Collision early warning method and device, vehicle and computer readable storage medium

Abstract

The invention relates to the field of road safety, in particular to a collision early warning method and device, a vehicle and a computer readable storage medium. The method comprises the steps of monitoring a target risk event; the target risk event comprises a target anti-collision object detected in the driving direction of the target vehicle; if the target risk event is monitored, obtaining target reference data; the target reference data comprises the windscreen wiper state of the target vehicle and / or weather data of the position where the target vehicle is located; determining target predicted collision time between the target vehicle and the target anti-collision object according to the target reference data; and performing collision early warning on the target vehicle according to the target predicted collision time. The effectiveness of vehicle collision early warning in severe environments such as rainy days can be improved.

Description

Technical Field

[0001] The present application relates to the field of road safety technology, and in particular to a collision warning method, device, vehicle and computer-readable storage medium. Background Art

[0002] With the development and popularization of intelligent driving technology, forward collision warning (FCW) has become one of the most practical functions for users and protects driver safety.

[0003] The existing forward collision warning solution mainly uses sensors such as cameras and millimeter-wave radars to detect the distance and speed of obstacles ahead in real time. When it detects that there is a risk of collision between the vehicle and the obstacle ahead, it will remind the driver of the risk of collision ahead through vision, sound, touch, etc., and actively intervene to avoid collision when necessary, thus bringing safety guarantees to the driver.

[0004] The effectiveness of related collision warning solutions depends on the accuracy and reliability of sensors such as cameras and millimeter-wave radars. In harsh environments such as rainy days, the sensors are disturbed by rain and other factors, and their ability to perceive obstacles in the direction of the vehicle's travel will be reduced, resulting in insufficient driving safety in harsh environments.

[0005] Therefore, a collision warning solution with a higher level of safety assurance is needed in severe weather conditions. Summary of the invention

[0006] In view of this, the embodiments of the present application provide a collision warning method, device, vehicle and computer-readable storage medium, which can solve the problem of insufficient safety guarantee of collision warning in existing harsh environments.

[0007] In a first aspect, an embodiment of the present application provides a collision warning method, the collision warning method comprising: monitoring a target risk event; the target risk event comprises detecting a target anti-collision object in the driving direction of a target vehicle; If the target risk event is monitored, target reference data is obtained; the target reference data includes the wiper status of the target vehicle and / or the weather data at the location of the target vehicle; Determining a target predicted collision time between the target vehicle and the target collision avoidance object according to the target reference data; A collision warning is provided to the target vehicle according to the target predicted collision time.

[0008] By adopting the above technical solution, when the accuracy and reliability of the sensor are affected by the severe weather environment such as rainy and snowy days, there is no need to improve the hardware of the sensor. Instead, it is considered that the target vehicle will generally start the wiper on demand in the rainy and snowy environment, and the working state of the wiper can indirectly reflect the amount of rain and snow, thereby reflecting the degree of influence of the weather environment on the sensor. The wiper status is easy to obtain and has strong universality. Correspondingly, in order to determine the weather conditions more accurately and directly, the weather data of the location of the target vehicle can also be obtained, and finally the target predicted collision time is determined based on the weather data and / or the wiper status. Different from the existing collision warning scheme, the target predicted collision time in this application introduces the degree of influence of the severe weather environment of rainy and snowy days on the accuracy and reliability of the sensor, thereby effectively improving the safety guarantee level of collision warning in the severe weather environment of rainy and snowy days, and providing protection for driving safety in severe weather environments.

[0009] In some embodiments, the method further comprises: Determining an original predicted collision time between the target vehicle and the target collision avoidance object according to relative motion information between the target collision avoidance object and the target vehicle; the relative motion information is determined according to data collected by a target sensor device; Determine a first influencing factor according to the target reference data; the first influencing factor is used to characterize the degree of influence of the weather conditions at the location of the target vehicle on the accuracy of the collected data; The original predicted collision time is adjusted according to the first influencing factor to obtain the target predicted collision time.

[0010] In some embodiments, the weather data includes a rainfall value; the wiper status includes a wiper gear position of the target vehicle; and the method further includes: The first influencing factor is determined according to the first sub-factor and / or the second sub-factor; wherein the first sub-factor is determined according to the comparison result between the rainfall value and a preset rainfall value threshold; the first sub-factor is positively correlated with the first influencing factor; the first sub-factor is positively correlated with the rainfall value; the second sub-factor is determined according to the wiper gear; the second sub-factor is positively correlated with the first influencing factor; the second sub-factor is positively correlated with the movement speed.

[0011] In some embodiments, the method further comprises: The first influencing factor is obtained by performing a weighted summation on the first sub-factor and the second sub-factor; wherein the weight corresponding to the first sub-factor is greater than the weight corresponding to the second sub-factor.

[0012] In some embodiments, the target vehicle is provided with a preset alarm system; the alarm system is used for the target vehicle to perform the collision warning; the method further includes: Determining the warning sensitivity of the alarm system according to the model information of the target vehicle; Determining a second influencing factor according to the warning sensitivity; The original predicted collision time is adjusted according to the second influencing factor and the first influencing factor to obtain the target predicted collision time.

[0013] In some embodiments, the method further comprises: Performing a product processing on the first influencing factor and the original predicted collision time to obtain a basic predicted collision time; The second influencing factor and the basic predicted collision time are summed to obtain the target predicted collision time.

[0014] In some embodiments, the weather data includes a rainfall value; the method further comprises: Detecting whether the target vehicle is provided with a rain sensor; If the target vehicle is provided with the rain sensor, the rain value is obtained through the rain sensor, and the rain value is used as the target reference data; If the target vehicle is not equipped with the rain sensor, the wiper status is used as the target reference data.

[0015] In a second aspect, an embodiment of the present application further provides a collision warning device, which includes a processor and a memory, the memory being used to store instructions, and the processor being used to call the instructions in the memory so that the collision warning device executes the collision warning method described in the first aspect.

[0016] In a third aspect, an embodiment of the present application further provides a vehicle, comprising: a processor and a memory, wherein the memory is used to store instructions, and the processor is used to call the instructions in the memory so that the vehicle executes the collision warning method as described in the first aspect.

[0017] In a fourth aspect, an embodiment of the present application further provides a computer-readable storage medium, wherein the computer-readable storage medium stores computer instructions. When the computer instructions are executed on a processor, the processor executes the collision warning method as described in the first aspect. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] Figure 1 The present invention is a flowchart of a collision warning method according to an embodiment of the present application.

[0019] Figure 2The present invention is a flowchart of a sub-step of a collision warning method provided according to an embodiment of the present application.

[0020] Figure 3 The present invention is a flowchart of a sub-step of a collision warning method provided according to an embodiment of the present application.

[0021] Figure 4 The present invention is a flowchart of a sub-step of a collision warning method provided according to an embodiment of the present application.

[0022] Figure 5 The present invention is a flowchart of a sub-step of a collision warning method provided according to an embodiment of the present application.

[0023] Figure 6 It is a schematic diagram of the structure of a collision warning device provided according to an embodiment of the present application.

[0024] Figure 7 It is a schematic diagram of the structure of a vehicle provided according to an embodiment of the present application. DETAILED DESCRIPTION

[0025] In order to more clearly understand the above-mentioned purposes, features and advantages of the present application, the present application is described in detail below in conjunction with the accompanying drawings and specific implementation methods. It should be noted that the implementation methods of the present application and the features in the implementation methods can be combined with each other without conflict.

[0026] In the following description, many specific details are set forth to facilitate a full understanding of the present application. The described implementations are only part of the implementations of the present application, rather than all the implementations.

[0027] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as those commonly understood by those skilled in the art to which this application belongs. The terms used herein in the specification of this application are only for the purpose of describing specific embodiments and are not intended to limit this application.

[0028] It should be further noted that, in this article, the terms "comprises", "includes" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also includes other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, an element defined by the sentence "comprises a ..." does not exclude the presence of other identical elements in the process, method, article or device including the element.

[0029] In this application, "at least one" means one or more, and "more" means two or more than two. "And / or" describes the association relationship of associated objects, indicating that three relationships may exist. For example, A and / or B can mean: A exists alone, A and B exist at the same time, and B exists alone, where A and B can be singular or plural. The terms "first", "second", "third", "fourth", etc. (if any) in the specification, claims and drawings of this application are used to distinguish similar objects, rather than to describe a specific order or sequence.

[0030] In the embodiments of the present application, words such as "exemplary" or "for example" are used to indicate examples, illustrations or descriptions. Any embodiment or design described as "exemplary" or "for example" in the embodiments of the present application should not be interpreted as being more preferred or more advantageous than other embodiments or designs. Specifically, the use of words such as "exemplary" or "for example" is intended to present related concepts in a specific way.

[0031] In the related art, the forward collision warning scheme generally detects obstacles in the direction of the vehicle's travel through sensors such as the forward-looking camera and the front radar installed on the vehicle, and issues a collision warning based on the detection results. For example, the distance, speed, and acceleration of the obstacle detected in front of the vehicle determine whether there is a risk of collision between the current vehicle and the obstacle. If there is a risk of collision, the driver is reminded to brake in a preset manner. The effectiveness of this collision warning scheme is highly dependent on the accuracy and reliability of sensors such as cameras and millimeter-wave radars. However, sensors such as the forward-looking camera and the front radar are exposed to the outside of the vehicle and are more sensitive to environmental conditions. In harsh environments such as rainy days, the sensors are interfered with and their ability to perceive obstacles in front of the vehicle's travel direction will be reduced, resulting in insufficient driving safety in harsh environments. At the same time, it should be noted that since environmental sensitivity is a hardware performance of sensors such as forward-looking cameras and front radars, it is difficult to optimize or the optimization cost is too high.

[0032] It can be seen from the above that there is a problem that the effectiveness of collision warning in severe weather conditions is insufficient.

[0033] In view of this, the embodiments of the present application provide a collision warning method, device, vehicle and computer-readable storage medium, which can improve the safety level of collision warning in severe weather conditions.

[0034] See also Figure 1, which is a flowchart of the steps of the collision warning method provided in one embodiment of the present application. According to different requirements, the order of the steps in the flowchart can be changed, and some steps can be omitted. The embodiment of the present application can be based on a preset electronic device. The electronic device has certain data processing capabilities, data storage capabilities, and communication capabilities. Specifically, the electronic device can be an intelligent driving device, a driving assistance device, etc., which is not limited by the embodiment of the present invention.

[0035] See also Figure 1 As shown, the collision warning method may include the following steps: Step 101: monitoring a target risk event; the target risk event includes detecting a target anti-collision object in the driving direction of a target vehicle.

[0036] Among them, the target anti-collision object may be an object that has a collision risk with the target vehicle. The collision risk may be determined through an existing collision prediction scheme, which is not limited by the present invention. Specifically, the target anti-collision object may include objects of preset target types, such as people, animals, buildings, preset plants, etc. The driving direction of the target vehicle may include the front of the target vehicle. The target risk event may be sent by a collision warning module preset on the target vehicle, which is used to detect obstacles in the driving direction of the target vehicle and identify whether there is a target anti-collision object. For example, the collision warning module is used to detect obstacles at a preset distance in the driving direction of the target vehicle to identify whether there is a target anti-collision object within a preset distance from the target vehicle.

[0037] Step 102: If the target risk event is monitored, target reference data is obtained; the target reference data includes the wiper status of the target vehicle and / or the weather data of the location of the target vehicle.

[0038] The wiper is used to wipe away foreign matter such as rain, dust, etc. attached to the front windshield of the target vehicle. The wiper state includes the working state of the wiper, and the working state can represent whether the wiper is turned on and the gear position of the wiper. The gear position of the wiper can represent the movement frequency of the wiper, the movement speed of the wiper, etc. It is understandable that the working state of the wiper can be subjectively controlled by the driver of the target vehicle. For example, in non-rainy scenes such as sunny days, the driver can also control the wiper to turn on to clean the front windshield.

[0039] The weather data at the location of the target vehicle includes meteorological information such as rainfall data, snow data, visibility, and illumination. Specifically, the corresponding type of weather data can be obtained through a preset type of meteorological sensor on the target vehicle. For example, rainfall data is obtained through a rain sensor on the target vehicle, and whether the fog lights on the target vehicle are turned on is used to determine whether the vehicle is currently in a foggy environment. Optionally, considering that some vehicle models may not be equipped with meteorological sensors such as rain sensors, the weather data at the location of the target vehicle can also be obtained through a preset meteorological service. Among them, the weather service is used to provide meteorological conditions at a specific geographical location.

[0040] In some embodiments, the weather data includes a rainfall value; wherein the rainfall value represents the rainfall amount, and the rainfall value can be collected by a rain sensor. The larger the rainfall value, the worse the weather conditions at the current location of the target vehicle, and the higher the risk of collision between the target vehicle and the vehicle in front. Among them, the reasons for the increased risk of collision due to bad weather may include at least one of the following: First, bad weather affects the reliability of data collected by target sensor devices such as the front-view camera and the front radar on which the forward collision warning relies. Second, the poor road conditions in bad weather increase the difficulty of driving, such as slippery roads, slow vehicles in front, congestion and other road conditions, which make collision accidents more likely to occur. Third, in bad weather conditions, the driver of the target vehicle may be limited in field of vision. For example, Figure 2 As shown, step 102 also includes: Step 1021: Detect whether the target vehicle is equipped with a rain sensor.

[0041] Considering that the working state of the wiper may be affected by the driver's manual control, the reliability of its correlation with the weather conditions is affected, and the rainfall data obtained by the rain sensor can more objectively reflect the severity of the weather. Therefore, it is preferred to use the rainfall value collected by the rain sensor as the target reference data. However, considering that some models may not be equipped with a rain sensor. Therefore, firstly, it is detected whether the target vehicle is equipped with a rain sensor.

[0042] Step 1022: If the target vehicle is provided with the rain sensor, the rainfall value is obtained through the rain sensor, and the rainfall value is used as the target reference data.

[0043] If the target vehicle is equipped with a rain sensor, the rainfall value is obtained through the rain sensor and used as the target reference data, thereby improving the reliability of reflecting the bad weather conditions through the target reference data, making the target predicted collision time subsequently determined based on the target reference data more accurate, thereby improving the safety level of the target vehicle.

[0044] Step 1023: If the target vehicle is not equipped with the rain sensor, the wiper status is used as the target reference data.

[0045] Among them, considering that in normal driving, if it rains, etc., the wiper of the target vehicle is generally activated, and the greater the rainfall, the greater the swing frequency and / or swing speed of the wiper. Therefore, if the target vehicle is not equipped with a rain sensor, the wiper state can also be used as the target reference data. And considering that wipers are currently equipped on various models, by using wipers as target reference data, more effective collision warnings can be provided for various models in bad weather environments, thereby improving the applicability of the embodiments of the present invention.

[0046] Step 103: Determine a target predicted collision time between the target vehicle and the target anti-collision object according to the target reference data.

[0047] Among them, considering that the existing collision warning generally only provides early warning based on the relative distance and relative speed between the target vehicle and the target anti-collision object, and the position and motion information of the target anti-collision object need to be collected by the target sensor equipment such as the front-view camera and the front radar on the target vehicle, and due to the hardware design and performance bottleneck of the target sensor equipment, the reliability of the data collected by the target sensor is more susceptible to the influence of the environment. For example, in severe weather environments such as rainstorms, the position information collected by the front-view camera may be offset, and the collection of motion information of the target anti-collision object by the front radar may be delayed. Therefore, in an embodiment of the present invention, based on the original predicted collision time determined by the existing collision warning scheme, the original predicted collision time is adjusted according to the target reference data, and the influence of weather conditions on the reliability of collision warning is introduced, so that the target predicted collision time is more accurate in the current scene. Among them, the degree of bad weather is determined according to the target reference data, and the original predicted collision time is adaptively amplified according to the degree of bad weather, so as to provide the driver of the target vehicle with a collision warning earlier, so that he has more time to react to the risk, greatly reducing the collision risk in severe weather scenes, and ensuring driving safety.

[0048] In some embodiments, Figure 3 As shown, step 103 also includes: Step 1031: determining an original predicted collision time between the target vehicle and the target collision avoidance object according to relative motion information between the target collision avoidance object and the target vehicle; the relative motion information is determined according to data collected by a target sensor device.

[0049] Among them, the relative motion information includes the relative distance, relative speed, relative acceleration, etc. between the target anti-collision object and the target vehicle. Among them, the relative distance may include the relative lateral distance and the relative longitudinal distance. According to the relative motion information, the original predicted collision time is obtained by calculating based on the preset forward collision warning algorithm. The preset forward collision warning algorithm may be an existing one, and the embodiments of the present application do not limit it. The target sensing device may include a forward-looking camera, a front radar, etc. provided on the target vehicle, and the collected data includes the position information, the motion state, etc. of the target anti-collision object.

[0050] Step 1032: Determine a first influencing factor based on the target reference data; the first influencing factor is used to characterize the degree of influence of the weather conditions at the location of the target vehicle on the accuracy of the collected data.

[0051] The target reference data is analyzed to obtain the severity of the weather at the location of the target vehicle, thereby determining the degree to which the accuracy of the collected data is affected according to the severity of the weather, and obtaining the first impact factor. Specifically, considering that the greater the rainfall, the worse the weather, and the greater the degree to which the accuracy and reliability of the collected data of the target sensor device are affected, the rainfall amount can be determined according to the target reference data, and the first impact factor can be determined according to the rainfall amount.

[0052] In some embodiments, the weather data includes a rainfall value; the wiper status includes a wiper gear position of the target vehicle; and the process of determining the first influencing factor further includes: The first influencing factor is determined according to the first sub-factor and / or the second sub-factor; wherein the first sub-factor is determined according to the comparison result between the rainfall value and a preset rainfall value threshold; the first sub-factor is positively correlated with the first influencing factor; the first sub-factor is positively correlated with the rainfall value. The second sub-factor is determined according to the wiper gear; the second sub-factor is positively correlated with the first influencing factor; the second sub-factor is positively correlated with the movement speed.

[0053] Among them, considering that the greater the rainfall, the worse the weather, the greater the degree of impact on the accuracy and reliability of the collected data of the target sensor device, therefore, the greater the rainfall value, the greater the first sub-factor. Specifically, the first sub-factor can be the multiple that the original predicted collision time needs to be amplified. In order to standardize the first sub-factor so that its value is within the preset interval, the first sub-factor can be determined according to the ratio of the rainfall value to the rainfall value threshold, wherein the rainfall value threshold is used to characterize the rainfall when the reliability of the collected data is most affected. For example, when the percentage of the rainfall value to the rainfall value threshold is 0.1 or less, the first sub-factor can be 1. When the percentage of the rainfall value to the rainfall value threshold is 0.1 to 0.4, the first sub-factor can be 1.1, and when the percentage of the rainfall value to the rainfall value threshold is 0.4 to 0.8, the first sub-factor can be 1.3. When the percentage of the rainfall value to the rainfall value threshold is 0.8 to 1, the first sub-factor can be 1.5.

[0054] Correspondingly, considering that the faster the wiper moves, the greater the amount of rain that needs to be cleared per unit time, and correspondingly, the greater the interference to the target sensor device, the wiper's movement speed can be determined according to the wiper gear, and the second sub-factor can be determined according to the movement speed, wherein the first sub-factor can be the multiple that the original predicted collision time needs to be amplified. The greater the movement speed, the greater the second sub-factor. For example, the movement speed can be compared with a plurality of preset speed thresholds to obtain whether the current wiper is in a gear such as off, slow, fast or intermittent, and the second sub-factor can be determined according to the gear. Among them, when the wiper is off, the first sub-factor can be 1, when the wiper is in an intermittent state, the first sub-factor can be 1.1, when the wiper is in a slow state, the first sub-factor can be 1.3, and when the wiper is in a fast state, the first sub-factor can be 1.5.

[0055] In some embodiments, the process of determining the first impact factor further includes: The first influencing factor is obtained by performing a weighted summation on the first sub-factor and the second sub-factor; wherein the weight corresponding to the first sub-factor is greater than the weight corresponding to the second sub-factor.

[0056] Among them, considering that the wiper state may be affected by human control, and under the same weather conditions, different users' control preferences may result in different wiper states. For example, when the weather is clear but there is dust on the windshield, the driver may also turn on the wiper, or users have different requirements for the clarity of the windshield. Even under the same rainfall, different drivers may control the wiper to work at different speeds. Correspondingly, the rainfall sensor collects rainfall more objectively and accurately. Therefore, in the embodiment of the present application, the weight corresponding to the first sub-factor is set to be greater than the weight corresponding to the second sub-factor, thereby improving the accuracy of the first influencing factor in reflecting severe weather conditions.

[0057] Step 1033: Adjust the original predicted collision time according to the first influencing factor to obtain the target predicted collision time.

[0058] The original predicted collision time may be amplified according to the first impact factor to obtain the target predicted collision time. The product of the first impact factor and the original predicted collision time may be used as the target predicted collision time.

[0059] In some embodiments, the target vehicle is provided with a preset alarm system; the alarm system is used to provide the target vehicle with the collision warning. Specifically, the alarm system can provide the target vehicle with a warning in the form of sound, vision, touch, etc. Figure 4 As shown, the process of determining the target predicted collision time includes: Step 1034: Determine the warning sensitivity of the alarm system according to the vehicle type information of the target vehicle.

[0060] Among them, the warning sensitivity is used to characterize the sensitivity of the alarm system for collision warning. Specifically, the warning sensitivity can be determined based on the time interval from detecting the presence of the target anti-collision object to issuing a warning to the driver of the target vehicle. The smaller the time interval, the greater the warning sensitivity. It is understandable that the warning sensitivity of the alarm system configured on vehicles of different models may vary due to different software and hardware configurations. It should be noted that the warning sensitivity can also be determined according to existing methods, and the embodiments of the present application are not limited to this.

[0061] Step 1035: Determine a second impact factor according to the warning sensitivity.

[0062] The second impact factor is used to characterize the degree to which the original predicted collision time needs to be increased. Considering that the more sensitive the alarm system is, the faster the user receives the collision warning, so the user has more time to avoid danger. Therefore, the greater the warning sensitivity, the smaller the second impact factor.

[0063] Step 1036: Adjust the original predicted collision time according to the second influencing factor and the first influencing factor to obtain the target predicted collision time.

[0064] Among them, considering that the first influencing factor is used to characterize the severity of the weather, and the second influencing factor is used to characterize the warning sensitivity of the alarm system, the severe weather has a greater impact on the effectiveness of the collision warning, and the warning sensitivity of the alarm system has a relatively smaller impact on the effectiveness of the collision warning. Therefore, when adjusting the original predicted collision time according to the second influencing factor and the first influencing factor, the weight corresponding to the first influencing factor can be set relatively larger, and the weight corresponding to the second influencing factor can be set relatively smaller.

[0065] In some embodiments, Figure 5 As shown, step 1036 also includes: Step 1037: Perform product processing on the first influencing factor and the original predicted collision time to obtain a basic predicted collision time.

[0066] Among them, considering that the first impact factor represents the current bad weather, and the bad weather has a greater impact on the accuracy of the original predicted collision time, the first impact factor is used as the degree to which the original predicted collision time needs to be magnified under the current bad weather environment. By performing a product process on the first impact factor and the original predicted collision time, the original predicted collision time is magnified as the basic predicted collision time, so that the target vehicle can be warned of collision earlier in bad weather environments such as rainy days, so that the driver of the target vehicle can have more time to respond to the brakes, effectively reducing the risk of collision in bad weather.

[0067] Step 1038: summing the second influencing factor and the basic predicted collision time to obtain the target predicted collision time.

[0068] Correspondingly, considering that the warning sensitivity of the alarm system has a relatively small impact on the effectiveness of the collision warning, the second influencing factor can be used as the time that needs to be added to the original predicted collision time on the basis of the basic predicted collision time to obtain the target predicted collision time. In this way, in severe weather conditions, the driver of the target vehicle is provided with more time to avoid danger, avoiding the target predicted collision time being too long, which makes the driver of the target vehicle less vigilant and reduces the effectiveness of the collision warning.

[0069] Optionally, considering that in addition to interfering with the target sensing equipment, thereby affecting the reliability and accuracy of the collected data, inclement weather can also interfere with driving difficulty, risk avoidance difficulty, etc., making the target vehicle more likely to collide with the vehicle in front, therefore, a third influencing factor can also be determined based on the target reference data, and the third influencing factor is used to characterize the degree of influence of the weather conditions at the location of the target vehicle on the driving difficulty and / or braking difficulty of the target vehicle. The original predicted collision time is amplified according to the third influencing factor to obtain the target predicted collision time.

[0070] Step 104: Providing a collision warning to the target vehicle according to the target predicted collision time.

[0071] Specifically, a collision warning is issued to the target vehicle before the target predicted collision time, so that the driver of the target vehicle can make a risk avoidance response in time to avoid collision with the target anti-collision object in front, effectively improving driving safety in severe weather conditions.

[0072] Please refer to Figure 6 , is a schematic diagram of the hardware structure of the collision warning device 20 provided in the embodiment of the present application. Figure 6 As shown, the collision warning device 20 may include: A monitoring module 201 is used to monitor a target risk event; the target risk event includes detecting a target anti-collision object in the driving direction of the target vehicle; The acquisition module 202 is used to acquire target reference data if the target risk event is monitored; the target reference data includes the wiper status of the target vehicle and / or the weather data of the location of the target vehicle; A determination module 203 is used to determine a target predicted collision time between the target vehicle and the target collision avoidance object according to the target reference data; The warning module 204 is used to provide a collision warning to the target vehicle according to the target predicted collision time.

[0073] Please refer to Figure 7 , is a schematic diagram of the hardware structure of the vehicle 30 provided in the embodiment of the present application. Figure 7 As shown, the vehicle 30 may include a processor 301 and a memory 302. The memory 302 is used to store one or more computer programs 303. The one or more computer programs 303 are configured to be executed by the processor 301. The one or more computer programs 303 include instructions, and the above instructions can be used to implement the above collision warning method in the vehicle 30.

[0074] It is understood that the structure shown in this embodiment does not constitute a specific limitation on the vehicle 30. In other embodiments, the vehicle 30 may include more or fewer components than shown, or combine some components, or separate some components, or arrange the components differently.

[0075] The processor 301 may include one or more processing units, for example, the processor 301 may include an application processor (AP), a modem, a graphics processing unit (GPU), an image signal processor (ISP), a controller, a video codec, a digital signal processor (DSP), a baseband processor, and / or a neural-network processing unit (NPU), etc. Different processing units may be independent devices or integrated into one or more processors.

[0076] The processor 301 may also be provided with a memory for storing instructions and data. In some embodiments, the memory in the processor 301 is a cache memory. The memory may store instructions or data that the processor 301 has just used or circulated. If the processor 301 needs to use the instruction or data again, it may be directly called from the memory. This avoids repeated access, reduces the waiting time of the processor 301, and thus improves the efficiency of the system.

[0077] In some embodiments, the processor 301 may include one or more interfaces. The interface may include an inter-integrated circuit (I2C) interface, an inter-integrated circuit sound (I2S) interface, a pulse code modulation (PCM) interface, a universal asynchronous receiver / transmitter (UART) interface, a mobile industry processor interface (MIPI), a general-purpose input / output (GPIO) interface, a SIM interface, and / or a USB interface, etc.

[0078] In some embodiments, the processor 301 is used to execute acceleration schemes such as single instruction multiple data (SIMD) and very long instruction word (VLIW).

[0079] In some embodiments, the memory 302 may include a high-speed random access memory and may also include a non-volatile memory, such as a hard disk, a memory, a plug-in hard disk, a Smart Media Card (SMC), a Secure Digital (SD) card, a flash card (Flash Card), at least one disk storage device, a flash memory device, or other volatile solid-state storage devices.

[0080] This embodiment also provides a computer-readable storage medium, in which computer instructions are stored. When the instructions are executed on a processor, the processor executes the above-mentioned related method steps to implement the collision warning method in the above-mentioned embodiment.

[0081] Among them, the collision warning device and computer-readable storage medium provided in this embodiment are used to execute the corresponding methods provided above. Therefore, the beneficial effects that can be achieved can refer to the beneficial effects in the corresponding methods provided above, and will not be repeated here.

[0082] In practical applications, the above functions can be distributed to different functional modules as needed, that is, the internal structure of the device can be divided into different functional modules to complete all or part of the functions described above.

[0083] In several embodiments provided in the present application, the disclosed devices and methods can be implemented in other ways. For example, the device embodiments described above are schematic. For example, the division of the modules or units is a logical function division. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another device, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0084] The unit described as a separate component may or may not be physically separated, and the component shown as a unit may be one physical unit or multiple physical units, that is, it may be located in one place or distributed in multiple different places. Some or all of the units may be selected according to actual needs to achieve the purpose of the embodiment.

[0085] In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0086] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a readable storage medium. Based on this understanding, the technical solution of the embodiment of the present application is essentially or the part that contributes to the prior art or all or part of the technical solution can be embodied in the form of a software product, which is stored in a storage medium and includes several instructions to enable a device (which can be a single-chip microcomputer, chip, etc.) or a processor (processor) to execute all or part of the steps of the method described in each embodiment of the present application. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (Read-Only Memory, ROM), random access memory (Random Access Memory, RAM), disk or optical disk and other media that can store program code.

[0087] The above description is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any changes or substitutions within the technical scope disclosed in the present application should be included in the protection scope of the present application.

Claims

1. A collision warning method, characterized in that: The method comprises: Monitoring target risk events; the target risk events include detecting a target anti-collision object in the driving direction of the target vehicle; If the target risk event is monitored, target reference data is obtained; the target reference data includes the wiper status of the target vehicle and / or the weather data at the location of the target vehicle; Determining a target predicted collision time between the target vehicle and the target collision avoidance object according to the target reference data; A collision warning is provided to the target vehicle according to the target predicted collision time.

2. The method according to claim 1, characterized in that The process of determining the target predicted collision time includes: Determining an original predicted collision time between the target vehicle and the target collision avoidance object according to relative motion information between the target collision avoidance object and the target vehicle; the relative motion information is determined according to data collected by a target sensor device; Determine a first influencing factor according to the target reference data; the first influencing factor is used to characterize the degree of influence of the weather conditions at the location of the target vehicle on the accuracy of the collected data; The original predicted collision time is adjusted according to the first influencing factor to obtain the target predicted collision time.

3. The method according to claim 2, characterized in that The weather data includes a rainfall value; the wiper state includes a wiper gear position of the target vehicle; and the determination process of the first influencing factor includes: The first influencing factor is determined according to the first sub-factor and / or the second sub-factor; wherein the first sub-factor is determined according to the comparison result between the rainfall value and a preset rainfall value threshold; the first sub-factor is positively correlated with the first influencing factor; the first sub-factor is positively correlated with the rainfall value; the second sub-factor is determined according to the wiper gear; the second sub-factor is positively correlated with the first influencing factor; the second sub-factor is positively correlated with the movement speed.

4. The method according to claim 3, characterized in that The process of determining the first impact factor further includes: The first influencing factor is obtained by performing a weighted summation on the first sub-factor and the second sub-factor; wherein the weight corresponding to the first sub-factor is greater than the weight corresponding to the second sub-factor.

5. The method according to claim 2, characterized in that: The target vehicle is provided with a preset alarm system; the alarm system is used for the target vehicle to perform the collision warning; The process of determining the target predicted collision time also includes: Determining the warning sensitivity of the alarm system according to the model information of the target vehicle; Determining a second influencing factor according to the warning sensitivity; The original predicted collision time is adjusted according to the second influencing factor and the first influencing factor to obtain the target predicted collision time.

6. The method according to claim 5, characterized in that The process of determining the target predicted collision time also includes: Performing a product processing on the first influencing factor and the original predicted collision time to obtain a basic predicted collision time; The second influencing factor and the basic predicted collision time are summed to obtain the target predicted collision time.

7. The method according to any one of claims 1 to 6, characterized in that: The weather data includes rainfall values; the determination process of the target reference data includes: Detecting whether the target vehicle is provided with a rain sensor; If the target vehicle is provided with the rain sensor, the rain value is obtained through the rain sensor, and the rain value is used as the target reference data; If the target vehicle is not equipped with the rain sensor, the wiper status is used as the target reference data.

8. A collision warning device, characterized in that: The collision warning device comprises: A monitoring module, used to monitor target risk events; the target risk events include detecting a target anti-collision object in the driving direction of the target vehicle; An acquisition module, configured to acquire target reference data if the target risk event is monitored; the target reference data includes the wiper status of the target vehicle and / or weather data at the location of the target vehicle; A determination module, configured to determine a target predicted collision time between the target vehicle and the target collision avoidance object according to the target reference data; The warning module is used to provide a collision warning to the target vehicle according to the target predicted collision time.

9. A vehicle, comprising a processor and a memory, characterized in that: The memory is used to store instructions, and the processor is used to call the instructions in the memory, so that the vehicle executes the collision warning method according to any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer instructions, and when the computer instructions are executed on a processor, the processor is enabled to execute the collision warning method according to any one of claims 1 to 7.

Images