Vehicle alarm method and device, vehicle, cloud, chip and storage medium

Abstract

The invention provides a vehicle alarm method and device, a vehicle, a cloud, a chip and a storage medium, and relates to the field of artificial intelligence technology and intelligent cabins, and the method comprises the steps: obtaining data collected by a sensor in a target area; wherein the target area is a target racing track and / or an area near the target racing track; sending first alarm information to the target vehicle in response to the obstacle information contained in the data acquired by the sensor; wherein the target vehicle is the vehicle participating in the competition in the target racing track. Therefore, the obstacle information in the environment where the target vehicle is located can be obtained and recognized in real time, the timeliness of recognizing obstacles (including racing track marks, racing track service facilities and dynamic obstacles temporarily invading racing tracks) is improved, a racing driver (or a driver) can know the front road condition more timely and accurately, and the accuracy of identification is improved. Therefore, a safer and more effective driving decision is made, and the safety of vehicle driving is improved.

Description

Technical Field

[0001] This application relates to the fields of artificial intelligence technology and smart cockpit, and more particularly to a vehicle alarm method, device, vehicle, cloud, chip, and storage medium. Background Technology

[0002] With the continuous development and popularization of motorsport, track safety and the level of sophistication in event management have become important indicators for measuring event organization capabilities. Against this backdrop, large racetracks are placing higher demands on dynamic environmental monitoring and emergency response mechanisms during races.

[0003] In actual races, track operators often need to set up temporary markers on the track according to the schedule or on-site conditions. For example, physical cones are placed at key corners or straights to mark braking points, entry points, or exit points, helping drivers better understand their driving lines. At the same time, unplanned obstacles may also intrude into the track, such as cats, dogs, or other foreign objects suddenly entering the track area. These can threaten the safe driving of vehicles, or even cause accidents, resulting in the interruption or delay of the race. Summary of the Invention

[0004] This application aims to at least partially address one of the technical problems in the related art.

[0005] To this end, this application proposes a vehicle warning method, device, vehicle, cloud platform, chip, and storage medium to achieve real-time acquisition and identification of obstacle information in the target vehicle's environment, and to issue vehicle warnings accordingly. This improves the timeliness of obstacle identification (including track markings, track service facilities, and dynamic obstacles temporarily encroaching on the track), allowing race car drivers to understand the road conditions ahead more promptly and accurately, thus making safer and more effective driving decisions and improving vehicle safety. Furthermore, it enables efficient monitoring and immediate feedback of track conditions, reducing race interruptions or delays caused by untimely manual checks, which helps maintain the smooth flow of the race and ensures that it proceeds as planned.

[0006] One embodiment of this application proposes a vehicle alarm method, including:

[0007] Acquire data collected by sensors within the target area; wherein the target area is the target track and / or the area near the target track;

[0008] In response to the data collected by the sensor containing obstacle information, a first warning message is issued to the target vehicle; wherein, the target vehicle is a vehicle participating in the race on the target track.

[0009] Another embodiment of this application proposes a different vehicle alarm method, including:

[0010] Acquire data collected by sensors within the target area; wherein the target area is the target track and / or the area near the target track;

[0011] Based on the scene feature library associated with the target track, obstacle detection is performed on the data collected by the sensors to obtain obstacle information;

[0012] The obstacle information is sent to the target vehicle; wherein the target vehicle is a vehicle participating in the race on the target track, and the obstacle information is used to issue an alarm to the target vehicle.

[0013] Another aspect of this application provides a vehicle warning device, comprising:

[0014] An acquisition module is used to acquire data collected by sensors within a target area; wherein, the target area is the target track and / or the area near the target track;

[0015] An alarm module is used to issue a first alarm message to the target vehicle in response to the data collected by the sensor containing obstacle information; wherein the target vehicle is a vehicle participating in the race on the target track.

[0016] Another embodiment of this application provides another vehicle warning device, including:

[0017] An acquisition module is used to acquire data collected by sensors within a target area; wherein, the target area is the target track and / or the area near the target track;

[0018] The detection module is used to perform obstacle detection on the data collected by the sensors based on the scene feature library associated with the target track, and obtain obstacle information;

[0019] The sending module is used to send the obstacle information to the target vehicle; wherein the target vehicle is a vehicle participating in the race on the target track, and the obstacle information is used to issue an alarm to the target vehicle.

[0020] Another embodiment of this application provides a vehicle, including: a processor; a memory for storing processor-executable instructions; wherein the processor is configured to implement the vehicle alarm method as described in the foregoing aspect.

[0021] In another aspect of this application, a cloud-based system is provided, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the program, it implements the vehicle alarm method as described in the other aspect above.

[0022] Another aspect of this application provides a chip including an interface circuit and a processing circuit coupled to each other. The interface circuit is used to input or output signals, and the processing circuit is configured to perform a vehicle alarm method as described in one aspect above, and / or to perform a vehicle alarm method as described in another aspect above.

[0023] In another aspect of this application, a non-transitory computer-readable storage medium is provided, on which computer program instructions are stored, which, when executed by a processor, implement the vehicle alarm method as described in the foregoing aspect, and / or, when executed, implement the vehicle alarm method as described in the foregoing other aspect.

[0024] Another aspect of this application provides a computer program product having a computer program stored thereon, which, when executed by a processor, implements the vehicle alarm method as described in the foregoing aspect, and / or, when executed, implements the vehicle alarm method as described in the foregoing aspect.

[0025] The vehicle warning method, device, vehicle, cloud platform, chip, and storage medium proposed in this application detect obstacles in data collected by sensors in the target track and / or the area near the target track, obtain obstacle information, and issue vehicle warnings based on the obstacle information. This method has at least the following advantages: First, it can acquire and identify obstacle information in the vehicle's environment in real time. Compared to traditional methods relying on manual patrols or race announcements, this significantly improves the timeliness of obstacle identification (including track markings, track service facilities, and dynamic obstacles temporarily encroaching on the track), allowing racers (or drivers) to understand the road conditions ahead more promptly and accurately, thus making safer and more effective driving decisions and improving vehicle safety. Second, it can not only identify static obstacles, such as track elements (including track markings, track service equipment, etc.), but also effectively detect dynamic obstacles on the track, such as movable targets (including animals or other foreign objects encroaching on the track). Once a potential threat is detected, the vehicle can issue a warning based on the obstacle information, notifying the racer in advance to take appropriate measures to avoid potential collisions, greatly enhancing the safety of the race. Third, it enables efficient monitoring and real-time feedback of track conditions, reducing race interruptions or delays caused by untimely manual checks. This helps maintain the smooth flow of the race and ensures it proceeds as planned. Fourth, accurate and timely obstacle detection and warning mechanisms help drivers better understand track dynamics, allowing them to focus on driving skills rather than dealing with unexpected situations. This enables drivers to enjoy the thrill of racing while ensuring safety, thus enhancing the overall driving experience.

[0026] Additional aspects and advantages of this application will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of this application. Attached Figure Description

[0027] The above and / or additional aspects and advantages of this application will become apparent and readily understood from the following description of the embodiments taken in conjunction with the accompanying drawings, wherein:

[0028] Figure 1 A schematic flowchart illustrating a vehicle alarm method provided for an exemplary embodiment of this application;

[0029] Figure 2 A schematic diagram of a scene feature library provided for an exemplary embodiment of this application;

[0030] Figure 3 A flowchart illustrating another vehicle alarm method provided for an exemplary embodiment of this application;

[0031] Figure 4 A schematic flowchart illustrating yet another vehicle alarm method provided for an exemplary embodiment of this application;

[0032] Figure 5 A flowchart illustrating another vehicle alarm method provided for an exemplary embodiment of this application;

[0033] Figure 6 A flowchart illustrating another vehicle alarm method provided for an exemplary embodiment of this application;

[0034] Figure 7 A flowchart illustrating another vehicle alarm method provided for an exemplary embodiment of this application;

[0035] Figure 8 A flowchart illustrating another vehicle alarm method provided for an exemplary embodiment of this application;

[0036] Figure 9 A schematic flowchart illustrating yet another vehicle alarm method provided for an exemplary embodiment of this application;

[0037] Figure 10 A schematic diagram showing the display position of the track marker provided for an exemplary embodiment of this application;

[0038] Figure 11 A schematic diagram illustrating the process of generating, updating, and synchronizing a scene feature library provided for an exemplary embodiment of this application;

[0039] Figure 12 A schematic diagram illustrating the obstacle recognition principle provided for an exemplary embodiment of this application;

[0040] Figure 13 A schematic diagram of the structure of a vehicle warning device provided for an exemplary embodiment of this application;

[0041] Figure 14 A schematic diagram of the structure of another vehicle warning device provided for an exemplary embodiment of this application;

[0042] Figure 15 A block diagram illustrating a vehicle according to an exemplary embodiment;

[0043] Figure 16 This is a schematic diagram of the structure of a chip proposed in an exemplary embodiment of this application. Detailed Implementation

[0044] The embodiments of this application are described in detail below. Examples of these embodiments are shown in the accompanying drawings, wherein the same or similar reference numerals denote the same or similar elements or elements having the same or similar functions throughout. The embodiments described below with reference to the accompanying drawings are exemplary and intended to explain this application, and should not be construed as limiting this application.

[0045] In related technologies, the focus is on manual patrols by track staff or announcements from race organizers to alert drivers to temporary track markings or obstacles, thus assisting them in driving.

[0046] However, the above methods not only have problems such as insufficient timeliness and inadequate location accuracy, but may also lead to vehicle accidents and event delays.

[0047] Therefore, in view of at least one of the problems existing in the above-mentioned related technologies, this application proposes a vehicle alarm method, device, vehicle, cloud, chip and storage medium.

[0048] The vehicle alarm method, apparatus, vehicle, cloud, chip, and storage medium of this application are described below with reference to the accompanying drawings.

[0049] Figure 1 This is a flowchart illustrating a vehicle alarm method provided for an exemplary embodiment of this application.

[0050] It should be noted that the vehicle alarm method of this application embodiment can be applied to a vehicle alarm device. In some possible embodiments, the vehicle alarm device can be configured in a vehicle or a chip so that the vehicle or chip can perform vehicle alarm functions. In addition, in some possible embodiments, the vehicle alarm device can also be software or an application (APP) in the vehicle.

[0051] In any embodiment of this application, the chip can be integrated into a vehicle. The chip includes a Central Processing Unit (CPU), Image Signal Processing (ISP), Application-Specific Integrated Circuit (ASIC), Digital Signal Processor (DSP), Field-Programmable Gate Array (FPGA), System on Chip (SOC), Reduced Instruction Set Computer (RISC), etc., which will not be listed here.

[0052] The vehicle can be a hybrid vehicle, a non-hybrid vehicle, an electric vehicle, a fuel cell vehicle, or other types of vehicles, and this application embodiment does not limit this.

[0053] For ease of explanation, the following description will use a vehicle (such as the target vehicle) as the executing entity of this vehicle alarm method. The target vehicle can be any vehicle participating in the race on the target track.

[0054] like Figure 1 As shown, the vehicle alarm method may include the following steps S101 to S102:

[0055] Step S101: Obtain data collected by sensors within the target area; wherein, the target area is the target track and / or the area near the target track.

[0056] The target track includes any track in a racetrack.

[0057] The area near the target track refers to the area where the distance to the target track is less than a set distance threshold.

[0058] The sensor (or data acquisition device) includes at least one of the following: on-board sensor on a vehicle participating in the race on the target track, sensor deployed on the target track, sensor deployed on both sides of the target track, sensor deployed in the area near the target track, and sensor deployed in the racetrack to which the target track belongs.

[0059] The data collected by the sensors includes, but is not limited to, images, videos, or video streams.

[0060] In the case where the sensor is mounted on the vehicle, the sensor can be an onboard camera or a multi-sensor fusion system that includes radar and a camera. The onboard camera can be an external camera mounted on the vehicle and can have surround-view functionality.

[0061] It should be noted that, to improve the comprehensiveness and accuracy of data collection, the number of sensors can be multiple, such as multiple vehicle-mounted cameras. These multiple cameras can be distributed in different locations within the vehicle as needed. "Multiple" means at least two, such as two, three, four, etc.

[0062] Understandably, by using multiple sensors to collect data from different angles, more comprehensive and richer information about road conditions and obstacles can be obtained. This helps reduce misjudgments that may result from a single perspective, thereby improving the accuracy of obstacle identification.

[0063] Step S102: In response to the obstacle information contained in the data collected by the sensor, a first alarm message is sent to the target vehicle; wherein, the target vehicle is a vehicle participating in the race on the target track.

[0064] The obstacle information is obtained by detecting obstacles from data collected by sensors. The obstacle information includes at least one of the following: the category (or object category) to which the obstacle belongs, the geographical location of the obstacle (such as its deployment location), and the direction of the obstacle relative to the target vehicle.

[0065] Geographical location includes, but is not limited to: absolute coordinates in a geographic coordinate system (i.e., latitude and longitude coordinates), absolute or relative position in a Cartesian coordinate system, etc.

[0066] Obstacles include, but are not limited to, track elements and / or movable targets. For example, obstacles may also include static targets that intrude into the target track, such as trash cans.

[0067] Among them, movable targets include, but are not limited to, obstacles that intrude into the target track, such as animals, pets, toy cars, and low-flying drones.

[0068] Track elements may include track signage and / or track service facilities, wherein track signage includes, but is not limited to: Figure 2 The braking points, entry points, apex points, speed gates, etc. shown are included. Track service facilities include, but are not limited to, rescue vehicles and repair shops.

[0069] In any embodiment of this application, while the target vehicle is driving on the target track, the target vehicle can perform obstacle detection on the data collected by sensors within the target area to obtain obstacle information. For example, the target vehicle can perform obstacle detection on the data collected by sensors within the target area based on a scene feature library associated with the target track to obtain obstacle information.

[0070] The scene feature library can include feature maps of various types of track elements. For example, taking track identifiers as an example, the scene feature library can include, for instance, track identifiers included in track elements. Figure 2 Feature diagrams of each track marker shown.

[0071] As an example, firstly, the target vehicle can extract features from the data collected by sensors in the target area to obtain target features. Then, the target features can be matched with the feature maps of various track elements in the scene feature library to obtain a first recognition result. Then, an obstacle detection algorithm (or target detection algorithm, target tracking algorithm) is used to identify obstacles in the target features to obtain a second recognition result. Thus, in this application, obstacle information can be generated based on the first recognition result and the second recognition result.

[0072] The first identification result is used to indicate at least one of the category, geographical location, and orientation of the track element existing in the target area, or the first identification result is used to indicate that there is no track element in the target area. That is, the first identification result is used to indicate whether there is a track element in the target area. If there is, the first identification result is also used to indicate at least one of the category, geographical location, and orientation of the track element.

[0073] The second identification result is used to indicate at least one of the category, geographical location, and orientation of the movable target within the target area; or, the second identification result is used to indicate that there is no movable target within the target area. That is, the second identification result is used to indicate whether there is a movable target within the target area. If there is, the second identification result is also used to indicate at least one of the category, geographical location, and orientation of the movable target.

[0074] In any embodiment of this application, while the target vehicle is traveling on the target track, obstacle detection can be performed on the data collected by sensors within the target area via the cloud to obtain obstacle information. For example, the cloud can perform obstacle detection on the data collected by sensors within the target area based on a scene feature library associated with the target track to obtain obstacle information.

[0075] As an example, while the target vehicle is driving on the target track, each sensor in the target area can upload or send the data it collects to the cloud in real time. Correspondingly, after receiving the data collected by each sensor, the cloud can perform obstacle detection on the data collected by the sensor based on the scene feature library associated with the target track, obtain obstacle information, and send the obstacle information to the target vehicle.

[0076] In this embodiment of the application, the target vehicle can also generate and issue a first alarm message based on obstacle information. For example, the target vehicle can generate and issue the first alarm message based on obstacle information and the actual position of the target vehicle. The actual position of the target vehicle and the geographical location of the obstacle can be coordinates within the same coordinate system.

[0077] As an example, when the obstacle information includes the obstacle's category and geographical location, the distance between the target vehicle and the obstacle can be determined based on the obstacle's geographical location and the target vehicle's actual location. Based on the distance to the obstacle and the type of obstacle, it can be determined whether the obstacle reaches a danger level. If so, a first alarm message is generated and sent to the target vehicle.

[0078] The alarm methods for the first alarm message include, but are not limited to: audible alarms, visual cues (such as icons on the dashboard or warning messages on the in-vehicle display), and tactile feedback (such as steering wheel vibration).

[0079] As another example, if the obstacle information includes the category to which the obstacle belongs, a first alarm message matching the category to which the obstacle belongs can be generated and sent to the target vehicle.

[0080] In other words, this application can issue different types of warning messages based on different categories of obstacles. For example, a high-level warning can be issued if there is a living organism in the target track; a medium-level warning can be issued if there is an object at the edge of the target track; and a low-level warning can be issued if there is a plastic bag within the space of the target track.

[0081] Optionally, if the obstacle information includes the category to which the obstacle belongs, a first risk level posed by the obstacle to the safe driving of the target vehicle can be determined based on the category to which the obstacle belongs, and a first alarm message can be generated based on the first risk level and sent to the target vehicle.

[0082] Among them, the first risk level of dynamic obstacles is higher than that of static obstacles. For dynamic obstacles, the first risk level of obstacles with vital signs (i.e., living things) is higher than that of non-living things.

[0083] In summary, by determining the risk level posed by an obstacle to the safe driving of a target vehicle based on its category, and generating and issuing different types of warning messages accordingly, driving safety and decision-making efficiency can be significantly improved. This method can accurately identify and distinguish between high-risk obstacles (such as dynamic living things) and low-risk obstacles (such as static non-living things), enabling drivers or intelligent driving systems to take appropriate countermeasures in the first instance, thereby effectively preventing potential accidents, reducing the incidence of traffic accidents, and improving driving safety and road use efficiency.

[0084] As another example, when the obstacle information includes the obstacle's orientation relative to the target vehicle, an alarm area matching the obstacle's orientation can be determined from the target vehicle's display interface, and the first alarm information can be displayed through the alarm area.

[0085] For example, if the obstacle is located to the left front of the target vehicle, the first warning message can be displayed in the left area of ​​the target vehicle's head-up display (HUD) interface; if the obstacle is located to the right front of the target vehicle, the first warning message can be displayed in the right area of ​​the target vehicle's HUD interface; and if the obstacle is located directly in front of the target vehicle, the first warning message can be displayed in the middle area of ​​the HUD interface.

[0086] Understandably, displaying warning information in an area that matches the actual location of the obstacle (such as the left side of the HUD interface corresponding to an obstacle in the left front) can help drivers quickly and intuitively locate the obstacle, reduce judgment time, and improve response efficiency. Furthermore, this spatially consistent design (visual direction consistent with the real environment) eliminates the need for race car drivers to perform "information conversion" processing (e.g., searching for the obstacle after hearing an audible warning), thereby reducing cognitive burden and allowing them to focus more on driving operations.

[0087] As another example, when the obstacle information includes the geographical location of the obstacle, the distance between the target vehicle and the obstacle can be determined based on the geographical location of the obstacle and the actual location of the target vehicle. Based on the distance to the obstacle, a first alarm message matching the distance can be generated and sent to the target vehicle.

[0088] In this application, different warning messages can be issued based on the distance of obstacles. For example, a high-level warning can be issued when the distance between the obstacle and the target vehicle is relatively close; a medium-level warning can be issued when the distance between the obstacle and the target vehicle is relatively moderate; and a low-level warning can be issued when the distance between the obstacle and the target vehicle is relatively far.

[0089] Optionally, a second risk level posed by the obstacle to the safe driving of the target vehicle can be determined based on the distance of the obstacle. A first alarm message can then be generated based on the second risk level and sent to the target vehicle. In other words, in this application, different levels of alarm content can be displayed based on the distance between the obstacle and the target vehicle.

[0090] Among them, the second risk level is negatively correlated with distance; that is, the smaller the distance, the higher the second risk level, and vice versa.

[0091] In summary, by dynamically determining the second risk level posed by the obstacle to the target vehicle based on the distance between the obstacle and the target vehicle, and generating and issuing different levels of warning information accordingly, this mechanism facilitates more refined and intelligent driver assistance decisions. The second risk level is negatively correlated with distance (i.e., the smaller the distance, the higher the risk). This mechanism provides tiered warning prompts at different stages of the obstacle's approach to the target vehicle, enabling race car drivers or intelligent driving systems to perceive potential threats in advance and take appropriate countermeasures based on the risk level. This not only improves the real-time performance and accuracy of vehicle warnings but also effectively avoids "warning fatigue," enhancing the user experience and significantly improving driving safety and the practicality of intelligent driving systems.

[0092] The vehicle warning method of this application embodiment detects obstacles in data collected by sensors in the target track and / or the area near the target track to obtain obstacle information, and issues vehicle warnings based on the obstacle information. It has at least the following advantages: First, it can acquire and identify obstacle information in the vehicle's environment in real time. Compared with traditional methods that rely on manual patrols or race announcements, this method greatly improves the timeliness of obstacle identification (including track markings, track service facilities, and dynamic obstacles temporarily encroaching on the track), allowing racers (or drivers) to understand the road conditions ahead more promptly and accurately, thereby making safer and more effective driving decisions and improving vehicle safety. Second, it can not only identify static obstacles, such as track elements (including track markings, track service equipment, etc.), but also effectively detect dynamic obstacles on the track, such as movable targets (including animals or other foreign objects encroaching on the track). Once a potential threat is detected, the vehicle can issue a warning based on the obstacle information, notifying the racer in advance to take appropriate measures to avoid potential collisions, greatly enhancing the safety of the race. Third, it enables efficient monitoring and real-time feedback of track conditions, reducing race interruptions or delays caused by untimely manual checks. This helps maintain the smooth flow of the race and ensures it proceeds as planned. Fourth, accurate and timely obstacle detection and warning mechanisms help drivers better understand track dynamics, allowing them to focus on driving skills rather than dealing with unexpected situations. This enables drivers to enjoy the thrill of racing while ensuring safety, thus enhancing the overall driving experience.

[0093] This application provides another vehicle alarm method. Figure 3 A flowchart illustrating another vehicle alarm method provided for an exemplary embodiment of this application.

[0094] It should be noted that the vehicle alarm method can be executed alone, or it can be executed together with any embodiment or possible implementation in the embodiment of this application, or it can be executed together with any technical solution in the related technology. The embodiments of this application do not limit this.

[0095] like Figure 3 As shown, the vehicle alarm method may include the following steps S301 to S303:

[0096] Step S301: Obtain data collected by sensors within the target area; wherein, the target area is the target track and / or the area near the target track.

[0097] Step S302: In response to the obstacle information contained in the data collected by the sensor, a first alarm message is sent to the target vehicle; wherein, the target vehicle is a vehicle participating in the race on the target track.

[0098] It should be noted that the explanations of steps S301 to S302 can be found in the relevant descriptions in any embodiment of this application, and will not be repeated here.

[0099] In any embodiment of this application, in addition to sending a first alarm message to the target vehicle, a first alarm message may also be sent to a target object associated with the target track; wherein the target object (such as track staff) is used to manage the target track.

[0100] This allows the target to be informed of the real-time situation within the target area in a timely manner and to take necessary measures to ensure the safety of the target track, such as quickly dispatching relevant personnel to the scene or adjusting the track layout to avoid potential dangers, thereby improving the level of event management and reducing the possibility of unexpected interruptions to the race.

[0101] In step S303, in response to the removal of the obstacle from the target area, a second alarm message is sent to the target vehicle; wherein the second alarm message is used to indicate that the obstacle has been removed from the target area.

[0102] In this embodiment of the application, when the obstacle is removed from the target area, a second alarm message can be issued to the target vehicle. The alarm level of the second alarm message can be lower than that of the first alarm message.

[0103] In any embodiment of this application, the first alarm information and the second alarm information include at least one of the following:

[0104] The first item is visual alarm information; wherein, visual alarm information includes at least one of the following: symbol information displayed on the user interface, animation information displayed on the user interface, and alarm information in the head-up display (HUD).

[0105] Symbolic information includes, but is not limited to, icons, text, graphic prompts, and other information.

[0106] The animation information includes, but is not limited to, color changes, dynamic arrow prompts, and other information.

[0107] The second item is auditory alarm information; among which, the alarm form of auditory alarm information includes at least one of voice broadcast, beeping, and warning sound.

[0108] The third item is tactile warning information; among which, the warning forms of tactile warning information include at least one of the following: steering wheel vibration, seat vibration, seat belt vibration, accelerator pedal feedback, and brake pedal feedback.

[0109] The vibration intensity varies depending on the risk level; for example, the vibration intensity corresponding to a high-risk level is greater than that corresponding to a low-risk level.

[0110] The fourth item is to perceive alarm information; among which, the alarm forms of perceived alarm information include at least one of ambient light alarm and exterior light warning.

[0111] Among them, for alarm information in the form of ambient light alarms, red light indicates a high-level warning and yellow light indicates a medium-level warning.

[0112] Among them, for warning information in the form of external lights, such as an increased flashing frequency of turn signals indicating a high-level warning.

[0113] The fifth item is alarm information sent through wearable devices.

[0114] Wearable devices include, but are not limited to: Artificial Intelligence (AI) glasses, headphones, watches, and wristbands.

[0115] In summary, combining multiple alarm methods not only enhances the flexibility and applicability of the method, but also improves the warning effect and the driver's response speed, thereby improving the user experience.

[0116] The vehicle alarm method of this application sends a first alarm message (high-risk level) to the target vehicle when an obstacle enters the target area, and a second alarm message (low-risk level) to the target vehicle after the obstacle is removed from the target area. By distinguishing the alarm level when the obstacle is present and when it is absent, the system can dynamically adjust according to environmental changes, avoiding the redundancy or false alarm problems caused by "static alarms," ​​and ensuring that the race car driver or autonomous driving system always has the most accurate understanding of the road conditions. It is understandable that if all alarms use the same intensity and form, race car drivers may become desensitized to frequent alarm messages. In this application, by setting different alarm levels, it is ensured that alarms at critical moments will attract sufficient attention from the race car driver, while non-urgent information is presented in a more gentle manner, maintaining the user's trust.

[0117] This application provides another vehicle alarm method. Figure 4 This is a flowchart illustrating yet another vehicle alarm method provided for an exemplary embodiment of this application.

[0118] It should be noted that the vehicle alarm method can be executed alone, or it can be executed together with any embodiment or possible implementation in the embodiment of this application, or it can be executed together with any technical solution in the related technology. The embodiments of this application do not limit this.

[0119] like Figure 4 As shown, the vehicle alarm method may include the following steps S401 to S403:

[0120] Step S401: Acquire data collected by sensors within the target area; wherein the target area is the target track and / or the area near the target track; wherein the data collected by sensors includes obstacle information.

[0121] It should be noted that the explanation of step S401 can be found in the relevant description in any embodiment of this application, and will not be repeated here.

[0122] Step S402: Determine the distance between the target vehicle and the obstacle based on the actual position of the target vehicle and the geographical location of the obstacle.

[0123] In this embodiment of the application, a distance calculation algorithm can be used to calculate the distance between the target vehicle and the obstacle based on the actual position of the target vehicle and the geographical location of the obstacle.

[0124] Step S403: Based on the distance and the speed of the target vehicle, determine the travel time of the target vehicle to the obstacle, generate a first alarm message based on the travel time and the category of the obstacle, and send the first alarm message to the target vehicle.

[0125] In this embodiment of the application, the travel time of the target vehicle to the obstacle can be determined based on the distance between the obstacle and the target vehicle and the travel speed of the target vehicle. Based on the travel time and the category of the obstacle, a first alarm message is generated and sent to the target vehicle.

[0126] For example, the danger level posed by an obstacle to the safe driving of a target vehicle can be determined based on the travel time and the obstacle's category. A first warning message is then generated based on this danger level and sent to the target vehicle. For instance, if the travel time is relatively long and the obstacle's danger level is determined to be relatively low, a low-level warning can be issued to the target vehicle. If the travel time is relatively short and the obstacle's category is non-living, the danger level can be determined to be relatively high, and a medium-level warning can be issued to the target vehicle. If the travel time is relatively short and the obstacle's category is a living organism such as a human or animal, the danger level can be determined to be high, and a high-level warning can be issued to the target vehicle.

[0127] The aforementioned travel time can be directly calculated based on the distance between the obstacle and the target vehicle, as well as the target vehicle's speed. For example, the ratio of the distance to the speed can be used as the travel time.

[0128] Alternatively, the aforementioned travel time can also be indirectly calculated based on the distance between the obstacle and the target vehicle, as well as the target vehicle's speed. For example, the initial travel time from the target vehicle to the obstacle can be determined based on the ratio of the distance to the speed, and this initial travel time can be corrected based on the hardware parameters associated with the target vehicle and / or the environmental parameters associated with the target track to obtain the total travel time from the target vehicle to the obstacle.

[0129] The hardware parameters associated with the target vehicle include, but are not limited to: tire parameters, rim parameters, brake pad parameters, etc. Tire parameters include, but are not limited to: tire type (which can be used to indicate tire grip, tire design purpose (such as summer tire, winter tire, all-season tire or high-performance tire) etc.), load index and speed symbol, etc. Rim parameters include, but are not limited to: rim type, rim size, offset, etc. Brake pad parameters include, but are not limited to: brake pad type (which can be used to indicate brake pad material, wear rate, heat resistance and brake disc friendliness), coefficient of friction, etc.

[0130] Among them, environmental parameters related to the target track include, but are not limited to: weather temperature, road surface wetness, etc.

[0131] As an example, the following formula can be used to calculate the travel time T1 of the target vehicle to the obstacle:

[0132] T1 = T*C; (1)

[0133] Where T refers to the ratio of the distance D between the target vehicle and the obstacle to the speed S of the target vehicle, i.e., T = D / S; C is a correction coefficient, which is determined or calibrated based on the hardware parameters associated with the target vehicle and / or the environmental parameters associated with the target track.

[0134] As an example, when C is determined based on hardware parameters associated with the target vehicle, a lookup table method can be used to determine the correction coefficient matching the actual hardware parameters by querying a first mapping table. The first mapping table records the mapping relationships between different hardware parameters and correction coefficients.

[0135] As another example, when C is determined based on environmental parameters associated with the target track, a lookup table method can be used. Based on the actual environmental parameters of the target track, a second mapping table can be consulted to determine the correction coefficient matching those environmental parameters. The second mapping table records the mapping relationships between different environmental parameters and correction coefficients.

[0136] As another example, when C is determined based on the hardware parameters associated with the target vehicle and the environmental parameters associated with the target track, a lookup table method can be used. Based on the actual hardware parameters of the target vehicle and the actual environmental parameters of the target track, a third mapping table can be consulted to determine the correction coefficients that match these hardware and environmental parameters. This third mapping table records the mapping relationships between different hardware parameters, environmental parameters, and correction coefficients.

[0137] In summary, by correcting the time T for the target vehicle to reach an obstacle based on the target vehicle's actual hardware parameters (such as braking efficiency and tire grip) and / or the target track's actual environmental parameters (such as weather temperature and road surface slippage), the arrival time T of the target vehicle can be more accurately predicted. This allows the target vehicle to issue warnings at more appropriate times, giving the racer more reaction time to avoid potential dangers and improving the safety of the target vehicle. Furthermore, considering the target vehicle's hardware characteristics and changes in the external environment, this approach effectively reduces interference caused by inaccurate warnings, enhancing user trust and satisfaction.

[0138] The vehicle warning method in this application takes into account that different types of obstacles have different degrees of impact on driving safety. For example, dynamic obstacles (such as pedestrians and animals) may require a more urgent response than static obstacles (such as track markings and track service facilities). By identifying the type of obstacle and combining it with the distance between the obstacle and the vehicle to issue a vehicle warning, a more accurate risk assessment can be achieved, and appropriate warnings can be issued in a timely manner, thereby effectively reducing the accident rate.

[0139] This application provides another vehicle alarm method. Figure 5 A flowchart illustrating another vehicle alarm method provided for an exemplary embodiment of this application.

[0140] It should be noted that the vehicle alarm method can be executed alone, or it can be executed together with any embodiment or possible implementation in the embodiment of this application, or it can be executed together with any technical solution in the related technology. The embodiments of this application do not limit this.

[0141] like Figure 5 As shown, the vehicle alarm method may include the following steps S501 to S505:

[0142] Step S501: Obtain data collected by sensors within the target area; wherein the target area is the target track and / or the area near the target track; wherein the data collected by sensors includes obstacle information.

[0143] Step S502: Determine the distance between the target vehicle and the obstacle based on the actual position of the target vehicle and the geographical location of the obstacle.

[0144] Step S503: Determine the travel time of the target vehicle to the obstacle based on the distance and the speed of the target vehicle.

[0145] It should be noted that the explanations of steps S501 to S503 can be found in the relevant descriptions in any embodiment of this application, and will not be repeated here.

[0146] Step S504: In response to the obstacle including track elements associated with the target track, and the driving time meeting the alarm triggering time associated with the track element, generate the first alarm information associated with the track element according to the category to which the track element belongs.

[0147] The track elements include track signage and / or track service facilities. It should be noted that the explanations of the track elements in the foregoing embodiments also apply to this embodiment, and will not be repeated here.

[0148] The alarm triggering timing associated with each track element can be obtained by labeling or configuring the track element based on the environmental parameters associated with the target track.

[0149] For the same track element, different environmental parameters correspond to different alarm triggering times. Taking the alarm triggering time as an example, the time threshold associated with the same track element is reached when the driving time reaches the time threshold associated with the same track element (i.e., the driving time is less than or equal to the time threshold associated with the same track element). The time threshold corresponding to poor environmental conditions (such as high road surface slipperiness) can be lower than the time threshold corresponding to better environmental conditions (such as low road surface slipperiness).

[0150] For different track elements, the alarm triggering timing for each track element under the same environmental parameters may be different or the same. This application embodiment does not impose any restrictions on this.

[0151] In this embodiment, when the obstacle includes a track element, it can be determined whether the travel time of the target vehicle to the obstacle meets the alarm triggering time associated with the track element. If not, no vehicle alarm is triggered; if so, a first alarm message associated with the track element is generated based on the category to which the track element belongs. The first alarm messages associated with different categories of track elements can be different.

[0152] For example, taking track elements including track markings such as "braking point" markings as an example, the first warning information is such as "Break X meters ahead" or "Break in Y seconds", where X refers to the distance between the target vehicle and the braking point, and Y is determined based on the travel time T1 of the target vehicle to the braking point, and Y≤T1.

[0153] Step S505: Send the first alarm message to the target vehicle.

[0154] In any embodiment of this application, the first alarm information can be displayed through a visual display method (such as a head-up display (HUD), an in-vehicle display screen, an instrument panel display, etc.) so that the race car driver can be informed of the first alarm information in real time.

[0155] Using the example above, a prominent sign or icon, such as a red "Brake" sign or symbol, can be projected onto the windshield of the target vehicle to alert the driver that they are approaching a braking point. Alternatively, the distance to the next braking point or a countdown timer can be displayed on the in-vehicle display screen, such as "Brake X meters ahead" or "Brake in Y seconds".

[0156] In any embodiment of this application, the first warning information can also be broadcast via voice, thereby reducing the driver's attention distraction during driving and improving driving safety. That is, the driver can quickly learn about the first warning information through auditory feedback without interrupting visual attention or manual operation to check. This instant feedback enhances user satisfaction.

[0157] Using the example above, a clear human voice can be used to prompt the race car driver to prepare to brake, such as: "Attention, brake in Y seconds." As the braking point approaches, the warnings can become more frequent and urgent, such as "Brake! Brake!"

[0158] In any embodiment of this application, the first alarm information can also be displayed visually or broadcast via voice.

[0159] Therefore, processing the first alarm information in different ways can improve the flexibility and applicability of this method.

[0160] In any embodiment of this application, in order to facilitate users to know the location of track elements (i.e., geographical location), each track element can be displayed on any side of the target track on the electronic map, or each track element can be displayed on the target track on the electronic map.

[0161] In any embodiment of this application, when the first alarm information is displayed in a visual manner, the first alarm information can be displayed on the electronic map in the area surrounding the track element.

[0162] Therefore, displaying the first warning information associated with the track element around the track element on the electronic map can enhance the driver's spatial awareness and reaction speed, allowing the driver to intuitively see the upcoming track element. This helps the driver better understand the relationship between their current position and these important track elements, receive notifications earlier, and begin to take corresponding preparatory actions, such as adjusting speed or changing lanes, thereby improving the accuracy of the operation.

[0163] The vehicle warning method of this application provides accurate first warning information for specific track elements, which can help race car drivers better grasp the timing of operations, such as braking accurately at the optimal braking point, reducing the risk of accidents caused by misjudgment. By issuing the first warning information in a timely manner, race car drivers can be given enough time to prepare for and respond to upcoming operational needs, enhancing their ability to deal with emergencies and greatly improving the driving experience.

[0164] This application provides another vehicle alarm method. Figure 6 This is a flowchart illustrating another vehicle alarm method provided as an exemplary embodiment of the present application.

[0165] It should be noted that the vehicle alarm method can be executed alone, or it can be executed together with any embodiment or possible implementation in the embodiment of this application, or it can be executed together with any technical solution in the related technology. The embodiments of this application do not limit this.

[0166] like Figure 6 As shown, the vehicle alarm method may include the following steps S601 to S606:

[0167] Step S601: Acquire data collected by sensors within the target area; wherein the target area is the target track and / or the area near the target track; wherein the data collected by sensors includes obstacle information.

[0168] Step S602: Determine the distance between the target vehicle and the obstacle based on the actual position of the target vehicle and the geographical location of the obstacle.

[0169] Step S603: Determine the travel time of the target vehicle to the obstacle based on the distance and the speed of the target vehicle.

[0170] It should be noted that the explanations of steps S601 to S603 can be found in the relevant descriptions in any embodiment of this application, and will not be repeated here.

[0171] Step S604: In response to the obstacle including a movable target, determine the risk level posed by the movable target to the safe driving of the target vehicle based on the driving time and the category to which the movable target belongs.

[0172] Among them, movable targets include, but are not limited to, obstacles that intrude into the target track, such as animals, pets, toy cars, and low-flying drones.

[0173] The number of movable targets can be one or more, and this application embodiment does not limit this.

[0174] In the embodiments of this application, when the obstacle includes a movable target, the risk level posed by the movable target to the safe driving of the target vehicle can be determined based on the travel time of the target vehicle to the movable target and the category to which the movable target belongs. In this application, this risk level is referred to as the third risk level (or threat level).

[0175] As an example, a lookup table method can be used. Based on the travel time of the target vehicle to the movable target and the category to which the movable target belongs, the object classification table (or object classification library) can be consulted to obtain the third risk level posed by the movable target to the safe driving of the vehicle.

[0176] The object classification table records the mapping relationship between different object categories, travel time, and risk level.

[0177] Among them, the risk level is negatively correlated with the driving time; that is, the shorter the driving time, the higher the risk level.

[0178] Step S605: Generate the first alarm message based on the category and risk level of the movable target.

[0179] In this embodiment of the application, a first alarm message corresponding to each movable target can be generated based on the category to which each movable target belongs and the third risk level. The first alarm message can be used to indicate the category to which the movable target belongs and the third risk level of the movable target.

[0180] Step S606: Send the first alarm message to the target vehicle.

[0181] In this embodiment, an alarm mechanism matching the first alarm information of the movable target can be used to send the first alarm information to the target vehicle. The alarm mechanisms corresponding to different risk levels can be different.

[0182] As an example, for high-risk (or high-threat) mobile targets, such as pedestrians who suddenly appear, vehicle warnings can be issued by combining audible alerts with visual cues (such as red warning lights on the dashboard or emergency information on the vehicle's display screen), or even tactile feedback (such as steering wheel vibration).

[0183] As another example, for low-risk (or low-threat) moving targets, vehicle warnings can be issued through gentle cues on the dashboard or head-up display to avoid unnecessary distraction for the racer. For instance, a simple icon or text prompt (such as "Caution" or "Object Ahead") in a muted color (like yellow) can be used to alert the driver to the presence of a low-risk moving target. Alternatively, the geographical location of the low-risk moving target can be marked on an electronic map to help the racer understand their surroundings. Or, vehicle warnings can be issued through subtle audible cues or limited tactile feedback (such as slight vibrations to the steering wheel or seat).

[0184] The vehicle alarm method of this application determines the third risk level posed by the movable target to the safe driving of the target vehicle based on the driving time of the target vehicle to the movable target and the category to which the movable target belongs, and generates the first alarm information accordingly. It has at least the following advantages: it improves the accuracy of risk assessment and the relevance of alarms, and reduces the possibility of false alarms or missed alarms; different risk levels correspond to different levels of alarm intensity and form (e.g., visual, auditory, tactile cues). This customized alarm strategy helps to rationally allocate the resources of the driver assistance system, so as not to overly interfere with the race car driver, but to provide necessary assistance at critical moments and improve the race car driver's driving experience.

[0185] This application provides another vehicle alarm method. Figure 7 A flowchart illustrating another vehicle alarm method provided for an exemplary embodiment of this application.

[0186] It should be noted that the vehicle alarm method can be executed alone, or it can be executed together with any embodiment or possible implementation in the embodiment of this application, or it can be executed together with any technical solution in the related technology. The embodiments of this application do not limit this.

[0187] like Figure 7 As shown, the vehicle alarm method may include the following steps S701 to S705:

[0188] Step S701: Acquire data collected by sensors within the target area; wherein the target area is the target track and / or the area near the target track; wherein the data collected by sensors includes obstacle information.

[0189] Step S702: Determine the distance between the target vehicle and the obstacle based on the actual position of the target vehicle and the geographical location of the obstacle.

[0190] Step S703: Determine the travel time of the target vehicle to the obstacle based on the distance and the speed of the target vehicle.

[0191] It should be noted that the explanations of steps S701 to S703 can be found in the relevant descriptions in any embodiment of this application, and will not be repeated here.

[0192] In step S704, in response to the obstacle including a movable target and a track element, a first alarm message for the track element is generated based on the travel time of the target vehicle to the track element and the category to which the track element belongs, and a first alarm message for the movable target is generated based on the travel time of the target vehicle to the movable target and the category to which the movable target belongs.

[0193] It should be noted that step S704 can be referred to in the above embodiments as step S504 and the relevant descriptions of steps S604 to S605, and will not be repeated here.

[0194] Step S705: Based on the alarm priorities corresponding to the movable target and the track element, send the first alarm information for the movable target and the first alarm information for the track element to the target vehicle.

[0195] Among them, the alarm priority of movable targets is higher than that of track elements. Furthermore, the alarm priority of different categories of movable targets can be different. For example, the alarm priority of humans is higher than that of other categories of movable targets. Similarly, the alarm priority of different categories of track elements can also be different.

[0196] In this embodiment, vehicle alarms can be issued for the first alarm information of the movable target and the first alarm information of the track element according to the alarm priorities corresponding to the movable target and the track element, respectively. For example, firstly, a vehicle alarm can be issued for the first alarm information of the movable target; the implementation principle can be found in the relevant description of step S505 in the above embodiment, and will not be repeated here. Then, a vehicle alarm can be issued for the first alarm information of the track element; the implementation principle can be found in the relevant description of step S606 in the above embodiment, and will not be repeated here either.

[0197] In any embodiment of this application, before the target vehicle races, the target vehicle can obtain a scene feature library associated with the target track from the cloud. The scene feature library includes feature maps of track elements, which include track identifiers and / or track service facilities. Based on the scene feature library, the target vehicle queries track data associated with the target track to obtain the geographical location of each track element. Based on the geographical location of each track element, the target vehicle displays each track element on an electronic map.

[0198] Track data, also known as track information, can be obtained by the track administrator (or racetrack administrator) configuring the target track, including the identity (ID) and geographical location of each track element.

[0199] As an example, for any track element among the track elements indicated by the scene feature library, the geographical location of the track element can be projected onto the display screen according to the track element's geographical location, the screen size of the display screen of the electronic map (such as an in-vehicle display screen), and the actual size of the target track, so as to obtain the projected coordinates of the track element on the display screen. Thus, the track element can be displayed on the electronic map based on the projected coordinates of the track element.

[0200] For example, the following formula can be used to calculate the projected coordinates of track elements:

[0201] The horizontal coordinate in the projected coordinates (also known as the screen horizontal coordinate) = the display width in the screen size / the area width in the actual size of the target track * the true horizontal coordinate X of the track element's geographical location;

[0202] The x and y coordinates in the projected coordinates (also known as the screen y coordinates) = display height in the screen size / area height in the actual size of the target track * the true y coordinate Y of the track element's geographical location;

[0203] It should be noted that the above formula for calculating the projected coordinates is only an example and this application is not limited to it. Other algorithms can also be used to calculate the projected coordinates of the track elements. For example, when the geographical location includes latitude and longitude coordinates, X' (X' = display width in the screen size / area width in the actual size of the target track * X in the geographical location of the track element) can be converted into two-dimensional plane coordinates, and Y' (Y' = display height in the screen size / area height in the actual size of the target track * Y in the geographical location of the track element) can be converted into two-dimensional plane coordinates.

[0204] Therefore, displaying various track elements associated with the target track on an electronic map allows racers to understand the specific layout of the target track and the geographical location of key elements in advance, which helps in formulating more precise race strategies and improving pre-race preparation efficiency. Furthermore, during racing, racers can directly view track elements on the electronic map as support for real-time decision-making, such as when to begin slowing down to enter a corner, enhancing their decision-making ability during the race and improving vehicle safety.

[0205] The vehicle warning method in this application takes into account that different types of obstacles pose different degrees of threat to driving safety. For example, movable targets (such as pedestrians, animals, etc.) often require more urgent attention because their behavior is unpredictable and they may suddenly change direction or speed. While track elements (such as track markings, track service facilities, etc.) also need attention, their positions are usually fixed, making it relatively easier to plan avoidance paths. By distinguishing between these two types of obstacles and setting corresponding warning priorities, a more accurate risk assessment can be achieved, ensuring that race car drivers can prioritize the most urgent situations and take corresponding measures, thereby improving driving safety.

[0206] The above are various implementation methods for vehicle execution. This application also provides a vehicle alarm method executed in the cloud.

[0207] Figure 8 A flowchart illustrating another vehicle alarm method provided for an exemplary embodiment of this application.

[0208] like Figure 8 As shown, the vehicle alarm method may include the following steps S801 to S803:

[0209] Step S801: Obtain data collected by sensors within the target area; wherein, the target area is the target track and / or the area near the target track.

[0210] In this embodiment of the application, the cloud can receive data collected and uploaded by various sensors within the target area.

[0211] Step S802: Based on the scene feature library associated with the target track, obstacle detection is performed on the data collected by the sensors to obtain obstacle information.

[0212] Step S803: Send obstacle information to the target vehicle; wherein, the target vehicle is a vehicle participating in the race on the target track, and the obstacle information is used to issue an alarm to the target vehicle.

[0213] It should be noted that the explanations and descriptions of the various method embodiments executed on the target vehicle mentioned above also apply to this embodiment, and their implementation principles are similar, so they will not be repeated here.

[0214] The vehicle warning method of this application embodiment, based on a scene feature library associated with the target track, performs obstacle detection on data collected by sensors in the target track and / or the area near the target track to obtain obstacle information, and issues vehicle warnings based on the obstacle information. It has at least the following advantages: First, it can acquire and identify obstacle information in the vehicle's environment in real time. Compared with traditional methods that rely on manual patrols or race announcements, this method greatly improves the timeliness and location accuracy of obstacle identification (including track markings, track service facilities, and dynamic obstacles temporarily encroaching on the track), allowing racers (or drivers) to understand the road conditions ahead more promptly and accurately, thereby making safer and more effective driving decisions and improving vehicle safety. Second, it can not only identify static obstacles, such as track elements (including track markings, track service equipment, etc.), but also effectively detect dynamic obstacles on the track, such as movable targets (including animals or other foreign objects encroaching on the track). Once a potential threat is detected, the vehicle can issue a warning based on the obstacle information, notifying the racer in advance to take appropriate measures to avoid potential collisions, greatly enhancing the safety of the race. Third, it enables efficient monitoring and real-time feedback of track conditions, reducing race interruptions or delays caused by untimely manual checks. This helps maintain the smooth flow of the race and ensures it proceeds as planned. Fourth, accurate and timely obstacle detection and warning mechanisms help drivers better understand track dynamics, allowing them to focus on driving skills rather than dealing with unexpected situations. This enables drivers to enjoy the thrill of racing while ensuring safety, thus enhancing the overall driving experience.

[0215] This application provides another vehicle alarm method. Figure 9 This is a flowchart illustrating yet another vehicle alarm method provided for an exemplary embodiment of this application.

[0216] It should be noted that the vehicle alarm method can be executed alone, or it can be executed together with any embodiment or possible implementation in the embodiment of this application, or it can be executed together with any technical solution in the related technology. The embodiments of this application do not limit this.

[0217] like Figure 9 As shown, the vehicle alarm method may include the following steps S901 to S906:

[0218] Step S901: Obtain data collected by sensors within the target area; wherein, the target area is the target track and / or the area near the target track.

[0219] It should be noted that the explanation of step S901 can be found in the relevant description in any embodiment of this application, and will not be repeated here.

[0220] Step S902: Extract features from the data collected by the sensor to obtain target features.

[0221] In this embodiment of the application, a feature extraction algorithm can be used to extract features from the data collected by the sensor to obtain the target features.

[0222] Step S903: Match the target features with the feature maps of track elements in the scene feature library to obtain the first recognition result.

[0223] The scene feature library includes feature maps of various types of track elements, including track identifiers and / or track service facilities.

[0224] The first identification result is used to indicate at least one of the category, geographical location, and orientation of the track element existing in the target area, or the first identification result is used to indicate that there is no track element in the target area. That is, the first identification result is used to indicate whether there is a track element in the environment (i.e., the target area) where the target vehicle is located. If there is, the first identification result is also used to indicate at least one of the category, geographical location, and orientation of the track element.

[0225] In this embodiment, the target feature can be matched with the feature maps of each track element in the scene feature library to obtain a first recognition result. For example, if the matching degree between the target feature and the feature map of a certain track element in the scene feature library is higher than or equal to a set matching degree threshold, the first recognition result indicates that the track element exists within the target area, and indicates at least one of the category, geographical location, and orientation of the track element; conversely, if the matching degree between the target feature and the feature maps of all track elements in the scene feature library is lower than the matching degree threshold, the first recognition result indicates that no track element exists within the target area.

[0226] The category, geographical location, and orientation of the track element can be obtained from the track data (or track information) associated with the target track.

[0227] Step S904: Obstacle recognition is performed on the target features to obtain a second recognition result.

[0228] The second identification result is used to indicate at least one of the category, geographical location, and orientation of the movable target within the target area; or, the second identification result is used to indicate that there is no movable target within the target area. That is, the second identification result is used to indicate whether there is a movable target within the target area. If there is, the second identification result is also used to indicate at least one of the category, geographical location, and orientation of the movable target.

[0229] In the embodiments of this application, an obstacle detection algorithm (or target detection algorithm, target tracking algorithm) can be used to identify obstacles in the target features and obtain a second identification result.

[0230] Step S905: Generate obstacle information based on the first recognition result and the second recognition result.

[0231] In this embodiment of the application, obstacle information within the target area can be generated based on the first identification result and the second identification result; wherein, the obstacle information may include at least one of the category, geographical location and orientation of the obstacle, and the obstacle includes track elements and / or movable targets.

[0232] Step S906: Send obstacle information to the target vehicle; wherein, the target vehicle is a vehicle participating in the race on the target track, and the obstacle information is used to issue an alarm to the target vehicle.

[0233] It should be noted that the explanation of step S906 can be found in the relevant description in any embodiment of this application, and will not be repeated here.

[0234] In any embodiment of this application, the scene feature library can be generated in the cloud using the following steps A to B:

[0235] Step A: Receive the input information sent by the track management terminal; the input information is used to indicate the various track elements in the venue where the target track is located and the geographical location of the track elements.

[0236] The entered information can be obtained by the track administrator on the track management side through a visual configuration of the target track, which is used to indicate the various track elements in the racetrack where the target track is located and the geographical location of the track elements.

[0237] As an example, the track management terminal can respond to configuration operations triggered by the track administrator, select track elements associated with the target track from various types of track elements on the management page, and respond to the track administrator's configuration operations on the track elements associated with the target track, determine the geographical location of the track elements associated with the target track from the electronic map displaying the target track. For example, the track administrator can determine the geographical location of the track elements from the electronic map by dragging and dropping. Thus, the track management terminal can generate input information based on the track elements associated with the target track and their corresponding geographical locations.

[0238] Therefore, by configuring the various track elements and their geographical locations within the racetrack where the target track is located through a visual configuration method, not only can efficient digital management of track elements be achieved, but also flexible adjustments can be made based on actual needs. This approach greatly accelerates the process of track preparation, improves the accuracy of location planning, and enhances the overall quality of event operation.

[0239] Step B: Generate a scene feature library based on the entered information.

[0240] In summary, by using cloud-based systems equipped with powerful computing resources and advanced algorithms (such as feature extraction algorithms and target tracking algorithms) to generate a scene feature library based on the information uploaded by the track management terminal, data processing capabilities can be enhanced, and the real-time performance and quality of the scene feature library generation can be improved.

[0241] In any embodiment of this application, the scene feature library can be obtained by updating it in the cloud using the following steps C to D:

[0242] Step C: Receive update information sent by the track management terminal; wherein, the update information is used to indicate the track elements that have been updated in the target track and the geographical location of the updated track elements.

[0243] The track elements that have been updated include: newly added track elements, deleted track elements, and track elements whose positions have changed.

[0244] The update information can be obtained by the track administrator on the track management side through a visual configuration of the target track, and is used to indicate the updated track elements in the track area where the target track is located, as well as the geographical location of the updated track elements.

[0245] Step D: Update the scene feature library based on the updated information.

[0246] In summary, by updating or dynamically maintaining the scene feature library in a timely manner through the cloud and synchronizing it to each vehicle participating in the competition, it is possible to ensure that all participants can obtain the latest track data, thereby further improving vehicle driving safety.

[0247] The vehicle alarm method of this application integrates the feature maps of each track element in the scene feature library associated with the target track and the obstacle detection algorithm to identify obstacles in the target features of the data collected by the sensor, which can improve the accuracy and reliability of the identification results.

[0248] In any embodiment of this application, in order to realize the automatic detection, marking, notification and early warning of track markings, track service facilities and temporary dynamic obstacles (referred to as movable targets in this application), this application also provides a vehicle alarm system based on a track special information database and video monitoring unit, which realizes the digital management of track markings and track service facilities, and performs real-time monitoring and early warning of sudden movable targets, thereby effectively improving the safety and management efficiency of motor racing events.

[0249] For example, a vehicle alarm system mainly includes the following components:

[0250] 1. Scene Feature Library Information Unit: Before the race, the onboard app automatically connects to the track management system and downloads track data specific to the race. This scene feature library includes, for example: Figure 2 The image shows some common track signs and track service facilities. Figure 2 (Not shown in the image) Different prompts can be provided to racers based on different track markings and track service facilities.

[0251] (1) After the vehicle APP is installed in the vehicle, it will store the track data in the scene feature library in advance, including feature maps of common track signs such as braking points, entry points, cornering points, speed gates, etc., as well as feature maps of track service facilities. The vehicle APP can display track signs and track service facilities on the electronic map according to the actual track conditions.

[0252] (2) The track data includes the ID and geographical location (such as latitude and longitude coordinates) corresponding to the track identifier and track service facilities. For example, the track data includes a set of line segments with latitude and longitude information. By adding or deleting track identifiers and track service facilities on the track line, the latitude and longitude coordinates of the track identifiers and track service facilities can be obtained.

[0253] (3) The vehicle APP queries the corresponding track identifier and track service facilities based on the scene feature database, converts the geographical location of the track identifier and track service facilities (such as real latitude and longitude coordinates, referred to as real coordinates) to the coordinates on the display screen, and displays them on the screen.

[0254] (4) The scene feature library can be dynamically updated as the track administrator updates, ensuring the real-time nature of the track data.

[0255] For example, the track markings displayed on the screen can be as follows: Figure 10 As shown, the track marker is displayed on the electronic map.

[0256] 2. Scene Feature Library Management Unit: Before the start of the event, the track administrator (or racetrack administrator) can add or edit key prompts such as cones, braking points, and cornering points in the track special information database as needed, and the track administrator can update the scene feature library in real time.

[0257] (1) Track administrators can dynamically add and delete track signs and service facilities in real time based on the actual scene of the racetrack. After addition or deletion, the cloud will update the vehicle's terminal in real time, and the terminal can display the latest track signs, service facilities and track information on the electronic map in real time. The implementation process is as follows: Figure 11 As shown.

[0258] (2) The management page provides a variety of track signs and track service facilities for track administrators to choose from. Track administrators only need to select the corresponding deployment location on the electronic map, and the system will generate the latitude and longitude coordinates and ID of the track signs and track service facilities for display and warning on the vehicle terminal.

[0259] 3. Video Monitoring Unit (or Video Monitoring System, located in the cloud): In addition to pre-installed track markings and service facilities, unexpected situations may arise during the race. For example, animals such as cats and dogs may appear unexpectedly as dynamic obstacles, or other foreign objects may intrude into the track. The video monitoring unit can identify these obstacles in real time. Its implementation process is as follows: Figure 12 As shown.

[0260] (1) The sensor can capture pictures or videos in real time, and the collected data (hereinafter referred to as multimedia information) will be pushed to the cloud for track management in real time;

[0261] (2) The multimedia information contains the sensor ID, which can be used to query the corresponding latitude and longitude coordinates;

[0262] (3) The cloud-based track management system will parse and extract features from the received multimedia information to obtain multimedia features;

[0263] (4) The cloud uses computer vision services related to the target tracking algorithm to analyze multimedia features;

[0264] Among them, target tracking algorithms include, but are not limited to, You Only Look Once (YOLO) and Deep Learning-based Multiple Object Tracking with Simple Online and Realtime Tracking (DeepSrot).

[0265] (5) Match each object in the multimedia features with the feature map in the scene feature library. If obstacles (including track signs, track service facilities and movable targets) are found, the latitude and longitude coordinates of the obstacles are analyzed and tracked in real time.

[0266] (6) Push the tracked obstacle information to the vehicle terminal in real time. The obstacle information includes the type of obstacle, latitude and longitude coordinates, and direction.

[0267] 4. Early warning unit: During the vehicle's operation, it receives obstacle information sent from the cloud, scene feature database updated by the track administrator, and makes judgments based on the distance between the obstacle and the vehicle and the type of obstacle. If the obstacle reaches the danger level, it will provide real-time prompts and warnings.

[0268] (1) During the driving process, the vehicle will obtain the current position and driving speed S in real time. At the same time, it will receive the scene feature library updated by the track administrator and the real-time obstacle information pushed by the image monitoring unit. Based on its current position, it will calculate the distance D between the vehicle and the obstacle.

[0269] (2) The vehicle terminal searches based on the ID of the obstacle. If the obstacle is a track marker or track service facility placed by the track administrator, it will be displayed on the electronic map.

[0270] (3) The vehicle will calculate the estimated time to reach the obstacle (referred to as travel time in this application) T = D / S. At the same time, T will be affected by environmental parameters, hardware parameters and other conditions, that is, the final travel time T1 = T*C.

[0271] Among them, vehicle-related hardware parameters include, but are not limited to: tire parameters, rim parameters, brake pad parameters, etc.; and track-related environmental parameters include, but are not limited to: weather temperature, road surface wetness, etc.

[0272] In this application, C can be calibrated according to the actual environmental conditions and vehicle information. For example, the worse the environment, the smaller C will be, and the smaller T1 will be, so the driver needs to avoid obstacles as early as possible.

[0273] (4) If the obstacle is a movable target, the video monitoring unit will package the obstacle's latitude and longitude coordinates, type, timestamp and other information and push it to the vehicle.

[0274] (5) If the cloud detects that a movable target has left the track or disappeared based on the real-time uploaded multimedia information, the cloud can push information such as the latitude and longitude coordinates of the movable target when it left the track to the vehicle APP so that the vehicle can update the status of the movable target in real time and cancel the warning.

[0275] (6) The vehicle can query the object classification library according to the category to which the mobile target belongs and T1 to determine the threat level (referred to as risk level in this application) posed by the mobile target to the safe driving of the vehicle, and generate a series of early warning events.

[0276] 5. Broadcasting Unit.

[0277] (1) When the vehicle is near the track elements (including track signs and track service facilities) recorded in the track special information database, the vehicle APP will issue warning prompts such as "braking point", "entry point" and "exit point" based on the vehicle's current driving speed and the best alarm triggering time of the track elements.

[0278] (2) If the alarm of the movable target and the alarm of the track element are triggered at the same time, the system will broadcast the alarm according to the alarm priority to avoid information overload.

[0279] (3) If a movable target temporarily intrudes into the racetrack, an alarm will be triggered continuously until the movable target leaves the track.

[0280] In summary, the solution provided in this application has at least the following advantages: it enables digital management of track elements and real-time monitoring and early warning of sudden dynamic obstacles, thereby effectively improving the safety and management efficiency of motorsports events.

[0281] To achieve the above embodiments, this application also proposes a vehicle alarm device.

[0282] Figure 13 This is a schematic diagram of the structure of a vehicle warning device provided for an exemplary embodiment of this application.

[0283] like Figure 13 As shown, the vehicle alarm device 1300 may include an acquisition module 1310 and an alarm module 1320.

[0284] The acquisition module 1310 is used to acquire data collected by sensors within the target area; wherein the target area is the target track and / or the area near the target track.

[0285] The alarm module 1320 is used to issue a first alarm message to the target vehicle in response to the data collected by the sensor containing obstacle information; wherein the target vehicle is a vehicle participating in the race on the target track.

[0286] Furthermore, in one implementation of this application embodiment, the alarm module 1320 is further configured to: issue a second alarm message to the target vehicle in response to the removal of the obstacle from the target area; wherein the second alarm message is used to indicate that the obstacle has been removed from the target area.

[0287] In one implementation of this application, the obstacle information includes the category to which the obstacle belongs. The alarm module 1320 is used to: generate a first alarm message matching the category to which the obstacle belongs, and send the first alarm message to the target vehicle.

[0288] In one implementation of this application, the obstacle information includes the position of the obstacle relative to the target vehicle. The alarm module 1320 is used to: determine an alarm area matching the position from the display interface of the target vehicle; and display first alarm information through the alarm area.

[0289] In one implementation of this application, the obstacle information includes the geographical location of the obstacle. The alarm module 1320 is used to: determine the distance between the target vehicle and the obstacle based on the geographical location; generate a first alarm message matching the distance based on the distance; and send the first alarm message to the target vehicle.

[0290] In one implementation of this application, the obstacle information includes the category and geographical location of the obstacle. The alarm module 1320 is used to: determine the distance between the target vehicle and the obstacle based on the actual location of the target vehicle and the geographical location of the obstacle; determine the travel time of the target vehicle to the obstacle based on the distance and the travel speed of the target vehicle; generate a first alarm message based on the travel time and the category of the obstacle, and send the first alarm message to the target vehicle.

[0291] In one implementation of this application, the alarm module 1320 is used to: determine the initial time for the target vehicle to travel to the obstacle based on the ratio of distance to the target vehicle's speed; and correct the initial time based on hardware parameters associated with the target vehicle and / or environmental parameters associated with the target track to obtain the travel time.

[0292] In one implementation of this application, the alarm module 1320 is used to: in response to the obstacle including track elements associated with the target track and the driving time satisfying the alarm triggering time associated with the track element, generate first alarm information associated with the track element according to the category to which the track element belongs; wherein, the track element includes track identifiers and / or track service facilities.

[0293] In one implementation of this application, the alarm triggering time is obtained by marking track elements based on environmental parameters associated with the target track. The alarm triggering time includes: the driving time reaching the time threshold associated with the track element.

[0294] In one implementation of this application, the track element is displayed on the target track side of the electronic map, and the alarm module 1320 is used to: display the first alarm information in the area surrounding the track element on the electronic map.

[0295] In one implementation of this application, the alarm module 1320 is configured to: in response to the obstacle including a movable target, determine the risk level posed by the movable target to the safe driving of the vehicle based on the driving time and the category to which the movable target belongs; and generate first alarm information based on the category to which the movable target belongs and the risk level.

[0296] In one implementation of this application, the alarm module 1320 is configured to: in response to the obstacle including a movable target and a track element, generate a first alarm message for the track element based on the travel time of the target vehicle to the track element and the category to which the track element belongs, and generate a first alarm message for the movable target based on the travel time of the target vehicle to the movable target and the category to which the movable target belongs; and send the first alarm message for the movable target and the first alarm message for the track element to the target vehicle according to the alarm priorities corresponding to the movable target and the track element respectively.

[0297] In one implementation of this application, the vehicle alarm device 1300 may further include:

[0298] The display module is used to retrieve scene feature libraries associated with the target track from the cloud. The scene feature library includes feature maps of track elements, which include track identifiers and / or track service facilities. Based on the scene feature library, the module queries track data associated with the target track to obtain the geographical location of each track element. Based on the geographical location of each track element, the module displays each track element on an electronic map.

[0299] In one implementation of this application, the display module is configured to: project the geographical location of any track element onto the display screen based on the geographical location of any track element, the screen size of the display screen of the electronic map, and the actual size of the target track, thereby obtaining the projected coordinates of any track element on the display screen; and display any track element on the electronic map based on the projected coordinates of any track element.

[0300] In one implementation of this application, the vehicle alarm device 1300 may further include:

[0301] The sending module is used to send the first alarm information to the target object associated with the target track; wherein, the target object is used to manage the target track.

[0302] In one implementation of this application, the first alarm information includes at least one of the following:

[0303] Visual alarm information; wherein, the visual alarm information includes at least one of the following: symbol information displayed on the user interface, animation information displayed on the user interface, and alarm information in the head-up display (HUD);

[0304] Auditory alarm information; wherein, the alarm form of the auditory alarm information includes at least one of the following: voice broadcast, buzzer sound, and warning sound;

[0305] Tactile warning information; wherein, the form of tactile warning information includes at least one of the following: steering wheel vibration, seat vibration, seat belt vibration, accelerator pedal feedback, and brake pedal feedback;

[0306] Perceive alarm information; wherein, the alarm forms of perceived alarm information include at least one of ambient light alarm and exterior light warning;

[0307] Alarm messages sent via wearable devices.

[0308] It should be noted that the explanation of the vehicle alarm method embodiment performed on the target vehicle described above also applies to the vehicle alarm device of this embodiment, and will not be repeated here.

[0309] The vehicle warning device in this application embodiment detects obstacles by analyzing data collected by sensors in the target track and / or the area near the target track to obtain obstacle information, and issues vehicle warnings based on this obstacle information. This has at least the following advantages: First, it can acquire and identify obstacle information in the vehicle's environment in real time. Compared to traditional methods relying on manual patrols or race announcements, this significantly improves the timeliness of obstacle identification (including track markings, track service facilities, and dynamic obstacles temporarily encroaching on the track), allowing racers (or drivers) to understand the road conditions ahead more promptly and accurately, thus making safer and more effective driving decisions and improving vehicle safety. Second, it can not only identify static obstacles, such as track elements (including track markings, track service equipment, etc.), but also effectively detect dynamic obstacles on the track, such as movable targets (including animals or other foreign objects encroaching on the track). Once a potential threat is detected, the vehicle can issue a warning based on the obstacle information, notifying the racer in advance to take appropriate measures to avoid potential collisions, greatly enhancing the safety of the race. Third, it enables efficient monitoring and real-time feedback of track conditions, reducing race interruptions or delays caused by untimely manual checks. This helps maintain the smooth flow of the race and ensures it proceeds as planned. Fourth, accurate and timely obstacle detection and warning mechanisms help drivers better understand track dynamics, allowing them to focus on driving skills rather than dealing with unexpected situations. This enables drivers to enjoy the thrill of racing while ensuring safety, thus enhancing the overall driving experience.

[0310] To achieve the above embodiments, this application also proposes a vehicle alarm device.

[0311] Figure 14 A schematic diagram of another vehicle warning device provided for an exemplary embodiment of this application.

[0312] like Figure 14 As shown, the vehicle alarm device 1400 may include: an acquisition module 1410, a detection module 1420, and a transmission module 1430.

[0313] The acquisition module 1410 is used to acquire data collected by sensors within the target area; wherein the target area is the target track and / or the area near the target track.

[0314] The detection module 1420 is used to detect obstacles based on the scene feature library associated with the target track and the data collected by the sensor to obtain obstacle information;

[0315] The sending module 1430 is used to send obstacle information to the target vehicle; wherein the target vehicle is a vehicle participating in the race on the target track, and the obstacle information is used to issue an alarm to the target vehicle.

[0316] Further, in one implementation of this application embodiment, the scene feature library includes feature maps of track elements, and the track elements include track identifiers and / or track service facilities; the detection module 1420 is used to: extract features from the data collected by the sensor to obtain target features; match the target features with the feature maps of track elements in the scene feature library to obtain a first identification result; wherein the first identification result is used to indicate at least one of the category, geographical location, and orientation of the track elements existing in the target area, or the first identification result is used to indicate that there are no track elements in the target area; perform obstacle identification on the target features to obtain a second identification result; wherein the second identification result is used to indicate at least one of the category, geographical location, and orientation of the movable target existing in the target area, or the second identification result is used to indicate that there are no movable targets in the target area; generate obstacle information based on the first identification result and the second identification result.

[0317] In one implementation of this application, the scene feature library is generated using the following modules:

[0318] The first receiving module is used to receive input information sent by the track management terminal; wherein, the input information is used to indicate the various track elements in the track venue where the target track is located and the geographical location of the track elements;

[0319] The first generation module is used to generate a scene feature library based on the entered information.

[0320] In one implementation of this application, the input information is generated using the following module:

[0321] The selection module is used to respond to configuration operations and select the track element associated with the target track from various types of track elements in the management page;

[0322] The determination module is used to determine the geographical location of the associated track elements from the electronic map displaying the target track in response to configuration operations on the associated track elements.

[0323] The second generation module is used to generate input information based on the associated track elements and corresponding geographical locations.

[0324] In one implementation of this application, the vehicle alarm device 1300 may further include:

[0325] The second receiving module is used to receive update information sent by the track management terminal; wherein, the update information is used to indicate the track elements that have been updated in the target track and the geographical location of the updated track elements;

[0326] The update module is used to update the scene feature library based on update information.

[0327] It should be noted that the foregoing explanation of the vehicle alarm method embodiment executed in the cloud also applies to the vehicle alarm device of this embodiment, and will not be repeated here.

[0328] In the vehicle warning device of this application embodiment, obstacle detection is performed on data collected by sensors in the target track and / or the area near the target track based on a scene feature library associated with the target track, to obtain obstacle information, and vehicle warnings are issued based on the obstacle information. This has at least the following advantages: First, it can acquire and identify obstacle information in the vehicle's environment in real time. Compared with traditional methods that rely on manual patrols or race broadcasts, this method greatly improves the timeliness and location accuracy of obstacle identification (including track markings, track service facilities, and dynamic obstacles temporarily encroaching on the track), allowing racers (or drivers) to understand the road conditions ahead more promptly and accurately, thereby making safer and more effective driving decisions and improving vehicle safety. Second, it can not only identify static obstacles, such as track elements (including track markings, track service equipment, etc.), but also effectively detect dynamic obstacles on the track, such as movable targets (including animals or other foreign objects encroaching on the track). Once a potential threat is detected, the vehicle can issue a vehicle warning based on the obstacle information, notifying the racer in advance to take appropriate measures to avoid possible collisions, greatly enhancing the safety of the race. Third, it enables efficient monitoring and real-time feedback of track conditions, reducing race interruptions or delays caused by untimely manual checks. This helps maintain the smooth flow of the race and ensures it proceeds as planned. Fourth, accurate and timely obstacle detection and warning mechanisms help drivers better understand track dynamics, allowing them to focus on driving skills rather than dealing with unexpected situations. This enables drivers to enjoy the thrill of racing while ensuring safety, thus enhancing the overall driving experience.

[0329] To implement the above embodiments, this application also proposes a cloud platform, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the program, it implements the aforementioned... Figures 8 to 9 The vehicle alarm method described in any embodiment.

[0330] To implement the above embodiments, this application also proposes a vehicle, including: a processor; and a memory for storing processor-executable instructions; wherein the processor is configured to: implement as described above. Figures 1 to 7 The vehicle alarm method described in any embodiment.

[0331] Figure 15This is a block diagram illustrating a vehicle 1500 according to an exemplary embodiment. For example, vehicle 1500 may be a hybrid vehicle, a non-hybrid vehicle, an electric vehicle, a fuel cell vehicle, or other types of vehicle. Vehicle 1500 may be an autonomous vehicle, a semi-autonomous vehicle, or a non-autonomous vehicle.

[0332] Reference Figure 15 The vehicle 1500 may include various subsystems, such as an infotainment system 1510, a perception system 1520, a decision control system 1530, a drive system 1540, and a computing platform 1550. The vehicle 1500 may also include more or fewer subsystems, and each subsystem may include multiple components. Furthermore, each subsystem and component of the vehicle 1500 can be interconnected via wired or wireless means.

[0333] In some embodiments, the infotainment system 1510 may include a communication system, an entertainment system, and a navigation system, etc.

[0334] The perception system 1520 may include several sensors for sensing information about the environment surrounding the vehicle 1500. For example, the perception system 1520 may include a global positioning system (which may be a GPS system, a BeiDou system, or another positioning system), an inertial measurement unit (IMU), a lidar, a millimeter-wave radar, an ultrasonic radar, and a camera device.

[0335] The decision control system 1530 may include a computing system, a vehicle controller, a steering system, a throttle, and a braking system.

[0336] The drive system 1540 may include components that provide powered motion to the vehicle 1500. In one embodiment, the drive system 1540 may include an engine, an energy source, a transmission system, and wheels. The engine may be one or a combination of internal combustion engines, electric motors, and compressed air engines. The engine is capable of converting energy provided by the energy source into mechanical energy.

[0337] Some or all of the functions of the vehicle 1500 are controlled by a computing platform 1550. The computing platform 1550 may include at least one processor 1551 and a memory 1552, the processor 1551 being able to execute instructions 1553 stored in the memory 1552.

[0338] Processor 1551 can be any conventional processor, such as a commercially available CPU. Processors may also include graphics processing units (GPUs), field-programmable gate arrays (FPGAs), systems-on-chips (SoCs), application-specific integrated circuits (ASICs), or combinations thereof.

[0339] The memory 1552 can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic storage, flash memory, magnetic disk or optical disk.

[0340] In addition to instruction 1553, memory 1552 can also store data, such as road maps, route information, vehicle position, direction, speed, and other data. The data stored in memory 1552 can be used by computing platform 1550.

[0341] In this embodiment of the application, processor 1551 may execute instruction 1553 to complete the above-described steps 1 to 2. Figure 6 All or part of the steps in any method embodiment.

[0342] To implement the above embodiments, this application also proposes a chip, wherein the chip includes an interface circuit and a processing circuit coupled to each other. The interface circuit is used to input or output signals, and the processing circuit is configured to execute the vehicle alarm method provided in any of the foregoing embodiments.

[0343] Figure 16 This is a schematic diagram of the structure of a chip proposed in an exemplary embodiment of this application. See also... Figure 16 The diagram shown is a schematic representation of the structure of chip 1600, but it is not limited to this.

[0344] Chip 1600 includes processing circuitry 1601, which is configured to execute any of the above vehicle alarm methods.

[0345] In some embodiments, chip 1600 further includes one or more interface circuits 1602. Optionally, interface circuit 1602 is connected to memory 1603, and interface circuit 1602 can be used to receive signals from memory 1603 or other devices, and interface circuit 1602 can be used to send signals to memory 1603 or other devices. For example, interface circuit 1602 can read instructions stored in memory 1603 and send the instructions to processing circuit 1601.

[0346] In some embodiments, the interface circuit 1602 performs at least one of the communication steps such as sending and / or receiving in the above method, while the processing circuit 1601 performs other steps.

[0347] In some embodiments, the terms interface circuit, interface, transceiver pin, transceiver, etc., can be used interchangeably.

[0348] In some embodiments, chip 1600 further includes one or more memories 1603 for storing instructions. Optionally, all or part of the memories 1603 may be located outside of chip 1600.

[0349] To implement the above embodiments, this application also proposes a non-transitory computer-readable storage medium storing a computer program thereon, which, when executed by a processor, implements the vehicle alarm method as described in any of the foregoing method embodiments.

[0350] To implement the above embodiments, this application also proposes a computer program product having a computer program stored thereon, wherein the computer program, when executed by a processor, implements the vehicle alarm method as described in any of the foregoing method embodiments.

[0351] In the description of this specification, the references to terms such as "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., refer to specific features, structures, materials, or characteristics described in connection with that embodiment or example, which are included in at least one embodiment or example of this application. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples. Moreover, without contradiction, those skilled in the art can combine and integrate the different embodiments or examples described in this specification, as well as the features of different embodiments or examples.

[0352] Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one of that feature. In the description of this application, "multiple" means at least two, such as two, three, etc., unless otherwise explicitly specified.

[0353] Any process or method description in the flowchart or otherwise herein can be understood as representing a module, segment, or portion of code comprising one or more executable instructions for implementing custom logic functions or processes, and the scope of the preferred embodiments of this application includes additional implementations in which functions may be performed not in the order shown or discussed, including substantially simultaneously or in reverse order depending on the functions involved, as should be understood by those skilled in the art to which embodiments of this application pertain.

[0354] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as a ordered list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by, or in conjunction with, an instruction execution system, apparatus, or device (such as a computer-based system, a processor-including system, or other system that can fetch and execute instructions from, an instruction execution system, apparatus, or device). For the purposes of this specification, "computer-readable medium" can be any means that can contain, store, communicate, propagate, or transmit programs for use by, or in conjunction with, an instruction execution system, apparatus, or device. More specific examples of computer-readable media (a non-exhaustive list) include: electrical connections (electronic devices) having one or more wires, portable computer disk drives (magnetic devices), random access memory (RAM), read-only memory (ROM), erasable and editable read-only memory (EPROM or flash memory), fiber optic devices, and compact disc read-only memory (CDROM). Furthermore, computer-readable media can even be paper or other suitable media on which the program can be printed, because the program can be obtained electronically, for example, by optically scanning the paper or other medium, followed by editing, interpreting, or otherwise processing as necessary, and then stored in computer memory.

[0355] It should be understood that various parts of this application can be implemented using hardware, software, firmware, or a combination thereof. In the above embodiments, multiple steps or methods can be implemented using software or firmware stored in memory and executed by a suitable instruction execution system. For example, if implemented in hardware as in another embodiment, it can be implemented using any one or a combination of the following techniques known in the art: discrete logic circuits having logic gates for implementing logical functions on data signals, application-specific integrated circuits (ASICs) having suitable combinational logic gates, programmable gate arrays (PGAs), field-programmable gate arrays (FPGAs), etc.

[0356] Those skilled in the art will understand that all or part of the steps of the methods in the above embodiments can be implemented by a program instructing related hardware. The program can be stored in a computer-readable storage medium, and when executed, the program includes one or a combination of the steps of the method embodiments.

[0357] Furthermore, the functional units in the various embodiments of this application can be integrated into a processing module, or each unit can exist physically separately, or two or more units can be integrated into a module. The integrated module can be implemented in hardware or as a software functional module. If the integrated module is implemented as a software functional module and sold or used as an independent product, it can also be stored in a computer-readable storage medium.

[0358] The storage medium mentioned above can be a read-only memory, a disk, or an optical disk, etc. Although embodiments of this application have been shown and described above, it is understood that the above embodiments are exemplary and should not be construed as limiting this application. Those skilled in the art can make changes, modifications, substitutions, and variations to the above embodiments within the scope of this application.

Claims

1. A vehicle alarm method, characterized in that, include: Acquire data collected by sensors within the target area; wherein the target area is the target track and / or the area near the target track; In response to the data collected by the sensor containing obstacle information, a first warning message is issued to the target vehicle; wherein, the target vehicle is a vehicle participating in the race on the target track.

2. The method according to claim 1, characterized in that, The method further includes: In response to the removal of the obstacle from the target area, a second alarm message is issued to the target vehicle; wherein the second alarm message is used to indicate that the obstacle has been removed from the target area.

3. The method according to claim 1, characterized in that, The obstacle information includes the category to which the obstacle belongs. The response to the data collected by the sensor containing the obstacle information, issuing a first warning to the target vehicle, includes: Based on the category to which the obstacle belongs, a first alarm message matching the category is generated, and the first alarm message is sent to the target vehicle.

4. The method according to claim 1, characterized in that, The obstacle information includes the position of the obstacle relative to the target vehicle. The response to the data collected by the sensor containing the obstacle information, issuing a first warning message to the target vehicle, includes: From the display interface of the target vehicle, determine the alarm area that matches the location; The first alarm information is displayed in the alarm area.

5. The method according to claim 1, characterized in that, The obstacle information includes the geographical location of the obstacle. The response to the data collected by the sensor containing the obstacle information, issuing a first warning message to the target vehicle, includes: Based on the geographical location, determine the distance between the target vehicle and the obstacle; Based on the distance, generate a first alarm message matching the distance, and send the first alarm message to the target vehicle.

6. The method according to claim 1, characterized in that, The obstacle information includes the obstacle's category and geographical location. In response to the data collected by the sensor containing the obstacle information, a first warning message is issued to the target vehicle, including: The distance between the target vehicle and the obstacle is determined based on the actual location of the target vehicle and the geographical location of the obstacle. Based on the distance and the speed of the target vehicle, determine the travel time of the target vehicle to the obstacle; Based on the driving time and the category of the obstacle, a first alarm message is generated and sent to the target vehicle.

7. The method according to claim 6, characterized in that, Determining the travel time of the target vehicle to the obstacle based on the distance and the vehicle's speed includes: The initial time taken for the target vehicle to travel to the obstacle is determined based on the ratio of the distance to the speed of the target vehicle. The initial duration is corrected based on the hardware parameters associated with the target vehicle and / or the environmental parameters associated with the target track to obtain the driving duration.

8. The method according to claim 6, characterized in that, The first alarm message is generated based on the driving time and the category of the obstacle, including: In response to the obstacle including track elements associated with the target track, and the driving time satisfying the alarm triggering timing associated with the track element, a first alarm message associated with the track element is generated according to the category to which the track element belongs; The track elements include track signage and / or track service facilities.

9. The method according to claim 8, characterized in that, The alarm triggering timing is obtained by labeling the track elements based on the environmental parameters associated with the target track. The alarm triggering timing includes: the driving time reaching the time threshold associated with the track element.

10. The method according to claim 8, characterized in that, The track elements are displayed on the target track side of the electronic map, and the issuance of the first alarm message to the target vehicle includes: On the electronic map, the first alarm information is displayed in the area surrounding the track element.

11. The method according to claim 6, characterized in that, The first alarm message is generated based on the driving time and the category of the obstacle, including: In response to the obstacle including a movable target, the risk level posed by the movable target to the safe driving of the target vehicle is determined based on the driving time and the category to which the movable target belongs; The first alarm message is generated based on the category to which the movable target belongs and the risk level.

12. The method according to any one of claims 6-11, characterized in that, The step of generating a first alarm message based on the driving time and the category of the obstacle, and sending the first alarm message to the target vehicle, includes: In response to the obstacle including a movable target and a track element, a first alarm message for the track element is generated based on the travel time of the target vehicle to the track element and the category to which the track element belongs; and a first alarm message for the movable target is generated based on the travel time of the target vehicle to the movable target and the category to which the movable target belongs. Based on the alarm priorities corresponding to the movable target and the track element, the first alarm information for the movable target and the first alarm information for the track element are sent to the target vehicle.

13. The method according to any one of claims 1-11, characterized in that, The method further includes: Obtain a scene feature library associated with the target track from the cloud; wherein, the scene feature library includes feature maps of track elements, and the track elements include track identifiers and / or track service facilities; Based on the scene feature library, query the track data associated with the target track to obtain the geographical location of each track element; Based on the geographical location of each track element, each track element is displayed on an electronic map.

14. The method according to claim 13, characterized in that, The display of each track element on the electronic map based on its geographical location includes: Based on the geographical location of any track element, the screen size of the display screen showing the electronic map, and the actual size of the target track, the geographical location of any track element is projected onto the display screen to obtain the projected coordinates of any track element on the display screen. Based on the projected coordinates of any track element, the track element is displayed on the electronic map.

15. The method according to any one of claims 1-11, characterized in that, The method further includes: Send the first alarm information to the target object associated with the target track; wherein the target object is used to manage the target track.

16. The method according to any one of claims 1-11, characterized in that, The first alarm message includes at least one of the following: Visual alarm information; wherein the visual alarm information includes at least one of the following: symbol information displayed on the user interface, animation information displayed on the user interface, and alarm information in the head-up display (HUD); Auditory alarm information; wherein the alarm form of the auditory alarm information includes at least one of voice broadcast, buzzer sound, and warning sound; Tactile alarm information; wherein the alarm form of the tactile alarm information includes at least one of the following: steering wheel vibration, seat vibration, seat belt vibration, accelerator pedal feedback, and brake pedal feedback; Perceive alarm information; wherein, the alarm forms of perceived alarm information include at least one of ambient light alarm and exterior light warning; Alarm messages sent via wearable devices.

17. A vehicle alarm method, characterized in that, include: Acquire data collected by sensors within the target area; wherein the target area is the target track and / or the area near the target track; Based on the scene feature library associated with the target track, obstacle detection is performed on the data collected by the sensors to obtain obstacle information; The obstacle information is sent to the target vehicle; wherein the target vehicle is a vehicle participating in the race on the target track, and the obstacle information is used to issue an alarm to the target vehicle.

18. The method according to claim 17, characterized in that, The scene feature library includes feature maps of track elements, which include track identifiers and / or track service facilities. The obstacle detection process, based on a scene feature library associated with the target track, performs obstacle detection on the data collected by the sensors to obtain obstacle information, including: Feature extraction is performed on the data collected by the sensor to obtain the target features; The target feature is matched with the feature map of the track element in the scene feature library to obtain a first recognition result; wherein, the first recognition result is used to indicate at least one of the category, geographical location and orientation of the track element existing in the target area, or, the first recognition result is used to indicate that the track element does not exist in the target area; Obstacle identification is performed on the target features to obtain a second identification result; wherein, the second identification result is used to indicate at least one of the category, geographical location and orientation of the movable target existing in the target area, or, the second identification result is used to indicate that the movable target does not exist in the target area; The obstacle information is generated based on the first recognition result and the second recognition result.

19. The method according to claim 17, characterized in that, The scene feature library is generated using the following steps: Receive input information sent by the track management terminal; wherein, the input information is used to indicate the various track elements in the venue where the target track is located and the geographical location of the track elements; The scene feature library is generated based on the entered information.

20. The method according to claim 19, characterized in that, The entered information is generated using the following steps: In response to the configuration operation, select the track element associated with the target track from various types of track elements in the management page; In response to the configuration operation of the associated track element, the geographical location of the associated track element is determined from the electronic map displaying the target track; The input information is generated based on the associated track elements and their corresponding geographical locations.

21. The method according to claim 19, characterized in that, The method further includes: Receive update information sent by the track management terminal; wherein the update information is used to indicate the track elements that have been updated in the target track and the geographical location of the updated track elements; The scene feature library is updated based on the updated information.

22. A vehicle alarm device, characterized in that, include: An acquisition module is used to acquire data collected by sensors within a target area; wherein, the target area is the target track and / or the area near the target track; An alarm module is used to issue a first alarm message to the target vehicle in response to the data collected by the sensor containing obstacle information; wherein the target vehicle is a vehicle participating in the race on the target track.

23. The apparatus according to claim 22, characterized in that, The alarm module is also used for: In response to the removal of the obstacle from the target area, a second alarm message is issued to the target vehicle; wherein the second alarm message is used to indicate that the obstacle has been removed from the target area.

24. The apparatus according to claim 22, characterized in that, The obstacle information includes the category to which the obstacle belongs, and the alarm module is used for: Based on the category to which the obstacle belongs, a first alarm message matching the category is generated, and the first alarm message is sent to the target vehicle.

25. The apparatus according to claim 22, characterized in that, The obstacle information includes the position of the obstacle relative to the target vehicle, and the alarm module is used for: From the display interface of the target vehicle, determine the alarm area that matches the location; The first alarm information is displayed through the alarm area.

26. The apparatus according to claim 22, characterized in that, The obstacle information includes the geographical location of the obstacle; the alarm module is used for: Based on the geographical location, determine the distance between the target vehicle and the obstacle; Based on the distance, generate a first alarm message matching the distance, and send the first alarm message to the target vehicle.

27. The apparatus according to any one of claims 21-25, characterized in that, The first alarm message includes at least one of the following: Visual alarm information; wherein the visual alarm information includes at least one of the following: symbol information displayed on the user interface, animation information displayed on the user interface, and alarm information in the head-up display (HUD); Auditory alarm information; wherein the alarm form of the auditory alarm information includes at least one of voice broadcast, buzzer sound, and warning sound; Tactile alarm information; wherein the alarm form of the tactile alarm information includes at least one of the following: steering wheel vibration, seat vibration, seat belt vibration, accelerator pedal feedback, and brake pedal feedback; Perceive alarm information; wherein, the alarm forms of perceived alarm information include at least one of ambient light alarm and exterior light warning; Alarm messages sent via wearable devices.

28. A vehicle alarm device, characterized in that, include: An acquisition module is used to acquire data collected by sensors within a target area; wherein, the target area is the target track and / or the area near the target track; The detection module is used to perform obstacle detection on the data collected by the sensors based on the scene feature library associated with the target track, and obtain obstacle information; The sending module is used to send the obstacle information to the target vehicle; wherein the target vehicle is a vehicle participating in the race on the target track, and the obstacle information is used to issue an alarm to the target vehicle.

29. The apparatus according to claim 28, characterized in that, The scene feature library includes feature maps of track elements, which include track identifiers and / or track service facilities; the detection module is used for: Feature extraction is performed on the data collected by the sensor to obtain the target features; The target feature is matched with the feature map of the track element in the scene feature library to obtain a first recognition result; wherein, the first recognition result is used to indicate at least one of the category, geographical location and orientation of the track element existing in the target area, or, the first recognition result is used to indicate that the track element does not exist in the target area; Obstacle identification is performed on the target features to obtain a second identification result; wherein, the second identification result is used to indicate at least one of the category, geographical location and orientation of the movable target existing in the target area, or, the second identification result is used to indicate that the movable target does not exist in the target area; The obstacle information is generated based on the first recognition result and the second recognition result.

30. A vehicle, characterized in that, include: processor; Memory used to store processor-executable instructions; The processor is configured as follows: The steps of implementing the method as described in any one of claims 1 to 16.

31. A cloud platform, characterized in that, It includes a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the program, it implements the steps of the method as described in any one of claims 17 to 21.

32. A non-transitory computer-readable storage medium having computer program instructions stored thereon, characterized in that, When executed by a processor, the program instructions implement the steps of the method according to any one of claims 1 to 16, and / or implement the steps of the method according to any one of claims 17 to 21.

33. A chip, characterized in that, The chip includes an interface circuit and a processing circuit that are coupled to each other. The interface circuit is used to input or output signals, and the processing circuit is used to implement the method of any one of claims 1 to 16, and / or to implement the method of any one of claims 17 to 21.

34. A computer program product, characterized in that, The method includes a computer program that, when executed by a processor, implements the steps of the method according to any one of claims 1 to 16, and / or implements the steps of the method according to any one of claims 17 to 21.

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