A vehicle-machine linkage reminding method and device and vehicle

Abstract

The application discloses a car-machine linkage reminding method and device and a vehicle, relates to the technical field of vehicle function safety reminding, and can effectively determine other vehicles driving near the target vehicle by acquiring a real-time fusion perception space corresponding to the target vehicle. Then, in the case that a takeover alarm revision coefficient is greater than a preset alarm threshold, a takeover alarm information is sent through a car machine of the target vehicle, reminding of the target vehicle driver is realized, abnormal reminding information is sent to other vehicles in the real-time fusion perception space, other vehicles can timely find abnormal vehicles around, car-machine linkage reminding is realized, and driving safety is improved.

Description

Technical Field

[0001] This application relates to the field of vehicle functional safety reminder technology, and more specifically, to a vehicle-machine linkage reminder method, device, and vehicle. Background Technology

[0002] Functional safety in intelligent driving has become a major development direction in functional safety, and in-vehicle alerts are undoubtedly an indispensable safety mechanism. However, in modern society where intelligent driving is becoming increasingly widespread, the role of in-vehicle alerts for drivers is gradually weakening. Related technologies for takeover alarm functions in Level 2 autonomous driving systems can proactively predict the system's control capabilities and revise the prediction results based on driver status and environmental conditions. Finally, the prediction is compared with the takeover alarm request trigger threshold to confirm whether to issue a takeover alarm and the alarm level. If the driver's takeover time exceeds the allowed time, the vehicle will stop to enter a safe state. Although the alarm message alerts the driver, this singular alert method may prevent the driver from promptly noticing the takeover alarm information, and the driver's failure to take over in time may threaten the safe driving of other vehicles. Summary of the Invention

[0003] This application aims to provide a vehicle-machine linkage reminder method, device, and vehicle, which addresses the problem that related technologies may fail to provide timely takeover alarm information due to a single reminder method, and that failure to take over in a timely manner may threaten the safe driving of other vehicles.

[0004] The first aspect of this application provides a vehicle-machine linkage reminder method, including: The real-time speed of the target vehicle is obtained, and the real-time fusion perception space corresponding to the target vehicle is obtained based on the real-time speed. The driver status and driving environment conditions are obtained, and the takeover alarm revision coefficient is determined based on the driver status and driving environment conditions. If the takeover alarm revision coefficient is greater than the preset alarm threshold, a takeover alarm message will be issued through the vehicle's infotainment system in the target vehicle, and an abnormality alert message will be sent to other vehicles in the real-time fusion perception space.

[0005] In this solution, by acquiring the real-time fusion perception space corresponding to the target vehicle, other vehicles driving near the target vehicle can be effectively identified. Then, if the takeover alarm revision coefficient exceeds a preset alarm threshold, the target vehicle's in-vehicle system issues a takeover alarm, alerting the driver of the target vehicle. Simultaneously, it sends anomaly alerts to other vehicles within the real-time fusion perception space, enabling them to promptly detect abnormal vehicles nearby. This vehicle-to-in-vehicle linkage alert enhances driving safety. After other vehicles receive the anomaly alert, the owner or the in-vehicle system can proactively issue auxiliary alerts, reducing the likelihood of the target vehicle's driver missing the takeover time and causing the vehicle to automatically engage parking measures, thus improving the user experience.

[0006] In conjunction with the first aspect, in one possible implementation, acquiring the real-time speed of the target vehicle and acquiring the real-time fusion perception space corresponding to the target vehicle based on the real-time speed includes: The real-time speed of the target vehicle is obtained, and the voxel unit corresponding to the target vehicle is obtained based on the real-time speed. Based on the voxel units corresponding to the target vehicle and the voxel units corresponding to other vehicles, overlapping voxel units are determined; Based on the overlapping voxel units, the voxel units of the target vehicle are fused with the voxel units of other vehicles to obtain the real-time fused perception space corresponding to the target vehicle.

[0007] In this solution, a real-time fusion perception space for the target vehicle is constructed, providing a foundation for vehicle-machine linkage reminders to be integrated into vehicle collaboration and interoperability, thereby improving the utilization rate of vehicle collaboration.

[0008] In conjunction with the first aspect, in one possible implementation, before acquiring the driver's state and driving environment conditions, the method further includes: Obtain the distance data between the target vehicle and the lane line; If the distance data is less than a preset distance threshold, continue to acquire the driver status and driving environment conditions; If the distance data is greater than or equal to a preset distance threshold, the process of obtaining the driver's status and driving environment conditions will not be initiated, and the distance data will continue to be monitored.

[0009] In this solution, by monitoring the distance data between the target vehicle and the lane line, it is possible to effectively determine whether the user needs to be reminded, thus ensuring that ineffective reminders are avoided.

[0010] In conjunction with the first aspect, in one possible implementation, the step of acquiring the driver's state and driving environment conditions, and determining the takeover alarm revision coefficient based on the driver's state and driving environment conditions, includes: Acquire driver status; the driver status includes whether the driver is fatigued or in a normal state. Based on the driver's status, determine the status alarm revision coefficient; Acquire driving environment conditions; the driving environment conditions include a first distance between the target vehicle and the road boundary and a second distance between the target vehicle and other vehicles; Based on the aforementioned driving environment conditions, determine the environmental alarm revision coefficient; The takeover alarm revision coefficient is obtained based on the status alarm revision coefficient and the environment alarm revision coefficient.

[0011] In this solution, the driver's status is combined with the driving environment conditions to determine the takeover alarm revision coefficient. This takeover alarm revision coefficient can evaluate whether the driver of the target vehicle needs to be reminded, providing a basis for vehicle-machine linkage reminders.

[0012] In conjunction with the first aspect, in one possible implementation, determining the status alarm revision coefficient based on the driver's status includes: When the driver's status is that the driver is in a normal state, the status alarm revision coefficient is determined to be the first preset coefficient; When the driver is in a state of fatigue, the status alarm revision coefficient is determined to be the second preset coefficient; the second preset coefficient is greater than the first preset coefficient.

[0013] In this solution, when the driver is in a normal state, it can be assumed that the driver is less likely to be distracted, so the status alarm revision coefficient can be set to the first preset coefficient. However, when the driver is fatigued, the driver may be driving abnormally, so the status alarm revision coefficient needs to be set to the second preset coefficient, which is greater than the first preset coefficient, thereby increasing the probability of triggering the vehicle-machine linkage reminder and improving the driver's driving safety.

[0014] In conjunction with the first aspect, in one possible implementation, determining the environmental alarm revision coefficient based on the driving environment conditions includes: The nearest distance is determined based on a first distance between the target vehicle and the road boundary and a second distance between the target vehicle and other vehicles; The environmental alarm revision coefficient is determined based on the nearest distance; the environmental alarm revision coefficient is inversely proportional to the nearest distance.

[0015] In this scheme, the greater the closest distance between the target vehicle and the road boundary and other vehicles, the longer the reaction time for the driver is expected. Therefore, a smaller environmental alarm revision coefficient can be set. As the closest distance decreases, the shorter the reaction time for the driver is expected. Therefore, the environmental alarm revision coefficient can be gradually increased, thereby increasing the probability of triggering the vehicle-machine linkage reminder and improving the driver's driving safety.

[0016] In conjunction with the first aspect, in one possible implementation, issuing anomaly alerts to other vehicles within the real-time fused perception space includes: Based on the real-time fusion perception space of the target vehicle, the relative positional relationship between the target vehicle and other vehicles is determined; An anomaly alert is generated, which carries the relative positional relationship between the target vehicle and other vehicles, and the anomaly alert is sent to other vehicles in the real-time fusion perception space.

[0017] This solution enhances the perception accuracy and precision of intelligent driving by leveraging real-time fusion perception space. When the driver of the target vehicle needs to be alerted, the abnormality alert information can be sent to other eligible vehicles via the vehicle's fusion perception space, and the source of the message can be displayed on the in-vehicle infotainment system of those other vehicles. Drivers of other vehicles receiving the abnormality alert information can then react appropriately based on the specific circumstances, such as honking their horn or paying more attention to the source vehicle, thereby increasing the likelihood and effectiveness of successful functional safety alerts.

[0018] In conjunction with the first aspect, in one possible implementation, after the takeover alarm information is issued via the vehicle's infotainment system of the target vehicle, the method further includes: If the time without intervention of the target vehicle exceeds a preset time without intervention threshold, the automatic parking function is triggered to automatically drive the target vehicle to a safe area for parking; the safe area is a pre-set parking area.

[0019] In this solution, by automatically driving the target vehicle to a safe area for parking, the driver's driving safety can be guaranteed in extreme abnormal situations.

[0020] A second aspect of this application provides a vehicle-mounted infotainment system alert device, comprising: The fusion perception module is used to acquire the real-time speed of the target vehicle and acquire the real-time fusion perception space corresponding to the target vehicle based on the real-time speed. The coefficient acquisition module is used to acquire the driver's status and driving environment conditions, and determine the takeover alarm revision coefficient based on the driver's status and driving environment conditions. The linkage reminder module is used to send a takeover alarm message through the vehicle's infotainment system when the takeover alarm revision coefficient is greater than a preset alarm threshold, and to send an abnormality reminder message to other vehicles in the real-time fusion perception space.

[0021] A third aspect of this application provides a vehicle that includes the vehicle-machine linkage reminder device as described in the second aspect.

[0022] The technical effects of any of the implementation methods in the second and third aspects can be found in the technical effects of different implementation methods in the first aspect, and will not be repeated here. Attached Figure Description

[0023] To more clearly illustrate the technical solutions of the embodiments of this application, the drawings used in the description of the embodiments of this application will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0024] Figure 1 This is a schematic flowchart of a vehicle-machine linkage reminder method proposed in an embodiment of this application; Figure 2 This is a schematic diagram of the process for obtaining the takeover alarm revision coefficient according to an embodiment of this application; Figure 3 This is a schematic diagram of the structure of a vehicle-machine linkage reminder device according to an embodiment of this application; Figure 4 This is a schematic diagram of the structure of an electronic device according to an embodiment of this application; Explanation of reference numerals in the attached figures: 301-Fusion sensing module, 302-Coefficient acquisition module, 303-Linkage reminder module, 401-Memory, 402-Processor, 403-Communication bus. Detailed Implementation

[0025] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, not all embodiments. All other embodiments obtained by those skilled in the art based on the embodiments of this application without creative effort are within the scope of protection of this application.

[0026] In related technologies, if the driver takes over for longer than the permitted time after being alerted, the vehicle will stop to enter a safe state. Although an alarm message alerts the driver, this single-method alert may prevent the driver from noticing the takeover alarm in time, and the driver's failure to take over in a timely manner may threaten the safe driving of other vehicles.

[0027] In view of this, this application proposes a vehicle-to-vehicle (V2V) linkage alert method. By acquiring the real-time fusion perception space corresponding to the target vehicle, other vehicles driving near the target vehicle can be effectively identified. Then, when the takeover alarm revision coefficient is greater than a preset alarm threshold, the V2V system of the target vehicle issues a takeover alarm message, thus alerting the driver of the target vehicle. Simultaneously, it issues anomaly alert messages to other vehicles in the real-time fusion perception space, enabling other vehicles to promptly detect abnormal vehicles in the vicinity. This achieves V2V linkage alerts and improves driving safety. After other vehicles receive the anomaly alert message, the vehicle owner or the V2V system can proactively issue auxiliary alerts, reducing the possibility that the driver of the target vehicle may miss the takeover time, leading to the vehicle taking automatic parking measures and improving the user experience.

[0028] Please refer to Figure 1 This is a flowchart illustrating a vehicle-machine linkage reminder method provided in an embodiment of this application. Figure 1 As shown, this vehicle-machine linkage reminder method includes: S101. Obtain the real-time speed of the target vehicle, and obtain the real-time fusion perception space corresponding to the target vehicle based on the real-time speed.

[0029] Perception fusion refers to integrating perception information from different sensors or different channels of the same sensor to obtain more comprehensive and accurate perception results. In autonomous vehicles, perception fusion is a key technology to ensure safe and reliable vehicle operation. The real-time fused perception space corresponding to the target vehicle can be the perception space formed by the target vehicle's sensors combined with the sensors of other surrounding vehicles, which can effectively improve the target vehicle's perception range and enhance the assisted driving decision-making capabilities. In traditional fusion perception processes, the real-time fused perception space usually only serves to improve the perception range. The embodiments of this application utilize the mutual communication functions and mutual positional relationships of the real-time fused perception space to achieve vehicle-machine linkage reminders, which can effectively improve the reminder effectiveness to the driver of the target vehicle, while also informing other vehicles of the abnormal vehicle, ensuring the safe driving of other vehicles.

[0030] In one possible implementation, after obtaining the real-time speed of the target vehicle, the side length of the vehicle's bird's-eye view perception space can be determined based on the real-time speed of the target vehicle. With the target vehicle as the center and the side length as a constraint, the target bird's-eye view perception space corresponding to the target vehicle can be determined. The target bird's-eye view perception space is then divided into multiple voxel units. When there is an overlap between the voxel units of the target vehicle and those of other vehicles, the multiple voxel units of the target vehicle can be fused with those of other vehicles to form a real-time fused perception space for the target vehicle.

[0031] For example, the minimum braking distance of the target vehicle, its body length, and a pre-defined redundancy value within the voxel unit range can be added together, and the result can be used as the side length of the vehicle's bird's-eye view perception space, thus determining the target bird's-eye view perception space corresponding to the target vehicle. The minimum braking distance of the target vehicle refers to the shortest distance the vehicle travels from when the driver presses the brake pedal until it comes to a complete stop under current driving conditions. The pre-defined redundancy value within the voxel unit range is a pre-set constant value (e.g., 5 meters, 10 meters, etc.). Alternatively, the minimum braking distance can be determined based on the target vehicle's real-time speed, and then an integer multiple of the minimum braking distance (e.g., 2 times) can be used as the side length of the vehicle's bird's-eye view perception space, thus determining the target bird's-eye view perception space corresponding to the target vehicle. After determining the target bird's-eye view perception space corresponding to the target vehicle, it can be uniformly divided into N*N voxel units, where N represents the total number of voxel units contained in a row or column of the target bird's-eye view perception space. After dividing the voxel units, the two overlapping voxel units with the highest overlap between the target vehicle and other vehicle voxel units can be identified. Then, based on the relative positional relationship between the two overlapping voxel units, the relative positional relationship between multiple voxel units of the target vehicle and multiple voxel units of other vehicles can be determined. Finally, based on the relative positional relationship, multiple voxel units of the target vehicle and multiple voxel units of other vehicles are fused to form a real-time fused perception space of the target vehicle.

[0032] This application embodiment obtains the real-time fusion perception space corresponding to the target vehicle, which can effectively identify other vehicles that can perform vehicle-to-vehicle communication in the real-time fusion perception space. This allows functional safety reminders to be integrated into vehicle-to-vehicle communication, improving the effectiveness of functional safety vehicle-mounted reminders and increasing the utilization rate of vehicle-to-vehicle communication. It also builds a highly interconnected vehicle fusion perception space, achieving the dual realization of functional safety and multi-vehicle communication.

[0033] S102. Obtain the driver's status and driving environment conditions, and determine the takeover alarm revision coefficient based on the driver's status and driving environment conditions.

[0034] Driver status can generally be categorized into normal and fatigued states. A normal state refers to the driver driving normally without fatigue, while fatigued driving refers to the driver exhibiting signs of fatigue, such as drowsiness, frequent yawning, or exceeding a driving time threshold (typically set at 4 hours). Driving environment conditions refer to the road boundary information and other vehicle information surrounding the target vehicle during its operation. Determining the takeover alarm revision coefficient based on the driver status and driving environment conditions effectively determines whether a takeover alarm is necessary while the target vehicle is in motion.

[0035] In one possible implementation, different status alarm revision coefficients can be assigned to different driving states, and different environmental alarm revision coefficients can be assigned to different driving environment conditions. The takeover alarm revision coefficient is obtained by adding or weighting the status alarm revision coefficients and environmental alarm revision coefficients. A larger takeover alarm revision coefficient indicates a lower level of safety for the driver, requiring a takeover alarm reminder to the driver so that the driver can take over the vehicle immediately. For example, different status alarm revision coefficients can be assigned to normal and fatigued states, with the status alarm revision coefficient for fatigued states being greater than that for normal states. This ensures that the driver can be promptly reminded to take over the vehicle when fatigued, guaranteeing the driving safety of the target vehicle. After acquiring road boundary information and other vehicle information around the vehicle, the closest distance between the target vehicle and the road boundary or other vehicles can be determined. This closest distance indicates the probability of a collision between the target vehicle and the road boundary or other vehicles. The larger the closest distance, the lower the probability of the target vehicle colliding with the road boundary or other vehicles. Conversely, the smaller the closest distance, the higher the probability of colliding with the road boundary or other vehicles. Therefore, an environmental alarm revision coefficient that is inversely proportional to the closest distance can be set to enable the driver of the target vehicle to take immediate control of the vehicle when the collision risk increases, thus ensuring the driver's driving safety.

[0036] S103. If the takeover alarm revision coefficient is greater than the preset alarm threshold, the takeover alarm information will be sent through the vehicle's infotainment system of the target vehicle, and abnormal reminder information will be sent to other vehicles in the real-time fusion perception space.

[0037] The preset alarm threshold can be a constant value, indicating that the target vehicle's current driving behavior poses a risk and requires a vehicle-to-everything (V2X) alert. Therefore, if the alarm correction coefficient exceeds the preset alarm threshold, a V2X alert is required.

[0038] The vehicle-to-vehicle (V2V) linkage reminders described in this application primarily address driving situations where the driver needs to take over during intelligent driving but fails to do so in a timely manner, or other situations where the driver needs to be reminded. By issuing a takeover alarm to the target vehicle's V2V system, an initial reminder can be given to the driver of the target vehicle. Then, multi-vehicle collaboration for functional safety reminders is added. When the driver needs to be reminded, an anomaly reminder will be sent to other vehicles within the real-time fusion perception space. The source of the message will be reflected through the V2V system displays of other vehicles, enabling them to avoid the abnormal target vehicle or to honk their horns to remind the target vehicle. This increases the likelihood and effectiveness of successful functional safety reminders. Furthermore, through the auxiliary reminder function of other vehicles, the possibility of the driver missing the takeover time and causing the vehicle to take automatic parking measures is significantly reduced, thereby improving the user experience.

[0039] In one possible implementation, the real-time speed of the target vehicle is obtained, and the real-time fusion perception space corresponding to the target vehicle is obtained based on the real-time speed, including: Obtain the real-time speed of the target vehicle, and obtain the voxel unit corresponding to the target vehicle based on the real-time speed.

[0040] For example, the minimum braking distance of the target vehicle can be determined based on its real-time speed as: (real-time speed * real-time speed) / 2 * road friction coefficient * gravitational acceleration. Then, using an integer multiple of the minimum braking distance as the side length of the vehicle's bird's-eye view perception space, and with the target vehicle as the center and the side length as a constraint, the target bird's-eye view perception space corresponding to the target vehicle is determined. After uniformly dividing the target bird's-eye view perception space corresponding to the target vehicle, the voxel unit corresponding to the target vehicle is obtained.

[0041] Based on the voxel units corresponding to the target vehicle and the voxel units corresponding to other vehicles, the overlapping voxel units are determined.

[0042] The feature maps of the voxel units corresponding to the target vehicle and the voxel units corresponding to other vehicles can be matched to determine the two voxel units with the highest similarity between the feature maps as overlapping voxel units. One of these two overlapping voxel units comes from the voxel unit corresponding to the target vehicle, and the other comes from the voxel unit corresponding to other vehicles.

[0043] Based on the overlapping voxel units, the voxel units of the target vehicle are fused with the voxel units of other vehicles to obtain the real-time fused perception space corresponding to the target vehicle.

[0044] Two overlapping voxel units between the target vehicle and other vehicles. The relative positional relationship between these two overlapping voxel units often foreshadows the relative positional relationship between the target vehicle and other vehicles. Based on this, the relative positional relationship between the target vehicle's voxel units and the voxel units of other vehicles can be determined. This allows for the fusion of the target vehicle's voxel units with those of other vehicles, resulting in a real-time fused perception space corresponding to the target vehicle. Constructing this real-time fused perception space provides the foundation for integrating vehicle-to-everything (V2X) alerts into vehicle-to-everything (V2X) communication, thereby improving the utilization rate of vehicle collaboration.

[0045] In one possible implementation, before acquiring the driver's state and driving environment conditions, the method further includes: Obtain the distance data between the target vehicle and the lane lines.

[0046] If the distance data is less than the preset distance threshold, continue to acquire the driver status and driving environment conditions.

[0047] If the distance data is greater than or equal to the preset distance threshold, the process of obtaining the driver status and driving environment conditions will not be initiated, and the distance data will continue to be monitored.

[0048] Acquiring distance data between the target vehicle and lane lines refers to the minimum distance between the target vehicle and the left and right lane lines during normal driving or lane departure. If the distance between the target vehicle and lane lines is less than a preset distance threshold, it indicates a potential abnormal driving environment, requiring driver intervention during autonomous driving. The preset distance threshold is a limit on the minimum distance between the target vehicle and lane lines. If the minimum distance between the target vehicle and the left and right lane lines is lower than this limit, it suggests potential lane narrowing, road detours, or lane departure, necessitating driver intervention. By monitoring the distance data between the target vehicle and lane lines, it is possible to effectively determine whether a user needs to be alerted, preventing ineffective alerts.

[0049] Please refer to Figure 2 This is a schematic diagram of the process for obtaining the takeover alarm revision coefficient provided in an embodiment of this application. Figure 2 As shown, the driver's status and driving environment conditions are obtained, and the takeover alarm revision coefficient is determined based on the driver's status and driving environment conditions, including: S201. Obtain the driver's status; the driver's status includes whether the driver is fatigued or in a normal state.

[0050] A normal driving state refers to a driver driving normally without fatigue. Fatigue driving refers to a driver experiencing fatigue while driving, such as drowsiness, frequent yawning, or exceeding a driving time threshold. Driving status can be obtained through the target vehicle's fatigue monitoring system. This can be determined by analyzing the driver's facial features, eye signals, and head movements, among other physiological imaging responses.

[0051] S202. Determine the status alarm revision coefficient based on the driver's status.

[0052] Different status alarm revision coefficients can be assigned to different driving states, and different environmental alarm revision coefficients can be assigned to different driving environment conditions. Adding or weighting these two coefficients together yields the takeover alarm revision coefficient. A higher takeover alarm revision coefficient indicates a lower level of safety for the driver, requiring a takeover alarm alert to prompt the driver to take over the vehicle immediately. For example, different status alarm revision coefficients can be assigned to normal driving conditions and fatigued driving conditions, with the coefficient for fatigued driving conditions being higher than that for normal driving conditions. This ensures that the driver can be promptly alerted to take over the vehicle when fatigued, guaranteeing driving safety.

[0053] For example, the status alarm revision coefficient is determined based on the driver's state, including: when the driver is in a normal state, the status alarm revision coefficient is set to a first preset coefficient; when the driver is in a fatigued state, the status alarm revision coefficient is set to a second preset coefficient. The second preset coefficient is greater than the first preset coefficient. When the driver is in a normal state, the possibility of the driver being distracted is considered low, so the status alarm revision coefficient can be set to the first preset coefficient. However, when the driver is in a fatigued state, the driver may be driving abnormally, so the status alarm revision coefficient needs to be set to the second preset coefficient, which is greater than the first preset coefficient, thereby increasing the probability of triggering the vehicle-to-everything (V2X) linkage reminder and improving the driver's driving safety. For example, the first preset coefficient can be set to 0, and the second preset coefficient can be set to 1. That is, when the driver is in a normal state, the status alarm revision coefficient is set to 0, and when the driver is in a fatigued state, the status alarm revision coefficient is set to 1, making it easier to trigger the V2X linkage reminder when the driver is fatigued.

[0054] S203. Obtain driving environment conditions; driving environment conditions include the first distance between the target vehicle and the road boundary and the second distance between the target vehicle and other vehicles.

[0055] Driving environment conditions include the first distance between the target vehicle and the road boundary, which is the minimum distance between the target vehicle and the road boundary; similarly, the second distance between the target vehicle and other vehicles, which is the minimum distance between the target vehicle and other vehicles. These two minimum distances indicate whether a collision is likely to occur between the target vehicles.

[0056] S204. Determine the environmental alarm revision coefficient based on driving environment conditions.

[0057] For example, determining the environmental alarm revision coefficient based on driving environment conditions includes: determining the closest distance based on a first distance between the target vehicle and the road boundary and a second distance between the target vehicle and other vehicles. The environmental alarm revision coefficient is then determined based on the closest distance. The environmental alarm revision coefficient is inversely proportional to the closest distance. A larger closest distance between the target vehicle and the road boundary and other vehicles indicates a longer reaction time for the driver, allowing for a smaller environmental alarm revision coefficient. As the closest distance decreases, the driver's reaction time decreases, allowing for a gradually increasing environmental alarm revision coefficient, thereby increasing the probability of triggering the vehicle-mounted system alert and improving driver safety. For example, the closest distance can be increased by one and then the reciprocal taken to determine the environmental alarm revision coefficient, thus ensuring that a smaller closest distance results in a larger environmental alarm revision coefficient, meeting the alarm requirements. Alternatively, in practice, a certain reserve distance can be set. For example, if the reserve distance is set to 1 meter, then 2 / (nearest distance + 1) can be used as the environmental alarm revision coefficient. This ensures that when the first distance between the target vehicle and the road boundary, or the second distance between the target vehicle and other vehicles, is less than or equal to 1 meter (in which case the unit of the closest distance should be meters), the environmental alarm revision coefficient reaches its maximum. This allows the driver sufficient reaction time when the vehicle-to-everything (V2X) system provides a triggering alert. However, it's worth noting that setting the reserve distance to 1 is merely an example. Other values ​​can be set, such as 2 meters, 3 meters, 4 meters, etc., to provide the driver with takeover time.

[0058] S205. Obtain the takeover alarm revision coefficient based on the status alarm revision coefficient and the environmental alarm revision coefficient.

[0059] For example, the sum of the status alarm revision coefficient and the environmental alarm revision coefficient can be used as the takeover alarm revision coefficient, or the weighted sum of the status alarm revision coefficient and the environmental alarm revision coefficient can be used as the takeover alarm revision coefficient. However, different preset alarm thresholds need to be set for different calculation methods. For example, when using the sum of the status alarm revision coefficient and the environmental alarm revision coefficient as the takeover alarm revision coefficient, the preset alarm threshold can be set to 1.5 or 1.6. When the takeover alarm revision coefficient is greater than 1.5 or 1.6, a warning can be issued. When using the weighted sum of the status alarm revision coefficient and the environmental alarm revision coefficient as the takeover alarm revision coefficient, the takeover alarm revision coefficient will be less than 1 in most cases. Therefore, the preset alarm threshold can be set to 0.7, 0.8, or 0.9, so that when the takeover alarm revision coefficient is greater than 0.7, 0.8, or 0.9, a warning can be issued. By combining the driver's status with the driving environment conditions, the takeover alarm revision coefficient is determined. This takeover alarm revision coefficient can evaluate whether the driver of the target vehicle needs to be reminded, providing a basis for vehicle-machine linkage reminders.

[0060] In one possible implementation, an anomaly alert is sent to other vehicles within the real-time fused perception space, including: Based on the real-time fusion perception space of the target vehicle, the relative positional relationship between the target vehicle and other vehicles is determined.

[0061] Generate anomaly alert information carrying the relative positional relationship between the target vehicle and other vehicles, and send the anomaly alert information to other vehicles in the real-time fusion perception space.

[0062] The relative positional relationship between a target vehicle and other vehicles typically includes directional and distance relationships. When other vehicles receive an anomaly alert message containing this relative positional relationship, they can process it through their in-vehicle infotainment system to determine which vehicle is the target vehicle. The target vehicle can then be displayed on the in-vehicle infotainment system of other vehicles, thus achieving the alert function. For example, the target vehicle can be marked within the real-time fusion perception space of other vehicles and displayed on their in-vehicle screens.

[0063] Real-time fusion perception enhances the perception accuracy and precision of intelligent driving. When the driver of a target vehicle needs to be alerted, the abnormality alert can be sent to other eligible vehicles via the vehicle's fusion perception space, and the source of the message can be displayed on the other vehicles' in-vehicle systems. Drivers of other vehicles receiving the abnormality alert can then react appropriately based on the specific circumstances, such as honking their horn or paying more attention to the source vehicle, thus increasing the likelihood and effectiveness of the functional safety alert.

[0064] By integrating functional safety into multi-vehicle collaboration, the utilization rate of vehicle collaboration can be improved, a highly interconnected vehicle fusion perception space can be built, and the frequency of vehicles taking automatic parking measures can be reduced, thereby improving the user experience.

[0065] In one possible implementation, after the takeover alarm message is issued via the vehicle's infotainment system, the process further includes: If the unattended time of the target vehicle exceeds a preset unattended time threshold, the automatic parking function will be triggered, and the target vehicle will be automatically driven to a safe area for parking. The safe area is a pre-defined parking area.

[0066] If, after other vehicles in the real-time fusion perception space receive an anomaly alert, the driver of the target vehicle still fails to take over the vehicle for a period of time, and the non-takeover time of the target vehicle exceeds a preset non-takeover time threshold, the target vehicle can be controlled to take emergency measures and automatically park in a safe area, thereby ensuring the safety of the target vehicle.

[0067] Please refer to Figure 3 Based on the same inventive concept, another embodiment of this application provides a vehicle-mounted infotainment system reminder device, which includes: The fusion perception module 301 is used to acquire the real-time speed of the target vehicle and acquire the real-time fusion perception space corresponding to the target vehicle based on the real-time speed.

[0068] In one possible implementation, the fusion sensing module 301 includes a voxel unit acquisition submodule, an overlap unit determination submodule, and a sensing space acquisition submodule.

[0069] The voxel unit acquisition submodule is used to acquire the real-time speed of the target vehicle and acquire the voxel unit corresponding to the target vehicle based on the real-time speed.

[0070] The overlapping unit determination submodule is used to determine overlapping voxel units based on the voxel units corresponding to the target vehicle and the voxel units corresponding to other vehicles.

[0071] The perception space acquisition submodule is used to fuse the voxel units of the target vehicle with the voxel units of other vehicles based on the overlapping voxel units, so as to obtain the real-time fused perception space corresponding to the target vehicle.

[0072] The coefficient acquisition module 302 is used to acquire the driver status and driving environment conditions, and determine the takeover alarm revision coefficient based on the driver status and driving environment conditions.

[0073] In one possible implementation, the coefficient acquisition module 302 includes a status acquisition submodule, a first revised coefficient acquisition submodule, an environmental condition acquisition submodule, a second revised coefficient acquisition submodule, and a third revised coefficient acquisition submodule.

[0074] The status acquisition submodule is used to acquire the driver's status; the driver's status includes whether the driver is in a fatigued state or the driver is in a normal state.

[0075] The first revision coefficient acquisition submodule is used to determine the status alarm revision coefficient based on the driver's status.

[0076] For example, determining the status alarm revision coefficient based on the driver's status includes: when the driver's status is that the driver is in a normal state, determining the status alarm revision coefficient as a first preset coefficient; when the driver's status is that the driver is in a fatigued state, determining the status alarm revision coefficient as a second preset coefficient; the second preset coefficient is greater than the first preset coefficient.

[0077] An environmental condition acquisition submodule is used to acquire driving environmental conditions; the driving environmental conditions include a first distance between the target vehicle and the road boundary and a second distance between the target vehicle and other vehicles.

[0078] The second revision coefficient acquisition submodule is used to determine the environmental alarm revision coefficient based on the driving environment conditions.

[0079] For example, determining the environmental alarm revision coefficient based on the driving environment conditions includes: determining the closest distance based on a first distance between the target vehicle and the road boundary and a second distance between the target vehicle and other vehicles; determining the environmental alarm revision coefficient based on the closest distance; and the environmental alarm revision coefficient being inversely proportional to the closest distance.

[0080] The third revision coefficient acquisition submodule is used to obtain the takeover alarm revision coefficient based on the status alarm revision coefficient and the environmental alarm revision coefficient.

[0081] In one possible implementation, the coefficient acquisition module 302 further includes a vehicle driving status monitoring submodule, which is used to acquire distance data between the target vehicle and the lane line; if the distance data is less than a preset distance threshold, it continues to acquire driver status and driving environment conditions; if the distance data is greater than or equal to the preset distance threshold, it does not enter the process of acquiring driver status and driving environment conditions, but continues to monitor the distance data.

[0082] The linkage reminder module 303 is used to send a takeover alarm message through the vehicle's infotainment system when the takeover alarm revision coefficient is greater than the preset alarm threshold, and to send abnormal reminder messages to other vehicles in the real-time fusion perception space.

[0083] In one possible implementation, the linkage reminder module 303 includes a first reminder submodule and a second reminder submodule.

[0084] The first alert submodule is used to send a takeover alarm message through the vehicle's infotainment system when the takeover alarm revision coefficient is greater than the preset alarm threshold.

[0085] The second alert submodule is used to send abnormal alert information to other vehicles in the real-time fusion perception space when the alarm revision coefficient exceeds the preset alarm threshold.

[0086] For example, sending anomaly alert information to other vehicles within the real-time fusion perception space includes: determining the relative positional relationship between the target vehicle and other vehicles based on the real-time fusion perception space of the target vehicle; generating anomaly alert information carrying the relative positional relationship between the target vehicle and other vehicles; and sending the anomaly alert information to other vehicles within the real-time fusion perception space.

[0087] The vehicle-machine linkage reminder device provided in this application embodiment can execute the above-mentioned method and technical solution. Its principle and beneficial effects are similar, and will not be described again here.

[0088] Please refer to Figure 4 Based on the same inventive concept, another embodiment of this application provides an electronic device. This electronic device includes a memory 401 and a processor 402. The memory 401 and the processor 402 communicate with each other via a communication bus 403.

[0089] Memory 401 is used to store code instructions.

[0090] The processor 402 is used to run code instructions, causing the electronic device to execute the vehicle-machine linkage reminder method provided in the embodiments of this application.

[0091] The aforementioned communication bus 403 can be a Peripheral Component Interconnect (PCI) bus or an Extended Industry Standard Architecture (EISA) bus, etc. This communication bus 403 can be divided into an address bus, a data bus, a control bus, etc. For ease of illustration, only one thick line is used to represent it in the figure, but this does not indicate that there is only one bus or one type of bus. The communication interface is used for communication between the aforementioned terminal and other devices. The memory 401 can include random access memory (RAM), or it can include non-volatile memory, such as at least one disk storage device. Optionally, the memory 401 can also be at least one storage device located remotely from the aforementioned processor 402.

[0092] The processor 402 mentioned above can be a general-purpose processor, including a central processing unit (CPU), a network processor (NP), etc. It can also be a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, or discrete hardware components.

[0093] Based on the same inventive concept, this application also provides a vehicle that includes a vehicle-machine linkage reminder device in any of the possible implementations described above.

[0094] In addition, to achieve the above objectives, embodiments of this application also propose a computer-readable storage medium storing a computer program, which, when executed by a processor, implements the vehicle-machine linkage reminder method provided in embodiments of this application.

[0095] Those skilled in the art will understand that embodiments of this application can be provided as methods, devices, or computer program products. Therefore, embodiments of this application can take the form of entirely hardware embodiments, entirely software embodiments, or embodiments combining software and hardware aspects. Furthermore, embodiments of this application can take the form of computer program products implemented on one or more computer-usable vehicles (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0096] This application describes embodiments with reference to flowchart illustrations and / or block diagrams of methods, terminal devices (apparatus), and computer program products according to embodiments of this application. It should be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing terminal device to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing terminal device, generate instructions for implementing the flowchart illustrations. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0097] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing terminal device to operate in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0098] These computer program instructions can also be loaded onto a computer or other programmable data processing terminal equipment, causing a series of operational steps to be performed on the computer or other programmable terminal equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable terminal equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0099] Finally, it should be noted that in this document, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. "" and / or "" indicate that either one or both can be selected. Furthermore, the terms "includes," "contains," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or terminal device that includes a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or terminal device. Without further limitations, an element defined by the statement "includes a..." does not exclude the presence of other identical elements in the process, method, article, or terminal device that includes the element.

[0100] The above are merely specific embodiments of this application, but the scope of protection of this application is not limited thereto. Any person skilled in the art can easily conceive of various equivalent modifications or substitutions within the technical scope disclosed in this application, and these modifications or substitutions should all be covered within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

Claims

1. A vehicle-mounted infotainment system-linked reminder method, characterized in that, include: The real-time speed of the target vehicle is obtained, and the real-time fusion perception space corresponding to the target vehicle is obtained based on the real-time speed. The driver status and driving environment conditions are obtained, and the takeover alarm revision coefficient is determined based on the driver status and driving environment conditions. If the takeover alarm revision coefficient is greater than the preset alarm threshold, a takeover alarm message will be issued through the vehicle's infotainment system and an abnormality alert message will be issued to other vehicles in the real-time fusion perception space. The step of acquiring the driver's status and driving environment conditions, and determining the takeover alarm revision coefficient based on the driver's status and driving environment conditions, includes: Acquire driver status; the driver status includes whether the driver is fatigued or in a normal state. Based on the driver's status, determine the status alarm revision coefficient; Acquire driving environment conditions; the driving environment conditions include a first distance between the target vehicle and the road boundary and a second distance between the target vehicle and other vehicles; Based on the aforementioned driving environment conditions, determine the environmental alarm revision coefficient; The takeover alarm revision coefficient is obtained based on the status alarm revision coefficient and the environment alarm revision coefficient; The step of determining the environmental alarm revision coefficient based on the driving environment conditions includes: The nearest distance is determined based on a first distance between the target vehicle and the road boundary and a second distance between the target vehicle and other vehicles; The environmental alarm revision coefficient is determined based on the nearest distance; the environmental alarm revision coefficient is inversely proportional to the nearest distance.

2. The vehicle-machine linkage reminder method according to claim 1, characterized in that, The step of acquiring the real-time speed of the target vehicle and acquiring the real-time fusion perception space corresponding to the target vehicle based on the real-time speed includes: The real-time speed of the target vehicle is obtained, and the voxel unit corresponding to the target vehicle is obtained based on the real-time speed. Based on the voxel units corresponding to the target vehicle and the voxel units corresponding to other vehicles, overlapping voxel units are determined; Based on the overlapping voxel units, the voxel units of the target vehicle are fused with the voxel units of other vehicles to obtain the real-time fused perception space corresponding to the target vehicle.

3. The vehicle-machine linkage reminder method according to claim 1, characterized in that, Before obtaining the driver's status and driving environment conditions, the process also includes: Obtain the distance data between the target vehicle and the lane line; If the distance data is less than a preset distance threshold, continue to acquire the driver status and driving environment conditions; If the distance data is greater than or equal to a preset distance threshold, the process of obtaining the driver's status and driving environment conditions will not be initiated, and the distance data will continue to be monitored.

4. The vehicle-machine linkage reminder method according to claim 1, characterized in that, The step of determining the status alarm revision coefficient based on the driver's status includes: When the driver's status is that the driver is in a normal state, the status alarm revision coefficient is determined to be the first preset coefficient; When the driver is in a state of fatigue, the status alarm revision coefficient is determined to be the second preset coefficient; the second preset coefficient is greater than the first preset coefficient.

5. The vehicle-machine linkage reminder method according to claim 1, characterized in that, The step of sending anomaly alerts to other vehicles within the real-time fused perception space includes: Based on the real-time fusion perception space of the target vehicle, the relative positional relationship between the target vehicle and other vehicles is determined; An anomaly alert is generated, which carries the relative positional relationship between the target vehicle and other vehicles, and the anomaly alert is sent to other vehicles in the real-time fusion perception space.

6. The vehicle-machine linkage reminder method according to claim 1, characterized in that, After the takeover alarm information is issued through the vehicle's infotainment system of the target vehicle, the following is also included: If the non-takeover time of the target vehicle exceeds a preset non-takeover time threshold, the automatic parking function is triggered to automatically drive the target vehicle to a safe area for parking; the safe area is a pre-set parking area.

7. A vehicle-mounted infotainment system-linked reminder device, characterized in that, include: The fusion perception module is used to acquire the real-time speed of the target vehicle and acquire the real-time fusion perception space corresponding to the target vehicle based on the real-time speed. The coefficient acquisition module is used to acquire the driver's status and driving environment conditions, and determine the takeover alarm revision coefficient based on the driver's status and driving environment conditions. The linkage reminder module is used to send a takeover alarm message through the vehicle's infotainment system of the target vehicle and send an abnormality reminder message to other vehicles in the real-time fusion perception space when the takeover alarm revision coefficient is greater than the preset alarm threshold. The coefficient acquisition module includes: The status acquisition submodule is used to acquire the driver's status; the driver's status includes whether the driver is in a fatigued state or the driver is in a normal state. The first revision coefficient acquisition submodule is used to determine the status alarm revision coefficient based on the driver's status. An environmental condition acquisition submodule is used to acquire driving environmental conditions; the driving environmental conditions include a first distance between the target vehicle and the road boundary and a second distance between the target vehicle and other vehicles; The second revision coefficient acquisition submodule is used to determine the environmental alarm revision coefficient based on the driving environment conditions. The third revision coefficient acquisition submodule is used to acquire the takeover alarm revision coefficient based on the status alarm revision coefficient and the environment alarm revision coefficient. The second revision coefficient acquisition submodule is specifically used for: The nearest distance is determined based on a first distance between the target vehicle and the road boundary and a second distance between the target vehicle and other vehicles; The environmental alarm revision coefficient is determined based on the nearest distance; the environmental alarm revision coefficient is inversely proportional to the nearest distance.

8. A vehicle, characterized in that, The vehicle includes the vehicle-machine linkage reminder device as described in claim 7.

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