is used to acquire the intervention timing and intensity of similar historical scenarios.

[0055] The vehicle stability control measures acquisition unit is used to obtain vehicle stability control measures based on the intervention timing and intensity of similar historical scenarios. The control acquisition unit is used to adjust the vehicle stability control threshold and limit the maximum vehicle speed according to the vehicle stability control measures. The safety information prompting unit is used to send safety information prompts based on vehicle safety accidents or safety risk events.

[0056] Based on the above embodiments, the present invention also provides a smart terminal, the principle block diagram of which can be as follows: Figure 6As shown, the smart terminal includes a processor, memory, network interface, display screen, and temperature sensor connected via a system bus. The processor provides computing and control capabilities. The memory includes non-volatile storage media and internal memory. The non-volatile storage media stores the operating system and computer programs. The internal memory provides an environment for the operation of the operating system and computer programs stored in the non-volatile storage media. The network interface is used to communicate with external terminals via a network connection. When the computer program is executed by the processor, it implements a vehicle positioning-based driving safety assistance method. The display screen can be an LCD screen or an e-ink screen. The temperature sensor is pre-installed inside the smart terminal to detect the operating temperature of internal devices.

[0057] Those skilled in the art will understand that Figure 6 The block diagram shown is merely a partial structural diagram related to the present invention and does not constitute a limitation on the smart terminal to which the present invention is applied. A specific smart terminal may include more or fewer components than those shown in the figure, or combine certain components, or have different component arrangements.

[0058] In one embodiment, a smart terminal is provided, comprising a memory, a processor, and a vehicle-location-based driving safety assistance program stored in the memory and executable on the processor. When the processor executes the vehicle-location-based driving safety assistance program, it implements the following operation instructions: Obtain vehicle driving information, which includes vehicle information and environmental information; When a vehicle safety accident or safety risk event is identified, the event type of the vehicle safety accident or safety risk event is obtained; Based on the event type, the vehicle driving information is compared with the historical vehicle driving information corresponding to the event type to obtain the similarity. Based on the similarity, similar historical scenes are obtained; Based on the timing and intensity of interventions in similar historical scenarios, the system controls vehicle movement and sends safety information alerts.

[0059] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium, and when executed, it can include the processes of the embodiments of the above methods. Any references to memory, storage, operational databases, or other media used in the embodiments provided by this invention can include non-volatile and / or volatile memory. Non-volatile memory may include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), or flash memory. Volatile memory may include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in a variety of forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), dual operating data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link DRAM (SLDRAM), RAMbus direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), etc.

[0060] In summary, this invention discloses a driving safety assistance method, device, and intelligent terminal based on vehicle positioning. The method includes: acquiring vehicle driving information; when a vehicle safety accident or safety risk event is detected, acquiring the event type of the vehicle safety accident or safety risk event; comparing the vehicle driving information with historical vehicle driving information corresponding to the event type to obtain a similarity score; obtaining historical similar scenarios matched by the similarity score, and controlling vehicle driving based on the intervention timing and intensity of the historical similar scenarios. This invention, based on vehicle environmental information combined with historical vehicle stability control processes or safety accident information, classifies and marks driving scenarios for safety risks, thereby providing sufficient and effective safety information prompts and vehicle stability control for current similar driving scenarios to achieve the goal of driving safety assistance.

[0061] It should be understood that the various parts of this application can be implemented using hardware, software, firmware, or a combination thereof. In the above embodiments, the N steps or methods can be implemented using software or firmware stored in memory and executed by a suitable instruction execution system. If implemented in hardware, as in another embodiment, it can be implemented using any one or a combination of the following techniques known in the art: discrete logic circuits having logic gates for implementing logical functions on data signals, application-specific integrated circuits (ASICs) having suitable combinational logic gates, programmable gate arrays (PGAs), field-programmable gate arrays (FPGAs), etc.

[0062] Those skilled in the art will understand that all or part of the steps of the methods described in the above embodiments can be implemented by a program instructing related hardware, and the program can be stored in a computer-readable storage medium. When executed, the program includes one or a combination of the steps of the method embodiments.

[0063] Furthermore, the functional units in the various embodiments of this application can be integrated into a processing module, or each unit can exist physically separately, or two or more units can be integrated into a module. The integrated module can be implemented in hardware or as a software functional module. If the integrated module is implemented as a software functional module and sold or used as an independent product, it can also be stored in a computer-readable storage medium.

[0064] The storage medium mentioned above can be a read-only memory, a disk, or an optical disk, etc. Although embodiments of this application have been shown and described above, it is understood that the above embodiments are exemplary and should not be construed as limiting this application. Those skilled in the art can make changes, modifications, substitutions, and variations to the above embodiments within the scope of this application.

Claims

1. A driving safety assistance method based on vehicle positioning, characterized in that, The method includes: Obtain vehicle driving information, wherein the vehicle driving information includes vehicle information and environmental information; Real-time monitoring of vehicle driving status; when the vehicle stability control system begins to intervene in driving, it determines that a vehicle safety accident or safety risk event has occurred. The event type of the vehicle safety accident or safety risk event is obtained, wherein the event type of the vehicle safety accident includes the collision location and collision intensity, and the event type of the safety risk event includes the intervention flag position and intensity of the anti-lock braking system, traction control system, yaw stability system and automatic emergency braking. Based on the event type, the historical vehicle driving information is classified to obtain the historical vehicle driving information corresponding to each event type. The vehicle driving information is then compared with the historical vehicle driving information corresponding to the event type to obtain the similarity. Based on the similarity, historical similar scenes matched by the similarity are obtained, and vehicle driving is controlled based on the intervention timing and intensity of the historical similar scenes.

2. The driving safety assistance method based on vehicle positioning according to claim 1, characterized in that, The vehicle information includes vehicle speed, acceleration, yaw rate, steering wheel angle, drive torque, and braking torque.

3. The driving safety assistance method based on vehicle positioning according to claim 2, characterized in that, The environmental information includes location, time, temperature, and rainfall.

4. The driving safety assistance method based on vehicle positioning according to claim 1, characterized in that, The step of comparing vehicle driving information with historical vehicle driving information corresponding to the event type to obtain similarity includes: Based on the event type at the time of the vehicle safety accident or safety risk event, the vehicle information and environmental information are compared with the historical vehicle driving information corresponding to each event type to obtain the single similarity with each historical vehicle driving information. The similarity of each historical category of vehicle driving information is obtained by weighting the individual similarities of each item according to a preset weight. The weights of location, rainfall, vehicle speed, and yaw rate are greater than the weights of acceleration, steering wheel angle, drive torque, braking torque, time, and temperature.

5. The driving safety assistance method based on vehicle positioning according to claim 4, characterized in that, The step of obtaining historical similar scenes matched based on the similarity includes: If the maximum value of the similarity among the vehicle driving information of each historical category is greater than or equal to a preset similarity threshold, then the historical similar scene is obtained based on the historical vehicle driving information corresponding to the maximum value.

6. The driving safety assistance method based on vehicle positioning according to claim 5, characterized in that, The control of vehicle driving based on the timing and intensity of intervention in the aforementioned historically similar scenarios includes: Obtain the timing and intensity of interventions in the aforementioned historically similar scenarios; Based on the timing and intensity of intervention in the aforementioned historically similar scenarios, vehicle stability control measures are derived. Based on the vehicle stability control measures, adjust the vehicle stability control threshold and limit the maximum vehicle speed; Based on the vehicle safety accident or safety risk event, send a safety information alert.

7. A driving safety assistance device based on vehicle positioning, characterized in that, The device includes: A vehicle driving information acquisition module is used to acquire vehicle driving information, wherein the vehicle driving information includes vehicle information and environmental information; The event type acquisition module is used to acquire the event type of a vehicle safety accident or safety risk event when it is identified that a vehicle safety accident or safety risk event has occurred. The event type acquisition module includes: The risk assessment unit is used to monitor the vehicle's driving status in real time. When it detects that the vehicle stability control system has begun to intervene in driving, it determines that a vehicle safety accident or safety risk event has occurred. The event type acquisition unit is used to acquire the event type of vehicle safety accidents or safety risk events. The event type of vehicle safety accidents includes collision location and collision intensity, while the event type of safety risk events includes the intervention flag position and intensity of the anti-lock braking system, traction control system, yaw stability system, and automatic emergency braking. The comparison module is used to classify historical vehicle driving information according to the event type, obtain historical vehicle driving information corresponding to each event type, and compare the vehicle driving information with the historical vehicle driving information corresponding to the event type to obtain the similarity. An intervention control module is used to obtain historical similar scenes matched by the similarity based on the similarity, and control vehicle driving based on the intervention timing and intensity of the historical similar scenes.

8. A smart terminal, characterized in that, The smart terminal includes a memory, a processor, and a vehicle positioning-based driving safety assistance program stored in the memory and executable on the processor. When the processor executes the vehicle positioning-based driving safety assistance program, it implements the steps of the vehicle positioning-based driving safety assistance method as described in any one of claims 1-6.

9. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a vehicle-positioning-based driving safety assistance program, which, when executed by a processor, implements the steps of the vehicle-positioning-based driving safety assistance method as described in any one of claims 1-6.

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