Vehicle control method and device, equipment, storage medium and program product

Abstract

The invention provides a vehicle control method and device, a vehicle, a storage medium and a program product, and relates to the field of auxiliary driving. The method comprises the following steps: acquiring environment sensing data of a vehicle; in response to the fact that the sensing data is matched with target weather, generating a control instruction associated with the target weather; and the working state of the vehicle is adjusted according to the control instruction. According to the method, the current weather scene can be determined according to the sensing data, the generation of the corresponding control instruction is automatically triggered according to the weather scene, and the working state of the vehicle is adjusted in time, so that the vehicle has the adjusting capability of actively sensing and adapting to the environment, the self-adaptability of the vehicle to the weather is greatly improved, and the user experience is improved. And more intelligent, safer and more comfortable driving experience can be provided.

Description

Technical Field

[0001] The present disclosure relates to the field of assisted driving, and in particular to a vehicle control method, device, vehicle, storage medium, and program product. Background Art

[0002] With the development of computer technology and vehicle intelligence, the degree of automation and intelligence of automobiles continues to improve. Vehicles may encounter a variety of complex weather conditions during daily driving, which may affect driving convenience and safety.

[0003] It should be noted that the information disclosed in the above background technology section is only used to enhance the understanding of the background of the present disclosure, and therefore may include information that does not constitute prior art known to ordinary technicians in the field. Summary of the Invention

[0004] The present disclosure aims to provide a vehicle control method, device, vehicle, storage medium and program product.

[0005] According to a first aspect of an embodiment of the present disclosure, a vehicle control method is provided, comprising: acquiring vehicle perception data of an environment; generating control instructions associated with the target weather in response to the perception data matching the target weather; and adjusting the operating state of the vehicle according to the control instructions.

[0006] The technical solutions provided by the embodiments of the present disclosure may have the following beneficial effects:

[0007] The present disclosure can determine the current weather scene based on perception data, and automatically trigger the generation of corresponding control instructions according to the weather scene, so as to timely adjust the working state of the vehicle, so that the vehicle has the ability to actively perceive and adapt to the environment, greatly improving the vehicle's adaptability to the weather, and thus providing a more intelligent, safe and comfortable driving experience.

[0008] In some embodiments, the perception data includes at least one of the following: vehicle sensor data, vehicle status data, and received external environment data.

[0009] In the above embodiment, various perception information that may be used by the vehicle during operation can be used to perceive the vehicle's surrounding environment, thereby determining the weather and making reasonable decisions to control the vehicle.

[0010] In some embodiments, the matching of the perception data with the target weather includes: in response to the perception data satisfying a target recognition condition associated with the target weather, determining that the perception data matches the target weather.

[0011] In the above embodiment, target recognition conditions can be set for judging the current weather conditions, providing specific and quantifiable standards for accurately judging the current weather conditions, establishing a clear association between perception data and target weather, providing an accurate basis for subsequent control decisions, and ensuring that the vehicle can respond according to actual weather conditions.

[0012] In some embodiments, the perception data satisfies the target recognition conditions associated with the target weather, including: the perception data satisfies the perception conditions in the target recognition conditions; and / or, the environment recognition results detected based on the perception data meet the environment recognition conditions in the target recognition conditions; wherein, the environment recognition results include: obtained by processing the perception data through a neural network model.

[0013] In the above-mentioned embodiment, by combining the two judgment methods of perception conditions and environmental recognition conditions, the respective advantages can be fully utilized. The perception conditions are used to quickly capture obvious weather characteristics, and the environmental recognition conditions are used to deeply analyze complex environmental information with the help of a neural network model. The two complement each other, reducing the probability of misjudgment and missed judgment, and enabling the vehicle to more accurately identify the target weather.

[0014] In some embodiments, the target weather includes at least one of the following: snowy weather, rainy weather, foggy weather, sandstorm weather, and high temperature weather.

[0015] In the above embodiment, a variety of common weather conditions that have a significant impact on vehicle driving can be considered. Setting corresponding control instructions for these weather conditions in advance can enhance the stability and controllability of the vehicle in different weather conditions and effectively reduce the accident rate of the vehicle in complex weather conditions.

[0016] In some embodiments, the control instructions include at least one of the following: starting the vehicle temperature control module; adjusting the braking parameters of the chassis system; starting the wiper module; starting the defogger module; updating the content in the cabin display module; starting the cabin interior atmosphere adjustment module; pushing music.

[0017] In the above-mentioned embodiment, corresponding control instructions can be automatically generated according to the sensed weather information, and adjustments to various vehicle systems and components can be completed without human intervention, thus realizing intelligent and automated vehicle control.

[0018] In some embodiments, the vehicle control method further includes: broadcasting prompt information corresponding to the control instruction.

[0019] In the above-mentioned embodiment, by broadcasting prompt information corresponding to the control instruction, the user can clearly understand the control instruction that the vehicle is about to execute and the related reasons and intentions, enhance the user's understanding of the vehicle control logic, and enhance the user's sense of control over the vehicle status changes, avoiding the user's tension or erroneous operation due to misunderstanding, thereby improving the user's driving safety and comfort.

[0020] In some embodiments, the vehicle control method further includes: determining the weather to be configured, the identification condition to be configured, and the control instruction to be configured; establishing an association relationship between the weather to be configured and the identification condition to be configured, wherein the identification condition to be configured is used to determine whether the weather to be configured matches the perception data; and establishing an association relationship between the control instruction to be configured and at least one of the weather to be configured and the identification condition to be configured.

[0021] In the above embodiment, personalized customization can be supported, allowing users to freely configure weather types, identification conditions and control instructions according to different regions and different usage scenarios, and establish associations between them, so that the vehicle can accurately identify the weather according to preset rules and take appropriate measures, thereby improving the vehicle's adaptability and response capabilities in complex environments.

[0022] In some embodiments, establishing an association relationship between the weather to be configured and the identification condition to be configured includes: determining at least one data configuration item associated with the weather to be configured; the data configuration item corresponds to the perception data or the environment identification result determined based on the perception data; configuring the data condition based on the data configuration item; configuring the logical relationship between each of the data conditions to generate the identification condition to be configured; wherein the logical relationship includes at least one of the following: an AND relationship, an OR relationship, and a NOT relationship; establishing an association relationship between the weather to be configured and the identification condition to be configured.

[0023] In the above implementation, by clarifying data configuration items, configuring specific data conditions, and reasonably combining logical relationships, the characteristics of various weather conditions can be comprehensively and meticulously described, so that the vehicle can comprehensively consider multiple relevant factors when judging the weather, thereby improving the accuracy and reliability of weather recognition.

[0024] In some embodiments, the target weather includes snowy weather; wherein, in response to the perception data matching the target weather, a control instruction associated with the target weather is generated, including: in response to the perception data satisfying the snowy weather identification condition associated with the snowy weather, a snowy weather control instruction associated with the snowy weather is generated; wherein, the snowy weather control instruction includes at least one of the following: starting the body heating module to heat the vehicle's sensors and / or peripheral equipment; adjusting the braking parameters of the chassis system to enhance the braking sensitivity and / or enhance the strength of the anti-lock braking system; starting the wiper module and / or the defogger module; displaying the effect image corresponding to the snowy weather and / or the prompt information corresponding to the snowy weather through the cockpit display module.

[0025] In the above-mentioned embodiment, the vehicle can be controlled from multiple aspects to automatically adapt to snowy scenes, ensuring that the vehicle's perception system and some key components can continue to work stably, providing reliable data support and functional guarantees for the vehicle's safe driving, and creating a driving atmosphere that is more in line with the actual environment for the driver.

[0026] In some embodiments, the perception data includes at least one of the following: temperature sensor data, wiper sensor data, chassis sensor data, laser sensor data and visual sensor data; the perception data satisfies the snowy day identification conditions associated with the snowy day, including: the perception data satisfies the air condition and / or the ground condition; wherein the air condition includes at least one of the following: the environmental recognition result detected based on the visual sensor data and / or the laser sensor data is that there are snowy day features in the air; it is determined according to the wiper sensor data that the wiper is turned on and the temperature sensor data is lower than the temperature threshold; the environmental recognition result detected based on the visual sensor data and / or the laser sensor data is that there are snowy day features in the air and the temperature sensor data is lower than the temperature threshold; the ground condition includes at least one of the following: the environmental recognition result detected based on the visual sensor data and / or the laser sensor data is that there are snowy day features on the ground; the environmental recognition result detected based on the visual sensor data and / or the laser sensor data is that there are snowy day features on the ground and the temperature sensor data is lower than the temperature threshold; it is determined according to the chassis sensor data that the road surface is slippery and the temperature sensor data is lower than the temperature threshold.

[0027] In the above implementation, by integrating various types of perception data and setting snow recognition conditions from both air and ground dimensions, the characteristics of snow can be fully and accurately captured, thereby improving the accuracy and reliability of snow recognition.

[0028] According to a second aspect of an embodiment of the present disclosure, a vehicle control device is provided, including: an acquisition unit for acquiring the vehicle's perception data of the environment; an instruction generation unit for generating control instructions associated with the target weather in response to the perception data matching the target weather; and a control unit for adjusting the working state of the vehicle according to the control instructions.

[0029] In some embodiments, the perception data includes at least one of the following: vehicle sensor data, vehicle status data, and received external environment data.

[0030] In some embodiments, the instruction generation unit is further configured to: in response to the perception data satisfying a target recognition condition associated with the target weather, determine that the perception data matches the target weather.

[0031] In some embodiments, the perception data satisfies the target recognition conditions associated with the target weather, including: the perception data satisfies the perception conditions in the target recognition conditions; and / or, the environment recognition results detected based on the perception data meet the environment recognition conditions in the target recognition conditions; wherein, the environment recognition results include: obtained by processing the perception data through a neural network model.

[0032] In some embodiments, the target weather includes at least one of the following: snowy weather, rainy weather, foggy weather, sandstorm weather, and high temperature weather.

[0033] In some embodiments, the control instructions include at least one of the following: starting the vehicle temperature control module; adjusting the braking parameters of the chassis system; starting the wiper module; starting the defogger module; updating the content in the cabin display module; starting the cabin interior atmosphere adjustment module; pushing music.

[0034] In some embodiments, the control unit is further configured to: broadcast prompt information corresponding to the control instruction.

[0035] In some embodiments, the vehicle control device also includes a configuration unit, which is used to: determine the weather to be configured, the identification conditions to be configured, and the control instructions to be configured; establish an association relationship between the weather to be configured and the identification conditions to be configured, wherein the identification conditions to be configured are used to determine whether the weather to be configured matches the perception data; and establish an association relationship between the control instructions to be configured and at least one of the weather to be configured and the identification conditions to be configured.

[0036] In some embodiments, the configuration unit establishes an association relationship between the weather to be configured and the identification condition to be configured, including: determining at least one data configuration item associated with the weather to be configured; the data configuration item corresponds to the perception data or the environment identification result determined based on the perception data; configuring the data condition based on the data configuration item; configuring the logical relationship between each of the data conditions to generate the identification condition to be configured; wherein the logical relationship includes at least one of the following: an AND relationship, an OR relationship, and a NOT relationship; establishing an association relationship between the weather to be configured and the identification condition to be configured.

[0037] In some embodiments, the target weather includes snowy weather; wherein, the instruction generation unit generates control instructions associated with the target weather in response to the perception data matching the target weather, including: generating snowy weather control instructions associated with the snowy weather in response to the perception data satisfying the snowy weather identification condition associated with the snowy weather; wherein, the snowy weather control instructions include at least one of the following: starting the body heating module to heat the vehicle's sensors and / or peripheral equipment; adjusting the braking parameters of the chassis system to enhance the braking sensitivity and / or enhance the strength of the anti-lock braking system; starting the wiper module and / or the defogger module; displaying the effect image corresponding to the snowy weather and / or the prompt information corresponding to the snowy weather through the cockpit display module.

[0038] In some embodiments, the perception data includes at least one of the following: temperature sensor data, wiper sensor data, chassis sensor data, laser sensor data and visual sensor data; the perception data satisfies the snowy day identification conditions associated with the snowy day, including: the perception data satisfies the air condition and / or the ground condition; wherein the air condition includes at least one of the following: the environmental recognition result detected based on the visual sensor data and / or the laser sensor data is that there are snowy day features in the air; it is determined according to the wiper sensor data that the wiper is turned on and the temperature sensor data is lower than the temperature threshold; the environmental recognition result detected based on the visual sensor data and / or the laser sensor data is that there are snowy day features in the air and the temperature sensor data is lower than the temperature threshold; the ground condition includes at least one of the following: the environmental recognition result detected based on the visual sensor data and / or the laser sensor data is that there are snowy day features on the ground; the environmental recognition result detected based on the visual sensor data and / or the laser sensor data is that there are snowy day features on the ground and the temperature sensor data is lower than the temperature threshold; it is determined according to the chassis sensor data that the road surface is slippery and the temperature sensor data is lower than the temperature threshold.

[0039] According to a third aspect of an embodiment of the present disclosure, a vehicle is provided, comprising: a processor; and a memory for storing processor-executable instructions; wherein the processor is configured to implement the above-mentioned vehicle control method.

[0040] According to a fourth aspect of an embodiment of the present disclosure, an electronic device is provided, comprising: a processor; and a memory for storing processor-executable instructions; wherein the processor is configured to implement the above-mentioned vehicle control method.

[0041] According to the fifth aspect of an embodiment of the present disclosure, a non-temporary computer-readable storage medium is provided. When the instructions in the storage medium are executed by a processor of a mobile terminal, the mobile terminal is enabled to execute a vehicle control method, the method comprising: acquiring the vehicle's perception data of the environment; in response to the perception data matching the target weather, generating a control instruction associated with the target weather; and adjusting the operating state of the vehicle according to the control instruction.

[0042] According to a sixth aspect of an embodiment of the present disclosure, a computer program product is provided, comprising a computer program, which implements the above-mentioned vehicle control method when executed by a processor.

[0043] It is to be understood that the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the disclosure. BRIEF DESCRIPTION OF THE DRAWINGS

[0044] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present disclosure and, together with the description, serve to explain the principles of the present disclosure.

[0045] Figure 1 is a flowchart illustrating a vehicle control method according to some embodiments of the present disclosure.

[0046] Figure 2 is a flowchart illustrating another vehicle control method according to some embodiments of the present disclosure.

[0047] Figure 3 is a flowchart illustrating another vehicle control method according to some embodiments of the present disclosure.

[0048] Figure 4 It is a flowchart illustrating the association configuration of weather, identification conditions and control instructions in a vehicle control method according to some embodiments of the present disclosure.

[0049] Figure 5 This is a flowchart illustrating the association configuration between weather and identification conditions in a vehicle control method according to some embodiments of the present disclosure.

[0050] Figure 6 is a block diagram of a vehicle control device according to some embodiments of the present disclosure.

[0051] Figure 7is a block diagram illustrating a device for vehicle control according to some embodiments of the present disclosure. DETAILED DESCRIPTION

[0052] Some exemplary embodiments of the present disclosure will be described in detail herein, examples of which are shown in the accompanying drawings. When the following description refers to the drawings, unless otherwise indicated, the same numbers in different drawings represent the same or similar elements. Various changes, modifications and equivalents of the methods, devices and / or systems described herein will become apparent after understanding the present disclosure. For example, the order of operations described herein is merely an example and is not limited to those orders set forth herein, but may be changed as becomes apparent after understanding the present disclosure, except for operations that must be performed in a specific order. In addition, descriptions of features known in the art may be omitted for clarity and brevity.

[0053] The following exemplary embodiments of the present disclosure do not represent all embodiments consistent with the present disclosure. Instead, they are merely examples of devices and methods consistent with some aspects of the present disclosure as detailed in the appended claims.

[0054] The specific implementation of the embodiment of the present disclosure is described in detail below with reference to the accompanying drawings.

[0055] Figure 1 is a flow chart of a vehicle control method according to some embodiments of the present disclosure. Figure 1 As shown, the vehicle control method can be applied to electronic devices, including but not limited to terminal devices such as vehicle-mounted terminals, smartphones, smart tablets, wearable devices, desktop computers, laptop computers, and smart speakers. It can also include server-side devices such as local servers and cloud servers. The server-side can be deployed in a single computer or a computer cluster consisting of multiple computers. The vehicle control method can include the following steps.

[0056] In step S110 , the vehicle's perception data of the environment is acquired.

[0057] In the disclosed embodiment, the perception data of the environment may include information obtained by the vehicle from multiple channels. This information can form the basis for the vehicle to understand the external environment, enabling the vehicle to understand its external environment from multiple dimensions, thereby providing basic data for subsequent decision-making and vehicle control so as to make reasonable responses.

[0058] In some embodiments of the present disclosure, the perception data includes at least one of the following: vehicle sensor data, vehicle status data, and received external environment data.

[0059] In the disclosed embodiment, vehicle sensor data may be information about the surrounding environment collected by the vehicle in all directions with the help of various sensors carried by the vehicle. These sensors may include, for example, cameras, millimeter-wave radars, lidars, ultrasonic sensors, meteorological sensors (such as temperature sensors), wiper sensors, chassis sensors, etc., to perceive the surrounding environment in real time. Among them, the camera can capture image information around the vehicle; the millimeter-wave radar can accurately measure the distance, speed and angle of the target object, and can work well even in bad weather; the lidar can create a three-dimensional point cloud map of the surrounding environment by emitting a laser beam and measuring the reflected light, providing high-precision environmental information; the meteorological sensor can be responsible for sensing meteorological data such as temperature, humidity, and rainfall. These sensor data can provide the vehicle with rich details about the external environment.

[0060] Vehicle status data can include information such as vehicle speed, acceleration, steering angle, braking status, engine speed, battery charge, etc. These data can reflect the current operating status of the vehicle and thus indirectly reflect the current weather conditions.

[0061] For example, in severe weather conditions (such as heavy rain, snow, and strong winds), drivers usually reduce their speed to ensure driving safety. If the vehicle status data shows that the vehicle speed is significantly lower than the normal driving speed and persists for a period of time, it can indicate that the current weather conditions are poor. For another example, the use of wipers can be used to determine whether it is raining and the intensity of the rain. If the vehicle status data shows that the wipers are frequently activated and the wiping speed is fast, it is likely that heavy rain or rainstorms have occurred. For another example, the vehicle can monitor the speed and slippage of the tires and feedback them through the vehicle status data. When the road is slippery or icy, the tires are prone to slipping, which indicates that the road condition is poor and there may be rain, ice, and snow. It can then be inferred that the current weather may be rainy, snowy, or cold weather causing the road to become icy.

[0062] Received external environmental data can be environmental information received by the vehicle through communication technologies. This external data can supplement the vehicle's own perception and provide more comprehensive environmental information. For example, a vehicle can use connected vehicle technology to receive real-time road conditions from traffic management departments, weather warnings from meteorological departments, or information about surrounding traffic conditions from other vehicles.

[0063] Through the embodiments of the present disclosure, perception data can cover direct data obtained by the vehicle from its own sensors, data reflecting its own status, and auxiliary data obtained from the outside. It can comprehensively summarize various perception information that the vehicle may use during operation, helping the vehicle to perceive the surrounding environment more accurately and make reasonable decisions and controls.

[0064] In step S120 , in response to the sensing data matching the target weather, a control instruction associated with the target weather is generated.

[0065] In the disclosed embodiment, the control instruction may be a command signal generated based on the matching result between the perception data and the target weather, and may be used to guide the various systems and components of the vehicle to make corresponding adjustments to achieve adaptive vehicle control.

[0066] The judgment criteria corresponding to various types of target weather can be set in advance, and the acquired perception data can be analyzed and judged. When it is determined that the perception data meets these criteria, it can be determined that the current environment is in a certain target weather, thereby triggering the generation of control instructions associated with the current weather.

[0067] For example, if the sensory data indicates light rain and persistent water accumulation on the road, it can be determined that it is raining, and the system will generate control instructions suitable for rainy weather driving. Another example is that if the sensory data indicates that both rainfall and wind speed reach certain values, it can be determined that it is stormy weather, triggering the generation of the following control instructions: turning on the wipers in high-speed mode, adjusting the headlight angle, lowering the upper speed limit, etc.

[0068] In this way, targeted control strategies can be formulated for vehicles according to different weather conditions to ensure that the vehicles can operate safely and stably under various complex weather conditions.

[0069] In some embodiments of the present disclosure, the target weather includes at least one of the following: snowy weather, rainy weather, foggy weather, sandstorm weather, and high temperature weather.

[0070] In the disclosed embodiments, these target weather conditions encompass a variety of common weather conditions that significantly impact vehicle operation. By pre-setting corresponding control instructions for these weather conditions, the vehicle's operating state can be automatically adjusted, enhancing its stability and maneuverability in varying weather conditions. This effectively reduces the accident rate in complex weather conditions and ensures the safety of drivers and passengers.

[0071] In step S130, the operating state of the vehicle is adjusted according to the control instruction.

[0072] In the disclosed embodiment, after receiving the control instruction, the vehicle can adjust its various systems and components to change the working state of the vehicle.

[0073] In an exemplary embodiment, these adjustments may involve, for example, a temperature control system (such as heating the vehicle body, heating the seats in the vehicle, and adjusting the temperature in the vehicle), a cockpit display system (such as updating the display content of the screen in the vehicle, such as updating the weather icon according to weather changes, adding prompts, etc.), a power system (such as adjusting the engine output power, motor torque, brake sensitivity, etc.), a steering system (such as adjusting the steering assist, steering sensitivity, etc.), a vehicle body lighting system (such as turning on or off fog lights, low beam lights, hazard warning flashers, etc.), a cabin atmosphere adjustment system (such as displaying different cabin atmosphere lights according to weather changes, adjusting the cabin humidification gear, releasing different fragrances, etc.), a playback system (such as synchronously playing the adjustment content corresponding to the control instructions, playing music pushed according to weather changes, etc.), etc.

[0074] Through this step, the vehicle can better adapt to driving requirements under target weather conditions and improve driving safety and comfort.

[0075] It can be seen from the above steps that the vehicle control method provided by the present invention can determine the current weather scene based on the perception data, and automatically trigger the generation of corresponding control instructions based on the weather scene, so as to adjust the working state of the vehicle in time, so that the vehicle has the ability to actively perceive and adapt to the environment, greatly improving the vehicle's adaptability to the weather, and thus can provide a more intelligent, safe and comfortable driving experience.

[0076] Figure 2 is a flowchart illustrating another vehicle control method according to some embodiments of the present disclosure.

[0077] In the embodiment of the present disclosure, Figure 2 The vehicle control method shown includes any one of step S210, step S220, step S230, and step S240 or any combination of multiple steps, wherein step S210, S230, and S240 are respectively Figure 1 Steps S110 , S120 , and S130 in the vehicle control method shown correspond to each other and are not repeated here.

[0078] In the embodiment of the present disclosure, Figure 1 Based on the vehicle control method shown, Figure 2 The vehicle control method shown may further include the following steps.

[0079] In step S220 , in response to the perception data satisfying the target recognition condition associated with the target weather, it is determined that the perception data matches the target weather.

[0080] In the disclosed embodiment, target recognition conditions can be set for each target weather type based on its typical meteorological characteristics and its impact on vehicle driving. The target recognition conditions can include data standards and / or logical judgment rules, and can be based on the perception data itself or on processing the perception data first and then judging the processing results.

[0081] When the perception data meets the target recognition conditions of a certain target weather, it can be determined that the current perception data matches the target weather, and the control instruction generation process related to the target weather can be triggered through subsequent steps.

[0082] For example, on rainy days, target recognition conditions might include the rain sensor detecting rainfall exceeding a certain value, the wipers operating continuously, the camera capturing light spots reflected by accumulated water on the road, and the millimeter-wave radar detecting a decrease in the road friction coefficient. When the relevant parameters in the perception data acquired by the vehicle meet or conform to these preset conditions, the perception data satisfies the target recognition conditions associated with the target weather. For another example, on snowy days, conditions might include the ambient temperature being below 0°C and the sensor detecting falling snowflakes for a certain period of time.

[0083] Through the disclosed embodiments, the target recognition conditions can provide specific and quantifiable standards for accurately judging the current weather conditions, establish a clear association between perception data and target weather, avoid weather recognition errors due to subjective judgment or ambiguous environmental characteristics, provide an accurate basis for subsequent control decisions, and ensure that the vehicle can respond according to actual weather conditions.

[0084] In some embodiments of the present disclosure, the perception data satisfies the target recognition conditions associated with the target weather, which may include: the perception data satisfies the perception conditions in the target recognition conditions; and / or, the environment recognition results detected based on the perception data meet the environment recognition conditions in the target recognition conditions; wherein, the environment recognition results include: obtained by processing the perception data through a neural network model.

[0085] In the disclosed embodiment, the matching relationship between the perception data and the target recognition conditions can be judged through multiple dimensions, and a neural network model can be introduced to process the perception data.

[0086] The perception conditions within the target recognition framework can include a series of parameter thresholds or feature requirements set for the perception data itself. When the relevant parameters in the perception data acquired by the vehicle meet these preset perception conditions, the conditions are considered met.

[0087] For example, when determining whether it is raining, the perception condition may include the rainfall value measured by the rain sensor reaching a specific standard (such as rainfall exceeding 10 mm per hour), or the air humidity detected by the humidity sensor exceeding a certain threshold (such as relative humidity greater than 80%). When determining whether it is snowing, the perception condition may include the temperature value measured by the temperature sensor being lower than a specific standard (such as the temperature being lower than 0°C).

[0088] By directly judging the raw perception data obtained by the sensor, some features related to the target weather can be quickly and intuitively identified, providing a basic basis for subsequent comprehensive judgment. This judgment method is relatively simple and efficient, and can respond to some obvious weather features in a short time.

[0089] Target recognition conditions can also include specific requirements for environmental recognition results, known as environmental recognition conditions. Perception data can be fed into a pre-trained neural network model. The model's learning and reasoning capabilities allow for a more comprehensive and complex assessment of the environment, resulting in environmental recognition results. For example, determining whether there's snow in the sky or the road is slippery is crucial. This condition is satisfied when the environmental recognition results obtained by processing the perception data with the neural network model meet these requirements.

[0090] Among them, the neural network model can capture the complex nonlinear relationships and potential characteristics in the perception data. Compared with the judgment directly based on the perception conditions, it can more accurately identify some environmental states that are difficult to describe with simple thresholds or features, thereby improving the accuracy and comprehensiveness of the judgment of the target weather and being able to better cope with the complex and changeable actual environment.

[0091] In an exemplary embodiment, only the perception condition, only the environment recognition condition, or both conditions may be satisfied, and then it may be determined that the perception data satisfies the target recognition condition associated with the target weather.

[0092] The disclosed embodiments combine the perception and environmental recognition methods, leveraging their respective strengths. The perception method can quickly capture distinct weather characteristics, while the environmental recognition method leverages neural network models to deeply analyze complex environmental information. The two complement each other, reducing the probability of misjudgments and missed detections, enabling the vehicle to more accurately identify target weather conditions and providing a reliable basis for subsequent control decisions.

[0093] Figure 3 is a flowchart illustrating another vehicle control method according to some embodiments of the present disclosure.

[0094] In the embodiment of the present disclosure, Figure 3The vehicle control method shown includes any one of steps S310, S320, S330, S340, S350, S360, S370, S380, and S390, or any combination of multiple steps, wherein steps S310 and S320 are respectively Figure 1 Steps S110 and S120 in the vehicle control method shown correspond to each other and are not repeated here.

[0095] In the embodiment of the present disclosure, there is no timing dependency between steps S330, S340, S350, S360, S370, S380, and S390. Each step can be executed independently, or multiple steps can be executed simultaneously or sequentially. The present disclosure does not limit the number of steps (steps S330 to S390) to be executed and the order in which they are executed.

[0096] In some embodiments of the present disclosure, Figure 1 Based on the vehicle control method shown, Figure 3 The vehicle control method shown may further include the following steps.

[0097] Step S330: Start the vehicle temperature adjustment module.

[0098] The vehicle temperature control system can receive the control signal and then adjust the cooling or heating function of the vehicle air conditioner according to the target weather and the temperature inside the vehicle, or start the heating module to heat the vehicle's sensors or body peripherals to achieve snow removal, defogging and / or decontamination effects on the vehicle body. For example, in hot weather, the cooling capacity can be increased to quickly lower the temperature inside the vehicle; in cold weather, the heating can be turned on and the seats can be preheated to improve the comfort inside the vehicle. For another example, in rainy or snowy scenes, if there is rain or snow remaining on the camera, the camera's built-in heating wire can be used to heat it, causing the rain or snow to melt or evaporate, thereby decontaminating the equipment and improving safety.

[0099] Step S340: Adjust the braking parameters of the chassis system.

[0100] The vehicle chassis control system can receive brake parameter adjustment commands and then change brake system parameters such as pressure, response speed, anti-lock braking parameters, and sensitivity based on the target weather conditions. For example, on slippery rainy or icy snowy days, brake pressure can be increased, brake response time can be shortened, and braking effectiveness can be improved to ensure driving safety.

[0101] Step S350: start the wiper module.

[0102] When a command involves a wiper operation, the corresponding module is activated immediately. For example, on rainy days, the wiper module automatically adjusts the wiper speed based on the amount of rain. As the rainfall intensifies, the module automatically switches from low-speed intermittent mode to high-speed continuous mode, quickly clearing rain from the windshield and maintaining a clear view ahead for the driver, ensuring driving safety.

[0103] Step S360: Start the demisting module.

[0104] When a command involves defogger operation, the corresponding module can be activated immediately. For example, when the windows fog up in fog, rain, or due to large temperature fluctuations, the defogger module can quickly clear the fog by heating the windows or adjusting the air conditioning mode, ensuring clear vision for the driver and driving safety.

[0105] Step S370: Update the content in the cockpit display module.

[0106] In the disclosed embodiment, the cockpit display system receives this control command and can then modify the display content on the instrument panel, central control screen, and other devices based on the target weather conditions, displaying visual effects or safety reminders related to the target weather conditions on the vehicle interface. For example, on snowy days, the display interface can display snowflake effects and snowy driving reminders; on foggy days, the display interface can highlight key information such as the distance and speed between the vehicle and the vehicle ahead; and on dusty days, the display interface can prompt the driver to close the windows, switch the air conditioning to internal recirculation, and other precautions, providing effective driver information.

[0107] Step S380: Start the cabin interior atmosphere adjustment module.

[0108] In the disclosed embodiment, the cabin interior atmosphere adjustment module may include components that enhance the riding experience, such as the in-car lighting system, air purification system, humidification system, and fragrance diffuser. Different control instructions may be generated for the cabin interior atmosphere adjustment module according to different weather conditions. The cabin interior atmosphere adjustment module may be used to adjust the color and brightness of the in-car atmosphere lights, or adjust the in-car fragrance system, thereby enhancing the user's riding experience.

[0109] For example, the interior ambient light can be switched to warm lights (such as orange and red) on rainy or snowy days to create a warm atmosphere visually; the interior ambient light can be switched to cool lights (such as light blue) on hot weather to create a cool atmosphere visually; the preset scent fragrance (such as mint fragrance) can be released on hot weather to relieve the user's discomfort in high temperatures; the air purification intensity in the car can be increased on dusty weather, so that the user can feel the fresh air in the car that is different from the air outside the car.

[0110] Step S390: Push music.

[0111] In the disclosed embodiment, music can be intelligently recommended based on weather scenarios, such as playing soothing piano music on rainy days and pushing light holiday songs on snowy days, etc., to soothe the user's mood.

[0112] In an exemplary embodiment, scenario-based music recommendations can be achieved by linking the music library in the vehicle system with the weather database.

[0113] In an exemplary embodiment, different control instructions may be set according to vehicle operation and driving experience requirements under different target weather scenarios.

[0114] Through the disclosed embodiments, corresponding control instructions can be automatically generated based on perceived weather information, enabling adjustments to various vehicle systems and components without manual intervention, thus achieving intelligent and automated vehicle control. This not only reduces the driver's burden and provides a more comfortable, convenient, and safe driving experience, but also enables the vehicle to adapt to different weather changes more quickly and accurately, improving the vehicle's overall performance and operating efficiency.

[0115] In some embodiments of the present disclosure, the vehicle control method further includes: broadcasting prompt information corresponding to the control instruction.

[0116] In the disclosed embodiments, the prompt information corresponding to the control instruction may be information associated with the control instruction, and may be used to convey the content, purpose, or related circumstances of the control instruction to a user (e.g., a driver or passenger). The prompt information may include the weather type and the content of the control instruction, and may be in the form of text, voice, or the like. The voice prompt associated with the instruction may be simultaneously broadcasted via an in-vehicle voice system (e.g., an in-vehicle smart speaker, an in-vehicle loudspeaker, etc.).

[0117] For example, if a control instruction for raising the temperature inside the car associated with snowy days is generated, the voice announcement can be "It's snowing heavily outside, turn up the temperature inside the car"; if a control instruction for turning on the wipers associated with rainy days is generated, the voice announcement can be "The current rainfall is heavy, turn on the wiper mode"; if a control instruction for adjusting the braking parameters associated with rainy days is generated, the voice announcement can be "The current rainfall is heavy, and the braking mode has been switched to wet road conditions".

[0118] Through the embodiments of the present disclosure, the user can clearly understand the control instructions that the vehicle is about to execute and the related reasons and intentions by broadcasting prompt information, thereby enhancing the user's understanding of the vehicle control logic and the user's sense of control over vehicle status changes, avoiding the user's tension or erroneous operations due to misunderstandings, thereby improving the user's driving safety and comfort.

[0119] Figure 4 This is a flow chart showing the association configuration of weather, identification conditions and control instructions in a vehicle control method according to some embodiments of the present disclosure. Figure 4 As shown, in some embodiments of the present disclosure, the vehicle control method may further include the following steps.

[0120] Step S410: Determine the weather to be configured, the identification conditions to be configured, and the control instructions to be configured.

[0121] Step S420: establishing an association relationship between the weather to be configured and the identification condition to be configured, wherein the identification condition to be configured is used to determine whether the weather to be configured matches the perception data.

[0122] Step S430: establishing an association relationship between the control instruction to be configured and at least one of the weather to be configured and the identification condition to be configured.

[0123] In the disclosed embodiments, users can select weather types to be included in system control based on actual application scenarios and needs. These weather types can include common severe weather conditions such as heavy rain, snow, and hail, as well as weather conditions unique to specific regions, or weather conditions that have a special impact on vehicle driving. For example, in foggy mountainous areas, dense fog can be listed as a weather type to be configured.

[0124] For each type of weather to be configured, corresponding identification conditions can be set based on its meteorological characteristics and impact on vehicle driving. These conditions can be set based on data collected by vehicle sensors. For example, conditions related to meteorological parameters such as temperature, humidity, light intensity, rainfall, wind speed, etc. can be set. Conditions related to environmental information such as camera images and radar detection data can also be set. Conditions related to the results obtained after the perception data is processed can also be set.

[0125] For example, in hail weather, the identification conditions to be configured can be set to detect granular objects of a certain size hitting the vehicle body, the ambient temperature is within a certain range, and the rainfall increases sharply in a short period of time.

[0126] The system can also determine the control commands required for the vehicle based on the potential impact of each type of weather condition. These commands are designed to ensure safe driving and comfortable riding in these conditions and can cover the operation of various vehicle systems, such as the powertrain, braking system, lighting system, and air conditioning system. For example, in the event of dusty weather, the control commands to be configured could include automatically closing windows, switching the air conditioning to recirculation mode, and reducing the vehicle's upper speed limit.

[0127] In the disclosed embodiment, at least two of the weather to be configured, the identification condition to be configured, and the control instruction to be configured may be associated with each other. Specifically, an association relationship may be established between the weather to be configured and the identification condition to be configured first, and then an association relationship may be established between the control instruction to be configured and at least one of the weather to be configured and the identification condition to be configured.

[0128] This association can be one-to-one, meaning that a specific set of identification conditions and control instructions corresponds to a specific weather type to be configured. Alternatively, it can be a one-to-many or many-to-one relationship to accommodate complex weather conditions and diverse control needs. For example, a rainstorm might correspond to multiple sets of identification conditions at different rainfall levels, with control instructions of varying intensities executed based on the rainfall. Alternatively, different levels of high temperatures could employ the same control strategy, creating a many-to-one association.

[0129] Through the disclosed embodiments, personalized customization is supported, allowing users to freely configure weather types, identification conditions, and control instructions according to different regions and usage scenarios, and establish associations between them. This allows the vehicle to accurately identify the weather and take appropriate measures based on preset rules, improving the vehicle's adaptability and response capabilities in complex environments and ensuring driving safety. Furthermore, through the configuration method provided by this embodiment, when it is necessary to add new weather types, optimize identification conditions, or adjust control instructions, only the corresponding parts need to be modified and configured, thereby reducing the cost of system upgrades and maintenance, improving the system's scalability and flexibility, and enabling the vehicle to continuously adapt to new weather environments and user needs.

[0130] Figure 5 This is a flow chart showing how to associate weather with identification conditions in a vehicle control method according to some embodiments of the present disclosure. Figure 4 As shown, in some embodiments of the present disclosure, the method of establishing the association relationship between the weather to be configured and the identification condition to be configured may include the following steps.

[0131] Step S510: determining at least one data configuration item associated with the weather to be configured; the data configuration item corresponds to the perception data or to an environment recognition result determined based on the perception data.

[0132] In the embodiment of the present disclosure, for the weather to be configured, relevant perception data or environmental recognition results can be determined according to its typical meteorological characteristics or impacts, and determined as data configuration items.

[0133] For example, on snowy days, data configuration items may include temperature data collected by temperature sensors, snowflake image features recognized by cameras, road snow reflection signals detected by lidar, etc.; on foggy days, data configuration items may include visibility sensor data, the degree of blur of camera images, etc.

[0134] Step S520: configuring data conditions based on the data configuration items.

[0135] In the disclosed embodiment, specific data judgment criteria can be set based on the characteristics of the data configuration items. For example, the temperature data configuration item for snowy days can be set to "temperature below 0°C," the recognition result data configuration item corresponding to radar sensor data (such as point cloud data) can be set to "snow is detected in the sky by radar," and the visibility data configuration item for foggy days can be set to "visibility is below a distance threshold (such as 300 meters or 500 meters)." This serves as the specific basis for determining whether the corresponding weather conditions have occurred.

[0136] Step S530: configuring the logical relationship between the various data conditions to generate the identification condition to be configured; wherein the logical relationship includes at least one of the following: an AND relationship, an OR relationship, and a NOT relationship.

[0137] In this disclosed embodiment, logical relationships such as "AND," "OR," and "NOT" can be configured based on the importance and interrelationship of various data conditions to weather identification. By integrating these configured data conditions and logical relationships, a complete set of identification conditions for a specific weather condition to be configured can be formed. These identification conditions form the criteria for determining whether the vehicle's current perception data matches the weather condition to be configured.

[0138] For example, when judging snowy days, you can set "temperature below 0℃" and "detection of snow in the sky by radar" as an "and" relationship, that is, only when both conditions are met at the same time can it be determined that it is a snowy day; for foggy days, you can set "visibility below 500 meters" and "camera image blur exceeds the threshold" as an "or" relationship, that is, meeting one of the conditions may trigger foggy day recognition.

[0139] Step S540: establishing an association relationship between the weather to be configured and the identification condition to be configured.

[0140] In the embodiment of the present disclosure, the generated identification conditions to be configured can be bound to the corresponding weather to be configured to complete the association between the two, so that the system can determine whether the corresponding weather occurs based on the identification conditions in subsequent operation.

[0141] Through the disclosed embodiments, by clarifying data configuration items, configuring specific data conditions, and rationally combining logical relationships, the characteristics of various weather conditions can be comprehensively and meticulously described. This allows the vehicle to comprehensively consider multiple relevant factors when determining the weather, avoiding misjudgments or missed judgments caused by single data or simple judgment methods, greatly improving the accuracy and reliability of weather recognition. Furthermore, through the flexible configuration of data conditions and logical relationships, this embodiment can adapt to various complex actual weather conditions, improving the vehicle's adaptability in complex environments.

[0142] In some embodiments of the present disclosure, the target weather includes snowy weather; wherein, in response to the perception data matching the target weather, generating a control instruction associated with the target weather may include: in response to the perception data satisfying a snowy weather identification condition associated with the snowy weather, generating a snowy weather control instruction associated with the snowy weather.

[0143] In the disclosed embodiment, snowy weather can be identified and control instructions can be generated based on the identified snowy weather conditions. These instructions can be designed to address the impact of snow on the vehicle and can cover the operation of multiple vehicle systems.

[0144] In some embodiments of the present disclosure, the snowy weather control instructions include at least one of the following: starting the vehicle body heating module to heat the vehicle's sensors and / or peripheral equipment; adjusting the braking parameters of the chassis system to enhance braking sensitivity and / or enhance the strength of the anti-lock braking system; starting the wiper module and / or the defogger module; displaying effect images corresponding to snowy weather and / or prompt information corresponding to snowy weather through the cockpit display module.

[0145] In the disclosed embodiment, activating the vehicle body heating module can heat the vehicle's sensors (such as radars and cameras) and peripheral devices (wipers, rearview mirrors, door handles, etc.) to achieve snow removal, defogging, decontamination, and / or cleanliness of the vehicle body. For example, in rainy or snowy scenes, if rain and snow remain on the camera, the camera's built-in heating wire can be used to heat the rain and snow to melt or evaporate it, thereby achieving snow removal, decontamination, and / or keeping the device clean, preventing the normal operation of the device from being affected by low-temperature snow accumulation, ice, fog, etc., thereby ensuring the accuracy of sensor data collection and / or the functionality of the device.

[0146] Adjusting the braking parameters of the chassis system may include adjusting the parameters of the braking system, including increasing the brake sensitivity, enhancing the strength of the anti-lock braking system, etc., so that the vehicle can brake more effectively on snowy and slippery roads and reduce the risk of skidding and loss of control.

[0147] Starting the wiper module can clear the snowflakes on the windshield in snowy scenes. The defogger module can clear the fog by heating the windows or adjusting the air conditioning mode to ensure clear vision for the driver.

[0148] The corresponding content is displayed through the cockpit display module, which may include displaying effect images corresponding to snowy days (such as snowflake animations) on the instrument panel, central control screen and other interfaces, and may also include displaying prompt information ("The road is slippery, drive carefully") to remind the driver to pay attention to driving safety in snowy days.

[0149] Through the disclosed embodiments, the vehicle can be controlled from multiple aspects to automatically adapt to snowy scenes, ensuring that the vehicle's perception system and some key components can continue to work stably, providing reliable data support and functional guarantees for the vehicle's safe driving, and creating a driving atmosphere that is more in line with the actual environment for the driver.

[0150] In some embodiments of the present disclosure, the sensory data includes at least one of the following: temperature sensor data, wiper sensor data, chassis sensor data, laser sensor data, and visual sensor data. The sensory data meeting the snowy weather recognition condition associated with the snowy weather may include: the sensory data meeting an air condition and / or a ground condition.

[0151] In the embodiment of the present disclosure, the overall judgment logic for snowy days may include determining whether the perception data meets the aerial conditions and / or ground conditions; wherein, only one set of conditions (aerial conditions or ground conditions) may be met, or both may be met, and it can be determined that the perception data meets the snowy day recognition conditions, thereby improving the flexibility and accuracy of snowy day recognition.

[0152] In some embodiments of the present disclosure, the aerial conditions include at least one of the following: an environmental recognition result detected based on visual sensing data and / or laser sensing data is that there are snowy features in the air; determining based on wiper sensor data that the wipers are turned on and the temperature sensor data is lower than a temperature threshold; an environmental recognition result detected based on visual sensing data and / or laser sensing data is that there are snowy features in the air and the temperature sensor data is lower than a temperature threshold.

[0153] In the disclosed embodiments, an environmental image can be captured using a visual sensor, and the image content can be analyzed using a trained first snow feature analysis model to detect whether snow features (such as falling snowflakes, a gloomy sky, and a cloud distribution typical of snowy days) are present in the air as an environmental recognition result. Alternatively, point cloud data can be captured using laser sensor data, and the point cloud data can be analyzed using a trained second snow feature analysis model to detect whether snow features (such as falling snowflakes, a gloomy sky, and a cloud distribution typical of snowy days) are present in the air as an environmental recognition result. If the presence of snow features is detected in the air based on the visual sensor data and / or the laser sensor data, it can be determined that the air conditions for snowy days are currently met.

[0154] If the wiper sensor detects that the wipers are on and the ambient temperature measured by the temperature sensor is lower than a preset temperature threshold (such as 0°C), the two can be combined as a basis for determining whether the conditions for flying in the sky under snow are met.

[0155] If the visual sensor data and / or laser sensor data detects snowy features in the air, and the temperature sensor indicates the ambient temperature is below a threshold (e.g., 0°C), then the airborne conditions for snowy conditions can be determined. Combining the laser sensor's detection results with the low-temperature condition can enhance the reliability of the snowy determination.

[0156] In some embodiments of the present disclosure, the ground conditions include at least one of the following: the environmental recognition result detected based on visual sensing data and / or laser sensing data is that there are snowy features on the ground; the environmental recognition result detected based on visual sensing data and / or laser sensing data is that there are snowy features on the ground and the temperature sensing data is lower than a temperature threshold; it is determined based on chassis sensing data that the road surface is slippery and the temperature sensing data is lower than a temperature threshold.

[0157] In the disclosed embodiments, a visual sensor can be used to capture environmental images, and the image content can be analyzed using a trained third snow feature analysis model to detect whether snow features (such as snow accumulation) are present on the ground as an environmental recognition result. Alternatively, laser sensor data can be used to capture point cloud data, and the trained fourth snow feature analysis model can be used to analyze the point cloud data to detect whether snow features (such as snow accumulation) are present on the ground as an environmental recognition result. If the presence of snow features is detected on the ground based on the visual sensor data and / or the laser sensor data, it can be determined that the ground conditions for snow are currently met.

[0158] If the presence of snowy features on the ground is detected based on the visual sensing data and / or laser sensing data, and the temperature sensor shows that the ambient temperature is lower than a threshold value (such as 0°C), it can be determined that the ground conditions for snowing are currently met.

[0159] If the chassis sensor determines that the road surface is slippery by monitoring parameters such as the friction between the tire and the road surface and chassis vibration, and the temperature sensor shows that the ambient temperature is lower than a threshold (such as 0°C), it can be determined that the current ground conditions meet the snowy conditions.

[0160] The disclosed embodiments can more comprehensively and accurately capture snowy features by integrating multiple types of sensor data and setting snowy conditions from both aerial and ground perspectives. The different sensor data types complement and validate each other, reducing the risk of misjudgment or missed detection by a single sensor and improving the accuracy and reliability of snowy recognition.

[0161] It should be noted that the above figures are merely illustrative of the processes included in the methods according to some embodiments of the present disclosure and are not intended to be limiting. It is readily understood that the processes illustrated in the above figures do not indicate or limit the temporal order of these processes. Furthermore, it is readily understood that these processes may be executed synchronously or asynchronously, for example, in multiple modules.

[0162] The following are embodiments of the apparatus disclosed herein, which can be used to implement the method embodiments disclosed herein. For details not disclosed in the apparatus embodiments disclosed herein, please refer to the method embodiments disclosed herein.

[0163] Figure 6 FIG. 1 is a block diagram of a vehicle control device according to some embodiments of the present disclosure. Figure 6 The device includes: an acquisition unit 601, an instruction generation unit 602, and a control unit 603.

[0164] The acquisition unit 601 is used to acquire the vehicle's perception data of the environment; the instruction generation unit 602 is used to generate a control instruction associated with the target weather in response to the perception data matching the target weather; the control unit 603 is used to adjust the working state of the vehicle according to the control instruction.

[0165] In some embodiments of the present disclosure, the perception data includes at least one of the following: vehicle sensor data, vehicle status data, and received external environment data.

[0166] In some embodiments of the present disclosure, the instruction generation unit 602 is further configured to: in response to the perception data satisfying a target recognition condition associated with the target weather, determine that the perception data matches the target weather.

[0167] In some embodiments of the present disclosure, the perception data satisfies the target recognition conditions associated with the target weather, including: the perception data satisfies the perception conditions in the target recognition conditions; and / or, the environment recognition results detected based on the perception data meet the environment recognition conditions in the target recognition conditions; wherein, the environment recognition results include: obtained by processing the perception data through a neural network model.

[0168] In some embodiments of the present disclosure, the target weather includes at least one of the following: snowy weather, rainy weather, foggy weather, sandstorm weather, and high temperature weather.

[0169] In some embodiments of the present disclosure, the control instructions include at least one of the following: starting the vehicle temperature control module; adjusting the braking parameters of the chassis system; starting the wiper module; starting the defogger module; updating the content in the cabin display module; starting the cabin interior atmosphere adjustment module; and pushing music.

[0170] In some implementations, the control unit 603 is further configured to: broadcast prompt information corresponding to the control instruction.

[0171] In some embodiments of the present disclosure, the vehicle control device also includes a configuration unit 604, which is used to: determine the weather to be configured, the identification condition to be configured, and the control instruction to be configured; establish an association relationship between the weather to be configured and the identification condition to be configured, wherein the identification condition to be configured is used to determine whether the weather to be configured matches the perception data; and establish an association relationship between the control instruction to be configured and at least one of the weather to be configured and the identification condition to be configured.

[0172] In some embodiments of the present disclosure, the configuration unit 604 establishes an association relationship between the weather to be configured and the identification condition to be configured, including: determining at least one data configuration item associated with the weather to be configured; the data configuration item corresponds to the perception data or the environment identification result determined based on the perception data; configuring the data condition based on the data configuration item; configuring the logical relationship between each of the data conditions to generate the identification condition to be configured; wherein the logical relationship includes at least one of the following: an AND relationship, an OR relationship, and a NOT relationship; establishing an association relationship between the weather to be configured and the identification condition to be configured.

[0173] In some embodiments of the present disclosure, the target weather includes snowy weather; wherein, the instruction generation unit 602 generates control instructions associated with the target weather in response to the perception data matching the target weather, including: generating snowy weather control instructions associated with the snowy weather in response to the perception data satisfying the snowy weather identification condition associated with the snowy weather; wherein, the snowy weather control instructions include at least one of the following: starting the body heating module to heat the vehicle's sensors and / or peripheral equipment; adjusting the braking parameters of the chassis system to enhance the braking sensitivity and / or enhance the strength of the anti-lock braking system; starting the wiper module and / or the defogger module; displaying the effect image corresponding to the snowy weather and / or the prompt information corresponding to the snowy weather through the cockpit display module.

[0174] In some embodiments of the present disclosure, the perception data includes at least one of the following: temperature sensor data, wiper sensor data, chassis sensor data, laser sensor data and visual sensor data; the perception data satisfies the snowy day identification conditions associated with the snowy day, including: the perception data satisfies the air condition and / or the ground condition; wherein the air condition includes at least one of the following: the environmental recognition result detected based on the visual sensor data and / or the laser sensor data is that there are snowy day features in the air; it is determined according to the wiper sensor data that the wiper is turned on and the temperature sensor data is lower than the temperature threshold; the environmental recognition result detected based on the visual sensor data and / or the laser sensor data is that there are snowy day features in the air and the temperature sensor data is lower than the temperature threshold; the ground condition includes at least one of the following: the environmental recognition result detected based on the visual sensor data and / or the laser sensor data is that there are snowy day features on the ground; the environmental recognition result detected based on the visual sensor data and / or the laser sensor data is that there are snowy day features on the ground and the temperature sensor data is lower than the temperature threshold; it is determined according to the chassis sensor data that the road surface is slippery and the temperature sensor data is lower than the temperature threshold.

[0175] Regarding the apparatus in the above embodiment, the specific manner in which each module performs operations has been described in detail in the embodiment of the method, and will not be elaborated here.

[0176] Figure 7 FIG2 is a block diagram illustrating an apparatus 700 for vehicle control according to some embodiments of the present disclosure. For example, the apparatus 700 may be a mobile phone, a computer, a digital broadcast terminal, a messaging device, a game console, a tablet device, a medical device, a fitness device, a personal digital assistant, etc.

[0177] Reference Figure 7, apparatus 700 may include one or more of the following components: a processing component 702 , a memory 704 , a power component 706 , a multimedia component 708 , an audio component 710 , an input / output (I / O) interface 712 , a sensor component 714 , and a communication component 716 .

[0178] The processing component 702 generally controls the overall operation of the device 700, such as operations associated with display, phone calls, data communications, camera operation, and recording operations. The processing component 702 may include one or more processors 720 to execute instructions to perform all or part of the steps of the above-described method. In addition, the processing component 702 may include one or more modules to facilitate interaction between the processing component 702 and other components. For example, the processing component 702 may include a multimedia module to facilitate interaction between the multimedia component 708 and the processing component 702.

[0179] The memory 704 is configured to store various types of data to support operations on the device 700. Examples of such data include instructions for any application or method operating on the device 700, contact data, phone book data, messages, pictures, videos, etc. The memory 704 can be implemented by any type of volatile or non-volatile storage device, or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic memory, flash memory, magnetic disk, or optical disk.

[0180] The power component 706 provides power to the various components of the device 700. The power component 706 may include a power management system, one or more power supplies, and other components associated with generating, managing, and distributing power to the device 700.

[0181] The multimedia component 708 includes a screen that provides an output interface between the device 700 and the user. In some embodiments, the screen may include a liquid crystal display (LCD) and a touch panel (TP). If the screen includes a touch panel, the screen can be implemented as a touch screen to receive input signals from the user. The touch panel includes one or more touch sensors to sense touches, slides, and gestures on the touch panel. The touch sensor can not only sense the boundaries of the touch or slide action, but also detect the duration and pressure associated with the touch or slide operation. In some embodiments, the multimedia component 708 includes a front camera and / or a rear camera. When the device 700 is in an operating mode, such as a shooting mode or a video mode, the front camera and / or the rear camera can receive external multimedia data. Each front camera and rear camera can be a fixed optical lens system or have focal length and optical zoom capabilities.

[0182] The audio component 710 is configured to output and / or input audio signals. For example, the audio component 710 includes a microphone (MIC), which is configured to receive external audio signals when the device 700 is in an operating mode, such as a call mode, a recording mode, and a voice recognition mode. The received audio signal can be further stored in the memory 704 or transmitted via the communication component 716. In some embodiments, the audio component 710 also includes a speaker for outputting audio signals.

[0183] I / O interface 712 provides an interface between processing component 702 and peripheral interface modules, such as a keyboard, click wheel, buttons, etc. These buttons may include but are not limited to: a home button, volume buttons, a start button, and a lock button.

[0184] The sensor assembly 714 includes one or more sensors for providing various aspects of the status assessment of the device 700. For example, the sensor assembly 714 can detect the open / closed state of the device 700, the relative positioning of components, such as the display and keypad of the device 700. The sensor assembly 714 can also detect changes in the position of the device 700 or a component of the device 700, the presence or absence of user contact with the device 700, the orientation or acceleration / deceleration of the device 700, and temperature changes of the device 700. The sensor assembly 714 may include a proximity sensor configured to detect the presence of nearby objects without any physical contact. The sensor assembly 714 may also include an optical sensor, such as a CMOS or CCD image sensor, for use in imaging applications. In some embodiments, the sensor assembly 714 may also include an accelerometer, a gyroscope sensor, a magnetic sensor, a pressure sensor, or a temperature sensor.

[0185] The communication component 716 is configured to facilitate wired or wireless communication between the device 700 and other devices. The device 700 can access a wireless network based on a communication standard, such as WiFi, 3G, 4G, 5G, other communication standards, or a combination thereof. In some embodiments of the present disclosure, the communication component 716 receives a broadcast signal or broadcast-related information from an external broadcast management system via a broadcast channel. In some embodiments of the present disclosure, the communication component 716 also includes a near field communication (NFC) module to facilitate short-range communication. For example, the NFC module can be implemented based on radio frequency identification (RFID) technology, infrared data association (IrDA) technology, ultra-wideband (UWB) technology, Bluetooth (BT) technology and other technologies.

[0186] In some embodiments of the present disclosure, the apparatus 700 may be implemented by one or more application-specific integrated circuits (ASICs), digital signal processors (DSPs), digital signal processing devices (DSPDs), programmable logic devices (PLDs), field programmable gate arrays (FPGAs), controllers, microcontrollers, microprocessors, or other electronic components to perform the above-described methods.

[0187] In some embodiments of the present disclosure, a non-transitory computer-readable storage medium including instructions is further provided, such as a memory 704 including instructions, and the instructions can be executed by the processor 720 of the apparatus 700 to perform the above method. For example, the non-transitory computer-readable storage medium can be a ROM, a random access memory (RAM), a CD-ROM, a magnetic tape, a floppy disk, an optical data storage device, etc.

[0188] A vehicle may be a hybrid vehicle, a non-hybrid vehicle, an electric vehicle, a fuel cell vehicle, or other types of vehicles. The vehicle may be an assisted driving vehicle, a semi-assisted driving vehicle, or a non-assisted driving vehicle.

[0189] A vehicle may include various subsystems, such as an infotainment system, a perception system, a decision-making and control system, a drive system, and a computing platform. A vehicle may also include more or fewer subsystems, and each subsystem may include multiple components. Furthermore, each subsystem and each component in the vehicle may be interconnected via wired or wireless means.

[0190] In some embodiments, the infotainment system may include a communication system, an entertainment system, and a navigation system, among others.

[0191] The perception system may include several sensors for sensing information about the vehicle's surrounding environment. For example, the perception system may include a global positioning system (GPS, BeiDou, or other positioning systems), an inertial measurement unit (IMU), lidar, millimeter-wave radar, ultrasonic radar, and a camera.

[0192] The decision-making control system may include a computing system, a vehicle controller, a steering system, a throttle, and a braking system.

[0193] The drive system may include components that provide powered motion for the vehicle. In one embodiment, the drive system may include an engine, an energy source, a transmission system, and wheels. The engine may be one or a combination of an internal combustion engine, an electric motor, and an air compression engine. The engine is capable of converting energy provided by the energy source into mechanical energy.

[0194] Some or all functions of the vehicle are controlled by a computing platform. The computing platform may include at least one processor and a memory, and the processor may execute instructions stored in the memory.

[0195] The processor may be any conventional processor, such as a commercially available CPU. The processor may also include a graphics processing unit (GPU), a field programmable gate array (FPGA), a system on chip (SoC), an application specific integrated circuit (ASIC), or a combination thereof.

[0196] The memory may be implemented by any type of volatile or non-volatile memory device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic memory, flash memory, magnetic disk or optical disk.

[0197] In addition to instructions, the memory can also store data, such as road maps, route information, vehicle location, direction, speed, etc. The data stored in the memory can be used by the computing platform.

[0198] In an embodiment of the present disclosure, a processor may execute instructions to complete all or part of the steps of the aforementioned vehicle control method. The vehicle control method includes: acquiring vehicle perception data of the environment; generating control instructions associated with the target weather in response to the perception data matching the target weather; and adjusting the operating state of the vehicle according to the control instructions.

[0199] A non-transitory computer-readable storage medium, when instructions in the storage medium are executed by a processor of a mobile terminal, enables the mobile terminal to execute a vehicle control method, the method comprising: obtaining vehicle perception data of the environment; in response to the perception data matching target weather, generating control instructions associated with the target weather; and adjusting the operating state of the vehicle according to the control instructions.

[0200] Other embodiments of the present disclosure will readily occur to those skilled in the art after considering the specification and practicing the invention disclosed herein. This application is intended to cover any variations, uses, or adaptations of the present disclosure that follow the general principles of the present disclosure and include common knowledge or customary techniques in the art not disclosed herein. The description and examples are to be considered as exemplary only, with the true scope and spirit of the present disclosure being indicated by the following claims.

[0201] It should be understood that the present disclosure is not limited to the exact structures that have been described above and shown in the drawings, and that various modifications and changes can be made without departing from the scope thereof. The scope of the present disclosure is limited only by the appended claims.

Claims

1. A vehicle control method, characterized in that: include: Obtain vehicle perception data of the environment; In response to the sensing data matching the target weather, generating a control instruction associated with the target weather; The operating state of the vehicle is adjusted according to the control instruction.

2. The method according to claim 1, characterized in that The perception data includes at least one of the following: vehicle sensor data, vehicle status data, and received external environment data.

3. The method according to claim 1, characterized in that The sensing data is matched with the target weather, including: In response to the perception data satisfying a target recognition condition associated with the target weather, it is determined that the perception data matches the target weather.

4. The method according to claim 3, characterized in that The perception data satisfies the target recognition condition associated with the target weather, including: The perception data satisfies the perception condition in the target recognition condition; and / or, The environment recognition result detected according to the perception data satisfies the environment recognition condition in the target recognition condition; wherein, the environment recognition result includes: obtained by processing the perception data through a neural network model.

5. The method according to claim 1, wherein The target weather includes at least one of the following: snowy weather, rainy weather, foggy weather, sandstorm weather, and high temperature weather.

6. The method according to claim 1, characterized in that The control instruction includes at least one of the following: Start the vehicle temperature control module; Adjust the braking parameters of the chassis system; Start the wiper module; Start the defogger module; Update the content in the cockpit display module; Start the cabin interior atmosphere adjustment module; Push music.

7. The method according to claim 1 or 6, characterized in that The method further comprises: The prompt information corresponding to the control instruction is broadcasted.

8. The method according to claim 1, characterized in that The method further comprises: Determine the weather to be configured, the identification conditions to be configured, and the control instructions to be configured; Establishing an association relationship between the weather to be configured and the identification condition to be configured, wherein the identification condition to be configured is used to determine whether the weather to be configured matches the perception data; An association relationship is established between the control instruction to be configured and at least one of the weather to be configured and the identification condition to be configured.

9. The method according to claim 8, characterized in that Establishing an association relationship between the weather to be configured and the identification condition to be configured includes: Determining at least one data configuration item associated with the weather to be configured; the data configuration item corresponds to the perception data or an environment recognition result determined based on the perception data; Based on the data configuration items, configure data conditions; Configuring the logical relationship between each of the data conditions to generate the identification condition to be configured; wherein the logical relationship includes at least one of the following: an AND relationship, an OR relationship, and a NOT relationship; Establish an association relationship between the weather to be configured and the identification condition to be configured.

10. The method according to claim 1, characterized in that The target weather includes snow; wherein, in response to the sensing data matching the target weather, generating a control instruction associated with the target weather includes: In response to the perception data satisfying a snowy day identification condition associated with the snowy day, generating a snowy day control instruction associated with the snowy day; The snow control instruction includes at least one of the following: Activate the vehicle body heating module to heat the vehicle's sensors and / or peripheral devices; Adjusting the braking parameters of the chassis system to enhance brake sensitivity and / or increase the strength of the anti-lock braking system; Start the wiper module and / or the defogger module; The cockpit display module displays effect images corresponding to snowy weather and / or prompt information corresponding to snowy weather.

11. The method according to claim 10, characterized in that The perception data includes at least one of the following: temperature sensing data, wiper sensing data, chassis sensing data, laser sensing data, and visual sensing data; The perception data satisfies a snowy day identification condition associated with the snowy day, including: the perception data satisfies an air condition and / or a ground condition; The air condition includes at least one of the following: an environmental recognition result detected based on visual sensor data and / or laser sensor data is that snowy features are present in the air; a determination based on wiper sensor data that wipers are on and temperature sensor data is lower than a temperature threshold; an environmental recognition result detected based on visual sensor data and / or laser sensor data is that snowy features are present in the air and temperature sensor data is lower than a temperature threshold; The ground conditions include at least one of the following: the environmental recognition result detected based on visual sensing data and / or laser sensing data is that there are snowy features on the ground; the environmental recognition result detected based on visual sensing data and / or laser sensing data is that there are snowy features on the ground and the temperature sensing data is lower than a temperature threshold; it is determined based on chassis sensing data that the road surface is slippery and the temperature sensing data is lower than a temperature threshold.

12. A vehicle control device, characterized in that: include: An acquisition unit, used to acquire the vehicle's perception data of the environment; an instruction generating unit, configured to generate a control instruction associated with the target weather in response to the sensing data matching the target weather; A control unit is used to adjust the working state of the vehicle according to the control instruction.

13. The device according to claim 12, characterized in that The control instruction includes at least one of the following: Start the vehicle temperature control module; Adjust the braking parameters of the chassis system; Start the wiper module; Start the defogger module; Update the content in the cockpit display module; Start the cabin interior atmosphere adjustment module; Push music.

14. The device according to claim 12, characterized in that The perception data includes at least one of the following: vehicle sensor data, vehicle status data, and received external environment data.

15. The device according to claim 12, characterized in that The target weather includes at least one of the following: snowy weather, rainy weather, foggy weather, sandstorm weather, and high temperature weather.

16. A vehicle, characterized in that: include: processor; a memory for storing processor-executable instructions; The processor is configured to implement the steps of the method according to any one of claims 1 to 11.

17. A non-transitory computer-readable storage medium, when instructions in the storage medium are executed by a processor of a mobile terminal, enables the mobile terminal to perform the steps of the method according to any one of claims 1 to 11.

18. A computer program product comprising a computer program, characterized in that When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 11 are implemented.

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