Motor vehicle and non-motor vehicle collision early warning system and method based on automatic driving vehicle

Abstract

The invention discloses a motor vehicle and non-motor vehicle collision early warning system and method based on an automatic driving vehicle, and belongs to the field of automatic driving. 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; the driving environment of the automatic driving vehicle can be provided through the positioning detection system, so that whether the collision early warning system needs to be started or not is judged, and when the collision risk level is calculated, only non-motor vehicles within the minimum safety distance of the automatic driving vehicle are calculated, so that the collision risk level of the automatic driving vehicle is calculated. And therefore, the waste of computing power resources and unnecessary deceleration behaviors caused by irrelevant non-motor vehicles can be effectively avoided.

Description

Technical Field

[0001] The present invention relates to the field of autonomous driving technology, and in particular to a non-collision warning system and method based on an autonomous driving vehicle. Background Art

[0002] The conventional technology closest to the present invention is: Patent document CN116206285A discloses a collision risk assessment method and system for vulnerable traffic groups applied to autonomous driving, including: identifying and obtaining information on vulnerable traffic groups around the vehicle, obtaining the position and speed information of the vehicle itself, and obtaining information on the surrounding traffic environment where the vulnerable traffic groups are located; using the obtained information on vulnerable traffic groups to classify and identify the driving intentions of vulnerable traffic groups; based on the historical multi-frame information of vulnerable traffic groups and combined with the driving intentions of vulnerable traffic groups, predicting the driving trajectory of vulnerable traffic groups; generating alternative trajectories according to the driving targets, and performing collision detection on the trajectories with the predicted trajectories of vulnerable groups, the vulnerable groups expand the influence boundaries according to their driving intentions, and calculate the collision location and collision time; calculating the collision risk between the vulnerable groups and the autonomous driving vehicle.

[0003] (1) When calculating the collision position and time between the vulnerable group and the autonomous driving vehicle, this method and system will take all vulnerable groups that can be detected into account, resulting in a waste of computing power of the autonomous driving vehicle chip.

[0004] (2) When classifying the collision risk level between vulnerable groups and autonomous vehicles, this method and system only considers the location of the preset group and the time of collision, and does not consider other relevant factors that may cause collision risks.

[0005] (3) After the collision risk assessment is completed, the method and system simply describe the relevant operations at each risk level, and do not mention any reminder measures for the driver of the autonomous vehicle.

[0006] (4) When identifying the driving intentions of a preset group, this method and system focus on the situation where the vulnerable group's own driving road is affected and invades the motor vehicle road, and do not consider the situation where an emergency occurs to the vulnerable group while driving normally, which may make the collision risk calculation results of individual vulnerable groups inaccurate.

[0007] The above contents are only used to assist in understanding the technical solution of the present invention and do not constitute an admission that the above contents are prior art. Summary of the invention

[0008] In order to solve the problem of chip computing power waste in existing conventional technologies for autonomous driving vehicles, the present invention uses a positioning detector to determine whether it is necessary to turn on the non-motor vehicle identification device based on the position of the vehicle. For example, when the autonomous driving vehicle is traveling in a motor vehicle lane separated from non-motor vehicles, the identification device is in the off state. In addition, the present invention only calculates the collision risk level of non-motor vehicles within the minimum safe distance between the autonomous driving vehicle and the non-motor vehicle, thereby further saving computing power resources.

[0009] In order to achieve the above object, the present invention is implemented by adopting the following technical scheme: the 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;

[0010] The data acquisition module, data processing module, control center module, and 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] Furthermore, the data acquisition module includes a video recording unit, a vehicle information acquisition unit, a positioning detector, and a data transmission port.

[0012] Furthermore, 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.

[0013] Furthermore, the control center module includes a data division unit, a data judgment unit, a command output unit, and a data transmission port.

[0014] Furthermore, the information communication module includes wired communication and wireless communication; wherein the wireless communication includes one or more forms such as Bluetooth, WIFI, data network, etc.

[0015] Furthermore, 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.

[0016] On the other hand, the present invention also proposes a non-collision warning method based on an autonomous driving vehicle, the method is applicable to the system, and the method is as follows:

[0017] S1: The data acquisition module obtains the real-time positioning information of the current vehicle through the positioning detector. If the current vehicle is traveling at an intersection or on a mixed road with vehicles and non-vehicles and a traffic environment where a vehicle and non-vehicle collision occurs, the collision warning system is activated, the video recording unit records the surrounding conditions, and the vehicle information acquisition unit obtains the speed information of the autonomous driving vehicle;

[0018] S2: The data processing module receives and processes the relevant information transmitted by the data acquisition module through the information communication module, and the target recognition unit processes the video information, identifies the type of non-motor vehicle 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 type of non-motor vehicle;

[0019] S3: The control center module receives the conflict time difference and 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] Beneficial effects of the present invention:

[0021] (1) The present invention can provide the driving environment of the autonomous driving vehicle through the positioning detection system, so as to determine whether it is necessary to activate the collision warning system. When calculating the collision risk level, only non-motor vehicles within the minimum safety distance of the autonomous driving vehicle are calculated, which effectively avoids the waste of computing resources and unnecessary deceleration caused by irrelevant non-motor vehicles.

[0022] (2) When calculating the minimum safe distance between the autonomous driving vehicle and the non-motor vehicle lane, the present invention fully considers factors such as the length, width, driving speed, driving acceleration and speed angle of the autonomous vehicle and the non-motor vehicle, so that the autonomous vehicle can handle possible collisions under various circumstances, provide a safety buffer for the driver, and improve the comprehensiveness of the collision detection mechanism, thereby ensuring driving safety.

[0023] (3) After calculating the collision risk level between each non-motor vehicle and the vehicle itself, the present invention uses an information response module to give the driver a warning in advance to prevent the driver from causing a traffic accident due to panic. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] Figure 1 It is a schematic diagram of the system of the present invention;

[0025] Figure 2 It is a flow chart of the system of the present invention.

[0026] The realization of the purpose, functional features and advantages of the present invention will be further explained in conjunction with embodiments and with reference to the accompanying drawings. DETAILED DESCRIPTION

[0027] In order to better understand the above technical solution, exemplary embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. Although 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 described herein. On the contrary, these embodiments are provided to enable a more thorough understanding of the present disclosure and to fully convey the scope of the present disclosure to those skilled in the art.

[0028] like Figure 1 As shown, the purpose of the present invention is to provide a non-collision warning system based on an autonomous driving vehicle, wherein the non-collision warning system based on an autonomous driving vehicle 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 various basic information of the autonomous driving vehicle and the surrounding road environment and traffic flow video information; the data processing module is used to organize the basic information collected in the data acquisition module, process the traffic flow video information, obtain non-motor vehicle data, and calculate relevant parameters; the control center module is used to determine the collision warning situation between the autonomous driving vehicle and the non-motor vehicle, and make relevant instructions; the information communication module is used to connect each module and transmit data; the information response module is used to implement the relevant instructions issued by the control center module to remind the driver of the autonomous driving vehicle to pay attention to the surrounding road traffic conditions.

[0030] The data acquisition module, data processing module, control center module, and 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 includes a video recording unit, a vehicle information acquisition unit, a positioning detector, and a data transmission port. 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. The control center module includes a data division unit, a data judgment unit, a command output unit, and a data transmission port. The information communication module includes wired communication and wireless communication; wherein the wireless communication includes one or more forms such as Bluetooth, WIFI, and data network. 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; the information display unit includes a car display and a car audio.

[0032] like Figure 2As shown, S1: the data acquisition module obtains the real-time positioning information of the current vehicle through the positioning detector. If the current vehicle is traveling at an intersection or on a mixed road where a traffic environment of vehicle-non-vehicle collision occurs, the collision warning system is activated, the video recording unit records the surrounding conditions, and the vehicle information acquisition unit obtains the speed information of the autonomous driving vehicle.

[0033] 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-motor vehicle in the video recording, and compares the identified non-motor vehicle type with the non-motor vehicle information stored in the database unit to obtain the relevant data of the non-motor vehicle of this type. The data calculation unit calculates the interval distance between the automatic driving 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 makes a judgment on the minimum safe braking distance between the automatic driving vehicle and the non-motor vehicle and the interval distance between the two vehicles. If the interval distance between the automatic driving vehicle and the non-motor vehicle is less than or equal to the minimum safe braking distance between the automatic driving 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 automatic driving vehicle and the non-motor vehicle; and the calculation results are transmitted to the control center module through the information communication module. If the interval distance between the automatic driving vehicle and the non-motor vehicle is greater than the minimum safe braking distance of the automatic driving vehicle, the early warning system ends the relevant calculation of the non-motor vehicle.

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

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

[0036]

[0037] Where D is the distance between the autonomous driving vehicle and the non-motor vehicle; f is the focal length of the on-board 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; α is the attenuation coefficient of the change in the focal length of the camera, which describes the influence of distance expansion on the height change in the image; d cam is the height from the camera to the ground; β is the correction coefficient for image processing, which takes into account the influence of different light, shadow or dynamic changes on the measurement accuracy; γ is used to normalize the height of non-motor vehicles relative to the reference height to cope with the influence of object size differences in different environments; H ref The standard height of the reference vehicle (e.g. the average height of similar non-motor vehicles).

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

[0039]

[0040]

[0041] Among them, R is the safe braking radius, S is the geometric size adjustment of the vehicle; v1 is the instantaneous speed of the autonomous driving 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 driving vehicle; l2 is the length of the non-motor vehicle; d1 is the width of the autonomous driving vehicle; d2 is the width of the non-motor vehicle; θ is the angle between the center of mass line of the autonomous driving vehicle and the non-motor vehicle and the vertical direction of the autonomous driving vehicle's speed; ε is the speed attenuation coefficient, which ranges from [0, 1] and reflects the correction of vehicle braking due to external influences (such as wind resistance, road conditions, etc.); t is the reaction time of the non-motor vehicle driver.

[0042] Optionally, the conflict time difference (TDTC) between the autonomous driving vehicle and the non-motor vehicle in the data calculation unit of the data processing module is the time difference between the autonomous driving vehicle and the non-motor vehicle arriving at the conflict point at the same time according to the current speed and driving trajectory. 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 the conflict point; d2 is the distance of the non-motor vehicle to 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, in the data calculation unit of the data processing module, the calculation method of the conflict equivalent speed v between the autonomous vehicle and the non-motor vehicle is:

[0051]

[0052] Wherein, v1 is the instantaneous speed of the autonomous vehicle; v2 is the instantaneous speed of the non-motor vehicle; α 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 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 between the autonomous vehicle and the non-motor vehicle into grades respectively, and the data judgment unit 02 comprehensively considers the two to obtain the final risk level, and the information response module gives relevant prompts to the driver according to the risk level calculated by the data judgment unit 02.

[0054] Optionally, in this embodiment, the data division unit divides the conflict equivalent speed between the autonomous vehicle and the non-motor vehicle into J Ⅰ 、J Ⅱ 、J Ⅲ Three danger levels. When the conflict equivalent speed V > 30 km / h, it corresponds to J Ⅰ ; when the conflict equivalent speed V ≤ 30 km / h and V > 15 km / h, it corresponds to J Ⅱ ; when the conflict equivalent speed V ≤ 15 km / h, it corresponds to J Ⅲ ; as shown in Table 1:

[0055] Table 1 Conflict Equivalent Speed Danger Level Table

[0056]

[0057] Optionally, in this embodiment, the data division unit divides the conflict time difference between the autonomous vehicle and the non-motor vehicle into T Ⅰ 、T Ⅱ 、T ⅢThree risk levels, where when the conflict time difference is 0 < t ≤ 0.66 s, it corresponds to T Ⅰ ; when the conflict time difference is 0.66 < t ≤ 1.1 s, it corresponds to T Ⅱ ; when the conflict time difference is 1.1 s < t, it corresponds to T Ⅲ ; as shown in Table 2

[0058] Table 2 Risk Level Table for Conflict Time Difference

[0059]

[0060]

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

[0062] Table 3 Collision Warning Level Table

[0063]

[0064] In addition, the calculation method of the Gaussian membership function in the data judgment unit is as follows:

[0065]

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

[0067] In this embodiment, the data judgment unit makes a real-time judgment on the collision warning level of the autonomous driving vehicle and the non-motor vehicle lane. When the collision warning level is 1, the command output unit issues relevant commands, wherein the relevant commands include braking commands, voice broadcast commands, and central control information display commands; the braking commands are transmitted to the braking unit in the information response module by the information communication module. After the braking unit receives the braking commands, the autonomous driving vehicle performs emergency braking and steering control, effectively preventing the driver from driving incorrectly in a panic and causing irreparable traffic accident losses. The voice broadcast commands and the central control information display commands are transmitted to the information display unit in the information response module through the information communication module. The voice broadcast commands give voice prompts to the driver of the autonomous driving vehicle through the vehicle-mounted audio system in the information display unit. The central control information display instruction displays the real-time position relationship and collision warning level between the autonomous driving vehicle and the non-motor vehicle lane through the car display, and provides a visual warning to 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. The voice broadcast instructions and the central control information display instructions are transmitted to the information display unit in the information response module through the information communication module, and provide real-time voice reminders and visual warnings to the driver of the autonomous driving vehicle respectively; when the collision warning level is III, the instruction output unit issues a central control information display instruction. The central control information display instruction displays the collision warning level between the non-motor vehicle and the autonomous driving vehicle in real time through the car display in the information response module, and reminds the driver of the autonomous driving vehicle to drive carefully at all times.

[0068] The following is a further explanation using a specific parameter as an example:

[0069] For example, assume that the camera system of the autonomous driving 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 camera, which is 50 mm; h is the height of the non-motor vehicle, which is 1.5 m; y is the pixel height of the non-motor vehicle in the image, which is 1.2 piex; θ is the tilt angle of the camera, which is 10°; k1 is the lens distortion correction coefficient, which is 0.8; α is the attenuation coefficient of the camera focal length change, which is 0.1. cam The height from the camera to the ground is 2m, β is the correction coefficient for image processing and is 0.8. γ is the normalization coefficient and is 0.5. ref The standard height of the reference vehicle is taken as 1.6m (e.g. the average height of similar non-motor vehicles).

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

[0072]

[0073] Among them, L j is the spacing distance between the autonomous vehicle and the non-motor vehicle, which is 38.02 m.

[0074] According to the detection data acquisition unit, relevant parameters for calculating the minimum safe braking distance Lz are obtained. Take v1 as the instantaneous speed of the autonomous vehicle, which is 15 m / s; v2 as the instantaneous speed of the non-motor vehicle, which is 10 m / s; a1 as the braking acceleration of the autonomous vehicle, which is 2 m / s 2 ; a2 as the braking acceleration of the non-motor vehicle, which is 1.5 m / s 2 ; l1 as the length of the autonomous vehicle, which is 4.5 m; l2 as the length of the non-motor vehicle, which is 2 m; d1 as the width of the autonomous vehicle, which is 1.8 m; d2 as the width of the non-motor vehicle, which is 0.8 m; δ as the angle between the line connecting the mass centers of the autonomous vehicle and the non-motor vehicle and the perpendicular direction of the driving speed of the autonomous vehicle, which is 15°; ε as the speed decay coefficient, which is 0.5, and t as the reaction time of the non-motor vehicle driver, which is 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 spacing distance L j = 38.02 m, Lz is 64.45 m, and L j < Lz; therefore, it is necessary to further calculate the collision-related indicators through the data calculation unit.

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

[0079] According to the relevant parameters of this example, calculate the conflict equivalent speed v between the autonomous vehicle and the non-motor vehicle:

[0080]

[0081] According to the comparison of the relevant parameter results of this instance with Table 1 and Table 2 respectively, it can be known that the danger level of the conflict equivalent speed between the non-motor vehicle and the autonomous vehicle is J I , and the danger level of the conflict time difference between the non-motor vehicle and the autonomous vehicle is T I .

[0082] Further, according to Table 3, in this embodiment, the collision warning level between the autonomous driving vehicle and the non-motor vehicle is 1, so the command output unit issues relevant commands, wherein the relevant commands include braking commands, voice broadcast commands, and central control information display commands; the braking commands are transmitted to the braking unit in the information response module by the information communication module, and after the braking unit receives the braking commands, the autonomous driving vehicle performs emergency braking and steering control, effectively avoiding the driver's wrong driving in a panic state, causing irreparable traffic accident losses, the voice broadcast commands and the central control information display commands are transmitted to the information display unit in the information response module through the information communication module, the voice broadcast commands give voice prompts to the driver of the autonomous driving vehicle through the on-board audio in the information display unit, and the central control information display commands display the real-time position relationship and collision warning level of the autonomous driving vehicle and the non-motor vehicle lane through the vehicle display, and give visual warnings to the driver.

[0083] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiments can be implemented by instructing the relevant hardware through a computer program, and the program can be stored in a computer-readable storage medium, and when the program is executed, it can include the processes of the embodiments of the above-mentioned methods. The storage medium can be a disk, an optical disk, a read-only memory (ROM) or a random access memory (RAM).

[0084] It should be understood that the detailed description of the technical solutions of the present invention by means of the preferred embodiments is illustrative rather than restrictive. A person skilled in the art may modify the technical solutions described in the embodiments, or replace some of the technical features by equivalents, based on reading the specification of the present invention; and these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A non-collision warning system based on an autonomous driving vehicle, characterized in that: The 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 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.

2. The non-collision warning system based on an autonomous driving vehicle 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 non-collision warning system based on an autonomous driving vehicle 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. The non-collision warning system based on an autonomous driving vehicle according to claim 1, characterized in that: The control center module includes a data division unit, a data judgment unit, a command output unit, and a data transmission port.

5. The non-collision warning system based on an autonomous driving vehicle according to claim 1, characterized in that: The information communication module includes wired communication and wireless communication; wherein the wireless communication includes one or more forms of Bluetooth, WIFI, and data network.

6. The non-collision warning system based on an autonomous driving vehicle 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.

7. A non-collision warning method based on an autonomous driving vehicle, the method being applicable to a system as claimed in any one of claims 1 to 6, characterized in that: The method described is as follows: S1: The data acquisition module obtains the real-time positioning information of the current vehicle through the positioning detector. If the current vehicle is traveling at an intersection or on a mixed road with vehicles and non-vehicles and a traffic environment where a vehicle and non-vehicle collision occurs, the collision warning system is activated, the video recording unit records the surrounding conditions, and the vehicle information acquisition unit obtains the speed information of the autonomous driving vehicle; S2: The data processing module receives and processes the relevant information transmitted by the data acquisition module through the information communication module, and the target recognition unit processes the video information, identifies the type of non-motor vehicle 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 type of non-motor vehicle; S3: The control center module receives the conflict time difference and conflict equivalent speed between the non-motor vehicle and the automatic driving vehicle calculated by the data processing module through the information communication module.

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