A dynamic warning system for vehicle braking distance based on traffic networking

Abstract

The present invention belongs to the technical field of vehicle collision avoidance, and specifically relates to a dynamic warning system for braking distance of a vehicle in a traffic network, comprising: the present invention is based on analyzing parameters of the surrounding environment during vehicle travel, monitoring surrounding vehicles, analyzing and processing the distance between the vehicle and a target vehicle and the real-time speed of the vehicle and the target vehicle, predicting possible dangers, and dynamically predicting and alarming dangerous vehicles, thereby improving the safety performance of the vehicle and greatly reducing the probability of accidents occurring during vehicle travel; being beneficial to protecting the safety of the vehicle and the people on board in dangerous situations, and staged processing being beneficial to reducing traffic accidents caused by misjudgment; being of great help in discovering and responding to dangers during vehicle travel, thereby improving the safety of the vehicle during travel.

Description

Technical Field

[0001] The invention belongs to the technical field of vehicle anti-collision, and in particular to a vehicle braking distance dynamic warning system for traffic networking. Background Art

[0002] Internet of Things technology is widely used in the collection and transmission of vehicle data. The vehicle braking distance dynamic warning system based on traffic networking is an important application of vehicle collision avoidance technology. It monitors and analyzes vehicle driving data in real time, predicts potential collision risks, and issues warnings to drivers, thereby effectively reducing the occurrence of traffic accidents.

[0003] A Chinese patent application with publication number CN115123284B discloses a dynamic warning system for vehicle braking distance, which is actually a vehicle collision avoidance system. The system includes: a data acquisition module for collecting data such as vehicle speed, distance between the vehicle and the preceding vehicle, brake pedal depth, brake pad temperature, and braking time sequence; a data processing module for analyzing the data collected by the data acquisition module to match the vehicle; and a vehicle warning module for warning the driver using the braking distance of the two vehicles in the vehicle matching pair and the distance between the vehicle and the preceding vehicle.

[0004] In the prior art, there are deficiencies in allowing the driver enough time to react during normal driving of the vehicle, analyzing potential collision risks, monitoring the vehicle ahead, predicting the distance between the vehicle and the target vehicle and the real-time speed of the vehicle and the target vehicle to predict the possible dangers, dynamically predicting and alarming dangerous vehicles, and predicting the time when potential collision risks will occur.

[0005] To this end, the present invention provides a vehicle braking distance dynamic warning system based on traffic networking. Summary of the invention

[0006] In order to make up for the deficiencies of the prior art, at least one technical problem raised in the background technology is solved.

[0007] The technical solution adopted by the present invention to solve the technical problem is: a vehicle braking distance dynamic warning system based on traffic networking, comprising:

[0008] Parameter acquisition module: During the monitoring period and while the vehicle is driving, the real-time distance between the vehicle and the vehicle in front and the vehicle's driving speed are obtained; the corresponding standard vehicle speed is obtained according to the vehicle's driving speed, and then the standard vehicle distance corresponding to the standard vehicle speed is obtained; the obtained data is analyzed and processed to obtain the warning level value;

[0009] Parameter analysis module: compares the obtained warning level value with the preset warning level threshold to determine whether it is necessary to send a warning signal to the car owner;

[0010] State parameter acquisition module: Based on the braking warning signal, a vehicle distance change curve is constructed according to the real-time vehicle distance between the vehicle and the vehicle in front during the out-of-bounds time period, and the change type of the real-time vehicle distance is judged based on the vehicle distance change curve, wherein the change types include linear continuous change and nonlinear continuous change, and the predicted target reaching time is obtained according to the change type of the real-time vehicle distance.

[0011] As a further technical solution of the present invention, the method for obtaining the warning level value is:

[0012] The time deviation ratio TP, speed deviation ratio VP and vehicle distance deviation ratio LP are processed to calculate the warning degree value YJ.

[0013] As a further technical solution of the present invention, the time deviation ratio TP is obtained in the following manner:

[0014] In the detection cycle, the duration of generating the analysis signal is obtained and summed, and marked as the out-of-bounds time period;

[0015] The time deviation ratio is obtained by ratioing the out-of-bounds time period with the total duration of the monitoring period, and is marked as TP.

[0016] As a further technical solution of the present invention, the speed deviation ratio VP is obtained in the following manner:

[0017] The speeds of the vehicles traveling during the out-of-bounds time period are obtained, summed and averaged, the average obtained is subjected to difference processing with the standard vehicle speed, and the difference obtained is subjected to ratio processing with the standard vehicle speed to obtain a speed deviation ratio, which is marked as VP.

[0018] As a further technical solution of the present invention, the vehicle distance deviation ratio LP is obtained in the following manner:

[0019] The real-time distance between the vehicle and the vehicle in front during the out-of-bounds time period is obtained, and the sum and average are calculated. The average is subtracted from the standard distance, and the difference is then compared with the standard distance to obtain the distance deviation ratio, which is marked as LP.

[0020] As a further technical solution of the present invention, the process of judging whether to send a brake warning signal according to the comparison result is as follows:

[0021] Specifically, the warning level value is compared with the preset warning level threshold, and the comparison process is:

[0022] If the warning level value is greater than or equal to the preset warning level threshold, a brake warning signal is generated;

[0023] If the warning level value is less than the preset warning level threshold, a normal signal is generated.

[0024] As a further technical solution of the present invention, the method for obtaining the predicted target reaching time is:

[0025] If the vehicle distance change type is linear continuous change, in the XY two-dimensional coordinate system where the vehicle distance change curve is located, the critical vehicle distance is marked on the Y axis as the reference value, and a straight line parallel to the X axis is drawn through the marked point and marked as the critical vehicle distance line;

[0026] Connect the two end points of the distance change curve with a straight line to obtain a linear reference line, extend the linear reference line to make it intersect with the critical distance line, obtain the time point corresponding to the intersection on the X-axis, which is the predicted compliance time point, perform difference processing on the predicted compliance time point and the time point corresponding to the end point of the distance change curve to obtain the predicted compliance time;

[0027] If the vehicle distance change type is nonlinear continuous change, the minimum slope value in the slope data group is obtained, wherein the minimum slope value is less than 0, the sub-curve corresponding to the minimum slope value is marked as the target sub-curve, the real-time vehicle distances corresponding to the two end points of the target sub-curve are obtained, and the real-time vehicle distances corresponding to the two end points of the target sub-curve are subjected to difference processing to obtain the real-time vehicle distance change value;

[0028] Based on the corresponding time points of the two end points of the target sub-curve on the X-axis, the change duration is obtained by subtraction;

[0029] The real-time vehicle distance change value is processed by ratio with the change duration to obtain the maximum vehicle distance change rate value;

[0030] Obtain the real-time vehicle distance corresponding to the end point of the vehicle distance change curve, and perform difference processing with the critical vehicle distance to obtain the allowable vehicle distance change value;

[0031] The allowable vehicle distance change value is ratioed with the maximum vehicle distance change rate value to obtain the predicted target reaching time.

[0032] As a further technical solution of the present invention, the vehicle distance change type is obtained in the following manner:

[0033] comparing the variance value of the slope value data set with a variance threshold;

[0034] If the variance value of the slope value data group is less than or equal to the variance threshold, it means that the vehicle distance change type is a linear continuous change;

[0035] If the variance value of the slope value data group is greater than the variance threshold, it indicates that the vehicle distance change type is a nonlinear continuous change.

[0036] As a further technical solution of the present invention, the variance value of the slope value data set is obtained by:

[0037] The vehicle distance change curve is divided into a plurality of sub-curves with equal horizontal lengths, the slope values ​​of the sub-curves are obtained, the slope values ​​of all the sub-curves are integrated into a slope value data group, and the variance value of the slope value data group is obtained.

[0038] As a further technical solution of the present invention, the vehicle distance change curve is obtained in the following manner:

[0039] With time as the X-axis and the real-time vehicle distance value as the Y-axis, an XY two-dimensional coordinate system is constructed. The real-time vehicle distance between the vehicle in the out-of-bounds period and the vehicle in front is marked and connected in the XY two-dimensional coordinate system to obtain the vehicle distance change curve.

[0040] The beneficial effects of the present invention are as follows:

[0041] 1. The technical solution of the embodiment of the present invention is: within the monitoring period and during the vehicle driving process, the real-time distance between the vehicle and the vehicle in front and the driving speed of the vehicle are obtained; the corresponding standard speed is obtained according to the driving speed of the vehicle, and then the standard distance corresponding to the standard speed is obtained; the obtained data is analyzed and processed to obtain a warning level value; the obtained warning level value is compared with a preset warning level threshold to determine whether it is necessary to send a warning signal to the vehicle owner; the present invention is based on analyzing the parameters of the surrounding environment during the vehicle driving process, monitoring the vehicle in front, predicting the possible dangers based on the distance between the vehicle and the target vehicle and the real-time speed of the vehicle and the target vehicle, and dynamically predicting and alarming dangerous vehicles, thereby improving the safety performance of the vehicle and greatly reducing the probability of accidents during vehicle driving.

[0042] 2. The technical solution of the embodiment of the present invention is: based on the braking warning signal, a vehicle distance change curve is constructed according to the real-time vehicle distance between the vehicle and the front vehicle in the overrun time period, and the change type of the real-time vehicle distance is judged based on the vehicle distance change curve, wherein the change type includes linear continuous change and nonlinear continuous change, and the predicted target time is obtained according to the change type of the real-time vehicle distance; the obtained predicted target time is compared with the predicted target time threshold, and an analysis signal is generated according to the comparison result; the present invention is based on the data processing and analysis of potential collision risks based on the parameters between the vehicle and the front vehicle in the overrun time period during normal driving of the vehicle, and can generate both a braking warning signal and a predicted target time, so that the driver has a clearer understanding of the current driving environment, provides certain assistance to the driver, reduces his driving pressure, and allows the driver to have enough time to react, avoid or reduce the occurrence of collision accidents, thereby protecting the safety of vehicle occupants, pedestrians and other road users. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] The present invention will be further described below in conjunction with the accompanying drawings.

[0044] Figure 1 It is a module diagram of a vehicle braking distance dynamic warning system based on traffic networking according to an embodiment of the present invention;

[0045] Figure 2 It is a flow chart of the steps of obtaining predicted target reaching time in a vehicle braking distance dynamic warning system based on traffic networking in an embodiment of the present invention. DETAILED DESCRIPTION

[0046] In order to make the technical means, creative features, objectives and effects achieved by the present invention easy to understand, the present invention is further explained below in conjunction with specific implementation methods.

[0047] Example 1

[0048] like Figure 1 - Figure 2 As shown, a vehicle braking distance dynamic warning system based on traffic networking according to an embodiment of the present invention includes:

[0049] Parameter acquisition module: During the monitoring period and while the vehicle is driving, the real-time distance between the vehicle and the vehicle in front and the vehicle's driving speed are obtained; the corresponding standard vehicle speed is obtained according to the vehicle's driving speed, and then the standard vehicle distance corresponding to the standard vehicle speed is obtained; the obtained data is analyzed and processed to obtain the warning level value;

[0050] Specifically, the real-time vehicle distance between the vehicle and the vehicle ahead is obtained, and when the real-time vehicle distance is less than or equal to the critical vehicle distance value, a braking warning signal is generated;

[0051] When the real-time vehicle distance is greater than the critical vehicle distance value and less than or equal to the standard vehicle distance value, an analysis signal is generated;

[0052] When the real-time vehicle distance is greater than the standard vehicle distance value, no special signal is generated;

[0053] It should be noted that when the real-time distance between the vehicle and the vehicle ahead is less than or equal to the critical distance value, a braking warning signal is generated and a braking prompt is issued to the driver;

[0054] In the detection cycle, the duration of generating the analysis signal is obtained and summed, and marked as the out-of-bounds time period;

[0055] The time period exceeding the limit is compared with the total duration of the monitoring period to obtain the time deviation ratio, which is marked as TP.

[0056] The speed of the vehicle during the over-boundary time period is obtained, summed and averaged, the average is subjected to difference processing with the standard vehicle speed, and the difference is subjected to ratio processing with the standard vehicle speed to obtain a speed deviation ratio, which is marked as VP;

[0057] The real-time distance between the vehicle and the vehicle ahead during the out-of-bounds time period is obtained, and the sum and average are calculated. The average is subtracted from the standard distance, and the difference is then compared with the standard distance to obtain the distance deviation ratio, which is marked as LP.

[0058] The time deviation ratio TP, speed deviation ratio VP and vehicle distance deviation ratio LP are processed and the formula is used. Get the warning level value YJ; where s1, s2, s3 are preset proportional coefficients;

[0059] It should be noted that the vehicle's braking warning distance is related to the vehicle's real-time speed. The greater the real-time speed, the longer the braking warning distance. The warning degree value is the criterion for judging whether a braking warning is needed. The greater the warning degree value, the higher the probability of a traffic accident between the vehicle and the vehicle ahead.

[0060] Parameter analysis module: compares the obtained warning level value with the preset warning level threshold to determine whether it is necessary to send a warning signal to the car owner;

[0061] Specifically, the warning level value is compared with the preset warning level threshold, and the comparison process is:

[0062] If the warning level value is greater than or equal to the preset warning level threshold, a brake warning signal is generated;

[0063] If the warning level value is less than the preset warning level threshold, a normal signal is generated;

[0064] The technical solution of the embodiment of the present invention is: within the monitoring period and during the vehicle driving process, the real-time distance between the vehicle and the vehicle in front and the driving speed of the vehicle are obtained; the corresponding standard speed is obtained according to the driving speed of the vehicle, and then the standard distance corresponding to the standard speed is obtained; the obtained data is analyzed and processed to obtain a warning level value; the obtained warning level value is compared with a preset warning level threshold to determine whether it is necessary to send a warning signal to the owner of the vehicle; the present invention is based on analyzing the parameters of the surrounding environment during the vehicle driving process, monitoring the vehicle in front, predicting the possible dangers based on the distance between the vehicle and the target vehicle and the real-time speed of the vehicle and the target vehicle, and dynamically predicting and alarming dangerous vehicles, thereby improving the safety performance of the vehicle and greatly reducing the probability of accidents during vehicle driving.

[0065] Example 2

[0066] like Figure 1 - Figure 2 As shown, based on Example 1, a vehicle braking distance dynamic warning system based on traffic networking according to an embodiment of the present invention includes:

[0067] State parameter acquisition module: Based on the braking warning signal, a distance change curve is constructed according to the real-time distance between the vehicle and the vehicle in front during the over-boundary time period, and the change type of the real-time distance is determined based on the distance change curve, wherein the change type includes linear continuous change and nonlinear continuous change, and the predicted target reaching time is obtained according to the change type of the real-time distance;

[0068] With time as the X-axis and the real-time vehicle distance as the Y-axis, an XY two-dimensional coordinate system is constructed, and the real-time vehicle distance between the vehicle in the over-boundary period and the vehicle in front is marked and connected in the XY two-dimensional coordinate system to obtain a vehicle distance change curve;

[0069] Divide the vehicle distance change curve into a number of sub-curves with equal horizontal lengths, obtain the slope values ​​of the sub-curves, integrate the slope values ​​of all the sub-curves into a slope value data group, and obtain the variance value of the slope value data group;

[0070] It should be noted that the smaller the variance value of the slope value data group, the smaller the discrete degree of all slopes, indicating that the distance change curve constructed based on the real-time distance between the vehicle and the vehicle in front is close to a straight line; the larger the slope variance value, the more it indicates that the distance change curve constructed based on the real-time distance between the vehicle and the vehicle in front is not close to a straight line;

[0071] comparing the variance value of the slope value data set with a variance threshold;

[0072] If the variance value of the slope value data group is less than or equal to the variance threshold, it means that the vehicle distance change type is a linear continuous change;

[0073] If the variance value of the slope value data group is greater than the variance threshold, it indicates that the vehicle distance change type is a nonlinear continuous change;

[0074] If the vehicle distance change type is linear continuous change, in the XY two-dimensional coordinate system where the vehicle distance change curve is located, the standard vehicle distance is marked on the Y axis as the reference value, and a straight line parallel to the X axis is drawn through the marked point and marked as the standard vehicle distance line;

[0075] At the same time, the two end points of the vehicle distance change curve are connected by straight lines to obtain a linear reference line, and the linear reference line is extended to intersect with the standard vehicle distance line, and the time point corresponding to the intersection on the X-axis is obtained, which is the predicted standard-reaching time point, and the predicted standard-reaching time point is differenced with the time point corresponding to the end point of the vehicle distance change curve to obtain the predicted standard-reaching time;

[0076] It should be noted that the predicted standard-reaching time refers to the predicted time when the real-time distance between the vehicle and the vehicle ahead reaches the standard distance;

[0077] If the vehicle distance change type is nonlinear continuous change, the minimum slope value in the slope data group is obtained, wherein the minimum slope value is less than 0, the sub-curve corresponding to the minimum slope value is marked as the target sub-curve, the real-time vehicle distances corresponding to the two end points of the target sub-curve are obtained, and the real-time vehicle distances corresponding to the two end points of the target sub-curve are subjected to difference processing to obtain the real-time vehicle distance change value;

[0078] Based on the corresponding time points of the two end points of the target sub-curve on the X-axis, the change duration is obtained by subtraction;

[0079] The real-time vehicle distance change value is processed by ratio with the change duration to obtain the maximum vehicle distance change rate value;

[0080] Obtain the real-time vehicle distance corresponding to the end point of the vehicle distance change curve, and perform difference processing with the standard vehicle distance to obtain the allowable vehicle distance change value;

[0081] The allowed vehicle distance change value is processed by ratio with the maximum vehicle distance change rate value to obtain the predicted target reaching time;

[0082] Send the acquired braking warning signal and predicted time to reach the target to the driver;

[0083] The technical solution of the embodiment of the present invention is: based on the braking warning signal, a vehicle distance change curve is constructed according to the real-time vehicle distance between the vehicle and the front vehicle in the over-boundary time period, and the change type of the real-time vehicle distance is judged based on the vehicle distance change curve, wherein the change type includes linear continuous change and nonlinear continuous change, and the predicted target time is obtained according to the change type of the real-time vehicle distance; the obtained predicted target time is compared with the predicted target time threshold, and an analysis signal is generated according to the comparison result; the present invention is based on the vehicle in the normal driving process, according to the parameters between the vehicle and the front vehicle in the over-boundary time period, data processing, analysis of potential collision risks, can generate both a braking warning signal and a predicted target time, so that the driver has a clearer understanding of the current driving environment, provides certain assistance to the driver, reduces his driving pressure, and allows the driver to have enough time to react, avoid or reduce the occurrence of collision accidents, thereby protecting the safety of vehicle occupants, pedestrians and other road users.

[0084] Example 3

[0085] A vehicle braking distance dynamic warning method based on traffic networking according to an embodiment of the present invention comprises the following steps:

[0086] Step 1: During the monitoring period and while the vehicle is traveling, obtain the real-time distance between the vehicle and the vehicle in front, and the vehicle's driving speed; obtain the corresponding standard vehicle speed according to the vehicle's driving speed, and then obtain the standard vehicle distance corresponding to the standard vehicle speed; analyze and process the obtained data to obtain the warning level value;

[0087] Step 2: Compare the obtained warning level value with the preset warning level threshold to determine whether it is necessary to send a warning signal to the vehicle owner;

[0088] Step 3: Based on the braking warning signal, a distance change curve is constructed according to the real-time distance between the vehicle and the vehicle in front during the over-boundary time period. The change type of the real-time distance is determined based on the distance change curve, where the change types include linear continuous change and nonlinear continuous change. The predicted target time is obtained according to the change type of the real-time distance.

[0089] The above shows and describes the basic principles, main features and advantages of the present invention. It should be understood by those skilled in the art that the present invention is not limited to the above embodiments. The above embodiments and descriptions are only for explaining the principles of the present invention. Without departing from the spirit and scope of the present invention, the present invention may have various changes and improvements, which fall within the scope of the present invention. The scope of protection of the present invention is defined by the attached claims and their equivalents.

Claims

1. A vehicle braking distance dynamic warning system based on traffic networking, characterized in that: include: Parameter acquisition module: during the monitoring period and while the vehicle is driving, obtain the real-time distance between the vehicle and the vehicle in front, and the driving speed of the vehicle; obtain the corresponding standard speed according to the driving speed of the vehicle, and then obtain the standard distance corresponding to the standard speed; Analyze and process the acquired data to obtain the warning level value; Parameter analysis module: compares the obtained warning level value with the preset warning level threshold to determine whether it is necessary to send a warning signal to the car owner; State parameter acquisition module: Based on the braking warning signal, a distance change curve is constructed according to the real-time distance between the vehicle and the vehicle in front during the over-boundary time period, and the change type of the real-time distance is determined based on the distance change curve, wherein the change type includes linear continuous change and nonlinear continuous change, and the predicted target reaching time is obtained according to the change type of the real-time distance; The method for obtaining the warning level value is as follows: The time deviation ratio TP, speed deviation ratio VP and vehicle distance deviation ratio LP are processed to calculate the warning level value YJ; The time deviation ratio TP is obtained as follows: In the detection cycle, the duration of generating the analysis signal is obtained and summed, and marked as the out-of-bounds time period; The time period exceeding the limit is compared with the total duration of the monitoring period to obtain the time deviation ratio, which is marked as TP. The method for obtaining the predicted target-reaching time is as follows: If the vehicle distance change type is linear continuous change, in the XY two-dimensional coordinate system where the vehicle distance change curve is located, the critical vehicle distance is marked on the Y axis as the reference value, and a straight line parallel to the X axis is drawn through the marked point and marked as the critical vehicle distance line; Connect the two end points of the distance change curve with a straight line to obtain a linear reference line, extend the linear reference line to make it intersect with the critical distance line, obtain the time point corresponding to the intersection on the X-axis, which is the predicted compliance time point, perform difference processing on the predicted compliance time point and the time point corresponding to the end point of the distance change curve to obtain the predicted compliance time; If the vehicle distance change type is nonlinear continuous change, the minimum slope value in the slope data group is obtained, wherein the minimum slope value is less than 0, the sub-curve corresponding to the minimum slope value is marked as the target sub-curve, the real-time vehicle distances corresponding to the two end points of the target sub-curve are obtained, and the real-time vehicle distances corresponding to the two end points of the target sub-curve are subjected to difference processing to obtain the real-time vehicle distance change value; Based on the corresponding time points of the two end points of the target sub-curve on the X-axis, the change duration is obtained by subtracting; The real-time vehicle distance change value is processed by ratio with the change duration to obtain the maximum vehicle distance change rate value; Obtain the real-time vehicle distance corresponding to the end point of the vehicle distance change curve, and perform difference processing with the critical vehicle distance to obtain the allowable vehicle distance change value; The allowable vehicle distance change value is ratioed with the maximum vehicle distance change rate value to obtain the predicted target reaching time.

2. The vehicle braking distance dynamic warning system based on traffic networking according to claim 1 is characterized by: The speed deviation ratio VP is obtained as follows: The speeds of the vehicles traveling during the out-of-bounds time period are obtained, summed and averaged, the average obtained is subjected to difference processing with the standard vehicle speed, and the difference obtained is subjected to ratio processing with the standard vehicle speed to obtain a speed deviation ratio, which is marked as VP.

3. The vehicle braking distance dynamic warning system based on traffic networking according to claim 1 is characterized by: The vehicle distance deviation ratio LP is obtained as follows: The real-time distance between the vehicle and the vehicle in front during the out-of-bounds time period is obtained, and the sum and average are calculated. The average is subtracted from the standard distance, and the difference is then compared with the standard distance to obtain the distance deviation ratio, which is marked as LP.

4. The vehicle braking distance dynamic warning system based on traffic networking according to claim 1 is characterized by: The process of judging whether to send a brake warning signal according to the comparison result is as follows: Specifically, the warning level value is compared with the preset warning level threshold, and the comparison process is: If the warning level value is greater than or equal to the preset warning level threshold, a brake warning signal is generated; If the warning level value is less than the preset warning level threshold, a normal signal is generated.

5. The vehicle braking distance dynamic warning system based on traffic networking according to claim 1 is characterized by: The method for obtaining the vehicle distance change type is as follows: comparing the variance value of the slope value data set with a variance threshold; If the variance value of the slope value data group is less than or equal to the variance threshold, it means that the vehicle distance change type is a linear continuous change; If the variance value of the slope value data group is greater than the variance threshold, it indicates that the vehicle distance change type is a nonlinear continuous change.

6. The vehicle braking distance dynamic warning system based on traffic networking according to claim 5 is characterized by: The variance value of the slope value data set is obtained as follows: The vehicle distance change curve is divided into a plurality of sub-curves with equal horizontal lengths, the slope values ​​of the sub-curves are obtained, the slope values ​​of all the sub-curves are integrated into a slope value data group, and the variance value of the slope value data group is obtained.

7. The vehicle braking distance dynamic warning system based on traffic networking according to claim 1 is characterized by: The vehicle distance variation curve is obtained in the following manner: With time as the X-axis and the real-time vehicle distance value as the Y-axis, an XY two-dimensional coordinate system is constructed. The real-time vehicle distance between the vehicle in the out-of-bounds period and the vehicle in front is marked and connected in the XY two-dimensional coordinate system to obtain the vehicle distance change curve.

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