WO2018016663A1

WO2018016663A1 - Vehicle to pedestrian (v2p) collision prevention system and method therefor

Info

Publication number: WO2018016663A1
Application number: PCT/KR2016/007922
Authority: WO
Inventors: 최광주
Original assignee: 최광주
Priority date: 2016-07-20
Filing date: 2016-07-20
Publication date: 2018-01-25

Abstract

A vehicle to pedestrian (V2P) collision prevention system and a method therefor are disclosed. In a V2P communication system for transmitting and receiving vehicle global navigation satellite system (GNSS) location information and pedestrian GNSS location information via wireless access in vehicular environments (WAVE) standard wireless communication, a V2P collision prevention system comprises: an on-board unit (OBU) in which a V2P collision prevention service is executed by calculating a relative distance between the vehicle and the pedestrian and which is mounted in the vehicle, road side equipment (RSE) which is capable of WAVE standard wireless communication with the OBU, and a user terminal which is capable of transmitting the pedestrian GNSS location information via WAN/Internet; and a server which calculates the possibility of collision between the vehicle and the pedestrian using the vehicle GNSS location information and the pedestrian GNSS location information via the RSE and WAN/Internet, and which transmits a danger signal to the driver of the vehicle and to the user terminal of the pedestrian. According to the present invention, the OBU provides a V2P collision prevention service via WAVE by calculating the relative distance between the vehicle and the pedestrian even when the accuracy of locations measured using the vehicle GNSS and measured using the pedestrian GNSS is low, and the latency executed using an ACK packet between the vehicle and the server, and between the pedestrian and the server is low.

Description

V2P collision prevention system and method

The present invention relates to a V2P collision prevention device and a method thereof, and specifically, a WAVE module is mounted on a vehicle and vehicle information is transmitted to a smartphone to predict collision with a vehicle or a pedestrian in a short distance, so that the driver and the pedestrian can see, hear or The present invention relates to a system and a method for preventing a collision by informing through tactile sense.

Recently, research on intelligent cars has been actively conducted. Among them, interest in information processing technology regarding accident prevention is increasing day by day. In particular, by providing the location and speed information of the vehicle in real time, efforts to prevent driving convenience and safety accidents are continuing.

As a representative example, with the evolution of technology, vehicle-to-vehicle communication (V2V communication) has been actively studied. V2V communication is expected to settle as a core technology essential for Intelligent Transport Systems. V2V communication is expected to be standardized using IEEE802.11p (WAVE) communication standard to enable autonomous driving and prevent vehicle collisions according to inter-vehicle communication.

The WAVE standard can use frequencies in the 5.9 GHz band. V2V communication based on the WAVE standard transmits standardized messages between terminals of a vehicle. For example, a terminal using V2V communication transmits and receives a message according to the message communication standard between terminals of SAE J2735. SAE J2735 defines a message set, which defines a Basic Safety Message (BSM). Through BSM, various types of messages including location information between terminals can be transmitted and received.

In order to prevent the collision between the vehicle and the pedestrian, it is necessary to anticipate the path of the pedestrian who has transmitted the message from the message according to the V2P communication, and to take the necessary action according to the path of the vehicle.

However, the known front or rear identification method of the vehicle cannot easily grasp the expected path of the vehicle because it utilizes the difference between the location data of the vehicle receiving the message and the vehicle transmitting the message. This is even more so when the direction of the vehicle receiving the message is variable.

As such, there is a need for a system and method for preventing collisions between vehicles and pedestrians by considering the direction of vehicles and pedestrians using the data used in V2P communication and predicting the paths of vehicles and pedestrians.

An object of the present invention is to predict a collision with a vehicle or a pedestrian by using vehicle information to prevent a collision by informing the driver and the pedestrian through sight, hearing, or touch.

In addition, another object of the present invention is the low accuracy of the position measured by the GNSS of the vehicle and the GNSS of the pedestrian, the latency between the vehicle and the server, and the latency between the pedestrian and the server executed using the ACK packet Even if low, the relative distance between the vehicle and the pedestrian is calculated to provide V2P collision prevention service through WAVE.

The technical problems to be achieved in the present invention are not limited to the technical problems mentioned above, and other technical problems not mentioned above will be clearly understood by those skilled in the art from the following description. Could be.

V2P collision prevention system according to an aspect of the present invention for achieving the above object of the present invention, in the V2P communication system for transmitting and receiving the GNSS position information of the vehicle and the GNSS position information of the pedestrian through WAVE wireless communication, An OBU (On Board Unit) mounted on a vehicle on which a V2P collision prevention service is executed by calculating a relative distance between the pedestrians; RSE (Road Side Equipment) capable of wireless communication with the OBU; A user terminal capable of transmitting the GNSS location information of the pedestrian through WAN / Internet; And calculating a possibility of collision between the vehicle and the pedestrian from the GNSS position information of the vehicle and the GNSS position information of the pedestrian through the RSE and the WAN / Internet, and transmitting a danger signal to the driver of the vehicle and the user terminal of the pedestrian. Server; includes.

According to another aspect of the present invention, a V2P collision prevention device is mounted on a vehicle, connected to an RSE, and transmitted from a GNSS satellite in a V2P communication device (OBU) that transmits and receives a dangerous signal from a server to a vehicle driver and a pedestrian through WAVE wireless communication. A GNSS module for generating GNSS data by receiving the received radio signal and outputting the generated GNSS data to a route prediction module; A measurement module connected to an ECU (Electronic Control Unit) inside the vehicle to receive data regarding the speed, RPM, and state of the vehicle and transmit the received data to a route prediction module; A route prediction module that calculates an expected route of the vehicle and the pedestrian from the route vector of the vehicle and the route vector of the pedestrian using the data received from the GNSS module and the data received from the measurement module; And transmitting data of the GNSS module, the measurement module, and the route prediction module to the server via the RSE, and receiving information of at least one vehicle and a pedestrian provided from the server via the RSE. And a WAVE module for detecting a situation and transmitting a danger signal to the server via the RSE.

V2P collision prevention method according to another aspect of the present invention, in the V2P communication method for transmitting and receiving the GNSS position information of the vehicle and the GNSS position information of the pedestrian through the WAVE, the vehicle for a vehicle equipped with OBU (first V2P) Obtaining a parameter and communicating with at least one user terminal (second V2P); Predicting a route of the vehicle based on the at least one vehicle parameter; Receiving at least one basic safety message from at least one user terminal (second V2P) device via a WAVE communication channel; Obtaining the user terminal parameters including the position and speed of the user terminal from at least one user terminal (second V2P); Calculating a likelihood and risk of collision between the vehicle and the user based on at least one user terminal parameter; Determining a possibility of collision between the vehicle and the user; And providing at least one danger signal to the driver and the user of the vehicle when the collision probability between the vehicle and the user is high.

According to the present invention, if a collision is expected from the predicted path of the vehicle and the predicted path of the pedestrian, a danger signal is transmitted to the smartphone of the driver and the pedestrian, thereby preventing a safety accident and improving the driving convenience of the driver.

In addition, according to the present invention, the relative distance between the vehicle and the pedestrian is more accurately estimated from the OBU of the vehicle equipped with the GNSS module and the user terminal of the pedestrian.

Further, according to the present invention, even if the accuracy of the position measured by the GNSS of the vehicle and the GNSS of the pedestrian is low, and the latency between the vehicle and the server and the pedestrian and the server executed using the ACK packet is low, Calculate the relative distance between vehicle and pedestrian and provide V2P collision prevention service through WAVE wireless communication.

In addition, according to the present invention, by reducing the amount of computation required to estimate the path of the OBU and pedestrians of the vehicle equipped with the GNSS module, it provides the driver and pedestrians with fast and accurate risk information in real time.

1 is a block diagram showing the configuration of a V2P collision prevention system according to an embodiment of the present invention.

2 is a block diagram showing a detailed configuration of a V2P collision prevention device (OBU) according to an embodiment of the present invention.

3 is a schematic diagram of Environment 1 for testing a V2P collision prevention device according to an embodiment of the present invention.

4 is a schematic diagram of Environment 2 for testing a V2P collision prevention device according to an embodiment of the present invention.

5 is a schematic diagram of Environment 3 for testing a V2P collision avoidance device according to an embodiment of the present invention.

FIG. 6 is a graph showing result 1 in a relative distance between a vehicle and a pedestrian test of the V2P collision prevention device according to an embodiment of the present invention.

Figure 7 is a graph showing the result 2 in the relative distance of the test of the vehicle and the pedestrian of the V2P collision prevention device according to an embodiment of the present invention.

8 is a graph showing the result 3 in the relative distance of the test of the vehicle and the pedestrian of the V2P collision prevention device according to an embodiment of the present invention.

FIG. 9 is a graph illustrating a latency result 1 of a test of a vehicle and a pedestrian of a V2P collision prevention device according to an embodiment of the present invention.

FIG. 10 is a graph illustrating a latency result 2 of a test of a V2P collision prevention device according to an embodiment of the present invention.

FIG. 11 is a graph illustrating a latency result 3 of a test of a V2P collision prevention device according to an embodiment of the present invention.

12 is a diagram illustrating a screen of a smartphone application of the V2P collision prevention system according to an embodiment of the present invention.

13 is a flowchart of an OBU and user terminal reception information processing of a V2P collision prevention system according to an embodiment of the present invention.

14 is a schematic diagram of format 1 of a message set between devices according to an embodiment of the present invention.

15 is a schematic diagram of format 2 of a message set between devices according to an embodiment of the present invention.

16 is a schematic diagram of format 3 of a message set between devices according to an embodiment of the present invention.

17 is a schematic diagram of format 4 of a message set between devices according to an embodiment of the present invention.

18 is a flowchart illustrating a V2P collision prevention method according to an embodiment of the present invention.

19 is an overall schematic diagram of a V2P collision prevention method according to an embodiment of the present invention.

20 is a schematic diagram of an included angel between the speed vector of the vehicle and the speed vector of the pedestrian in the V2P collision prevention method according to an embodiment of the present invention.

21 is a schematic diagram of various embodiments of an included angel between a speed vector of a vehicle and a speed vector of a pedestrian in a V2P collision prevention method according to an embodiment of the present invention.

22 is a schematic diagram of a normal line of the V2P collision prevention method according to an embodiment of the present invention.

23 is a schematic diagram of the crossing (Crossing) of the V2P collision prevention method according to an embodiment of the present invention.

24 is a schematic diagram of a non-matching case 1 of the V2P collision prevention method according to an embodiment of the present invention.

25 is a schematic diagram of a non-collision case 2 of the V2P collision prevention method according to an embodiment of the present invention.

26 is a schematic diagram of scenario 1 of a V2P collision prevention method according to an embodiment of the present invention.

27 is a schematic diagram of scenario 2 of a V2P collision prevention method according to an embodiment of the present invention.

28 is a schematic diagram of scenario 3 of a V2P collision prevention method according to an embodiment of the present invention.

29 is a schematic diagram of scenario 4 of a V2P collision prevention method according to an embodiment of the present invention.

30 is a schematic diagram of scenario 5 of a V2P collision prevention method according to an embodiment of the present invention.

31 is a schematic diagram of scenario 6 of a V2P collision prevention method according to an embodiment of the present invention.

32 is a schematic diagram of scenario 7 of a V2P collision prevention method according to an embodiment of the present invention.

33 is a schematic diagram of scenario 8 of a V2P collision prevention method according to an embodiment of the present invention.

34 is a schematic diagram of scenario 9 of a V2P collision prevention method according to an embodiment of the present invention.

35 is a schematic diagram of scenario 10 of a V2P collision prevention method according to an embodiment of the present invention.

36 is a schematic diagram of scenario 11 of a V2P collision prevention method according to an embodiment of the present invention.

10: V2P collision prevention system

20: V2P collision prevention device

30: V2P collision prevention method

100: OBU

110: GNSS Module

120: measurement module

130: route prediction module

140: WAVE module

150: input module

160: output module

170: storage module

180: interface module

200: RSE

300: user terminal

310: smart phone

400: server

Advantages and features of the present invention and methods for achieving them will be apparent with reference to the embodiments described below in detail with the accompanying drawings. However, the present invention is not limited to the embodiments disclosed below, but will be implemented in various forms, and only the present embodiments are intended to complete the disclosure of the present invention, and the general knowledge in the art to which the present invention pertains. It is provided to fully convey the scope of the invention to those skilled in the art, and the present invention is defined only by the scope of the claims. Meanwhile, the terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention. In this specification, the singular also includes the plural unless specifically stated otherwise in the phrase.

The term "module" as used herein is to be interpreted to include software, hardware or a combination thereof, depending on the context in which the term is used. For example, the software can be machine language, firmware, embedded code, and application software. As another example, the hardware may be a circuit, a processor, a computer, an integrated circuit, an integrated circuit core, a sensor, a micro-electro-mechanical system (MEMS), a passive device, or a combination thereof.

1 is a block diagram showing a schematic configuration of a V2P collision prevention system 10 according to an embodiment of the present invention.

Referring to FIG. 1, the V2P collision prevention system 10 includes an OBU 100, an RSE 200, a user terminal 300, and a server 400.

The OBU 100 is mounted on a vehicle and enables wireless communication in WAVE (Wireless Access in Vehicular Environment). The OBU 100 has a low accuracy of the position measured by the vehicle GNSS and the pedestrian GNSS, and is executed between the vehicle OBU 100 and the server 400 and the pedestrian user terminal 300 which is executed by using an ACK packet. Even if the latency between the servers 400 is low, the relative distance between the vehicle OBU 100 and the pedestrian user terminal 300 may be calculated to execute a V2P collision prevention service through WAVE wireless communication.

The RSE 200 may perform WAVE wireless communication with the OBU 100. The RSE 200 collects driving information (eg, vehicle position and speed), traffic conditions, image information (eg, images and videos), etc. collected through the OBU 110 and a web camera by an access point (AP). The receiving device is preferably a radio frequency (RF) transmitter and receiver capable of wirelessly communicating with the OBU 100.

The user terminal 300 transmits the location information of the pedestrian collected by the GNSS module 110. The user terminal 300 may be a smart phone 310 of the pedestrian linked with the terminal capable of tethering. Pedestrian smartphone 310 includes a smartphone application consisting of pedestrian data upload, upload stop, log file recording and the like.

The server 400 transmits and receives information to and from the RSE 200 through a wireless access network (WAN) or the Internet (Internet), and transmits and receives information to and from the user terminal 300 through a mobile communication network. The server 400 transmits location and status information to the OBU 100 and the user terminal 300.

Hereinafter, the operation of each component and the V2P collision prevention system operation will be described in detail with reference to the accompanying drawings.

2, an OBU 100 of a V2P collision avoidance system 10 is disclosed. The OBU 100 of the V2P collision prevention system 10 is an embodiment of the V2P collision prevention apparatus 20 of the present invention.

The OBU 100 includes a GNSS module 110 for measuring the position and speed of a vehicle, a measurement module 120 connected to an ECU (Electronic Control Unit) inside the vehicle, and receiving data regarding the state of the vehicle, and a GNSS module. The path prediction module 130 for calculating the estimated path of the vehicle using the data of the 110 and the measurement module 120, the data of the GNSS module 110 and the measurement module 120 and the path prediction module 130 Transmitting data to the RSE 200, receiving the information of the surrounding vehicles and pedestrians provided via the RSE 200 from the server 400 to detect a dangerous situation to the server 400 via the RSE 200 It includes a WAVE module 140 for transmitting the dangerous signal, it is preferable to further include an input module 150, an output module 160, a storage module 170, the interface module 180.

The OBU 100 is mounted on a vehicle. The input module 150, the output module 160, and the storage module 170 of the OBU 100 may be omitted according to need or design change. The GNSS module 110 may be omitted when the GNSS module 110 generating GNSS data outside the OBU 100 is embedded in the vehicle or attached to the vehicle.

The GNSS module 110 receives a radio signal transmitted from a GNSS satellite. The GNSS module 110 generates GNSS data for identifying the location of the vehicle on which the OBU 100 is mounted according to wireless signals received from a plurality of GNSS satellites, and outputs the generated GNSS data to the path prediction module 130. do. GNSS data includes latitude data, longitude data and heading angle data. The orientation angle represents the angle with respect to the reference direction of the direction in which the OBU 100 is directed and proceeds.

The measurement module 120 is connected to an ECU (Electronic Control Unit) inside the vehicle. The measurement module 120 may receive data according to the OBD-II standard and transmit the data to the ECU. The measurement module 120 may receive various data for knowing the state of the vehicle according to the OBD-II standard. For example, the measurement module 120 may receive data indicating a vehicle state such as a vehicle speed, RPM, various sensors, and the like, and transmit the received data to the route prediction module 130. If the measurement module 120 determines that the vehicle is in an abnormal state, the vehicle is determined to be in an abnormal state, and the measurement module 120 determines that the vehicle is not in an abnormal state. If there is a possibility of collision between pedestrians, it is considered a dangerous situation.

The route prediction module 130 is based on the vehicle position, the speed data and the position of the pedestrian, and the speed data received from the GNSS module 110, the measurement module 120, and the WAVE module 140. Calculate According to one embodiment of the invention, the path prediction module 130 preferably includes instructions of a program stored in the storage module 170, including one or more execution units capable of performing instructions. The program can be executed by loading into the execution unit. The path prediction module 130 may be configured or include logic (for example, a field programmable gate array (FPGA)) implementing the V2P collision prevention method 30. The route prediction module 130 may load the discrimination program stored in the storage module 170 into the execution unit and communicate with another adjacent vehicle (second V2P) by executing the instructions of the discrimination program. In particular, the route prediction module 130 is a vehicle (first V2P) on which the adjacent vehicle (second V2P) and the V2P collision prevention device 20 are mounted using latitude and longitude data of a message received from the adjacent vehicle (second V2P). The relative orientation angle with the OBU 100 may be calculated and the position of the pedestrian with respect to the vehicle (first V2P) OBU 100 may be determined based on the calculated relative orientation angle. The route prediction module 130 may further determine the position of the pedestrian by further using the latitude and longitude data and the direction angle data received through the GNSS module 110. The route prediction module 130 also generates a message including latitude and longitude data received through the GNSS module 110 and a vehicle identifier indicating the vehicle (first V2P) and sends the generated message to the WAVE module 140. Can be sent through. The message sent includes at least vehicle identifier, latitude and longitude data and may further include other data in accordance with the promised standard. The path prediction module 130 may execute the determination program according to the control input from the user through the input module 150 and display the positions of the plurality of pedestrians determined according to the execution of the determination program through the output module 160. You may.

Preferably, the route prediction module 130 determines that the vehicle is in a dangerous state when there is a possibility of collision between the vehicle and the pedestrian only when the measurement module 120 determines that the state of the vehicle is not an abnormal state of the vehicle. A signal is sent and it is determined whether the danger situation is due to a vehicle abnormality condition or whether there is a possibility of a collision between the vehicle and a pedestrian. The V2P collision prevention method 30 performed by the path prediction module 130 will be described in more detail through the example of FIG. 18.

The WAVE module 140 receives information about the position and speed of the vehicle from the GNSS module 110 and receives information about the position and speed of the pedestrian from the server 400. According to an embodiment of the present invention, the WAVE module 140 transmits the MAC packet according to the WAVE standard to the path prediction module 130 and modulates it into a wireless signal of a designated band (for example, 5.9 GHz band). The vehicle may be transmitted to the adjacent vehicle (second V2P). In addition, the WAVE module 140 may demodulate a radio signal of a specified band, convert it into a MAC packet, and transmit the same to a path prediction module 130. For example, the WAVE module 140 receives a message (a wireless packet) according to the J2735 BSM standard including latitude and longitude data wirelessly from an adjacent vehicle (second V2P) through a demodulation process and routes the received message. The module 130 may transmit the message received from the path prediction module 130 to the adjacent vehicle wirelessly through a modulation process. The WAVE module 140 may be configured as a chipset capable of performing modulation and demodulation from the base frequency at a carrier frequency and configuring a MAC packet. The WAVE module 140 may transmit and receive a message according to the V2V communication standard, and the message to be transmitted and received includes one or more network packets on a Mac layer. The message received via the WAVE module 140 includes at least latitude and longitude data and further includes an identifier of the vehicle.

The input module 150 is an interface for receiving an input from a user using a vehicle on which the OBU 100 is mounted. The input module 150 may be configured as a touch panel, a button, and / or a microphone, and receive a control input designated as a user touch input through a touch panel, a button input through a button, or a voice input through a microphone. The received input may be transmitted to the route prediction module 130.

The output module 160 outputs data received from the path prediction module 130. The output module 160 includes a display, a speaker, and / or one or more LEDs, and outputs an image, voice, or LED control signal to a corresponding display, speaker, or LED according to data received from the path prediction module 130. do.

The storage module 170 stores various data and programs, including a volatile memory and / or a nonvolatile memory. The volatile memory of the storage module 170 temporarily stores various data and programs, and the nonvolatile memory stores at least configuration data and programs according to the present invention. The program may be performed by the route prediction module 130 and may be a determination program for determining a collision between a vehicle and a pedestrian according to the present invention. The nonvolatile memory of the storage module 170 stores at least a vehicle identifier on which the OBU 100 is mounted or a vehicle identifier for identifying the device and a determination program for vehicle position determination.

The interface module 180 transmits and receives various data between blocks. The interface module 180 may transmit control data to another block under the control of the path predicting module 130 or transmit data according to the control data from the other block to the path predicting module 130. The interface module 180 may be configured of, for example, a parallel bus or a serial bus that can be controlled by the path prediction module 130. The parallel bus may for example be a 32-bit bus and the serial bus may consist of, for example, a TX (transmitter) line and / or a RX (receiver) line of a universal asynchronous receiver transmitter (UART).

Hereinafter, the operation of each component and the operation of the V2P collision prevention device 20 will be described in detail with reference to the drawings showing the embodiments.

One embodiment of the V2P collision prevention device 20 is an OBU 100 mounted on a vehicle. As shown in FIG. 2, the vehicle may be equipped with the OBU 100 and share information between the vehicle and the pedestrian through the pedestrian and the WAVE communication. Preferably, a plurality of vehicles may be equipped with the OBU 100 and share information between the vehicles through V2V communication with other vehicles.

The OBU 100 wirelessly transmits a message indicating the information of the vehicle on which the device is mounted to the server 400 and transmits a message indicating the information of the pedestrian via the server 400 wirelessly from the user terminal 300 of the pedestrian. Can be received. For example, the OBU 100 may transmit a message according to the Society of Automotive Engineers (SAE) J2735 Basic Safety Message (BSM) standard.

The OBU 100 may receive a message transmitted from the pedestrian and determine whether the pedestrian is near by using data included in the received message.

The message includes at least latitude data and longitude data determined by the Global Navigation Satellite System (GNSS) and also includes a vehicle identifier. The vehicle identifier is an identifier for identifying the vehicle on which the OBU 100 itself or the OBU 100 is mounted. This identifier may be predetermined according to an appointment between the OBUs 100 or according to a V2V communication standard.

The transmitted message is sent out wirelessly periodically (e.g. 100mSec, etc.) and is preferably sent out as MAC (MAC) data according to the WAVE standard.

The OBU 100 is generally mounted in a vehicle, but may be in the form of a terminal that may be embedded in the production of the vehicle or may be attached to the vehicle. For example, the OBU 100 may be a device capable of interfacing with the on-board diagnostics (OBD) -II and embedded in the front panel of the vehicle, or may be a portable terminal detachable to the front panel of the vehicle. The OBU 100 may be a smart phone, a tablet PC, a PDA, or the like as a portable terminal. The OBU 100 of the first V2P may determine whether the pedestrian or the vehicle is near by using latitude and longitude data of the message transmitted from the second V2P user terminal 300 of the adjacent vehicle.

The OBU 100 classifies the relative position of each object by feature based on itself using the position and the relative distance. This provides benefits such as reducing the computation time before making decisions by identifying objects that do not need to be included in the computation or applying more accurate operations. In addition, when the relative distance is used, the accuracy of the position measured by the GNSS module 110 of the vehicle OBU 100 and the GNSS of the pedestrian user terminal 300 is low, and is performed between the vehicle and the server executed by using an ACK packet. And even if the latency between the pedestrian and the server is low, the V2P collision prevention system can be operated. The test of the effect of the GNSS error on the relative distance between the vehicle and the pedestrian was conducted, and this will be described in more detail.

Test of the Effect of GNSS Error on Relative Distance between Vehicle and Pedestrian

We calculated the distance between the vehicle and the pedestrian and compared it with the actual distance on the map to see how the error of GNSS affects the relative distance error.

In addition, the latency between vehicle and server and between pedestrian and server was calculated. This process was performed using an ACK packet, which was performed as a ping. The calculation can evaluate how long it takes to service.

3 to 5 are schematic diagrams of an environment for testing a V2P collision prevention device according to an embodiment of the present invention, Figures 6 to 8 are the distance (difference) and the difference (difference) according to an embodiment of the present invention Is a graph.

Referring to FIG. 3, in Example 1, a standard distance between a stationary pedestrian and a stationary vehicle is 36m, and a minimum allowed error of the user terminal GNSS is 10.

Referring to FIG. 6, in Example 1, the average pedestrian is 57.37m, the difference average is 21.48m, the vehicle average is 56.97m, and the difference average is Difference Average. 21.18m.

Referring to FIG. 4, in Example 2, a standard distance between a stationary pedestrian and a stationary vehicle is 36m, and a minimum allowed error of the user terminal GNSS is 3.

Referring to FIG. 7, in Example 2, the average pedestrian is 35.77 m, the difference average is 2.60 m, the vehicle average is 35.30 m, and the difference average is Difference Average. 2.53m.

Referring to FIG. 5, in Example 3, the standard distance between pedestrians traveling within 15m on a straight path and the stationary vehicle is 34m, and the minimum allowed error of the user terminal GNSS is 3. .

Referring to FIG. 8, in Example 3, the average pedestrian is 34.96m, the difference average is 2.13m, the vehicle average is 33.43m, and the difference average is Difference Average. 1.23m.

9 to 11 are graphs illustrating a latency of the vehicle OBE 100 and the pedestrian user terminal 300.

Referring to FIG. 9, in Embodiment 1, the average delay speed of the pedestrian user terminal is 50.80 ms, and the average speed of the vehicle OBE is 8.57 ms.

Referring to FIG. 10, in Example 2, the average delay speed of the pedestrian user terminal is 66.53 ms, and the average speed of the vehicle OBE is 9.81 ms.

Referring to FIG. 11, in Example 3, the average delay speed of the pedestrian user terminal is 68.74 ms, and the average speed of the vehicle OBE is 11.54 ms.

According to the above results, it can be seen that the GNSS setting of the user terminal affects the relative distance error ratio between the vehicle and the pedestrian.

In addition, according to the above results, it can be seen that the V2P collision prevention service using the WAVE can be executed using the OBU 100 of the vehicle and the user terminal 300 of the pedestrian.

12, the smartphone 310 application of the user terminal 300 of the V2P collision prevention system according to an embodiment of the present invention includes a pedestrian data upload, upload stop, log file recording.

Referring to FIG. 13, the operation steps for the reception information processing of the OBU 100 and the user terminal 300 of the V2P collision prevention system according to an embodiment of the present invention are as follows.

S410 is a step of downloading the packet to the OBU 100 and the user terminal 300 (S410).

S420 is a step of analyzing the packets downloaded to the OBU 100 and the user terminal 300 (S420).

S430 is a step of calculating a relative distance using the analyzed packet information (S430).

S440 is a step of calculating a V2P collision prevention service that anticipates a collision possibility from the relative distance (S440) or adding to the history queue (S441).

S450 is a step of updating the MIS (S450).

S460 is a step of storing information in the MIS when the decision manager is executed (S460).

S470 is a step of updating the PIS (S470).

The server 400 includes a MIB data structure, an MIS data structure, an HIS data structure, a PIS data structure, and an EIS data structure.

The Management Information Base (MIB) includes various thresholds for determining alert conditions. Minimum Warning Angle defines the minimum angle between warnings. The default value is 85 (degrees), which corresponds to i of FIG. Minimum Warning Distance defines the minimum distance for warning. The default value is 100 (m) and corresponds to d in FIG. 19. Minimum Warning Shortened Acceleration Distance defines the minimum distance deceleration that generates a warning, and the default value is 6 (mps), which corresponds to the variation of d in FIG. 19. Minimum Warning Normal Line Distance defines the minimum normal distance for generating a warning. The default value is 10 (m) and corresponds to n in FIG. 19. Minimum Warning Vehicle Speed defines a minimum vehicle speed for generating a warning, the default value is 3 (mps), and corresponds to the speed of v of FIG. 19. Minimum History Searching Count defines the minimum number of information needed to search History for risk determination. The default value is 10 (times), and Minimum Distance Decrease Count should be generated to determine the path access to v of P. Defines the minimum number of access determination through History Searching. The default value is ((Minimum History Searching Count / 2) +1). Max Estimation Count defines the maximum number of times the route prediction to support the risk determination, the default value is 50 (times).

MIS (Management Information Structure) is information for managing each object (vehicle or pedestrian), and includes data for each. The composition of MIS is as follows. Object Identifier is used as an identifier to separate each item by vehicle or pedestrian. Path collision possibility Flag is the current cross path state of the target. Included Angle is the angle between the target and its respective path. Distance is the distance value between the target and itself. Normal Line Distance is the distance value between the vehicle's path and pedestrians. Shortened Acceleration Distance is a decreasing trend of distance value between the target and itself.

HIS (History Information Structure) includes past location information of each target (vehicle or pedestrian). The configuration of the HIS is as follows. Object Identifier is used as an identifier to separate each item by vehicle or pedestrian. Distance is your distance from the target at that point. Normal Line Distance is the normal distance between the vehicle's path and pedestrians at that time.

Presentation Information Structure (PIS) contains information for presentation of events and is managed in the form of queues. The configuration of the PIS is as follows. Event type indicates the type of event that has occurred. This parameter is created for the case where both vehicles and pedestrians are later processed by smartphones. MIS is MIS data about an event that occurred. EIS is the EIS data about the event that occurred.

Estimation Information Structure (EIS) contains prediction information about the future path of each target. Before saving, calculate the probability of collision with the target, location and time, and save the result. The composition of the EIS is as follows. Object Identifier is used as an identifier to separate each item by vehicle or pedestrian. Estimated Collision Time is the estimated collision estimated time. Collision Occurrence Estimation Flag is the predicted collision value.

Referring to FIG. 14, the frame format of a message set between devices includes a header and a payload. The header consists of time (year, month, day, hour, minute, second, millisecond), device type, device identifier, sequence number, and data type. The frame is 2 bytes per year, 1 byte per month, 1 byte for hour, 1 byte for hour, 1 byte for minute, 1 byte for second, 2 bytes for milliseconds, 1 byte for device type, 6 bytes for device identifier. The sequence number is 4 bytes, the data type is 1 byte, and the payload is n bytes. The time (year, month, day, hour, minute, second, millisecond) is the time of the system obtained from GNSS. The device type is 1 for pedestrians, 2 for vehicles, 3 for servers, and follows the initial setting for each device. The device identifier identifies each device by its MAC address. The sequence number is a value from 0 to 4294967295, and is reset to 0 upon device reboot. The data type is 1 for information upstream, 2 for information downstream, 3 for ACK, and data type of payload. Payloads have different configuration values for different data types.

Referring to FIG. 15, the payload is 4 bytes longitude, 4 bytes latitude, 2 bytes long, and 2 bytes long at the time of Information Upstream, and the longitude has a value of -1800000000 or more and less than 1800000001. This is not available for 1800000001 in 1/10 micro degree units. Latitude is a value between -900000000 and less than 900000001. 900000001 cannot be used. The value ranges from 0 to less than 28800, in 0.0125 degree units, and the 28800 cannot be used. Speed is a value between 0 and 8191, in 0.02m / s units, and 8191 cannot be used.

Referring to FIG. 16, in an information downstream, a payload includes one encapsuled data count of 1 byte and N encapsulated data of 28 bytes. N is a maximum of 30 and has a value from 1 to 30. One Encapsulated Data is 4 bytes longitude, 4 bytes latitude, 2 bytes speed, 2 bytes speed, 1 byte device type, 6 bytes device identifier, 2 bytes per year, 1 byte per month, 1 byte per hour, 1 byte per minute, 1 byte per minute. , 1 byte per second and 2 bytes in milliseconds.

Hardness has a value of -1800000000 or more and less than 1800000001. This is not available for 1800000001 in 1/10 micro degree units. Latitude is a value between -900000000 and less than 900000001. 900000001 cannot be used. The value ranges from 0 to less than 28800, in 0.0125 degree units, and the 28800 cannot be used. Speed is a value between 0 and 8191, in 0.02m / s units, and 8191 cannot be used. The device type is 1 for pedestrians and 2 for vehicles with values collected from the device. The device identifier identifies each device by its MAC address.

The time is 2 bytes, the month is 1 byte, the day is 1 byte, the hour is 1 byte, the minute is 1 byte, the second is 1 byte, and the millisecond is 2 bytes.

Referring to FIG. 17, ACK is 2 bytes in time, 1 byte in month, 1 byte in day, 1 byte in hour, 1 byte in minutes, 1 byte in seconds, 2 bytes in milliseconds, and 1 byte in device type. The device identifier consists of 6 bytes, the sequence number of 4 bytes, the data type of 1 byte, and the payload of n bytes. The payload consists of 2 bytes per year, 1 byte for month, 1 byte for day, 1 byte for hour, 1 byte for minute, 1 byte for second, 2 bytes for milliseconds, and 4 bytes for sequence number.

The time is a time stamp of the transmission packet and the sequence number is a value between 0 and 4294967295, and means the sequence number of the received packet.

Referring to FIG. 18, the method of preventing a V2P collision 30 may include obtaining vehicle parameters for a vehicle including a first V2P device and communicating with at least one user terminal (second V2P) (S510); Predicting a route of the vehicle based on the at least one vehicle parameter (S520); Receiving at least one basic safety message from at least one user terminal (second V2P) device via a WAVE communication channel (S530); Obtaining the user terminal parameters including the position and speed of the user terminal from at least one user terminal (second V2P) (S540); Estimating a collision potential path between the vehicle and the user terminal and a risk based on at least one user terminal parameter (S550); Determining a possibility of collision between the vehicle and the user (S560); And providing a dangerous signal to the driver and the user of the vehicle when the collision between the vehicle and the user is high (S570).

Hereinafter, each process will be described in more detail with reference to the drawings.

In operation 510, vehicle parameters for the vehicle including the first V2P device may be acquired and communicated with at least one pedestrian user terminal 300. Referring to FIG. 19, the meanings of the entities represented by the alphabet are as follows. V is the position of the vehicle. v is the moving direction vector of the vehicle. P is the position of the pedestrian. p is the moving direction vector of the pedestrian. b is the cabinet between the direction vector of the vehicle and the pedestrian path and the moving direction vector of the vehicle. i is a cabinet formed by the movement direction vector of the vehicle and the movement direction vector of the pedestrian. n is the vertical distance between the moving direction vector of the vehicle and the pedestrian. d is the distance between the vehicle and the pedestrian.

In step 520, the path of the pedestrian is estimated based on the at least one parameter of the user terminal 300 of the pedestrian. Referring to FIG. 20, it refers to a value obtained by calculating an angle between each of v and d or between v and p (each b or i), and is one of values essential for calculating other variables. It is also possible to apply a threshold range of the value and use it to determine the risk. This is an optional threshold method. Referring to FIG. 21, the cabinets of the vectors b1 to b4 for a correspond to Θ1 to Θ4, respectively. First, subtract the smaller angle from the larger angle to find the angle difference. According to the definition of the cabinet, the cabinet cannot be greater than 180 °, so if the result is greater than 180 °, subtract that value from 360 ° to find the cabinet between the two vectors. Referring to FIG. 22, a normal line refers to a distance of a normal line lowered from P with respect to a path v, and is used as a value for determining a proximity state and intersection of v and P.

Referring to FIG. 19, d denotes a distance between two points of V and P, and a calculation method is a Computational Formulas Method to which haversine formula (hav (θ) = sin ² (θ / 2)) is applied among the Great Circle Distance Formula. Obtain it using The haversine formula works better when calculating small distances. Such numerical methods are described in RW Sinnott, "Virtues of the Haversine", Sky and Telescope, vol. 68, no. 2, 1984, p. It is described in 159. R corresponds to the earth radius.

In step 530, at least one basic safety message is received from the user terminal (second V2P) device of the pedestrian.

In operation 540, the pedestrian parameter including the position and the speed of at least one pedestrian is obtained.

In step 550, the collision probability and the risk of the pedestrian are estimated based on the at least one pedestrian parameter. The probability of collision refers to a judgment as to whether or not v and p intersect, and to determine this, it is determined by calculating the variation of n. The collision timing and the degree of danger are determined by using other variables, and the value is used only to determine whether the paths intersect.

In operation 560, a possibility of collision between the pedestrian and the vehicle is determined.

Referring to FIG. 23, when n1> n2 over time, the paths of P and V must be crossed.

Referring to FIG. 24, when P crosses the path of V, since n1 <n2, it can be seen that the two paths do not intersect.

Referring to FIG. 25, when V crosses a path of P, n1 <n2, but when checking another variable d1 <d2, it can be seen that the two paths do not cross each other.

In step 570, if the collision probability between the vehicle and the pedestrian is high, at least one danger signal is provided to the vehicle and the pedestrian.

26 to 36 illustrate scenarios of the possibility of collision between the predicted vector of the vehicle and the predicted vector of the pedestrian.

Referring to FIG. 26, in scenario 1, when the included angle between the expected path vector of the vehicle and the expected path vector of the pedestrian is 90 degrees, the collision probability T / F is true.

Referring to FIG. 27, in scenario 2, when the included angle between the predicted path vector of the vehicle and the predicted vector of the pedestrian is 90 degrees, the collision probability T / F is False.

Referring to FIG. 28, in scenario 3, when the included angle between the predicted path vector of the vehicle and the predicted vector of the pedestrian is less than 90 degrees, the collision probability T / F is true.

Referring to FIG. 29, in scenario 4, when the included angle between the predicted path vector of the vehicle and the predicted vector of the pedestrian is less than 90 degrees, the collision probability T / F is False.

Referring to FIG. 30, in scenario 5, when the included angle between the predicted path vector of the vehicle and the predicted path vector of the pedestrian is greater than 90 degrees, the probability of collision T / F is true.

Referring to FIG. 31, in scenario 6, when the included angle between the predicted path vector of the vehicle and the predicted vector of the pedestrian is greater than 90 degrees, the probability of collision T / F is False.

Referring to FIG. 32, scenario 7 includes an included angle between an expected path vector of a vehicle and an estimated path vector of a pedestrian within 5 degrees from 180 degrees, and a minimum warning distance between a vehicle and a pedestrian. When Normal Line Distance is closer than the default value, the collision probability T / F is True.

Referring to FIG. 33, scenario 8 includes a minimum warning distance between an expected path vector of a vehicle and an estimated path vector of a pedestrian (included angle) within 180 degrees and a position of the vehicle and a pedestrian. When Normal Line Distance is farther than the default value, the probability of collision T / F: False.

Referring to FIG. 34, scenario 9 is a vehicle passed condition in an expected path vector of a vehicle and an expected path vector of a pedestrian.

Referring to FIG. 35, in scenario 10, when the included angle between the predicted vector of the vehicle and the predicted vector of the pedestrian is less than 5 degrees from 180 degrees and the speed of the vehicle is less than 5 km / h, the vehicle is decelerated. The probability of collision T / F is true if the location of the pedestrian and the pedestrian is close to the minimum warning normal line distance.

Referring to FIG. 36, in scenario 11, when the included angle between the predicted vector of the vehicle and the predicted vector of the pedestrian is less than 5 degrees from 180 degrees and the speed of the vehicle is 5 km / h or less, the vehicle is decelerated. The collision probability T / F is False if the location of the pedestrian and pedestrian is farther away than the minimum warning normal line distance.

Scenarios 10 and 11 are applied to prevent contact accidents with vehicles, bicycles, motorcycles and pedestrians in front of or behind the vehicle when the vehicle is stopped or the door is opened.

As described above, in the embodiment of the present invention, the vehicle and the GNSS location information of the vehicle provided by the OBU 100 of the vehicle equipped with the GNSS module 110 and the pedestrian user terminal 300 and the GNSS location information of the pedestrian. Predict the relative distance of pedestrians more accurately.

In addition, by reducing the amount of computation required to predict the route of the OBU 100 and the pedestrian of the vehicle on which the GNSS module 110 is mounted, the driver provides a fast and accurate danger signal in real time.

Meanwhile, the V2P collision prevention method 30 according to an embodiment of the present invention may be implemented in a computer system or recorded on a recording medium. The computer system may include at least one processor, memory, user input device, data communication bus, user output device, and storage. Each of the above components communicates data via a data communication bus.

The computer system can further include a network interface coupled to the network. The processor may be a central processing unit (CPU) or a semiconductor device that processes instructions stored in a memory and / or a storage.

The memory and the storage may include various types of volatile or nonvolatile storage media. For example, the memory may include a ROM and a RAM.

On the other hand, the V2P collision prevention method 30 according to the embodiment of the present invention can be implemented as computer-readable code on a computer-readable recording medium. Computer-readable recording media include all kinds of recording media having data stored thereon that can be decrypted by a computer system. For example, there may be a read only memory (ROM), a random access memory (RAM), a magnetic tape, a magnetic disk, a flash memory, an optical data storage device, and the like. The computer readable recording medium can also be distributed over computer systems connected over a computer network, stored and executed as readable code in a distributed fashion.

Those skilled in the art will appreciate that the present invention can be embodied in other specific forms without changing the technical spirit or essential features of the present invention. Therefore, it should be understood that the embodiments described above are exemplary in all respects and not restrictive. The protection scope of the present invention is shown by the following claims rather than the above description, and all changes or modifications derived from the claims and their equivalents should be construed as being included in the scope of the present invention.

Claims

In the V2P communication system for transmitting and receiving the vehicle GNSS location information and the pedestrian GNSS location information via WAVE wireless communication,

An OBU (On Board Unit) mounted on a vehicle on which a V2P collision prevention service is executed by calculating a relative distance between the vehicle and the pedestrian;

RSE (Road Side Equipment) capable of wireless communication with the OBU;

A user terminal capable of transmitting the GNSS location information of the pedestrian through WAN / Internet; And

A server for calculating a likelihood of collision between the vehicle and the pedestrian from the GNSS position information of the vehicle and the GNSS position information of the pedestrian through the RSE and WAN / Internet, and transmits a danger signal to a user terminal of the driver of the vehicle and the pedestrian. V2P collision prevention system comprising a.
The method of claim 1,

The OBU has low accuracy of the position measured by the GNSS of the vehicle and the GNSS of the pedestrian, and the latency between the vehicle and the server and between the pedestrian and the server that is executed by using an ACK packet. V2P collision prevention system, characterized in that the low V2P collision prevention device.
The method of claim 1,

The RSE is a device for receiving driving information, traffic conditions and image information collected through the OBU, V2P collision prevention system, characterized in that the radio frequency (RF) transmitter and receiver capable of WAVE wireless communication with the OBU.
The method of claim 1,

The server may include a MIB data structure having various threshold information for determining a warning situation, an MIS data structure having information for managing at least one vehicle or pedestrian, and past location information of at least one vehicle or pedestrian. HIS data structure that records the information, PIS data structure that stores information for expressing the event, calculates the prediction information about the route from the location and time data of each target, and calculates the probability of collision between the targets. V2P collision prevention system comprising an EIS data structure for storing.
The method of claim 1,

The OBU and the user terminal download the packet (S410), the step of analyzing the packet downloaded to the OBU and the user terminal (S420), and calculates the relative distance using the analyzed information of the packet In step S430, calculating a V2P collision prevention service predicting a collision possibility from the relative distance (S440) or adding the relative distance to the history queue (S441), updating the MIS (S450) and Storing the information in the MIS when the decision manager is executed (S460), and updating the PIS (S470).
In the V2P communication device (OBU) mounted on the vehicle and connected to the RSE to transmit and receive the dangerous signal from the server to the vehicle driver and pedestrian through WAVE wireless communication,

A GNSS module configured to receive a radio signal transmitted from a GNSS satellite to generate GNSS data including latitude data, longitude data, and heading angle data, and output the generated GNSS data to a route prediction module;

A measurement module connected to an ECU (Electronic Control Unit) inside the vehicle to receive data regarding a speed, RPM, abnormal state of the vehicle, and transmit the received data to a route prediction module;

A route prediction module that calculates an expected route of the vehicle and the pedestrian from the route vector of the vehicle and the route vector of the pedestrian using the data received from the GNSS module and the data received from the measurement module; And

Transmit the data of the GNSS module, the measurement module and the route prediction module to the server via the RSE, and receives the information of at least one vehicle and pedestrian provided through the RSE from the server and receives a dangerous situation And a WAVE module for detecting a signal and transmitting a dangerous signal to the server via the RSE.
The method of claim 6,

The path prediction module uses the angle information between the moving direction vector of the vehicle and the moving direction vector of the pedestrian and the normal distance information of the moving direction vector of the vehicle and the moving direction vector of the pedestrian. V2P collision prevention device characterized in that the collision is determined when the distance is shortened and the linear distance between the position of the vehicle and the position of the pedestrian is shortened.
The method of claim 7, wherein

The linear distance between the position of the vehicle and the position of the pedestrian is calculated using a computer calculation method in which hav (θ) = sin 2 (θ / 2), which is a haversine formula, of the Great Circle Distance Formula is applied. .
The method of claim 6,

The route prediction module determines that a dangerous situation exists when there is a possibility of collision between a vehicle and a pedestrian expected from the GNSS module and the route prediction module only when it is determined that the data received from the measurement module is not a vehicle abnormality state. In the case of a state, V2P collision prevention device characterized in that it is determined whether the possibility of collision between the vehicle and the pedestrian is due to the abnormal state of the vehicle or whether there is a possibility of collision between the vehicle and the pedestrian.
The method of claim 6,

The WAVE module is composed of a chipset capable of modulating and demodulating from a base frequency at a carrier frequency and composing a MAC packet, and the received message includes at least latitude and longitude data and further includes an identifier of a vehicle. V2P collision prevention device, characterized in that.
The method of claim 6,

V2P collision prevention, characterized in that it further comprises an input module for receiving a control input specified as a user touch input through a touch panel, a button input through a button or a voice input through a microphone to transmit the control input to the route prediction module. Device.
The method of claim 6,

And an output module for outputting a display, a speaker, or an LED corresponding to an image, voice, or LED control signal according to the data received from the path prediction module.
The method of claim 6,

V2P collision prevention program for calculating the collision between the vehicle and the pedestrian, a volatile memory for temporarily storing data, nonvolatile data for storing the setting data, the vehicle identifier for identifying the OBU, and the program for vehicle location determination V2P collision prevention device further comprising a storage module equipped with a memory.
The method of claim 6,

Under the control of the route prediction module, control data is transmitted to another block including at least one GNSS module, a WAVE module, a measurement module, an input module, an output module, and a storage module, or the control data is transmitted from the other block to the route prediction module. V2P collision prevention device further comprises an interface module consisting of a parallel bus or a serial bus to transmit to.
In the V2P communication method for transmitting and receiving the vehicle GNSS location information and the pedestrian GNSS location information through the WAVE,

Obtaining vehicle parameters for a vehicle equipped with an OBU (first V2P) and communicating with at least one user terminal (second V2P);

Predicting a route of the vehicle based on the at least one vehicle parameter;

Receiving at least one basic safety message from at least one user terminal (second V2P) device via a WAVE communication channel;

Obtaining the user terminal parameters including the position and speed of the user terminal from at least one user terminal (second V2P);

Calculating a likelihood and risk of collision between the vehicle and the user based on at least one user terminal parameter;

Determining a possibility of collision between the vehicle and the user; And

And providing at least one danger signal to a driver and the user of the vehicle when the collision between the vehicle and the user is high.
The method of claim 15,

The collision possibility refers to a determination as to whether or not the vehicle's moving direction vector v and the pedestrian's moving direction vector p intersect, and to determine this, the vertical distance between the vehicle's moving direction vector and the pedestrian's position (n). Calculate the amount of change and use it as a variable to determine whether the route crosses, and when n1> n2 as time passes, the pedestrian (P) and the vehicle (V) path must cross only V2P collision prevention method.
The method of claim 15,

The collision possibility refers to a determination as to whether the moving direction vector (v) of the vehicle and the moving direction vector (p) of the pedestrian intersect, and to determine this, the vertical distance (n) between the moving direction vector of the vehicle and the position of the pedestrian is determined. V2P collision, characterized in that the two paths do not cross because n1 <n2 when the pedestrian P crosses the path of the vehicle V. Prevention method.
The method of claim 15,

The collision possibility refers to a determination as to whether the moving direction vector (v) of the vehicle and the moving direction vector (p) of the pedestrian intersect, and to determine this, the vertical distance (n) between the moving direction vector of the vehicle and the position of the pedestrian is determined. Calculate the amount of change and use it as a variable to determine whether the paths cross. If the vehicle V passes the path of the pedestrian P, n1> n2, but if the other variable d1 <d2, the two paths V2P collision prevention method characterized in that it does not intersect.
The method of claim 15,

The collision possibility is a warning of the vehicle and the pedestrian when the included angle between the predicted vector of the vehicle and the predicted vector of the pedestrian is less than 5 degrees from 180 degrees and the speed of the vehicle is less than 5 km / h. Collision likelihood T / F is True if the minimum warning normal line distance is within the default value, V2P collision prevention method characterized in that.
The method of claim 15,

And the user of the user terminal (second V2P) is at least one pedestrian or driver.