Method for vehicle predictive warning and corresponding system

Abstract

A method and system for vehicle predictive warning is provided. [Solution] The method includes acquiring an image of the surroundings of the vehicle, detecting mark features from the acquired image, analyzing the mark features to determine whether the vehicle has entered a risk area, and if it is determined that the vehicle has entered the risk area, issuing safety reminder information to the vehicle or vehicle personnel. By using the solution of the present invention, it is possible to determine that the vehicle has entered a risk area, such as an energy refueling station, by detecting and analyzing mark features in the image of the surroundings of the vehicle, and to timely issue safety reminder information to the vehicle or vehicle personnel to avoid potential risk accidents and improve the safety of the vehicle personnel and the environment in which they are located.

Description

[Technical Field]

[0001] The present invention relates to the field of vehicle predictive warning, and more particularly to a method, a system and a vehicle including the same for vehicle predictive warning, a corresponding computer device and a computer-readable storage medium. [Background technology]

[0002] When a vehicle enters a risk area, such as an energy refueling station, attention should be paid to the safe operation of the vehicle or the safety conditions of the environment in which the vehicle is located, in order to avoid potential risk failures or accidents such as leakage of refueling energy, fire or explosion in the risk area due to improper operation behavior of the vehicle or vehicle personnel. In addition, if there are explosive, flammable or toxic gases in the environment in which the vehicle is located, it is necessary to alert the vehicle or vehicle personnel to avoid dangerous situations such as fire, explosion or poisoning due to improper operation behavior of the vehicle or vehicle personnel.

[0003] Therefore, a method for providing a warning to the vehicle is required. Summary of the Invention [Problem to be solved by the invention]

[0004] In order to at least solve the above technical problems, the present invention provides the following vehicle predictive warning method, system, vehicle including the same, corresponding computer device, and computer-readable storage medium. [Means for solving the problem]

[0005] According to a first aspect of the present invention, there is provided a method for vehicle predictive warning, the method including: acquiring an image of a vehicle's surroundings; detecting a mark feature from the acquired image; analyzing the mark feature to determine whether the vehicle has already entered a risk area; and issuing safety alert information to the vehicle or vehicle personnel if it is determined that the vehicle has already entered the risk area.

[0006] In one embodiment, the method further includes obtaining other environmental information about the surroundings of the vehicle, the other environmental information including a target gas concentration, a sound volume, a temperature, or a humidity level about the surroundings of the vehicle.

[0007] In one embodiment, the method further includes comparing the other environmental information with a corresponding threshold value, and if the other environmental information is greater than the corresponding threshold value, activating a first collection module to acquire the image of the vehicle surroundings and then detecting mark features from the acquired image.

[0008] In one embodiment, the mark features include a size of a mark characterizing a risk in the image, and the method further includes indicating that the vehicle is approaching the risk area when a proportion of the detected mark features in the acquired image gradually increases but has not yet exceeded a set threshold, and indicating that the vehicle has already entered the risk area when the proportion of the detected mark features in the acquired image exceeds the set threshold.

[0009] In one embodiment, the risk area comprises an energy refueling station, a chemical storage area, or a high voltage area, and the marking feature comprises an energy refueling station marking feature, a chemical storage area, or a high voltage marking feature.

[0010] In one embodiment, the safety reminder information includes reminding the vehicle or vehicle personnel to avoid fire sources and static electricity, not use mobile phones, close vehicle windows, and / or shut off the engine if necessary.

[0011] According to a second aspect of the present invention, there is provided a system for vehicle predictive warning, the system including a first collection module configured to acquire an image of the surroundings of the vehicle, a detection module configured to detect a mark feature from the acquired image, a first judgment module configured to analyze the mark feature to determine whether the vehicle has already entered a risk area, and a control module configured to issue safety warning information to the vehicle or vehicle personnel when the vehicle has already entered the risk area.

[0012] In one embodiment, the system further includes a second collection module configured to acquire other environmental information around the vehicle, the other environmental information including a target gas concentration, a sound volume, a temperature, or a humidity around the vehicle.

[0013] In one embodiment, the system further includes a second determination module configured to compare the other environmental information with a corresponding threshold, and if the other environmental information is greater than the corresponding threshold, activate the first collection module to acquire the image of the vehicle surroundings, and then cause the detection module to detect mark features from the acquired image.

[0014] In one embodiment, the mark feature includes a size of a mark that characterizes a risk in the image, and the first judgment module is further configured to indicate that the vehicle is approaching the risk area when the proportion of the size of the detected mark feature in the acquired image gradually increases but has not yet exceeded a set threshold, and to indicate that the vehicle has already entered the risk area when the proportion of the size of the detected mark feature in the acquired image exceeds the set threshold.

[0015] According to a third aspect of the present invention, there is provided a vehicle, the vehicle including a system for vehicle predictive warning as described above.

[0016] According to a fourth aspect of the present invention, there is provided a computer device including a memory and a processor, wherein computer instructions are stored on the memory, and when the computer instructions are executed by the processor, the method for vehicle predictive warning according to any one of the above embodiments is performed.

[0017] According to a fifth aspect of the present invention, there is provided a non-transitory computer-readable storage medium having stored thereon a computer program, the computer program being characterized in that, when executed by a processor, the method for vehicle predictive warning as described above is performed. [Effects of the Invention]

[0018] The solution of the present invention determines whether a vehicle has entered a risk area by analyzing mark features detected from images captured around the vehicle. When the vehicle enters the risk area, safety alert information is issued to the vehicle or vehicle personnel. The present invention can also obtain other environmental information around the vehicle, such as gas concentration, sound volume, temperature, or humidity, through other sensors to assist or make the risk pre-judgment in advance. Advantageously, when the vehicle enters a risk area (e.g., an energy refueling station, e.g., a gas station or charging station), safety alert information is issued to the vehicle or vehicle personnel in a timely manner, so that the vehicle or vehicle user can pay attention to the relevant potential risks and take necessary actions to avoid potential risk failures or accidents, thereby improving the safety of the vehicle personnel or the environment in which it is located. [Brief explanation of the drawings]

[0019] Non-limiting and non-exhaustive embodiments of the present invention are described with reference to the following drawings, in which: [Figure 1A] 1 exemplarily shows a schematic flow chart of a method for vehicle predictive warning according to one embodiment of the present invention; [Figure 1B] 4 exemplarily shows a schematic flow chart of a method for vehicle predictive warning according to another embodiment of the present invention; [Figure 2] 1 exemplarily shows a schematic flow chart of a method for vehicle predictive warning according to an embodiment of the present invention; [Figure 3A] 1 shows an exemplary schematic block diagram of a system for vehicle predictive warning according to one embodiment of the present invention; [Figure 3B] 2 shows an exemplary schematic block diagram of a system for vehicle predictive warning according to another embodiment of the present invention;

[0020] Artisans will appreciate that elements in the figures are illustratively shown for simplicity and clarity and have not necessarily been drawn to scale, and that common but easily understood elements useful or necessary in commercially feasible embodiments are not generally depicted so as not to obscure the view of these respective embodiments of the present invention. DETAILED DESCRIPTION OF THE INVENTION

[0021] In the following description, numerous specific details are set forth in order to provide a thorough understanding of the present invention. However, it will be apparent to those skilled in the art that the specific details are not required to practice the present invention. In other instances, well-known methods have not been described in detail to avoid obscuring the present invention.

[0022] References throughout this specification to "one embodiment," "one embodiment," "another embodiment," "another embodiment," "one example," "one example," and "another example" mean that the specific features, structures, or characteristics described in connection with this embodiment or example are included in at least one embodiment of the present invention, and do not necessarily refer to the same embodiment or example. However, the specific features, structures, or characteristics may be combined in any suitable combinations and / or subcombinations in one or more embodiments or examples.

[0023] FIG. 1A exemplarily illustrates a schematic flow chart of a method 100 for vehicle predictive warning according to one embodiment of the present invention, and FIG. 1B exemplarily illustrates a schematic flow chart of a method 100′ for vehicle predictive warning according to another embodiment of the present invention.

[0024] Referring to FIG. 1A, the method 100 includes steps S102, S104, S106 and S107.

[0025] In step S102, an image of the surroundings of the vehicle is acquired. For example, the image of the surroundings of the vehicle can be acquired through a first acquisition module (for example, an image sensor, such as a camera, mounted inside or outside the vehicle), and may include, for example, images within a camera's capture range in front of, behind, or on both sides of the vehicle.

[0026] In step S104, mark features are detected from the acquired image, which may include information such as the size, pattern, shape, or color of the mark that characterizes the risk area.

[0027] In some examples, the risk area may include an energy refueling station (e.g., a gas station, charging station, or gas station), a chemical storage area (e.g., a chemical warehouse), a high voltage area, or other area that may cause a hazard to occur.

[0028] For example, if the risk area is an energy refueling station (e.g., a gas station), mark features may include the following: a gas station sign typically includes a single large fuel pump icon or vehicle refueling graphic sign, typically has an oil company trademark and corresponding prominent color, and also has a prominent text sign such as "gas station."

[0029] For example, if the risk area is a gas station, the marking features may include the following: a gas station sign typically has an icon of a gas cylinder or a chemical molecular model of natural gas, the sign includes text such as "gas" or "natural gas," and is a commonly used warning color, such as yellow or orange.

[0030] For example, if the risk area is a chemical warehouse, the marking features may include: an icon of a hazardous chemical, such as a skull and crossbones to represent toxicity; a general warning color may be a black pattern on a yellow background, with warning text such as "Danger" or "Toxic" present.

[0031] Further for example, if the risk area is a high voltage area, the marking features may include signs that typically include a lightning arrow pattern, represent an electrical hazard, use a warning yellow or orange background, and often have text warnings such as "high voltage," "danger," or "keep out."

[0032] It is contemplated that in other areas that can cause the occurrence of danger, the discriminant analysis of mark features for other risk areas can be extended by adding other relevant mark features.

[0033] In step S106, the mark feature is analyzed to determine whether the vehicle has already entered a risk area. Specifically, for example, an image identification analysis can be performed on the mark feature. If the mark feature is identified as belonging to a sign corresponding to a designated risk area, the vehicle is considered to have already entered the risk area. In one embodiment, entering a risk area may be defined as the vehicle simply entering the risk area. In another embodiment, entering a risk area may be defined as the vehicle approaching the risk area. For example, if an actual risk area is defined by a significant physical boundary, the vehicle may be considered to have already entered the risk area when it is within the boundary, or may be considered to be approaching the risk area when it is close to the outer boundary. In addition, for some risk areas, such as an area where an energy delivery vehicle is present ahead, the area where the energy delivery vehicle exists may not have a strict boundary, and in this case, entering the risk area may be considered to be approaching or having already entered the risk area. It should be understood that entering a risk area may be considered to indicate the presence of a potentially dangerous situation that may occur at this time.

[0034] In step S107, when the vehicle enters the risk area, a safety alert message is issued to the vehicle or vehicle personnel. In one embodiment, the safety alert message may be provided via other means, such as visual, auditory, or tactile.

[0035] In one embodiment, the method 100 may further include acquiring other environmental information around the vehicle, where the other environmental information includes a gas concentration, a sound volume, a temperature, or a humidity around the vehicle. For example, the gas concentration, the sound volume, the temperature, or the humidity around the vehicle may be acquired via a gas sensor (e.g., an odor sensor), a sound sensor, a temperature sensor, or a humidity sensor, respectively.

[0036] 1B, in one embodiment, the method 100′ may further include step S108 in addition to steps S102, S104, S106, and S107 shown in FIG. 1A. In step S108, the other environmental information is compared with a corresponding threshold. If the other environmental information is greater than the corresponding threshold, the first collection module is activated to acquire the image around the vehicle and then detect mark features from the acquired image. In other words, in one embodiment, the method described in detail in steps S102, S104, S106, and S107 can be executed only if any one or more of the target gas concentration, sound volume, temperature, and humidity around the vehicle are greater than the corresponding threshold, as a prerequisite for activating the first collection module to acquire the image around the vehicle. For example, the vehicle can be directly controlled to activate a first collection module mounted thereon to acquire the image of the vehicle's surroundings only when any one or more of the target gas concentration, sound volume, temperature or humidity around the vehicle is greater than its corresponding threshold, or to issue appropriate warning information to vehicle occupants while simultaneously activating the first collection module to acquire the image of the vehicle's surroundings.

[0037] In one embodiment, method 100, method 100', or step S106 may further include indicating that the vehicle is approaching the risk area when the ratio of the size of the detected mark in the image acquired in real time gradually increases but has not yet exceeded a set threshold, and indicating that the vehicle has already entered the risk area when the ratio of the size of the detected mark in the image acquired in real time exceeds the set threshold. The set threshold may refer to the proportion of the size of the mark and the acquired image, and may be flexibly set for different marks depending on the actual size of the mark corresponding to a specific risk area.

[0038] In one embodiment, for the above-mentioned set threshold of the proportion of the size of the mark in the image, an appropriate set threshold may be selected by comprehensively considering the following three important factors: 1. actual size of the mark feature: understanding the physical size of the mark feature can help set a reasonable threshold for the viewing angle of the first collection module (e.g., camera), 2. resolution and viewing angle of the first collection module (e.g., camera): different first collection modules (e.g., cameras) may have different resolutions and viewing angle widths, and these factors will affect the size representation of the mark in the collected image, and 3. type and size of the vehicle: vehicles of different sizes and types may stop at different distances, so it may be necessary to set a threshold range that accommodates different types of vehicles. Based on the consideration of the above three factors, the set threshold range may be, for example, between 90% and 150%, where 90% represents that the mark is entirely contained within the boundary of the collected image space and the size of the mark (i.e., the area of ​​the entire mark) occupies 90% of the area of ​​the image acquired by the first acquisition module (e.g., camera), and 150% represents that a portion of the mark (e.g., a significant portion of the mark, e.g., a central portion) has already completely covered the area of ​​the image acquired by the first acquisition module, and the ratio of the size of the mark (i.e., the area of ​​the entire mark including the portion not represented in the image) to the area of ​​the image acquired by the first acquisition module (e.g., camera) is 150%. In one embodiment, based on the above three factors, the set threshold may be, for example, 100%, 120%, or 125%.

[0039] As noted above, in one embodiment, the risk area may be an energy refueling station, e.g., a gas station or a charging station, and the marking feature may be an energy refueling station marking feature, e.g., a gas station or a charging station sign. In another embodiment, the safety reminder information may include at least a reminder to the vehicle or vehicle personnel to avoid fires and static electricity, not use mobile phones (especially at gas stations), close vehicle windows, and / or shut off the engine if necessary (e.g., shut off a fuel engine before refueling or shut off an electric motor before charging).

[0040] Specifically, since the energy refueling station is a place with potential risks, when the driver drives the vehicle to the energy refueling station, there are some potential dangers and problems, and the driver needs to be aware of the relevant precautions, such as: - Fire and static electricity: Energy refueling stations are flammable and explosive environments, so you must stay away from any fire sources, including lit cigarettes, open flames, and lighters. Static electricity can also cause fires, so you must stay away from your vehicle when refueling and touch a metal part to eliminate static electricity. - Regarding the use of mobile phones: As electromagnetic radiation from mobile phones can cause fires, please refrain from using mobile phones as much as possible, answering calls or sending text messages near energy refueling stations, especially gas stations. - Regarding engine shutdown: Before refueling, ensure that the vehicle's fuel engine has already shut down to avoid gasoline spills or accidental starting of the vehicle; before charging, ensure that the vehicle's electric motor has already shut down to avoid electrical leakage or accidental starting of the vehicle.

[0041] 2 exemplarily shows a schematic flowchart of a method 200 for vehicle predictive warning according to an embodiment of the present invention. The method 200 includes steps S201 to S221. In this embodiment, the risk area is a gas station, and the mark feature is a gas station mark feature.

[0042] 2, a method for performing a vehicle pre-warning based on a gas sensor and a camera when a vehicle is approaching or has already entered a gas station will be described in detail. For example, the gas sensor and the camera may be used to detect whether the vehicle has entered a gas station, and preferably, after the gas sensor and the camera detect that the vehicle has entered the gas station, a safety pre-warning alert is issued to vehicle personnel (e.g., the driver) to be aware of the above-mentioned dangers and problems, during the preparation for refueling or the refueling process. However, the timing of the safety alert is not limited to the preparation for refueling or the refueling process, and may be any of the above-mentioned descriptions for the timing of the safety alert (not further described in this embodiment).

[0043] In response to the above-mentioned risks and problems, this method 200 implements an innovative vehicle pre-alarm and identification method that can be used to accurately detect and confirm when a vehicle enters a gas station. The method aims to improve safety and identification efficiency by skillfully combining external gas sensors and cameras (e.g., high-precision visual cameras).

[0044] First, the method 200 detects the gasoline concentration in the surrounding environment using gas sensors mounted on the exterior of the vehicle, and when these sensors detect that the gasoline concentration exceeds a preset safety threshold, it immediately activates a camera to begin carefully observing the environment around the vehicle.

[0045] The camera then pays particular attention to the gas station's distinctive features, such as a gas pump. When the camera identifies these gas station features, it can accurately determine that the vehicle has already approached or entered the gas station area. If the size of these features gradually increases in the image captured by the camera but does not exceed a preset threshold, it can further determine that the vehicle is heading toward the gas station's interior.

[0046] Most importantly, if the size of the gas station mark in the image exceeds another set threshold, it is determined that the vehicle has safely entered the gas station and is ready to begin refueling. At this time, method 200 automatically reports this detection result to the vehicle central control system or the vehicle pre-warning system. The vehicle pre-warning system then issues pre-warning safety warning information to alert the vehicle or vehicle personnel (e.g., the driver) to pay attention to related safety issues and potential dangers, such as avoiding fires and static electricity, not using mobile phones, and turning off the engine, as mentioned above.

[0047] In summary, this embodiment detects according to the gas sensor and camera, and determines whether a gas station scene has been entered according to the size of the gas station mark in the image, thereby greatly improving the safety standards of gas stations and ensuring the safety of drivers and passengers.

[0048] Specifically, in step S201, environmental odor data collection can be performed. Specifically, multiple gas sensors are installed at strategic locations on the vehicle (e.g., the front bumper, sides) to specifically detect and analyze the gas composition in the environment, especially gasoline vapor. These sensors have high sensitivity and a fast response time, making it easy to accurately capture gas changes in the environment.

[0049] In step S203, odor data preprocessing can be performed. Specifically, the collected gas data is first subjected to a noise reduction process to remove the influence of environmental factors (e.g., temperature, humidity) on the sensor readings. The data is then standardized to ensure comparability across different environments and conditions.

[0050] In step S205, specific calculations of the odor data can be performed. Specifically, advanced chemical analysis algorithms, such as gas chromatography analysis, can be used to accurately calculate the proportions of various components in the gas sample, particularly the concentration of gasoline vapors, to facilitate subsequent analysis and interpretation.

[0051] In step S207, a gasoline odor concentration threshold determination can be performed. Specifically, a safety threshold is set. If the gasoline vapor concentration detected by the gas sensor exceeds this threshold, it is considered that a potential danger exists in the environment, and step S209 is entered. This threshold should be set based on safety standards and experimental data. Conversely, if the gasoline vapor concentration detected by the gas sensor does not exceed this threshold, the process returns to step S205.

[0052] In step S209, image data collection can be performed using cameras. Specifically, after determining that the gasoline vapor concentration exceeds a threshold, the vehicle's cameras, particularly the front and side cameras of the vehicle, are immediately activated. These cameras should be capable of capturing high-resolution video or static images to facilitate subsequent image analysis.

[0053] In step S211, image data preprocessing can be performed. Specifically, the image data captured by the camera is preprocessed to improve image quality, including adjusting contrast and brightness, removing noise and blur, etc., to ensure that the processed image is clear and makes it easier to identify objects in the image.

[0054] In step S213, a target detection algorithm can be applied. Specifically, an efficient target detection algorithm, such as a convolutional neural network (CNN) based on deep learning, can be employed to identify and classify various objects in the image, particularly gas station-specific marks (e.g., gas pumps, company logos).

[0055] In step S215, gas station mark feature detection can be performed. Specifically, if a gas station mark is detected through image analysis, the algorithm determines that the vehicle has already approached or entered the gas station range. At this time, this event is recorded, and the specific location of the vehicle is further analyzed based on the type and location of the mark, and then the process proceeds to step S217. Conversely, if a gas station mark is not detected, the process returns to step S213.

[0056] In step S217, a mark size change analysis can be performed. Specifically, the size change of the gas station marks in the image is continuously detected. If these marks gradually increase in size in consecutive image frames but do not exceed a preset threshold, it is determined that the vehicle is driving toward the gas station.

[0057] In step S219, a determination can be made as to whether the vehicle is ready for refueling. Specifically, if the camera indicates that the vehicle has stopped moving and the size of the gas station mark exceeds the preset threshold, it is determined that the vehicle has already stopped at the gas station and is ready for refueling. At this time, the vehicle's stopped state and time are recorded, preparations for the refueling process are made, and the process proceeds to step S221. Conversely, if the camera indicates that the vehicle has not stopped moving or the size of the gas station mark does not exceed the preset threshold, the process returns to step S217.

[0058] In step S221, a result report and a safety warning can be performed. Specifically, after all the above steps are completed, the detection result is reported to the vehicle's central control system or the vehicle warning system. At the same time, a safety warning is issued to the vehicle or vehicle personnel (e.g., the driver) to alert them to potential dangers and take appropriate measures, such as stopping the engine, avoiding the use of mobile phones, and paying attention to static electricity and fire, to ensure safety during the refueling process.

[0059] FIG. 3A exemplarily illustrates a schematic block diagram of a system 30 for vehicle predictive warning according to one embodiment of the present invention, and FIG. 3B exemplarily illustrates a schematic block diagram of a system 30′ for vehicle predictive warning according to another embodiment of the present invention.

[0060] 3A, the system 30 may include at least a first acquisition module 302, a detection module 304, a first determination module 306, and a control module 307. The first acquisition module 302 may include at least one image sensor.

[0061] In one embodiment, the first collection module 302 is configured to acquire an image of the vehicle's surroundings. The detection module 304 is configured to detect a mark feature from the acquired image. The first determination module 306 is configured to analyze the mark feature to determine whether the vehicle has already entered a risk area. The control module 307 is further configured to issue a safety alert to the vehicle or vehicle personnel if it determines that the vehicle has already entered a risk area.

[0062] In one embodiment, the system 30 may further include a second collection module (not shown) configured to acquire other environmental information about the vehicle's surroundings, including target gas concentrations, sound volume, temperature, or humidity. The second collection module may include at least a gas sensor (e.g., an odor sensor), a sound sensor, a temperature sensor, or a humidity sensor.

[0063] 3B, in one embodiment, the system 30′ may further include a second determination module 308 in addition to the first collection module 302, the detection module 304, the first determination module 306, and the control module 307 shown in FIG. 3A. The second determination module 308 is configured to compare the other environmental information with a corresponding threshold, and if the other environmental information is greater than the corresponding threshold, activate the first collection module 302 to acquire the image of the vehicle surroundings, and then cause the detection module to detect mark features from the acquired image.

[0064] In one embodiment, the first judgment module 306 may be further configured to indicate that the vehicle is traveling toward the risk area when the ratio of the size of the detected mark in the image acquired in real time gradually increases but has not yet exceeded a set threshold, and to indicate that the vehicle has already entered the risk area when the ratio of the size of the detected mark in the image acquired in real time exceeds the set threshold.

[0065] The system for vehicle early warning herein can be similarly extended using the method for vehicle early warning of any one of the above embodiments or examples, and will not be further described here.

[0066] Advantageously, a method for vehicle predictive warning based on a first collection module (e.g., a camera) and a second collection module (e.g., an environmental sensor such as a gas sensor located outside the vehicle) has a wide range of advantages:

[0067] - Improved safety: By detecting in a timely manner when the concentration of gasoline vapor in the environment exceeds the standard, or when an unexpected fire or electrical leak occurs, it can provide a pre-warning before the vehicle enters a risky environment (such as a gas station or charging station), reducing the risk of accidents caused by oil or gas leaks or other dangerous conditions. - Accuracy and reliability: The method of combining the first and second collection modules improves the accuracy and reliability of identification, which is very important to ensure the safety and smooth operation of the energy refueling station; - Precautions and warnings: When a potential danger is detected, possible accidents can be prevented by immediately alerting the driver and passengers to take safety measures, for example by switching off the engine if necessary and not using mobile phones.

[0068] It should be noted that the above method for vehicle warning can be used in a variety of existing or future products, such as: - Smart Car Safety Systems: By integrating the technology involved in this method into the safety systems of smart cars, drivers can be automatically alerted to take safety precautions when approaching a gas station or charging station. This is particularly useful for autonomous vehicles and can be part of their safety protocols.

[0069] - Emergency response systems: The technology involved in this method can be combined with fire and emergency response systems to improve the speed and efficiency of response to potential fires or chemical leaks at gas stations or charging stations.

[0070] In summary, the method for vehicle predictive warning based on such a first collection module and a second collection module has wide applicability and can enhance safety in risk areas, environmental sustainability, and vehicle traffic efficiency within multiple fields.

[0071] Another aspect of the present invention provides a vehicle including the system for vehicle predictive warning described above. The vehicle may be an internal combustion engine vehicle powered by an internal combustion engine, an electric vehicle or fuel cell vehicle powered by an electric motor, or a hybrid vehicle powered by both of the above.

[0072] Another aspect of the present invention provides a computer device, including a memory and a processor, wherein computer instructions are stored in the memory, and when executed by the processor, the method for vehicle predictive warning described above is performed. The computer device may broadly be a server, an in-vehicle terminal, or any other electronic device having necessary computing and / or processing capabilities. In one embodiment, the computer device may include a processor, memory, a network interface, a communication interface, etc., connected via a system bus. The processor of the computer device may be used to provide the necessary computing, processing, and / or control capabilities. The memory of the computer device may include a non-volatile storage medium and internal memory. An operating system, a computer program, etc. may be stored in or on the non-volatile storage medium. The internal memory may provide an environment for the operation of the operating system and the computer program stored in the non-volatile storage medium. The network interface and communication interface of the computer device may be used to connect to and communicate with external devices via a network. When the computer program is executed by the processor, the steps of any one of the methods for vehicle predictive warning described above can be performed.

[0073] Another aspect of the present invention further provides a computer-readable storage medium having a computer program stored thereon, the computer program realizing, when executed by a processor, the method for vehicle predictive warning described in any one of the above embodiments or examples.

[0074] As will be understood by those skilled in the art, all or part of the steps of the method for vehicle predictive warning described above can be instructed to be completed by a computer program that instructs associated hardware, such as a computer device or processor. The computer program can be stored in a non-transitory computer-readable storage medium, and when the computer program is executed, the steps of the method for vehicle predictive warning of the present invention are performed. In some cases, any reference to memory, storage device, database, or other medium in this specification may include non-volatile and / or volatile memory. Examples of non-volatile memory include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), flash memory, magnetic tape, floppy disk, magneto-optical data storage device, optical data storage device, hard disk, solid-state disk, etc. Examples of volatile memory include random access memory (RAM), external high-speed cache memory, etc.

[0075] The above description of exemplary embodiments or examples of the present invention, including what is set forth in the Abstract, is not intended to be exhaustive or to be limited to the precise form disclosed. While specific embodiments and examples of the present invention have been described herein for illustrative purposes, various equivalent modifications are possible without departing from the broader spirit and scope of the present invention.

Claims

1. 1. A method for vehicle predictive warning, comprising: Acquiring an image of the vehicle's surroundings; Detecting mark features from the captured image; analyzing the marking feature to determine whether the vehicle has already entered a risk area; and issuing a safety alert to the vehicle or vehicle personnel if it is determined that the vehicle has already entered the risk area.

2. 2. The method of claim 1, further comprising acquiring other environmental information around the vehicle, the other environmental information comprising a target gas concentration, a sound volume, a temperature, or a humidity around the vehicle.

3. The method comprises: comparing the other environmental information with a corresponding threshold; 3. The method of claim 2, further comprising: if the other environmental information is greater than the corresponding threshold, activating a first collection module to acquire the image of the vehicle surroundings, and then detecting mark features from the acquired image.

4. The mark characteristics include at least a size of a mark characterizing a risk area in the image, and the method further comprises: If the proportion of the size of the detected mark in the acquired image gradually increases but does not exceed a set threshold, it indicates that the vehicle is traveling toward the risk area; 2. The method of claim 1, further comprising: indicating that a vehicle has already entered the risk area if a ratio of a size of the detected mark in the acquired image exceeds the set threshold.

5. 5. The method of claim 1, wherein the risk area includes an energy refueling station, a chemical storage area, or a high voltage area, and the marking feature includes an energy refueling station marking feature, a chemical storage area, or a high voltage marking feature.

6. 6. The method of claim 5, wherein the safety reminder information includes reminding the vehicle or vehicle personnel to avoid fire sources and static electricity, not use mobile phones, close vehicle windows and / or shut off the engine if necessary.

7. A system for vehicle early warning, comprising: a first acquisition module configured to acquire an image of the vehicle's surroundings; a detection module configured to detect mark features from the acquired image; a first determination module configured to analyze the mark feature to determine whether the vehicle has already entered a risk area; and a control module configured to issue a safety alert to the vehicle or vehicle personnel if it determines that the vehicle has already entered the risk area.

8. 8. The system of claim 7, further comprising a second collection module configured to acquire other environmental information around the vehicle, the other environmental information including a target gas concentration, a sound volume, a temperature, or a humidity around the vehicle.

9. The system further includes a second determination module, the second determination module comprising: comparing the other environmental information with a corresponding threshold; 9. The system of claim 8, further comprising: if the other environmental information is greater than the corresponding threshold, activating a first collection module to acquire the image of the vehicle surroundings, and then causing the detection module to detect mark features from the acquired image.

10. The mark feature includes at least a size of a mark that characterizes a risk in the image, and the first judgment module further includes: If the proportion of the size of the detected mark in the acquired image gradually increases but does not exceed a set threshold, this indicates that the vehicle is moving closer to the risk area; and 8. The system of claim 7, configured to indicate that a vehicle has already entered the risk area if the proportion of the size of the detected mark in the acquired image exceeds the set threshold.

11. 11. The system of claim 7, wherein the risk area includes an energy refueling station, a chemical storage area, or a high voltage area, and the marking feature includes an energy refueling station marking feature, a chemical storage area, or a high voltage marking feature.

12. 11. The system of claim 10, wherein the safety reminder information includes reminding the vehicle or vehicle personnel to avoid fire sources and static electricity, not use mobile phones, close vehicle windows, and / or shut off the engine if necessary.

13. A vehicle comprising a system for vehicle predictive warning according to any one of claims 7 to 10 and 12.

14. 5. A computer device including a memory in which computer instructions are stored and a processor, wherein, when the computer instructions are executed by the processor, the computer device performs the method for vehicle predictive warning according to any one of claims 1 to 4.

15. 5. A non-transitory computer-readable storage medium having a computer program stored thereon, the computer program being adapted to perform the method for vehicle predictive warning according to claim 1 when executed by a processor.

16. A program that, when executed by a processor, implements the method for vehicle predictive warning according to any one of claims 1 to 4.

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