Vehicle-mounted thunder and lightning early warning method and system, electronic equipment and storage medium

Abstract

The invention discloses a vehicle-mounted thunder and lightning early warning method and system, electronic equipment and a storage medium, and relates to the field of vehicle safety early warning, and the method comprises the steps: obtaining thunder and lightning early warning data of a target vehicle position, target vehicle surrounding electrostatic field intensity data and vehicle surrounding cloud layer charge density data, and the thunder and lightning early warning data comprises a thunder and lightning probability and thunderbolt time; obtaining a lightning risk dynamic arbitration algorithm, wherein the algorithm comprises cloud data verification and local sensing verification; the cloud data verification comprises the following steps: if the lightning probability is greater than a preset threshold and the thunderbolt time is less than a preset time threshold, activating an electric field sensor; the local sensing verification comprises the following steps: if the electrostatic field intensity is greater than a preset threshold value, activating the millimeter wave radar; if the charge density is greater than a preset threshold value and / or the electrostatic field intensity is greater than a preset threshold value, entering risk confidence coefficient calculation; and triggering corresponding early warning and protection actions according to the risk confidence.

Description

Technical Field

[0001] This application relates to the field of vehicle safety warning, and in particular to a vehicle-mounted lightning warning method, a vehicle-mounted lightning warning system, electronic equipment, and storage medium. Background Technology

[0002] Currently, lightning risk warnings for consumers are mainly concentrated on mobile devices, including officially authorized apps from the China Meteorological Administration such as "Thunder Weather" (formerly "China Lightning"). These apps provide location-based, minute-by-minute lightning forecasts and warnings, as well as hazard assessments, to the public. When lightning risks are imminent, they alert users to take shelter through app push notifications and SMS messages.

[0003] Mobile devices have limitations in providing early warnings. For example, in scenarios such as camping, hiking, or working outdoors, users are often far from their phones (e.g., fishing by a river or resting in a tent). In these situations, the reach of mobile alarm notifications is low, and users are unlikely to perceive the risk of lightning. Furthermore, mobile devices lack information about the user's environment and cannot provide the most accurate avoidance solutions (e.g., mobile devices cannot detect whether there are places nearby where users can avoid the risk of lightning).

[0004] Vehicles themselves are relatively safe lightning shelters because the metal body of a vehicle can form a "Faraday cage" effect, conducting the lightning current to the ground and protecting the safety of the occupants. The value of vehicles as lightning shelters in the field has been proven.

[0005] In view of the shortcomings of the existing technology, there is an urgent need for a vehicle-mounted lightning risk early warning system. Summary of the Invention

[0006] In view of this, the purpose of the present invention is to provide a vehicle-mounted lightning warning method, a vehicle-mounted lightning warning system, an electronic device, and a storage medium, aiming to provide a vehicle-mounted lightning risk warning solution. That is, in scenarios such as camping in the wild, hiking outdoors, or working, when the user is away from the mobile device, the vehicle-mounted system monitors the lightning risk in real time through vehicle body sensors and cloud data, and uses the vehicle's external speakers to broadcast an alarm to guide the user to return to the vehicle in time to avoid the lightning risk, so as to avoid missing the opportunity to avoid danger because the mobile phone is not nearby.

[0007] This invention provides the following solution:

[0008] According to one aspect of this application, a vehicle-mounted lightning warning method is provided, comprising the following steps:

[0009] Acquire lightning warning data of the target vehicle's location, electrostatic field strength data around the target vehicle, and cloud charge density data around the vehicle. The lightning warning data includes lightning probability and lightning strike time.

[0010] The algorithm for obtaining dynamic arbitration of lightning risk includes: cloud data verification and local sensor verification;

[0011] The cloud data verification includes: if the lightning probability is greater than a preset threshold and the lightning strike time is less than a preset time threshold, then local sensor verification is activated.

[0012] Local sensor verification includes: detecting electrostatic field strength; if the electrostatic field strength is greater than a preset threshold, then activating charge density detection.

[0013] If the charge density is greater than a preset threshold and / or the electrostatic field strength is greater than a preset threshold, then proceed to the risk confidence calculation.

[0014] The risk confidence calculation is as follows: Comprehensive lightning probability = Cloud lightning probability × First coefficient + Electric field strength factor × Second coefficient + Radar charge factor × Third coefficient;

[0015] Based on the stated risk confidence level, corresponding early warning and protective actions are triggered.

[0016] Furthermore, including:

[0017] Based on the risk confidence level, corresponding early warning and protective actions are triggered, including:

[0018] If the overall probability of lightning is less than the preset threshold, it is judged as low risk, and a yellow lightning icon will be displayed on the dashboard.

[0019] If the overall probability of lightning falls within the preset threshold range, it is determined to be of medium risk, triggering a lightning warning pop-up window to appear on the vehicle's touchscreen.

[0020] If the overall probability of lightning exceeds a preset threshold, it is judged as high risk, triggering the external speakers to start and the vehicle lights to flash.

[0021] Furthermore, including:

[0022] In local sensor calibration, the preset threshold for electrostatic field strength is 1.5 kV / m, and the preset threshold for charge density is 15 nC / m³.

[0023] When the detected electrostatic field strength value is >1.5kV / m, the millimeter-wave radar is activated to scan the charge density of the clouds around the vehicle.

[0024] When the charge density detection value is >15nC / m³, proceed to the risk confidence calculation step.

[0025] Furthermore, including:

[0026] Triggering corresponding early warning and protective actions based on the aforementioned risk confidence level also includes:

[0027] The vehicle's cameras detect in real time whether any users have entered the vehicle.

[0028] If a user is detected entering the vehicle, the system will automatically close all windows and prompt the user to close the doors.

[0029] Continuously monitor the overall lightning probability. Once the overall lightning probability drops below the low-risk threshold, the warning will be lifted.

[0030] Furthermore, including:

[0031] The specific lightning warning data obtained for the current vehicle location includes:

[0032] The vehicle's real-time location information is obtained through the vehicle's infotainment system.

[0033] Based on real-time location information, the system receives lightning warning data corresponding to the current vehicle location. This lightning warning data serves as the data source for lightning probability and strike time.

[0034] Furthermore, including:

[0035] Triggering the activation of the exterior speakers and the flashing of the vehicle lights includes:

[0036] The vehicle's external speakers play a car-finding beep and repeat preset warning messages.

[0037] The vehicle lights use a method of alternating flashing of high beams and low beams.

[0038] Furthermore, including:

[0039] Preprocess the data on the electrostatic field strength around the vehicle and the charge density of the clouds around the vehicle.

[0040] Specifically, the electrostatic field strength detection values ​​collected by the electric field sensor are filtered to remove instantaneous interference data, and the stable detection values ​​within a continuous preset time threshold are retained as the input values ​​for calculating the electric field strength factor.

[0041] The average value of the charge density data scanned by the millimeter-wave radar is calculated, and the average charge density of the target sampling points within the scanning range is taken as the input value for calculating the radar charge factor.

[0042] According to two aspects of this application, a vehicle-mounted lightning warning system is provided, comprising:

[0043] The module comprises a data acquisition module, an algorithm arbitration module, and an early warning and protection execution module.

[0044] The data acquisition module is used to acquire lightning warning data of the current vehicle location, including lightning probability and lightning strike time; acquire electrostatic field strength data around the vehicle and cloud charge density data around the vehicle;

[0045] The algorithm arbitration module has a built-in dynamic arbitration algorithm for lightning risk, including: a cloud data verification unit and a local sensor verification unit;

[0046] The cloud data verification unit includes: if the lightning probability is greater than a preset threshold and the lightning strike time is less than a preset time threshold, then the electric field sensor is activated.

[0047] The local sensing verification unit includes: activating the millimeter-wave radar if the electrostatic field strength is greater than a preset threshold;

[0048] If the charge density is preset to a threshold, then proceed to the risk confidence calculation;

[0049] The risk confidence calculation is as follows: Comprehensive lightning probability = Cloud lightning probability × First coefficient + Electric field strength factor × Second coefficient + Radar charge factor × Third coefficient;

[0050] The early warning and protection execution module is used to trigger corresponding early warning and protection actions based on the risk confidence level.

[0051] According to three aspects of the present invention, an electronic device is provided, comprising: a processor, a communication interface, a memory, and a communication bus, wherein the processor, the communication interface, and the memory communicate with each other through the communication bus;

[0052] The memory stores a computer program, which, when executed by a processor, causes the processor to perform the steps of a vehicle-mounted lightning warning method.

[0053] According to four aspects of the present invention, a computer-readable storage medium is provided that stores a computer program executable by an electronic device, which, when run on the electronic device, causes the electronic device to perform the steps of a vehicle-mounted lightning warning method.

[0054] Compared with the prior art, the present invention has the following advantages:

[0055] This application achieves fully automated operation, from cloud data subscription, local sensor activation, risk confidence calculation to early warning triggering, without requiring manual operation by the user. It adapts to the state of users focused on activities in the wild, reduces user intervention costs, and avoids untimely risk avoidance due to cumbersome operation or forgetting to perform the operation.

[0056] This application addresses the short-duration and highly sudden nature of lightning weather, such as severe summer convection and sudden thunderstorms in mountainous areas. By utilizing cloud data updated in minutes and local sensors that respond in real time, it achieves rapid identification and early warning of lightning risks. Compared with the regionalization and lag of traditional meteorological early warning systems, it has stronger adaptability to extreme weather and can cope with various sudden lightning risk scenarios.

[0057] This application employs a multi-level risk assessment mechanism that combines cloud-based meteorological data verification with local dual-sensor verification. This mechanism, along with a scientific risk confidence weighted calculation model, avoids false alarms caused by location deviations in single cloud-based data and eliminates missed alarms caused by environmental interference from single local sensors. This significantly improves the accuracy of lightning risk assessment and reduces the probability of users ignoring risks due to false alarms or facing danger due to missed alarms. Attached Figure Description

[0058] To more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the specific embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0059] Figure 1 This is a flowchart of a vehicle-mounted lightning warning method provided by one or more embodiments of the present invention.

[0060] Figure 2 This is a structural diagram of a vehicle-mounted lightning warning system provided by one or more embodiments of the present invention.

[0061] Figure 3 This is a flowchart of a vehicle-mounted lightning warning method according to a specific embodiment of the present invention.

[0062] Figure 4 This is a system block diagram of a vehicle-mounted lightning warning system according to a specific embodiment of the present invention.

[0063] Figure 5 This is an algorithm flowchart of a vehicle-mounted lightning warning method according to a specific embodiment of the present invention.

[0064] Figure 6 This is a block diagram of an electronic device structure for a vehicle-mounted lightning warning method provided by one or more embodiments of the present invention. Detailed Implementation

[0065] The technical solution of the present invention will now be clearly and completely described with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0066] The terminology used in the embodiments of this application is for the purpose of describing particular embodiments only and is not intended to limit the application. The singular forms “a,” “said,” and “the” used in the embodiments of this application and the appended claims are also intended to include the plural forms, and “multiple” generally includes at least two unless the context clearly indicates otherwise.

[0067] It should be understood that the term "and / or" used in this article is merely a description of the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A existing alone, A and B existing simultaneously, and B existing alone. Additionally, the character " / " in this article generally indicates that the preceding and following related objects have an "or" relationship.

[0068] It should be understood that although the terms first, second, third, etc., may be used in the embodiments of this application, these descriptions should not be limited to these terms. These terms are only used to distinguish the descriptions. For example, first may also be referred to as second without departing from the scope of the embodiments of this application, and similarly, second may also be referred to as first.

[0069] Depending on the context, the words “if” or “suppose” as used here can be interpreted as “when” or “in response to determination” or “in response to detection.” Similarly, depending on the context, the phrases “if determination” or “if detection (of the stated condition or event)” can be interpreted as “when determination” or “in response to determination” or “when detection (of the stated condition or event)” or “in response to detection (of the stated condition or event).”

[0070] It should also be noted that the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that an article or device that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such an article or device. Without further limitation, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the article or device that includes said element.

[0071] It should be noted that any symbols and / or numbers present in the specification that are not marked in the accompanying drawings are not reference numerals.

[0072] Figure 1 This is a flowchart of a vehicle-mounted lightning warning method provided by one or more embodiments of the present invention.

[0073] like Figure 1 As shown, it includes the following steps:

[0074] Step S1: Obtain lightning warning data of the target vehicle location, electrostatic field strength data around the target vehicle, and cloud charge density data around the vehicle. The lightning warning data includes lightning probability and lightning strike time.

[0075] Specifically, obtaining lightning warning data for the current vehicle location includes:

[0076] The vehicle's real-time location information is obtained through the vehicle's infotainment system.

[0077] Based on real-time location information, the system receives lightning warning data corresponding to the current vehicle location. This lightning warning data serves as the data source for lightning probability and strike time.

[0078] Step S2: Obtain the dynamic arbitration algorithm for lightning risk, including: cloud data verification and local sensor verification;

[0079] The cloud data verification includes: if the lightning probability is greater than a preset threshold and the lightning strike time is less than a preset time threshold, then the electric field sensor is activated.

[0080] Local sensor verification includes: if the electrostatic field strength is greater than a preset threshold, then the millimeter-wave radar is activated;

[0081] If the charge density is greater than a preset threshold, then proceed to the risk confidence calculation;

[0082] The risk confidence calculation is as follows: Comprehensive lightning probability = Cloud lightning probability × First coefficient + Electric field strength factor × Second coefficient + Radar charge factor × Third coefficient;

[0083] Specifically, the first coefficient is 0.4; the second and third coefficients are 0.3. In local sensing calibration, the preset threshold for electrostatic field strength is 1.5kV / m, and the preset threshold for charge density is 15nC / m³.

[0084] When the detected electrostatic field strength value is >1.5kV / m, the millimeter-wave radar is activated to scan the charge density of the clouds around the vehicle.

[0085] When the charge density detection value is >15nC / m³, proceed to the risk confidence calculation step.

[0086] Step S3: Trigger corresponding early warning and protective actions based on the risk confidence level.

[0087] Specifically, the corresponding early warning and protective actions triggered based on the risk confidence level include:

[0088] If the overall probability of lightning is less than the preset threshold, it is judged as low risk, and a yellow lightning icon will be displayed on the dashboard.

[0089] If the overall probability of lightning falls within the preset threshold range, it is determined to be of medium risk, triggering a lightning warning pop-up window to appear on the vehicle's touchscreen.

[0090] If the overall probability of lightning exceeds a preset threshold, it is judged as high risk, triggering the external speakers to start and the vehicle lights to flash.

[0091] Triggering corresponding early warning and protective actions based on the aforementioned risk confidence level also includes:

[0092] The vehicle's cameras detect in real time whether any users have entered the vehicle.

[0093] If a user is detected entering the vehicle, the system will automatically close all windows and prompt the user to close the doors.

[0094] Continuously monitor the overall lightning probability. Once the overall lightning probability drops below the low-risk threshold, the warning will be lifted.

[0095] Furthermore, including:

[0096] Triggering the activation of the exterior speakers and the flashing of the vehicle lights includes:

[0097] The vehicle's external speakers play a car-finding beep and repeat preset warning messages.

[0098] The vehicle lights use a method of alternating flashing of high beams and low beams.

[0099] Furthermore, including:

[0100] Preprocess the data on the electrostatic field strength around the vehicle and the charge density of the clouds around the vehicle.

[0101] Specifically, the electrostatic field strength detection values ​​collected by the electric field sensor are filtered to remove instantaneous interference data, and the stable detection values ​​within a continuous preset time threshold are retained as the input values ​​for calculating the electric field strength factor.

[0102] The average value of the charge density data scanned by the millimeter-wave radar is calculated, and the average charge density of the target sampling points within the scanning range is taken as the input value for calculating the radar charge factor.

[0103] Specifically, by using a multimodal warning system with external speakers (vehicle location beeping + looping warning voice) and alternating flashing of high and low beams, the system eliminates reliance on mobile phones, ensuring that outdoor users far from their phones can quickly receive risk information. This completely solves the core pain point of inadequate warning delivery and significantly improves the timeliness of risk avoidance in outdoor scenarios.

[0104] By adopting a two-level mechanism of cloud data verification and local sensor verification: firstly, the local sensor is activated by the cloud lightning probability and lightning strike time, and then the electrostatic field strength and charge density are used for secondary screening. Risk calculation is only entered when multiple conditions are met, which effectively avoids false alarms / missed alarms from a single data source.

[0105] Targeted preprocessing of sensor data is performed: electrostatic field strength is filtered to remove interference, and charge density is taken as the average of sampling points to ensure that the data for calculating input risk factors is stable and reliable, thereby further improving the accuracy of risk confidence calculation.

[0106] The sensor is activated in stages (first the electric field sensor, then the millimeter-wave radar) through a dual-level verification mechanism, which avoids energy waste caused by continuous sensor operation and adapts to the energy constraints of the vehicle system.

[0107] The data preprocessing and lightweight risk calculation model (weighted summation + normalization) is adapted to the computing power limitations of automotive MCU / vehicle infotainment chips, reducing the difficulty of engineering implementation and possessing the potential for mass production applications.

[0108] Figure 2 This is a structural diagram of a vehicle-mounted lightning warning system provided by one or more embodiments of the present invention.

[0109] like Figure 2 As shown, it includes:

[0110] The module comprises a data acquisition module, an algorithm arbitration module, and an early warning and protection execution module.

[0111] The data acquisition module is used to acquire lightning warning data of the current vehicle location, including lightning probability and lightning strike time; acquire electrostatic field strength data around the vehicle and cloud charge density data around the vehicle;

[0112] The algorithm arbitration module has a built-in dynamic arbitration algorithm for lightning risk, including: a cloud data verification unit and a local sensor verification unit;

[0113] The cloud data verification unit includes: if the lightning probability is greater than a preset threshold and the lightning strike time is less than a preset time threshold, then the electric field sensor is activated.

[0114] The local sensing verification unit includes: activating the millimeter-wave radar if the electrostatic field strength is greater than a preset threshold;

[0115] If the charge density is preset to a threshold, then proceed to the risk confidence calculation;

[0116] The risk confidence level calculation is specifically as follows: Comprehensive lightning probability = cloud lightning probability × first coefficient + electric field strength factor × second coefficient + radar charge factor × third coefficient;

[0117] The early warning and protection execution module is used to trigger corresponding early warning and protection actions based on the risk confidence level.

[0118] It is worth noting that although only some basic functional modules are disclosed in this embodiment, it does not mean that the composition of this system is limited to the above-mentioned basic functional modules. On the contrary, what this embodiment intends to express is that, based on the above-mentioned basic functional modules, those skilled in the art can arbitrarily add one or more functional modules in combination with existing technology to form an infinite number of embodiments or technical solutions. That is to say, this system is open rather than closed. The fact that this embodiment only discloses a few basic functional modules does not mean that the scope of protection of the claims of this invention is limited to the disclosed basic functional modules. At the same time, for the convenience of description, the above device is described separately according to its functions as various units and modules. Of course, in implementing this invention, the functions of each unit and module can be implemented in one or more software and / or hardware.

[0119] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate, and the components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs. Those skilled in the art can understand and implement this without any creative effort.

[0120] Figure 3 This is a flowchart of a vehicle-mounted lightning warning method according to a specific embodiment of the present invention.

[0121] like Figure 3 As shown, the implementation process includes the following:

[0122] The vehicle's infotainment system obtains minute-level lightning warnings via the "Thunder Weather" API.

[0123] Vehicle-mounted electric field sensors detect sudden changes in electrostatic field.

[0124] Millimeter-wave radar scans charge density distribution.

[0125] The confidence level calculation model calculates the risk confidence level based on the confidence weights of the cloud and sensors.

[0126] Based on the risk level, a corresponding lightning risk warning will be triggered. The risk levels range from low to high: low risk is indicated by a yellow lightning bolt icon on the dashboard, medium risk is indicated by a pop-up warning on the touchscreen in addition to the low risk warning, and high risk is indicated by a warning broadcast via the vehicle's external speakers in addition to the medium risk warning.

[0127] When a high-risk warning is triggered, the system controls the external speakers to play a buzzer sound and simultaneously controls the lights to flash to attract the user's attention. Then, the radar risk warning is broadcast through the external speakers.

[0128] Once the system detects a user entering the vehicle via the OMS camera, it automatically closes all windows and doors and prompts the user to stay inside the vehicle until the risk is reduced or eliminated.

[0129] Among them, the dynamic arbitration algorithm for lightning risk combines cloud-based lightning warning data (such as data obtained from the "Thunder Weather" APP) and local vehicle-mounted sensor data (electric field sensor and millimeter-wave radar) for multi-level verification, and finally outputs the lightning risk level.

[0130] Obtain lightning warning information for your current location through the "Thunder Weather" API, including the probability of lightning occurring within the next 30 minutes (0-100%), the estimated arrival time of the lightning (minutes), and the lightning intensity level.

[0131] The atmospheric electric field strength (in kV / m) at the current location is obtained using an onboard electric field sensor. Under normal clear weather conditions, the electric field strength is approximately 0.1-0.3 kV / m. When the absolute value of the electric field strength exceeds 1.5 kV / m, it indicates the possibility of thunderstorms developing; when it exceeds 5 kV / m, the risk of lightning strikes is very high.

[0132] The charge density (in nC / m³) in the clouds at the current location is obtained using millimeter-wave radar. When the charge density is greater than 15 nC / m³, it indicates the possibility of thunderstorm development; when it exceeds 50 nC / m³, the risk of lightning strike is very high.

[0133] A tiered decision-making logic is employed, integrating cloud data and local sensor data to assess lightning risk. The specific arbitration strategy is as follows:

[0134] Level 1 Arbitration: Initial Screening via Cloud-based Early Warning

[0135] If the probability of a lightning warning in the cloud is less than 30%, it is directly determined to be risk-free.

[0136] Otherwise, the case will proceed to secondary arbitration.

[0137] Secondary arbitration: Local sensor verification

[0138] Verification was performed using data from an electric field sensor and millimeter-wave radar, with two sub-conditions set:

[0139] Condition A: The absolute value of the electric field strength exceeds 1.5 kV / m for 10 consecutive seconds.

[0140] Condition B: The millimeter-wave radar detects an average charge density above the vehicle that is greater than 10 nC / m³.

[0141] If either of the two conditions is met, the case proceeds to the third level of arbitration.

[0142] Otherwise, it is judged as low risk.

[0143] Three-tier arbitration: Decision-making based on multi-source data integration

[0144] By combining cloud-based early warnings and local sensor data, a comprehensive risk score is calculated:

[0145] Comprehensive risk score (score mapped to 0-1) = Probability of lightning strikes in the cloud * 0.4 + Electric field intensity factor * 0.3 + Charge density factor * 0.3

[0146] Electric field intensity factor (intensity mapping is 0-1) = min(1,max(0,(|electric field intensity| - 1.5) / (5-1.5)));

[0147] Radar charge factor (intensity mapped to 0-1) = min(1, average charge density / 50);

[0148] Classification based on comprehensive risk score

[0149] 0.0-0.3: Low risk

[0150] 0.3-0.6: Medium risk

[0151] 0.6-1.0: High risk

[0152] Special case: When the absolute value of the electric field strength is > 10 kV / m or the average charge density is > 50 nC / m³, it is directly judged as high risk regardless of the cloud data, and the comprehensive risk score is set to 1.0.

[0153] Output risk level and overall risk score:

[0154] Risk levels: No risk, low risk, medium risk, high risk.

[0155] Confidence level: Overall risk score (0-1)

[0156] In another embodiment of a complete vehicle-mounted lightning risk warning system in a camping scenario,

[0157] Specifically, it includes:

[0158] Warning triggered:

[0159] Weather data: Thunderstorm API detected thunderstorm clouds forming within 10 kilometers of the campsite, with lightning expected to arrive in 25 minutes and a 72% probability of lightning.

[0160] Vehicle actions: A yellow lightning bolt icon pops up on the dashboard, and the touchscreen displays "Thunderstorm risk detected, please be aware of subsequent warnings."

[0161] Sensor calibration:

[0162] Electric field sensor: detected a sudden increase in electrostatic field strength to 4.2 kV / m (exceeding the threshold by 280%).

[0163] Millimeter-wave radar: The charge density of clouds on the vehicle roof was detected to be 28 nC / m³ (exceeding the threshold by 187%).

[0164] Dynamic fusion calculation:

[0165] Electric field intensity factor = min(1, max(0, (|electric field intensity| - 1.5) / (5 - 1.5)) = min(1,max(0, (|4.2| - 1.5) / (5 - 1.5)) = 0.7714;

[0166] Radar charge factor = min(1, average charge density / 50) = min(1, 28 / 50) = 0.56;

[0167] Overall risk score = (Probability of lightning in the cloud × 0.4) + (Electric field strength factor × 0.3) + (Radar charge factor × 0.3) = (0.72 × 0.4) + (0.7714 × 0.3) + (0.56 × 0.3) = 0.6874 (68.74%)

[0168] System Decision-Making:

[0169] The overall risk score for the current scenario is 0.6874 (or 68.74%), which is considered a high-risk level (defined as >60% triggering an advanced response).

[0170] Multimodal alarm:

[0171] External loudspeakers: Repeatedly broadcasting "Lightning Warning! Please return to your vehicle immediately for safety."

[0172] Headlights: Headlights flashing alternately

[0173] Dashboard and touchscreen: Red flashing + text prompts

[0174] Automatic protection:

[0175] The sunroof and windows close automatically.

[0176] The touchscreen displays a lightning protection warning: "Do not touch the metal body."

[0177] In another specific embodiment,

[0178] The user is driving towards the campsite.

[0179] Upon arrival at their destination, the user began fishing on the riverbank near the vehicle.

[0180] Half an hour later, the user noticed that dark clouds were gathering overhead, at which point the vehicle broadcast a lightning warning via its external speakers.

[0181] After receiving the notification, the user entered the vehicle.

[0182] Once the user enters the vehicle, all windows automatically close and the doors lock.

[0183] The touchscreen displayed a message: "Please stay inside the vehicle. High risk of lightning detected."

[0184] The first lightning strike hit a tree 300 meters away, causing a slight vibration in the vehicle, and the Faraday cage protection activated.

[0185] Figure 6 This is a block diagram of an electronic device structure for a vehicle-mounted lightning warning method provided by one or more embodiments of the present invention.

[0186] like Figure 6 As shown, this application provides an electronic device, including: a processor, a communication interface, a memory, and a communication bus, wherein the processor, the communication interface, and the memory communicate with each other through the communication bus;

[0187] The memory stores a computer program that, when executed by a processor, causes the processor to perform the steps of a vehicle-mounted lightning warning method.

[0188] This application also provides a computer-readable storage medium storing a computer program executable by an electronic device, which, when run on the electronic device, causes the electronic device to perform the steps of a vehicle-mounted lightning warning method.

[0189] For the sake of simplicity, the method embodiments are described as a series of actions. However, those skilled in the art should understand that the embodiments of the present invention are not limited to the described order of actions, because according to the embodiments of the present invention, some steps can be performed in other orders or simultaneously. Furthermore, those skilled in the art should also understand that the embodiments described in the specification are preferred embodiments, and the actions involved are not necessarily essential to the embodiments of the present invention.

[0190] As can be seen from the above description of the embodiments, those skilled in the art can clearly understand that this application can be implemented by means of software plus necessary general-purpose hardware platforms. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product can be stored in a storage medium, such as ROM / RAM, magnetic disk, optical disk, etc., and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute the methods described in various embodiments or some parts of the embodiments of this application.

[0191] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some or all of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention.

Claims

1. A lightning early warning method for a vehicle, characterized in that, The method comprises the following steps: obtaining lightning warning data of a target vehicle position, static electric field intensity data around the target vehicle, and cloud charge density data around the vehicle, wherein the lightning warning data comprises a lightning probability and a lightning time; obtaining a lightning risk dynamic arbitration algorithm, comprising cloud data verification and local sensor verification; wherein the cloud data verification comprises activating the local sensor verification if the lightning probability is greater than a preset threshold and the lightning time is less than a preset time threshold; the local sensor verification comprises detecting the static electric field intensity, and activating charge density detection if the static electric field intensity is greater than a preset threshold; if the charge density is greater than a preset threshold and / or the static electric field intensity is greater than a preset threshold, proceed to risk confidence calculation; the risk confidence calculation is specifically: comprehensive lightning probability = cloud lightning probability × first coefficient + electric field intensity factor × second coefficient + radar charge factor × third coefficient; triggering corresponding warning and protection actions according to the risk confidence.

2. The lightning early warning method for vehicles as claimed in claim 1 wherein, triggering corresponding warning and protection actions according to the risk confidence comprises: if the comprehensive lightning probability is less than a preset threshold, determining as low risk, triggering the instrument panel to display a yellow lightning icon; if the comprehensive lightning probability is in a preset threshold interval, determining as medium risk, triggering the vehicle touch screen to pop up a lightning warning pop-up window; if the comprehensive lightning probability is greater than a preset threshold, determining as high risk, triggering the external speaker to start and the vehicle lights to flash.

3. The lightning early warning method for vehicles as claimed in claim 1 wherein, in the local sensor verification, the preset threshold of the static electric field intensity is 1.5 kV / m, and the preset threshold of the charge density is 15 nC / m³; when the static electric field intensity detection value > 1.5 kV / m, activate the millimeter wave radar to scan the cloud charge density around the vehicle; when the charge density detection value > 15 nC / m³, proceed to the risk confidence calculation step.

4. The vehicle-mounted lightning warning method according to claim 1, wherein triggering corresponding warning and protection actions according to the risk confidence further comprises: detecting whether a user enters the vehicle through a vehicle camera in real time; if a user is detected to enter the vehicle, automatically control all vehicle windows to close and prompt the user to close the vehicle door; continuously monitor the comprehensive lightning probability, and remove the warning prompt when the comprehensive lightning probability falls below the low risk threshold.

5. The vehicle-mounted lightning warning method according to claim 1, wherein obtaining lightning warning data of the current vehicle position specifically comprises: obtaining real-time position information of the current vehicle through the vehicle system; based on the real-time position information, receiving lightning warning data corresponding to the current vehicle position, wherein the lightning warning data is the data source of the lightning probability and the lightning time.

6. The vehicle-mounted lightning warning method according to claim 1, wherein triggering the external speaker to start and the vehicle lights to flash comprises: the external speaker plays a car-seeking beep sound and cyclically broadcasts a preset warning voice; the vehicle lights use the high beam and the low beam to flash alternately.

7. The vehicle-mounted lightning warning method according to claim 1, wherein Also includes: preprocessing the data of the static electric field intensity and the cloud charge density around the vehicle; The static electric field intensity detection value collected by the electric field sensor is filtered to remove transient interference data and retain stable detection values within a continuous preset time threshold as input values for calculating the electric field intensity factor; The charge density data scanned by the millimeter wave radar is averaged to take the average charge density of the target sampling points in the scanning range as the input value for calculating the radar charge factor.

8. A lightning early warning system for a vehicle, characterized in that It includes: Data acquisition module, algorithm arbitration module and early warning and protection execution module; The data acquisition module is used for acquiring lightning warning data of the current vehicle position, and the lightning warning data includes lightning probability and lightning time; Obtain the static electric field intensity data and the cloud charge density data around the vehicle; The algorithm arbitration module is built-in lightning risk dynamic arbitration algorithm, including: cloud data verification unit and local sensor verification unit; The cloud data verification unit includes: if the lightning probability is greater than a preset threshold and the lightning time is less than a preset time threshold, the electric field sensor is activated; The local sensor verification unit includes: if the static electric field intensity is greater than a preset threshold, the millimeter wave radar is activated; If the charge density is less than a preset threshold, the risk confidence is calculated; The risk confidence calculation is: the comprehensive lightning probability = cloud lightning probability × first coefficient + electric field intensity factor × second coefficient + radar charge factor × third coefficient; The early warning and protection execution module is used for triggering corresponding early warning and protection actions according to the risk confidence.

9. An electronic device, comprising: It includes: Processor, communication interface, memory and communication bus, wherein the processor, communication interface, memory complete mutual communication through communication bus; The memory stores a computer program, when the computer program is executed by the processor, the processor executes the steps of the vehicle lightning warning method in any one of claims 1-7.

10. A computer readable storage medium characterized by It stores a computer program executable by an electronic device, when the computer program runs on the electronic device, the electronic device executes the steps of the vehicle lightning warning method in any one of claims 1-7.

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