JP7254890B1 - Collision possibility determination device, communication terminal device, mobile object, system, method and program for determining collision possibility - Google Patents

Abstract

A collision possibility determination device capable of determining the possibility of a collision between mobile bodies in anticipation of the future when another mobile body joins a moving route on which the mobile body is traveling is provided. A collision possibility determination device acquires moving body information including current positions and velocities of a plurality of moving bodies moving toward a confluence of movement paths at a predetermined frequency, and estimating a predicted merging area indicating an error range of predicted arrival positions of moving bodies at a merging point based on the moving body information and the frequency information for each of the plurality of moving bodies; Based on this information, the passage time period during which the moving bodies pass through the expected confluence area is calculated, and the possibility of collision between the plurality of moving bodies is determined based on the overlap of the passage time periods between the plurality of moving bodies. [Selection drawing] Fig. 1

Description

TECHNICAL FIELD The present invention relates to a technique for determining the possibility of a collision between moving bodies such as vehicles on a moving route along which the moving bodies are moving.

Conventionally, there has been known a collision possibility determination device that determines a collision between moving bodies between the vehicle and surrounding vehicles based on the output of a sensor such as a camera or radar that detects objects in front of the vehicle in the direction in which the vehicle is moving. It is For example, in Patent Document 1, a circle centered on a pixel position in the traveling direction based on the traveling direction of the own vehicle is set in an image of the traveling direction of the own vehicle captured by a camera. A collision possibility determination device is disclosed that determines the possibility of a collision between the own vehicle and an object (another vehicle) depending on whether or not a movement vector indicating the moving direction of the object pointing toward the inside of a circle indicates a direction toward the inside of a circle. .

Japanese Patent Application Laid-Open No. 2005-202876

The above-mentioned conventional collision possibility determination device is a determination after detecting another moving body (vehicle) with a sensor such as a camera, and before detecting another moving body (vehicle) with a sensor Unable to determine the likelihood of a collision. In particular, when a moving body (self-vehicle) is moving on a moving route such as an expressway, and another moving body (vehicle) traveling on a side road that joins the moving route, the other moving body (vehicle) Since the bodies (vehicles) cannot be detected by a sensor such as a camera, there is a problem that it is impossible to determine the possibility of a future collision between moving bodies at the time of merging.

A collision possibility determination device according to an aspect of the present invention is a collision possibility determination device that determines the possibility of collision between moving bodies. This collision possibility determination device includes: information acquisition means for acquiring, at a predetermined frequency, mobile body information including current positions and velocities of a plurality of mobile bodies moving toward a confluence of moving paths; region estimating means for estimating a predicted merging region indicating an error range of predicted arrival positions of the moving bodies at the merging point based on the moving body information and the frequency information for each of the moving bodies; time period calculation means for calculating a passage time period during which the moving object passes through the expected confluence region based on information on the current position and speed of the moving object;
determining means for determining a possibility of collision of the plurality of moving bodies based on overlap of the passing time zones of the plurality of moving bodies;

In the collision possibility determination device, the determination means determines that, of the plurality of passage time periods calculated for the plurality of moving objects, a plurality of overlapping area passage time periods that pass through an overlapping area of the plurality of predicted confluence areas are: It may be determined that there is a high possibility of collision between the plurality of moving bodies when the plurality of moving bodies overlap each other.

In the collision possibility determination device, the moving body information includes information on the acceleration and yaw rate of the moving body, and the time period calculation means includes information on the current position and speed of the moving body and the acceleration and yaw rate of the moving body. The transit time period may be calculated based on yaw rate information.

In the collision possibility determination device, a communication terminal device mounted on at least one mobile body of the plurality of mobile bodies or a communication terminal device possessed or attached to a user using the at least one mobile body, The apparatus may further include notification means for notifying the determination result of the possibility of collision.

In the collision possibility determination device, the collision possibility determination result may be used for control for avoiding the collision in at least one of the plurality of moving bodies.

In the collision possibility determination device, the predicted confluence area may be a circular, elliptical, or oval area in which the confluence point is located at the center.

In the collision possibility determination device, the predicted merging area is an arc-triangular area whose base is an arc of a circle, ellipse, or ellipse in which the merging point is located in the center and whose vertex is the current position of the moving object. may be

In the collision possibility determination device, the passage time period may be a passage time period during which the moving object passes through a portion of the predicted confluence area within a range in which the moving object can merge.

In the collision possibility determination device, the identification of the confluence, the estimation of the predicted confluence area, and the calculation of the passage time period may be performed based on the position information of the driving reference line of the movement route in the map information.

The collision possibility determination device may be a base station of a mobile communication network, a node between the base station and the core network, or an MEC (Multi-access Edge Computing) device provided outside the core network.

A mobile object according to another aspect of the present invention includes any of the collision possibility determination devices described above.

A communication terminal device according to still another aspect of the present invention includes any of the collision possibility determination devices described above.

A communication terminal device according to still another aspect of the present invention is a communication terminal device mounted on a moving body or a communication terminal device in the moving body for which the possibility of collision at a confluence is determined by any one of the collision possibility determination devices. It is a communication terminal device possessed or worn by a user. This communication terminal device comprises: information transmitting means for transmitting mobile information including the current position and speed of the mobile to the collision possibility determination device at the predetermined frequency; determination result receiving means for receiving a result of the determined determination from the collision possibility determination device.

A system according to still another aspect of the present invention is a system that determines the possibility of a collision between moving bodies when another moving body joins a moving path on which the moving body is moving. This system includes any of the collision possibility determination devices described above and the communication terminal device of the mobile body.

The system includes a map database device that stores map information including information on the reference line of the moving route, and the collision possibility determination device receives the position information of the reference line on the moving route from the map database device. may be obtained.

A method according to still another aspect of the present invention is a method for determining the possibility of collision between moving bodies. This method includes acquiring, at a predetermined frequency, mobile body information including current positions and velocities of a plurality of mobile bodies moving toward a confluence of movement paths; and for each of the plurality of mobile bodies, estimating a predicted confluence area indicating an error range of predicted arrival positions of the moving bodies at the confluence based on the moving body information and the frequency information; calculating a passage time period during which the moving body passes through the predicted confluence region based on information on the current position and velocity of the body; and determining a probability of collision of the moving bodies of the.

A program according to still another aspect of the present invention is a program executed by a computer or processor provided in a device for determining the possibility of collision between moving bodies. This program includes a program code for acquiring, at a predetermined frequency, mobile body information including current positions and velocities of a plurality of mobile bodies moving toward a confluence of movement paths; a program code for estimating a predicted confluence area indicating an error range of predicted arrival positions of the moving bodies at the merging point based on the moving body information and the frequency information; program code for calculating a passage time zone in which the moving object passes through the predicted confluence area based on information on the current position and speed of the moving object; and the passing time of the plurality of moving objects, and program code for determining a likelihood of collision of the plurality of moving objects based on swath overlap. Also, the program for estimation and judgment includes a learned model used for machine learning.

In the collision possibility determination device, the communication terminal device, the mobile body, the system, the method, and the program, the mobile body may be a mobile body that moves on the ground, in the ground, in the air, on water, or in water. The information on the moving body may include information used for controlling automatic operation of the moving body. Further, the moving object may be a vehicle that moves on the ground, and the information on the moving object may include information used for controlling automatic operation of the vehicle.

Advantageous Effects of Invention According to the present invention, it is possible to determine the possibility of collision between moving bodies in anticipation of the future at the time when another moving body joins the moving route on which the moving body is traveling.

Explanatory drawing which shows an example of the whole structure of the collision possibility determination system which concerns on embodiment. 1 is a block diagram showing an example of main functions of an MEC server (collision possibility determination device) according to an embodiment; FIG. FIG. 2 is a block diagram showing an example of main functions of a communication terminal device (UE) mounted on an in-vehicle device of a vehicle according to the embodiment; FIG. 3 is an explanatory diagram showing an example of a driving reference line, a merging point, and a predicted merging area used for vehicle collision possibility determination processing in the MEC server (collision possibility determination device) according to the embodiment; 4(a) and 4(b) are explanatory diagrams each showing an example of a predicted merging area when a plurality of vehicles according to the embodiment are traveling at different speeds; FIG. FIG. 4 is an explanatory diagram showing a calculation example (estimation example) of the entry time at which a plurality of vehicles enter the predicted confluence area and the arrival time at which the confluence is reached when a plurality of vehicles are moving toward the confluence according to the embodiment; FIG. 4 is an explanatory diagram showing an example of a passage time zone of a predicted confluence area used for determining the possibility of a vehicle collision according to the embodiment; FIG. 5 is an explanatory diagram showing an example of six types of collision possibility determination based on overlapping of passing time zones of a plurality of vehicles on the time axis according to the embodiment; 4 is a flowchart showing an example of vehicle collision possibility determination processing in the MEC server (collision possibility determination device) according to the embodiment. 4(a) to 4(d) are explanatory diagrams showing examples of predicted merging regions when the combinations of manual driving and automatic driving of a plurality of vehicles moving toward a merging point are different from each other. An explanatory diagram showing a calculation example (estimation example) of the entry time at which a plurality of vehicles in the combination of FIG. . Explanatory diagram showing a calculation example (estimation example) of the entry time at which the vehicles enter the predicted confluence area and the arrival time at which the confluence is reached when the plurality of vehicles in the combination of FIG. 10C are moving toward the confluence. . Explanatory diagram showing a calculation example (estimation example) of the entry time at which the vehicles enter the predicted confluence area and the arrival time at which the confluence is reached when the plurality of vehicles in the combination of FIG. 10C are moving toward the confluence. . 4 is a flowchart showing another example of the vehicle collision possibility determination process for a vehicle traveling on a merging side road according to the embodiment;

Embodiments of the present invention will be described below with reference to the drawings.
A device according to an embodiment described in this document is a collision possibility determination device that determines the possibility of collision between vehicles when vehicles merge onto the main line of an expressway.

In the present embodiment, a case will be described in which the mobile body that is the object of the collision possibility determination is a vehicle traveling on a road that is a travel route on the ground, but there are no particular restrictions on the type of mobile body and the type of travel route. For example, vehicles are automobiles, trucks, buses, and motorcycles. The vehicle may be a vehicle that has an automatic driving function, or a manually operated vehicle that does not have an automatic driving function. In addition, the mobile object to be subjected to collision possibility determination may be a vehicle on the ground, or a mobile object such as a flying object that can fly and move along a movement route in the sky above a predetermined altitude. In addition, the moving body is an underground moving body that moves along an underground movement path, a water moving body such as a ship that can move along a movement path on water (e.g., sea), or an underwater movement path (e.g., in the sea). It may be an underwater mobile such as a diving robot.

Further, in the present embodiment, the collision possibility between two vehicles (moving bodies) is determined, but the number of moving bodies subject to the collision possibility determination may be three or more.

FIG. 1 is an explanatory diagram showing an example of the overall configuration of a collision possibility determination system according to this embodiment. In FIG. 1, the collision possibility determination system of the present embodiment is configured from a merging side road 93 of a main road 91, 92 of a road 90 such as an expressway, which is a movement route on the ground on which a vehicle 30A as a moving body is traveling. A collision possibility determination device 10 is provided for determining the possibility of a collision between moving bodies when a vehicle 30B as another moving body joins. The collision possibility determination system may include a plurality of moving bodies such as vehicle 30A and vehicle 30B.

In FIG. 1, the main lane of road 90 has a driving lane 91 and an overtaking lane 92 . Vehicles 30A and 30C are traveling on the driving lane 91, and vehicles 30E and 30F are traveling on the passing lane 92. The merging side road 93 is in contact with the driving lane 91 of the main roadway in the merging possible range Wx. The vehicles 30B and 30D are traveling on the merging side road 93 toward the main roadway. In addition, in the following description, the vehicle 30 is used when the description is common to each vehicle.

The collision possibility determination device 10 of the present embodiment is provided, for example, in the base station 16 of the mobile communication network 15, and performs various data processing transmitted and received with the communication terminal device 31 of the vehicle 30 via the base station 16. It is an MEC (Multi-access Edge Computing) device capable of performing A collision possibility determination device (hereinafter referred to as “MEC server”) 10 may be provided at a node between the base station 16 and the core network of the mobile communication network 15 or outside the core network.

A base station 16 forms one or more cells (sectors, also called sector cells). The cells may be two-dimensionally formed on the ground or the sea, or three-dimensionally formed from the sky toward the ground or the sea. A cell may be a macrocell, a small cell, a femtocell, a picocell, a large cell, and so on. A plurality of cells may constitute a cellular structure distributed so as to be adjacent to each other two-dimensionally or three-dimensionally, or may constitute a hierarchical cell structure in which a part or all of them overlap hierarchically. . The base station 16 is a macrocell base station, a small cell base station, a femtocell base station, a picocell base station, a large cell base station, a fixed base station fixedly installed on the ground or the like, or a mobile station that can move on the ground, on the sea, in the sky, or the like. type base station or the like. The base station 16 may be a wireless communication device called eNodeB (evolved Node B: eNB), gNodeB (gNB), en-NodeB (en-gNB), access point, or the like.

A communication terminal device 31 of the vehicle 30 functions as a user equipment (UE) that can be used as a mobile communication service subscriber. A communication terminal device (hereafter also referred to as “UE”) 31 is, for example, an in-vehicle device installed in the vehicle 30 (for example, a device incorporated as part of a navigation device). The UE 31 of the vehicle 30 may be a device carried or worn by a user (eg, driver or passenger) within the vehicle 30 . The UE 31 may be a wireless communication device called a user terminal, terminal, terminal device, mobile station, mobile device, or the like.

The UE 31 of the vehicle 30 may have a function capable of close proximity wireless communication with other vehicles in the vicinity through vehicle-to-vehicle communication (for example, short-range wireless communication such as Sidelink (PC-5)).

The MEC server 10 of this embodiment may have a function of communicating with a user's communication terminal device located outside the vehicle 30 via the base station 16 . A user's communication terminal device is a user device (UE) such as a smart phone that can be used as a subscriber of a mobile communication service, and is a wireless communication device called a user terminal, terminal, terminal device, mobile station, mobile device, or the like. may

The UE 31 of the vehicle 30 and the UE outside the vehicle 30 are IoT devices, AR (Augmented Reality) devices, VR (Virtual Reality) devices, MR (Mixed Reality) devices or smart It can be a device. In addition, the UE is a glasses-type device (eg, AR glasses, VR glasses, MR glasses, smart glasses), a watch-type device (eg, smart watch), etc. that has a function of acquiring current location information and a communication function. good. Also, the UE may be a GNSS (Global Navigation Satellite System) tracker, a security buzzer, a pedometer, etc. having a function of acquiring current location information and a communication function.

The UE 31 of the vehicle 30 periodically (periodically, for example) or irregularly transmits vehicle information as mobile body information to the MEC server 10 at a predetermined frequency. The vehicle information includes position information and speed information indicating the current position of the vehicle 30 (UE31). The “velocity” of the vehicle 30 is a vector quantity represented by the direction and speed (=absolute value and magnitude of velocity) of movement of the vehicle 30 (UE 31). The vehicle information may include a vehicle ID as identification information of the vehicle 30 or a terminal ID as identification information of the UE 31 . The vehicle information may also include acceleration information and yaw rate information of the vehicle 30 (UE31). The yaw rate is the rate of change in the yaw angle when the vehicle 30 turns, and is the rotational angular velocity around the vertical axis passing through the center of gravity of the vehicle 30 .

The position information indicating the current position of the vehicle 30 (UE31) can be calculated, for example, based on the output (positioning result) of a GNSS (Global Navigation Satellite System) receiver provided in the UE31. In addition to the GNSS receiver, the UE 31 may also include at least one of a gyroscope (also referred to as a "rate gyro" or "gyro sensor"), an acceleration sensor, and a velocity sensor. Based on the output of this sensor, even if the current position measurement accuracy of the GNSS receiver of the vehicle 30 (UE31) is low, the moving route of the vehicle 30 (UE31) is calculated and the current position of the vehicle 30 (UE31) is accurately determined. can be estimated. Further, the acceleration and yaw rate of the vehicle 30 may be calculated, and the posture and orientation of the vehicle 30 may be estimated based on the outputs of the sensors. These calculation results and estimation results may be included in the vehicle information transmitted to the MEC server 10 .

The frequency of transmission of vehicle information from the UE 31 of the vehicle 30 to the MEC server 10 is, for example, a period of several milliseconds to several tens of seconds, and is used to determine the possibility of vehicle collision. The transmission frequency of vehicle information may be changed according to the degree of risk of vehicle collision. For example, during times or areas when the risk of vehicle collisions is low, the transmission frequency of vehicle information is set to be low, and during times or areas when the risk of vehicle collisions is high, the transmission frequency of vehicle information is set to be high. good too.

The collision possibility determination system is a map information database (DB) device that manages map information including road information such as the position, shape and width W of the road (lane) 90, the main roads 91 and 92, and the junction side road 93. map server 11. In the example of FIG. 1, the map server 11 is provided in the mobile communication network 15, but the map server 11 is provided in a MEC device provided in the base station 16 or in a node between the base station 16 and the core network of the mobile communication network 15. It may be configured with an MEC device. Also, the map server 11 may be configured integrally with the MEC server 10 .

The roadway of the road 90 in the map information managed by the map server 11 is managed by, for example, lanes divided into a plurality of straight roadway portions for each lane. The map server 11 sets, for each of the plurality of roadway lanes, a line passing through the center of the roadway lane or a starting point of a driving reference line (also called a "lane line"), which is a trajectory used as a guideline during driving. and the data of the coordinates of the end point, the coordinates of the point where multiple driving reference lines intersect (for example, confluence), the data of the coordinates of the range where multiple lanes meet, the width of each lane, etc. are stored. are doing. In addition, in order to represent a curvilinear road such as a curve, the driving reference line may have a plurality of points between its start point and end point, and a single driving reference line may be composed of a plurality of line segments. .

In the case of the road 90 in FIG. Data of the coordinates of the start point and the end point of the road 903, data of the coordinates defining the possible merging range Wx where the merging side road 93 contacts the driving lane 91 of the main road, etc. are stored. Here, the coordinates that define the possible merging range Wx are, for example, the coordinates of the starting point and the end point of the driving reference line 901 of the driving lane 91 in the possible merging range Wx, and the driving reference line of the merging side road 93 in the possible merging range Wx. 903 are the coordinates of the start and end points.

Further, the map server 11 may store the data of the coordinates of the point where the reference driving line 901 of the driving lane 91 and the reference driving line 903 of the merging side road 93 intersect as the data of the coordinates of the merging point Px. good.

FIG. 2 is a block diagram showing an example of main functions of the MEC server 10 according to this embodiment. In FIG. 2 , the MEC server 10 includes a vehicle information acquisition unit 101 , an information storage unit (DB: database) 102 , a determination processing unit 103 , a determination result notification unit 104 and a map information acquisition unit 105 .

The MEC server 10; It may be configured to communicate with the NW-RTK positioning core system (also referred to as “cloud RTK system” or “server RTK”) and cooperate with the NW-RTK positioning core system. Here, the RTK (real-time kinematic) positioning method uses a reference station (fixed station) placed at a known position to receive radio waves from satellites of the GNSS (Global Navigation Satellite System) and determine the position of the positioning target. This is a positioning method that performs measurements in real time. In this RTK positioning method, for example, the carrier wave observation data of the reference station that received the radio wave from the satellite, the carrier wave observation data of the positioning target that received the radio wave from the artificial satellite, and the positioning correction information determined in advance by the initialization process Based on this, the high-precision position coordinates of the positioning target are calculated. In the NW-RTK positioning core system (cloud RTK system), a server provided on a network accessible from a positioning target (for example, a terminal device such as a UE) receives carrier wave observation data (raw data) from the positioning target. , and the RTK method to calculate high-precision position coordinates of a positioning target. According to the NW-RTK positioning core system, even if the terminal device such as the UE does not have high-precision positioning means for calculating high-precision position information by the RTK method, the terminal device such as the UE is the centimeter of its current position. High-precision location information for orders can be obtained.

The vehicle information acquisition unit 101 functions as information acquisition means for acquiring vehicle information including the current positions and speeds of the plurality of vehicles 30A and 30B moving toward the junction Px on the road 90 at a predetermined frequency. For example, the vehicle information acquisition unit 101 receives and acquires vehicle information including position information and speed information of the current position of the UE 31 of the vehicle 30 from the UE 31 via the base station 16 . The vehicle information acquisition unit 101 may pass the location information to the NW-RTK positioning system (cloud RTK system) and receive the centimeter-level location information calculation result.

The information storage unit 102 stores the position information received from the UEs 31 of the plurality of vehicles 30 in association with the vehicle ID, which is the identification information of the vehicles 30 . The information storage unit 102 stores the map information of the monitored area received from the map server 11 . Note that the map information of the monitoring target area may be stored in advance in the information storage unit 102 without being acquired from the map server 11 .

The determination processing unit 103 functions as the following units (1) to (3) when a computer or processor of the MEC server 10 executes a predetermined program.
(1) For each of the plurality of vehicles 30A and 30B traveling on the road 90 (the main roads 91 and 92 and the merging side road 93), based on the vehicle information and information on the acquisition frequency of the information, a merging point Region estimating means for estimating confluence prediction regions 70A, 70B indicating error ranges of predicted arrival positions of vehicles 30A, 30B in Px.
(2) For each of the plurality of vehicles 30A and 30B, based on the current position and speed information of the vehicles 30A and 30B, the passage time zone 80A (81A and 81B ) and 80B (81B, 82B).
(3) Judgment means for judging the possibility of collision of the plurality of vehicles 30A, 30B based on the overlap of the passage time zones 80A (81A, 81B) and 80B (81B, 82B) between the plurality of vehicles 30A, 30B .

The determination result notification unit 104 notifies the UE 31 of the vehicle 30 (the vehicle 30A, the vehicle 30B, or both) of the information on the determination result of the possibility of collision determined by the determination processing unit 103 via the base station 16. function as a means to The determination result information is, for example, information indicating a determination result that there is a possibility of a vehicle collision at the time of merging, or information indicating a determination result that there is no possibility of a vehicle collision at the time of merging. The determination result notification unit 104 notifies the UE possessed or worn by the user (driver or passenger) using the vehicle 30 (vehicle 30A, vehicle 30B, or both) to the determination result of the possibility of collision. can be sent to notify you.

Based on the position information received from the UE 31 of the vehicle 30, the map information acquisition unit 105 acquires map information including the coordinate data of the start point, end point, and intersection (merging point) of the driving reference line of the roadway lane of the road 90 from the map server. 11.

FIG. 3 is a block diagram showing an example of main functions of a communication terminal device (UE) 31 of a vehicle 30 according to this embodiment. UE 31 of vehicle 30 includes measurement unit 301 , information storage unit 302 , vehicle information transmission unit 303 , determination result reception unit 304 , and determination result output unit 305 .

The measurement unit 301 measures and acquires information on the current position and speed of the vehicle 30 (UE 31). The measurement unit 301, for example, based on the information of the output of at least one of the GNSS receiver, the gyroscope, the acceleration sensor, the speed sensor, and the magnetic sensor provided in the vehicle body, the in-vehicle device, or the UE 31, the vehicle 30 (UE 31) Calculate current position (latitude, longitude and altitude) and speed information. The measurement unit 301 may also measure and acquire information on the acceleration and yaw rate of the vehicle 30 (UE 31). Also, the current location of the UE 31 may be centimeter-level location information with an accuracy of several centimeters. The centimeter-level location information may be acquired in cooperation with, for example, the NW-RTK positioning core system (cloud RTK system).

The information storage unit 302 stores information such as the current position and speed of the vehicle 30 (UE 31 ) measured by the measurement unit 301 . The information storage unit 302 also stores the determination result of the vehicle collision possibility received from the MEC server 10 .

The vehicle information transmission unit 303 transmits vehicle information including the current position and speed of the vehicle 30 (UE 31 ) to the MEC server 10 via the base station 16 . The vehicle information may further include information on the acceleration and yaw rate of the vehicle 30 (UE31), user identification information (user ID), and the like.

The determination result receiving unit 304 receives the determination result of the possibility of vehicle collision determined by the MEC server 10 from the MEC server 10 via the base station 16 .

The determination result output unit 305 outputs the determination result of the vehicle collision possibility received from the MEC server 10 as image information or sound information such as voice, and outputs the result to the user (for example, the driver, the passenger, or both) in the vehicle 30. ). The determination result output unit 305 may have a function of transmitting the determination result of the vehicle collision possibility to the surrounding vehicles 30 by inter-vehicle communication (for example, short-range wireless communication such as Sidelink (PC-5)). good. If the vehicle 30 has an automatic driving function, the determination result output unit 305 may notify the automatic driving control unit of the vehicle 30 of the vehicle collision possibility determination result.

FIG. 4 is an explanatory diagram showing an example of the driving reference lines 901 and 903, the merging point Px, and the predicted merging areas 70A and 70B used in the vehicle collision possibility determination process in the MEC server 10 according to the embodiment. In FIG. 4 , the confluence Px is a point where a reference driving line 901 of the main roadway (driving lane) 91 of the road 90 and a reference driving line 903 of the merging side road 93 intersect. Confluence prediction regions 70A and 70B indicating error ranges of predicted arrival positions of vehicles 30A and 30B when each of vehicles 30A and 30B reaches confluence Px are estimated and determined so as to include this confluence Px.

The shapes of the predicted confluence areas 70A and 70B including the confluence point Px may be changed depending on whether the vehicles 30A and 30B to be determined are traveling in automatic driving mode or manual driving mode. For example, when the vehicles 30A and 30B are driving automatically, the positional error in the lateral direction intersecting the driving reference lines 901 and 903 is small, so as shown in FIG. error circles) are used. In this case, the shape of the predicted confluence areas 70A and 70B may be circular, elliptical or oval in which the confluence point Px is located in the center.

On the other hand, when the vehicles 30A and 30B are manually operated, the position error in the lateral direction intersecting the driving reference lines 901 and 903 is large. Alternatively, it is also possible to use predicted confluence areas 70A and 70B of circular arc triangles with the base being a partial arc of an ellipse and the current positions of the vehicles 30A and 30B being the vertices. In this case, the arc-triangular merging predicted areas 70A and 70B may be limited within the merging possible range Wx as described later.

Also, the sizes of the predicted merging areas 70A and 70B may be changed according to at least one of the speed of the vehicles 30A and 30B to be determined and the frequency of vehicle information acquisition (the frequency of upload transmission from the UE 31). For example, the higher the speed of the vehicles 30A and 30B or the longer the vehicle information acquisition frequency, the greater the error when each of the vehicles 30A and 30B reaches the merging point Px. Enlarge. On the other hand, the lower the speed of the vehicles 30A and 30B or the lower the frequency of acquisition of vehicle information, the smaller the error when each of the vehicles 30A and 30B reaches the junction Px. Make smaller.

FIGS. 5A and 5B are explanatory diagrams showing examples of predicted merging areas 70A and 70B when a plurality of vehicles 30A and 30B are traveling at different speeds, respectively, according to the embodiment. In both figures, the cycle of acquisition frequency of vehicle information is 1 second. FIG. 5(a) shows an example of a circular predicted merging area 70A for a vehicle 30A that is automatically driven at a speed v _A =60 [km/h]. In this case, the predicted confluence area 70A has a diameter D _A of, _for example, about 40 [m]. It has lengths L _AF and L _AB of [m]. FIG. 5(b) shows an example of a circular predicted merging area 70B for the vehicle 30B that is automatically driven at v _B =30 [km/h] per hour. In this case, the predicted confluence area 70B has a diameter D _B of, for _example , about 20 [m]. It has lengths L _BF and L _BB of [m].
Note that machine learning may be used to determine the size of the predicted confluence region. Specifically, a learned model is built using training data that links the speed of each vehicle, the frequency of vehicle information acquisition, the set merging prediction area, etc., with information on whether or not a collision actually occurred. After that, the speed and the like of each vehicle may be input to the learned model, and the size of the optimum predicted merging area in which collision accidents do not occur may be output.

FIG. 6 shows intrusion times T A1 , T B1 , T A2 , T B2 and intrusion times T _A1 , T _B1 , T _A2 , T _B2 at which a plurality of vehicles 30A, 30B enter the predicted confluence areas 70A, 70B while moving toward the confluence point Px according to the embodiment. FIG. 11 is an explanatory diagram showing a calculation example (estimation example) of arrival times T _A and T _B at which a confluence point Px is reached; Note that FIG. 6 is an example in which the plurality of vehicles 30A and 30B moving toward the confluence Px are all automatically driven vehicles.

In FIG. 6, with the current position _x0 of each of the vehicles 30A and 30B as the origin, the position _coordinates ( x _A1 , x _B1 ) and the velocities v _A and v _B of the vehicles 30A and 30B, the entry times T _1A and T _1B at which the vehicles 30A and 30B enter the predicted confluence area 70A are calculated (estimated). ) is done.

Further, the distance from the current position x ₀ of the vehicles 30A and 30B to the position coordinates (x _A2 , x _B2 ) of the outer edge of the predicted merging area 70B of the vehicle 30B along the reference driving lines 901 and 903, and the distance of the vehicles 30A and 30B Entry times T _2A and T _2B at which vehicles 30A and 30B enter predicted confluence area 70B are calculated (estimated) based on velocities v _A and v _B .

Also, the distance from the current position x ₀ of the vehicles 30A, 30B to the position coordinates (x _A , x _B ) of the merging point Px along the driving reference lines 901, 903 and the velocities v _A , v _B of the vehicles 30A, 30B , the arrival times T _A and T _B at which the vehicles 30A and 30B reach the junction Px are calculated (estimated).

In the calculation (estimation) of the intrusion times T _A1 , T _B1 , T _A2 , T _B2 and the arrival times T _A , T _B , in addition to the velocities v _A , v _B of the vehicles 30A, 30B, At least one of acceleration and yaw rate may be used.

FIG. 7 is an explanatory diagram showing an example of passage time zones 80A and 80B of predicted confluence areas 70A and 70B used for determining the possibility of both collisions according to the embodiment. In FIG. 7, the passage time zone 80A during which the vehicle 30A traveling in the driving lane 91 of the main roadway passes through the predicted merging areas 70A and 70B is from the time _T1A when the vehicle 30A enters the predicted merging area 70A to the merging point Px. It is a time zone up to the arrival time _TA , and is composed of a first transit time zone 81A and a second transit time zone 82A. The first passing time zone 81A is a time zone from the entry time _T1A of the vehicle 30A into the confluence prediction area 70A to the entry time _T2A into the confluence prediction area 70B. 30B is a medium time period. The second passing time period 82A is a time period from the entry time _T2A into the confluence prediction area 70B to the arrival time _TA at the confluence point Px, and is a time period in which the possibility of collision with the vehicle 30B is relatively high. is.

Further, the passage time period 80B during which the vehicle 30B traveling on the merging side road 93 passes through the predicted merging areas 70A, 70B is the time from the time T1B when the vehicle 30B enters the predicted merging area 70A to the time when the vehicle _30B reaches the merging point Px. It is a time zone up to _TB , and is composed of a first transit time zone 81B and a second transit time zone 82B. The first passing time period 81B is a time period from time _T1B when the vehicle 30B enters the predicted confluence area 70A to time _T2B when the vehicle 30B enters the predicted confluence area 70B. collision probability is medium. The second passage time period 82B is a time period from the entry time _T2B into the confluence prediction area 70B to the arrival time _TB at the confluence point Px, and is a time period in which the possibility of collision with the vehicle 30A is relatively high. is.

The collision possibility of the vehicles 30A and 30B when the vehicle 30B merges can be determined from the overlap on the time axis of the passage time zones 80A and 80B of the plurality of vehicles 30A and 30B.

FIG. 8 is an explanatory diagram showing an example of six types of collision possibility determination based on overlap on the time axis of passage time zones 80A and 80B of a plurality of vehicles 30A and 30B according to the embodiment.
In FIG. 8, in determination example 1 and determination example 6, the passage time zones 80A and 80B of the vehicles 30A and 30B do not overlap on the time axis, so it is determined that the collision possibility of the vehicles 30A and 30B is low.

In Determination Example 2, the first transit time slot 81A in which the vehicle 30A passes through 80A has a medium collision possibility, and overlaps the vehicle 30B transit time slot 80B on the time axis. Since the two passing time zones 82A and 82B do not overlap each other, the collision possibility of the vehicles 30A and 30B is determined to be moderate.

In Determination Example 5, the first transit time slot 81B in which the vehicle 30B passes through the vehicle 30B has a medium collision possibility, and overlaps the vehicle 30A transit time slot 80A on the time axis. Since the two passing time zones 82A and 82B do not overlap each other, the collision possibility of the vehicles 30A and 30B is determined to be moderate.

In determination examples 3 and 4, the second passage time zones 82A and 82B in which the collision probability of the vehicles 30A and 30B is high overlap on the time axis, so it is determined that the collision probability of the vehicles 30A and 30B is high. .

FIG. 9 is a flowchart showing an example of vehicle collision possibility determination processing in the MEC server (collision possibility determination device) 10 according to the embodiment.
In FIG. 9, the MEC server 10 identifies the coordinates of the confluence point Px based on the driving reference lines 901 and 903 of the main roadway 91 and the confluence side road 93 of the road 90 included in the map information of the target area. From the vehicle 30A on the main road 91 (hereinafter referred to as the "main vehicle") and the vehicle 30B on the merging side road 93 (hereinafter also referred to as the "merging vehicle") 30B, which are the targets of the collision possibility determination and are heading toward the point Px, the current Vehicle information including position and speed information is received and acquired (S101).

Next, the MEC server 10 calculates the predicted merging areas 70A and 70B at the merging point Px based on the current position and speed information of each vehicle 30A and 30B for each of the target vehicles, namely the main line vehicle 30A and the merging vehicle 30B. It is estimated and determined (S102). At least one of the acceleration and yaw rate information of each vehicle 30A, 30B may be used in addition to the current position and speed information of each vehicle 30A, 30B to estimate the confluence prediction areas 70A, 70B.

Next, the MEC server 10 determines whether the main line vehicle 30A and the merging vehicle 30B, which are the target vehicles, are aligned with the driving reference lines 901 and 903 as illustrated in FIGS. 6 and 7 described above. Passing time zones 80A (81A, 82A) and 80B (81B, 82B) on the time axis passing through the expected confluence areas 70A, 70B (or within the confluence possible area) are calculated (S103).

Next, as illustrated in FIG. 8 described above, the MEC server 10 calculates passage time zones 80A (81A, 82A) and 80B on the time axis calculated for each of the target vehicles, namely the main line vehicle 30A and the merging vehicle 30B. It is determined whether (81B, 82B) overlap between vehicles (S104). Here, if there is an overlap between the passing time zones 80A (81A, 82A) and 80B (81B, 82B) (YES in S104), the MEC server 10 determines that the main line vehicle 30A and the merging vehicle 30B collide when the merging vehicle 30B merges. It is determined that there is a possibility of doing so (S105). On the other hand, if the passing time zones 80A (81A, 82A) and 80B (81B, 82B) do not overlap (NO in S104), the MEC server 10 determines that the main line vehicle 30A and the merging vehicle 30B will collide when the merging vehicle 30B joins. It is determined that there is no possibility (S106).

Next, when the MEC server 10 determines that there is a possibility of collision, the MEC server 10 transmits and notifies each of the main line vehicle 30A and the merging vehicle 30B, which are the target vehicles, of the determination result (S107). In addition to transmitting the determination results, the MEC server 10 may transmit control information for automatic driving that avoids collisions to each of the main line vehicle 30A and the merging vehicle 30B. The transmission (notification) of the determination result may also be performed when it is determined that there is no possibility of collision. Also, the MEC server 10 may transmit the determination result to the UE possessed by or worn by the driver or fellow passenger of each vehicle.

When the main line vehicle 30A and the merging vehicle 30B receive the determination result of the possibility of collision from the MEC server 10, they display a collision warning on the display unit (for example, DA (display audio)) of the in-vehicle device. Each of the vehicles 30A and 30B may output a sound such as a voice to notify the collision warning instead of or in addition to the display of the collision warning. Further, when each of the vehicles 30A and 30B receives the control information from the MEC server 10, the vehicles 30A and 30B execute automatic operation control so as to avoid a collision based on the control information.

When at least one of the main line vehicle 30A and the merging vehicle 30B is a manually operated vehicle, in addition to output such as a collision warning display, the vehicle outputs a warning level (collision possibility), a merging point (collision prediction point) The distance to the confluence point (collision prediction point) and the time (seconds) to reach the confluence point may be displayed. Here, as the warning level, a first warning level with a high collision possibility and a second warning level with a low collision possibility may be set. For example, in the case of the determination result of FIG. 8 described above, the first warning level is set for determination 3 or determination 4, and the second warning level is set for determination 2 or determination 5.

Further, when the MEC server 10 receives moving image data of a forward image (real-time moving image) captured by an in-vehicle camera from one of the main vehicle 30A and the merging vehicle 30B and transmits the moving image data to the other vehicle, the moving image data is received. In addition to output such as display of collision warning, the vehicle displays a front image (real-time video) of the vehicle with a possibility of collision on the display unit (e.g. DA) of the vehicle's in-vehicle device, and manually performs collision avoidance. The driver may be prompted to drive.

Figures 10(a)-(d) show a plurality of vehicles 30A. 30B is an explanatory diagram showing an example of predicted confluence regions 70A and 70B when combinations of manual operation and automatic operation of 30B are different from each other; FIG.

FIG. 10(a) is an example of a case where a main line vehicle 30A and a merging vehicle 30B are traveling in automatic operation along driving reference lines 901 and 903, respectively. Each vehicle 30A. The predicted confluence areas 70A and 70B for 30B are circular areas in which the confluence point Px is located in the center. The shape of the area may be oval or oblong.

FIG. 10(b) is an example of a case where the main line vehicle 30A and the merging vehicle 30B are both manually operated. The predicted merging areas 70A and 70B for the respective vehicles 30A and 30B in this example are circular arc triangles with the base being a partial arc of a circle, ellipse or ellipse in which the merging point Px is located in the center, and the current position of the vehicle being the vertex. area. Information on the yaw rates of the main line vehicle 30A and the merging vehicle 30B may be used to estimate the area of the circular arc triangle.

FIG. 10(c) shows an example in which the main line vehicle 30A is automatically driven and the merging vehicle 30B is manually driven. The predicted merging area 70A for the main line vehicle 30A in this example is a circular (elliptical or oval) area in which the merging point Px is located in the center. is the area of

FIG. 10(d) is an example in which the main line vehicle 30A is manually operated and the merging vehicle 30B is automatically operated. The predicted merging area 70A for the main line vehicle 30A in this example is an arc-triangular area, and the predicted merging area 70A for the merging vehicle 30B is circular (elliptical or elliptical) with the merging point Px positioned in the center. is the area of

FIG. 11 shows entry times T _A1 and T _B1 at which the plurality of vehicles 30A and 30B in the combination of FIG. FIG. 4 is an explanatory diagram showing a calculation example (estimation example) of arrival times T _A and T _B at which Px is reached; Both the vehicles 30A and 30B of this example are manually driven.

In FIG. 11, with respect to the main line vehicle 30A, with the current position x ₀ as the origin, along the driving reference line 901 from the current position x ₀ of the main line vehicle 30A, the merging predicted area 70A of the main line vehicle 30A is within the possible merging range Wx. Intrusion in which the main line vehicle 30A enters a portion within the possible merging range Wx of the merging predicted area 70A based on the distance to the position coordinate (x _A1 ) of the vehicle side edge of the portion and the speed v _A of the main line vehicle 30A. Time _T1A is calculated (estimated).

On the other hand, for the merging vehicle 30B, with the current position x ₀ as the origin, the merging predicted area 70B of the merging vehicle 30B is drawn from the current position x ₀ of the merging vehicle 30B along the auxiliary reference line 903′ at the upper edge of the predicted merging area 70B. Based on the shortest distance to the position coordinate (x _B1 ) of the vehicle-side edge of the portion within the possible merging range Wx and the speed _vB of the merging vehicle 30B, the merging vehicle 30B determines the possible merging range of the predicted merging area 70B. A break-in time _T1B is calculated (estimated) for breaking into the portion within Wx.

FIG. 12 shows entry times T _A1 , T _B1 , T _A2 at which the plurality of vehicles 30A, 30B in the combination of FIG. , _{TB2 and a calculation example (estimation example) of the arrival times TA and TB at} which they reach the junction Px. The main line vehicle 30A in this example runs automatically, and the merging vehicle 30B runs manually.

In FIG. 12, with respect to the main line vehicle 30A, with the current position x ₀ as the origin, along the driving reference line 901 from the current position x ₀ of the main line vehicle 30A, the merging predicted area 70B of the merging vehicle 30B is within the possible merging range Wx. Based on the distance to the position coordinate (x _A1 ) of the vehicle side edge of the portion and the speed v _A of the main line vehicle 30A, the main line vehicle 30A enters the portion within the possible merging range Wx of the merging predicted area 70B. Time _T1A is calculated (estimated).

On the other hand, for the merging vehicle 30B, with the current position x ₀ as the origin, the merging predicted area 70B of the merging vehicle 30B is drawn from the current position x ₀ of the merging vehicle 30B along the auxiliary reference line 903′ at the upper edge of the predicted merging area 70B. Based on the shortest distance to the position coordinate (x _B1 ) of the vehicle-side edge of the portion within the possible merging range Wx and the speed _vB of the merging vehicle 30B, the merging vehicle 30B determines the possible merging range of the predicted merging area 70B. A break-in time _T1B is calculated (estimated) for breaking into the portion within Wx.

Furthermore, the distance from the current position x ₀ of the main line vehicle 30A and the merging vehicle 30B to the position coordinates (x _A2 , x _B2 ) of the outer edge of the merging prediction area 70A of the main line vehicle 30A along the reference driving lines 901 and 903, and each Based on the velocities v _A and v _B of vehicles 30A and 30B, entry times T _2A and T _2B at which vehicles 30A and 30B enter predicted confluence area 70A are calculated (estimated).

Also, the distance from the current position x ₀ of the main line vehicle 30A and the merging vehicle 30B to the position coordinates (x _A , x _B ) of the merging point Px along the driving reference lines 901 and 903, and the speed v The arrival times T _A and T _B at _which the vehicles 30A and 30B reach the junction Px are calculated (estimated) based on A and _vB .

FIG. 13 shows entry times T _A1 , T _B1 , T _A2 at which the plurality of vehicles 30A, 30B in the combination of FIG. , _{TB2 and a calculation example (estimation example) of the arrival times TA and TB at} which they reach the junction Px. The main line vehicle 30A of the present example is driven manually, and the merging vehicle 30B is driven automatically.

In FIG. 13, the position of the vehicle side edge of the portion within the possible merging range Wx of the expected merging area 70A of the main line vehicle 30A along the driving reference lines 901 and 903 from the current position _x0 of the main line vehicle 30A and the merging vehicle 30B. Based on the distance to the coordinates (x _A1 , x _B1 ) and the velocities v _A and v _B of the vehicles 30A and 30B, the vehicles 30A and 30B enter the possible merging range Wx of the predicted merging area 70A. Intrusion times T _1A and T _B1 are calculated (estimated).

Furthermore, the distance from the current position x ₀ of the main line vehicle 30A and the merging vehicle 30B to the position coordinates (x _A2 , x _B2 ) of the outer edge of the merging prediction area 70B of the merging vehicle 30B along the reference driving lines 901 and 903, and each Based on the velocities v _A and v _B of the vehicles 30A and 30B, entry times T _2A and T _2B at which the vehicles 30A and 30B enter the predicted confluence area 70B are calculated (estimated).

Also, the distance from the current position x ₀ of the main line vehicle 30A and the merging vehicle 30B to the position coordinates (x _A , x _B ) of the merging point Px along the driving reference lines 901 and 903, and the speed v The arrival times T _A and T _B at _which the vehicles 30A and 30B reach the junction Px are calculated (estimated) based on A _and vB.

FIG. 14 is a flowchart showing another example of the vehicle collision possibility determination process for the vehicle 30B traveling on the merging side road 93 according to the present embodiment. This vehicle collision possibility determination process can be executed by an in-vehicle device including the UE 31 of the vehicle 30B and a computer (or processor). In FIG. 14, the description of the processing common to FIG. 9 is omitted.

In FIG. 14, the in-vehicle device of the merging vehicle 30B communicates with the MEC server 10 via the base station 16 based on the direction instruction (winker) operation for merging onto the main roadway (driving lane) 91. Network communication mode A vehicle-to-vehicle communication mode in which vehicle-to-vehicle communication (for example, short-range wireless communication such as Sidelink (PC-5)) communicates with a vehicle (main vehicle) 30A traveling on the main roadway (driving lane) 91. (S201).

Next, the in-vehicle device of the merging vehicle 30B requests the vehicle information including the current position and speed information of the main line vehicle 30A from the main line vehicle 30A via inter-vehicle communication (S202). The vehicle information including the current position and speed information of the main line vehicle 30A is received and acquired from the vehicle 30A (S203).

Next, the in-vehicle device of the merging vehicle 30B, based on the driving reference lines 901 and 903 of the main roadway 91 of the road 90 and the merging side road 93 included in the map information of the target area stored in advance in the own device, The coordinates of the merging point Px are specified, and based on the current position and speed information of the main line vehicle 30A and the own vehicle 30B heading toward the merging point Px, the predicted merging areas 70A and 70B at the merging point Px are estimated and determined. (S204). At least one of the acceleration and yaw rate information of each vehicle 30A, 30B may be used in addition to the current position and speed information of each vehicle 30A, 30B to estimate the confluence prediction areas 70A, 70B.

Next, the in-vehicle device of the merging vehicle 30B, as illustrated in FIGS. , within the convergence possible region) on the time axis, the passage time zones 80A (81A, 82A) and 80B (81B, 82B) are calculated (S205).

Next, as exemplified in FIG. 8 and the like, the in-vehicle device of the merging vehicle 30B calculates passage time zones 80A (81A, 82A) and 80B ( 81B, 82B) overlap between the vehicles (S206). Here, if there is an overlap between the passing time zones 80A (81A, 82A) and 80B (81B, 82B) (YES in S206), the in-vehicle device of the merging vehicle 30B controls the main line vehicle 30A and the own vehicle when the own vehicle 30B merges. 30B may collide (S207). On the other hand, if the passing time zones 80A (81A, 82A) and 80B (81B, 82B) do not overlap (NO in S206), the in-vehicle device of the merging vehicle 30B controls the main line vehicle 30A and the own vehicle 30B when the own vehicle 30B merges. determines that there is no possibility of collision (S208).

Next, when the in-vehicle device of the merging vehicle 30B determines that there is a possibility of collision, it notifies the main vehicle 30A of the determination result by transmitting it (S208). The transmission (notification) of the determination result may also be performed when it is determined that there is no possibility of collision.

When the merging vehicle 30B determines that there is a possibility of collision, it displays a collision warning on the display unit (eg, DA) of the in-vehicle device. Further, when the main line vehicle 30A receives the determination result indicating that there is a possibility of collision from the merging vehicle 30B, it displays a collision warning on the display unit (for example, DA) of the vehicle-mounted device.

The vehicle collision possibility determination process illustrated in FIG. 14 may be performed by a main vehicle traveling in the driving lane 91 or the passing lane 92 of the main road. In this case, the in-vehicle device including the UE and the computer (or processor) of the main line vehicle receives information on the merging vehicle traveling on the merging side road 93 from the merging vehicle via inter-vehicle communication, or from the MEC server 10, for example. (For example, information of direction indication (winker) operation for merging) is detected, the same processing as S202 to S209 in FIG. 14 is executed for the merging vehicle and own vehicle.

As described above, according to the present embodiment, when another vehicle 30B joins the main lanes 91 and 92 of the road 90 on which the vehicles 30A and 30B are traveling, the possibility of collision between the vehicles is determined in anticipation of the future. can do.

Further, according to this embodiment, the MEC server (collision possibility determination device) 10 is provided outside the base station 16 of the mobile communication network 15 or a node between the base station 16 and the core network or outside the core network. It is an MEC device, and can perform distributed processing for judging the possibility of a vehicle collision for UEs 31 of a plurality of vehicles 30 connected to a base station 16, thereby suppressing an increase in the load on the mobile communication network (core network) 15. can do.

In this embodiment, the MEC server (collision possibility determination device) 10 is a server capable of communicating with UEs (communication terminal devices) 31 of a plurality of vehicles (mobile bodies) 30 via the mobile communication network 15. good too. In this case, it is possible to centrally manage collision danger notifications for a plurality of vehicles.

Further, in the present embodiment, all or part of the functions of the MEC server (collision possibility determination device) 10 may be provided in the UE 31 of the vehicle (mobile body) 30 or an in-vehicle device having the UE 31 .

It should be noted that the processing steps and components of the collision probability determination device, server, map database device and system described herein may be implemented by various means. For example, these processes and components may be implemented in hardware, firmware, software, or any combination thereof.

For hardware implementation, means such as processing units used to implement the above steps and components in an entity (e.g., various wireless communication devices, eNode Bs, terminals, hard disk drives, or optical disk drives) are: One or more of an application specific integrated circuit (ASIC), digital signal processor (DSP), digital signal processor (DSPD), programmable logic device (PLD), field programmable gate array (FPGA), processor , controllers, microcontrollers, microprocessors, electronic devices, other electronic units designed to perform the functions described herein, computers, or combinations thereof.

Also, for firmware and/or software implementations, means such as processing units used to implement the above components may be programs (e.g., procedures, functions, modules, instructions) that perform the functions described herein. , etc.). In general, any computer/processor readable medium tangibly embodying firmware and/or software code means, such as a processing unit, used to implement the above steps and components described herein. may be used to implement For example, firmware and/or software code may be stored in memory and executed by a computer or processor, such as in a controller. The memory may be implemented within the computer or processor, or external to the processor. The firmware and/or software code may also be, for example, random access memory (RAM), read only memory (ROM), non-volatile random access memory (NVRAM), programmable read only memory (PROM), electrically erasable PROM (EEPROM). ), flash memory, floppy disk, compact disk (CD), digital versatile disk (DVD), magnetic or optical data storage devices, etc. good. The code may be executed by one or more computers or processors and may cause the computers or processors to perform certain aspects of the functionality described herein.

Also, the medium may be a non-temporary recording medium. Also, the code of the program is not limited to a specific format as long as it can be read and executed by a computer, processor, or other device or machine. For example, the program code may be source code, object code, or binary code, or may be a mixture of two or more of these codes.

Moreover, the description of the embodiments disclosed herein is provided to enable any person skilled in the art to make or use the present disclosure. Various modifications to this disclosure will be readily apparent to those skilled in the art, and the general principles defined herein are applicable to other variations without departing from the spirit or scope of this disclosure. This disclosure, therefore, is not to be limited to the examples and designs described herein, but is to be accorded the broadest scope consistent with the principles and novel features disclosed herein.

10: MEC server (collision possibility determination device)
11: map server 15: mobile communication network 16: base station 30: vehicle 30A: vehicle 30B: vehicle (merging vehicle)
30C-30F: vehicle 31: communication terminal equipment (UE)
70A, 70B: predicted merging areas 80A, 80B: passing time zones 81A, 81B: first passing time zone 82A, 82B: second passing time zone 90: road 91: driving lane of the main roadway 92: follow-up of the main roadway Overpass lane 93: Merging side road 101: Vehicle information acquisition unit 102: Information storage unit 103: Judgment processing unit 104: Judgment result notification unit 105: Map information acquisition unit 301: Measurement unit 302: Information storage unit 303: Vehicle information transmission unit 304: Determination result receiving unit 305: Determination result output unit 901: Driving reference line 902: Driving reference line 903: Driving reference line 903': Auxiliary reference line

Claims (17)

A collision possibility determination device for determining the possibility of collision between moving bodies,
an information acquiring means for acquiring, at a predetermined frequency, mobile body information including current positions and velocities of a plurality of mobile bodies moving toward a confluence of movement paths;
region estimation means for estimating a predicted merging region indicating an error range of predicted arrival positions of the moving bodies at the merging point based on the moving body information and the frequency information for each of the plurality of moving bodies;
time period calculation means for calculating a passage time period during which the moving bodies pass through the predicted confluence area based on information on the current position and speed of the moving bodies for each of the plurality of moving bodies;
determination means for determining a possibility of collision of the plurality of moving bodies based on the overlap of the passage time zones of the plurality of moving bodies;
A collision possibility determination device comprising: In the collision possibility determination device of claim 1,
The determining means determines that, among the plurality of passage time periods calculated for the plurality of moving bodies, a plurality of overlapping area passage time periods that pass through the overlapping area of the plurality of predicted confluence areas are between the plurality of moving bodies. A collision possibility determination device, characterized in that, when the plurality of moving bodies overlap each other, it is determined that there is a high possibility of collision between the plurality of moving bodies. In the collision possibility determination device according to claim 1 or 2,
The moving body information includes information on the acceleration and yaw rate of the moving body,
The collision possibility determination device, wherein the time zone calculation means calculates the passing time zone based on information on the current position and speed of the moving body and information on the acceleration and yaw rate of the moving body. In the collision possibility determination device according to any one of claims 1 to 3,
The determination result of the collision possibility is sent to the communication terminal device installed in at least one of the plurality of mobile bodies or the communication terminal device possessed or attached to the user using the at least one mobile body. A collision possibility determination device, further comprising notifying means for notifying. In the collision possibility determination device according to any one of claims 1 to 4,
A collision possibility determination device, wherein the determination result of the collision possibility is used for control for avoiding the collision in at least one of the plurality of moving bodies. In the collision possibility determination device according to any one of claims 1 to 5,
A collision possibility determination device, wherein the predicted confluence area is a circular, elliptical, or oval area in which the confluence point is located at the center. In the collision possibility determination device according to any one of claims 1 to 5,
The predicted confluence area is an area of an arc triangle having a base that is a partial arc of a circle, an ellipse, or an ellipse in which the confluence point is located at the center and a vertex that is the current position of the moving body. Possibility determination device. In the collision possibility determination device according to any one of claims 1 to 7,
The collision possibility determination device, wherein the passage time zone is a passage time zone in which the moving object passes through a portion within a range in which the moving object can merge in the predicted merging area. In the collision possibility determination device according to any one of claims 1 to 8,
A collision possibility determination device, wherein the determination of the confluence, the estimation of the predicted merge area, and the calculation of the passage time zone are performed based on position information of a reference line of the movement route in map information. In the collision possibility determination device according to any one of claims 1 to 9,
The collision possibility determination device is a base station of a mobile communication network, a node between the base station and the core network, or an MEC (Multi-access Edge Computing) device provided outside the core network. Collision possibility determination device. A moving object comprising the collision possibility determination device according to any one of claims 1 to 9. A communication terminal device comprising the collision possibility determination device according to any one of claims 1 to 9. A communication terminal device installed in a mobile body for which the possibility of collision at a junction is determined by the collision possibility determination device according to any one of claims 1 to 10, or communication carried or worn by a user in the mobile body. A terminal device,
information transmitting means for transmitting moving body information including the current position and speed of the moving body to the collision possibility determination device at the predetermined frequency;
a determination result receiving means for receiving, from the collision possibility determination device, a result of determination of the possibility of collision at the junction. A system for determining the possibility of a collision between moving bodies when another moving body joins a movement route on which the moving body is traveling,
11. A system comprising: the collision possibility determination device according to any one of claims 1 to 10; and the mobile communication terminal device. 15. The system of claim 14, wherein
A map database device that stores map information including information on the driving reference line of the moving route,
The system, wherein the collision possibility determination device acquires the position information of the driving reference line of the moving route from the map database device. A method for determining the possibility of collision between moving bodies,
Obtaining, at a predetermined frequency, moving body information including current positions and velocities of a plurality of moving bodies moving toward a confluence of movement paths;
estimating, for each of the plurality of moving bodies, a predicted confluence region indicating an error range of predicted arrival positions of the moving bodies at the confluence based on the moving body information and the frequency information;
calculating, for each of the plurality of moving bodies, a passage time period during which the moving bodies pass through the predicted confluence region based on information on the current position and velocity of the moving body;
Determining the possibility of collision of the plurality of moving bodies based on the overlap of the passage time zones of the plurality of moving bodies;
A method comprising: A program executed in a computer or processor provided in a device for determining the possibility of collision between moving bodies,
A program code for acquiring, at a predetermined frequency, mobile body information including current positions and velocities of a plurality of mobile bodies moving toward a confluence of movement paths;
program code for estimating a predicted confluence area indicating an error range of predicted arrival positions of the moving bodies at the confluence for each of the plurality of moving bodies based on the moving body information and the frequency information; ,
a program code for calculating, for each of the plurality of moving bodies, a passage time period during which the moving bodies pass through the predicted confluence region based on information on the current position and velocity of the moving body;
a program code for determining a possibility of collision of the plurality of moving bodies based on the overlap of the passing time zones of the plurality of moving bodies;
A program characterized by comprising:

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