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

Abstract

The invention discloses a vehicle forward collision early warning method, device and equipment and a storage medium, and relates to the technical field of intelligent driving, and the vehicle forward collision early warning method comprises the steps: obtaining a plurality of frames of road environment feature images in front of a vehicle, and determining the position and speed information corresponding to an obstacle; according to a set safety distance, determining a suspected target with a potential threat; based on the position and the speed of the suspected target, calculating collision time corresponding to each frame of road environment feature image, and when the collision time calculated under a certain continuous frame number of road environment feature images is smaller than a set threshold value, marking the suspected target and the corresponding collision time; and selecting the suspected target with the collision time closest to the current time as a final target, and performing forward collision early warning by taking the collision time corresponding to the final target as the latest warning time. According to the method and the device, the probability of forward collision early warning false triggering caused by visual interference can be effectively reduced.

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 continuously senses the road conditions ahead through sensors installed on the front of the vehicle, such as radar and cameras. These sensors obtain the position, speed and other information of the vehicle ahead in real time and transmit it to the FCW system. After receiving the information of the vehicle ahead, the system makes judgments and decisions through algorithms. That is, it analyzes factors such as the movement trajectory of the vehicle ahead and the relative speed with the vehicle ahead to assess whether there is a potential risk of collision. Once the FCW system determines that there is a risk of collision, the system will issue a timely warning to the driver, usually through sound, light signals, vibration seats, etc.

[0004] However, due to the instability of information brought by visual perception, for example, when driving on a curve or uphill or downhill, the perceived distance and the actual distance will deviate. Generally speaking, the perceived distance will be longer when driving uphill and shorter when driving downhill. This will affect the collision time calculated by FCW, thus causing FCW to be triggered incorrectly.

[0005] In addition, the collision time threshold for triggering the forward collision warning function in the prior art 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 the road environment feature image 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 combination with the first aspect, in one implementation, 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 combination with the first aspect, in one implementation, the calculating the collision time corresponding to each frame of the road environment feature image based on the position and speed of the suspected target includes:

[0016] According to the position of the suspected target, determine the forward collision distance between the center of mass of the vehicle and the suspected target;

[0017] According to the speed of the suspected target, determine the relative speed between the vehicle and 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 combination with the first aspect, in one implementation, 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 implementation, the safety distance d is determined according to the formula: d=k*(t*v+b);

[0023] Among them, k is the safety factor set according to road conditions and weather conditions, t is the average reaction time of the driver, 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 implementation, the position and speed information corresponding to the obstacle are determined based on the camera acquiring multiple frames of road environment feature images in front of the vehicle and combining the road terrain information and target coordinate information acquired by the global positioning system GPS.

[0025] In combination with the first aspect, in one implementation, the method further includes:

[0026] Color-coded labels are added to each frame of the road environment feature image 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, and marks the suspected target and the corresponding collision time when the calculated collision time under a certain number of consecutive frames of the road environment feature image is less than a set threshold;

[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 brought by the technical solution provided by the embodiment 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 according to 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, and marks the suspected target and the corresponding collision time when the calculated collision time under a certain number of consecutive frames of road environment feature images is less than a set threshold; 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] That is to say, the present application calculates the collision time under multiple frames of road environment characteristic images, and only issues a forward collision warning when the collision time calculated under a certain number of consecutive frames of road environment characteristic images is less than a set threshold. That is, the present application is a comprehensive consideration made after comprehensive calculation of multiple frames of images, so as to avoid false triggering caused by perception errors in the prior art.

[0037] In addition, the present application also adjusts the threshold of the collision warning according to 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 flow chart of step S3 of this application;

[0040] Figure 3 This is a flow chart 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 a 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 solution of the present application, the technical solution in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, 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 the present application clearer, the implementation methods of the present 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 the present application. Figure 1 As shown, the vehicle forward collision warning method includes:

[0047] S1, obtaining multiple frames of road environment feature images in front of the vehicle, and determining the position and speed information corresponding to the obstacle;

[0048] In this embodiment, the position and speed information corresponding to the obstacle are determined mainly by collecting the characteristic image of the road environment in front of the vehicle through the camera.

[0049] Preferably, the position and speed information corresponding to the obstacle can be determined based on the camera acquiring multiple frames of road environment feature images in front of the vehicle, and combining the road terrain information and target coordinate information acquired 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. The location information can be provided by GPS, while the camera provides real-time visual images.

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

[0052] Specifically, for obstacles outside the curb contour, it is usually not considered that the vehicle (the vehicle) will collide with it. For lane lines, it is usually not considered that obstacles will change lanes at long solid lines. Therefore, based on the constraints of lane lines and curb contours, some data can be well excluded to remove noise for subsequent analysis and calculation.

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

[0054] S2. Determine suspected targets with 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] Among them, k is the safety factor set according to road conditions and weather conditions, t is the average reaction time of the driver, 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, based on the position and speed of the suspected target, calculate the collision time corresponding to each frame of the road environment feature image, and when the calculated collision time under 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, determining a forward collision distance between the center of mass of the vehicle and the suspected target according to the position of the suspected target;

[0062] S32, determining the relative speed between the vehicle and the suspected target according to 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 the 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 ahead.

[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 caused by perception errors in the prior art, 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 within 100 consecutive frames, the calculated collision time is less than the set threshold value before it is determined as 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, but the collision time calculated in the subsequent frames is greater than the threshold. If a forward collision warning is made based on the previous frame less than the threshold, it will cause false triggering. Therefore, in this application, it is required that the collision time of 100 consecutive frames is less than the threshold before the conclusion is considered 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 it 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 for forward collision warning.

[0069] Let's take a specific example to illustrate. In step S2, it can be considered that according to the set safety distance, there are 10 suspected targets with potential threats. Then, based on the processing of step S3, it is found that only 5 of them meet the collision time calculated for 100 consecutive frames that is less than the threshold. Then, these 5 suspected targets are marked. Then, combined with the current time, from these 5 marked suspected targets, a suspected target with a collision time closest to the current time is selected as the final target. Finally, a forward collision warning is performed 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 well screened and the most appropriate target can be accurately selected for forward collision warning.

[0071] It is worth noting that in some embodiments, the step S5 of adjusting the threshold to adapt to the driver's driving style is also included. 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, recording 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] In summary, 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 according to 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 calculated collision time 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] That is to say, the present application calculates the collision time under multiple frames of road environment characteristic images, and only issues a forward collision warning when the collision time calculated under a certain number of consecutive frames of road environment characteristic images is less than a set threshold. That is, the present application is a comprehensive consideration made after comprehensive calculation of multiple frames of images, so as to avoid false triggering caused by perception errors in the prior art.

[0076] In addition, the present application also adjusts the threshold of the collision warning according to 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 a vehicle forward collision warning device of the present 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 obstacles.

[0080] The calculation module determines a suspected target with potential threat according to 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, and when the calculated collision time 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 also used for:

[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] According to the position of the suspected target, determine the forward collision distance between the center of mass of the vehicle and the suspected target;

[0087] According to the speed of the suspected target, determine the relative speed between the vehicle and 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 used for:

[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] Among them, k is the safety factor set according to road conditions and weather conditions, t is the average reaction time of the driver, 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 used for:

[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 used for:

[0098] Color-coded labels are added to each frame of the road environment feature image 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 its functions and implementation processes are no longer repeated here one by one.

[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 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, the memory, and the communication interface.

[0103] The communication interface includes input / output (I / O) interfaces, physical interfaces, and logical interfaces for interconnecting the components inside the vehicle forward collision warning device, and interfaces for interconnecting the vehicle forward collision warning device with other devices (such as other computing devices or user devices). The physical interface can be an Ethernet interface, a fiber optic interface, an ATM interface, etc.; the user device can be a display, a keyboard, 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, and the general-purpose processor may call the vehicle forward collision warning program stored in the memory and execute the vehicle forward collision warning method provided by the embodiment 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 may refer to 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 on the present application, and may include more or less components than shown in the figure, or combine certain components, or arrange the components differently.

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

[0108] A vehicle forward collision warning program is stored on the readable storage medium of the present application, 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 only for description 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 a necessary general hardware platform, and of course by hardware, but in many cases the former is a better implementation method. Based on such an understanding, the technical solution of the present application is essentially 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, disk, CD) as described above, and includes a number of instructions for 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 "first", "second" and "third" to different types.

[0113] In the description of the embodiments of the present application, "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 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", "for example" or "for example" is intended to present related concepts in a specific way.

[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; the “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 that appear in a specific order are included, but it should be understood that these operations or steps may not be executed in the order in which they appear in the embodiments of the present application or in parallel, and the sequence number of the operation is only used to distinguish the different operations, and the sequence number itself does not represent any execution order. In addition, these processes may include more or fewer operations, and these operations or steps may be executed 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 are not intended to 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 are not intended to 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 the road environment feature image 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 step of calculating the collision time corresponding to each frame of the road environment feature image based on the position and speed of the suspected target includes: According to the position of the suspected target, determine the forward collision distance between the center of mass of the vehicle and the suspected target; According to the speed of the suspected target, determine the relative speed between the vehicle and 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, characterized in that: 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, characterized in that: According to the formula: d = k*(t*v+b), determine the safety distance d; Among them, k is the safety factor set according to road conditions and weather conditions, t is the average reaction time of the driver, 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, characterized in that: 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, characterized in that: Also includes: Color-coded labels are added to each frame of the road environment feature image 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, and marks the suspected target and the corresponding collision time 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 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 as described in 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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