Early warning method for rear unmanned vehicle

Abstract

The invention discloses an early warning method for a rear unmanned vehicle, relates to the technical field of driving early warning, and solves the technical problem that timely and accurate early warning cannot be provided due to lack of effective monitoring means for unique driving characteristics and state changes of the rear unmanned vehicle. According to the method, various road condition factors such as the road surface friction coefficient, the flatness, the gradient and the damage condition are comprehensively considered, the safety coefficient is obtained through standardization processing and weight calculation, the safety distance is determined in combination with the real-time speed difference, and the safety distance is determined by means of a high-precision sensor such as a gyroscope or an electronic compass. The angle deflection condition of a rear unmanned vehicle is monitored according to a set time period, whether angle change exists or not is judged according to an allowable range set by an operator, dangerous behaviors such as vehicle lane changing are found in time, timely early warning is provided for a driver, and the driving safety is improved. The speed change, angle deflection and other information of the rear unmanned vehicle are comprehensively analyzed, and a targeted early warning signal is generated.

Description

Technical Field

[0001] The present invention relates to the technical field of driving warning, and particularly to a warning method for a rear unmanned vehicle. Background Art

[0002] With the continuous development and application of unmanned driving technology, the number of unmanned vehicles on the road has gradually increased. During vehicle driving, accurately perceiving the state of the rear vehicle, especially the state of the rear unmanned vehicle, is crucial for ensuring traffic safety.

[0003] According to the patent application with the publication number CN111746526B, a warning method, device, equipment and vehicle for a rear unmanned vehicle are disclosed. The method includes: obtaining the rear road image information of the current vehicle, identifying the rear vehicle according to the rear road image information to obtain the rear vehicle image information, determining whether the rear vehicle is a rear unmanned vehicle according to the rear vehicle image information, when determining that the rear vehicle is a rear unmanned vehicle, increasing the collision warning distance between the current vehicle and the rear unmanned vehicle, and reducing the collision warning speed difference between the current vehicle and the rear unmanned vehicle, and warning of the collision between the current vehicle and the rear unmanned vehicle based on the increased collision warning distance and the reduced collision warning speed difference.

[0004] However, traditional vehicle warning methods mainly focus on the interaction between manned vehicles. When facing unmanned vehicles, there is a lack of effective monitoring means for their unique driving characteristics and state changes. Existing monitoring methods often cannot accurately identify whether the rear vehicle is unmanned, it is difficult to comprehensively obtain key information such as the speed change and angle deflection of unmanned vehicles, and there are deficiencies in determining the safety distance in combination with complex road conditions, and it is impossible to provide timely and accurate warnings for drivers or autonomous driving systems, making it difficult to meet the growing traffic safety requirements. Summary of the Invention

[0005] Aiming at the deficiencies of the prior art, the present invention provides a warning method for a rear unmanned vehicle, which solves the problems of lack of effective monitoring means for its unique driving characteristics and state changes and inability to provide timely and accurate warnings.

[0006] To achieve the above object, the present invention is realized through the following technical solutions: A warning method for a rear unmanned vehicle, the method includes the following steps:

[0007] Obtain the rear road video information of the current vehicle through a streaming media camera, and identify the driving situation of the rear vehicle to generate a signal of unmanned or manned driving;

[0008] For the analysis of manned driving signals, based on the vehicle image of the vehicle behind, obtain the corresponding vehicle speed and vehicle distance, and calculate the speed difference between the current vehicle and the vehicle behind, which is denoted as the real-time speed difference;

[0009] And calculate the safety factor according to the safety factor formula. At the same time, combine the formula Dc = S × Vc to calculate the safety distance, where S is the safety factor and Vc is the real-time speed difference. Compare the vehicle distance with the safety distance to generate real-time monitoring information or distance warning information;

[0010] For the analysis of unmanned driving signals, based on the vehicle image of the vehicle behind, judge the change of its vehicle speed and generate a signal indicating that the vehicle speed changes or remains unchanged. For the signal indicating that the vehicle speed remains unchanged, calculate the safety distance according to the formula and compare it with the vehicle distance to generate real-time monitoring information or distance warning information;

[0011] Analyze the signal indicating the change of vehicle speed, identify and analyze the angle parameter of the vehicle behind to generate a signal indicating that the angle deflects or remains unchanged. At the same time, analyze the signal indicating that the angle remains unchanged, calculate the braking distance of the vehicle behind, and obtain the vehicle speed change value of the vehicle behind;

[0012] Based on the above two, calculate the safety distance according to the formula P0 = [P1+(V1×t1)]×S, where t1 is the reaction time and V1 is the vehicle speed change value. Compare the safety distance with the vehicle distance to generate real-time monitoring information or distance warning information.

[0013] As a further solution of the present invention, the specific method for generating manned or unmanned driving signals is as follows:

[0014] Obtain the rear road video information of the current vehicle through a streaming media camera. Based on an image recognition algorithm, obtain the vehicle image of the vehicle behind, and perform feature extraction on the segmented image based on a preset convolutional network;

[0015] At the same time, identify the obtained features to judge whether there is a driver in the vehicle behind. If there is a person, generate a manned driving signal. Otherwise, if there is no person, generate an unmanned driving signal.

[0016] As a further solution of the present invention, the specific method for calculating the safety factor according to the safety factor formula is as follows:

[0017] Obtain the current road conditions, and calculate the safety factor S corresponding to the current road surface according to the formula S = ω1×F + ω2×I + ω3×G + ω4×D, where F is the standardized value of the road surface friction coefficient, f is the actual friction coefficient, f min and f max are the possible minimum and maximum coefficients respectively, and I is the standardization of the road surface flatness.

[0018] As a further solution of the present invention, the specific method for comparing the vehicle distance with the safety distance to generate real-time monitoring information or distance warning information is as follows:

[0019] Based on the vehicle image, obtain the vehicle speed and the corresponding vehicle distance of the vehicle behind, and at the same time obtain the real-time vehicle speed of the current vehicle, and calculate the speed difference between the two and record it as the real-time speed difference. Calculate the safety distance Dc according to the formula Dc = S × Vc, where Vc is the real-time speed difference;

[0020] And compare the vehicle distance Ds with the safety distance Dc. If the vehicle distance Ds is greater than the safety distance Dc, generate real-time monitoring information. On the contrary, if the vehicle distance Ds is less than the safety distance Dc, generate distance warning information.

[0021] As a further solution of the present invention, the specific method for analyzing the driverless signal to generate a vehicle speed change or unchanged signal is as follows:

[0022] Using advanced image recognition and motion analysis technologies, accurately process the high-definition image of the vehicle behind, compare the position changes of the vehicle in consecutive multiple frames of images, and calculate the displacement of the driverless vehicle behind within a unit time to obtain the corresponding vehicle speed;

[0023] Set a time window, compare the speed calculated within the current time window with the speed of the previous time window. If the speed difference between the two is within the preset error range, generate a vehicle speed unchanged signal. Otherwise, generate a vehicle speed change signal.

[0024] As a further solution of the present invention, the specific method for calculating the safety distance according to the formula based on the vehicle speed unchanged signal and generating real-time monitoring information or distance warning information is as follows:

[0025] Obtain the real-time vehicle speed of the vehicle behind and the real-time vehicle speed corresponding to the current vehicle, calculate the difference between the two real-time vehicle speeds, record it as the speed difference, and obtain the safety factor k. Then, according to the formula D = k × V 差 Calculate the safety distance;

[0026] Compare the obtained safety distance with the vehicle distance between the two. If the safety distance is greater than the vehicle distance, generate real-time monitoring information. On the contrary, if the safety distance is less than the vehicle distance, generate distance warning information.

[0027] As a further solution of the present invention, the specific method for analyzing the vehicle speed change signal is as follows:

[0028] Taking the time t as a period, judge the speed change of the vehicle behind, generate an increasing change signal or real-time monitoring information, analyze the increasing change signal, take the time t as a period, obtain the angle deflection situation of the vehicle behind. If the angle deflection is within the allowable range within the time t, generate an angle unchanged signal, otherwise generate an angle deflection signal, and for the generated angle deflection signal, generate real-time monitoring information.

[0029] As a further solution of the present invention, the specific method for comparing the safety distance with the vehicle distance to generate real-time monitoring information or distance warning information is as follows:

[0030] Then analyze the generated angle unchanged signal, obtain the vehicle speed of the vehicle behind and the corresponding vehicle speed change value, and according to the formula Calculate the braking distance P1 corresponding to the vehicle behind, where v0 is the initial vehicle speed and a is the braking deceleration. At the same time, based on the vehicle speed change value, perform comprehensive calculations, and calculate the safety distance P0 between the vehicle behind and the current vehicle according to the formula P0 = [P1+(V1×t1)]×S, where t1 is the reaction time and V1 is the vehicle speed change value;

[0031] Compare the obtained safety distance P0 with the vehicle distance between the current vehicle and the vehicle behind. If the safety distance is greater than the vehicle distance, generate a distance warning information, otherwise generate real-time monitoring information.

[0032] The present invention provides a warning method for a rear unmanned vehicle. Compared with the prior art, it has the following beneficial effects:

[0033] By relying on image recognition and motion analysis technologies, the present invention uses optical flow algorithms to accurately calculate the speed of the rear unmanned vehicle, and by setting a time window to compare the speed difference, it can timely and accurately judge the speed change situation, generate corresponding signals, provide detailed vehicle speed dynamic information for the driver, and facilitate early response.

[0034] Considering various road condition factors such as road surface friction coefficient, flatness, slope, and damage situation, through standardization processing and weight calculation, obtain the safety coefficient, and then combine the real-time speed difference to determine the safety distance. Compared with the prior art, the calculation of the safety distance is more scientific and accurate, can better adapt to complex and changeable road conditions, and effectively reduce the accident risk.

[0035] With the help of high-precision sensors such as gyroscopes or electronic compasses, monitor the angle deflection situation of the rear unmanned vehicle at a set time period, judge whether there is an angle change according to the allowable range set by the operator, timely detect dangerous behaviors such as vehicle lane change, provide timely warnings for the driver, and improve driving safety.

[0036] Comprehensively analyze information such as the speed change and angle deflection of the rear driverless vehicle, generate targeted warning signals, such as increased change signals, angle deflection signals, etc., and further determine whether to generate distance warning information in combination with the safety distance calculation result. Compared with the prior art, the warning is more comprehensive, timely, and accurate, providing a more reliable guarantee for road traffic safety. Brief Description of the Drawings

[0037] Figure 1 It is a flowchart of the method steps of the present invention. Detailed Embodiment

[0038] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0039] Please refer to Figure 1 , the present application provides a warning method for a rear driverless vehicle, and the method specifically includes the following steps:

[0040] Step1. Obtain the rear road video information of the current vehicle through a streaming camera. Specifically, a streaming camera with high resolution (such as 8 million pixels) and ultra-wide angle (150° - 180° viewing angle) is used to continuously and stably obtain the rear road video information of the current vehicle at a frame rate of 30 frames per second or more.

[0041] Step2. Identify the driverless vehicles on the rear road according to the obtained rear road video information, and the specific identification method is:

[0042] Based on the image recognition algorithm, obtain the vehicle image of the rear vehicle, then perform segmentation processing on the obtained vehicle image to obtain a segmented image, and perform feature extraction on the segmented image based on a preset convolutional network. Specifically, the convolutional network structure is carefully designed and optimized. Through the coordinated operation of multiple convolutional layers, pooling layers, and fully connected layers, it can effectively capture key visual features in the driver's seat area, such as distinguishable feature information such as human body contours, head positions, and hand movements. At the same time, the obtained features are identified to determine whether there is a driver in the rear vehicle. If there is a person, a manned driving signal is generated; otherwise, if there is no person, an unmanned driving signal is generated. Specifically, the features here are extracted from the driver's seat area of the rear vehicle.

[0043] Step 3. Analyze the obtained manned driving signal, obtain the vehicle image of the vehicle behind, and based on the vehicle image, obtain the vehicle speed and the corresponding vehicle distance of the vehicle behind. At the same time, obtain the real-time vehicle speed of the current vehicle, and calculate the speed difference between the two and record it as the real-time speed difference. Then, obtain the current road condition, and determine the safety distance in combination with the real-time speed difference;

[0044] Calculate the safety factor S corresponding to the current road surface according to the formula S = ω1×F + ω2×I + ω3×G + ω4×D, and the value range is from 0 to 1, where F is the standardized value of the road surface friction coefficient, and the actual friction coefficient is standardized through the formula , f is the actual friction coefficient, f min and f max are the possible minimum and maximum coefficients respectively. I is the standardization of the road surface flatness. For example, on a dry asphalt road surface, f min is about 0.6, f max is about 0.8; while on an icy road surface, f min may be as low as 0.1, f max is about 0.3,

[0045] Through the formula When IRI is greater than 2.5, I is a negative number, indicating the negative impact of poor flatness on safety. IRI represents the international roughness index. G is the standardized value of the road surface slope. For a low slope, G = 1, for a medium slope, G = 0.8, for a high slope, G = 0.6. D is the standardized value of the road surface damage condition. When the damage area ratio is less than 5%, D = 1. When it is between 5% - 15%, D = 0.8. When it is greater than 15%, D = 0.6. ω1, ω2, ω3 and ω4 are the weight coefficients corresponding to each factor, and ω1 + ω2 + ω3 + ω4 = 1. Generally, ω1 = 0.4, ω2 = 0.3, ω3 = 0.2, ω4 = 0.1;

[0046] Calculate the corresponding safety distance by combining the safety factor S and the real-time speed difference. Calculate the safety distance Dc according to the formula Dc = S×Vc, where Vc is the real-time speed difference, and compare the vehicle distance Ds with the safety distance Dc. If the vehicle distance Ds is greater than the safety distance Dc, it means that the distance between the vehicle behind and the current vehicle is safe, and generate real-time monitoring information. Otherwise, if the vehicle distance Ds is less than the safety distance Dc, it means that the distance between the vehicle behind and the current vehicle is unsafe, and generate a distance warning information;

[0047] For example, at a certain moment, it is calculated that the safety factor S of the current road section is 0.6, and the real-time speed difference Vc is 20 km / h. Then the safety distance calculated according to the formula is 12 m. At the same time, through radar measurement, the vehicle distance is 10 m. After comparing the two, 10 m is less than 12 m. In such a case, a distance warning information will be generated.

[0048] Step 4. Analyze the obtained driverless signals. Based on the vehicle images of the following vehicle, obtain the vehicle speed corresponding to the following vehicle, and obtain and judge the change situation of the vehicle speed. Specifically, first, relying on advanced image recognition and motion analysis technologies, accurately process the previously obtained high-definition images of the following vehicle. By comparing the position changes of the vehicle in multiple consecutive frames of images and using mature technologies such as the optical flow algorithm, accurately calculate the displacement of the following driverless vehicle per unit time, and then convert it to obtain the corresponding vehicle speed;

[0049] After obtaining the vehicle speed, the system continuously monitors the change situation of the vehicle speed. By setting a short time window (for example, every 0.5 seconds), compare the speed calculated within the current time window with the speed of the previous time window. If the speed difference between the two is within the preset error range (such as ±1 km / h, and this error range can be adjusted according to the actual application scenario and accuracy requirements), the system determines that the vehicle speed remains stable and immediately generates a vehicle speed unchanged signal; if the speed difference exceeds the preset error range, a vehicle speed change signal is generated, and at the same time, the generated vehicle speed unchanged signal is analyzed;

[0050] Obtain the real-time vehicle speed of the following vehicle, and at the same time obtain the real-time vehicle speed corresponding to the current vehicle, calculate the difference between the two real-time vehicle speeds, denoted as the speed difference, and calculate the safety factor k corresponding to the current road surface according to the formula. And the method of calculating the safety factor here is the same as that in Step 3. Then, according to the formula D = k × V 差 Calculate the safety distance, and at the same time compare the obtained safety distance with the vehicle distance between the two. If the safety distance is greater than the vehicle distance, generate real-time monitoring information; conversely, if the safety distance is less than the vehicle distance, generate a distance warning information;

[0051] Analyze the generated vehicle speed change signal. Taking time t as the period, obtain the specific vehicle speed change of the following vehicle. If the vehicle speed is increasing, generate an increasing change signal; conversely, if the vehicle speed is decreasing, generate real-time monitoring information. Specifically, for the situation where the vehicle speed of the following vehicle decreases, it means that the distance from the current vehicle increases with time, which also means that the safety distance between the two is getting larger and no corresponding distance warning information will be generated.

[0052] Step 5. Process the generated increasing change signal, obtain the angle parameter of the vehicle behind based on the vehicle image of the vehicle behind, and continuously monitor the angle deflection of the vehicle behind with the help of high-precision sensors equipped on the vehicle, such as gyroscopes or electronic compasses, etc., and analyze the obtained angle parameter to generate an angle deflection signal or an angle unchanged signal. The specific analysis method is as follows: taking time t as a cycle, and the value of time t here is the same as the value of time t in Step 4, obtain the angle deflection situation of the vehicle behind. If the angle deflection is within the allowable range within time t, it means that there is no angle change in the vehicle behind, and an angle unchanged signal is generated. On the contrary, if the angle deflection is not within the allowable range within time t, it means that there is an angle change in the vehicle behind, and an angle deflection signal is generated. For the generated angle deflection signal, real-time monitoring information is generated. Here, the angle deflection indicates that the vehicle behind has a lane-changing behavior, and the specific value of the allowable range is set by the operator.

[0053] For example, set the time period t = 5 seconds, and the operator sets the angle allowable range to -5° to +5°. Vehicle A continuously monitors the angle deflection of vehicle B behind through sensors. Within a certain 5-second time period, the angle deflection value of vehicle B always fluctuates between -3° and +2°. The system determines that there is no angle change in vehicle B and generates an angle unchanged signal, and the driver of vehicle A can continue to drive normally. However, in the next 5-second time period, the angle deflection value of vehicle B instantly reaches +8°, exceeding the allowable range, and the system immediately generates an angle deflection signal.

[0054] Then analyze the generated angle unchanged signal, obtain the vehicle speed of the vehicle behind and the corresponding vehicle speed change value, and according to the formula calculate the braking distance P1 corresponding to the vehicle behind, where v0 is the initial vehicle speed and a is the braking deceleration. Generally, for a small car on a dry road surface, the braking deceleration is 5 - 7m / s 2 , and on a wet and slippery road surface, it is 2 - 4m / s 2 . At the same time, when calculating in this application, take the value 6 for calculation for the dry road surface and take the value 3 for calculation for the wet and slippery road surface. At the same time, based on the vehicle speed change value, perform comprehensive calculation. According to the formula P0 = [P1+(V1×t1)]×S, calculate the safety distance P0 between the vehicle behind and the current vehicle, where t1 is the reaction time, V1 is the vehicle speed change value, generally taking a value of 0.5 - 1 second, taking a value of 0.8 in this application, and S is the safety factor, obtained from the calculation in Step 3, and the specific value is set by the operator;

[0055] For example, on a highway, if a vehicle behind accelerates from 100 km / h to 120 km / h, the corresponding vehicle speed change value V1 is 20 km / h (further converted to 5.6 m / s), and the braking deceleration of the vehicle when driving on a dry road surface is 6 m / s 2 , the braking distance is calculated to be 92.4 meters according to the calculation formula. The reaction time t1 is taken as 0.8 seconds, where the safety factor S is taken as 1.5, and substituting into the formula, the safety distance is calculated to be 138.6 meters.

[0056] Compare the obtained safety distance P0 with the vehicle distance between the current vehicle and the vehicle behind. If the safety distance is greater than the vehicle distance, it means there is a danger between the two, and a distance warning message is generated. On the contrary, if the safety distance is less than the vehicle distance, it means there is no danger between the two, and a real-time monitoring message is generated.

[0057] Some of the data in the above formula are taken for numerical calculation without substituting parameter units, and the content not described in detail in this specification belongs to the prior art well-known to those skilled in the art.

[0058] The above embodiments are only used to illustrate the technical method of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those of ordinary skill in the art should understand that the technical method of the present invention can be modified or equivalently replaced without departing from the spirit and scope of the technical method of the present invention.

Claims

1. A warning method for a rear driverless vehicle, characterized in that, The method includes the following steps: Obtain the rear road video information of the current vehicle through a streaming camera, identify the driving situation of the rear vehicle, and generate a driverless or manned driving signal; Analyze the manned driving signal, obtain the corresponding vehicle speed and vehicle spacing based on the vehicle image of the rear vehicle, and calculate the speed difference between the current vehicle and the rear vehicle, which is recorded as the real-time speed difference; Calculate the safety factor according to the safety factor formula, and at the same time calculate the safety distance in combination with the formula Dc = S×Vc, where S is the safety factor and Vc is the real-time speed difference. Compare the vehicle spacing with the safety distance to generate real-time monitoring information or distance warning information; Analyze the driverless signal, judge the change of the vehicle speed of the rear vehicle based on the vehicle image of the rear vehicle, and generate a vehicle speed change or unchanged signal. Calculate the safety distance according to the formula for the unchanged vehicle speed signal, and compare it with the vehicle spacing to generate real-time monitoring information or distance warning information; Analyze the vehicle speed change signal, identify and analyze the angle parameter of the rear vehicle to generate an angle deflection or unchanged signal. At the same time, analyze the unchanged angle signal, calculate the braking distance of the rear vehicle, and obtain the vehicle speed change value of the rear vehicle; Comprehensively calculate the safety distance according to the formula P0 = [P1+(V1×t1)]×S, where t1 is the reaction time and V1 is the vehicle speed change value. Compare the safety distance with the vehicle spacing to generate real-time monitoring information or distance warning information.

2. The early warning method for a rear driverless vehicle according to claim 1, wherein, The specific method for generating the driverless or manned driving signal is as follows: Obtain the rear road video information of the current vehicle through a streaming camera, obtain the vehicle image of the rear vehicle based on the image recognition algorithm, and perform feature extraction on the segmented image based on the preset convolutional network; At the same time, identify the obtained features to judge whether there is a driver in the rear vehicle. If there is a person, generate a manned driving signal, otherwise, if there is no person, generate a driverless signal.

3. The early warning method for a rear driverless vehicle according to claim 1, wherein The specific method for calculating the safety factor according to the safety factor formula is as follows: Obtain the current road conditions, and calculate the safety factor S corresponding to the current road surface according to the formula S = ω1×F + ω2×I + ω3×G + ω4×D, where F is the standardized value of the road surface friction coefficient, f is the actual friction coefficient, f min and f max are the possible minimum and maximum coefficients respectively, and I is the standardization of the road surface flatness.

4. The warning method for a rear driverless vehicle according to claim 1, wherein The specific method for comparing the vehicle spacing with the safety distance to generate real-time monitoring information or distance warning information is as follows: Obtain the corresponding vehicle speed and vehicle spacing of the rear vehicle based on the vehicle image, and at the same time obtain the real-time vehicle speed of the current vehicle, and calculate the speed difference between the two, which is recorded as the real-time speed difference. Calculate the safety distance Dc according to the formula Dc = S×Vc, where Vc is the real-time speed difference; Compare the vehicle spacing Ds with the safety distance Dc. If the vehicle spacing Ds is greater than the safety distance Dc, generate real-time monitoring information. Otherwise, if the vehicle spacing Ds is less than the safety distance Dc, generate distance warning information.

5. The warning method for a rear driverless vehicle according to claim 1, characterized in that, The specific method for analyzing the driverless signal to generate a vehicle speed change or unchanged signal is as follows: Use advanced image recognition and motion analysis technology to accurately process the high-definition image of the rear vehicle, compare the position changes of the vehicle in multiple consecutive frames of images, and calculate the displacement of the rear driverless vehicle within a unit time to obtain the corresponding vehicle speed; Set a time window, compare the speed calculated within the current time window with the speed of the previous time window. If the speed difference between the two is within the preset error range, generate a vehicle speed unchanged signal, otherwise generate a vehicle speed change signal.

6. The early warning method for a rear unmanned vehicle according to claim 1, characterized in that, The specific method for calculating the safe distance according to the formula for the constant vehicle speed signal and generating real-time monitoring information or distance warning information is as follows: Obtain the real-time vehicle speed of the vehicle behind and the real-time vehicle speed corresponding to the current vehicle, calculate the difference between the two real-time vehicle speeds, denoted as the speed difference, and obtain the safety factor k. Then, according to the formula D = k×V 差 Calculate the safety distance; Compare the obtained safe distance with the vehicle distance between the two. If the safe distance is greater than the vehicle distance, generate real-time monitoring information; otherwise, if the safe distance is less than the vehicle distance, generate distance warning information.

7. A warning method for a rear driverless vehicle according to claim 1, characterized in that, The specific method for analyzing the vehicle speed change signal is as follows: Taking time t as a period, judge the vehicle speed change situation of the vehicle behind, generate an increasing change signal or real-time monitoring information, analyze the increasing change signal, take time t as a period, obtain the angle deflection situation of the vehicle behind. If the angle deflection is within the allowable range within time t, generate an angle unchanged signal; otherwise, generate an angle deflection signal, and for the generated angle deflection signal, generate real-time monitoring information.

8. The warning method for a rear driverless vehicle according to claim 1, characterized in that, The specific method for comparing the safe distance with the vehicle spacing to generate real-time monitoring information or distance warning information is as follows: Next, analyze the generated angle-invariant signal to obtain the vehicle speed of the vehicle behind and the corresponding vehicle speed change value, and according to the formula calculate the braking distance P1 corresponding to the vehicle behind, where v0 is the initial vehicle speed and a is the braking deceleration. At the same time, perform comprehensive calculations based on the vehicle speed change value, and calculate the safety distance P0 between the vehicle behind and the current vehicle according to the formula P0 = [P1+(V1×t1)]×S, where t1 is the reaction time and V1 is the vehicle speed change value; Compare the obtained safe distance P0 with the vehicle spacing between the current vehicle and the vehicle behind. If the safe distance is greater than the vehicle spacing, generate distance warning information; otherwise, generate real-time monitoring information.

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