Rear warning method and device of vehicle, vehicle and storage medium

Abstract

This invention relates to the field of vehicle technology and discloses a method, device, vehicle, and storage medium for rear-end collision warning. The method includes: acquiring real-time distance data, real-time relative speed, and road surface adhesion coefficient between the vehicle and the following vehicle; determining dynamic threshold data between the vehicle and the following vehicle based on the real-time distance data, real-time relative speed, and road surface adhesion coefficient; and determining target warning information in a mapping relationship based on the dynamic threshold data. The mapping relationship records at least one preset threshold range and the warning information corresponding to each preset threshold. Applying the technical solution of this invention can effectively prevent the risk of rear-end collisions while ensuring the driving safety of the vehicle itself.

Description

Technical Field

[0001] This invention relates to the field of vehicle technology, specifically to a rearward warning method, device, vehicle, and storage medium for a vehicle. Background Technology

[0002] Currently, in high-density traffic scenarios such as urban expressways and highways, when vehicles are traveling in the same direction at high speeds, rear-end collisions are very likely to occur due to drivers of following vehicles being distracted, following too closely, or not anticipating the braking of the vehicle in front.

[0003] Most vehicles currently rely on the driver to manually operate the brake pedal to alert following vehicles to maintain a safe distance. However, lightly applying the brakes may cause the vehicle to slow down, which in turn increases the risk of a rear-end collision. Summary of the Invention

[0004] In view of the above problems, embodiments of the present invention provide a vehicle rear warning method, device, vehicle and storage medium to solve the technical problem in the prior art that it is impossible to ensure the driving safety of the vehicle itself while effectively preventing the risk of rear-end collisions.

[0005] According to one aspect of the present invention, a rearward warning method for a vehicle is provided, the method comprising:

[0006] Obtain real-time distance data, real-time relative speed, and road surface adhesion coefficient between this vehicle and the vehicle behind it;

[0007] Based on the real-time distance data, the real-time relative speed, and the road surface adhesion coefficient, determine the dynamic threshold data between the vehicle and the following vehicle;

[0008] Based on the dynamic threshold data, target warning information is determined in the mapping relationship, which records at least one preset threshold range and the warning information corresponding to each preset threshold.

[0009] According to another aspect of the present invention, a rear-view warning device for a vehicle is provided, comprising:

[0010] The acquisition module is used to acquire real-time distance data, real-time relative speed, and road surface adhesion coefficient between the vehicle and the vehicle behind it.

[0011] The first determining module is used to determine the dynamic threshold data between the vehicle and the following vehicle based on the real-time distance data, the real-time relative speed, and the road surface adhesion coefficient.

[0012] The second determining module is used to determine the target warning information in the mapping relationship based on the dynamic threshold data. The mapping relationship records at least one preset threshold range and the warning information corresponding to each preset threshold.

[0013] According to another aspect of the present invention, a vehicle is provided, comprising: a processor, a memory, a communication interface, and a communication bus, wherein the processor, the memory, and the communication interface communicate with each other via the communication bus;

[0014] The memory is used to store at least one executable instruction that causes the processor to perform operations such as the vehicle rear warning method described above.

[0015] According to another aspect of the present invention, a computer-readable storage medium is provided:

[0016] The storage medium stores at least one executable instruction that causes the vehicle's rear warning device / vehicle to perform the operation of the vehicle's rear warning method as described above.

[0017] According to another aspect of the present invention, a computer program product is provided, including a computer program that, when executed by a processor, causes a vehicle's rear warning device / vehicle to perform the operation of the aforementioned vehicle rear warning method.

[0018] This invention acquires real-time distance data, real-time relative speed, and road surface adhesion coefficient between the vehicle and the following vehicle; based on these data, it determines dynamic threshold data between the vehicle and the following vehicle; and based on the dynamic threshold data, it identifies target warning information in a mapping relationship, which records at least one preset threshold range and the warning information corresponding to each preset threshold. This technical solution, by acquiring the distance, relative speed, and road surface adhesion coefficient between the vehicle and the following vehicle in real time, comprehensively perceives real-time data such as vehicle driving status and environmental changes; then, based on this real-time data, it calculates dynamic threshold data, which can adaptively adjust the safe distance standard, avoiding inaccuracies caused by the failure of fixed thresholds in complex road conditions; finally, it matches the corresponding warning information in the mapping relationship based on the dynamic threshold data, providing timely and appropriate reminders for the current risk level, effectively reducing false alarms or missed alarms, thereby significantly enhancing driving safety.

[0019] The above description is merely an overview of the technical solutions of the embodiments of the present invention. In order to better understand the technical means of the embodiments of the present invention and to implement them in accordance with the contents of the specification, and to make the above and other objects, features and advantages of the embodiments of the present invention more apparent and understandable, specific embodiments of the present invention are described below. Attached Figure Description

[0020] The accompanying drawings are for illustrative purposes only and are not intended to limit the invention. Furthermore, the same reference numerals denote the same parts throughout the drawings. In the drawings:

[0021] Figure 1 A flowchart illustrating the rearward warning method for vehicles provided by current technology is shown.

[0022] Figure 2 A schematic diagram of the structure of the vehicle rear warning system provided by the present invention is shown;

[0023] Figure 3 A flowchart of a first embodiment of the vehicle rear warning method provided by the present invention is shown;

[0024] Figure 4 A flowchart of a second embodiment of the vehicle rear warning method provided by the present invention is shown;

[0025] Figure 5 A flowchart of a third embodiment of the vehicle rear warning method provided by the present invention is shown;

[0026] Figure 6 A flowchart of a fourth embodiment of the vehicle rear warning method provided by the present invention is shown;

[0027] Figure 7 A schematic diagram of an embodiment of the rear warning device for vehicles provided by the present invention is shown;

[0028] Figure 8 A structural schematic diagram of an embodiment of the vehicle provided by the present invention is shown. Detailed Implementation

[0029] Exemplary embodiments of the invention will now be described in more detail with reference to the accompanying drawings. While exemplary embodiments of the invention are shown in the drawings, it should be understood that the invention can be implemented in various forms and should not be limited to the embodiments set forth herein.

[0030] In high-density traffic scenarios such as urban expressways and highways, when vehicles are traveling at high speeds in the same direction, rear-end collisions are highly likely to occur due to drivers being distracted, following too closely, or failing to anticipate the braking of the vehicle in front. Especially in complex road conditions (such as rainy or snowy weather, or in areas with speed limits on curves), following vehicles that approach too closely are even more likely to cause traffic accidents.

[0031] Existing technologies for rear-view warning processing of vehicles are mainly based on the following implementation:

[0032] 1) Relying on the driver to manually operate the brake pedal to prompt following vehicles to maintain a safe distance.

[0033] In this approach, lightly applying the brakes may cause the vehicle to slow down, thereby increasing the risk of a rear-end collision; while not applying the brakes at all may result in a lack of effective warning signals, making it impossible to promptly remind the driver of the following vehicle to adjust their distance.

[0034] 2) The method relies on a fixed security threshold; see the documentation for details. Figure 1 , Figure 1 A flowchart illustrating the rearward warning method for vehicles currently provided by technology is shown, such as... Figure 1 As shown:

[0035] Step 11: Monitor the status of the vehicle behind;

[0036] Step 12: Determine whether the distance between the following vehicle and the current vehicle is less than the first safety threshold and whether the current vehicle speed is greater than the second safety threshold; if both are true, proceed to step 13; if neither is true, proceed to step 14.

[0037] Step 13: Turn on the hazard warning lights; then the process is complete.

[0038] Step 14: Maintain normal status.

[0039] This method has the drawback of increased false alarm rate at high speeds or on roads with low adhesion coefficients (such as in rain or snow), which affects the judgment of drivers behind.

[0040] Based on the above-mentioned technical problems, the technical concept of this invention is as follows: To accurately assess the risk of following vehicles, multi-dimensional dynamic parameters can be introduced. Therefore, by acquiring the real-time distance, relative speed, and road surface adhesion coefficient between the vehicle and the following vehicle, the vehicle's motion state and environmental influences can be comprehensively captured. Next, in order to overcome the shortcomings of fixed thresholds in adapting to changing scenarios, the method of dynamically calculating safety thresholds based on the above-mentioned real-time data can adjust the judgment criteria in real time according to the current actual working conditions (e.g., slippery road surface or high-speed approach affecting the road surface adhesion coefficient), thereby significantly improving the accuracy of warnings. Finally, in order to effectively transmit this dynamic judgment result to the driver, a mapping relationship between preset threshold ranges and warning information can be designed to ensure that the vehicle can automatically match the most appropriate reminder method according to different risk levels, thereby solving the problem of difficulty in accurately identifying the risk of following vehicles and the ease of false alarms.

[0041] Based on the above technical concept, Figure 2 A schematic diagram of the structure of the vehicle rear warning system provided by the present invention is shown, as follows: Figure 2 As shown, the vehicle's rear warning system includes: a vehicle domain controller, a smart driving controller, brake lights, a high-mounted brake light, and a solid-state laser rangefinder.

[0042] The intelligent driving controller is connected to the vehicle controller and the solid-state laser rangefinder via a communication bus; the vehicle domain controller is connected to the brake lights and the high-mounted brake lights via hard wiring.

[0043] In one possible implementation, the intelligent driving controller in the vehicle acts as the execution subject. First, it acquires the distance information of the following vehicle transmitted by the solid-state laser rangefinder, determines the real-time distance data and real-time relative speed between itself and the following vehicle, and obtains the road surface adhesion coefficient. Then, by combining the above data, it transmits the determined target warning information to the vehicle domain controller, which controls the brake lights and / or high-mounted brake lights to be illuminated.

[0044] It should be understood that any aspects not detailed above are disclosed in the following embodiments.

[0045] Based on the above technical concept and system embodiments, the technical solution of the present invention will be described in detail through specific embodiments. The executing subject of the present invention is a vehicle (e.g., the vehicle in the following embodiments), specifically a driving controller or a vehicle domain controller. It should be noted that the following specific embodiments can be combined with each other, and the same or similar concepts or processes may not be described again in some embodiments.

[0046] Figure 3 A flowchart of a first embodiment of the vehicle rear-view warning method provided by the present invention is shown, the method being executed by a vehicle. Figure 3 As shown, the method includes the following steps:

[0047] Step 31: Obtain real-time distance data, real-time relative speed, and road surface adhesion coefficient between this vehicle and the vehicle behind it;

[0048] In this step, a rearward multi-dimensional perception module that integrates millimeter-wave radar or visual cameras can be used to construct a fan-shaped monitoring area with a preset rear angle (e.g., 180 degrees) to collect real-time distance data and real-time relative speed of the following vehicle; real-time distance data and real-time relative speed between the vehicle and the following vehicle can also be obtained in real time through the vehicle's onboard perception system (e.g., solid-state laser rangefinder).

[0049] Additionally, the road adhesion coefficient can be obtained through onboard sensors (e.g., rain sensors, road condition estimation models) or based on vehicle dynamics models.

[0050] It should be understood that real-time distance data, real-time relative speed, and road surface adhesion coefficient are all collected in real time and input into subsequent calculation steps.

[0051] Step 32: Determine the dynamic threshold data between this vehicle and the following vehicle based on real-time distance data, real-time relative speed, and road surface adhesion coefficient;

[0052] In this step, based on the real-time distance data, real-time relative speed, and road surface adhesion coefficient obtained in step 31, a dynamic threshold data is calculated to quantify the risk level of the following vehicle to the current vehicle.

[0053] Optionally, one possible implementation of step 32 could be:

[0054] Step 1: Determine the first ratio between the real-time relative velocity and the real-time distance data;

[0055] In this implementation, the real-time relative speed Vr(t) of the following vehicle relative to the following vehicle is divided by the real-time distance data d(t) between the two vehicles to obtain a first ratio. This first ratio represents the urgency of the following vehicle approaching the following vehicle. The larger the first ratio, the more drastic the speed change per unit distance, and the higher the risk of a rear-end collision.

[0056] For example, the first ratio = Vr(t) / d(t).

[0057] Step 2: Determine the first product between the first ratio and the road surface adhesion coefficient as the dynamic threshold data.

[0058] In this implementation, after obtaining the first ratio, it is multiplied by the road adhesion coefficient Wv to obtain the first product value as dynamic threshold data.

[0059] Among them, the road adhesion coefficient reflects the friction conditions of the current road surface. The lower the adhesion coefficient (e.g., wet and slippery road surface), the longer the actual braking distance for the same ratio, and the greater the risk. Road surface factors are incorporated into the risk measurement through a product.

[0060] For example, D(t) = first ratio × Wv.

[0061] Step 33: Based on the dynamic threshold data, determine the target warning information in the mapping relationship;

[0062] The mapping relationship contains at least one preset threshold range and the warning information corresponding to each preset threshold.

[0063] In this step, based on the dynamic threshold data obtained in the previous steps, the corresponding warning information is searched in the preset mapping relationship and recorded as the target warning information.

[0064] Then, the vehicle applies the target warning information to alert the vehicles behind it.

[0065] Optionally, at least one preset threshold range includes: a first preset range, a second preset range, and a third preset range; the second preset range is greater than the first preset range and less than the third preset range;

[0066] In this implementation, the first preset range can be a range smaller than the first preset threshold, for example, less than 0.1m. The second preset range can be the range between the first preset threshold and the second preset threshold, for example, 0.1m. -0.3m The third preset range can be a range greater than the second preset threshold, for example, less than 0.3m. .

[0067] Correspondingly, the warning information corresponding to the first preset range includes: no action; the warning information corresponding to the second preset range includes: control the vehicle's hazard lights to flash at the first preset frequency; the warning information corresponding to the third preset range includes: control the vehicle's hazard lights to flash continuously and illuminate the vehicle's brake lights pulse.

[0068] In this implementation, the first preset frequency can be 1Hz; the flashing frequency of the brake light pulse can be the second preset frequency, which can be 3Hz.

[0069] The vehicle rear-view warning method provided in this invention acquires real-time distance data, real-time relative speed, and road surface adhesion coefficient between the vehicle and the following vehicle; determines dynamic threshold data between the vehicle and the following vehicle based on the real-time distance data, real-time relative speed, and road surface adhesion coefficient; and determines target warning information in a mapping relationship based on the dynamic threshold data. The mapping relationship records at least one preset threshold range and the warning information corresponding to each preset threshold. In this technical solution, by acquiring the distance, relative speed, and road surface adhesion coefficient between the vehicle and the following vehicle in real time, real-time data such as vehicle driving status and environmental changes can be comprehensively perceived. Then, dynamic threshold data is calculated based on this real-time data, which can adaptively adjust the safety distance standard, avoiding inaccuracies caused by the failure of fixed thresholds in complex road conditions. Finally, matching the corresponding warning information in the mapping relationship based on the dynamic threshold data can provide timely and appropriate reminders according to the current risk level, effectively reducing false alarms or missed alarms, thereby significantly enhancing driving safety. Furthermore, in a simulation environment, it was verified that the false alarm rate is reduced by 62% compared to the current fixed threshold scheme.

[0070] Based on the above embodiments, Figure 4 A flowchart of a second embodiment of the vehicle rear-view warning method provided by the present invention is shown, the method being executed by the vehicle. Figure 4 As shown, step 33 may include any of the following steps:

[0071] Step 41: If the dynamic threshold data is within the first preset range, determine the warning information corresponding to the first preset range as the target warning information;

[0072] In this step, since the first preset range is in a safe distance state, it means that the distance to the following vehicle is far enough or the risk is extremely low. At this time, no warning action is required, and the vehicle can continue to drive normally. When the dynamic threshold data is within the first preset range, the warning information corresponding to the first preset range is determined as the target warning information.

[0073] Step 42: If the dynamic threshold data is within the second preset range, determine the warning information corresponding to the second preset range as the target warning information;

[0074] In this step, since the second preset range is in the warning distance state, it means that the following vehicle is close but has not yet reached the danger level. If the dynamic threshold data is within the second preset range, the warning information corresponding to the second preset range will be determined as the target warning information.

[0075] Step 43: If the dynamic threshold data is within the third preset range, determine the target warning information in the mapping relationship based on the duration of the dynamic threshold data being within the third preset range.

[0076] In this step, since the third preset range is in a dangerous distance state, but in order to prevent false triggering for vehicles that briefly enter the dangerous area (e.g., overtaking), a time window mechanism can be introduced to dynamically adjust the warning information based on the duration of the dynamic threshold data within the third preset range.

[0077] Optionally, one possible implementation of step 43 could be:

[0078] Step 1: If the duration exceeds the first preset duration, the warning information corresponding to the third preset range is determined as the target warning information;

[0079] In this implementation, if the duration of the dynamic threshold data within the third preset range is longer than the first preset duration (e.g., 0.5 seconds), then the warning information corresponding to the third preset range is determined as the target warning information.

[0080] If the duration exceeds the first preset time, it means that the following vehicle is within the danger distance for an extended period of time, and the risk persists. The strongest warning method needs to be adopted, namely, keeping the hazard lights constantly on and simultaneously illuminating the brake light pulses (e.g., at a 3Hz frequency) to conspicuously warn the following vehicle to immediately increase the distance.

[0081] Step 2: If the duration is less than or equal to the first preset duration, the warning information corresponding to the second preset range is determined as the target warning information.

[0082] In this implementation, if the duration of the dynamic threshold data within the third preset range is less than or equal to the first preset duration, then the warning information corresponding to the second preset range is determined as the target warning information.

[0083] Among them, less than or equal to the first preset duration means that the following vehicle only briefly enters the danger zone, and it is downgraded to a warning treatment, triggering only the hazard lights to flash intermittently, so as to avoid triggering a strong warning due to instantaneous approach.

[0084] The vehicle rearward warning method provided in this embodiment of the invention determines the warning information corresponding to the first preset range as the target warning information if the dynamic threshold data is within a first preset range; determines the warning information corresponding to the second preset range as the target warning information if the dynamic threshold data is within a second preset range; and determines the target warning information in a mapping relationship based on the duration of the dynamic threshold data being within the third preset range if the dynamic threshold data is within a third preset range. In this technical solution, when the dynamic threshold data is within the first preset range, the warning message is directly determined to be inactive. This intelligently filters low-risk scenarios, preventing unnecessary interference with normal following behavior within a safe distance and thus improving the driving experience. When the dynamic threshold data is within the second preset range, a warning message is matched by controlling the vehicle's hazard lights to flash at a first preset frequency. This can promptly remind following vehicles to maintain distance in medium-risk situations through regular lighting, while avoiding excessive stimulation of the driver and surrounding vehicles. When the dynamic threshold data is within the third preset range, a duration determination is introduced. If the risk persists, a warning message is determined by controlling the hazard lights to remain constantly on and illuminating the brake light pulses. This strengthens the presence of the vehicle through constant flashing and simulates deceleration with brake light pulses, thereby delivering the strongest warning signal to following vehicles in high-risk scenarios and effectively reducing the probability of rear-end collisions.

[0085] Based on the above embodiments, Figure 5 A flowchart of a third embodiment of the vehicle rear-view warning method provided by the present invention is shown, the method being executed by the vehicle. Figure 5 As shown, step 32 may include the following steps:

[0086] Step 51: Based on the driving status data of the following vehicle, predict the first driving trajectory of the following vehicle;

[0087] In this step, the vehicle continuously acquires the driving status data of the following vehicle and predicts the subsequent driving trajectory of the following vehicle based on this driving status data, which is recorded as the first driving trajectory.

[0088] For example, driving status data includes information such as the historical position, speed, acceleration, and steering angle of the following vehicle, which can be obtained through continuous tracking using millimeter-wave radar and visual cameras.

[0089] Furthermore, trajectory prediction algorithms such as Kalman filtering, particle filtering, or artificial intelligence (AI) large models can be used to infer the first driving trajectory of the following vehicle in the future (e.g., within 1 second).

[0090] Step 52: Based on the first driving trajectory and the second driving trajectory of this vehicle, determine whether the following vehicle has entered the danger zone behind the preceding vehicle;

[0091] In this step, the first driving trajectory of the following vehicle is compared with the second driving trajectory of this vehicle to determine whether the following vehicle has entered the danger zone behind this vehicle.

[0092] The danger zone can be a lane area within a certain distance starting from the rear of the vehicle, and the size of this lane area can be dynamically adjusted according to the speed of the vehicle; the second driving trajectory is the driving trajectory that the vehicle has already passed between the following vehicle and the vehicle behind.

[0093] Optionally, one possible implementation of step 52 may include any of the following:

[0094] Item 1: If the first driving trajectory coincides with the second driving trajectory and the real-time distance data is less than the first preset distance, it is determined that the following vehicle has entered the danger zone;

[0095] In this implementation, if the first driving trajectory of the following vehicle coincides with the second driving trajectory of the current vehicle, it can be considered that the driving paths of the current vehicle and the following vehicle are in the same lane, and the real-time distance data is less than the first preset distance (e.g., 10 meters).

[0096] If the trajectories of the two vehicles overlap and the real-time distance data is less than the first preset distance, it indicates that the following vehicle does not have enough space to adjust its speed and is in a state of emergency. Therefore, it is determined that the following vehicle has entered the danger zone.

[0097] Item 2: If the first driving trajectory coincides with the second driving trajectory, and the real-time distance data is greater than or equal to the first preset distance, it is determined that the following vehicle has not entered the danger zone;

[0098] In this implementation, if the first driving trajectory of the following vehicle coincides with the second driving trajectory of the current vehicle, but the real-time distance data is greater than or equal to the first preset distance, it is determined that the following vehicle has not entered the danger zone.

[0099] Although the trajectories overlap, the relative distance is still far enough that the following vehicle has enough space to adjust its speed. Since there is no immediate risk, it can be determined that the following vehicle has not entered the danger zone.

[0100] Item 3: If the first driving trajectory does not overlap with the second driving trajectory, it is determined that the following vehicle has not entered the danger zone.

[0101] In this implementation, if the first driving trajectory of the following vehicle does not coincide with the second driving trajectory of the current vehicle, then regardless of the real-time distance, it is determined that the following vehicle has not entered the danger zone.

[0102] In other words, if the trajectories do not overlap, it means that the following vehicle is in a different lane or is changing lanes, and will not directly rear-end the vehicle, so it is not considered a danger zone.

[0103] Step 53: If the following vehicle enters the danger zone, determine the dynamic threshold data between this vehicle and the following vehicle based on the real-time distance data, real-time relative speed, and road surface adhesion coefficient.

[0104] In this step, after confirming that the following vehicle has entered the danger zone, it is considered necessary to determine whether there is a possibility of collision between the following vehicle and the vehicle itself, and to issue necessary warnings. At this point, dynamic threshold data between the vehicle and the following vehicle can be calculated based on real-time distance data, real-time relative speed, and road adhesion coefficient.

[0105] The rearward warning method for vehicles provided in this invention predicts the first driving trajectory of the following vehicle based on its driving status data; determines whether the following vehicle has entered a danger zone behind the preceding vehicle based on the first driving trajectory and the vehicle's second driving trajectory; if the following vehicle has entered the danger zone, determines the dynamic threshold data between the vehicle and the following vehicle based on real-time distance data, real-time relative speed, and road surface adhesion coefficient. In this technical solution, the first driving trajectory of the following vehicle is predicted based on its driving status data, enabling early detection of the following vehicle's movement trend; then, the first driving trajectory is compared with the vehicle's second driving trajectory to determine whether the following vehicle has entered a danger zone behind the preceding vehicle, effectively avoiding indiscriminate calculations for all approaching vehicles and significantly reducing computational power consumption and the probability of false triggering; finally, only after confirming that the following vehicle has entered the danger zone, the dynamic threshold data is calculated by combining real-time distance, relative speed, and road surface adhesion coefficient, ensuring the high specificity and real-time nature of subsequent risk assessments, enabling the vehicle to dynamically adjust based on real threats and improving the reliability of rear-vehicle collision avoidance.

[0106] Based on the above embodiments, Figure 6 A flowchart of a fourth embodiment of the vehicle rear-view warning method provided by the present invention is shown, the method being executed by a vehicle. Figure 6 As shown, one possible implementation of this method is:

[0107] Step 61: Monitor the status of the vehicle behind;

[0108] Step 62: Determine the following vehicle and the preceding vehicle: Is the distance between them less than the first dynamic threshold, and is the relative speed between them greater than the second dynamic threshold? If not, proceed to step 64; if yes, proceed to step 63.

[0109] Step 63: Turn on the hazard warning lights; End;

[0110] Step 64: Is the distance between vehicles less than the first dynamic threshold, and is the relative speed between vehicles less than the second dynamic threshold, and does this last for 5 seconds? If not, continue monitoring; if yes, proceed to step 65.

[0111] Step 65: Intermittently illuminate the brake lights.

[0112] The rearward warning method for vehicles provided in this embodiment of the invention can effectively illuminate the brake lights to warn following vehicles to maintain a safe distance when the user is not applying the brakes, thereby reducing the risk of rear-end collisions.

[0113] Figure 7 A schematic diagram of an embodiment of the rear-view warning device for vehicles provided by the present invention is shown. (See attached diagram.) Figure 7 As shown, the device includes:

[0114] The acquisition module 71 is used to acquire real-time distance data, real-time relative speed, and road surface adhesion coefficient between the vehicle and the following vehicle;

[0115] The first determining module 72 is used to determine the dynamic threshold data between the vehicle and the following vehicle based on real-time distance data, real-time relative speed, and road surface adhesion coefficient.

[0116] The second determining module 73 is used to determine the target warning information in the mapping relationship based on the dynamic threshold data. The mapping relationship records at least one preset threshold range and the warning information corresponding to each preset threshold.

[0117] In one or more embodiments, the first determining module 72 determines dynamic threshold data between the vehicle and the following vehicle based on real-time distance data, real-time relative speed, and road surface adhesion coefficient, specifically for:

[0118] Determine the first ratio between the real-time relative velocity and the real-time distance data;

[0119] The first product between the first ratio and the road surface adhesion coefficient is determined as the dynamic threshold data.

[0120] In one or more embodiments, at least one preset threshold range includes: a first preset range, a second preset range, and a third preset range; the second preset range is greater than the first preset range and less than the third preset range;

[0121] The warning information corresponding to the first preset range includes: no action;

[0122] The warning information corresponding to the second preset range includes: controlling the vehicle's hazard lights to flash at the first preset frequency;

[0123] The warning information corresponding to the third preset range includes: controlling the vehicle's hazard lights to flash continuously and illuminating the vehicle's brake lights with pulses.

[0124] In one or more embodiments, the second determining module 73 determines the target warning information in the mapping relationship based on the dynamic threshold data, specifically for:

[0125] If the dynamic threshold data is within the first preset range, the warning information corresponding to the first preset range will be determined as the target warning information;

[0126] If the dynamic threshold data is within the second preset range, the warning information corresponding to the second preset range will be determined as the target warning information;

[0127] If the dynamic threshold data is within the third preset range, the target warning information is determined in the mapping relationship based on the duration of the dynamic threshold data being within the third preset range.

[0128] In one or more embodiments, the second determining module 73 determines the target warning information in the mapping relationship based on the duration for which the dynamic threshold data remains within a third preset range, specifically for:

[0129] If the duration exceeds the first preset duration, the warning information corresponding to the third preset range will be determined as the target warning information;

[0130] If the duration is less than or equal to the first preset duration, the warning information corresponding to the second preset range will be determined as the target warning information.

[0131] In one or more embodiments, the first determining module 72 determines dynamic threshold data between the vehicle and the following vehicle based on real-time distance data, real-time relative speed, and road surface adhesion coefficient, specifically for:

[0132] Based on the driving status data of the following vehicle, predict the first driving trajectory of the following vehicle;

[0133] Based on the first driving trajectory and the second driving trajectory of this vehicle, determine whether the following vehicle has entered the danger zone behind the preceding vehicle;

[0134] If a following vehicle enters a dangerous area, the dynamic threshold data between the vehicle and the following vehicle is determined based on real-time distance data, real-time relative speed, and road surface adhesion coefficient.

[0135] In one or more embodiments, the first determining module 72 determines whether the following vehicle has entered the danger zone behind the preceding vehicle based on the first driving trajectory and the second driving trajectory of the vehicle itself, specifically for:

[0136] If the first driving trajectory coincides with the second driving trajectory and the real-time distance data is less than the first preset distance, it is determined that the following vehicle has entered the danger zone;

[0137] If the first driving trajectory coincides with the second driving trajectory, and the real-time distance data is greater than or equal to the first preset distance, it is determined that the following vehicle has not entered the danger zone;

[0138] If the first driving trajectory does not overlap with the second driving trajectory, it is determined that the following vehicle has not entered the danger zone.

[0139] It should be noted that the division of the various modules in the above device is merely a logical functional division. In actual implementation, they can be fully or partially integrated into a single physical element, or they can be physically separated. Furthermore, these modules can be implemented entirely in software through processing element calls, or entirely in hardware. Alternatively, some modules can be implemented through processing element calls in software, while others can be implemented in hardware. Moreover, these modules can be integrated together or implemented independently. The processing element here can be an integrated circuit with signal processing capabilities. During implementation, each step of the above method or each of the above modules can be completed through the integrated logic circuits in the hardware of the processor element or through software instructions.

[0140] As can be seen from the above, the vehicle rear warning device provided in this embodiment of the invention can comprehensively perceive real-time data such as vehicle driving status and environmental changes by acquiring the distance, relative speed and road surface adhesion coefficient between the vehicle and the following vehicle in real time; then, based on these real-time data, dynamic threshold data is calculated, which can adaptively adjust the safety distance standard and avoid the inaccuracy caused by the failure of fixed thresholds under complex road conditions; finally, according to the dynamic threshold data, the corresponding warning information is matched in the mapping relationship, which can provide timely and appropriate reminders for the current risk level, effectively reducing false alarms or missed alarms, thereby greatly enhancing driving safety.

[0141] Figure 8 A structural schematic diagram of an embodiment of the vehicle provided by the present invention is shown, as follows. Figure 8 As shown, the vehicle may include: a processor 82, a communications interface 84, a memory 86, and a communications bus 88.

[0142] The processor 82, communication interface 84, and memory 86 communicate with each other via communication bus 88. Communication interface 84 is used to communicate with other network elements such as clients or other servers. The processor 82 executes program 80, specifically performing the relevant steps in the above method embodiments.

[0143] Specifically, program 80 may include program code, which includes computer-executable instructions.

[0144] Processor 82 may be a central processing unit (CPU), an application-specific integrated circuit (ASIC), or one or more integrated circuits configured to implement embodiments of the present invention. The vehicle may include one or more processors of the same type, such as one or more CPUs, or processors of different types, such as one or more CPUs and one or more ASICs.

[0145] Memory 86 is used to store program 80. Memory 86 may include high-speed RAM memory, and may also include non-volatile memory, such as at least one disk storage device.

[0146] Program 80 can be called by processor 82 to cause the vehicle to perform the following operations:

[0147] Obtain real-time distance data, real-time relative speed, and road surface adhesion coefficient between this vehicle and the vehicle behind it;

[0148] Based on real-time distance data, real-time relative speed, and road surface adhesion coefficient, determine the dynamic threshold data between this vehicle and the following vehicle;

[0149] Based on dynamic threshold data, target warning information is determined in the mapping relationship, which records at least one preset threshold range and the warning information corresponding to each preset threshold.

[0150] In one or more embodiments, dynamic threshold data between the vehicle and the following vehicle is determined based on real-time distance data, real-time relative speed, and road surface adhesion coefficient, including:

[0151] Determine the first ratio between the real-time relative velocity and the real-time distance data;

[0152] The first product between the first ratio and the road surface adhesion coefficient is determined as the dynamic threshold data.

[0153] In one or more embodiments, at least one preset threshold range includes: a first preset range, a second preset range, and a third preset range; the second preset range is greater than the first preset range and less than the third preset range;

[0154] The warning information corresponding to the first preset range includes: no action;

[0155] The warning information corresponding to the second preset range includes: controlling the vehicle's hazard lights to flash at the first preset frequency;

[0156] The warning information corresponding to the third preset range includes: controlling the vehicle's hazard lights to flash continuously and illuminating the vehicle's brake lights with pulses.

[0157] In one or more embodiments, the target warning information is determined from the mapping relationship based on dynamic threshold data, including:

[0158] If the dynamic threshold data is within the first preset range, the warning information corresponding to the first preset range will be determined as the target warning information;

[0159] If the dynamic threshold data is within the second preset range, the warning information corresponding to the second preset range will be determined as the target warning information;

[0160] If the dynamic threshold data is within the third preset range, the target warning information is determined in the mapping relationship based on the duration of the dynamic threshold data being within the third preset range.

[0161] In one or more embodiments, determining target warning information in the mapping relationship based on the duration for which dynamic threshold data remains within a third preset range includes:

[0162] If the duration exceeds the first preset duration, the warning information corresponding to the third preset range will be determined as the target warning information;

[0163] If the duration is less than or equal to the first preset duration, the warning information corresponding to the second preset range will be determined as the target warning information.

[0164] In one or more embodiments, dynamic threshold data between the vehicle and the following vehicle is determined based on real-time distance data, real-time relative speed, and road surface adhesion coefficient, including:

[0165] Based on the driving status data of the following vehicle, predict the first driving trajectory of the following vehicle;

[0166] Based on the first driving trajectory and the second driving trajectory of this vehicle, determine whether the following vehicle has entered the danger zone behind the preceding vehicle;

[0167] If a following vehicle enters a dangerous area, the dynamic threshold data between the vehicle and the following vehicle is determined based on real-time distance data, real-time relative speed, and road surface adhesion coefficient.

[0168] In one or more embodiments, determining whether a following vehicle has entered a dangerous area behind a preceding vehicle based on a first driving trajectory and a second driving trajectory of the vehicle includes:

[0169] If the first driving trajectory coincides with the second driving trajectory and the real-time distance data is less than the first preset distance, it is determined that the following vehicle has entered the danger zone;

[0170] If the first driving trajectory coincides with the second driving trajectory, and the real-time distance data is greater than or equal to the first preset distance, it is determined that the following vehicle has not entered the danger zone;

[0171] If the first driving trajectory does not overlap with the second driving trajectory, it is determined that the following vehicle has not entered the danger zone.

[0172] As can be seen from the above, the vehicle provided in this embodiment of the invention can comprehensively perceive real-time data such as the vehicle's driving status and environmental changes by acquiring the distance, relative speed, and road surface adhesion coefficient between itself and the vehicle behind it. Based on this real-time data, dynamic threshold data can be calculated, which can adaptively adjust the safety distance standard and avoid inaccuracies caused by the failure of fixed thresholds under complex road conditions. Finally, according to the dynamic threshold data, the corresponding warning information is matched in the mapping relationship, which can provide timely and appropriate reminders for the current risk level, effectively reducing false alarms or missed alarms, thereby greatly enhancing driving safety.

[0173] This invention provides a computer-readable storage medium storing at least one executable instruction that, when executed on a vehicle's rear warning device / vehicle, causes the vehicle's rear warning device / vehicle to perform the vehicle's rear warning method as described in any of the above method embodiments.

[0174] The executable instructions can specifically be used to cause the vehicle's rear warning device / vehicle to perform the following operations:

[0175] Obtain real-time distance data, real-time relative speed, and road surface adhesion coefficient between this vehicle and the vehicle behind it;

[0176] Based on real-time distance data, real-time relative speed, and road surface adhesion coefficient, determine the dynamic threshold data between this vehicle and the following vehicle;

[0177] Based on dynamic threshold data, target warning information is determined in the mapping relationship, which records at least one preset threshold range and the warning information corresponding to each preset threshold.

[0178] In one or more embodiments, dynamic threshold data between the vehicle and the following vehicle is determined based on real-time distance data, real-time relative speed, and road surface adhesion coefficient, including:

[0179] Determine the first ratio between the real-time relative velocity and the real-time distance data;

[0180] The first product between the first ratio and the road surface adhesion coefficient is determined as the dynamic threshold data.

[0181] In one or more embodiments, at least one preset threshold range includes: a first preset range, a second preset range, and a third preset range; the second preset range is greater than the first preset range and less than the third preset range;

[0182] The warning information corresponding to the first preset range includes: no action;

[0183] The warning information corresponding to the second preset range includes: controlling the vehicle's hazard lights to flash at the first preset frequency;

[0184] The warning information corresponding to the third preset range includes: controlling the vehicle's hazard lights to flash continuously and illuminating the vehicle's brake lights with pulses.

[0185] In one or more embodiments, the target warning information is determined from the mapping relationship based on dynamic threshold data, including:

[0186] If the dynamic threshold data is within the first preset range, the warning information corresponding to the first preset range will be determined as the target warning information;

[0187] If the dynamic threshold data is within the second preset range, the warning information corresponding to the second preset range will be determined as the target warning information;

[0188] If the dynamic threshold data is within the third preset range, the target warning information is determined in the mapping relationship based on the duration of the dynamic threshold data being within the third preset range.

[0189] In one or more embodiments, determining target warning information in the mapping relationship based on the duration for which dynamic threshold data remains within a third preset range includes:

[0190] If the duration exceeds the first preset duration, the warning information corresponding to the third preset range will be determined as the target warning information;

[0191] If the duration is less than or equal to the first preset duration, the warning information corresponding to the second preset range will be determined as the target warning information.

[0192] In one or more embodiments, dynamic threshold data between the vehicle and the following vehicle is determined based on real-time distance data, real-time relative speed, and road surface adhesion coefficient, including:

[0193] Based on the driving status data of the following vehicle, predict the first driving trajectory of the following vehicle;

[0194] Based on the first driving trajectory and the second driving trajectory of this vehicle, determine whether the following vehicle has entered the danger zone behind the preceding vehicle;

[0195] If a following vehicle enters a dangerous area, the dynamic threshold data between the vehicle and the following vehicle is determined based on real-time distance data, real-time relative speed, and road surface adhesion coefficient.

[0196] In one or more embodiments, determining whether a following vehicle has entered a dangerous area behind a preceding vehicle based on a first driving trajectory and a second driving trajectory of the vehicle includes:

[0197] If the first driving trajectory coincides with the second driving trajectory and the real-time distance data is less than the first preset distance, it is determined that the following vehicle has entered the danger zone;

[0198] If the first driving trajectory coincides with the second driving trajectory, and the real-time distance data is greater than or equal to the first preset distance, it is determined that the following vehicle has not entered the danger zone;

[0199] If the first driving trajectory does not overlap with the second driving trajectory, it is determined that the following vehicle has not entered the danger zone.

[0200] As can be seen from the above, the rear warning device / vehicle provided in this embodiment of the invention can comprehensively perceive real-time data such as vehicle driving status and environmental changes by acquiring the distance, relative speed and road surface adhesion coefficient between the vehicle and the following vehicle in real time; then, based on this real-time data, dynamic threshold data is calculated, which can adaptively adjust the safety distance standard and avoid the inaccuracy caused by the failure of fixed thresholds in complex road conditions; finally, according to the dynamic threshold data, the corresponding warning information is matched in the mapping relationship, which can provide timely and appropriate reminders for the current risk level, effectively reducing false alarms or missed alarms, thereby greatly enhancing driving safety.

[0201] This invention provides a computer program product, including a computer program that, when executed by a processor, implements the above-described vehicle rear warning method.

[0202] Its implementation principle and technical effects are as disclosed above.

[0203] The description of the various embodiments above tends to emphasize the differences between the various embodiments. The similarities or similarities between them can be referred to, and for the sake of brevity, they will not be repeated here.

[0204] The methods disclosed in the various method embodiments provided by this invention can be arbitrarily combined without conflict to obtain new method embodiments.

[0205] The features disclosed in the various product embodiments provided by this invention can be arbitrarily combined without conflict to obtain new product embodiments.

[0206] The features disclosed in the various method or device embodiments provided by the present invention can be arbitrarily combined without conflict to obtain new method embodiments or vehicle embodiments.

[0207] It should be noted that the aforementioned computer-readable storage media can be ROM, Programmable Read-Only Memory (PROM), Erasable Programmable Read-Only Memory (EPROM), Electrically Erasable Programmable Read-Only Memory (EEPROM), Ferromagnetic Random Access Memory (FRAM), Flash Memory, Magnetic Surface Memory, Optical Disc, or Compact Disc Read-Only Memory (CD-ROM), etc. It can also be various vehicles that include one or any combination of the above-mentioned storage media.

[0208] It should be noted that, in this document, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises 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 apparatus. Unless otherwise specified, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes that element.

[0209] The sequence numbers of the above embodiments of the present invention are for descriptive purposes only and do not represent the superiority or inferiority of the embodiments.

[0210] Through the above description of the embodiments, those skilled in the art can clearly understand that the methods of the above embodiments can be implemented by means of software plus necessary general-purpose hardware nodes. Of course, they can also be implemented by hardware, but in many cases the former is a better implementation method. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk) and includes several instructions to cause a terminal device (which may be a mobile phone, computer, server, air conditioner, vehicle terminal, or network device, etc.) to execute the methods described in the various embodiments of the present invention.

[0211] This invention is described with reference to flowchart illustrations and / or block diagrams of methods, apparatuses, devices, and computer program products according to embodiments of the invention. It will 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 apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart... Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0212] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function 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.

[0213] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The algorithms or displays provided herein for the functions specified in the boxes or boxes are not inherently related to any particular computer, virtual system, or other device. Furthermore, the embodiments of this invention are not directed to any particular programming language.

[0214] It should be noted that the above embodiments are illustrative of the invention and not restrictive, and that those skilled in the art can devise alternative embodiments without departing from the scope of the appended claims. In the claims, any reference signs placed between parentheses should not be construed as limiting the claims. The word "comprising" does not exclude the presence of elements or steps not listed in the claims. The word "a" or "an" preceding an element does not exclude the presence of a plurality of such elements. The invention can be implemented by means of hardware comprising several different elements and by means of a suitably programmed computer. In the unit claims enumerating several means, several of these means may be embodied by the same item of hardware. The use of the words first, second, and third, etc., does not indicate any order. These words can be interpreted as names. The steps in the above embodiments, unless otherwise specified, should not be construed as limiting the order of execution.

Claims

1. A rearward warning method of a vehicle, characterized by, The method includes: Obtain real-time distance data, real-time relative speed, and road surface adhesion coefficient between this vehicle and the vehicle behind it; Based on the real-time distance data, the real-time relative speed, and the road surface adhesion coefficient, determine the dynamic threshold data between the vehicle and the following vehicle; Based on the dynamic threshold data, target warning information is determined in the mapping relationship, which records at least one preset threshold range and the warning information corresponding to each preset threshold.

2. The method of claim 1, wherein, The step of determining the dynamic threshold data between the vehicle and the following vehicle based on the real-time distance data, the real-time relative speed, and the road surface adhesion coefficient includes: Determine a first ratio between the real-time relative velocity and the real-time distance data; The first product between the first ratio and the road surface adhesion coefficient is determined as the dynamic threshold data.

3. The method according to claim 1 or 2, characterized in that, The at least one preset threshold range includes: a first preset range, a second preset range, and a third preset range; the second preset range is greater than the first preset range and less than the third preset range; The warning information corresponding to the first preset range includes: no action; The warning information corresponding to the second preset range includes: controlling the hazard lights of the vehicle to flash at a first preset frequency; The warning information corresponding to the third preset range includes: controlling the hazard lights of the vehicle to flash continuously and illuminating the brake lights of the vehicle with pulses.

4. The method according to claim 3, characterized in that, The step of determining the target warning information in the mapping relationship based on the dynamic threshold data includes: If the dynamic threshold data is within the first preset range, the warning information corresponding to the first preset range will be determined as the target warning information; If the dynamic threshold data is within the second preset range, the warning information corresponding to the second preset range will be determined as the target warning information; If the dynamic threshold data is within the third preset range, the target warning information is determined in the mapping relationship based on the duration for which the dynamic threshold data is within the third preset range.

5. The method according to claim 4, characterized in that, The step of determining the target warning information in the mapping relationship based on the duration for which the dynamic threshold data lies within the third preset range includes: If the duration is longer than the first preset duration, the warning information corresponding to the third preset range will be determined as the target warning information; If the duration is less than or equal to the first preset duration, the warning information corresponding to the second preset range is determined as the target warning information.

6. The method according to claim 1 or 2, characterized in that, The step of determining the dynamic threshold data between the vehicle and the following vehicle based on the real-time distance data, the real-time relative speed, and the road surface adhesion coefficient includes: Based on the driving status data of the following vehicle, predict the first driving trajectory of the following vehicle; Based on the first driving trajectory and the second driving trajectory of the vehicle, determine whether the following vehicle has entered the danger zone behind the preceding vehicle; If the following vehicle enters the danger zone, the dynamic threshold data between the vehicle and the following vehicle is determined based on the real-time distance data, the real-time relative speed, and the road surface adhesion coefficient.

7. The method according to claim 6, characterized in that, The step of determining whether the following vehicle has entered the danger zone behind the preceding vehicle based on the first driving trajectory and the second driving trajectory of the vehicle itself includes: If the first driving trajectory coincides with the second driving trajectory, and the real-time distance data is less than the first preset distance, it is determined that the following vehicle has entered the danger zone; If the first driving trajectory coincides with the second driving trajectory, and the real-time distance data is greater than or equal to the first preset distance, it is determined that the following vehicle has not entered the danger zone; If the first driving trajectory does not coincide with the second driving trajectory, it is determined that the following vehicle has not entered the danger zone.

8. A rear-facing warning device for a vehicle, characterized in that, The device includes: The acquisition module is used to acquire real-time distance data, real-time relative speed, and road surface adhesion coefficient between the vehicle and the vehicle behind it. The first determining module is used to determine the dynamic threshold data between the vehicle and the following vehicle based on the real-time distance data, the real-time relative speed, and the road surface adhesion coefficient. The second determining module is used to determine the target warning information in the mapping relationship based on the dynamic threshold data. The mapping relationship records at least one preset threshold range and the warning information corresponding to each preset threshold.

9. A vehicle, characterized in that, include: The processor, memory, communication interface, and communication bus are provided, wherein the processor, memory, and communication interface communicate with each other via the communication bus. The memory is used to store at least one executable instruction that causes the processor to perform the operation of the vehicle rear warning method as described in any one of claims 1-7.

10. A computer-readable storage medium, characterized in that, The storage medium stores at least one executable instruction; When the executable instruction is executed on the vehicle / vehicle rear warning device, it causes the vehicle / vehicle rear warning device to perform the operation of the vehicle rear warning method as described in any one of claims 1-7.

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