Vehicle forward collision warning method, device, equipment and storage medium

Abstract

The present invention discloses a vehicle forward collision warning method, device, equipment, and storage medium, relating to the field of intelligent driving technology. The vehicle forward collision warning method includes: acquiring multiple frames of road environment feature images in front of the vehicle to determine the position and speed information corresponding to the obstacle; determining suspected targets posing potential threats based on a set safety distance; calculating the collision time corresponding to each frame of the road environment feature image based on the position and speed of the suspected target; when the calculated collision time under a certain number of consecutive frames of road environment feature images is less than a set threshold, marking the suspected target and the corresponding collision time; selecting the suspected target with the collision time closest to the current time as the final target, and using the collision time corresponding to the final target as the latest warning time for forward collision warning. This application can effectively reduce the probability of false triggering of forward collision warnings caused by visual interference.

Description

Technical Field

[0001] The present application relates to the field of intelligent driving technology, and in particular to a vehicle forward collision warning method, device, equipment and storage medium. Background Art

[0002] FCW (Forward Collision Warning) is a car safety assistance system whose main purpose is to reduce the risk of accidents by warning the driver in advance of possible forward collision hazards.

[0003] The FCW system uses sensors mounted on the front of the vehicle, such as radar and cameras, to continuously monitor road conditions ahead. These sensors acquire real-time information such as the position and speed of the vehicle ahead and transmit it to the FCW system. After receiving this information, the system uses algorithms to make decisions. This involves analyzing factors such as the vehicle ahead's trajectory and its relative speed to assess the potential for a collision. If the FCW system determines a collision is imminent, it will issue a timely warning to the driver, typically through audible, visual, or seat vibrations.

[0004] However, due to the instability of visual perception, such as when traveling on curves or uphill or downhill, the perceived distance and actual distance may deviate. Generally speaking, the perceived distance is longer when traveling uphill and shorter when traveling downhill. This can affect the collision time calculated by FCW, leading to false triggering of FCW.

[0005] In addition, the collision time threshold for triggering the forward collision warning function in the existing technology is too fixed and single, and cannot be learned based on different drivers to provide warnings that are more in line with the driver's own driving habits, which to some extent affects the user's driving experience. Summary of the Invention

[0006] The present application provides a vehicle forward collision warning method, device, equipment and storage medium, which can effectively reduce the probability of false triggering of forward collision warning due to visual interference.

[0007] In a first aspect, an embodiment of the present application provides a vehicle forward collision warning method, the vehicle forward collision warning method comprising:

[0008] Obtain multiple frames of road environment feature images in front of the vehicle to determine the position and speed information corresponding to the obstacle;

[0009] Identify suspected targets with potential threats based on the set safety distance;

[0010] Based on the position and speed of the suspected target, the collision time corresponding to each frame of the road environment feature image is calculated. When the calculated collision time under a certain number of consecutive frames of road environment feature images is less than the set threshold, the suspected target and the corresponding collision time are marked;

[0011] The suspected target whose collision time is closest to the current time is selected as the final target, and the collision time corresponding to the final target is used as the latest warning time for forward collision warning.

[0012] In conjunction with the first aspect, in one embodiment, the method further includes:

[0013] Record the latest warning time of the most recent forward collision warning;

[0014] The threshold is adjusted so that a forward collision warning is performed only when the next calculated collision time is less than or equal to the latest warning time.

[0015] In conjunction with the first aspect, in one embodiment, calculating the collision time corresponding to each frame of the road environment feature image based on the position and velocity of the suspected target includes:

[0016] Determine the forward collision distance between the center of mass of the vehicle and the suspected target based on the position of the suspected target;

[0017] Determine the relative speed between the vehicle and the suspected target based on the speed of the suspected target;

[0018] The collision time corresponding to each frame of the road environment feature image is calculated according to the forward collision distance and the relative speed.

[0019] In conjunction with the first aspect, in one embodiment, the method further includes:

[0020] Extract lane line and curb contour information from road environment feature images;

[0021] Based on the constraints of lane lines and curb contours, irrelevant obstacles are eliminated.

[0022] In combination with the first aspect, in one embodiment, the safety distance d is determined according to the formula: d=k*(t*v+b);

[0023] Where k is the safety factor set according to road and weather conditions, t is the average driver's reaction time, v is the relative speed between the vehicle and the obstacle, and b is the braking distance of the vehicle at the current speed.

[0024] In combination with the first aspect, in one embodiment, the position and speed information corresponding to the obstacle are determined by obtaining multiple frames of road environment feature images in front of the vehicle based on a camera, and combining the road terrain information and target coordinate information obtained by the global positioning system GPS.

[0025] In conjunction with the first aspect, in one embodiment, the method further includes:

[0026] Color-coded labels are added to each frame of road environment feature images to distinguish different types of obstacles.

[0027] In a second aspect, an embodiment of the present application provides a vehicle forward collision warning device, the vehicle forward collision warning device comprising:

[0028] An image processing module is used to obtain multiple frames of road environment feature images in front of the vehicle and determine the position and speed information corresponding to the obstacle;

[0029] A calculation module, which determines suspected targets with potential threats based on a set safety distance;

[0030] The calculation module also calculates the collision time corresponding to each frame of the road environment feature image based on the position and speed of the suspected target. When the calculated collision time under a certain number of consecutive frames of the road environment feature image is less than a set threshold, the suspected target and the corresponding collision time are marked;

[0031] The early warning module is used to select the suspected target whose collision time is closest to the current time as the final target, and use the collision time corresponding to the final target as the latest warning time for forward collision warning.

[0032] In a third aspect, an embodiment of the present application provides a vehicle forward collision warning device, which includes a processor, a memory, and a vehicle forward collision warning program stored in the memory and executable by the processor, wherein when the vehicle forward collision warning program is executed by the processor, the steps of the above-mentioned vehicle forward collision warning method are implemented.

[0033] In a fourth aspect, a computer-readable storage medium stores a vehicle forward collision warning program, wherein when the vehicle forward collision warning program is executed by a processor, the steps of the above-mentioned vehicle forward collision warning method are implemented.

[0034] The beneficial effects of the technical solutions provided in the embodiments of the present application include at least:

[0035] The vehicle forward collision warning method in the present application obtains multiple frames of road environment feature images in front of the vehicle to determine the position and speed information corresponding to the obstacle; determines a suspected target with potential threat based on a set safety distance; calculates the collision time corresponding to each frame of the road environment feature image based on the position and speed of the suspected target; when the collision time calculated under a certain number of consecutive frames of road environment feature images is less than a set threshold, marks the suspected target and the corresponding collision time; selects the suspected target whose collision time is closest to the current time as the final target, and uses the collision time corresponding to the final target as the latest warning time for forward collision warning.

[0036] In other words, this application calculates the collision time based on multiple frames of road environment feature images and only issues a forward collision warning when the calculated collision time based on a certain number of consecutive frames of road environment feature images is less than a set threshold. This application comprehensively considers the calculations of multiple frames of images, thus effectively avoiding false triggering caused by perception errors in the existing technology.

[0037] In addition, this application also adjusts the collision warning threshold based on the latest warning time of the most recent forward collision warning, so as to better adapt to the driving styles of different drivers and improve the driving experience. BRIEF DESCRIPTION OF THE DRAWINGS

[0038] Figure 1 This is a flow chart of an embodiment of a vehicle forward collision warning method of the present application;

[0039] Figure 2 This is a flowchart of step S3 of this application;

[0040] Figure 3 This is a flowchart of step S5 of this application;

[0041] Figure 4 This is a structural block diagram of an embodiment of a vehicle forward collision warning device of the present application;

[0042] Figure 5 This is a schematic diagram of the hardware structure of the vehicle forward collision warning device involved in the embodiment of the present application. DETAILED DESCRIPTION

[0043] In order to enable those skilled in the art to better understand the present invention, the following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0044] In order to make the objectives, technical solutions and advantages of this application clearer, the implementation methods of this application will be further described in detail below with reference to the accompanying drawings.

[0045] In a first aspect, an embodiment of the present application provides a vehicle forward collision warning method.

[0046] In one embodiment, referring to Figure 1 , Figure 1 This is a flow chart of an embodiment of the vehicle forward collision warning method of this application. Figure 1 As shown, the vehicle forward collision warning method includes:

[0047] S1. Acquire multiple frames of road environment feature images in front of the vehicle and determine the position and speed information corresponding to the obstacle;

[0048] In this embodiment, the camera is mainly used to capture characteristic images of the road environment in front of the vehicle to determine the position and speed information corresponding to the obstacle.

[0049] Preferably, the position and speed information corresponding to the obstacle can be determined by obtaining multiple frames of road environment feature images in front of the vehicle based on the camera and combining the road terrain information and target coordinate information obtained by the global positioning system GPS.

[0050] It is understood that in order to obtain more accurate image information of the road, a camera or other image capture device can be used and then combined with GPS data to provide richer location awareness information, such as for self-driving cars. GPS can provide location information, while the camera provides real-time visual images.

[0051] In addition, in order to exclude some data that does not need to be considered, this embodiment also extracts lane line and curb contour information from the road environment feature image; based on the constraints of lane line and curb contour, irrelevant obstacles are excluded.

[0052] Specifically, obstacles outside the curb are generally not considered to be a collision risk for the vehicle (the ego vehicle). For lane markings, obstacles are generally not considered to change lanes at long solid lines. Therefore, based on the constraints of lane markings and curbs, some data can be effectively excluded, removing noise for subsequent analysis and calculations.

[0053] In addition, color-coded labels are added to each frame of the road environment feature image to distinguish different types of obstacles for statistical classification. For example, color-coded labels include green, yellow, and red to distinguish between vehicles, pedestrians, traffic signs, etc.

[0054] S2. Identify suspected targets that pose potential threats based on the set safety distance;

[0055] Specifically, in step S2:

[0056] According to the formula: d = k*(t*v+b), determine the safety distance d;

[0057] Where k is the safety factor set according to road and weather conditions, t is the average driver's reaction time, v is the relative speed between the vehicle and the obstacle, and b is the braking distance of the vehicle at the current speed.

[0058] When the distance between an obstacle and the vehicle is less than the safe distance, it is considered a suspected target with potential threat.

[0059] S3. Calculate the collision time corresponding to each frame of the road environment feature image based on the position and velocity of the suspected target. When the calculated collision time for a certain number of consecutive frames of the road environment feature image is less than a set threshold, mark the suspected target and the corresponding collision time.

[0060] For details, see Figure 2 As shown, based on the position and speed of the suspected target, the collision time corresponding to each frame of the road environment feature image is calculated, including:

[0061] S31. Determine a forward collision distance between the vehicle and the center of mass of the suspected target based on the position of the suspected target;

[0062] S32. Determine the relative speed between the vehicle and the suspected target based on the speed of the suspected target;

[0063] S33. Calculate the collision time corresponding to each frame of the road environment feature image according to the forward collision distance and relative speed.

[0064] It is worth noting that the threshold here refers to the triggering threshold of the FCW function, which is often related to the vehicle speed and the relative speed between the vehicle and the target in front.

[0065] Based on the above steps, the collision time corresponding to each frame of the road environment feature image can be calculated. In order to avoid false triggering due to perception errors in the existing technology, this embodiment will comprehensively consider the results of multi-frame calculations. Only when the collision time calculated under a certain number of consecutive frames of road environment feature images is less than the set threshold, it is considered to be a suspected target.

[0066] Specifically, it can be set that the collision time calculated within 100 consecutive frames is less than the set threshold value before it is determined to be a suspected target. It can be understood that in step S1, multiple frames (greater than 100 frames) of road environment feature images in front of the vehicle will be obtained, and then calculated frame by frame. Generally speaking, the collision time of the first calculated frame may be less than the threshold value, but the collision time calculated in the subsequent frames may be greater than the threshold value. If a forward collision warning is made based on the conclusion that the previous frame is less than the threshold value, it will cause a false trigger. Therefore, in this application, it is limited to the collision time of 100 consecutive frames that are less than the threshold value before a conclusion is made and a forward collision warning is made.

[0067] In addition, for repeated situations that occur in multi-frame calculations, such as the previous frame is greater than the threshold and the next frame is less than the threshold, you can ignore them and continue iterating.

[0068] S4. Select the suspected target whose collision time is closest to the current time as the final target, and use the collision time corresponding to the final target as the latest warning time to perform a forward collision warning.

[0069] To illustrate this with a specific example, in step S2, we can assume that based on the set safety distance, there are 10 suspected targets that pose a potential threat. Then, based on step S3, we find that only 5 of them meet the collision time threshold calculated for 100 consecutive frames. These 5 suspected targets are marked. Then, based on the current time, from these 5 marked suspected targets, the suspected target with the collision time closest to the current time is selected as the final target. Finally, the forward collision warning is issued based on the collision time corresponding to the final target as the latest warning time.

[0070] It can be understood that based on the above processing, obstacles can be screened well and the most appropriate target can be accurately selected for forward collision warning.

[0071] It is worth noting that some embodiments further include a step S5 of adjusting the threshold to suit the driver's driving style. Generally speaking, the triggering threshold of the FCW function is fixed. In order to improve the driver's experience, this embodiment will adaptively learn and dynamically adjust the threshold value. Specifically, see Figure 3 As shown, step S5 includes:

[0072] S51. Record the latest warning time of the most recent forward collision warning;

[0073] S52: Adjust the threshold so that a forward collision warning is issued only when the next calculated collision time is less than or equal to the latest warning time.

[0074] To summarize, the vehicle forward collision warning method in the present application obtains multiple frames of road environment feature images in front of the vehicle to determine the position and speed information corresponding to the obstacle; determines the suspected target with potential threat based on the set safety distance; calculates the collision time corresponding to each frame of the road environment feature image based on the position and speed of the suspected target, and when the collision time calculated under a certain number of consecutive frames of road environment feature images is less than the set threshold, marks the suspected target and the corresponding collision time; selects the suspected target whose collision time is closest to the current time as the final target, and uses the collision time corresponding to the final target as the latest warning time for forward collision warning.

[0075] In other words, this application calculates the collision time based on multiple frames of road environment feature images and only issues a forward collision warning when the calculated collision time based on a certain number of consecutive frames of road environment feature images is less than a set threshold. This application comprehensively considers the calculations of multiple frames of images, thus effectively avoiding false triggering caused by perception errors in the existing technology.

[0076] In addition, this application also adjusts the collision warning threshold based on the latest warning time of the most recent forward collision warning, so as to better adapt to the driving styles of different drivers and improve the driving experience.

[0077] In a second aspect, an embodiment of the present application also provides a vehicle forward collision warning device.

[0078] In one embodiment, referring to Figure 4 , Figure 4 This is a functional module diagram of an embodiment of the vehicle forward collision warning device of this application. Figure 4 As shown, the vehicle forward collision warning device includes an image processing module, a calculation module and a warning module.

[0079] Among them, the image processing module is used to obtain multiple frames of road environment feature images in front of the vehicle and determine the position and speed information corresponding to the obstacle.

[0080] The calculation module determines suspected targets that pose potential threats based on a set safety distance. The calculation module also calculates the collision time corresponding to each frame of the road environment feature image based on the position and speed of the suspected target. When the collision time calculated under a certain number of consecutive frames of road environment feature images is less than a set threshold, the suspected target and the corresponding collision time are marked.

[0081] The warning module is used to select the suspected target whose collision time is closest to the current time as the final target, and use the collision time corresponding to the final target as the latest warning time for forward collision warning.

[0082] Furthermore, in one embodiment, the early warning module is further configured to:

[0083] Record the latest warning time of the most recent forward collision warning;

[0084] The threshold is adjusted so that a forward collision warning is performed only when the next calculated collision time is less than or equal to the latest warning time.

[0085] Furthermore, in one embodiment, the calculation module calculates the collision time corresponding to each frame of the road environment feature image based on the position and speed of the suspected target, including:

[0086] Determine the forward collision distance between the center of mass of the vehicle and the suspected target based on the position of the suspected target;

[0087] Determine the relative speed between the vehicle and the suspected target based on the speed of the suspected target;

[0088] The collision time corresponding to each frame of the road environment feature image is calculated according to the forward collision distance and the relative speed.

[0089] Furthermore, in one embodiment, the image processing module is further configured to:

[0090] Extract lane line and curb contour information from road environment feature images;

[0091] Based on the constraints of lane lines and curb contours, irrelevant obstacles are eliminated.

[0092] Furthermore, in one embodiment, the calculation module is used to:

[0093] According to the formula: d = k*(t*v+b), determine the safety distance d;

[0094] Where k is the safety factor set according to road and weather conditions, t is the average driver's reaction time, v is the relative speed between the vehicle and the obstacle, and b is the braking distance of the vehicle at the current speed.

[0095] Furthermore, in one embodiment, the image processing module is further configured to:

[0096] The camera obtains multiple frames of road environment feature images in front of the vehicle, and combines the road terrain information and target coordinate information obtained by the global positioning system GPS to determine the position and speed information corresponding to the obstacle.

[0097] Furthermore, in one embodiment, the image processing module is further configured to:

[0098] Color-coded labels are added to each frame of road environment feature images to distinguish different types of obstacles.

[0099] Among them, the functional implementation of each module in the above-mentioned vehicle forward collision warning device corresponds to the various steps in the above-mentioned vehicle forward collision warning method embodiment, and their functions and implementation processes are no longer detailed here.

[0100] In a third aspect, an embodiment of the present application provides a vehicle forward collision warning device, which may be a device with data processing capabilities, such as a personal computer (PC), a laptop computer, or a server.

[0101] Reference Figure 5 , Figure 5 FIG2 is a schematic diagram of the hardware structure of the vehicle forward collision warning device involved in the embodiment of the present application. In the embodiment of the present application, the vehicle forward collision warning device may include a processor, a memory, a communication interface, and a communication bus.

[0102] The communication bus may be of any type and is used to interconnect the processor, memory, and communication interface.

[0103] Communication interfaces include input / output (I / O) interfaces, physical interfaces, and logical interfaces, used to interconnect components within the vehicle forward collision warning system, as well as interfaces used to interconnect the vehicle forward collision warning system with other devices (such as other computing devices or user devices). Physical interfaces can include Ethernet interfaces, fiber optic interfaces, ATM interfaces, etc.; user devices can include displays, keyboards, etc.

[0104] The memory can be various types of storage media, such as random access memory (RAM), read-only memory (ROM), non-volatile RAM (NVRAM), flash memory, optical storage, hard disk, programmable ROM (PROM), erasable PROM (EPROM), electrically erasable PROM (EEPROM), etc.

[0105] The processor may be a general-purpose processor that can call a vehicle forward collision warning program stored in a memory and execute the vehicle forward collision warning method provided in the embodiments of the present application. For example, the general-purpose processor may be a central processing unit (CPU). The method executed when the vehicle forward collision warning program is called can be referred to in the various embodiments of the vehicle forward collision warning method of the present application and will not be repeated here.

[0106] Those skilled in the art will understand that Figure 5 The hardware structure shown in the figure does not constitute a limitation to the present application and may include more or fewer components than shown in the figure, or a combination of certain components, or a different arrangement of components.

[0107] In a fourth aspect, an embodiment of the present application also provides a readable storage medium.

[0108] The readable storage medium of the present application stores a vehicle forward collision warning program, wherein when the vehicle forward collision warning program is executed by the processor, the steps of the vehicle forward collision warning method as described above are implemented.

[0109] Among them, the method implemented when the vehicle forward collision warning program is executed can refer to the various embodiments of the vehicle forward collision warning method of the present application, and will not be repeated here.

[0110] It should be noted that the serial numbers of the above-mentioned embodiments of the present application are for description only and do not represent the advantages or disadvantages of the embodiments.

[0111] Through the description of the above implementation methods, those skilled in the art can clearly understand that the above-mentioned embodiment methods can be implemented by means of software plus the necessary general hardware platform, of course, it 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 application, or the part that contributes to the prior art, can be embodied in the form of a software product, which is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk) as described above, and includes a number of instructions for enabling a terminal device to execute the methods described in each embodiment of the present application.

[0112] The terms "including" and "having" and any variations thereof in the specification and claims of this application and the above-mentioned drawings are intended to cover non-exclusive inclusions. For example, a process, method, system, product or device that includes a series of steps or units is not limited to the listed steps or units, but optionally includes steps or units that are not listed, or optionally includes other steps or units inherent to these processes, methods, products or devices. The terms "first", "second" and "third" are used to distinguish different objects, etc., and do not represent a sequence, nor do they limit the "first", "second" and "third" to different types.

[0113] In the description of the embodiments of this application, the words "exemplary," "for example," or "for example" are used to indicate examples, illustrations, or descriptions. Any embodiment or design described as "exemplary," "for example," or "for example" in the embodiments of this application should not be construed as being preferred or advantageous over other embodiments or designs. Rather, the use of words such as "exemplary," "for example," or "for example" is intended to present the relevant concepts in a concrete manner.

[0114] In the description of the embodiments of the present application, unless otherwise specified, “ / ” means or, for example, A / B can mean A or B; “and / or” in the text is merely a description of 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. In addition, in the description of the embodiments of the present application, “multiple” refers to two or more than two.

[0115] In some processes described in the embodiments of the present application, multiple operations or steps are included that appear in a specific order. However, it should be understood that these operations or steps may not be performed in the order in which they appear in the embodiments of the present application or may be performed in parallel. The sequence numbers of the operations are only used to distinguish between different operations, and the sequence numbers themselves do not represent any order of execution. In addition, these processes may include more or fewer operations, and these operations or steps may be performed in sequence or in parallel, and these operations or steps may be combined.

[0116] The above are only preferred embodiments of the present application and do not limit the patent scope of the present application. Any equivalent structure or equivalent process transformation made using the contents of the present application specification and drawings, or directly or indirectly applied in other related technical fields, are also included in the patent protection scope of the present application.

[0117] The above are only preferred embodiments of the present application and do not limit the patent scope of the present application. Any equivalent structure or equivalent process transformation made using the contents of the present application specification and drawings, or directly or indirectly applied in other related technical fields, are also included in the patent protection scope of the present application.

Claims

1. A vehicle forward collision warning method, characterized in that: The vehicle forward collision warning method comprises: Obtain multiple frames of road environment feature images in front of the vehicle to determine the position and speed information corresponding to the obstacle; Identify suspected targets with potential threats based on the set safety distance; Based on the position and speed of the suspected target, the collision time corresponding to each frame of the road environment feature image is calculated. When the calculated collision time under a certain number of consecutive frames of road environment feature images is less than the set threshold, the suspected target and the corresponding collision time are marked; The suspected target whose collision time is closest to the current time is selected as the final target, and the collision time corresponding to the final target is used as the latest warning time for forward collision warning.

2. The vehicle forward collision warning method according to claim 1, characterized in that: Also includes: Record the latest warning time of the most recent forward collision warning; The threshold is adjusted so that a forward collision warning is performed only when the next calculated collision time is less than or equal to the latest warning time.

3. The vehicle forward collision warning method according to claim 1 or 2, characterized in that: The calculation of the collision time corresponding to each frame of the road environment feature image based on the position and speed of the suspected target includes: Determine the forward collision distance between the center of mass of the vehicle and the suspected target based on the position of the suspected target; Determine the relative speed between the vehicle and the suspected target based on the speed of the suspected target; The collision time corresponding to each frame of the road environment feature image is calculated according to the forward collision distance and the relative speed.

4. The vehicle forward collision warning method according to claim 1, wherein: Also includes: Extract lane line and curb contour information from road environment feature images; Based on the constraints of lane lines and curb contours, irrelevant obstacles are eliminated.

5. The vehicle forward collision warning method according to claim 1, wherein: According to the formula: d = k*(t*v+b), determine the safety distance d; Where k is the safety factor set according to road and weather conditions, t is the average driver's reaction time, v is the relative speed between the vehicle and the obstacle, and b is the braking distance of the vehicle at the current speed.

6. The vehicle forward collision warning method according to claim 1, wherein: The camera obtains multiple frames of road environment feature images in front of the vehicle, and combines the road terrain information and target coordinate information obtained by the global positioning system GPS to determine the position and speed information corresponding to the obstacle.

7. The vehicle forward collision warning method according to claim 1, wherein: Also includes: Color-coded labels are added to each frame of road environment feature images to distinguish different types of obstacles.

8. A vehicle forward collision warning device, characterized in that: The vehicle forward collision warning device comprises: An image processing module is used to obtain multiple frames of road environment feature images in front of the vehicle and determine the position and speed information corresponding to the obstacle; A calculation module, which determines suspected targets with potential threats based on a set safety distance; The calculation module also calculates the collision time corresponding to each frame of the road environment feature image based on the position and speed of the suspected target. When the calculated collision time under a certain number of consecutive frames of the road environment feature image is less than a set threshold, the suspected target and the corresponding collision time are marked; The early warning module is used to select the suspected target whose collision time is closest to the current time as the final target, and use the collision time corresponding to the final target as the latest warning time for forward collision warning.

9. A vehicle forward collision warning device, characterized in that: The vehicle forward collision warning device includes a processor, a memory, and a vehicle forward collision warning program stored in the memory and executable by the processor, wherein when the vehicle forward collision warning program is executed by the processor, the steps of the vehicle forward collision warning method according to any one of claims 1 to 7 are implemented.

10. A computer-readable storage medium, characterized in that The computer-readable storage medium stores a vehicle forward collision warning program, wherein when the vehicle forward collision warning program is executed by the processor, the steps of the vehicle forward collision warning method according to any one of claims 1 to 7 are implemented.

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