Vehicle warning method, device, equipment and storage medium

Abstract

The present invention relates to the field of automobile control technology, and more particularly to a vehicle early warning method, device, equipment, and storage medium. The present invention detects vehicle temperature information and uses a temperature analysis model to determine whether there are temperature anomalies, thereby determining whether there are other organisms around the vehicle. Furthermore, when a temperature anomaly is detected, a vehicle heat distribution map is generated based on the abnormal temperature distribution location and the temperature information around the vehicle. This map is used to provide a location warning to the user, facilitating user inspection. This avoids the technical problem in the prior art of organisms in the vehicle's blind spot affecting safe driving, thereby improving vehicle driving safety.

Description

Technical Field

[0001] The present invention relates to the field of automobile control technology, and in particular to a vehicle early warning method, device, equipment and storage medium. Background Art

[0002] Affected by the traditional car structure, there are some areas around the car that are blind spots. Therefore, if there are animals or other biological influences in the blind spots when the car starts, there will be safety hazards, which is not conducive to the driving safety of the car.

[0003] The above content is only used to assist in understanding the technical solution of the present invention and does not constitute an admission that the above content is prior art. Summary of the Invention

[0004] The main purpose of the present invention is to provide a vehicle warning method, device, equipment and storage medium, aiming to solve the technical problem in the prior art that the presence of organisms in the blind spot of the car's field of vision affects the safe driving of the car.

[0005] To achieve the above object, the present invention provides a vehicle early warning method, which includes the following steps:

[0006] Upon receiving a vehicle start signal, obtaining temperature information of the target vehicle;

[0007] Determining whether there is a temperature anomaly using a preset temperature analysis model based on the temperature information;

[0008] If it exists, obtain the abnormal temperature distribution location;

[0009] generating a vehicle heat distribution map according to the abnormal temperature distribution position and the temperature information;

[0010] A warning signal is generated according to the vehicle heat distribution map, and the target vehicle is controlled to issue a warning to the user according to the warning signal.

[0011] Optionally, the temperature information includes: internal temperature information and external temperature information within a preset distance range;

[0012] The determining whether there is a temperature anomaly using a preset temperature analysis model according to the temperature information includes:

[0013] extracting an internal temperature distribution and an internal temperature mean from the internal temperature information;

[0014] determining whether there is a temperature abnormality inside the vehicle according to the internal temperature distribution and the internal temperature mean;

[0015] extracting external temperature distribution and external temperature extreme values ​​from the external temperature information;

[0016] According to the external temperature distribution and the temperature extreme value, a preset temperature analysis model is used to determine whether there is a temperature anomaly within the preset distance range.

[0017] Optionally, the determining whether there is abnormal temperature distribution inside the vehicle according to the internal temperature distribution and the internal temperature mean includes:

[0018] detecting whether there is target temperature information greater than the internal temperature mean in the internal temperature distribution information;

[0019] If so, obtaining the target position information corresponding to the target temperature information;

[0020] Updating the target position information according to a preset pipeline position;

[0021] It is determined whether there is target temperature information greater than the internal temperature average in the target temperature information corresponding to the updated target position information.

[0022] Optionally, judging whether there is a temperature anomaly within the preset distance range by using a preset temperature analysis model according to the external temperature distribution and the temperature extreme value includes:

[0023] determining an external heat distribution map corresponding to the external temperature distribution;

[0024] performing image segmentation on the external heat distribution map to obtain an external heat distribution map contour;

[0025] Get the current ambient temperature;

[0026] It is determined whether there is a temperature anomaly within the preset distance range through a preset temperature analysis model according to the current ambient temperature, the temperature extreme value and the external heat distribution profile.

[0027] Optionally, generating a vehicle heat distribution map according to the abnormal temperature distribution position and the temperature information includes:

[0028] Obtain vehicle subsystem models;

[0029] matching the abnormal temperature distribution position with the vehicle subsystem model;

[0030] Mark the corresponding vehicle subsystem model according to the matching result;

[0031] A vehicle heat distribution map is generated according to the labeled vehicle subsystem model, the internal temperature information, and the external temperature information.

[0032] Optionally, the vehicle early warning method further includes:

[0033] Upon receiving a vehicle shutdown signal, obtaining internal vital sign information of the target vehicle;

[0034] Performing vital sign analysis using a preset feature analysis model based on the internal vital sign information;

[0035] Determining whether the target life form characteristics exist based on the life characteristics analysis results;

[0036] If so, the target vehicle is controlled to issue an alarm based on a preset alarm strategy.

[0037] Optionally, controlling the target vehicle to issue an alarm based on a preset alarm strategy includes:

[0038] Obtaining a heat mean value of the target life form characteristic;

[0039] When the heat mean value is within a preset first heat range, controlling the target vehicle to turn on the hazard lights and sound the horn;

[0040] When the heat mean value is not within a preset first heat range, the target vehicle is controlled to turn on the hazard lights.

[0041] In addition, to achieve the above-mentioned purpose, the present invention further proposes a vehicle warning device, which includes:

[0042] A temperature detection module is used to obtain the temperature information of the target vehicle when receiving a vehicle start signal;

[0043] An anomaly detection module, configured to determine whether there is a temperature anomaly based on the temperature information using a preset temperature analysis model;

[0044] a location determination module for obtaining the location of abnormal temperature distribution, if any;

[0045] a heat detection module, configured to generate a vehicle heat distribution map based on the abnormal temperature distribution location and the temperature information;

[0046] The vehicle warning module is used to generate a warning signal according to the vehicle heat distribution map, and control the target vehicle to warn the user according to the warning signal.

[0047] In addition, to achieve the above-mentioned purpose, the present invention also proposes a vehicle warning device, which includes: a memory, a processor, and a vehicle warning program stored on the memory and runnable on the processor, and the vehicle warning program is configured to implement the steps of the vehicle warning method described above.

[0048] In addition, to achieve the above-mentioned purpose, the present invention also proposes a storage medium, on which a vehicle warning program is stored. When the vehicle warning program is executed by a processor, the steps of the vehicle warning method described above are implemented.

[0049] The present invention discloses a vehicle early warning method, which includes: obtaining temperature information of a target vehicle when a vehicle start signal is received; judging whether there is a temperature anomaly through a preset temperature analysis model according to the temperature information; if there is, obtaining the abnormal temperature distribution position; generating a vehicle heat distribution map according to the abnormal temperature distribution position and the temperature information; generating an early warning signal according to the vehicle heat distribution map, and controlling the target vehicle to issue an early warning to a user according to the early warning signal. Compared with the prior art, the present invention detects the temperature information of the vehicle and judges whether there is a temperature anomaly through a temperature analysis model to judge whether there are other organisms around the vehicle. At the same time, when a temperature anomaly is detected, a vehicle heat distribution map is generated through the abnormal temperature distribution position and the temperature information around the vehicle, which is used to issue a position early warning to the user, making it convenient for the user to check, avoiding the technical problem in the prior art that the presence of organisms in the blind spot of the vehicle's field of view affects the safe driving of the vehicle, and improving the driving safety performance of the vehicle. BRIEF DESCRIPTION OF THE DRAWINGS

[0050] Figure 1 It is a structural diagram of a vehicle warning device in a hardware operating environment involved in an embodiment of the present invention;

[0051] Figure 2 This is a flow chart of a first embodiment of the vehicle warning method of the present invention;

[0052] Figure 3 A schematic diagram of a whole vehicle model according to an embodiment of a vehicle early warning method of the present invention;

[0053] Figure 4 This is a flow chart of a second embodiment of the vehicle warning method of the present invention;

[0054] Figure 5 This is a flow chart of a third embodiment of the vehicle warning method of the present invention;

[0055] Figure 6 This is a structural block diagram of the first embodiment of the vehicle warning device of the present invention.

[0056] The purpose, features and advantages of the present invention will be further described with reference to the accompanying drawings and in conjunction with the embodiments. DETAILED DESCRIPTION

[0057] It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.

[0058] Reference Figure 1 , Figure 1 This is a schematic diagram of the structure of a vehicle warning device in the hardware operating environment involved in an embodiment of the present invention.

[0059] like Figure 1 As shown, the vehicle warning device may include: a processor 1001, such as a central processing unit (CPU), a communication bus 1002, a user interface 1003, a network interface 1004, and a memory 1005. Among them, the communication bus 1002 is used to realize the connection and communication between these components. The user interface 1003 may include a display screen (Display), an input unit such as a keyboard (Keyboard), and the user interface 1003 may also include a standard wired interface and a wireless interface. The network interface 1004 may optionally include a standard wired interface and a wireless interface (such as a wireless fidelity (Wireless-Fidelity, Wi-Fi) interface). The memory 1005 may be a high-speed random access memory (Random Access Memory, RAM) or a stable non-volatile memory (Non-Volatile Memory, NVM), such as a disk storage. The memory 1005 may also be a storage device independent of the aforementioned processor 1001.

[0060] Those skilled in the art will understand that Figure 1 The structure shown in the figure does not constitute a limitation on the vehicle warning device, and may include more or fewer components than shown in the figure, or combine certain components, or arrange the components differently.

[0061] like Figure 1 As shown, the memory 1005 as a storage medium may include an operating system, a network communication module, a user interface module and a vehicle warning program.

[0062] exist Figure 1 In the vehicle warning device shown, the network interface 1004 is mainly used for data communication with the network server; the user interface 1003 is mainly used for data interaction with the user; the processor 1001 and the memory 1005 in the vehicle warning device of the present invention can be set in the vehicle warning device, and the vehicle warning device calls the vehicle warning program stored in the memory 1005 through the processor 1001, and executes the vehicle warning method provided by the embodiment of the present invention.

[0063] The embodiment of the present invention provides a vehicle early warning method, referring to Figure 2 , Figure 2 This is a flow chart of a first embodiment of a vehicle early warning method according to the present invention.

[0064] In this embodiment, the vehicle early warning method includes the following steps:

[0065] Step S10: upon receiving a vehicle start signal, obtaining temperature information of the target vehicle.

[0066] It should be noted that the execution subject of the method of this embodiment can be a device with data acquisition, data processing and output transmission functions, such as: a vehicle-mounted controller or control chip, etc., or other devices with the same or similar functions. This embodiment does not impose specific restrictions on this. In this embodiment and the following embodiments, the vehicle-mounted controller will be used as an example for explanation.

[0067] It is worth noting that the vehicle start-up signal can be the ignition signal of the vehicle engine, so that each device or program of the vehicle is powered on to realize subsequent temperature collection. The collected temperature information can be obtained through a temperature collection device, such as an infrared temperature collection sensor or other device that can realize temperature collection. This embodiment does not impose specific restrictions on this.

[0068] In a specific implementation, obtaining the vehicle's temperature information includes: internal temperature information and external temperature information, wherein the internal temperature information refers to the temperature information inside the vehicle, such as: the cockpit, the engine compartment trunk, etc., and the external temperature information refers to the temperature information within a preset range around the vehicle, such as: the temperature information within 1m or the temperature information near the wheel, etc. This embodiment does not impose specific restrictions on this.

[0069] Step S20: determining whether there is a temperature anomaly using a preset temperature analysis model according to the temperature information.

[0070] It should be noted that the preset temperature analysis model is used to analyze the internal and external temperature information of the vehicle to determine whether there are abnormal temperature areas inside and outside the vehicle. When determining whether there is abnormal temperature, the current ambient temperature also needs to be considered. The preset temperature analysis model can be a temperature analysis model based on a linear regression algorithm, or other models that can achieve the same or similar functions. This embodiment does not impose specific restrictions on this.

[0071] In order to obtain the preset temperature analysis model, temperature information samples and temperature analysis result samples may be obtained before step S20; and the initial neural network algorithm may be trained based on the temperature information samples and the temperature analysis result samples to obtain the preset temperature analysis model.

[0072] In a specific implementation, temperature anomaly can be reflected in whether there is temperature information or whether there is a particularly prominent temperature area.

[0073] Step S30: If it exists, obtain the abnormal temperature distribution position.

[0074] It should be noted that the abnormal temperature distribution location refers to the location of a particularly prominent temperature area within a preset range inside or outside the vehicle compared to the vehicle coordinate system, where the vehicle coordinate system can be a vehicle coordinate system established by the on-board controller based on the vehicle reference point, and the vehicle reference point can be the central dividing point or mass point of the vehicle, etc. This embodiment does not impose specific restrictions on this.

[0075] Step S40: generating a vehicle heat distribution map according to the abnormal temperature distribution position and the temperature information.

[0076] It can be understood that the vehicle heat distribution map is a heat distribution map based on the entire vehicle model. The temperature of each area is marked in the vehicle heat distribution map, and the areas with abnormal temperatures can also be marked by highlighting. The higher the temperature, the darker the color, and the temperature information of different areas is provided.

[0077] Furthermore, the step S40 includes:

[0078] Obtain vehicle subsystem models;

[0079] matching the abnormal temperature distribution position with the vehicle subsystem model;

[0080] Mark the corresponding vehicle subsystem model according to the matching result;

[0081] A vehicle heat distribution map is generated according to the labeled vehicle subsystem model, the internal temperature information, and the external temperature information.

[0082] In the specific implementation, refer to Figure 3 , area A is a temperature abnormality area, the vehicle subsystem model can be a subsystem model included in the whole vehicle model stored in the database, and can be displayed on the vehicle display screen, or it can be a subsystem model in other ways, and this embodiment does not impose specific restrictions on this.

[0083] Step S50: generating a warning signal according to the vehicle heat distribution map, and controlling the target vehicle to issue a warning to the user according to the warning signal.

[0084] It should be understood that the warning signal includes the specific location of the high-temperature area in the vehicle, which can be in the form of a voice reminder or a preset reminder warning sign displayed on a display screen loaded inside the vehicle. This embodiment does not impose specific restrictions on this.

[0085] In a specific implementation, if an animal that affects the vehicle's driving is detected inside the vehicle, such as at the tires, in the engine compartment, or on the periphery when the vehicle is started, a warning instruction corresponding to the location will be issued. In addition, when some high-temperature areas are detected inside the vehicle, a warning instruction will be issued to remind the user to get off the vehicle immediately to avoid possible risks, such as the presence of animals that pose a threat to the driver in areas such as the cab. This embodiment does not impose specific restrictions on this.

[0086] The present embodiment discloses a vehicle warning method, which includes: upon receiving a vehicle start-up signal, obtaining temperature information of a target vehicle; judging whether there is a temperature anomaly through a preset temperature analysis model based on the temperature information; if so, obtaining the abnormal temperature distribution position; generating a vehicle heat distribution map based on the abnormal temperature distribution position and the temperature information; generating a warning signal based on the vehicle heat distribution map, and controlling the target vehicle to warn a user based on the warning signal. The present embodiment detects the temperature information of the vehicle and judges whether there is a temperature anomaly through a temperature analysis model to judge whether there are other organisms around the vehicle. At the same time, when a temperature anomaly is detected, a vehicle heat distribution map is generated through the abnormal temperature distribution position and the temperature information around the vehicle for providing a position warning to the user, facilitating the user's inspection, avoiding the technical problem in the prior art that the presence of organisms in the blind spot of the vehicle's field of view affects the safe driving of the vehicle, and improving the vehicle driving safety performance.

[0087] refer to Figure 4 , Figure 4 This is a flow chart of a second embodiment of a vehicle early warning method according to the present invention.

[0088] Based on the above first embodiment, in this embodiment, step S20 includes:

[0089] Step S201: extracting the internal temperature distribution and the internal temperature mean from the internal temperature information.

[0090] It should be noted that the vehicle's temperature information includes internal temperature information and external temperature information, wherein the internal temperature information refers to the temperature information of areas such as the cab, engine compartment and trunk, and the external temperature information refers to the temperature information within a preset range around the vehicle, for example: temperature information within 1m or temperature information near the wheels, etc. This embodiment does not impose specific restrictions on this.

[0091] It is worth noting that the internal temperature distribution refers to the temperature distribution of areas such as the cab, engine cabin and trunk inside the vehicle. The internal temperature mean can be obtained by assigning different weights to areas such as the cab, engine cabin and trunk inside the vehicle to determine the temperature mean inside the vehicle. When allocating weights, the heat generated by the engine in the cabin needs to be considered. Therefore, when allocating weights, the weights corresponding to the cab, engine cabin and trunk are 0.2:0.4:0.4, etc., respectively. This embodiment does not impose any specific restrictions on this.

[0092] Step S202: Determine whether there is a temperature abnormality inside the vehicle based on the internal temperature distribution and the internal temperature mean.

[0093] It should be noted that the judgment of whether the internal temperature is abnormal can be to detect whether there is an area in the internal temperature distribution that exceeds the internal temperature mean. If there is an area in the internal temperature distribution that is higher than the internal temperature mean, the area is determined to be a temperature abnormality area.

[0094] In addition, in this embodiment, the judgment of whether the internal temperature is abnormal can also be made by setting a temperature threshold, that is, the part of the internal temperature distribution that exceeds the temperature threshold is judged as a temperature abnormality area. This embodiment does not impose specific restrictions on this.

[0095] Furthermore, considering the heat effect of the vehicle engine and the connected pipes when the vehicle is started, step S202 includes:

[0096] detecting whether there is target temperature information greater than the internal temperature mean in the internal temperature distribution information;

[0097] If so, obtaining the target position information corresponding to the target temperature information;

[0098] Updating the target position information according to a preset pipeline position;

[0099] It is determined whether there is target temperature information greater than the internal temperature average in the target temperature information corresponding to the updated target position information.

[0100] It should be noted that the preset pipe position may be the position of a pipe connected to the vehicle engine or the position of an exhaust pipe, etc., and this embodiment does not impose any specific restrictions on this.

[0101] In a specific implementation, after detecting the presence of an abnormal temperature area based on the internal temperature distribution and the internal temperature mean, the abnormal temperature area is compared with the preset pipeline position to eliminate the abnormal temperature area caused by vehicle operation, thereby improving the accuracy of the temperature analysis results.

[0102] Step S203: extracting the external temperature distribution and the external temperature extreme value from the external temperature information.

[0103] It should be understood that the external temperature distribution refers to the temperature distribution within a preset range around the vehicle, where the preset range may be 0.5 m. This embodiment does not impose any specific restrictions on this. The external temperature extreme value may be the maximum temperature within the preset range around the vehicle.

[0104] Step S204: determining whether there is a temperature anomaly within the preset distance range using a preset temperature analysis model according to the external temperature distribution and the temperature extreme value.

[0105] It should be noted that the preset temperature analysis model is used to analyze whether there is a temperature anomaly area in the external temperature information. If so, it is used to determine the anomaly type of the temperature anomaly area. Since the external temperature will be affected by the current ambient temperature, when detecting whether there is an external temperature anomaly within the preset distance range, the impact of the current ambient temperature on the temperature anomaly detection results also needs to be considered.

[0106] Furthermore, the step S204 includes:

[0107] determining an external heat distribution map corresponding to the external temperature distribution;

[0108] performing image segmentation on the external heat distribution map to obtain an external heat distribution map contour;

[0109] Get the current ambient temperature;

[0110] It is determined whether there is a temperature anomaly within the preset distance range through a preset temperature analysis model according to the current ambient temperature, the temperature extreme value and the external heat distribution profile.

[0111] It can be understood that the external heat distribution map contour refers to segmenting the temperature detection results outside the preset distance range of the vehicle to obtain external temperature information within the distance that may affect the vehicle's driving.

[0112] In a specific implementation, in order to reduce the impact of the current ambient temperature on the temperature detection results, in this embodiment, the current ambient temperature is combined with a preset temperature analysis model to determine whether there is a temperature anomaly within the preset distance range. For example, when the current ambient temperature is 30 degrees Celsius, the temperature extreme value within 0.5m of the vehicle is detected to be 37 degrees Celsius. Then, combined with the external heat distribution map, it is determined that there is a temperature anomaly in the extreme value area.

[0113] The present embodiment discloses extracting the internal temperature distribution and the internal temperature mean from the internal temperature information; determining whether there is a temperature anomaly inside the vehicle based on the internal temperature distribution and the internal temperature mean; extracting the external temperature distribution and the external temperature extreme value from the external temperature information; and judging whether there is a temperature anomaly within the preset distance range through a preset temperature analysis model based on the external temperature distribution and the temperature extreme value. The present embodiment improves the accuracy of temperature anomaly judgment by separately detecting whether there are temperature anomaly areas in the internal temperature information and the external temperature information, and performing different temperature detection strategies on different areas.

[0114] refer to Figure 5 , Figure 5 This is a flow chart of a third embodiment of a vehicle early warning method according to the present invention.

[0115] Based on the above second embodiment, in this embodiment, after step S50, the following steps are further included:

[0116] Step S60: upon receiving a vehicle shutdown signal, obtaining internal vital sign information of the target vehicle.

[0117] It should be noted that the internal life characteristic information can be obtained by scanning through infrared sensors, image detection equipment, life detection equipment, etc., to determine whether there are infants, children, or animals in the car.

[0118] Step S70: Performing vital sign analysis based on the internal vital sign information using a preset feature analysis model.

[0119] It can be understood that the preset feature analysis model is used to perform information feature analysis based on the detected internal life feature information to determine whether there are life features in the car. If so, the category of the life features is detected, where the categories of life include: pets or infants, etc.

[0120] It is easy to understand that infants and pets have different body temperatures, sizes, and vital signs, and the warning priority for infants is higher than that for pets.

[0121] In a specific implementation, if life characteristics are detected, the vehicle will be shut down and the power will be cut off after a preset time interval is received after the vehicle shutdown signal is received to avoid safety accidents. The preset time interval can be 1 minute or other time intervals, and this embodiment does not impose any specific restrictions on this.

[0122] Step S80: Determine whether the target life feature exists based on the life feature analysis result.

[0123] Step S90: If yes, control the target vehicle to issue an alarm based on a preset alarm strategy.

[0124] In specific implementation, if vital signs of infants, children, or pets are detected inside the vehicle, the vehicle will be controlled to issue an early warning to prevent safety accidents.

[0125] Furthermore, the step S90 includes:

[0126] Obtaining a heat mean value of the target life form characteristic;

[0127] When the heat mean value is within a preset first heat range, controlling the target vehicle to turn on the hazard lights and sound the horn;

[0128] When the heat mean value is not within a preset first heat range, the target vehicle is controlled to turn on the hazard lights.

[0129] In specific implementations, different warning methods can be selected according to the priority of different life characteristics. For example, when there are infants and young children in the car, the car will still use forced double flashes and horn after the vehicle is turned off; when there are pets in the car, only forced double flashes will be used.

[0130] This embodiment discloses that upon receiving a vehicle shutdown signal, internal vital sign information of the target vehicle is obtained; vital signs analysis is performed using a preset feature analysis model based on the internal vital sign information; whether target vital signs exist based on the vital sign analysis results is determined; if so, the target vehicle is controlled to issue an alarm based on a preset alarm strategy. In this embodiment, the user is warned by delaying the shutdown and power off, and forcibly turning on the hazard lights and horn, thereby preventing safety accidents and increasing the user's personal safety.

[0131] In addition, an embodiment of the present invention further provides a storage medium on which a vehicle warning program is stored. When the vehicle warning program is executed by a processor, the steps of the vehicle warning method described above are implemented.

[0132] Since the storage medium adopts all the technical solutions of all the above embodiments, it has at least all the beneficial effects brought by the technical solutions of the above embodiments, which will not be described one by one here.

[0133] Reference Figure 6 , Figure 6 This is a structural block diagram of the first embodiment of the vehicle warning device of the present invention.

[0134] like Figure 6 As shown, the vehicle warning device proposed in the embodiment of the present invention includes:

[0135] The temperature detection module 10 is used to obtain the temperature information of the target vehicle when receiving the vehicle start signal.

[0136] The anomaly detection module 20 is configured to determine whether a temperature anomaly exists based on the temperature information using a preset temperature analysis model.

[0137] The location determination module 30 is configured to obtain the location of the abnormal temperature distribution, if any.

[0138] The heat detection module 40 is configured to generate a vehicle heat distribution map according to the abnormal temperature distribution position and the temperature information.

[0139] The vehicle warning module 50 is configured to generate a warning signal according to the vehicle heat distribution map, and control the target vehicle to issue a warning to the user according to the warning signal.

[0140] The present embodiment discloses a vehicle warning method, which includes: upon receiving a vehicle start-up signal, obtaining temperature information of a target vehicle; judging whether there is a temperature anomaly through a preset temperature analysis model based on the temperature information; if so, obtaining the abnormal temperature distribution position; generating a vehicle heat distribution map based on the abnormal temperature distribution position and the temperature information; generating a warning signal based on the vehicle heat distribution map, and controlling the target vehicle to warn a user based on the warning signal. The present embodiment detects the temperature information of the vehicle and judges whether there is a temperature anomaly through a temperature analysis model to judge whether there are other organisms around the vehicle. At the same time, when a temperature anomaly is detected, a vehicle heat distribution map is generated through the abnormal temperature distribution position and the temperature information around the vehicle for providing a position warning to the user, facilitating the user's inspection, avoiding the technical problem in the prior art that the presence of organisms in the blind spot of the vehicle's field of view affects the safe driving of the vehicle, and improving the vehicle driving safety performance.

[0141] In one embodiment, the abnormality detection module 20 is further used to extract the internal temperature distribution and the internal temperature mean from the internal temperature information; determine whether there is a temperature abnormality inside the vehicle based on the internal temperature distribution and the internal temperature mean; extract the external temperature distribution and the external temperature extreme value from the external temperature information; and determine whether there is a temperature abnormality within the preset distance range based on the external temperature distribution and the temperature extreme value through a preset temperature analysis model.

[0142] In one embodiment, the abnormality detection module 20 is further used to detect whether there is target temperature information greater than the internal temperature mean in the internal temperature distribution information; if so, obtain target position information corresponding to the target temperature information; update the target position information according to a preset pipeline position; and determine whether there is target temperature information greater than the internal temperature mean in the target temperature information corresponding to the updated target position information.

[0143] In one embodiment, the anomaly detection module 20 is further used to determine an external heat distribution map corresponding to the external temperature distribution; perform image segmentation on the external heat distribution map to obtain an external heat distribution map outline; obtain the current ambient temperature; and determine whether there is a temperature anomaly within the preset distance range through a preset temperature analysis model based on the current ambient temperature, the temperature extreme value, and the external heat distribution map outline.

[0144] In one embodiment, the heat detection module 40 is further used to obtain a vehicle subsystem model; match the abnormal temperature distribution position with the vehicle subsystem model; mark the corresponding vehicle subsystem model according to the matching result; and generate a vehicle heat distribution map based on the marked vehicle subsystem model, the internal temperature information and the external temperature information.

[0145] In one embodiment, the vehicle warning module 50 is further configured to obtain internal vital sign information of the target vehicle upon receiving a vehicle shutdown signal; perform vital sign analysis based on the internal vital sign information using a preset feature analysis model; determine whether target vital sign characteristics exist based on the vital sign analysis results; and if so, control the target vehicle to issue an alarm based on a preset alarm strategy.

[0146] In one embodiment, the vehicle warning module 50 is also used to obtain the heat mean value of the target life form characteristic; when the heat mean value is within a preset first heat range, the target vehicle is controlled to turn on the hazard lights and sound the horn; when the heat mean value is not within the preset first heat range, the target vehicle is controlled to turn on the hazard lights.

[0147] It should be understood that the above is only an example and does not constitute any limitation to the technical solution of the present invention. In specific applications, those skilled in the art can make settings as needed, and the present invention does not impose any limitation on this.

[0148] It should be noted that the workflow described above is merely illustrative and does not limit the scope of protection of the present invention. In practical applications, technicians in this field can select part or all of it according to actual needs to achieve the purpose of the embodiment scheme, and no limitation is made here.

[0149] In addition, for technical details not fully described in this embodiment, reference can be made to the vehicle warning method provided in any embodiment of the present invention, and will not be repeated here.

[0150] In addition, it should be noted that, in this document, the terms "comprises," "includes," or any other variations thereof are intended to encompass non-exclusive inclusion, such that a process, method, article, or system comprising a series of elements includes not only those elements but also other elements not explicitly listed, or elements inherent to such process, method, article, or system. In the absence of further limitations, an element defined by the phrase "comprising a ..." does not exclude the presence of other identical elements in the process, method, article, or system comprising the element.

[0151] The serial numbers of the above embodiments of the present invention are for description only and do not represent the advantages or disadvantages of the embodiments.

[0152] Through the description of the above embodiments, those skilled in the art can clearly understand that the above-mentioned embodiment methods can be implemented by means of software plus the necessary general hardware platform, or of course by hardware, but in many cases the former is a better embodiment. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art, can be embodied in the form of a software product. The computer software product is stored in a storage medium (such as a read-only memory (ROM) / RAM, a magnetic disk, or an optical disk), and includes a number of instructions for enabling a terminal device (which can be a mobile phone, a computer, a server, or a network device, etc.) to execute the methods described in each embodiment of the present invention.

[0153] The above are only preferred embodiments of the present invention and are not intended to limit the patent scope of the present invention. Any equivalent structure or equivalent process transformation made using the contents of the present invention description and drawings, or directly or indirectly applied in other related technical fields, are also included in the patent protection scope of the present invention.

Claims

1. A vehicle early warning method, characterized in that: The vehicle early warning method comprises: Upon receiving a vehicle start signal, acquiring temperature information of the target vehicle, wherein the temperature information includes internal temperature information and external temperature information within a preset distance range; Obtain temperature information samples and temperature analysis result samples; Performing model training on an initial neural network algorithm based on the temperature information samples and the temperature analysis result samples to obtain a preset temperature analysis model; extracting an internal temperature distribution and an internal temperature mean from the internal temperature information; determining whether there is a temperature abnormality inside the vehicle according to the internal temperature distribution and the internal temperature mean; extracting external temperature distribution and external temperature extreme values ​​from the external temperature information; Determining whether there is a temperature anomaly within the preset distance range using the preset temperature analysis model according to the external temperature distribution and the temperature extreme value; If it exists, obtain the abnormal temperature distribution location; generating a vehicle heat distribution map according to the abnormal temperature distribution position and the temperature information; A warning signal is generated according to the vehicle heat distribution map, and the target vehicle is controlled to issue a warning to the user according to the warning signal.

2. The vehicle warning method according to claim 1, characterized in that: The determining whether there is a temperature abnormality inside the vehicle according to the internal temperature distribution and the internal temperature mean includes: detecting whether there is target temperature information greater than the internal temperature mean in the internal temperature distribution information; If so, obtaining the target position information corresponding to the target temperature information; Updating the target position information according to a preset pipeline position; It is determined whether the target temperature information corresponding to the updated target position information includes target temperature information that is greater than the internal temperature average.

3. The vehicle warning method according to claim 1, characterized in that: The determining whether there is a temperature anomaly within the preset distance range by using a preset temperature analysis model according to the external temperature distribution and the temperature extreme value includes: determining an external heat distribution map corresponding to the external temperature distribution; performing image segmentation on the external heat distribution map to obtain an external heat distribution map contour; Get the current ambient temperature; It is determined whether there is a temperature anomaly within the preset distance range through a preset temperature analysis model according to the current ambient temperature, the temperature extreme value and the external heat distribution profile.

4. The vehicle warning method according to any one of claims 1 to 3, characterized in that: Generating a vehicle heat distribution map according to the abnormal temperature distribution position and the temperature information includes: Obtain vehicle subsystem models; matching the abnormal temperature distribution position with the vehicle subsystem model; Mark the corresponding vehicle subsystem model according to the matching result; A vehicle heat distribution map is generated according to the labeled vehicle subsystem model, the internal temperature information, and the external temperature information.

5. The vehicle warning method according to claim 1, characterized in that: The vehicle early warning method further includes: Upon receiving a vehicle shutdown signal, obtaining internal vital sign information of the target vehicle; Performing vital sign analysis using a preset feature analysis model based on the internal vital sign information; Determining whether the target life form characteristics exist based on the life characteristics analysis results; If so, the target vehicle is controlled to issue an alarm based on a preset alarm strategy.

6. The vehicle warning method according to claim 5, characterized in that: The controlling the target vehicle to issue an alarm based on a preset alarm strategy includes: Obtaining a heat mean value of the target life form characteristic; When the heat mean value is within a preset first heat range, controlling the target vehicle to turn on the hazard lights and sound the horn; When the heat mean value is not within a preset first heat range, the target vehicle is controlled to turn on the hazard lights.

7. A vehicle warning device, characterized in that: The vehicle early warning device comprises: A temperature detection module, configured to obtain temperature information of a target vehicle upon receiving a vehicle start signal, wherein the temperature information includes internal temperature information and external temperature information within a preset distance range; an anomaly detection module configured to obtain temperature information samples and temperature analysis result samples; perform model training on an initial neural network algorithm based on the temperature information samples and the temperature analysis result samples to obtain a preset temperature analysis model; extract an internal temperature distribution and an internal temperature mean from the internal temperature information; determine whether a temperature anomaly exists inside the vehicle based on the internal temperature distribution and the internal temperature mean; extract an external temperature distribution and an external temperature extreme value from the external temperature information; and determine whether a temperature anomaly exists within a preset distance range based on the external temperature distribution and the temperature extreme value using the preset temperature analysis model; a location determination module for obtaining the location of abnormal temperature distribution, if any; a heat detection module, configured to generate a vehicle heat distribution map based on the abnormal temperature distribution location and the temperature information; The vehicle warning module is used to generate a warning signal according to the vehicle heat distribution map, and control the target vehicle to warn the user according to the warning signal.

8. A vehicle warning device, characterized in that: The vehicle warning device includes: a memory, a processor, and a vehicle warning program stored in the memory and executable on the processor, wherein the vehicle warning program is configured to implement the vehicle warning method according to any one of claims 1 to 6.

9. A storage medium, characterized in that: The storage medium stores a vehicle warning program, which, when executed by the processor, implements the vehicle warning method according to any one of claims 1 to 6.

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