Vehicle rescue method and device and electronic equipment

Abstract

The invention relates to the field of vehicle control, in particular to a vehicle rescue method and device and electronic equipment. According to the method, the in-vehicle call event is obtained, the traditional call layer-by-layer transfer process is simplified, and the rescue response is directly started. And positioning data and vehicle condition data of the target vehicle are synchronously obtained during response, so that the cloud can quickly and accurately judge the rescue type according to the vehicle condition, and information dispersion and communication delay are avoided. For example, vehicle condition data can visually present vehicle fault parts, and rescue strength is accurately matched. Furthermore, the vehicle is controlled to whistle and give an alarm, so that surrounding personnel are reminded to provide temporary assistance, and the rescue vehicle is assisted to be quickly positioned. In addition, positioning data and vehicle condition data are directly transmitted to the cloud end and are scheduled by the cloud end in a unified mode, department barriers are broken, and seamless joint of all links is achieved. The time consumed from calling to rescue dispatching is shortened, the probability of implementing rescue at the optimal rescue time is increased, and meanwhile the rescue efficiency and the success rate are improved.

Description

Technical Field

[0001] The present application relates to the field of vehicle control, and in particular to a vehicle rescue method, device and electronic equipment. Background Art

[0002] As the number of cars continues to rise, vehicle driving safety has received more and more attention, and the vehicle emergency call system (ECALL) has come into being, aiming to call for help in time and ensure the safety of people in the event of sudden danger.

[0003] Traditional call centers play a key role in vehicle rescue, responsible for dispatching and arranging rescue matters, but many drawbacks have gradually emerged. The dispatch process is cumbersome and complicated. From the time the car owner or the person in the car makes a call, the information goes through multiple steps such as transfer, screening, and matching rescue units. During this period, it is easy to lose time due to poor coordination between departments and delayed information communication. This often leads to a long time from the time the call is issued to the time the rescue force arrives at the scene. In an emergency rescue situation where every second counts, the best rescue opportunity is likely to be missed, resulting in untimely rescue and endangering the safety of life and property. Summary of the invention

[0004] In view of this, the embodiments of the present application provide a vehicle rescue method, device and electronic device to solve the problem that the scheduling process of the traditional call center in the vehicle rescue link is cumbersome and complicated, and time is lost due to poor departmental connection and delayed information communication, which easily leads to time-consuming rescue and missing the best rescue time.

[0005] In a first aspect, an embodiment of the present application provides a vehicle rescue method, the method comprising:

[0006] Obtain the call event generated in the target vehicle;

[0007] In response to the call event, the positioning data and vehicle condition data of the target vehicle are obtained, and the target vehicle is controlled to perform a horn alarm operation;

[0008] The positioning data and the vehicle condition data are sent to the cloud, wherein the cloud is used to analyze the vehicle condition data to obtain the rescue type of the target vehicle, and dispatch a rescue vehicle matching the rescue type according to the positioning data.

[0009] Furthermore, obtaining the call event generated in the target vehicle includes:

[0010] Detecting a click operation on any one of the call buttons in the target vehicle, wherein the call button in the target vehicle is arranged corresponding to a driver's seat in the target vehicle;

[0011] In response to the click operation, determining a clicked target call button;

[0012] Based on the button identifier corresponding to the target call button, the call event is generated based on the button identifier.

[0013] Further, the obtaining of the positioning data and vehicle condition data of the target vehicle includes:

[0014] Querying the positioning data of the target vehicle from the navigation system of the target vehicle;

[0015] Obtaining a target driving seat corresponding to the button identifier included in the call event;

[0016] Calling the image acquisition device of the target vehicle to capture the target driving seat to obtain seat image data, and calling the image acquisition device of the target vehicle to capture the key area in the target vehicle to obtain area image data;

[0017] Acquiring operating data of each electronic control unit in the target vehicle;

[0018] The vehicle condition data is generated based on the seat image data, the area image data, and the operation data.

[0019] Furthermore, after sending the positioning data and the vehicle condition data to the cloud, the method further includes:

[0020] Detecting environmental data of the environment where the target vehicle is located;

[0021] Predicting potential safety hazard information of the vehicle based on the environmental data and the vehicle condition data;

[0022] The safety hazard information is sent to the cloud, wherein the cloud is used to adjust the rescue vehicle according to the safety hazard information.

[0023] Furthermore, the method further comprises:

[0024] Obtaining current operating behavior of the driver and passengers in the target vehicle;

[0025] Matching the current operation behavior with the correct operation behavior of the potential safety hazard information;

[0026] If the current operation behavior does not match the correct operation behavior, an operation suggestion is generated based on difference information between the current operation behavior and the correct operation behavior, and the operation suggestion is sent.

[0027] In a second aspect, an embodiment of the present application provides a vehicle rescue method, the method comprising:

[0028] Receiving positioning data and vehicle condition data sent by the target vehicle, and analyzing the vehicle condition data to obtain the rescue type of the target vehicle;

[0029] Acquire vehicle configuration information corresponding to a vehicle matching the positioning data, and a distance between the vehicle and the target vehicle;

[0030] taking a vehicle whose vehicle configuration information matches the rescue type as a candidate vehicle;

[0031] The candidate vehicle with the shortest distance from the target vehicle is used as a rescue vehicle, and the positioning data and the rescue type of the target vehicle are sent to the rescue vehicle.

[0032] Furthermore, after sending the location data of the target vehicle and the rescue type to the rescue vehicle, the method further includes:

[0033] Obtaining the current vehicle state of the target vehicle;

[0034] If the vehicle is in a stationary state, a navigation route between the rescue vehicle and the target vehicle is planned, the navigation route is sent to the rescue vehicle, and a guidance instruction is sent to a traffic light located on the navigation route based on the real-time position of the rescue vehicle, so that the traffic light guides the rescue vehicle to preferentially pass through the intersection where the traffic light is located according to the guidance instruction;

[0035] Or, if the vehicle state is a driving state, the driving route of the target vehicle is predicted, the road condition information of the driving route is obtained, the dynamic rescue route of the rescue vehicle is planned according to the road condition information and the location information of the rescue vehicle, and the dynamic rescue route is sent to the rescue vehicle.

[0036] In a third aspect, an embodiment of the present application provides a vehicle rescue device, the device comprising:

[0037] An acquisition module, used for acquiring a call event generated in a target vehicle;

[0038] A response module, used to respond to the call event, control the target vehicle to sound a horn alarm, and obtain the positioning data and vehicle condition data of the target vehicle;

[0039] A sending module is used to send the positioning data and the vehicle condition data to the cloud, wherein the cloud is used to analyze the vehicle condition data to obtain the rescue type of the target vehicle, and dispatch a rescue vehicle matching the rescue type according to the positioning data.

[0040] In a fourth aspect, an embodiment of the present application provides a vehicle rescue device, the device comprising:

[0041] A receiving module, used to receive the positioning data and vehicle condition data sent by the target vehicle, and analyze the vehicle condition data to obtain the rescue type of the target vehicle;

[0042] A detection module, used to obtain vehicle configuration information corresponding to a vehicle matching the positioning data, and a distance between the vehicle and the target vehicle;

[0043] A processing module, configured to take a vehicle whose vehicle configuration information matches the rescue type as a candidate vehicle;

[0044] The execution module is used to select the candidate vehicle with the shortest distance from the target vehicle as a rescue vehicle, and send the positioning data of the target vehicle and the rescue type to the rescue vehicle.

[0045] In a fifth aspect, an embodiment of the present application provides an electronic device, comprising: a memory and a processor, the memory and the processor being communicatively connected to each other, computer instructions being stored in the memory, and the processor executing the method of the above-mentioned first aspect or any corresponding embodiment thereof by executing the computer instructions.

[0046] In a sixth aspect, an embodiment of the present application provides a computer-readable storage medium having computer instructions stored thereon, the computer instructions being used to enable a computer to execute the method of the first aspect or any corresponding embodiment thereof.

[0047] This application obtains in-vehicle call events, simplifies the traditional call transfer process, and directly starts the rescue response. When responding, the positioning data and vehicle condition data of the target vehicle are synchronously obtained, so that the cloud can quickly and accurately determine the type of rescue based on the vehicle condition, avoiding information dispersion and communication delays. For example, the vehicle condition data can intuitively present the fault location of the vehicle and accurately match the rescue force. Furthermore, controlling the vehicle horn to sound the alarm not only reminds surrounding personnel to provide temporary assistance, but also assists in the rapid positioning of rescue vehicles. In addition, the positioning data and vehicle condition data are directly transmitted to the cloud, which is uniformly dispatched by the cloud to break down departmental barriers and achieve seamless connection of all links. It shortens the time from calling to dispatching rescue, increases the probability of implementing rescue at the best rescue time, and also improves the efficiency and success rate of rescue. BRIEF DESCRIPTION OF THE DRAWINGS

[0048] In order to more clearly illustrate the specific implementation methods of the present application or the technical solutions in the prior art, the drawings required for use in the specific implementation methods or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are some implementation methods of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0049] Figure 1is a flow chart of a vehicle rescue method according to some embodiments of the present application;

[0050] Figure 2 is a flow chart of a vehicle rescue method according to some embodiments of the present application;

[0051] Figure 3 is a structural block diagram of a vehicle rescue device according to an embodiment of the present application;

[0052] Figure 4 is a structural block diagram of a vehicle rescue device according to an embodiment of the present application;

[0053] Figure 5 It is a schematic diagram of the hardware structure of the electronic device according to an embodiment of the present application. DETAILED DESCRIPTION

[0054] In order to make the purpose, technical solution and advantages of the embodiments of the present application clearer, the technical solution in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without making creative work are within the scope of protection of this application.

[0055] According to an embodiment of the present application, a vehicle rescue method, device and electronic device are provided. It should be noted that the steps shown in the flowchart of the accompanying drawings can be executed in a computer system such as a set of computer executable instructions, and although a logical order is shown in the flowchart, in some cases, the steps shown or described can be executed in an order different from that shown here.

[0056] In this embodiment, a vehicle rescue method is provided. Figure 1 is a flow chart of a vehicle rescue method according to an embodiment of the present application, such as Figure 1 As shown, the process includes the following steps:

[0057] Step S101, obtaining a call event generated in a target vehicle.

[0058] In the embodiment of the present application, obtaining a call event generated in the target vehicle includes the following steps A1-A3:

[0059] Step A1, detecting a click operation on any call button in the target vehicle, wherein the call button in the target vehicle is arranged corresponding to the driving seat in the target vehicle.

[0060] Specifically, the call button corresponding to each driver's seat in the target vehicle is connected to the vehicle's control module through an independent wire. For example, the call button of the driver's seat is connected to the corresponding input pin, and the call buttons of the co-driver's seat and the rear seat are also connected to the corresponding input pins. These pins are finally gathered on the vehicle's control module for signal monitoring.

[0061] When the vehicle is started, the control module will initialize the circuit connected to the call button and set the default level state for the corresponding input pin, for example, to a high level (or a low level, depending on the specific circuit design logic), which will serve as the reference state for subsequent detection of whether the button is pressed.

[0062] The vehicle's control module has a built-in scanning circuit or a polling mechanism implemented by a software program, which scans and detects the level status of each input pin connected to the call button at a certain time interval (for example, every few milliseconds).

[0063] When the level of an input pin changes from a high level to a low level, and this level change lasts for a certain period of time (to prevent misjudgment due to circuit jitter, etc., a time threshold of about tens of milliseconds is generally set), it is preliminarily determined that the corresponding call button may have been pressed, triggering the subsequent response process.

[0064] Step A2, responding to the click operation, determining the clicked target call button.

[0065] Specifically, when the control module detects a qualified change in the level of a certain input pin through hardware scanning and software judgment, it will first mark and temporarily store the signal. Then, it will quickly confirm the pin level again for multiple times (for example, 3-5 times in a row, each time with a few milliseconds interval) to ensure that the level is indeed stable in the changed state, so as to confirm that it is a valid button click operation, rather than an accidental interference signal.

[0066] Since each call button corresponds to a unique input pin, a mapping table of the pin-to-call button correspondence is stored in the control module. By querying this mapping table, it is possible to clearly know which specific call button (for example, the call button for the driver's seat, the call button for the rear left seat, etc.) is clicked, thereby determining the target call button that is clicked.

[0067] After determining the target call button, the control module will record the relevant information of the button (such as button number, seat location, etc.) and store it in the internal temporary cache area for use when generating call events later. At the same time, a notification message will be sent to the relevant functional modules in the vehicle (such as the modules responsible for alarm prompts and data transmission) to inform them that a valid call button click operation has been detected and which specific button has been clicked, so as to prepare for subsequent collaborative work.

[0068] Step A3: Based on the button identifier corresponding to the target call button, a call event is generated based on the button identifier.

[0069] Specifically, the corresponding button identifier is extracted from the target call button related information previously recorded in the temporary cache area. This identifier may be a simple digital code (for example, 1 represents the driver's seat call button, 2 represents the passenger seat call button, etc.), or a more unique and standardized character or digital combination generated according to the vehicle's internal unified coding rules, which can uniquely determine the identifier of this call button in the entire vehicle call system.

[0070] According to the communication protocol and event format pre-defined by the vehicle, the data structure of the call event is obtained. This data structure contains multiple fields, including a field specifically for storing button identification information. In addition, it also contains a timestamp field for the event (accurately recording the time when the call button is clicked to facilitate subsequent analysis and tracing), a vehicle identification code field (used to identify which specific vehicle issued the call event), etc.

[0071] By detecting the click operation on the call button corresponding to the driver's seat in the target vehicle, the specific source of the operation can be accurately located, realizing refined management of call triggering. After responding to the click operation, the clicked target call button is determined. This process makes each call have a clear direction and avoids the situation where the call source is unknown and the information is confusing. Generating call events based on the button identification corresponding to the target call button enables subsequent rescue-related processes, such as information transmission and rescue dispatch, to quickly and accurately identify which driver or passenger initiated the call, seat location and other key information based on this clear and unique identification, so as to arrange rescue measures more targetedly and improve the efficiency and accuracy of the entire rescue operation.

[0072] Step S102, responding to the call event, obtaining the positioning data and vehicle condition data of the target vehicle, and controlling the target vehicle to sound a horn alarm.

[0073] In the embodiment of the present application, obtaining the positioning data and vehicle condition data of the target vehicle includes the following steps B1-B5:

[0074] Step B1, querying the positioning data of the target vehicle from the navigation system of the target vehicle.

[0075] Specifically, different functional modules in the vehicle usually interact through an internal communication bus (such as a CAN bus, etc.). The control module responsible for obtaining vehicle condition data (which can be the vehicle's control module or a dedicated rescue-related processing module) will send a data query request to the navigation system. This request follows the unified communication protocol format specified within the vehicle, and contains information such as the type of request (here, querying positioning data), the module identifier of the request source, etc., and the request is accurately sent to the node where the navigation system is located through the bus.

[0076] After receiving the query request, the navigation system will first verify the legitimacy and integrity of the request. After confirming that it is a valid request from the legal module inside the vehicle, it will combine the map data and its own positioning algorithm (such as differential positioning algorithm, etc.) to calculate the latitude and longitude coordinates of the vehicle's current location. At the same time, it will obtain some auxiliary positioning data, such as the vehicle's driving direction, speed and other information provided by the vehicle's inertial navigation sensors (such as gyroscopes, accelerometers, etc.), to further improve the positioning data content.

[0077] The navigation system will encapsulate the acquired positioning data including latitude coordinates, driving direction, speed, etc. according to the agreed communication protocol format, and send it back to the control module that initiated the query request through the internal communication bus to ensure that the control module can accurately receive and parse the positioning data.

[0078] Step B2: Obtain the target driving seat corresponding to the button identifier included in the call event.

[0079] Specifically, when a call event is generated, the relevant control module will parse the data structure of the call event. According to the previously defined format (such as the structure form containing fields such as button ID mentioned above), the button ID information is extracted from it. For example, if the data structure of the call event is stored in JSON format, the button ID is obtained by parsing the corresponding key-value pair (such as the value corresponding to the "buttonId" field).

[0080] In the vehicle configuration information database or the configuration table pre-stored in the control module, there is a mapping of the correspondence between the call button identifier and the driver's seat. For example, there is a table that clearly records that the button identifier "1" corresponds to the driver's seat, "2" corresponds to the co-driver's seat, and so on. The control module can accurately determine which driver's seat's corresponding call button is pressed by querying this correspondence table based on the extracted button identifier, thereby determining the target driver's seat.

[0081] Step B3, calling the image acquisition device of the target vehicle to acquire the target driver's seat to obtain seat image data, and calling the image acquisition device of the target vehicle to acquire the key area in the target vehicle to obtain area image data.

[0082] Specifically, when receiving an instruction to capture the target driver's seat image, the control module first determines which driver's seat (such as the driver's seat, the front passenger seat, or a seat in the back row) made the call based on the button identifier corresponding to the previously acquired call event, and then identifies the target driver's seat. Then, based on the layout and shooting coverage information of the cameras in the vehicle, a camera that can clearly capture the target driver's seat is selected from the cameras that have established communication.

[0083] For example, a downward-shooting camera is installed above the driver's seat of the vehicle to monitor the situation in the driver's seat area. The control module selects this camera to perform the image acquisition task of the driver's seat. The control module sends configuration adjustment instructions (if necessary) to the selected camera, such as further fine-tuning the exposure parameters according to the current light conditions, adjusting the resolution to a higher definition (if the previous default resolution was lower), etc., to ensure that high-quality target driver's seat images can be acquired.

[0084] After receiving the acquisition instruction, the selected camera starts to continuously acquire image frames at the set frame rate. The lens focuses the light from the target driving seat area onto the image sensor. The image sensor converts the light signal into a corresponding electrical signal through the photoelectric effect according to the light intensity and color information. Light of different intensities generates electrical signals of different sizes at different pixel points, thus forming a simulated electrical signal image.

[0085] Next, the image sensor transmits the analog electrical signal to the analog-to-digital conversion circuit (ADC) inside the camera. The ADC converts the analog electrical signal into a digital signal at a certain sampling frequency. Each pixel corresponds to a digital value, representing its color and brightness information, thus converting the analog image into digital image data. For example, in the common RGB color mode, each pixel is represented by the digital values ​​of the three color channels of red, green, and blue to represent its color composition, ultimately forming digital image data presented in the form of a pixel matrix.

[0086] Each frame of image data collected will be encoded and compressed according to a preset image format (such as JPEG, PNG, etc.) to reduce the amount of data for easy transmission, and then sent back to the control module frame by frame through the communication bus. The control module receives and caches the image data to form seat image data.

[0087] The key areas in the vehicle cabin usually include the instrument panel, center console, door interior, interior mirrors, rear seats and passages, footwells, etc. These areas play an important role in reflecting the overall condition of the vehicle, the status of the driver and passengers, and potential safety hazards. The camera number or location information corresponding to each key area is clearly recorded in the vehicle configuration file or the pre-stored area information table.

[0088] Based on this information, the control module traverses all key areas that need to be collected and determines the corresponding camera for each area. For example, for the dashboard area, a camera installed in front of the driver and facing the dashboard will be selected; for the door interior area, a camera installed on the top of the door that can cover the entire door interior will be selected. For some larger key areas, multiple cameras may be required to shoot together to fully cover them. The control module will coordinate the work of these cameras to ensure that a comprehensive regional image is collected.

[0089] After the corresponding camera is determined for each key area, the control module sends acquisition instructions to these cameras respectively. The instructions also include the corresponding parameter configuration requirements (such as resolution, frame rate, exposure parameters, etc.). Each camera starts to synchronously acquire images according to the instructions. Due to different shooting angles and coverage ranges, the image data collected by different cameras reflects the situation of different parts of the key area.

[0090] Each camera will first perform analog-to-digital conversion, encoding compression and other processing on the collected image data according to the process in the above-mentioned image acquisition operation, and then send their respective image data back to the control module through the communication bus. After receiving the image data from multiple cameras, the control module will classify and sort these image data according to the identification of the key areas, integrate the image data belonging to the same key area together, form an image data set for each key area, and finally summarize the complete regional image data.

[0091] Step B4, obtaining the operating data of each electronic control unit in the target vehicle.

[0092] Specifically, the electronic control units (ECUs) in the vehicle, such as the engine control unit, brake control unit, body stability control unit, etc., interact with other systems through the vehicle's internal communication bus (such as CAN bus, LIN bus, etc.; different ECUs may use different bus connection methods according to their functions and data transmission requirements).

[0093] The control module responsible for generating vehicle condition data will send data acquisition requests to each ECU that needs to obtain data in turn. The request clearly indicates the specific operating data type to be obtained (for example, the engine control unit needs to provide data such as engine speed, water temperature, oil pressure, etc.; the brake control unit needs to provide data such as brake pedal travel and brake pressure), and is packaged in the communication protocol format of the corresponding bus and sent to the communication node where the corresponding ECU is located.

[0094] After receiving the data acquisition request, each ECU will monitor and collect data on the status of its own internal sensors, actuators and other components (for example, the engine control unit obtains water temperature data through the water temperature sensor, and obtains engine speed data through the crankshaft position sensor, etc.), and then package the collected operating data in the specified format.

[0095] The ECU then returns the packaged operating data to the control module that sent the request through the communication bus. After receiving the operating data from different ECUs, the control module will classify and organize them according to the type of ECU and the nature of the data. For example, engine-related data can be classified into one category and brake-related data can be classified into another category, to facilitate the subsequent comprehensive generation of vehicle condition data.

[0096] Step B5, generating vehicle condition data based on the seat image data, the area image data and the operation data.

[0097] Specifically, first, the seat image data is analyzed, and the status characteristics of the driver and passengers are identified through image recognition algorithms (such as target detection algorithms based on deep learning, etc.), such as whether they are wearing seat belts, whether there are signs of injury (by detecting whether there are bloodstains, abnormal limb postures, etc.), the integrity of the seats (whether there is damage, deformation, etc.), and other information. The feature information extracted from these images is quantified and encoded, and converted into a data form that can be used to describe the vehicle condition.

[0098] Secondly, for regional image data, image analysis technology is used to detect the status of components in key areas, such as whether there are leaks in the pipes in the engine compartment (by detecting whether there are traces of liquid, color abnormalities, etc. in the image), the status of indicator lights on the dashboard (by identifying the on and off status of the indicator lights and the corresponding icon meanings), whether the door is closed normally (by detecting the fit between the door and the body, etc.), etc., to extract the vehicle condition characteristics reflected by these key areas and perform corresponding data processing.

[0099] Then, the operating data obtained from each electronic control unit is combined with the feature information extracted from the image data. For example, the engine water temperature data is combined with the coolant pipeline conditions detected in the engine compartment image to determine whether the coolant system is working properly; the brake pressure data is associated with the brake pedal travel conditions observed through the image to comprehensively evaluate the performance status of the brake system.

[0100] Then, based on the results of fusion and analysis, the vehicle condition data format pre-defined inside the vehicle is generated. The vehicle condition data can be a structured data set, containing multiple fields, such as basic vehicle information (vehicle identification code, vehicle model, etc.), driver and passenger status information (description of the personnel situation in each seat), key area component status information (summary of the detection status of each key area), and operating parameter information of each major system (key operating data of the engine, brake, steering and other systems).

[0101] Finally, the generated vehicle condition data will be packaged to ensure its completeness and accuracy so that it can be smoothly sent to the cloud later.

[0102] First, query the positioning data from the navigation system of the target vehicle to accurately determine the location of the vehicle and provide accurate orientation guidance for subsequent rescue operations. Obtaining the target driving seat corresponding to the button logo contained in the call event can clarify the location of the person who specifically initiated the demand and enhance the pertinence of the rescue response. The image acquisition device of the vehicle is called to collect the target driving seat and key areas in the car respectively. The seat image data and regional image data obtained can intuitively present the status of the driver and passengers and the actual situation of key parts in the car, such as whether there are injuries and whether there are abnormal items in the car. Then obtain the operating data of each electronic control unit of the vehicle to fully understand the working conditions of each system of the vehicle. Based on these multi-dimensional seat image data, regional image data and operating data, the vehicle condition data is generated, making the vehicle condition information more complete and detailed, which provides strong support for accurately judging the vehicle condition, efficiently carrying out rescue operations, and accurately dispatching corresponding resources.

[0103] Step S103, sending the positioning data and vehicle condition data to the cloud, wherein the cloud is used to analyze the vehicle condition data to obtain the rescue type of the target vehicle, and dispatch a rescue vehicle that matches the rescue type according to the positioning data.

[0104] In an embodiment of the present application, by sending positioning data and vehicle condition data to the cloud, with the help of the powerful data analysis capabilities of the cloud, the vehicle condition data is deeply analyzed to accurately derive the rescue type of the target vehicle, such as engine failure, braking system problems or other situations, and then based on the acquired positioning data, from a large number of deployable rescue vehicles, select vehicles that match the rescue type and have corresponding rescue capabilities, and make reasonable dispatches. In this way, the entire process is efficient and orderly, which can effectively shorten the rescue response time, improve the accuracy and timeliness of the rescue operation, and ensure the smooth implementation of vehicle rescue work.

[0105] This application obtains in-vehicle call events, simplifies the traditional call transfer process, and directly starts the rescue response. When responding, the positioning data and vehicle condition data of the target vehicle are synchronously obtained, so that the cloud can quickly and accurately determine the type of rescue based on the vehicle condition, avoiding information dispersion and communication delays. For example, the vehicle condition data can intuitively present the fault location of the vehicle and accurately match the rescue force. Furthermore, controlling the vehicle horn to sound the alarm not only reminds surrounding personnel to provide temporary assistance, but also assists in the rapid positioning of rescue vehicles. In addition, the positioning data and vehicle condition data are directly transmitted to the cloud, which is uniformly dispatched by the cloud to break down departmental barriers and achieve seamless connection of all links. It shortens the time from calling to dispatching rescue, increases the probability of implementing rescue at the best rescue time, and also improves the efficiency and success rate of rescue.

[0106] In the embodiment of the present application, after sending the positioning data and the vehicle condition data to the cloud, the method further includes the following steps C1-C3:

[0107] Step C1, detecting environmental data of the environment where the target vehicle is located.

[0108] Specifically, the target vehicle is equipped with different types of sensors, such as a temperature sensor, a humidity sensor, a light sensor, a rain sensor, an air pressure sensor, and the like.

[0109] The temperature sensor senses the change of the ambient temperature through thermistor. For example, the temperature sensor at the front of the vehicle can obtain the external ambient temperature in real time, which is critical for understanding the climatic conditions of the vehicle. For example, in extremely cold weather, low temperature may affect the performance of the vehicle battery and the elasticity of the tire rubber. The temperature sensor inside the vehicle can reflect the thermal comfort inside the vehicle and the working effect of the air conditioning system.

[0110] The humidity sensor is installed on the outside of the vehicle body to detect the humidity of the external environment. The humidity of the external environment is of great reference value for judging whether the road is slippery (for example, in a high humidity environment, the road surface is prone to condensation and become slippery) and whether the metal parts of the vehicle are prone to rust.

[0111] The light sensor is installed near the front windshield of the vehicle. It can detect the light intensity of the external environment and convert the light intensity into a corresponding electrical signal for output. The light intensity data can help determine whether it is daytime, nighttime, or in special weather conditions (such as fog, rainstorm, etc. that cause weak light). It has an impact on the control of the vehicle's automatic headlights and some auxiliary driving functions that rely on light (such as vision-based road condition recognition, etc.). It can also help determine the visibility conditions of the vehicle's environment.

[0112] The rain sensor is installed on the inside of the vehicle's windshield and detects whether there is rain on the windshield and how much rain there is through optical principles or capacitance change principles.

[0113] The air pressure sensor detects the atmospheric pressure of the vehicle's environment, which is helpful for judging the vehicle's altitude and weather trends. For example, when a vehicle is driving in a plateau area, lower air pressure may affect the engine's intake efficiency, thereby affecting the power performance. At the same time, parameters such as the vehicle's tire pressure under different air pressure environments also need to be reasonably adjusted to ensure driving safety. The air pressure sensor converts the air pressure change into an electrical signal and then into a digital air pressure value for subsequent analysis.

[0114] The data collected by each sensor will be transmitted to the vehicle's control module through the vehicle's internal communication bus (such as CAN bus, etc.). The control module will first perform format verification on the received data to ensure the integrity and accuracy of the data and eliminate abnormal data (such as data values ​​that are obviously beyond the reasonable range) that may be caused by sensor failure, communication interference, etc.

[0115] Then, the data collected by different sensors at the same time are integrated according to a unified timestamp to form a data package containing multi-dimensional environmental data such as temperature, humidity, light intensity, rainfall, and air pressure, which facilitates subsequent overall environmental condition analysis and combines with vehicle condition data to predict safety hazard information.

[0116] Step C2: predicting potential safety hazard information of the vehicle based on the environmental data and the vehicle condition data.

[0117] Specifically, the environmental data and vehicle condition data are analyzed according to preset dimensions to predict safety hazard information. Safety hazard information includes road condition safety hazards, climate safety hazards, sight safety hazards, operation safety hazards, etc.

[0118] Regarding road safety hazards: combined with the rainfall data and light intensity data in the environmental data, if the rainfall is heavy and the light intensity is weak (such as in heavy rain), and referring to the tire wear in the vehicle condition data and the vehicle's braking system performance data, it can be determined whether the vehicle's braking distance on a slippery road will exceed the safe range, and then predict whether there is a safety hazard of collision due to insufficient braking; if the environmental data shows that the road surface temperature is low (obtained through a temperature sensor), combined with the tire pressure and rubber aging degree in the vehicle condition data, it can analyze the possibility of reduced tire grip and assess the risk of the vehicle skidding when turning, accelerating or braking.

[0119] For climate safety hazards: use the temperature, humidity and air pressure information in the environmental data. When the vehicle is in a high temperature and high humidity environment, check the engine's cooling system operating parameters and the electrical system's moisture-proof measures in the vehicle condition data to determine whether the engine is prone to overheating and whether the electrical components have a short circuit risk. In a low temperature environment, based on the battery power status and antifreeze performance indicators in the vehicle condition data, estimate the probability of hidden dangers such as difficulty in starting the vehicle and cooling system failure.

[0120] Regarding safety hazards in vision: By using environmental data such as light intensity, rainfall, and dust concentration, combined with the working status of the vehicle's lighting system and the cleanliness of the windshield in the vehicle condition data, we analyze whether the driver's vision is affected. For example, in foggy weather (weak light and high humidity) and when the windshield is not clean enough, can the driver clearly see the road conditions ahead? This will help determine whether there are safety hazards caused by obstructed vision.

[0121] For operational safety hazards: use information such as air pressure and wind speed in environmental data (some vehicles can obtain this information through external meteorological data or a simple wind speed detection device configured by themselves), combined with the vehicle's appearance and structural parameters and the status of the suspension system in the vehicle condition data, to estimate the air resistance and crosswind impact that the vehicle is subject to during driving, and determine whether the vehicle will have safety hazards such as unstable driving and deviation.

[0122] Step C3, sending the safety hazard information to the cloud, wherein the cloud is used to adjust the rescue vehicle according to the safety hazard information.

[0123] Specifically, on the vehicle side, the predicted safety hazard information is encapsulated in a predetermined communication protocol format, which usually includes fields such as the vehicle identification code, a specific description of the hazard information (such as hazard type, hazard level, etc.), and a timestamp. The vehicle establishes a communication connection with the cloud through a wireless communication module (such as a 4G / 5G communication module, etc.) to ensure the stability and reliability of the communication link, and performs identity authentication and other operations to ensure the legitimacy and security of data transmission. Only authorized vehicles can send data to the cloud.

[0124] The vehicle sends the packaged safety hazard information data packet to the cloud server through a wireless communication link. The cloud server is equipped with a corresponding receiving service program to perform integrity verification and decryption (if encrypted transmission) on the received data to ensure that the received data is accurate and meets safety requirements. After verification, the cloud will store the received safety hazard information in the corresponding database and start the relevant analysis and scheduling modules. According to this safety hazard information, the rescue vehicles that have been dispatched or are being dispatched will be adjusted, such as changing the driving route of the rescue vehicle (if there are hidden dangers such as road waterlogging, choose a safer route to go), adjusting the estimated arrival time of the rescue vehicle (taking into account the changes in driving speed caused by environmental factors, etc.), and increasing the rescue force (if the safety hazard level is high, increase the corresponding rescue vehicles or rescue personnel), etc.

[0125] First, when the cloud receives the safety hazard information data packet sent from the vehicle, it extracts the key contents contained therein, such as vehicle identification code, hazard type, hazard level, hazard discovery time and other information. Analyze the type and severity of safety hazard information. For the hazard type, by matching with the pre-established vehicle fault type knowledge base, accurately identify whether it is a brake system failure, engine failure, electrical system failure, or other types such as damaged body structure, tire problems, etc.; for the severity, according to the set classification standards, combined with the specific description of the hazard and related key parameter indicators (if any, such as the specific temperature value of the engine water temperature being too high, the proportion of brake system pressure loss, etc.), it is divided into high, medium and low levels. For example, when the engine shows serious smoke or even signs of fire, or the brake system fails completely, it is judged as high risk.

[0126] Secondly, according to the hidden danger types obtained through analysis, a comprehensive search and screening is conducted in the rescue resource database in the cloud. If it is determined to be an engine failure, a rescue station that is close to the vehicle and equipped with professional engine maintenance technicians and advanced testing equipment is found; if it is a brake system failure, priority is given to locating rescue forces that have the ability to quickly repair the brake system and have a reserve of suitable brake components. At the same time, differentiated response strategies are formulated according to the severity of the hidden danger. For hidden dangers of high severity, they are marked as emergency priority levels to ensure that relevant rescue resources can respond and be put into rescue operations in the shortest time; for medium hidden dangers, regular rapid response processes are arranged; for low-level hidden dangers, regular maintenance-type rescue arrangements are focused on, and rescue resources are reasonably allocated to avoid waste caused by excessive investment.

[0127] Then, if the severity of the potential safety hazard is high, other available rescue resources will be searched around the target vehicle. For example, when a vehicle encounters a serious collision, the body is severely deformed, and there may be people trapped, in addition to dispatching regular road rescue vehicles, the fire department and medical emergency department will be urgently contacted to coordinate fire trucks equipped with demolition and rescue equipment and ambulances carrying professional first aid equipment to go to the rescue site together. At the same time, a real-time communication group is established to include rescue vehicles, trapped vehicles, and terminal devices of various collaborative rescue departments to achieve real-time information exchange, so that all parties can understand the rescue progress at any time and share key information on the scene, such as vehicle damage details, personnel conditions, etc., to ensure rescue efficiency.

[0128] As an example, the cloud receives safety hazard information from a faulty vehicle, and after a series of processes such as verification and identity verification, it is confirmed to have passed the verification. The cloud will accurately store the safety hazard information including the vehicle identification code, specific hazard details such as engine overheating, brake system failure risk, and key elements such as hazard level and discovery time in a structured database specifically used to manage such data, ensuring orderly archiving of data for subsequent tracing and statistical analysis at any time.

[0129] If the safety hazard information shows that the vehicle is trapped in a road section with heavy rain and severe waterlogging, and a rescue vehicle is heading to the scene, the cloud will re-plan a driving route for the rescue vehicle that avoids the deep waterlogging area and has a smoother and safer terrain based on high-precision map data and real-time road condition feedback. At the same time, taking into account environmental factors such as the slowing down of the vehicle speed due to waterlogging and the increased difficulty of driving due to slippery roads, the rescue vehicle's original estimated arrival time will be dynamically adjusted to ensure that the information is accurate and reliable. If the safety hazard level is determined to be a high-risk level, such as a serious power system failure in the vehicle, which may cause more serious consequences at any time, the cloud will issue instructions to surrounding service stations with corresponding rescue capabilities to send additional rescue vehicles with professional maintenance equipment.

[0130] In an embodiment of the present application, the method also includes: obtaining the current operating behavior of the driver and passengers in the target vehicle; matching the current operating behavior with the correct operating behavior of the safety hazard information; if the current operating behavior does not match the correct operating behavior, generating an operating suggestion based on the difference information between the current operating behavior and the correct operating behavior, and sending the operating suggestion.

[0131] Specifically, first of all, various sensors capture the current operating behaviors of drivers and passengers in all directions, such as the steering wheel rotation angle, the travel of the accelerator pedal, the pressure change of the brake pedal, etc. These data are transmitted to the matching analysis module in real time. At the same time, the system monitors road conditions, climate, sight, operating status and other aspects, integrates data packets containing various safety hazard information, and presets corresponding correct operating behavior templates for each hazard based on professional knowledge and massive actual test cases. For example, when encountering road safety hazards such as heavy rain, the correct operation is to appropriately reduce the speed, increase the following distance, and keep the wipers working efficiently; in the face of safety hazards in foggy weather, the fog lights and low beams should be turned on and the speed should be strictly controlled.

[0132] Next, the matching analysis module compares the various parameters of the current operation behavior with the correct operation behavior templates under different safety hazards according to the operation category. Considering the flexibility of actual driving, a reasonable error range is set. As long as the current operation behavior parameters are within the error range of the corresponding template parameters, it is determined to be matched, otherwise it is determined to be mismatched. Once it is determined to be mismatched, the difference analysis mechanism is immediately activated. It accurately calculates the difference between the current operation and the correct operation in each parameter. For example, if the vehicle speed is too fast in heavy fog, the value exceeding the standard speed is calculated, or the degree of steering wheel turning angle deviation when driving on a curve. Combined with the vehicle's real-time speed, specific road conditions, current climate conditions, etc., the built-in intelligent algorithm quickly generates highly targeted operation suggestions. For example, on a snowy curve, if the driver and passengers turn too hard, the suggestion is: "The current snowy curve has low friction. Please reduce the steering angle, reduce the speed, and pass the curve smoothly and slowly to avoid vehicle loss of control."

[0133] By detecting the environmental data of the target vehicle's environment and combining it with the vehicle condition data to predict the vehicle's safety hazard information, it is possible to gain insight into potential risks in advance, no longer limited to post-event response, and strive for more initiative in rescue operations, making rescue preparations more forward-looking. Sending these safety hazard information to the cloud and adjusting the rescue vehicles based on them can achieve accurate deployment of rescue resources, such as reasonably planning the routes of rescue vehicles according to the severity of the hazard and the environmental conditions, and dispatching appropriate rescue forces, etc., greatly improving rescue efficiency. In addition, the current operating behavior of the driver and passengers in the target vehicle is further obtained and matched with the correct operating behavior corresponding to the safety hazard information, so as to accurately determine whether the driver and passengers are operating properly. Once a mismatch is found, an operation suggestion is generated and sent based on the difference information between the two, which can promptly correct the improper operation of the driver and passengers, avoid the aggravation of safety hazards due to operational errors, reduce risks from the driver and passenger operation level, and ensure vehicle driving safety in all aspects.

[0134] The present application embodiment provides a vehicle rescue method, such as Figure 2 As shown, the method includes:

[0135] Step S201, receiving the positioning data and vehicle condition data sent by the target vehicle, and analyzing the vehicle condition data to obtain the rescue type of the target vehicle.

[0136] In an embodiment of the present application, the cloud opens a specific port through a network communication module to listen to data transmission requests from the target vehicle. The target vehicle uses its built-in wireless communication unit (such as a 4G / 5G module) to send positioning data (including latitude and longitude coordinates, altitude and other information, usually presented in a structured data format, such as JSON format) and vehicle condition data (covering various aspects such as operating parameters of various systems of the vehicle, fault prompt information, etc.) to the receiving port specified in the cloud according to a predetermined communication protocol (for example, encapsulation based on HTTP, MQTT and other protocols). After the cloud receives the data packet, it first performs a data integrity check, and compares it with the corresponding check information attached when the target vehicle sends it by calculating the checksum or hash value, etc., to ensure that the data is not lost or tampered with during the transmission process. At the same time, if the data is encrypted for transmission (such as based on SSL / TLS encryption protocol), a decryption operation is performed to restore the original positioning data and vehicle condition data.

[0137] Extract key information from the vehicle condition data, which may include but is not limited to the engine's operating status (such as whether there is a fault code, whether the water temperature is abnormal, whether the oil pressure is normal, etc.), the brake system condition (brake pad wear, brake line pressure, etc.), the electrical system's operating status (battery power, whether each electrical component has a short circuit or open circuit prompt, etc.), and vehicle body structure integrity related prompts (whether there is collision sensor trigger information, etc.).

[0138] These vehicle condition data are input into a pre-built fault diagnosis and rescue type judgment model. The model can be a rule-based expert system, that is, based on the experience and knowledge of a large number of vehicle maintenance experts, a series of rules are formulated, such as "If the engine water temperature is too high and the cooling fan cannot operate normally, it is judged as the engine cooling fault rescue type" and "If the brake pad is worn to a thickness below the safety threshold, it is judged as the brake system maintenance rescue type". The rescue type is determined by matching the vehicle condition data with these rules; it can also be a classification model based on machine learning (for example, trained using decision trees, neural networks and other algorithms), trained using a large amount of historical vehicle condition data and its corresponding known rescue type annotation data, so that the model can learn the intrinsic mapping relationship between vehicle condition characteristics and rescue types, and then after the received real-time vehicle condition data is input into the model, the corresponding rescue type is output, such as "engine failure rescue", "tire failure rescue" and other specific rescue type results.

[0139] Step S202, obtaining vehicle configuration information corresponding to the vehicle matching the positioning data, and the distance between the vehicle and the target vehicle.

[0140] In an embodiment of the present application, a vehicle resource database is stored in the cloud, which records relevant information of all vehicles that can participate in the rescue (such as vehicles in the rescue team of a rescue company, etc.), including each vehicle's unique identifier (such as license plate number, frame number, etc.), the vehicle's own positioning information (updated in real time through the on-board positioning device and uploaded to the cloud), and vehicle configuration information (such as vehicle model, type and specification of on-board rescue equipment, maximum load weight, whether it has special rescue functions, etc.).

[0141] Based on the received positioning data of the target vehicle, all vehicles within a certain geographical range (this range can be pre-set based on factors such as the actual rescue service coverage area and response time requirements) are screened out in the database through spatial query algorithms (such as range query based on geographic coordinates, nearest neighbor query, etc.). These vehicles are the set of potential rescue vehicles that match the positioning data of the target vehicle.

[0142] For each potential rescue vehicle selected, the actual distance between them and the target vehicle is calculated using a geospatial calculation algorithm (e.g., a spherical distance calculation formula based on longitude and latitude coordinates, such as the Haversing formula, or with the help of a distance calculation interface provided by a map service provider). At the same time, the vehicle configuration information corresponding to these vehicles is extracted from the vehicle resource database to form the "distance-configuration information" corresponding data for each vehicle, such as "the vehicle with license plate number XXXXX, 10 kilometers away from the target vehicle, model XX, equipped with professional engine repair tools, towing equipment, etc.", in preparation for further screening of rescue vehicles.

[0143] Step S203: taking vehicles whose vehicle configuration information matches the rescue type as candidate vehicles.

[0144] In the embodiment of the present application, for each potential rescue vehicle screened out and its corresponding vehicle configuration information, it is matched and analyzed with the determined rescue type of the target vehicle. For example, if the rescue type of the target vehicle is "engine failure rescue", then the vehicle configuration information of each potential rescue vehicle will be checked to see whether it has professional equipment related to engine maintenance (such as professional fault diagnosis computers, engine lifting tools, wrenches of various specifications, etc.) and corresponding technical personnel qualifications (if recorded); if the rescue type is "fire rescue", then check whether the vehicle is equipped with fire extinguishing equipment, fire protection equipment, etc.

[0145] Only vehicles whose vehicle configuration information meets the basic conditions required for the target vehicle rescue type (these conditions can be a pre-set detailed list that clearly specifies the necessary equipment, skills, and other requirements for different rescue types) will be marked as candidate vehicles and enter the next step of screening.

[0146] Step S204: The candidate vehicle with the shortest distance to the target vehicle is used as a rescue vehicle, and the positioning data of the target vehicle and the rescue type are sent to the rescue vehicle.

[0147] In the embodiment of the present application, the distance data between each candidate vehicle and the target vehicle (which has been calculated and recorded before) is compared, and the vehicle closest to the target vehicle is found through a sorting algorithm (such as a simple sorting algorithm such as bubble sort, quick sort, or a sorting function in a database query statement), and it is determined as the final rescue vehicle. For example, after comparison, it is found that the vehicle with the license plate number "ABC123" among the candidate vehicles is only 5 kilometers away from the target vehicle, which is the closest among all the candidate vehicles, so it is selected as the rescue vehicle for this rescue operation.

[0148] The cloud establishes a communication connection with the selected rescue vehicle through the network communication module. This connection also needs to perform security mechanisms such as identity authentication to ensure the legitimacy and security of the communication (for example, two-way authentication based on digital certificates and key pairs). After establishing a stable connection, the positioning data of the target vehicle (so that the navigation system of the rescue vehicle can accurately navigate to the target location) and the rescue type (so that rescue personnel know the content of the rescue mission in advance and prepare the corresponding rescue tools and equipment) are encapsulated in accordance with the pre-agreed communication protocol format. The encapsulated data is then sent to the rescue vehicle through a wireless communication link (such as using a 4G / 5G network). After receiving the data, the receiving module on the rescue vehicle side performs operations such as unpacking and verification to extract the positioning data and rescue type information.

[0149] In the embodiment of the present application, after sending the location data of the target vehicle and the rescue type to the rescue vehicle, the method further includes: obtaining the current vehicle state of the target vehicle. If the vehicle state is stationary, a navigation route between the rescue vehicle and the target vehicle is planned, the navigation route is sent to the rescue vehicle, and a guidance instruction is sent to the traffic light located on the navigation route based on the real-time position of the rescue vehicle, so that the traffic light guides the rescue vehicle to pass through the intersection where the traffic light is located first according to the guidance instruction.

[0150] Specifically, the current status information of the target vehicle is obtained by relying on various sensors installed on the target vehicle and the communication link with the vehicle's electronic control unit (ECU). These sensors are like sharp scouts, collecting data from all directions, including the vehicle's speed sensor to determine whether the vehicle speed is zero to confirm whether it is stationary, the engine's operating parameters to reflect whether it is working, and the gear position sensor to determine the gear position, etc., combining this information to accurately determine the vehicle's status.

[0151] After confirming that the target vehicle is stationary, the cloud-based rescue dispatch system immediately takes action. On the one hand, with the help of a high-precision map service platform, combined with the current real-time location of the rescue vehicle and the location of the target vehicle, an intelligent path planning algorithm is used to plan an optimal navigation route. This route comprehensively considers many factors such as the distance, road congestion, and road conditions to ensure that the rescue vehicle can arrive at the fastest speed.

[0152] Then, through the wireless communication module, the planned navigation route information is encapsulated in accordance with a predetermined communication protocol, such as the common JSON format, and accurately sent to the on-board navigation system of the rescue vehicle, so that the rescue personnel can intuitively see the path ahead.

[0153] At the same time, the cloud keeps tracking the real-time location of the rescue vehicle. When the rescue vehicle gradually approaches the traffic lights along the way, it sends precise guidance instructions to the traffic lights on the navigation route based on the data interaction interface pre-established with the traffic management department, combined with the rescue vehicle's real-time speed, distance from the traffic lights and other parameters. For example, if the traffic light is currently in red light state and the rescue vehicle is about to arrive at the intersection, it will send instructions to let the traffic light end the red light cycle in advance and quickly switch to green light, so as to guide the rescue vehicle to pass the intersection without waiting, and minimize the time loss during the rescue.

[0154] Or, if the vehicle state is in driving state, the driving route of the target vehicle is predicted, the road condition information of the driving route is obtained, the dynamic rescue route of the rescue vehicle is planned according to the road condition information and the location information of the rescue vehicle, and the dynamic rescue route is sent to the rescue vehicle.

[0155] Specifically, when the target vehicle is detected to be in motion, the system immediately starts a series of efficient operation processes. First, the system uses the location data continuously uploaded by the target vehicle's built-in positioning system (such as GPS, Beidou, etc.), combined with its historical driving trajectory, current speed, driving direction, and traffic rules of surrounding roads, to predict its most likely next driving route through intelligent algorithms.

[0156] Next, a deep connection is established with the traffic big data platform to obtain real-time traffic information on each section of the route based on the predicted driving route, covering the degree of road congestion, whether there are traffic accidents, the distribution of construction areas, and even the impact of weather changes on road conditions.

[0157] Then, the obtained road condition information is used as the key guide, and the path optimization algorithm is used to plan a dynamic rescue route for the rescue vehicle in combination with the current location of the rescue vehicle. Finally, the planned dynamic rescue route is sent to the rescue vehicle's onboard navigation system in the form of a data packet (such as the common JSON format) through the wireless communication module to ensure that the target vehicle can be reached in time.

[0158] In this embodiment, a vehicle rescue device is also provided, which is used to implement the above-mentioned embodiments and preferred implementation modes, and the descriptions that have been made will not be repeated. As used below, the term "module" can be a combination of software and / or hardware that implements a predetermined function. Although the devices described in the following embodiments are preferably implemented in software, the implementation of hardware, or a combination of software and hardware, is also possible and conceivable.

[0159] This embodiment provides a vehicle rescue device, such as Figure 3 As shown, including:

[0160] An acquisition module 301 is used to acquire a call event generated in a target vehicle;

[0161] The response module 302 is used to respond to the call event, control the target vehicle to sound a horn alarm, and obtain the positioning data and vehicle condition data of the target vehicle;

[0162] The sending module 303 is used to send the positioning data and the vehicle condition data to the cloud, wherein the cloud is used to analyze the vehicle condition data to obtain the rescue type of the target vehicle, and dispatch a rescue vehicle matching the rescue type according to the positioning data.

[0163] In an embodiment of the present application, the acquisition module 301 is used to detect a click operation on any call button in the target vehicle, wherein the call button in the target vehicle is arranged corresponding to the driver's seat in the target vehicle; respond to the click operation, determine the clicked target call button; based on the button identifier corresponding to the target call button, and generate a call event based on the button identifier.

[0164] In an embodiment of the present application, the response module 302 is used to query the positioning data of the target vehicle from the navigation system of the target vehicle; obtain the target driving seat corresponding to the button identifier contained in the call event; call the image acquisition device of the target vehicle to capture the target driving seat to obtain seat image data, and call the image acquisition device of the target vehicle to capture key areas in the target vehicle to obtain regional image data; obtain the operating data of each electronic control unit in the target vehicle; and generate vehicle condition data based on the seat image data, regional image data and operating data.

[0165] In an embodiment of the present application, the device also includes: a detection module for detecting environmental data of the target vehicle's environment; predicting safety hazard information of the vehicle based on environmental data and vehicle condition data; and sending the safety hazard information to the cloud, wherein the cloud is used to adjust the rescue vehicle according to the safety hazard information.

[0166] In an embodiment of the present application, the device also includes: a matching module, which is used to obtain the current operating behavior of the driver and passengers in the target vehicle; match the current operating behavior with the correct operating behavior of the safety hazard information; if the current operating behavior does not match the correct operating behavior, generate an operation suggestion based on the difference information between the current operating behavior and the correct operating behavior, and send the operation suggestion.

[0167] In this embodiment, a vehicle rescue device is also provided, which is used to implement the above-mentioned embodiments and preferred implementation modes, and the descriptions that have been made will not be repeated. As used below, the term "module" can be a combination of software and / or hardware that implements a predetermined function. Although the devices described in the following embodiments are preferably implemented in software, the implementation of hardware, or a combination of software and hardware, is also possible and conceivable.

[0168] This embodiment provides a vehicle rescue device, such as Figure 4 As shown, including:

[0169] The receiving module 401 is used to receive the positioning data and vehicle condition data sent by the target vehicle, and analyze the vehicle condition data to obtain the rescue type of the target vehicle;

[0170] A detection module 402 is used to obtain vehicle configuration information corresponding to the vehicle matching the positioning data, and the distance between the vehicle and the target vehicle;

[0171] A processing module 403 is used to take a vehicle whose vehicle configuration information matches the rescue type as a candidate vehicle;

[0172] The execution module 404 is used to select the candidate vehicle with the shortest distance from the target vehicle as a rescue vehicle, and send the positioning data of the target vehicle and the rescue type to the rescue vehicle.

[0173] In the embodiment of the present application, the device further includes: a planning module, which is used to obtain the current vehicle state of the target vehicle; if the vehicle state is a stationary state, a navigation route between the rescue vehicle and the target vehicle is planned, the navigation route is sent to the rescue vehicle, and a guidance instruction is sent to the traffic light located on the navigation route based on the real-time position of the rescue vehicle, so that the traffic light guides the rescue vehicle to pass through the intersection where the traffic light is located first according to the guidance instruction;

[0174] Or, if the vehicle state is in driving state, the driving route of the target vehicle is predicted, the road condition information of the driving route is obtained, the dynamic rescue route of the rescue vehicle is planned according to the road condition information and the location information of the rescue vehicle, and the dynamic rescue route is sent to the rescue vehicle.

[0175] See also Figure 5 , Figure 5is a schematic diagram of the structure of an electronic device provided by an optional embodiment of the present application, such as Figure 5 As shown, the electronic device includes: one or more processors 10, a memory 20, and interfaces for connecting various components, including high-speed interfaces and low-speed interfaces. The various components are connected to each other using different buses for communication, and can be installed on a common mainboard or installed in other ways as needed. The processor can process instructions executed in the electronic device, including instructions stored in or on the memory to display graphical information of the GUI on an external input / output device (such as a display device coupled to the interface). In some optional embodiments, if necessary, multiple processors and / or multiple buses can be used together with multiple memories and multiple memories. Similarly, multiple electronic devices can be connected, and each device provides some necessary operations (for example, as a server array, a group of blade servers, or a multi-processor system). Figure 5 A processor 10 is taken as an example.

[0176] The processor 10 may be a central processing unit, a network processor or a combination thereof. The processor 10 may further include a hardware chip. The hardware chip may be a dedicated integrated circuit, a programmable logic device or a combination thereof. The programmable logic device may be a complex programmable logic device, a field programmable gate array, a general purpose array logic or any combination thereof.

[0177] The memory 20 stores instructions executable by at least one processor 10, so that the at least one processor 10 executes the method shown in the above embodiment.

[0178] The memory 20 may include a program storage area and a data storage area, wherein the program storage area may store an operating system, an application required for at least one function; the data storage area may store data created by the use of an electronic device based on the presentation of a small program landing page, etc. In addition, the memory 20 may include a high-speed random access memory, and may also include a non-transient memory, such as at least one disk storage device, a flash memory device, or other non-transient solid-state storage device. In some optional embodiments, the memory 20 may optionally include a memory remotely arranged relative to the processor 10, and these remote memories may be connected to the electronic device via a network. Examples of the above-mentioned network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

[0179] The memory 20 may include a volatile memory, such as a random access memory; the memory may also include a non-volatile memory, such as a flash memory, a hard disk or a solid state drive; the memory 20 may also include a combination of the above types of memory.

[0180] The electronic device further comprises a communication interface 30 for the electronic device to communicate with other devices or a communication network.

[0181] The embodiment of the present application also provides a computer-readable storage medium. The above method according to the embodiment of the present application can be implemented in hardware, firmware, or can be implemented as a computer code that can be recorded in a storage medium, or can be implemented as a computer code that is originally stored in a remote storage medium or a non-temporary machine-readable storage medium and will be stored in a local storage medium through a network download, so that the method described herein can be stored in such software processing on a storage medium using a general-purpose computer, a dedicated processor, or programmable or dedicated hardware. Among them, the storage medium can be a magnetic disk, an optical disk, a read-only storage memory, a random access memory, a flash memory, a hard disk or a solid-state hard disk, etc.; further, the storage medium can also include a combination of the above types of memories. It can be understood that a computer, a processor, a microprocessor controller, or programmable hardware includes a storage component that can store or receive software or computer code. When the software or computer code is accessed and executed by a computer, a processor, or hardware, the method shown in the above embodiment is implemented.

[0182] Although the embodiments of the present application are described in conjunction with the accompanying drawings, those skilled in the art may make various modifications and variations without departing from the spirit and scope of the present application, and such modifications and variations are all within the scope defined by the appended claims.

Claims

1. A vehicle rescue method, characterized in that: The method comprises: Obtain the call event generated in the target vehicle; In response to the call event, the positioning data and vehicle condition data of the target vehicle are obtained, and the target vehicle is controlled to perform a horn alarm operation; The positioning data and the vehicle condition data are sent to the cloud, wherein the cloud is used to analyze the vehicle condition data to obtain the rescue type of the target vehicle, and dispatch a rescue vehicle matching the rescue type according to the positioning data.

2. The method according to claim 1, characterized in that: The step of obtaining a call event generated in the target vehicle includes: Detecting a click operation on any one of the call buttons in the target vehicle, wherein the call button in the target vehicle is arranged corresponding to a driver's seat in the target vehicle; In response to the click operation, determining a clicked target call button; Based on the button identifier corresponding to the target call button, the call event is generated based on the button identifier.

3. The method according to claim 1, characterized in that The obtaining of the positioning data and vehicle condition data of the target vehicle includes: Querying the positioning data of the target vehicle from the navigation system of the target vehicle; Obtaining a target driving seat corresponding to the button identifier included in the call event; Calling the image acquisition device of the target vehicle to capture the target driving seat to obtain seat image data, and calling the image acquisition device of the target vehicle to capture the key area in the target vehicle to obtain area image data; Acquiring operating data of each electronic control unit in the target vehicle; The vehicle condition data is generated based on the seat image data, the area image data, and the operation data.

4. The method according to claim 1, characterized in that After sending the positioning data and the vehicle condition data to the cloud, the method further includes: Detecting environmental data of the environment where the target vehicle is located; Predicting potential safety hazard information of the vehicle based on the environmental data and the vehicle condition data; The safety hazard information is sent to the cloud, wherein the cloud is used to adjust the rescue vehicle according to the safety hazard information.

5. The method according to claim 4, characterized in that The method further comprises: Obtaining current operating behavior of the driver and passengers in the target vehicle; Matching the current operation behavior with the correct operation behavior of the potential safety hazard information; If the current operation behavior does not match the correct operation behavior, an operation suggestion is generated based on difference information between the current operation behavior and the correct operation behavior, and the operation suggestion is sent.

6. A vehicle rescue method, characterized in that: The method comprises: Receiving positioning data and vehicle condition data sent by the target vehicle, and analyzing the vehicle condition data to obtain the rescue type of the target vehicle; Acquire vehicle configuration information corresponding to a vehicle matching the positioning data, and a distance between the vehicle and the target vehicle; taking a vehicle whose vehicle configuration information matches the rescue type as a candidate vehicle; The candidate vehicle with the shortest distance from the target vehicle is used as a rescue vehicle, and the positioning data and the rescue type of the target vehicle are sent to the rescue vehicle.

7. The method according to claim 6, characterized in that After sending the location data of the target vehicle and the rescue type to the rescue vehicle, the method further includes: Obtaining the current vehicle state of the target vehicle; If the vehicle is in a stationary state, a navigation route between the rescue vehicle and the target vehicle is planned, the navigation route is sent to the rescue vehicle, and a guidance instruction is sent to a traffic light located on the navigation route based on the real-time position of the rescue vehicle, so that the traffic light guides the rescue vehicle to preferentially pass through the intersection where the traffic light is located according to the guidance instruction; Or, if the vehicle state is a driving state, the driving route of the target vehicle is predicted, the road condition information of the driving route is obtained, the dynamic rescue route of the rescue vehicle is planned according to the road condition information and the location information of the rescue vehicle, and the dynamic rescue route is sent to the rescue vehicle.

8. A vehicle rescue device, characterized in that: The device comprises: An acquisition module, used for acquiring a call event generated in a target vehicle; A response module, used to respond to the call event, control the target vehicle to sound a horn alarm, and obtain the positioning data and vehicle condition data of the target vehicle; A sending module is used to send the positioning data and the vehicle condition data to the cloud, wherein the cloud is used to analyze the vehicle condition data to obtain the rescue type of the target vehicle, and dispatch a rescue vehicle matching the rescue type according to the positioning data.

9. A vehicle rescue device, characterized in that: The device comprises: A receiving module, used to receive the positioning data and vehicle condition data sent by the target vehicle, and analyze the vehicle condition data to obtain the rescue type of the target vehicle; A detection module, used to obtain vehicle configuration information corresponding to a vehicle matching the positioning data, and a distance between the vehicle and the target vehicle; A processing module, configured to take a vehicle whose vehicle configuration information matches the rescue type as a candidate vehicle; The execution module is used to select the candidate vehicle with the shortest distance from the target vehicle as a rescue vehicle, and send the positioning data of the target vehicle and the rescue type to the rescue vehicle.

10. An electronic device, characterized in that: include: A memory and a processor, wherein the memory and the processor are communicatively connected to each other, the memory stores computer instructions, and the processor executes the method according to any one of claims 1 to 7 by executing the computer instructions.

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