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

Abstract

The invention relates to a vehicle control method and device, computer equipment, a storage medium and a computer program product. The method comprises the following steps: acquiring at least one type of vehicle environment information acquired by a vehicle environment information acquisition system, and performing feature extraction on each piece of vehicle environment information to obtain each initial environment feature; fusing the initial environment features to obtain target environment features; generating a global environment view based on the target environment features; and processing the global environment view to obtain interaction information, and outputting the interaction information to a screen tail lamp. By adopting the method, effective interaction information can be provided for other vehicles.

Description

Technical Field

[0001] The present application relates to the field of vehicle technology, and in particular to a vehicle control method, device, computer equipment, storage medium and computer program product. Background Art

[0002] Recently, with the increasing intelligence of cars, the demand for efficient, safe and comfortable driving is also increasing. To meet this demand, intelligent and interactive LED screen taillights will also play an important role.

[0003] In traditional technology, for example, the LED display screens installed at the front and rear of a bus can display platform information, safety tips, route numbers and other texts, and the LED display screens installed on the top of a taxi can display advertising slogans.

[0004] However, the current display modes of such information are all pre-fixed, the display content is single, and it is played in a loop, and it is impossible to provide effective interactive information to other vehicles. Summary of the invention

[0005] Based on this, it is necessary to provide a vehicle control method, device, computer equipment, computer-readable storage medium and computer program product that can provide effective interactive information to other vehicles in response to the above technical problems.

[0006] In a first aspect, the present application provides a vehicle control method, the method comprising:

[0007] Acquire vehicle environment information collected by at least one type of vehicle environment information collection system, and extract features from each of the vehicle environment information to obtain initial environment features;

[0008] Fusing the initial environmental features to obtain target environmental features;

[0009] generating a global environment view based on the target environment characteristics;

[0010] The global environment view is processed to obtain interaction information, and the interaction information is output to a screen taillight.

[0011] In one embodiment, the acquiring of vehicle environment information collected by at least one type of vehicle environment information collection system and performing feature extraction on each of the vehicle environment information to obtain each initial environment feature includes at least one of the following:

[0012] The first real-time traffic information and the first real-time road information are acquired by the navigation system, and features are extracted from the first real-time traffic information and the first real-time road information to obtain first real-time traffic features and first real-time road features;

[0013] A radar signal of a first target collected by a radar system is used to extract a distance feature and a speed feature of the first target based on the radar signal of the first target;

[0014] The vehicle surrounding environment image is captured by the camera system, and features are extracted from the vehicle surrounding environment image to obtain targets located around the vehicle;

[0015] Collecting radar laser signals through a radar laser system, and performing feature extraction based on the radar laser signals to obtain a three-dimensional map around the vehicle;

[0016] An ultrasonic signal of a second target collected by the ultrasonic system, and feature extraction based on the ultrasonic signal of the second target to obtain a distance feature and a speed feature of the second target; and

[0017] The second real-time traffic information and the second real-time road information transmitted by the neighboring vehicles are acquired through the communication system, and the second real-time traffic information and the second real-time road information are subjected to feature extraction to obtain the second real-time traffic feature and the second real-time road feature.

[0018] In one embodiment, the fusing of the initial environment features to obtain the target environment features includes:

[0019] Matching the target located around the vehicle and the first target to obtain a first matching result;

[0020] Determine the distance feature and the speed feature of each of the targets located around the vehicle based on the first matching result;

[0021] Matching the second target with the target located around the vehicle to obtain a second matching result;

[0022] Based on the second matching result and the distance feature and the speed feature of the second target, the distance feature and the speed feature of the target located around the vehicle are corrected.

[0023] In one embodiment, generating a global environment view based on the target environment characteristics includes:

[0024] The target environment characteristics are input into an artificial intelligence network, and the three-dimensional map around the vehicle, the first real-time traffic characteristics and the first real-time road characteristics, the distance characteristics and the speed characteristics of the first target, the target located around the vehicle, the distance characteristics and the speed characteristics of the second target, and the second real-time traffic characteristics and the second real-time road characteristics are integrated through the artificial intelligence network to obtain a global environment view.

[0025] In one embodiment, extracting features based on the radar signal of the first target to obtain the distance feature and the speed feature of the first target includes:

[0026] Obtain vehicle speed and radar signal speed;

[0027] Obtaining a first time interval of a radar signal returned in a previous test cycle and a second time interval of a radar signal returned in a current test cycle;

[0028] Obtaining a distance characteristic of the first target based on the vehicle speed, the radar signal speed, and the second time interval;

[0029] Obtaining a first distance feature of the first target based on the vehicle speed, the radar signal speed, and the first time interval;

[0030] A speed feature of the first target is obtained based on the current distance feature, the first distance feature, the first time interval, the second time interval, and the vehicle speed.

[0031] In one embodiment, the processing of the global environment view to obtain the interaction information includes:

[0032] Acquire a preconfigured rule set, the rule set comprising processing rule subsets, each of the processing rule subsets comprising a condition and interaction information;

[0033] Extracting the to-be-processed environment features corresponding to each of the processing rule subsets from the global environment view;

[0034] When the to-be-processed environmental feature satisfies the condition, the interaction information corresponding to the condition is acquired.

[0035] In a second aspect, the present application further provides a vehicle control device, the device comprising:

[0036] A collection module, used to obtain vehicle environment information collected by at least one type of vehicle environment information collection system, and extract features from each of the vehicle environment information to obtain each initial environment feature;

[0037] A feature fusion module, used to fuse the initial environment features to obtain target environment features;

[0038] A global environment view generation module, used to generate a global environment view based on the target environment characteristics;

[0039] The decision module is used to process the global environment view to obtain interaction information and output the interaction information to the screen taillight.

[0040] In a third aspect, the present application further provides a computer device, comprising a memory and a processor, wherein the memory stores a computer program, and the processor implements the steps of the method in any one of the above-mentioned embodiments when executing the computer program.

[0041] In a fourth aspect, the present application further provides a computer-readable storage medium having a computer program stored thereon, wherein the computer program, when executed by a processor, implements the steps of the method in any one of the above-mentioned embodiments.

[0042] In a fifth aspect, the present application also provides a computer program product, including a computer program, which implements the steps of the method in any one of the above-mentioned embodiments when executed by a processor.

[0043] The above-mentioned vehicle control method, device, computer equipment, storage medium and computer program product collect vehicle environment information through multiple vehicle environment information collection systems, and process it to obtain initial environment characteristics, fuse each of the initial environment characteristics to obtain target environment characteristics, and then generate a global environment view based on the target environment characteristics, which can ensure that the global environment view is relatively accurate, and then generate interactive information based on the global environment view to ensure that the interactive information is real-time and effective, and output the interactive information to the screen taillights, so as to provide effective interactive information to other vehicles. BRIEF DESCRIPTION OF THE DRAWINGS

[0044] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the related technologies, the drawings required for use in the embodiments or the related technical descriptions are 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 paying creative work.

[0045] Figure 1 A diagram showing an application environment of a vehicle control method in an embodiment;

[0046] Figure 2 A schematic flow chart of a vehicle control method in one embodiment;

[0047] Figure 3 A schematic diagram of a process of generating target environment characteristics in one embodiment;

[0048] Figure 4 is a flow chart of steps for obtaining distance features and speed features in one embodiment;

[0049] Figure 5 is a structural block diagram of a vehicle control device in one embodiment;

[0050] Figure 6FIG. 4 is a diagram showing the internal structure of a computer device in one embodiment. DETAILED DESCRIPTION

[0051] In order to make the purpose, technical solution and advantages of the present application more clearly understood, the present application is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0052] The vehicle control method provided in the embodiment of the present application can be applied to Figure 1 In the application environment shown. The vehicle terminal communicates with each type of vehicle environment information collection system to obtain the vehicle environment information collected by each type of vehicle environment information collection system. The vehicle terminal also communicates with the screen taillight to output the interactive information to the screen taillight. The number of vehicle environment information collection systems and the number of screen taillights are not specifically limited here, and those skilled in the art can set them based on needs.

[0053] In some optional embodiments, the vehicle environment information acquisition system includes at least one of a navigation system, a radar system, a radar laser system, a camera system, an ultrasonic system, and a communication system.

[0054] In this embodiment, the vehicle terminal is used to extract features from each vehicle environment information to obtain each initial environment feature; fuse each initial environment feature to obtain the target environment feature; generate a global environment view based on the target environment feature; process the global environment view to obtain interactive information, and output the interactive information to the screen taillight

[0055] In the above embodiment, vehicle environment information is collected through multiple vehicle environment information collection systems, and processed to obtain initial environment characteristics, the initial environment characteristics are fused to obtain target environment characteristics, and then a global environment view is generated based on the target environment characteristics. This can ensure that the global environment view is relatively accurate, and then interactive information is generated based on the global environment view to ensure that the interactive information is real-time and effective, and the interactive information is output to the screen taillights, so as to provide effective interactive information to other vehicles.

[0056] In an exemplary embodiment, Figure 2 As shown, a vehicle control method is provided, which is applied to Figure 1 Taking the vehicle terminal in the example as an example, the method includes the following steps 202 to 206. Among them:

[0057] S202: Acquire vehicle environment information collected by at least one type of vehicle environment information collection system, and perform feature extraction on each vehicle environment information to obtain each initial environment feature.

[0058] Among them, the vehicle environment information collection system includes at least one of a navigation system, a radar system, a radar laser system, an ultrasonic system and a communication system.

[0059] The navigation system can collect first real-time traffic information and first real-time road information. Many vehicles are equipped with built-in GPS and navigation systems, which provide updates of first real-time traffic information. These GPS and navigation systems use information from traffic monitoring services to provide route suggestions and generate first real-time road information to alert drivers of traffic jams and road closures.

[0060] A radar system can collect radar signals of the first target. A radar system includes at least one radar sensor that emits radio waves and measures reflections to detect the distance and speed of an object. Radar sensors are essential for adaptive cruise control, collision avoidance systems, and blind spot detection; they help vehicles maintain a safe distance from other cars and detect obstacles on the road.

[0061] Radar laser systems can obtain a three-dimensional map of the vehicle's surroundings; LiDAR uses laser pulses to create a high-resolution 3D map of the vehicle's surroundings. This technology is often used in self-driving vehicles and has the ability to detect obstacles, pedestrians and other vehicles with high accuracy.

[0062] The ultrasonic system can collect ultrasonic signals of the second target. The ultrasonic system includes at least one ultrasonic sensor. These ultrasonic sensors use sound waves to detect objects close to the vehicle. They are often used in parking assistance systems during parking operations to help drivers avoid collisions with nearby objects.

[0063] The camera system can collect images of the vehicle's surroundings; the camera system includes at least one camera for collecting images. Cameras installed around the vehicle provide visual data that can be used to detect lane markings, road signs, pedestrians and other vehicles. These cameras are key components of lane keeping assist, traffic sign recognition and automatic parking systems.

[0064] The communication system can obtain second real-time traffic information and second real-time road information transmitted by neighboring vehicles. For example, a vehicle exchanges information with other vehicles and traffic infrastructure through wireless communication to obtain real-time traffic conditions and road information.

[0065] In some optional embodiments, the working state of each vehicle environment information collection system can be determined based on the driving state of the vehicle. For example, when the vehicle is driving at a low speed or parked, the ultrasonic system is turned on, and when the vehicle is driving at a high speed, the radar system is turned on. Wherein, low-speed driving means driving at a speed within a first speed range, and high-speed driving means driving at a speed within a second speed range, and the minimum speed of the second speed range is greater than or equal to the maximum speed of the first speed range. For example, when the vehicle is driving, the navigation system and the communication system are turned on, and when the vehicle is parked, the radar laser system and the camera system are turned on. The mapping relationship between the working state of each vehicle environment information collection system and the corresponding driving state of the vehicle can be predetermined and can be adjusted based on the actual hardware of the vehicle, and is not specifically limited here.

[0066] The initial environmental features are based on the environmental features obtained from the environmental information of each vehicle.

[0067] In one of the optional embodiments, vehicle environment information collected by at least one type of vehicle environment information collection system is obtained, and feature extraction is performed on each vehicle environment information to obtain each initial environment feature, including at least one of the following: first real-time traffic information and first real-time road information obtained by a navigation system, and feature extraction is performed on the first real-time traffic information and the first real-time road information to obtain first real-time traffic features and first real-time road features; a radar signal of a first target collected by a radar system, and feature extraction is performed based on the radar signal of the first target to obtain distance features and speed features of the first target; an image of the vehicle surrounding environment collected by a camera system, and feature extraction is performed on the image of the vehicle surrounding environment to obtain targets located around the vehicle; a radar laser signal is collected by a radar laser system, and feature extraction is performed based on the radar laser signal to obtain a three-dimensional map around the vehicle; an ultrasonic signal of a second target is collected by an ultrasonic system, and feature extraction is performed based on the ultrasonic signal of the second target to obtain distance features and speed features of the second target; and second real-time traffic information and second real-time road information transmitted by neighboring vehicles obtained by a communication system, and feature extraction is performed on the second real-time traffic information and the second real-time road information to obtain second real-time traffic features and second real-time road features.

[0068] Feature extraction may include data preprocessing and feature extraction of the preprocessed data, wherein feature extraction may be performed through an artificial intelligence model, and no specific limitation is made to the feature extraction method herein.

[0069] For example, GPS is used in combination with real-time traffic information services to provide real-time traffic conditions on the road ahead, thereby serving as first real-time traffic features and first real-time road features obtained by extracting features from the first real-time traffic information and the first real-time road information.

[0070] The radar system collects a radar signal of the first target, and performs feature extraction based on the radar signal of the first target to obtain a distance feature and a speed feature of the first target, wherein the radar system includes a long-range radar sensor and a short-range radar sensor, thereby being able to detect the distance and speed of objects at different distance ranges from the vehicle.

[0071] The camera system collects images of the vehicle's surrounding environment and performs feature extraction on the images of the vehicle's surrounding environment to obtain targets located around the vehicle. Specifically, computer vision and deep learning algorithms are used to process the images to identify targets on the road, including vehicles, pedestrians, and other obstacles.

[0072] The radar laser system collects radar laser signals and performs feature extraction based on the radar laser signals to obtain a three-dimensional map of the vehicle's surroundings. Specifically, the laser radar generates a three-dimensional image of the surrounding environment by emitting and receiving laser pulses.

[0073] The ultrasonic signal of the second target is collected by the ultrasonic system, and feature extraction is performed based on the ultrasonic signal of the second target to obtain the distance feature and speed feature of the second target. Specifically, the ultrasonic sensor detects obstacles at a close distance to the vehicle and is mainly used in low-speed and parking environments.

[0074] The second real-time traffic information and the second real-time road information transmitted by the neighboring vehicles are obtained through the communication system, and the second real-time traffic information and the second real-time road information are subjected to feature extraction to obtain the second real-time traffic feature and the second real-time road feature. Specifically, the vehicle exchanges information with other vehicles and traffic infrastructure through wireless communication to obtain real-time traffic conditions and road information.

[0075] S204: Fusing the initial environmental features to obtain target environmental features.

[0076] Among them, the fusion process is based on the classification of each initial environmental feature, wherein it is first determined whether each initial environmental feature belongs to the same category; if the initial environmental features belong to the same category, the target environmental features can be obtained by weighted fusion based on the initial environmental features of the same category; if the initial environmental features belong to different categories, the initial environmental features are spliced.

[0077] For convenience, it is assumed that the initial environmental features include a, b and c, a and b belong to the same first category, and c belongs to the second category. Then a and b are weightedly fused to obtain d, and then d and c are concatenated to obtain the target environmental features.

[0078] S206: Generate a global environment view based on the target environment characteristics.

[0079] The global environment view is a description of the global environment around the vehicle based on the environmental characteristics of each target, which may include but is not limited to various targets around the vehicle, the distance and speed of each target from the vehicle, the real-time traffic conditions of the road ahead and real-time road information, where the traffic conditions may be the traffic signal ahead, and the real-time road information may include whether the road ahead is congested, whether there is an accident, etc.

[0080] In one of the optional embodiments, a global environment view is generated based on target environment features, including: inputting the target environment features into an artificial intelligence network, and fusing a three-dimensional map around the vehicle, a first real-time traffic feature and a first real-time road feature, a distance feature and a speed feature of a first target, a target located around the vehicle, a distance feature and a speed feature of a second target, and a second real-time traffic feature and a second real-time road feature through the artificial intelligence network to obtain a global environment view.

[0081] The artificial intelligence network may be pre-trained, with the input being the target environment features and the output being the global environment view. Therefore, in this embodiment, the target environment features are input into the artificial intelligence network, and the three-dimensional map around the vehicle, the first real-time traffic features and the first real-time road features, the distance features and speed features of the first target, the targets located around the vehicle, the distance features and speed features of the second target, the second real-time traffic features and the second real-time road features are integrated through the artificial intelligence network to obtain a global environment view.

[0082] Specifically, the artificial intelligence network mainly takes the three-dimensional map around the vehicle as a benchmark, and integrates the first real-time traffic feature and the first real-time road feature, the distance feature and the speed feature of the first target, the target located around the vehicle, the distance feature and the speed feature of the second target, the second real-time traffic feature and the second real-time road feature into the three-dimensional map around the vehicle. For example, the matching results of each initial environmental feature in the target environmental feature and the three-dimensional map around the vehicle are determined, and then each initial environmental feature is integrated with the three-dimensional map around the vehicle based on the matching results. The fusion method can be weighted fusion, which is not specifically limited here.

[0083] S208: Process the global environment view to obtain interactive information, and output the interactive information to the screen taillight.

[0084] The global environment view is processed by making rule judgments based on various targets around the vehicle, the distance and speed of each target from the vehicle, the real-time traffic conditions of the road ahead, and real-time road information to obtain interactive information.

[0085] Optionally, different rules have different priorities, so the priority of the rules satisfied by the global environment view can be confirmed first, and then the priority of the interaction information is obtained based on the priority, and the interaction information is output to the screen taillight based on the priority of the interaction information.

[0086] For example, the vehicle can efficiently identify the road ahead that is blocked and respond in time. If an obstacle is detected on the road ahead, it will display "Road ahead is blocked, please detour". If an accident is detected on the road ahead, it will display "Accident ahead, please drive carefully" to ensure driving safety. For example, if the traffic light ahead is red, it will display "Red light ahead, please wait patiently" and other preset words, and control the display content of the taillight screen to remind the vehicles or people behind.

[0087] Car lights no longer have only lighting functions, but are given the mission of intelligent interaction. Intelligent interactive screen taillights can automatically respond to changes in the surrounding environment and adjust their display content in real time according to different driving conditions without the need for manual intervention by the driver. This provides more convenience, allowing drivers to focus more on roads and traffic, helping other drivers to more easily identify and understand the vehicle's intentions, and reducing the risk of traffic accidents.

[0088] The above-mentioned vehicle control method collects vehicle environment information through multiple vehicle environment information collection systems, processes it to obtain initial environment characteristics, fuses the initial environment characteristics to obtain target environment characteristics, and then generates a global environment view based on the target environment characteristics. This can ensure that the global environment view is relatively accurate, and then generate interactive information based on the global environment view to ensure that the interactive information is real-time and effective, and output the interactive information to the screen taillights, so as to provide effective interactive information to other vehicles.

[0089] In one optional embodiment, when the initial environmental features include the distance features and speed features of the first target, the targets around the vehicle, and the distance features and speed features of the second target, that is, when the vehicle surrounding environment information acquisition system includes a radar system, a camera system, and an ultrasonic system, the initial environmental features are fused to obtain the target environmental features, including the following steps, which can be specifically combined with Figure 3 As shown:

[0090] S302: Matching the targets located around the vehicle and the first target to obtain a first matching result.

[0091] The targets located around the vehicle are obtained by extracting the vehicle surrounding environment images captured by the camera system. The targets include but are not limited to vehicles, pedestrians and obstacles. The distance between each target and the vehicle can also be simply obtained from the image information.

[0092] The first target is acquired by the radar system, which includes the distance characteristics and speed characteristics of the target.

[0093] Therefore, when matching, matching can be performed based on distance. In some optional embodiments, when determining the distance of each first target, the radar system can first classify the target based on the radar signal, and then calculate the distance and speed of the first target. Therefore, when matching, the first target and the targets located around the vehicle can be classified first, and then those of the same classification can be matched to determine the first matching result.

[0094] S304: Determine the distance characteristics and speed characteristics of each target located around the vehicle based on the first matching result.

[0095] After the matching is successful, the distance characteristics and speed characteristics of the corresponding targets located around the vehicle can be obtained based on the distance characteristics and speed characteristics of the first target collected by the radar system to improve accuracy.

[0096] S306: Match the second target with targets located around the vehicle to obtain a second matching result.

[0097] The targets located around the vehicle are obtained by extracting the vehicle surrounding environment images captured by the camera system. The targets include but are not limited to vehicles, pedestrians and obstacles. The distance between each target and the vehicle can also be simply obtained from the image information.

[0098] The second target is acquired by the ultrasonic system, which includes the distance characteristics and speed characteristics of the target.

[0099] Therefore, when matching, matching can be performed based on distance. In some optional embodiments, when determining the distance of each second target, the ultrasonic system can first classify the target based on the ultrasonic signal, and then calculate the distance and speed of the first target. Therefore, when matching, the second target and the target located around the vehicle can be classified first, and then the targets of the same classification can be matched to determine the second matching result.

[0100] S308: Based on the second matching result and the distance feature and speed feature of the second target, correct the distance feature and speed feature of the target located around the vehicle.

[0101] After the matching is successful, the distance characteristics and speed characteristics of the corresponding targets located around the vehicle can be obtained based on the distance characteristics and speed characteristics of the second target collected by the ultrasonic system to improve accuracy.

[0102] During the correction, it can be determined whether the distance characteristics and speed characteristics of the targets around the vehicle have been corrected by the radar system. If so, the distance characteristics and speed characteristics of the target obtained by the radar system are weightedly fused with the distance characteristics and speed characteristics of the target obtained by the ultrasonic system; if not, the distance characteristics and speed characteristics of the target obtained by the ultrasonic system are used as the distance characteristics and speed characteristics of the target.

[0103] In the above embodiment, the initial environmental features acquired by different vehicle environmental information acquisition systems may be fused to improve the accuracy of the target environmental features.

[0104] In one of the optional embodiments, in combination Figure 4 As shown, Figure 4 Flow chart of the steps of obtaining the distance feature and the speed feature in one embodiment. In this embodiment, the distance feature and the speed feature of the first target are obtained by performing feature extraction based on the radar signal of the first target, including:

[0105] S402: Obtain vehicle speed and radar signal speed.

[0106] The speed of the radar signal is the propagation speed of the electromagnetic wave, and the speed of the vehicle can be directly obtained.

[0107] S404: Acquire a first time interval of a radar signal returned in a previous test cycle and a second time interval of a radar signal returned in a current test cycle.

[0108] The first time interval of the radar signal returned in the previous test cycle, that is, the first time interval from the sending to the receiving of the previous radar signal.

[0109] The second time interval of the radar signal returned in the current test cycle is the second time interval from the sending to the receiving of the current radar signal.

[0110] S406: Obtaining a distance feature of the first target based on the vehicle speed, the radar signal speed, and the second time interval.

[0111] The current distance characteristic of the first target is (radar signal speed*second time interval−vehicle speed*second time interval) / 2.

[0112] S408: Obtaining a first distance feature of the first target based on the vehicle speed, the radar signal speed, and the first time interval.

[0113] Likewise, the first distance feature is (radar signal speed*first time interval−vehicle speed*first time interval) / 2.

[0114] S410: Obtaining a speed feature of the first target based on a current distance feature, a first distance feature, a first time interval, a second time interval, and a vehicle speed.

[0115] Since the two radar signals are transmitted at different times, the speed characteristic of the first target can be obtained based on this. Specifically, the speed characteristic of the first target = current distance characteristic - first distance characteristic) / (second time interval - first time interval) - vehicle speed.

[0116] In the above embodiment, the distance characteristics and speed characteristics of different first targets can be acquired by radar, laying a foundation for the subsequent extraction of initial environmental characteristics.

[0117] In other embodiments, radar signals may be classified based on the test distance range of the radar sensor and then processed in parallel to obtain distance characteristics and speed characteristics of targets in different distance ranges.

[0118] In one of the optional embodiments, the global environment view is processed to obtain interaction information, including: obtaining a preconfigured rule set, the rule set includes each processing rule subset, each processing rule subset includes a condition and interaction information; extracting the to-be-processed environment features corresponding to each processing rule subset from the global environment view; when the to-be-processed environment features meet the conditions, obtaining interaction information corresponding to the conditions.

[0119] The preconfigured rule set includes multiple rule subsets, each rule subset includes at least one rule, and the rule subset includes conditions and interaction information.

[0120] During processing, the to-be-processed environment features corresponding to each processing rule subset may be first extracted from the global environment view, and then it is determined whether the to-be-processed environment features meet the conditions of the rule subset. If so, the interaction information is obtained.

[0121] Optionally, when extracting the environmental features to be processed, the priority of each processing rule subset can be determined first, and the environmental features to be processed corresponding to each processing rule subset can be extracted from the global environment view in turn based on the priority and processed, so as to obtain multiple interactive information, and then the screen taillights can be controlled to play these interactive information in a loop.

[0122] In the above embodiments, the required sensors can be installed according to the scene requirements. For example, distance sensors (such as ultrasonic sensors or lidars) can be used to detect objects or vehicles close to the rear of the vehicle, cameras can be used to identify traffic signs, other vehicles or road markings, and sound sensors can be used to monitor the sound or noise level in the surrounding environment. They can trigger the reaction of the taillights, such as displaying warning patterns in sudden braking or emergency situations. These sensor types can be combined and integrated according to the design and functional requirements of the interactive taillights. The real-time data collected by the sensors is analyzed and processed by a high-performance processor, and a specific control algorithm is used to adjust the screen display in real time. Pre-set scene characters or images, such as "The road ahead is blocked, please detour", "Accident ahead, please drive carefully", "Red light ahead, please wait patiently" or real-time traffic information and warnings are displayed on the screen taillights through the LED display module, providing a reference for pedestrians and vehicles behind participating in the passage, so as to alleviate the impatience or irritability caused by traffic jams and enhance driving safety and comfort.

[0123] It should be understood that, although the steps in the flowcharts involved in the above embodiments are displayed in sequence according to the indication of the arrows, these steps are not necessarily executed in sequence according to the order indicated by the arrows. Unless there is a clear explanation in this article, the execution of these steps is not strictly limited in order, and these steps can be executed in other orders. Moreover, at least a part of the steps in the flowcharts involved in the above embodiments may include multiple steps or multiple stages, and these steps or stages are not necessarily executed at the same time, but can be executed at different times, and the execution order of these steps or stages is not necessarily carried out in sequence, but can be executed in turn or alternately with other steps or at least a part of the steps or stages in other steps.

[0124] Based on the same inventive concept, the embodiment of the present application also provides a vehicle control device for implementing the vehicle control method involved above. The implementation scheme for solving the problem provided by the device is similar to the implementation scheme recorded in the above method, so the specific limitations in one or more vehicle control device embodiments provided below can refer to the limitations on the vehicle control method above, and will not be repeated here.

[0125] In an exemplary embodiment, Figure 5 As shown, a vehicle control device is provided, including: a collection module 501, a feature fusion module 502, a global environment view generation module 503 and a decision module 504, wherein:

[0126] The acquisition module 501 is used to acquire vehicle environment information collected by at least one type of vehicle environment information acquisition system, and extract features from each vehicle environment information to obtain each initial environment feature;

[0127] A feature fusion module 502 is used to fuse the initial environment features to obtain the target environment features;

[0128] A global environment view generation module 503, used to generate a global environment view based on target environment features;

[0129] The decision module 504 is used to process the global environment view to obtain interaction information, and output the interaction information to the screen taillight.

[0130] In one of the optional embodiments, the acquisition module 501 is specifically used to acquire each initial environmental feature based on any one of the following: first real-time traffic information and first real-time road information acquired by a navigation system, and feature extraction of the first real-time traffic information and the first real-time road information to obtain first real-time traffic features and first real-time road features; radar signals of a first target acquired by a radar system, and feature extraction based on the radar signals of the first target to obtain distance features and speed features of the first target; images of the vehicle surroundings acquired by a camera system, and feature extraction of the images of the vehicle surroundings to obtain targets located around the vehicle; radar laser signals acquired by a radar laser system, and feature extraction based on the radar laser signals to obtain a three-dimensional map around the vehicle; ultrasonic signals of a second target acquired by an ultrasonic system, and feature extraction based on the ultrasonic signals of the second target to obtain distance features and speed features of the second target; and second real-time traffic information and second real-time road information transmitted by neighboring vehicles acquired by a communication system, and feature extraction of the second real-time traffic information and the second real-time road information to obtain second real-time traffic features and second real-time road features.

[0131] In one of the optional embodiments, the feature fusion module 502 is specifically used to match the targets located around the vehicle with the first target to obtain a first matching result; determine the distance characteristics and speed characteristics of each target located around the vehicle based on the first matching result; match the second target with the target located around the vehicle to obtain a second matching result; and correct the distance characteristics and speed characteristics of the targets located around the vehicle based on the second matching result and the distance characteristics and speed characteristics of the second target.

[0132] In one of the optional embodiments, the global environment view generation module 503 is specifically used to input the target environment characteristics into the artificial intelligence network, and integrate the three-dimensional map around the vehicle, the first real-time traffic characteristics and the first real-time road characteristics, the distance characteristics and speed characteristics of the first target, the target located around the vehicle, the distance characteristics and speed characteristics of the second target, and the second real-time traffic characteristics and the second real-time road characteristics through the artificial intelligence network to obtain a global environment view.

[0133] In one of the optional embodiments, the feature fusion module 502 is specifically used to obtain the vehicle speed and the radar signal speed; obtain the first time interval of the radar signal returned in the previous test cycle and the second time interval of the radar signal returned in the current test cycle; obtain the distance feature of the first target based on the vehicle speed, the radar signal speed and the second time interval; obtain the first distance feature of the first target based on the vehicle speed, the radar signal speed and the first time interval; obtain the speed feature of the first target based on the current distance feature, the first distance feature, the first time interval, the second time interval and the vehicle speed.

[0134] In one of the optional embodiments, the above-mentioned decision module 504 is specifically used to obtain a pre-configured rule set, the rule set includes various processing rule subsets, each processing rule subset includes conditions and interaction information; extract the to-be-processed environment features corresponding to each processing rule subset from the global environment view; when the to-be-processed environment features meet the conditions, obtain the interaction information corresponding to the conditions.

[0135] Each module in the above vehicle control device can be implemented in whole or in part by software, hardware or a combination thereof. Each module can be embedded in or independent of a processor in a computer device in the form of hardware, or can be stored in a memory in a computer device in the form of software, so that the processor can call and execute the operations corresponding to each module.

[0136] In an exemplary embodiment, a computer device is provided. The computer device may be a terminal, and its internal structure diagram may be as shown in FIG. Figure 6As shown. The computer device includes a processor, a memory, an input / output interface, a communication interface, a display unit and an input device. Among them, the processor, the memory and the input / output interface are connected through a system bus, and the communication interface, the display unit and the input device are connected to the system bus through the input / output interface. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The input / output interface of the computer device is used to exchange information between the processor and an external device. The communication interface of the computer device is used to communicate with an external terminal in a wired or wireless manner, and the wireless manner can be implemented through WIFI, a mobile cellular network, NFC (near field communication) or other technologies. When the computer program is executed by the processor, a vehicle control method is implemented. The display unit of the computer device is used to form a visually visible picture, which can be a display screen, a projection device or a virtual reality imaging device. The display screen can be a liquid crystal display screen or an electronic ink display screen, and the input device of the computer device can be a touch layer covering the display screen, or a button, trackball or touchpad set on the computer device shell, or an external keyboard, touchpad or mouse.

[0137] Those skilled in the art will understand that Figure 6 The structure shown in the figure is only a block diagram of a part of the structure related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than those shown in the figure, or combine certain components, or have a different arrangement of components.

[0138] In one embodiment, a computer device is further provided, including a memory and a processor, wherein a computer program is stored in the memory, and the processor implements the steps in the above method embodiments when executing the computer program.

[0139] In one embodiment, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, the steps in the above-mentioned method embodiments are implemented.

[0140] In one embodiment, a computer program product is provided, including a computer program, which implements the steps in the above method embodiments when executed by a processor.

[0141] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, stored data, displayed data, etc.) 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 regulations.

[0142] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to the memory, database or other medium used in the embodiments provided in the present application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetoresistive random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. As an illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM). The database involved in each embodiment provided in this application may include at least one of a relational database and a non-relational database. Non-relational databases may include distributed databases based on blockchains, etc., but are not limited to this. The processor involved in each embodiment provided in this application may be a general-purpose processor, a central processing unit, a graphics processor, a digital signal processor, a programmable logic device, a data processing logic device based on quantum computing, etc., but are not limited to this.

[0143] The technical features of the above embodiments may be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0144] The above-described embodiments only express several implementation methods of the present application, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the scope of the present application. It should be pointed out that, for a person of ordinary skill in the art, several variations and improvements can be made without departing from the concept of the present application, and these all belong to the protection scope of the present application. Therefore, the protection scope of the present application shall be subject to the attached claims.

Claims

1. A vehicle control method, characterized in that: The method comprises: Acquire vehicle environment information collected by at least one type of vehicle environment information collection system, and extract features from each of the vehicle environment information to obtain initial environment features; Fusing the initial environmental features to obtain target environmental features; generating a global environment view based on the target environment characteristics; The global environment view is processed to obtain interaction information, and the interaction information is output to a screen taillight.

2. The method according to claim 1, characterized in that The acquiring of vehicle environment information collected by at least one type of vehicle environment information collection system, and performing feature extraction on each of the vehicle environment information to obtain each initial environment feature, includes at least one of the following: The first real-time traffic information and the first real-time road information are acquired by the navigation system, and features are extracted from the first real-time traffic information and the first real-time road information to obtain first real-time traffic features and first real-time road features; A radar signal of a first target collected by a radar system is used to extract a distance feature and a speed feature of the first target based on the radar signal of the first target; The vehicle surrounding environment image is captured by the camera system, and features are extracted from the vehicle surrounding environment image to obtain targets located around the vehicle; Collecting radar laser signals through a radar laser system, and performing feature extraction based on the radar laser signals to obtain a three-dimensional map around the vehicle; The ultrasonic signal of the second target is collected by the ultrasonic system, and feature extraction is performed based on the ultrasonic signal of the second target to obtain a distance feature and a speed feature of the second target; and The second real-time traffic information and the second real-time road information transmitted by the neighboring vehicles are acquired through the communication system, and the second real-time traffic information and the second real-time road information are subjected to feature extraction to obtain the second real-time traffic feature and the second real-time road feature.

3. The method according to claim 2, characterized in that The step of fusing the initial environmental features to obtain the target environmental features includes: Matching the target located around the vehicle and the first target to obtain a first matching result; Determine the distance feature and the speed feature of each of the targets located around the vehicle based on the first matching result; Matching the second target with the target located around the vehicle to obtain a second matching result; Based on the second matching result and the distance feature and the speed feature of the second target, the distance feature and the speed feature of the target located around the vehicle are corrected.

4. The method according to claim 2, characterized in that: The generating a global environment view based on the target environment feature comprises: The target environment characteristics are input into an artificial intelligence network, and the three-dimensional map around the vehicle, the first real-time traffic characteristics and the first real-time road characteristics, the distance characteristics and the speed characteristics of the first target, the target located around the vehicle, the distance characteristics and the speed characteristics of the second target, and the second real-time traffic characteristics and the second real-time road characteristics are integrated through the artificial intelligence network to obtain a global environment view.

5. The method according to claim 2, characterized in that: The extracting features based on the radar signal of the first target to obtain the distance feature and the speed feature of the first target includes: Obtain vehicle speed and radar signal speed; Obtaining a first time interval of a radar signal returned in a previous test cycle and a second time interval of a radar signal returned in a current test cycle; Obtaining a distance characteristic of the first target based on the vehicle speed, the radar signal speed, and the second time interval; Obtaining a first distance feature of the first target based on the vehicle speed, the radar signal speed, and the first time interval; A speed feature of the first target is obtained based on the current distance feature, the first distance feature, the first time interval, the second time interval, and the vehicle speed.

6. The method according to any one of claims 1 to 5, characterized in that: The processing of the global environment view to obtain the interaction information includes: Acquire a preconfigured rule set, the rule set comprising processing rule subsets, each of the processing rule subsets comprising a condition and interaction information; Extracting the to-be-processed environment features corresponding to each of the processing rule subsets from the global environment view; When the to-be-processed environmental feature satisfies the condition, the interaction information corresponding to the condition is acquired.

7. A vehicle control device, characterized in that: The device comprises: A collection module, used to obtain vehicle environment information collected by at least one type of vehicle environment information collection system, and extract features from each of the vehicle environment information to obtain each initial environment feature; A feature fusion module, used to fuse the initial environment features to obtain target environment features; A global environment view generation module, used to generate a global environment view based on the target environment characteristics; The decision module is used to process the global environment view to obtain interaction information and output the interaction information to the screen taillight.

8. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 6 are implemented.

9. A computer-readable storage medium having a computer program stored thereon, 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 6 are implemented.

10. 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 6 are implemented.

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