Vehicle lamp control method, device and equipment

Abstract

The invention discloses an automobile lamp control method, device and equipment, and relates to the technical field of automobiles, the method comprises the following steps: collecting environment information in real time, the environment information being used for describing the environment of a road where a first automobile is located; predicting road condition information based on the environment information, wherein the road condition information is used for indicating road conditions and illumination conditions of a first road section which is not passed by on the driving path; the road condition information is analyzed, vehicle lamp scene demand information in the first road section is obtained, and the vehicle lamp scene demand information is used for describing the situation that the first vehicle has a vehicle lamp control demand in the first road section; generating a vehicle lamp control instruction based on the vehicle lamp scene demand information and the environment information, and controlling the vehicle lamp of the first vehicle based on the vehicle lamp control instruction. The vehicle lamp control mode can be decided only at the vehicle end, information does not need to be transmitted from the vehicle end to the cloud end for decision making, and the decision making efficiency and the data safety are improved.

Description

Technical Field

[0001] The embodiments of the present application relate to the field of automobile technology, and in particular to a method, device, and equipment for controlling vehicle lights. Background Art

[0002] With the development of autonomous driving technology, headlight control has become an important function. Automatically turning on the headlights in road conditions with poor lighting conditions and low visibility can greatly improve driving safety and convenience.

[0003] In related technologies, headlight control mainly relies on information collection and cloud-based decision-making processes. The vehicle side collects vehicle environmental information through sensors and other devices, and transmits the information to the cloud. The cloud side analyzes and makes decisions based on the environmental information to generate control instructions, and transmits the control instructions back to the vehicle side, thereby achieving precise control of the headlights.

[0004] However, there is a risk of information leakage during the transmission process between the vehicle and the cloud, and the time-consuming data transmission will also affect decision-making efficiency, thereby increasing driving risks. Summary of the invention

[0005] The embodiments of the present application provide a vehicle light control method, device, and apparatus, which can make decisions on the vehicle light control mode only on the vehicle side, without transmitting information from the vehicle side to the cloud for decision making, thereby improving decision efficiency and data security. The technical solution is as follows:

[0006] In one aspect, a vehicle light control method is provided, the method comprising:

[0007] Collecting environmental information in real time, where the environmental information is used to describe the environment of the road where the first vehicle is located;

[0008] Predicting road condition information based on the environmental information, the road condition information being used to indicate road conditions and lighting conditions of a first road section that has not been traveled on the driving path;

[0009] Analyze the road condition information to obtain vehicle light scene requirement information in the first road section, where the vehicle light scene requirement information is used to describe vehicle light control requirements of the first vehicle in the first road section;

[0010] A headlight control instruction is generated based on the headlight scene requirement information and the environmental information, and the headlight of the first vehicle is controlled based on the headlight control instruction.

[0011] In another aspect, a vehicle light control device is provided, the device comprising:

[0012] A collection module, used for collecting environmental information in real time, where the environmental information is used to describe the environment of the road where the first vehicle is located;

[0013] A prediction module, used to predict road condition information based on the environmental information, where the road condition information is used to indicate the road condition and lighting condition of a first road section that has not been traveled on the driving path;

[0014] an analysis module, configured to analyze the road condition information to obtain vehicle light scene requirement information within the first road section, wherein the vehicle light scene requirement information is used to describe vehicle light control requirements of the first vehicle within the first road section;

[0015] A control module is used to generate a headlight control instruction based on the headlight scene requirement information and the environmental information, and control the headlight of the first vehicle based on the headlight control instruction.

[0016] In an optional embodiment, the illumination condition includes illumination values ​​of a plurality of position points in the first road section;

[0017] The analysis module is used to determine that the vehicle light scene requirement information includes turning on the vehicle lights at the first position point or keeping the vehicle lights on in response to the illumination value corresponding to the first position point in the illumination condition being lower than a preset first illumination threshold; or, in response to the illumination value corresponding to the second position point in the illumination condition being higher than a preset second illumination threshold, determine that the vehicle light scene requirement information includes turning off the vehicle lights at the second position point or keeping the vehicle lights off; or, in response to the illumination value corresponding to the third position point in the illumination condition being higher than the first illumination threshold and lower than the second illumination threshold, determine that the vehicle light scene requirement information includes keeping the vehicle lights unchanged at the third position point.

[0018] In an optional embodiment, the headlight scene requirement information further includes headlight brightness information, and the headlight brightness information is used to indicate the headlight brightness when the headlight of the first vehicle is turned on;

[0019] The analysis module is further used to calculate a first difference between the illumination value corresponding to the first position point and the first illumination threshold; and obtain corresponding vehicle light brightness information based on the first difference.

[0020] In an optional embodiment, the road condition information includes lighting conditions, weather types and road types corresponding to a plurality of location points in the first road section;

[0021] The analysis module is further used to obtain a preset headlight scene mapping table, wherein the headlight scene mapping table includes a first mapping relationship between a plurality of lighting conditions and a plurality of headlight control scenes, a second mapping relationship between a plurality of weather types and the plurality of headlight control scenes, and a third mapping relationship between a plurality of front road types and the plurality of headlight control scenes; based on the road condition information, the target headlight control scenes corresponding to the plurality of location points are determined from the headlight scene mapping table to obtain the headlight scene demand information within the first road section.

[0022] In an optional embodiment, the control module is also used to update the environmental information in real time to obtain the environmental information at the current moment, wherein the environmental information at the current moment includes the vehicle position of the first vehicle; wherein the headlight scene requirement information includes at least one position point in the first road section where there is a headlight control requirement; when the preset instruction generation conditions are met between the at least one position point and the vehicle position of the first vehicle, the headlight control instruction is generated based on the headlight scene requirement information.

[0023] In an optional embodiment, the control module is also used to calculate the i-th distance between the vehicle position of the first vehicle and the i-th position point among the at least one position point; i is a positive integer; in response to the i-th distance being less than or equal to a preset distance threshold, determine that the distance between the i-th position point and the vehicle position of the first vehicle meets the preset instruction generation conditions; wherein the headlight scene requirement information includes a control type for headlight control of the at least one position point, and the control type includes turning off the headlights, turning on the headlights, and keeping the headlights unchanged; based on the control type for headlight control of the i-th position point in the headlight scene requirement information, generate a headlight control instruction corresponding to the i-th position point.

[0024] In an optional embodiment, the road condition information includes a road type of the first road section and illumination values ​​of a plurality of position points in the first road section;

[0025] The analysis module is further used to obtain a preset coefficient table, which includes safety coefficients corresponding to multiple road types, and the value of the safety coefficient is used to describe the safety level of a vehicle when traveling on different types of roads, and the value of the safety coefficient is positively correlated with the safety level; a first coefficient is obtained from the coefficient table based on the road type of the first road section, and the first coefficient is used to indicate the safety level of the first vehicle when traveling in the first road section; a plurality of values ​​corresponding to the plurality of position points are obtained based on the product of the illumination values ​​of the plurality of position points and the first coefficient; and a headlight scene corresponding to the plurality of position points is determined based on the plurality of values ​​to obtain the headlight scene requirement information.

[0026] In an optional embodiment, the analysis module is further used to determine at least one position point corresponding to the at least one value in response to the presence of at least one value among the multiple values ​​that meets the preset headlight turning-on requirement, and to determine that the headlight scene requirement information includes turning on the headlights or keeping the headlights on at the at least one position point.

[0027] On the other hand, a computer device is provided, which includes a processor and a memory, wherein the memory stores at least one instruction, at least one program, a code set or an instruction set, and the at least one instruction, the at least one program, the code set or the instruction set is loaded and executed by the processor to implement a vehicle light control method as described in any of the above-mentioned embodiments of the present application.

[0028] On the other hand, a computer-readable storage medium is provided, in which at least one instruction, at least one program, a code set or an instruction set is stored. The at least one instruction, the at least one program, the code set or the instruction set is loaded and executed by a processor to implement a vehicle light control method as described in any of the above-mentioned embodiments of the present application.

[0029] On the other hand, a computer program product or a computer program is provided, the computer program product or the computer program includes computer instructions, the computer instructions are stored in a computer-readable storage medium. A processor of a computer device reads the computer instructions from the computer-readable storage medium, and the processor executes the computer instructions, so that the computer device executes any of the vehicle light control methods described in the above embodiments.

[0030] The beneficial effects brought by the technical solution provided by the embodiment of the present application include at least:

[0031] By collecting environmental information, it is possible to predict the road conditions and lighting conditions in the road section that the first vehicle is about to pass, determine whether there is a scene in the road section that requires the lights to be turned on or off, provide sufficient time for turning the lights on and off in advance, and realize automatic control of the lights. The information collection process and the process of generating the light control instructions are all executed by the vehicle side. There is no need to send the collected information to the cloud for analysis and decision-making by the cloud, and then the cloud returns the decision results to the vehicle side to control the lights. This can reduce the risk of leakage in the information transmission process, improve the security of information data, reduce the transmission time in the process of information and decision results transmission, and improve decision-making efficiency and efficiency of controlling lights. In the face of extreme situations, the lights can be automatically turned on and off in time when the road conditions, lighting conditions, etc. change, to ensure the safety of the driver during driving. BRIEF DESCRIPTION OF THE DRAWINGS

[0032] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0033] Figure 1 is a schematic diagram of a vehicle light control system provided by an exemplary embodiment of the present application;

[0034] Figure 2 This is an exemplary embodiment of the present application based on Figure 1 A schematic diagram showing the interaction mode of the vehicle light control system;

[0035] Figure 3 is a flow chart of a vehicle light control method provided by an exemplary embodiment of the present application;

[0036] Figure 4 is a structural block diagram of a vehicle light control device provided by an exemplary embodiment of the present application;

[0037] Figure 5 It is a structural block diagram of a computer device provided by an exemplary embodiment of the present application. DETAILED DESCRIPTION

[0038] In order to make the objectives, technical solutions and advantages of the present application clearer, the implementation methods of the present application will be further described in detail below with reference to the accompanying drawings.

[0039] Exemplary embodiments will be described in detail herein, examples of which are shown in the accompanying drawings. When the following description refers to the drawings, the same numbers in different drawings represent the same or similar elements unless otherwise indicated. The implementations described in the following exemplary embodiments do not represent all implementations consistent with the present application. Instead, they are merely examples of devices and methods consistent with some aspects of the present application as detailed in the appended claims.

[0040] The terms used in this application are for the purpose of describing specific embodiments only and are not intended to limit this application. The singular forms of "a", "said" and "the" used in this application and the appended claims are also intended to include plural forms unless the context clearly indicates other meanings. It should also be understood that the term "and / or" used herein refers to and includes any or all possible combinations of one or more associated listed items.

[0041] It should be noted that the information and data involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of relevant data must comply with relevant laws, regulations and standards of relevant countries and regions.

[0042] It should be understood that, although the terms first, second, etc. may be used in the present application to describe various information, these information should not be limited to these terms. These terms are only used to distinguish the same type of information from each other. For example, without departing from the scope of the present application, the first parameter may also be referred to as the second parameter, and similarly, the second parameter may also be referred to as the first parameter. Depending on the context, the word "if" as used herein may be interpreted as "at the time of" or "when" or "in response to determining".

[0043] First, a brief introduction is given to the terms involved in the embodiments of this application:

[0044] Global Positioning System (GPS): is a satellite-based radio navigation system. It consists of a space part (satellite constellation), a ground control part, and a user equipment part (such as a car GPS receiver). The satellite constellation transmits radio signals containing timestamps, satellite positions, and other information to the surface of the earth. After receiving signals from multiple satellites, the car GPS receiver calculates the distance to each satellite based on the signal propagation time (through the relationship between the speed of light and the signal propagation time), and then uses the triangulation principle to determine the three-dimensional position of the vehicle on the earth (longitude, latitude, and altitude).

[0045] The main functions of GPS include positioning navigation, speed and track recording. In the in-vehicle navigation system, GPS can accurately determine the location of the vehicle and display it on an electronic map. The driver can follow the navigation prompts and drive along the preset route. For example, when the driver enters the destination, the navigation system combines GPS positioning information and map data to provide the driver with the best driving route, including turn prompts, estimated arrival time, etc.

[0046] In this application, the road condition information of the road section that will be passed in the future can be predicted based on the current position and driving trajectory of the vehicle provided by GPS.

[0047] Electronic Control Unit (ECU): ECU is the core component of the automotive electronic control system. It receives signals from various sensors, processes data according to pre-written programs and control strategies, and finally sends control instructions to the actuator to achieve precise control of specific vehicle systems.

[0048] Micro Controller Unit (MCU): MCU is a microcomputer system that integrates multiple functional components such as central processing unit, memory, timer / counter, input / output interface, etc. on a single chip. It is mainly used to control the operation of various electronic devices. In vehicles, MCU is mainly responsible for various basic functions of the vehicle. For example, MCU can control simple devices such as door locks, window lifts, and interior lights.

[0049] Deep learning accelerator: A hardware device or processor architecture specifically designed to accelerate the training and reasoning process of deep learning models. The training and reasoning of deep learning models involve a large number of complex matrix operations, convolution operations, etc., which are computationally intensive and require high computing resources. By optimizing the hardware architecture and using specialized computing units, deep learning accelerators can efficiently process these specific types of computing tasks, thereby significantly improving the training speed and reasoning efficiency of deep learning models.

[0050] The deep learning accelerator in the vehicle local processor involved in this application is designed for automotive application scenarios and needs, and can process complex computing tasks in real time in the vehicle: reasoning based on the collected environmental information, determining whether the first vehicle meets the conditions for turning on / off the lights and making decisions, and generating instructions for controlling the lights. There is no need to transmit data to the cloud for processing, thereby reducing dependence on the network, improving the response speed and reliability of the system, and enhancing the intelligent experience and safety of the vehicle.

[0051] With the continuous evolution and expansion of autonomous driving technology, the headlight control function occupies an increasingly important position in the entire autonomous driving system. In actual driving scenarios, when encountering complex road conditions with poor lighting conditions and significantly reduced visibility, such as driving at night, in bad weather (such as heavy rain, dense fog, sandstorms, etc.), or driving in special sections such as dimly lit tunnels and underground parking lots, if the vehicle can automatically and promptly turn on the headlights, it will improve driving safety and reduce distractions that may be caused by manually operating the headlights.

[0052] In related technologies, the realization of the headlight control function relies on the vehicle-side information collection and cloud-based decision-making process system. The vehicle-side is equipped with various types of sensor devices that can collect environmental information such as the light intensity of the vehicle's surrounding environment, the shape of objects, and the road conditions of the vehicle's road. After the collection is completed, the vehicle-side transmits the environmental information data to the cloud server, which makes decisions based on the received environmental information and generates instructions for headlight control. The cloud then transmits these control instructions back to the vehicle-side through the communication network. After receiving the control instructions, the vehicle-side accurately controls the headlights based on the control instructions.

[0053] However, information is transmitted between the vehicle and the cloud through a wireless communication network, which is vulnerable to attacks in an open environment, and there is a risk of information leakage during the information transmission process. In addition, it takes a certain amount of time for information to be transmitted between the vehicle and the cloud. In autonomous driving scenarios with high real-time requirements, even a short data transmission delay may cause cloud-based decision lags. For example, when a vehicle suddenly enters an area where the light changes dramatically (such as suddenly entering a dark tunnel from bright sunlight), the cloud may not be able to make a quick decision and issue a control command due to the time-consuming data transmission, resulting in a delay in turning on the lights, causing the driver to face blind spots in a short period of time, greatly increasing the risk of driving.

[0054] The present application provides a method for controlling vehicle lights, which can realize steps such as information collection, decision analysis, command generation and vehicle light control based on the local computing power of the vehicle. There is no need to send the collected environmental information to the cloud for the cloud to make decisions and issue commands, which reduces the risk of leakage and decision-making delay in the information transmission process and improves the efficiency of decision-making.

[0055] Next, the vehicle light control system involved in the embodiment of the present application is described. For schematic illustration, please refer to Figure 1 The vehicle light control system 100 is a system inside a first vehicle.

[0056] The vehicle light control system 100 includes vehicle-mounted hardware and software 101 , a local processor 102 , an ECU 103 , and vehicle lights 104 .

[0057] The vehicle-mounted software and hardware 101 collects environmental information, including the road conditions and lighting conditions of the road where the first vehicle is located. The local processor 102 analyzes and processes the environmental information collected by the vehicle-mounted software and hardware 101 and outputs a decision result, which is used to indicate the way to control the headlight 104. The ECU 103 converts the decision output by the local processor 102 into a control instruction, and controls the headlight 104 to perform a corresponding operation, for example, turning on the headlight 104 / turning off the headlight 104 at the time specified by the control instruction.

[0058] Indicative, Figure 2 is based on Figure 1 A schematic diagram showing the interaction mode of the vehicle light control system.

[0059] The vehicle-mounted software and hardware 101 includes but is not limited to a camera 1011, a radar 1012, and a vehicle-mounted navigation system 1013. The camera 1011 and the radar 1012 can collect information about the lighting conditions and road conditions of the first vehicle under the current driving state. The lighting conditions are used to describe the visual conditions and visibility of the current environment; the vehicle-mounted navigation system 1013 can obtain the road conditions of the road ahead. Based on the information collected by the vehicle-mounted software and hardware 101, the road conditions of the road that the first vehicle is about to enter can be predicted, and whether there is a section with poor visual conditions in the road ahead can be determined in time.

[0060] The local processor 102 includes a high-performance MCU1021 and a deep learning accelerator 1022. The MCU1021 is first used to classify and judge the environmental information, and the road condition information of the road ahead obtained by the vehicle navigation 1013 is processed by the MCU1021 to determine the possible scenarios on the road ahead that require turning on the headlights 104, including but not limited to the first vehicle entering a tunnel, rainy days, foggy days, etc.

[0061] Then, the current road condition information is collected through the camera 1011, the radar 1012, and the vehicle navigation 1013, and the road condition information and the scene of turning on the headlights are collected to the deep learning accelerator 1022. The deep learning accelerator 1022 uses the deep learning algorithm to identify whether the current road condition information has met the headlight change condition. Meeting the headlight change condition means that the first vehicle is about to arrive at the scene position where the headlights 104 need to be turned on. When the headlight change condition is met, the decision information is transmitted to the ECU 103, and the ECU 103 controls the headlights 104 in time according to the decision information, for example, turning on the headlights 104. Among them, the decision information indicates the way to control the headlights 104, including but not limited to the on / off state of the headlights 104, the brightness of the headlights 104 when they are turned on, and the duration of the on / off state of the headlights 104.

[0062] The headlight control system 100 is a system inside the first vehicle. The above-mentioned information collection, information processing and decision-making control processes are all completed on the vehicle side without the need for server-side / cloud processing, thereby improving decision-making efficiency and data security.

[0063] In combination with the above-mentioned noun introduction and application scenarios, the vehicle light control method provided by the present application is described, taking the method executed by the vehicle-mounted terminal of the first vehicle as an example. Figure 3 As shown, Figure 3 FIG. 1 is a flow chart of a vehicle light control method provided by an exemplary embodiment of the present application. The method includes the following steps.

[0064] Step 310: Collect environmental information in real time.

[0065] The environmental information is used to describe the environment of the road where the first vehicle is located.

[0066] Optionally, the first vehicle is equipped with a camera, various sensors, and an onboard navigation system to collect environmental information during the driving of the first vehicle. The environmental information includes but is not limited to the following:

[0067] (1) Weather conditions: rainy / snowy / foggy / sunny / cloudy / overcast weather conditions, etc. The weather condition information can be collected by a meteorological sensor installed on the first vehicle, or by receiving data from an external meteorological service through a wireless network to obtain the weather condition information.

[0068] (2) Road conditions: road flatness (such as whether there are potholes or bumps), road type (highway / urban road / country road / mountain road), road slipperiness (dry / wet / waterlogged, etc.). Road condition information can be collected through chassis sensors and wheel speed sensors of the vehicle, or by obtaining map data through a wireless network (such as high-precision maps that provide information such as road type).

[0069] (3) Traffic sign and traffic facility information: the location and status of various traffic signs (such as speed limit signs, no overtaking signs, etc.) and traffic facilities (such as traffic lights, toll booths, etc.) on the road. This information can be collected by the camera of the first vehicle.

[0070] (4) Surrounding vehicle information: the number, location, speed, driving direction, etc. of other vehicles around the first vehicle. Surrounding vehicle information can be collected by sensors such as millimeter wave radar, laser radar or camera installed on the vehicle.

[0071] (5) Information about buildings and obstacles around the road: the location and height of buildings, as well as obstacles on both sides of the road (such as temporary construction fences, vehicles parked on the roadside, etc.). LiDAR can perform a three-dimensional scan of the vehicle's surroundings to obtain detailed information about these buildings and obstacles.

[0072] Among them, weather conditions, traffic signs and traffic facilities information, surrounding vehicle information, and road surrounding building and obstacle information are related to the visibility / lighting conditions of the road where the first vehicle is currently located.

[0073] For example, rain, snow or dense fog can reduce the intensity and clarity of light, interfere with the driver's vision, and reduce lighting conditions and visibility. On sunny days, there is plenty of sunlight and visibility is usually high. In cloudy weather, clouds block part of the sunlight, which reduces the intensity of light.

[0074] For example, when surrounding vehicles turn on their lights, strong light irradiation improves the lighting conditions of the surrounding environment, but when the strong light directly shines into the eyes of the driver of the first vehicle, it will affect the driver's vision and visibility.

[0075] For example, the shadows of tall buildings around the road will affect the lighting conditions. When the sun is low, the shadows of tall buildings may cover part of the road, reducing the light intensity of this part of the road and causing poor lighting conditions.

[0076] For example, some traffic facilities such as street lights and signal lights are directly related to lighting conditions. The brightness and distribution of street lights will affect the lighting conditions of roads at night.

[0077] Step 320: predicting road condition information based on environmental information.

[0078] The road condition information is used to indicate the road condition and lighting conditions of the first road section that has not been traveled on the driving route.

[0079] Optionally, based on the current road condition described by the environmental information, an extended inference is made on the road condition of the first road section to be traveled through to obtain road condition information.

[0080] For example, the weather conditions in the environmental information can reflect the lighting conditions from one aspect. For example, if it is currently sunny or cloudy, and there is no sign of weather change (such as the meteorological sensor does not detect rain clouds or fog gathering in the distance, and the meteorological data received by the wireless network also shows that the weather is stable in a short period of time), it can be inferred that the lighting conditions are good within a certain distance ahead. For example, if it is currently snowy, rainy, or foggy, the current low light and poor visibility may continue to the first section of the road ahead.

[0081] Exemplarily, the road condition in the environmental information can reflect the road surface type of the first road section and infer the lighting conditions ahead. For example, the road condition information indicates that the vehicle is currently traveling on a highway with a wide field of vision and usually sufficient lighting. It is inferred that the first road section is still a highway and the lighting conditions remain unchanged. Alternatively, the road condition information indicates that the vehicle is currently traveling on a country road with trees or mountains blocking the road and poor lighting conditions. For mountain roads, combined with map information, if the first vehicle is traveling along the sunny side of the mountain and is about to turn to the shady side of the mountain, the lighting conditions may deteriorate.

[0082] For example, the traffic signs and traffic facilities information in the environmental information can indicate whether the first road section ahead is under construction or is a special road section type. For example, there are signs with prompt information such as "tunnel ahead" or "underground passage ahead", indicating that the lighting on the first road section will be significantly reduced and the headlights need to be turned on.

[0083] For example, the surrounding vehicle information in the environmental information can reflect the movement trend of the surrounding vehicles, and the lighting conditions can be inferred based on the lighting conditions of the surrounding vehicles, the driving conditions of the vehicles, etc. For example, the surrounding vehicles include a vehicle traveling in front of the first vehicle, which turns on its lights and travels at a relatively slow speed. Even if there is no obvious change in the current lighting conditions and weather conditions, it indicates that there may be a poorly lit area ahead, such as a tunnel about to be entered or an underground parking lot entrance with dim light.

[0084] Exemplarily, the building and obstacle information in the environmental information can determine whether the height of the building will cause a shadow, affecting the lighting conditions of the first road section. For example, there is a tall building on one side of the road in front of the first vehicle, and the vehicle is driving towards the shadow area of ​​the building. At the same time, the map shows that the distribution of buildings within a certain distance ahead is similar. It is inferred that the first road section will continue to be in the shadow, the light will be weakened, and the lighting conditions will be poor. In the above manner, an extended prediction of the current environment of the first vehicle can be made, and the road conditions and lighting conditions of the first road section to be entered can be predicted, and the road condition information of the first road section can be obtained.

[0085] In some embodiments, the first position of the first vehicle at the current moment can also be determined based on environmental information, a map corresponding to the road section where the first position is located can be obtained from the on-board navigation, and road section information can be obtained from the map based on the driving path of the first vehicle as road condition information for predicting the first road section that the first vehicle is about to pass.

[0086] Exemplarily, the environmental information includes positioning information collected by the on-board navigation of the first vehicle. The on-board navigation relies on a GPS receiver to receive satellite signals to obtain information such as the longitude, latitude and altitude of the first vehicle to obtain positioning information.

[0087] Obtain a high-precision map, compare the driving trajectory of the first vehicle with the direction and shape of the road on the map, and determine the first location of the first vehicle. The map records the road type, and predicts the subsequent road sections along the road network according to the driving direction to determine the first road section that the first vehicle is about to enter. The traffic signs, surrounding landmark buildings and other information captured by the camera of the first vehicle add details to the road section prediction and calibrate the direction. After determining the first road section, obtain the road conditions of the first road section from the map.

[0088] In some embodiments, a light sensor is deployed on the first vehicle, and the light sensor can convert light intensity into an electrical signal, and the light intensity is determined based on the size of the electrical signal. Once a sharp drop in light intensity is detected, the information collected by the camera is analyzed to identify the entrance features of special areas such as tunnels, and it can be determined whether the first vehicle has entered a special light section, such as a tunnel or a boulevard. The light conditions of the first road section to be entered are determined based on the weather condition information and light intensity in the environmental information.

[0089] Step 330: Analyze the road condition information to obtain the vehicle lighting scene requirement information in the first road section.

[0090] The vehicle light scene requirement information is used to describe the vehicle light control requirement of the first vehicle in the first road section.

[0091] Among them, the road condition information of the first road section is the information predicted before the first vehicle enters the first road section, and is used to determine the type of control of the headlights when the first vehicle enters the entrance / starting point of the first road section. During the driving process of the first vehicle, environmental information is collected in real time and the road condition information of the road section within a preset distance ahead is predicted based on the currently collected environmental information, and the headlight scene demand information in the road section is further analyzed. When the first vehicle is driving on the first road section, it is still necessary to collect environmental information in real time. When the length of the first road section reaches the first preset length, the first road section is divided into multiple sub-sections by multiple position points. When the first vehicle is driving on one of the sub-sections, the environmental information of the current sub-section is collected and the road condition information of the next sub-section is predicted, and the headlight scene demand information of the next sub-section is analyzed.

[0092] Alternatively, in some embodiments, each sub-section can still be regarded as an independent section. When the length of the first section does not reach the first preset length, when the first vehicle is traveling on the first section, it collects environmental information of the first section in real time, predicts the road condition information of the adjacent front section (the second section), and analyzes the road condition information of the second section to obtain the vehicle lighting scene demand information in the second section.

[0093] That is, when the first vehicle is traveling, environmental information is collected in real time and the road condition information of the road section ahead is predicted based on the environmental information. The headlight scene requirement information of the road section ahead is predicted based on the road condition information. Before the first vehicle enters the road section ahead, the headlights are controlled in advance based on the headlight scene requirement information, so that the headlight status of the first vehicle when entering the road section ahead meets the safety requirements.

[0094] Optionally, the headlight scene requirement information includes the following scenarios and corresponding headlight control information: 1. When the first vehicle is traveling on the first road section, the visibility / lighting conditions of the surrounding environment meet the headlight turning-on requirements, then the headlight control information instructs to turn on the headlights; 2. When the first vehicle is traveling on the first road section, the visibility / lighting conditions of the surrounding environment meet the headlight turning-off requirements, then the headlight control information instructs to turn off the headlights; 3. When the first vehicle is traveling on the first road section, the visibility / lighting conditions of the surrounding environment neither meet the headlight turning-on requirements nor meet the headlight turning-off requirements, then the headlight state is maintained unchanged; for example, if the headlights of the first vehicle were originally in the on state, then they are maintained in the on state; if the headlights of the first vehicle were originally in the off state, then they are maintained in the off state.

[0095] Optionally, the lighting conditions include lighting values ​​at multiple location points in the first road section. When the first vehicle is traveling on the first road section, the lighting conditions may change at any time. The lighting values ​​are collected in real time and the method of controlling the headlights of the first vehicle when passing each location point is determined based on the changes in the lighting values.

[0096] In some embodiments, the first road section is divided based on distance to obtain multiple location points, the light intensity of each location point is collected to obtain a light value, and based on the size of the light value, it is determined whether the vehicle light scene demand information exists and the type of the vehicle light scene demand information.

[0097] In some embodiments, the illumination intensity is collected in real time by the illumination sensor of the first vehicle during the driving process of the first vehicle to obtain illumination intensity change data. The illumination intensity change data includes the change process of the illumination value. When the change of the illumination value within a unit distance / unit duration meets the preset requirements, it is determined that the location point generates a headlight control demand. The type of the headlight scene demand information is determined based on the change amplitude and direction (increase or decrease) of the illumination value.

[0098] Exemplarily, in response to the illumination value corresponding to the first position point in the illumination condition being lower than a preset first illumination threshold, determining that the vehicle light scene requirement information includes turning on the vehicle lights or keeping the vehicle lights on at the first position point.

[0099] For example, the unit of light intensity is lux, the first light threshold is 1000 lux, and the first position point is the tunnel entrance with poor lighting conditions. When the light sensor collects a light intensity value of 900 lux at the first position point, the light value at the first position point is lower than the first light threshold, and if the lights of the first vehicle are on, they remain on until the first vehicle passes the first position point; if the lights of the first vehicle are off, the lights of the first vehicle are automatically turned on until the first vehicle passes the first position point.

[0100] Exemplarily, in response to the illumination value corresponding to the second position point in the illumination condition being higher than a preset second illumination threshold, determining that the vehicle light scene requirement information includes turning off the vehicle lights or keeping the vehicle lights off at the second position point.

[0101] For example, the unit of light intensity is lux, the second light threshold is 2000lux, and the second position is the tunnel exit with good lighting conditions. When the light sensor collects a light intensity value of 2100lux at the second position, the light value at the second position is higher than the second light threshold, and if the lights of the first vehicle are off, they remain off until the first vehicle passes the second position; if the lights of the first vehicle are on, the lights of the first vehicle are automatically turned off until the first vehicle passes the second position.

[0102] Exemplarily, in response to the illumination value corresponding to the third position point in the illumination condition being higher than the first illumination threshold and lower than the second illumination threshold, it is determined that the vehicle light scene requirement information includes keeping the vehicle light state unchanged at the third position point.

[0103] For example, the unit of light intensity is lux, the first light threshold is 1000 lux, the second light threshold is 2000 lux, and the third position point is an open road with clear weather and good lighting conditions. When the light sensor collects a light intensity value of 1800 lux at the third position point, the light value at the third position point is higher than the first light threshold and lower than the second light threshold. If the lights of the first vehicle are off, they remain off until the first vehicle passes the third position point; if the lights of the first vehicle are on, they remain on until the first vehicle passes the third position point. In some embodiments, the light scene requirement information also includes light brightness information, which is used to indicate the light brightness when the lights of the first vehicle are turned on.

[0104] For a first position point in the vehicle light scene requirement information indicating that the vehicle light needs to be turned on, a first difference between an illumination value corresponding to the first position point and a first illumination threshold is calculated.

[0105] The corresponding vehicle light brightness information is obtained based on the first difference.

[0106] Exemplarily, a vehicle headlight brightness mapping table is obtained, wherein the table contains a preset mapping relationship between the interval in which the first difference value is located and the vehicle headlight brightness, and the corresponding vehicle headlight brightness information is determined based on the interval in which the first difference value is located, wherein the unit of each interval is lux.

[0107] For example, when the value of the first difference is within the first interval [0, 250], the headlight brightness information indicates that the headlight brightness is set to 40% of the maximum brightness of the headlight. When the value of the first difference is within the second interval (250, 500], the headlight brightness information indicates that the headlight brightness is set to 60% of the maximum brightness of the headlight. When the value of the first difference is within the third interval (500, 750], the headlight brightness information indicates that the headlight brightness is set to 80% of the maximum brightness of the headlight. When the value of the first difference is within the fourth interval (750, 1000], the headlight brightness information indicates that the headlight brightness is set to 100% of the maximum brightness of the headlight.

[0108] In some embodiments, for the third position point in the headlight scene requirement information that indicates maintaining the headlight state, if the headlight state is on, the second difference between the illumination value corresponding to the third position point and the first illumination threshold and the third difference between the illumination value corresponding to the third position point and the second illumination threshold can also be calculated, and the method for adjusting the headlight brightness is determined based on the larger of the second difference and the third difference.

[0109] For example, if the second difference is greater than the third difference, the headlight brightness is reduced; if the second difference is less than the third difference, the headlight brightness is increased; if the second difference is equal to the third difference, the headlight brightness is kept unchanged. The brightness amplitude of the headlight brightness reduction / increase is n% of the maximum brightness of the headlight, and n is a preset positive number.

[0110] Optionally, the road condition information includes lighting conditions, weather types and road types corresponding to a plurality of location points in the first road section.

[0111] Obtain a preset headlight scene mapping table, which includes a first mapping relationship between a plurality of lighting conditions and a plurality of headlight control scenes, a second mapping relationship between a plurality of weather types and a plurality of headlight control scenes, and a third mapping relationship between a plurality of front road types and a plurality of headlight control scenes.

[0112] Based on the road condition information, target headlight control scenes respectively corresponding to the plurality of position points are determined from a headlight scene mapping table to obtain headlight scene requirement information within the first road section.

[0113] Exemplarily, for the kth position point, three mapping relationships corresponding to the kth lighting condition, the kth weather type, and the kth road type of the kth position point are determined based on the vehicle light scene mapping table. k is a positive integer.

[0114] When at least one mapping relationship among the first mapping relationship, the second mapping relationship, and the third mapping relationship corresponding to the k-th position point indicates that the vehicle light control scene is to turn on the vehicle light, the target vehicle light control scene corresponding to the k-th position point is determined to be the vehicle light turn-on scene. When no mapping relationship among the first mapping relationship, the second mapping relationship, and the third mapping relationship corresponding to the k-th position point indicates that the vehicle light control scene is to turn on the vehicle light, the target vehicle light control scene corresponding to the k-th position point is determined to be the vehicle light turn-off scene.

[0115] When the target headlight control scenes corresponding to all position points are determined, the headlight scene demand information in the first road section is obtained. The headlight scene demand information in the first road section can indicate whether the first vehicle needs to turn on / off the headlights when passing through the first road section, at which position points the headlights need to be turned on / off, and how long the headlight state is maintained each time the headlights are turned on / off.

[0116] Optionally, the road condition information includes the road type of the first road section and illumination values ​​of multiple location points in the first road section.

[0117] Obtain a preset coefficient table, which includes safety factors corresponding to various road types. The value of the safety factor is used to describe the safety level of a vehicle when driving on different types of roads. The value of the safety factor is positively correlated with the safety level.

[0118] A first coefficient is obtained from the coefficient table based on the road type of the first road section, where the first coefficient is used to indicate a safety level when the first vehicle travels in the first road section.

[0119] A plurality of values ​​respectively corresponding to the plurality of position points are obtained based on the product of the illumination values ​​of the plurality of position points and the first coefficient.

[0120] Based on the multiple values, the vehicle lighting scenes corresponding to the multiple position points are determined respectively to obtain the vehicle lighting scene requirement information.

[0121] Exemplarily, in response to at least one value among multiple values ​​meeting a preset headlight turning-on requirement, at least one position point corresponding to at least one value is determined, and it is determined that the headlight scene requirement information includes turning on the headlights or keeping the headlights on at least one position point.

[0122] For example, the preset vehicle light on requirement means that the product of the illumination value at the location point and the first coefficient is less than a preset product threshold.

[0123] The coefficient table includes the following contents: when the road type is highway / urban road, the safety factor is 10; when the road type is rural road, the safety factor is 5; when the road type is mountain road, the safety factor is 1.

[0124] Among them, the road type of the first section is an urban road, the first coefficient is 1, the light intensity at the first position point is 1500 lux, the light intensity at the second position point is 1000 lux, and the preset product threshold is 10000.

[0125] Then, the value corresponding to the first position point is 1500*10=15000, which is greater than the preset product threshold value 10000, and the value corresponding to the second position point is 1000*10=10000, which is equal to the preset product threshold value 10000. Then, the first position point does not meet the preset headlight on requirement, and the second position point meets the preset headlight on requirement.

[0126] Step 340: Generate a headlight control instruction based on the headlight scene requirement information and the environmental information, and control the headlight of the first vehicle based on the headlight control instruction.

[0127] After the vehicle light scene demand information is predicted, the environment information is updated in real time to obtain the environment information at the current moment, which includes the vehicle position of the first vehicle. The vehicle position of the first vehicle is used to indicate whether the first vehicle has entered the first road section.

[0128] The vehicle light scene requirement information includes at least one location point in the first road section where there is a vehicle light control requirement.

[0129] When a preset instruction generation condition is met between at least one position point and the vehicle position of the first vehicle, a headlight control instruction is generated based on the headlight scene requirement information.

[0130] After the vehicle light control instruction is generated, the vehicle light of the first vehicle is immediately controlled to be turned on or off based on the vehicle light control instruction.

[0131] Exemplarily, for an i-th position point among the at least one position point, an i-th distance between the vehicle position of the first vehicle and the i-th position point is calculated, where i is a positive integer.

[0132] In response to the i-th distance being less than or equal to a preset distance threshold, it is determined that a preset instruction generation condition is met between the i-th position point and the vehicle position of the first vehicle.

[0133] The headlight scene requirement information includes a control type for controlling the headlights at at least one location point, and the control types include turning off the headlights, turning on the headlights, and keeping the headlights unchanged.

[0134] Based on the control type of the headlight control for the i-th position point in the headlight scene requirement information, a headlight control instruction corresponding to the i-th position point is generated.

[0135] For example, when the i-th distance between the position of the first vehicle and the i-th position point is less than or equal to a preset distance threshold, it indicates that the first vehicle is about to pass the i-th position point. The preset distance threshold is 10 meters, and the i-th distance is 9 meters.

[0136] If the headlight scene requirement information indicates that the headlights need to be turned on when passing the i-th position point, a headlight control instruction is generated to turn on the headlights in advance to ensure that the lighting conditions when the first vehicle passes the i-th position point meet driving safety.

[0137] When the distance between the first vehicle and the i-th position point is the preset sensor detection distance, the light sensor is started to collect the light intensity near the i-th position point, and it is determined based on the light intensity whether the control type of the light control at the i-th position point in the light scene requirement information needs to be corrected. If correction is required, the control type of the light control is determined based on the light intensity collected by the light sensor. If correction is not required, the control type of the light control at the i-th position point continues to be generated based on the control type of the light control at the i-th position point in the light scene requirement information.

[0138] Among them, the preset sensor detection distance is greater than the preset distance threshold. When the i-th distance is less than or equal to the preset distance threshold, a headlight control instruction is generated based on the corrected headlight control type, and the headlight is controlled immediately after the headlight control instruction is generated.

[0139] When the first vehicle passes the i-th position point, if there is an i+1-th position point and the distance between the i+1-th position point and the i-th position point is greater than a preset distance threshold, the headlight state at the i-th position point is maintained until the distance between the first vehicle and the i+1-th position point is only the preset distance threshold, and a headlight control instruction corresponding to the i+1-th position point is generated based on the headlight control information for the i+1-th position point in the headlight scene requirement information.

[0140] For example, the distance between the i-th position point and the i+1-th position point is 20 meters, and the preset distance threshold is 10 meters. When the first vehicle passes the i-th position point, the headlight status continues to be maintained until the i+1-th distance between the first vehicle and the i+1-th position point is equal to the preset distance threshold. Based on the control type of the headlight control for the i+1-th position point in the headlight scene requirement information, a headlight control instruction corresponding to the i+1-th position point is generated to control the headlight status.

[0141] In summary, the vehicle light control method provided by the present application can predict the road condition information and lighting conditions in the road section that the first vehicle is about to pass through by collecting environmental information, and judge whether there is a scene in the road section that requires the vehicle lights to be turned on or off, so as to provide sufficient time for turning the vehicle lights on and off in advance, and realize automatic control of the vehicle lights. The information collection process and the process of generating vehicle light control instructions are all executed by the vehicle side. There is no need to send the collected information to the cloud for analysis and decision-making by the cloud, and then the cloud returns the decision results to the vehicle side to control the vehicle lights. This can reduce the risk of leakage in the information transmission process, improve the security of information data, reduce the transmission time in the process of information and decision results transmission, and improve the decision efficiency and the efficiency of controlling the vehicle lights. In the face of extreme situations, the vehicle lights can be automatically turned on and off in time when the road conditions, lighting conditions, etc. change, to ensure the safety of the driver during driving.

[0142] Figure 4 is a structural block diagram of a vehicle light control device provided by an exemplary embodiment of the present application. Figure 4 As shown, the device includes the following parts.

[0143] A collection module 410 is used to collect environmental information in real time, where the environmental information is used to describe the environment of the road where the first vehicle is located;

[0144] A prediction module 420, configured to predict road condition information based on the environmental information, wherein the road condition information is used to indicate the road condition and lighting condition of a first road section that has not been traveled on the driving path;

[0145] An analysis module 430 is used to analyze the road condition information to obtain vehicle light scene requirement information in the first road section, where the vehicle light scene requirement information is used to describe vehicle light control requirements of the first vehicle in the first road section;

[0146] The control module 440 is used to generate a headlight control instruction based on the headlight scene requirement information and the environmental information, and control the headlight of the first vehicle based on the headlight control instruction.

[0147] In an optional embodiment, the illumination condition includes illumination values ​​of a plurality of position points in the first road section;

[0148] The analysis module 430 is used to determine that the vehicle light scene requirement information includes turning on the vehicle lights at the first position point or keeping the vehicle lights on in response to the presence of a lighting value corresponding to a first position point in the lighting condition being lower than a preset first lighting threshold; or, in response to the presence of a lighting value corresponding to a second position point in the lighting condition being higher than a preset second lighting threshold, determine that the vehicle light scene requirement information includes turning off the vehicle lights at the second position point or keeping the vehicle lights off; or, in response to the presence of a lighting value corresponding to a third position point in the lighting condition being higher than the first lighting threshold and lower than the second lighting threshold, determine that the vehicle light scene requirement information includes keeping the vehicle lights unchanged at the third position point.

[0149] In an optional embodiment, the headlight scene requirement information further includes headlight brightness information, and the headlight brightness information is used to indicate the headlight brightness when the headlight of the first vehicle is turned on;

[0150] The analysis module 430 is further configured to calculate a first difference between the illumination value corresponding to the first position point and the first illumination threshold; and obtain corresponding vehicle light brightness information based on the first difference.

[0151] In an optional embodiment, the road condition information includes lighting conditions, weather types and road types corresponding to a plurality of location points in the first road section;

[0152] The analysis module 430 is further used to obtain a preset headlight scene mapping table, which includes a first mapping relationship between a plurality of lighting conditions and a plurality of headlight control scenes, a second mapping relationship between a plurality of weather types and the plurality of headlight control scenes, and a third mapping relationship between a plurality of front road types and the plurality of headlight control scenes; based on the road condition information, the target headlight control scenes corresponding to the plurality of position points are determined from the headlight scene mapping table to obtain the headlight scene demand information within the first road section.

[0153] In an optional embodiment, the control module 440 is also used to update the environmental information in real time to obtain the environmental information at the current moment, wherein the environmental information at the current moment includes the vehicle position of the first vehicle; wherein the headlight scene requirement information includes at least one position point in the first road section where there is a headlight control requirement; when the preset instruction generation conditions are met between the at least one position point and the vehicle position of the first vehicle, the headlight control instruction is generated based on the headlight scene requirement information.

[0154] In an optional embodiment, the control module 440 is also used to calculate the i-th distance between the vehicle position of the first vehicle and the i-th position point among the at least one position point; i is a positive integer; in response to the i-th distance being less than or equal to a preset distance threshold, determine that the distance between the i-th position point and the vehicle position of the first vehicle meets the preset instruction generation conditions; wherein the headlight scene requirement information includes a control type for headlight control of the at least one position point, and the control type includes turning off the headlights, turning on the headlights, and keeping the headlights unchanged; based on the control type for headlight control of the i-th position point in the headlight scene requirement information, generate a headlight control instruction corresponding to the i-th position point.

[0155] In an optional embodiment, the road condition information includes a road type of the first road section and illumination values ​​of a plurality of position points in the first road section;

[0156] The analysis module 430 is further used to obtain a preset coefficient table, which includes safety coefficients corresponding to multiple road types, and the value of the safety coefficient is used to describe the safety level of a vehicle when traveling on different types of roads, and the value of the safety coefficient is positively correlated with the safety level; a first coefficient is obtained from the coefficient table based on the road type of the first road section, and the first coefficient is used to indicate the safety level of the first vehicle when traveling in the first road section; a plurality of values ​​corresponding to the plurality of position points are obtained based on the product of the illumination values ​​of the plurality of position points and the first coefficient; and the headlight scenes corresponding to the plurality of position points are determined based on the plurality of values ​​to obtain the headlight scene requirement information.

[0157] In an optional embodiment, the analysis module 430 is further used to determine at least one position point corresponding to the at least one value in response to the presence of at least one value among the multiple values ​​that meets the preset headlight turning-on requirement, and to determine that the headlight scene requirement information includes turning on the headlights or keeping the headlights on at the at least one position point.

[0158] In summary, the headlight control device provided by the present application can predict the road condition information and lighting conditions in the road section that the first vehicle is about to pass by by collecting environmental information, and judge whether there is a scene in the road section that requires the headlights to be turned on or off, so as to provide sufficient time for turning the headlights on and off in advance, and realize automatic control of the headlights. The information collection process and the headlight control instruction generation process are all executed by the vehicle side. There is no need to send the collected information to the cloud for analysis and decision-making by the cloud, and then the cloud returns the decision results to the vehicle side to control the headlights. This can reduce the risk of leakage in the information transmission process, improve the security of information data, reduce the transmission time in the process of information and decision results transmission, and improve the decision efficiency and the efficiency of controlling the headlights. In the face of extreme situations, the headlights can be automatically turned on and off in time when the road conditions, lighting conditions, etc. change, to ensure the safety of the driver during driving.

[0159] It should be noted that the vehicle light control device provided in the above embodiment is only illustrated by the division of the above functional modules. In actual applications, the above functions can be assigned to different functional modules as needed, that is, the internal structure of the device is divided into different functional modules to complete all or part of the functions described above. In addition, the vehicle light control device provided in the above embodiment and the vehicle light control method embodiment belong to the same concept, and the specific implementation process is detailed in the method embodiment, which will not be repeated here.

[0160] Figure 5 The block diagram of the structure of a computer device 500 provided by an exemplary embodiment of the present application is shown. The computer device 500 may be: a smart phone, a tablet computer, an MP3 player (Moving Picture Experts Group Audio Layer III, Moving Picture Experts Group Audio Layer 3), an MP4 (Moving Picture Experts Group Audio Layer IV, Moving Picture Experts Group Audio Layer 4) player, a laptop computer or a desktop computer. The computer device 500 may also be called a user device, a portable terminal, a laptop terminal, a desktop terminal or other names.

[0161] Typically, the computer device 500 includes a processor 501 and a memory 502 .

[0162] The processor 501 may include one or more processing cores, such as a 4-core processor, an 8-core processor, etc. The processor 501 may be implemented in at least one hardware form of DSP (Digital Signal Processing), FPGA (Field-Programmable Gate Array), and PLA (Programmable Logic Array). The processor 501 may also include a main processor and a coprocessor. The main processor is a processor for processing data in the awake state, also known as a CPU (Central Processing Unit); the coprocessor is a low-power processor for processing data in the standby state. In some embodiments, the processor 501 may be integrated with a GPU (Graphics Processing Unit), which is responsible for rendering and drawing the content to be displayed on the display screen. In some embodiments, the processor 501 may also include an AI (Artificial Intelligence) processor, which is used to process computing operations related to machine learning.

[0163] The memory 502 may include one or more computer-readable storage media, which may be non-transitory. The memory 502 may also include a high-speed random access memory and a non-volatile memory, such as one or more disk storage devices and flash memory storage devices. In some embodiments, the non-transitory computer-readable storage medium in the memory 502 is used to store at least one instruction, which is used to be executed by the processor 501 to implement the vehicle light control method provided in the method embodiment of the present application.

[0164] In some embodiments, the computer device 500 further includes some other components 503, and the type and quantity of the other components 503 can be selected based on the functional requirements of the computer device 500. Those skilled in the art will appreciate that Figure 5 The structure shown in the figure does not constitute a limitation on the computer device 500, and the computer device 500 may include more or less components than those shown in the figure, or combine some components, or adopt a different arrangement of components.

[0165] Optionally, the computer readable storage medium may include: a read-only memory (ROM), a random access memory (RAM), a solid state drive (SSD), or an optical disk. Among them, the random access memory may include a resistance random access memory (ReRAM) and a dynamic random access memory (DRAM). The serial numbers of the above embodiments of the present application are only for description and do not represent the advantages and disadvantages of the embodiments.

[0166] An embodiment of the present application also provides a computer device, which includes a processor and a memory, wherein the memory stores at least one instruction, at least one program, a code set or an instruction set, and the at least one instruction, the at least one program, the code set or the instruction set is loaded and executed by the processor to implement the vehicle light control method as described in any of the above embodiments of the present application.

[0167] An embodiment of the present application also provides a computer-readable storage medium, in which at least one instruction, at least one program, a code set or an instruction set is stored. The at least one instruction, the at least one program, the code set or the instruction set is loaded and executed by a processor to implement a vehicle light control method as described in any of the above embodiments of the present application.

[0168] The embodiment of the present application also provides a computer program product or a computer program, which includes a computer instruction stored in a computer-readable storage medium. The processor of the computer device reads the computer instruction from the computer-readable storage medium, and the processor executes the computer instruction, so that the computer device executes the vehicle light control method described in any of the above embodiments.

[0169] A person skilled in the art will understand that all or part of the steps to implement the above embodiments may be accomplished by hardware or by instructing related hardware through a program, and the program may be stored in a computer-readable storage medium, and the above-mentioned storage medium may be a read-only memory, a disk or an optical disk, etc.

[0170] The above description is only an optional embodiment of the present application and is not intended to limit the present application. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present application shall be included in the protection scope of the present application.

Claims

1. A vehicle light control method, characterized in that: The method comprises: Collecting environmental information in real time, where the environmental information is used to describe the environment of the road where the first vehicle is located; Predicting road condition information based on the environmental information, the road condition information being used to indicate road conditions and lighting conditions of a first road section that has not been traveled on the driving path; Analyze the road condition information to obtain vehicle light scene requirement information in the first road section, where the vehicle light scene requirement information is used to describe vehicle light control requirements of the first vehicle in the first road section; A headlight control instruction is generated based on the headlight scene requirement information and the environmental information, and the headlight of the first vehicle is controlled based on the headlight control instruction.

2. The method according to claim 1, characterized in that The lighting conditions include lighting values ​​at a plurality of locations in the first road section; The analyzing the road condition information to obtain vehicle light scene requirement information in the first road section includes: In response to the illumination value corresponding to the first position point in the illumination condition being lower than a preset first illumination threshold, determining that the vehicle light scene requirement information includes turning on or keeping the vehicle light on at the first position point; or, In response to the illumination value corresponding to the second position point in the illumination condition being higher than a preset second illumination threshold, determining that the vehicle light scene requirement information includes turning off the vehicle lights or keeping the vehicle lights off at the second position point; or, In response to the presence of a third position point in the lighting condition corresponding to a lighting value higher than the first lighting threshold and lower than the second lighting threshold, determining that the vehicle light scene requirement information includes keeping the vehicle light state unchanged at the third position point.

3. The method according to claim 2, characterized in that The vehicle light scene requirement information also includes vehicle light brightness information, and the vehicle light brightness information is used to indicate the brightness of the vehicle lights when the vehicle lights are turned on; the method further includes: Calculating a first difference between the illumination value corresponding to the first position point and the first illumination threshold; The corresponding vehicle light brightness information is acquired based on the first difference.

4. The method according to any one of claims 1 to 3, characterized in that: The road condition information includes lighting conditions, weather types and road types corresponding to a plurality of location points in the first road section; The analyzing the road condition information to obtain vehicle light scene requirement information in the first road section includes: Obtaining a preset vehicle light scene mapping table, wherein the vehicle light scene mapping table includes first mapping relationships between a plurality of lighting conditions and a plurality of vehicle light control scenes, second mapping relationships between a plurality of weather types and the plurality of vehicle light control scenes, and third mapping relationships between a plurality of front road types and the plurality of vehicle light control scenes; Based on the road condition information, target headlight control scenes corresponding to the plurality of position points are determined from the headlight scene mapping table to obtain headlight scene requirement information within the first road section.

5. The method according to any one of claims 1 to 3, characterized in that: The generating the vehicle light control instruction based on the vehicle light scene requirement information and the environment information includes: updating the environmental information in real time to obtain the environmental information at a current moment, wherein the environmental information at the current moment includes the vehicle position of the first vehicle; wherein the vehicle light scene requirement information includes at least one location point in the first road section where there is a vehicle light control requirement; When a preset instruction generation condition is met between the at least one position point and the vehicle position of the first vehicle, the headlight control instruction is generated based on the headlight scene requirement information.

6. The method according to claim 5, characterized in that When a preset instruction generation condition is met between the at least one position point and the vehicle position of the first vehicle, generating the headlight control instruction based on the headlight scene requirement information includes: For an i-th position point among the at least one position point, calculating an i-th distance between the vehicle position of the first vehicle and the i-th position point; i is a positive integer; In response to the i-th distance being less than or equal to a preset distance threshold, determining that a preset instruction generation condition is met between the i-th position point and the vehicle position of the first vehicle; wherein the headlight scene requirement information includes a control type for headlight control of the at least one position point, and the control type includes turning off the headlight, turning on the headlight, and keeping the headlight state unchanged; Based on the control type of the headlight control for the i-th position point in the headlight scene requirement information, a headlight control instruction corresponding to the i-th position point is generated.

7. The method according to any one of claims 1 to 3, characterized in that: The road condition information includes a road type of a first road section and illumination values ​​of a plurality of position points in the first road section; The analyzing the road condition information to obtain vehicle light scene requirement information in the first road section includes: Obtaining a preset coefficient table, wherein the coefficient table includes safety coefficients corresponding to a plurality of road types, respectively. The values ​​of the safety coefficients are used to describe the safety level of a vehicle when driving on different types of roads, and the values ​​of the safety coefficients are positively correlated with the safety level; acquiring a first coefficient from the coefficient table based on the road type of the first road section, wherein the first coefficient is used to indicate a safety level when the first vehicle travels in the first road section; Obtaining a plurality of values ​​corresponding to the plurality of position points respectively based on the product of the illumination values ​​of the plurality of position points and the first coefficient; The vehicle light scenes corresponding to the multiple position points are determined based on the multiple values ​​to obtain the vehicle light scene requirement information.

8. The method according to claim 7, characterized in that The determining, based on the multiple values, the vehicle light scenes corresponding to the multiple position points respectively, and obtaining the vehicle light scene requirement information includes: In response to at least one value among the multiple values ​​meeting the preset headlight turning-on requirement, determining at least one position point corresponding to the at least one value, and determining that the headlight scene requirement information includes turning on the headlights or keeping the headlights on at the at least one position point.

9. A vehicle light control device, characterized in that: The device comprises: A collection module, used for collecting environmental information in real time, where the environmental information is used to describe the environment of the road where the first vehicle is located; A prediction module, used to predict road condition information based on the environmental information, where the road condition information is used to indicate the road condition and lighting condition of a first road section that has not been traveled on the driving path; an analysis module, configured to analyze the road condition information to obtain vehicle light scene requirement information within the first road section, wherein the vehicle light scene requirement information is used to describe vehicle light control requirements of the first vehicle within the first road section; A control module is used to generate a headlight control instruction based on the headlight scene requirement information and the environmental information, and control the headlight of the first vehicle based on the headlight control instruction.

10. A computer device, characterized in that: The computer device includes a processor and a memory, wherein the memory stores at least one program, and the at least one program is loaded and executed by the processor to implement the vehicle light control method according to any one of claims 1 to 8.

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