A vehicle-to-pedestrian collision warning system and method based on an autonomous vehicle

Abstract

The application discloses a non-motor vehicle collision warning system and method based on an automatic driving vehicle, and belongs to the field of automatic driving.The warning system comprises a data acquisition module, a data processing module, a control center module, an information communication module and an information response module.The application can provide the driving environment of the automatic driving vehicle through a positioning detection system, so as to determine whether it is necessary to start the collision warning system, and when the collision risk level is calculated, only the non-motor vehicle in the minimum safety distance of the automatic driving vehicle is calculated, so that the waste of computing resources and unnecessary deceleration behavior of the automatic driving vehicle caused by irrelevant non-motor vehicles are effectively avoided.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of automatic driving, in particular to a machine-non-machine collision warning system and method based on an automatic driving vehicle. BACKGROUND

[0002] The closest conventional technology to the present application is: patent document CN116206285A discloses a traffic vulnerable group collision risk assessment method and system applied to automatic driving, comprising: identifying and obtaining traffic vulnerable group information around the vehicle, obtaining position and speed information of the vehicle itself, obtaining surrounding traffic environment information of the traffic vulnerable group; using the obtained traffic vulnerable group information to classify and identify the driving intention of the traffic vulnerable group; based on the historical multi-frame information of the traffic vulnerable group, combining the driving intention of the traffic vulnerable group, the driving trajectory of the traffic vulnerable group is predicted; according to the driving target, a candidate trajectory is generated, and the trajectory is detected with the predicted trajectory of the vulnerable group, the vulnerable group expands the influence boundary according to its driving intention, and the position and time of collision are calculated; the collision risk of the vulnerable group and the automatic driving vehicle is calculated.

[0003] (1) The method and system consider all detectable vulnerable groups when calculating the collision position and time of the vulnerable group and the automatic driving vehicle, resulting in waste of automatic driving vehicle chip computing power.

[0004] (2) The method and system only consider the position of the preset group and the collision time when dividing the collision risk level between the vulnerable group and the automatic driving vehicle, without considering other related factors that may cause collision risk.

[0005] (3) After the collision risk is judged, the method and system only simply describe the related operation under each risk level, and do not mention the reminding measures for the driver of the automatic driving vehicle.

[0006] (4) When identifying the driving intention of the preset group, the method and system mainly consider the situation that the vulnerable group itself driving road is affected and invades the motor vehicle road, and do not consider the situation that the normally driving vulnerable group has a sudden situation, which may make the collision risk calculation result of individual vulnerable group inaccurate.

[0007] The above content is only used to assist in understanding the technical solutions of the present application, and does not represent the acknowledgement of the above content as prior art. SUMMARY

[0008] In view of the problem of waste of chip computing power of an existing conventional automatic driving vehicle, the present application judges whether a non-motor vehicle recognition device needs to be started by a positioning detector according to the position of the vehicle, such as when the automatic driving vehicle travels on a motor vehicle lane isolated from non-motor vehicles, the recognition device is in a closed state, and the present application only calculates the collision risk level of non-motor vehicles within the minimum safety distance between the automatic driving vehicle and the non-motor vehicles, thereby further saving computing power resources.

[0009] In order to achieve the above-mentioned purpose, the present application is realized by adopting the following technical scheme: the early warning system comprises a data acquisition module, a data processing module, a control center module, an information communication module and an information response module;

[0010] The data acquisition module, the data processing module, the control center module and the information response module are connected in sequence through the information communication module, that is, the output end of the data acquisition module serves as the input end of the data processing module, the output end of the data processing module serves as the input end of the control center module, and the output end of the control center module serves as the input end of the information response module.

[0011] Further, the data acquisition module comprises a video recording unit, a vehicle information acquisition unit, a positioning detector and a data transmission port.

[0012] Further, the data processing module comprises a target recognition unit, a data calculation unit, a database unit, a data judgment unit and a data transmission port.

[0013] Further, the control center module comprises a data division unit, a data judgment unit, an instruction output unit and a data transmission port.

[0014] Further, the information communication module comprises wired communication and wireless communication; wherein the wireless communication comprises one or more forms of Bluetooth, WIFI, data network, etc.

[0015] Further, the information response module comprises a braking unit and an information display unit; wherein the braking unit comprises a brake system and a steering system; and the information display unit comprises an automobile display and an automobile audio.

[0016] In another aspect, the present application further provides a non-motor vehicle collision early warning method based on an automatic driving vehicle, which is applicable to the system and comprises the following steps:

[0017] S1: the data acquisition module acquires real-time positioning information of the current vehicle through the positioning detector, and if the current vehicle travels in a traffic environment where a non-motor vehicle collision occurs at an intersection and a mixed motor vehicle and non-motor vehicle road, the collision early warning system is started, the video recording unit records a video of the surrounding conditions, and the vehicle information acquisition unit acquires speed information of the automatic driving vehicle;

[0018] S2: The data processing module receives the relevant information transmitted by the data acquisition module through the information communication module and processes it, the target recognition unit processes the video information, identifies the non-motor vehicle type in the video recording, compares the identified non-motor vehicle type with the non-motor vehicle information stored in the database unit, and obtains the relevant data of the non-motor vehicle of this type;

[0019] S3: The control center module receives the conflict time difference and the conflict equivalent speed between the non-motor vehicle and the automatic driving vehicle calculated by the data processing module through the information communication module.

[0020] Advantages of the present application:

[0021] (1) The present application can provide the driving environment of the automatic driving vehicle through the positioning detection system, so as to judge whether it is necessary to start the collision warning system, and when calculating the collision risk level, only the non-motor vehicle within the minimum safety distance of the automatic driving vehicle is calculated, effectively avoiding the waste of computing resources and unnecessary deceleration behavior of the vehicle caused by irrelevant non-motor vehicles.

[0022] (2) When calculating the minimum safety distance of the automatic driving vehicle and the non-motor vehicle lane, the present application fully considers the length, width, speed, acceleration and speed angle of the vehicle and other factors, so that the vehicle can handle the possible collision situation under various conditions, provide safety buffer for the driver, improve the comprehensiveness of the collision detection mechanism, and thus ensure driving safety.

[0023] (3) After calculating the collision risk level between each non-motor vehicle and the vehicle, the present application uses the information response module to remind the driver in advance, so as to avoid traffic accidents caused by the driver in a panic state. BRIEF DESCRIPTION OF DRAWINGS

[0024] Figure 1 The present application is a schematic diagram of the system;

[0025] Figure 2 The present application is a flow chart of the system.

[0026] The implementation, functional characteristics and advantages of the present application will be further described with reference to the embodiments and the accompanying drawings. DETAILED DESCRIPTION

[0027] For a better understanding of the above technical solutions, the exemplary embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. Although the exemplary embodiments of the present disclosure are shown in the accompanying drawings, it should be understood that the present disclosure can be implemented in various forms and should not be limited by the embodiments set forth herein. On the contrary, these embodiments are provided so that the present disclosure can be more thoroughly understood and the scope of the present disclosure can be fully conveyed to those skilled in the art.

[0028] As Figure 1 shown, the purpose of the present application is to provide a non-motor vehicle collision warning system based on an automatic driving vehicle, which comprises a data acquisition module, a data processing module, a control center module, an information communication module and an information response module.

[0029] The data acquisition module is used to collect the basic information of the automatic driving vehicle and the surrounding road environment and traffic flow video information; the data processing module is used to arrange the basic information collected by the data acquisition module, process the traffic flow video information, obtain non-motor vehicle data, and calculate related parameters; the control center module is used to judge the collision warning situation between the automatic driving vehicle and the non-motor vehicle, and make related instructions; the information communication module is used to connect each module for data transmission; and the information response module is used to realize the related instructions issued by the control center module, reminding the driver of the automatic driving vehicle to pay attention to the surrounding road traffic conditions.

[0030] The data acquisition module, the data processing module, the control center module and the information response module are connected in sequence through the information communication module, that is, the output end of the data acquisition module serves as the input end of the data processing module, the output end of the data processing module serves as the input end of the control center module, and the output end of the control center module serves as the input end of the information response module.

[0031] The data acquisition module comprises a video recording unit, a vehicle information acquisition unit, a positioning detector and a data transmission port. The data processing module comprises a target recognition unit, a data calculation unit, a database unit, a data judgment unit and a data transmission port. The control center module comprises a data division unit, a data judgment unit, an instruction output unit and a data transmission port. The information communication module comprises wired communication and wireless communication; wherein the wireless communication comprises one or more forms of Bluetooth, WIFI, data network, etc. The information response module comprises a braking unit and an information display unit; wherein the braking unit comprises a brake system and a steering system; and the information display unit comprises an automobile display and an automobile audio.

[0032] As Figure 2As shown, S1: the data acquisition module obtains the real-time positioning information of the current vehicle through the positioning detector, and if the current vehicle is driving in the intersection and the mixed traffic road where the machine and non-machine collision traffic environment occurs, the collision warning system is started, the video recording unit records the surrounding situation, and the vehicle information acquisition unit obtains the speed information of the autonomous vehicle.

[0033] S2: the data processing module receives the relevant information transmitted by the data acquisition module through the information communication module and processes it, the target recognition unit processes the video information, identifies the type of non-motor vehicle in the video recording, compares the identified type of non-motor vehicle with the non-motor vehicle information stored in the database unit, and obtains the relevant data of the type of non-motor vehicle; the data calculation unit calculates the interval distance between the autonomous vehicle and the non-motor vehicle and the minimum safe braking distance of the two vehicles at the current speed; the data judgment unit 01 judges the minimum safe braking distance of the autonomous vehicle and the non-motor vehicle and the interval distance between the two vehicles, if the interval distance between the autonomous vehicle and the non-motor vehicle is less than or equal to the minimum safe braking distance of the autonomous vehicle and the non-motor vehicle, the data calculation unit is started again to calculate the conflict time difference (TDTC) and the conflict equivalent speed v between the autonomous vehicle and the non-motor vehicle; and the calculation result is transmitted to the control center module through the information communication module; if the interval distance between the autonomous vehicle and the non-motor vehicle is greater than the minimum safe braking distance of the autonomous vehicle, the warning system ends the related calculation of the non-motor vehicle.

[0034] In this embodiment, the data judgment unit judges the relationship between the minimum safe braking distance L z and the interval distance L j between the autonomous vehicle and the non-motor vehicle, if L j ≤L z , the data calculation unit is started again to calculate the conflict time difference (TDTC) and the conflict equivalent speed v between the autonomous vehicle and the non-motor vehicle; and the calculation result is transmitted to the control center module through the information communication module; if L j ≥L z , the warning system ends the related calculation of the non-motor vehicle.

[0035] Optionally, the interval distance calculation method between the autonomous vehicle and the non-motor vehicle in the data calculation unit of the data processing module is:

[0036]

[0037] Wherein, D is the interval distance between the autonomous vehicle and the non-motor vehicle; f is the focal length of the vehicle-mounted camera; h is the height of the non-motor vehicle; y is the pixel height of the non-motor vehicle in the image; θ is the tilt angle of the camera; k1 is the lens distortion correction coefficient, which is used to correct the influence of lens distortion on the measured distance; a is the attenuation coefficient of the camera focal length change, which describes the influence of distance expansion on the height change in the image; d cam H is the height of the camera to the ground; β is the correction coefficient of image processing, which considers the influence of different light, shadow or dynamic change on the measurement accuracy; γ is used to normalize the height of the non-motor vehicle relative to the reference height, to cope with the influence of object size difference in different environments; H ref is the standard height of the reference vehicle (for example, the average height of the same non-motor vehicle).

[0038] Optionally, the minimum safe braking distance calculation method between the autonomous vehicle and the non-motor vehicle in the data calculation unit of the data processing module is:

[0039]

[0040]

[0041] Wherein, R is the safe braking radius, S is the geometric size adjustment amount of the vehicle; v1 is the instantaneous speed of the autonomous vehicle; v2 is the instantaneous speed of the non-motor vehicle; a2 is the braking acceleration of the non-motor vehicle; l1 is the length of the autonomous vehicle; l2 is the length of the non-motor vehicle; d1 is the width of the autonomous vehicle; d2 is the width of the non-motor vehicle; θ is the included angle between the center of mass line of the autonomous vehicle and the non-motor vehicle and the vertical direction of the driving speed of the autonomous vehicle; ε is the speed attenuation coefficient, the value range is [0, 1], which reflects the correction of external influence (such as wind resistance, road conditions, etc.) on vehicle braking; t is the reaction time of the non-motor vehicle driver.

[0042] Optionally, the conflict time difference (TDTC) between the autonomous vehicle and the non-motor vehicle in the data calculation unit of the data processing module, the conflict time difference (TDTC) is the time difference of the two vehicles reaching the conflict point according to the current speed and the driving trajectory at the same time, and the calculation method of the conflict time difference (TDTC) is:

[0043] When d1 / v1≥d2+l2 / v2:

[0044]

[0045] When d2 / v2≥d1+l1 / v1:

[0046]

[0047] When d1 / v1 < d2 / v2 < d1+l1 / v1 or d2 / v2 < d1 / v1 < d2+l2:

[0048] T TDTC = 0

[0049] Wherein, d1 is the distance of the autonomous vehicle to reach the conflict point; d2 is the distance of the non-motor vehicle to reach the conflict point; l1 is the length of the autonomous vehicle; l2 is the length of the non-motor vehicle; v1 is the instantaneous speed of the autonomous vehicle, and v2 is the instantaneous speed of the non-motor vehicle.

[0050] Optionally, the calculation method of the conflict equivalent speed v between the autonomous vehicle and the non-motor vehicle in the data calculation unit of the data processing module is:

[0051]

[0052] Wherein, v1 is the instantaneous speed of the autonomous vehicle; v2 is the instantaneous speed of the non-motor vehicle; and a is the included angle between the driving speeds of the autonomous vehicle and the non-motor vehicle.

[0053] S3: The control center module receives the conflict time difference and the conflict equivalent speed between the non-motor vehicle and the autonomous vehicle calculated by the data processing module through the information communication module; the data division unit divides the conflict equivalent speed and the conflict time difference of the autonomous vehicle and the non-motor vehicle into grades respectively, the data judgment unit 02 comprehensively considers the two, obtains the final risk grade, and the information response module gives relevant prompts to the driver according to the risk grade calculated by the data judgment unit 02.

[0054] Optionally, in the embodiment, the data division unit divides the conflict equivalent speed between the autonomous vehicle and the non-motor vehicle into three risk grades, J Ⅰ , J Ⅱ , and J Ⅲ , wherein when the conflict equivalent speed V is greater than 30 km / h, it corresponds to J Ⅰ ; when the conflict equivalent speed V is less than or equal to 30 km / h and greater than 15 km / h, it corresponds to J Ⅱ ; and when the conflict equivalent speed V is less than or equal to 15 km / h, it corresponds to J Ⅲ ; see Table 1:

[0055] Table 1: Conflict Equivalent Speed Risk Grade Table

[0056]

[0057] Optionally, in the embodiment, the data division unit divides the conflict time difference between the autonomous vehicle and the non-motor vehicle into T Ⅰ , T Ⅱ , and T ⅢThree risk levels, wherein the conflict time difference is 0 < t < 0.66 s, corresponding to T Ⅰ ; the conflict time difference is 0.66 < t < 1.1 s, corresponding to T Ⅱ ; the conflict time difference is 1.1 s < t, corresponding to T Ⅲ ; see Table 2.

[0058] Table 2 Conflict time difference risk level table

[0059]

[0060]

[0061] Optionally, in the embodiment, the data judging unit uses a Gaussian membership function to describe the conflict equivalent speed risk level and the conflict time difference risk level, two fuzzy variables, to construct a fuzzy surface, and to establish the relationship between the three comprehensive collision warning levels (I, II, III) and the conflict equivalent speed risk level and the conflict time difference risk level, as shown in Table 3:

[0062] Table 3 Collision warning level table

[0063]

[0064] In addition, the Gaussian membership function calculation method in the data judging unit is:

[0065]

[0066] Where f(x) is the membership degree of parameter x; u is the distribution expectation; and δ is the width of the Gaussian function.

[0067] In this embodiment, the data judging unit judges the collision warning level of the autonomous vehicle and the non-motor vehicle lane in real time, when the collision warning level is I, the instruction output unit issues relevant instructions, wherein the relevant instructions include brake instructions, voice broadcast instructions, and central control information display instructions; the brake instructions are transmitted to the brake unit in the information response module by the information communication module, after the brake unit receives the brake instructions, the autonomous vehicle performs emergency braking and steering control, effectively avoiding the driver's wrong driving in a panic situation, causing irreparable traffic accident losses, the voice broadcast instructions and the central control information display instructions are transmitted to the information display unit in the information response module by the information communication module, the voice broadcast instructions are prompted to the driver of the autonomous vehicle by the vehicle audio in the information display unit, and the central control information display instructions display the real-time position relationship and the collision warning level of the autonomous vehicle and the non-motor vehicle lane on the automobile display, and visually warn the driver; when the collision warning level is II, the instruction output unit issues relevant instructions, including voice broadcast instructions and central control information display instructions, which are transmitted to the information display unit in the information response module by the information communication module, and respectively perform real-time voice prompting and visual warning on the driver of the autonomous vehicle; when the collision warning level is III, the instruction output unit issues the central control information display instructions, and the central control information display instructions are displayed on the automobile display in the information response module in real time, reminding the driver of the autonomous vehicle to drive carefully.

[0068] The following is further described with a specific parameter as an example:

[0069] For example, it is assumed that the camera system of the autonomous vehicle is detecting a non-motor vehicle in front, and the relevant parameters are as follows:

[0070] f is the focal length of the vehicle-mounted camera, taking 50mm, h is the height of the non-motor vehicle, taking 1.5m, y is the pixel height of the non-motor vehicle in the image, taking 1.2piex, θ is the tilt angle of the camera, taking 10°, k1 is the lens distortion correction coefficient, taking 0.8, and α is the attenuation coefficient of the camera focal length change, taking 0.1. cam d is the height of the camera to the ground, taking 2m, β is the correction coefficient of image processing, taking 0.8, γ is the normalization coefficient, taking 0.5, and H ref is the standard height of the reference vehicle, taking 1.6m (for example, the average height of similar non-motor vehicles).

[0071] The interval distance L between the autonomous vehicle and the non-motor vehicle in the data calculation unit j The calculation method is:

[0072]

[0073] wherein, L j is the interval distance between the autonomous vehicle and the non-motor vehicle, and is 38.02 m.

[0074] According to the detection data acquisition unit, the related parameters for calculating the minimum safe braking distance Lz are obtained, v1 is the instantaneous speed of the autonomous vehicle, which is taken as 15 m / s; v2 is the instantaneous speed of the non-motor vehicle, which is taken as 10 m / s; a1 is the braking acceleration of the autonomous vehicle, which is taken as 2 m / s 2 ; a2 is the braking acceleration of the non-motor vehicle, which is taken as 1.5 m / s 2 ; l1 is the length of the autonomous vehicle, which is taken as 4.5 m; l2 is the length of the non-motor vehicle, which is taken as 2 m; d1 is the width of the autonomous vehicle, which is taken as 1.8 m; d2 is the width of the non-motor vehicle, which is taken as 0.8 m; δ is the included angle between the line connecting the centers of mass of the autonomous vehicle and the non-motor vehicle and the vertical direction of the driving speed of the autonomous vehicle, which is taken as 15°; ε is the speed attenuation coefficient, which is taken as 0.5, and t is the reaction time of the non-motor vehicle driver, which is taken as 1 s.

[0075] The minimum safe braking distance Lz between the autonomous vehicle and the non-motor vehicle in the data calculation unit is:

[0076]

[0077] In this embodiment, since the current interval distance L j = 38.02 m, Lz is 64.45 m, and L j <Lz; therefore, further calculation of the collision-related indicators is required by the data calculation unit.

[0078] According to the related parameters of this example, it can be found that d1 / v1 < d2 / v2 < d1+l1 / v1, and therefore T TDTC = 0.

[0079] According to the related parameters of this example, the conflict equivalent speed v between the autonomous vehicle and the non-motor vehicle is calculated as:

[0080]

[0081] According to the results of the related parameters of this example and Table 1 and Table 2, respectively, it can be found that the conflict equivalent speed risk level of the non-motor vehicle and the autonomous vehicle is J I , and the conflict time difference risk level of the non-motor vehicle and the autonomous vehicle is T I .

[0082] Further according to Table 3, in the present embodiment, the collision warning level between the autonomous vehicle and the non-motor vehicle is I, and thus the instruction output unit sends relevant instructions, including braking instructions, voice broadcast instructions, and central control information display instructions. The braking instructions are transmitted by the information communication module to the braking unit in the information response module, and after the braking unit receives the braking instructions, the autonomous vehicle performs emergency braking and steering control, effectively avoiding the driver's erroneous driving in a panic situation, causing irreparable traffic accident losses. The voice broadcast instructions and the central control information display instructions are transmitted by the information communication module to the information display unit in the information response module, and the voice broadcast instructions are transmitted by the vehicle audio in the information display unit to the driver of the autonomous vehicle for voice prompting. The central control information display instructions are displayed by the automobile display to show the real-time position relationship and the collision warning level between the autonomous vehicle and the non-motor vehicle, and to visually warn the driver.

[0083] Those of ordinary skill in the art can understand that all or part of the processes in the above-mentioned embodiments can be completed by a computer program instructing relevant hardware, and the program can be stored in a computer-readable storage medium. When the program is executed, it can include the processes of the above-mentioned embodiments. The storage medium can be a magnetic disc, an optical disc, a read-only memory (ROM), a random access memory (RAM), or the like.

[0084] It should be understood that the above detailed description of the technical solutions of the present application by means of preferred embodiments is illustrative rather than limiting. Those of ordinary skill in the art can modify the technical solutions recorded in the embodiments or make equivalent substitutions for part of the technical features on the basis of the present application; and these modifications or substitutions do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the embodiments of the present application.

Claims

1. A collision warning system for motorized and non-motorized vehicles based on autonomous vehicles, characterized in that: The aforementioned early warning system includes a data acquisition module, a data processing module, a control center module, an information communication module, and an information response module; The data acquisition module, data processing module, control center module, and information response module are connected sequentially through an information communication module. That is, the output end of the data acquisition module serves as the input end of the data processing module, the output end of the data processing module serves as the input end of the control center module, and the output end of the control center module serves as the input end of the information response module. The method for calculating the distance between autonomous vehicles and non-motorized vehicles in the data calculation unit of the data processing module is as follows: Where D is the distance between the autonomous vehicle and the non-motorized vehicle; f is the focal length of the onboard camera; h is the height of the non-motorized vehicle; y is the pixel height of the non-motorized vehicle in the image; θ is the tilt angle of the camera; k1 is the lens distortion correction coefficient, used to correct the influence of lens distortion on the measured distance; α is the attenuation coefficient of the camera focal length change, describing the influence of distance increase on the height change in the image; d cam β is the height of the camera from the ground; β is the image processing correction coefficient, taking into account the impact of different lighting, shadows, or dynamic changes on measurement accuracy; γ is used to normalize the height of non-motorized vehicles relative to the reference height to account for the influence of differences in object size under different environments; H ref This is for reference to the standard height of vehicles.

2. The collision warning system for motorized and non-motorized vehicles based on autonomous vehicles according to claim 1, characterized in that: The data acquisition module includes a video recording unit, a vehicle information acquisition unit, a positioning detector, and a data transmission port.

3. The collision warning system for motorized and non-motorized vehicles based on autonomous vehicles according to claim 1, characterized in that: The data processing module includes a target recognition unit, a data calculation unit, a database unit, a data judgment unit, and a data transmission port.

4. A collision warning system for motorized and non-motorized vehicles based on autonomous vehicles according to claim 1, characterized in that: The control center module includes a data partitioning unit, a data judgment unit, an instruction output unit, and a data transmission port.

5. A collision warning system for motorized and non-motorized vehicles based on autonomous vehicles according to claim 1, characterized in that: The information communication module includes wired communication and wireless communication; wherein wireless communication includes one or more forms such as Bluetooth, WIFI, and data networks.

6. A collision warning system for motorized and non-motorized vehicles based on autonomous vehicles according to claim 1, characterized in that: The information response module includes a braking unit and an information display unit; wherein the braking unit includes a braking system and a steering system; and the information display unit includes a car display and a car audio system.

7. A method for collision warning of motor vehicles and non-motor vehicles based on autonomous vehicles, wherein the method is applicable to the system as described in any one of claims 1-6, characterized in that: The method is as follows: S1: The data acquisition module obtains the real-time location information of the current vehicle through the positioning detector. If the current vehicle is driving in an intersection or a road where motor vehicles and non-motor vehicles collide, the collision warning system is activated, the video recording unit records the surrounding situation, and the vehicle information acquisition unit obtains the speed information of the autonomous vehicle. S2: The data processing module receives and processes the relevant information transmitted by the data acquisition module through the information communication module. The target recognition unit processes the video information, identifies the type of non-motorized vehicle in the video recording, compares the identified non-motorized vehicle type with the non-motorized vehicle information stored in the database unit, and obtains the relevant data of the non-motorized vehicle of that type. S3: The control center module receives the conflict time difference and conflict equivalent speed between non-motorized vehicles and autonomous vehicles calculated by the data processing module through the information communication module.

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