阅读说明：本技术 驾驶辅助方法及驾驶辅助装置 (Driving assistance method and driving assistance device ) 是由 山口翔太郎 方芳 南里卓也 于 2019-03-27 设计创作，主要内容包括：本发明的驾驶辅助方法中,检测从与第一路径(21)不同的第二路径(22)驶入本车辆(20)行驶的第一路径(21)上的交叉路口的第一其他车辆(v1)(S4),并预测第一其他车辆(v1)是否在交叉路口内停止,在预测为在交叉路口内停止的情况下,预测第一其他车辆(v1)的停止位置(S7),并计算第一其他车辆(v1)停止在预测的停止位置的情况下的第一其他车辆(v1)的车身与第一其他车辆(v1)的周围物体之间或者第一其他车辆(v1)的车身与第一其他车辆(v1)的行驶车道的道路端部之间、即第一间隔的最小距离(d1)(S8),根据计算出的最小距离(d1),预测是否具有第一其他车辆(v1)的后续车辆即第二其他车辆(v2)从第一其他车辆(v1)的后方穿过第一间隔的可能性(S9、S12、S18)。(In a driving assistance method, a first another vehicle (v1) entering an intersection on a first route (21) on which a host vehicle (20) travels from a second route (22) different from the first route (21) is detected (S4), it is predicted whether the first another vehicle (v1) stops in the intersection, if it is predicted to stop in the intersection, a stop position of the first another vehicle (v1) is predicted (S7), a minimum distance (d1) between a vehicle body of the first another vehicle (v1) and a peripheral object of the first another vehicle (v1) or between a vehicle body of the first another vehicle (v1) and a road end of a traveling lane of the first another vehicle (v1), that is, a first interval, is calculated (S8), and it is predicted whether there is a first another vehicle (v1), that is, from a first another vehicle (v2), based on the calculated minimum distance (d 6853), it is predicted whether there is a second another vehicle (v1) having the first another vehicle (v1) that is a second vehicle (v 73742) traveling from the calculated minimum distance (d 6853) Possibility that the rear of the other vehicle (v1) passes through the first interval (S9, S12, S18).)

1. A driving assistance method characterized by comprising the steps of,

detecting a first other vehicle that enters an intersection on a first path traveled by the own vehicle from a second path different from the first path,

predicting whether or not the first another vehicle stops in the intersection, and predicting a stop position of the first another vehicle when the first another vehicle is predicted to stop in the intersection,

calculating a minimum distance of a first interval, which is an interval between the body of the first another vehicle and a peripheral object of the first another vehicle or between the body of the first another vehicle and a road end of a travel lane of the first another vehicle in a case where the first another vehicle is stopped at the predicted stop position,

predicting, based on the calculated minimum distance, a likelihood of whether a second other vehicle, which is a succeeding vehicle having the first other vehicle, passes through the first interval from behind the first other vehicle.

2. The driving assistance method according to claim 1,

when the priority of the own vehicle traveling on a route passing through an intersection is lower than the priority of the own vehicle traveling on the traveling lane of the first another vehicle, it is predicted whether or not there is a possibility that the second another vehicle passes through the first gap from behind the first another vehicle.

3. The drive assist method according to claim 1 or 2,

when the calculated minimum distance is equal to or less than a predetermined threshold value, it is predicted that there is no possibility that the second another vehicle passes through the first interval from behind the first another vehicle.

4. The drive assist method according to any one of claims 1 to 3,

detecting a vehicle width of the second another vehicle,

when the detected vehicle width of the second another vehicle is longer than the calculated minimum distance, it is predicted that there is no possibility that the second another vehicle passes through the first interval from behind the first another vehicle.

5. The drive assist method according to any one of claims 1 to 4,

in a case where there is an obstacle on a travel route of the first another vehicle, it is predicted that the first another vehicle stops within the intersection.

6. The driving assistance method according to claim 5,

the obstacle on the course of the first another vehicle is a preceding vehicle of the first another vehicle, a congested vehicle ahead of the course of the first another vehicle, another vehicle traveling on a course intersecting the course of the first another vehicle, the own vehicle, or a pedestrian on the course of the first another vehicle.

7. The drive assist method according to any one of claims 1 to 6,

in a case where the first interval is an interval between the vehicle body of the first other vehicle and the surrounding object, sequentially selecting each of a plurality of points on the outer peripheral surface of the vehicle body of the first other vehicle, and determining a combination of the selected point and a plurality of points on the outer peripheral surface of the surrounding object, respectively, calculating a minimum distance among distances between the points of the determined combination as the minimum distance of the first interval.

8. The drive assist method according to any one of claims 1 to 6,

in a case where the first interval is an interval between the vehicle body of the first another vehicle and a road end of the traveling lane of the first another vehicle, sequentially selecting each of a plurality of points on the outer peripheral surface of the vehicle body of the first another vehicle, and determining a combination of the selected point and the plurality of points on the road end, respectively, calculating a minimum distance among distances between the points of the determined combination as the minimum distance of the first interval.

9. The drive assist method according to any one of claims 1 to 8,

the end part of the road is a wall, a curb stone, a guardrail, a telegraph pole, a road mark and a lane boundary line for forbidding lane change.

10. The drive assist method according to any one of claims 1 to 9,

detecting a vehicle width of a third another vehicle that is a succeeding vehicle of the second another vehicle,

calculating a minimum distance of a second interval, which is an interval between the body of the second other vehicle and a peripheral object of the second other vehicle or between the body of the second other vehicle and a road end of the driving lane of the second other vehicle,

when the vehicle width of the third another vehicle is longer than the smaller one of the minimum distance of the first interval and the minimum distance of the second interval, it is predicted that there is no possibility that the third another vehicle passes through the first interval from behind the first another vehicle.

11. The drive assist method according to any one of claims 1 to 10,

and if it is predicted that there is no possibility that another vehicle passes through the first interval from behind the first another vehicle, causing the own vehicle to travel to a predetermined path that travels within the intersection.

12. A driving assistance device is characterized by comprising:

a sensor that detects a first another vehicle that enters an intersection on a first path on which the own vehicle is traveling from a second path different from the first path;

and a controller that predicts whether or not the first another vehicle stops in the intersection, predicts a stop position of the first another vehicle when the first another vehicle is predicted to stop in the intersection, calculates a minimum distance of a first interval, which is an interval between a vehicle body of the first another vehicle and a peripheral object of the first another vehicle or between the vehicle body of the first another vehicle and a road end of a travel lane of the first another vehicle when the first another vehicle stops at the predicted stop position, and predicts whether or not there is a possibility that a second another vehicle, which is a vehicle following the first another vehicle, will pass through the first interval from behind the first another vehicle, based on the calculated minimum distance.

Technical Field

The present invention relates to a driving assistance method and a driving assistance apparatus.

Background

As a technique for controlling the travel of a host vehicle at an intersection, a technique described in patent document 1 is known. The driving support apparatus described in patent document 1 provides normative action candidates in consideration of the risk of contact between an obstacle around the host vehicle and the host vehicle.

Documents of the prior art

Patent document

Patent document 1: japanese patent laid-open publication No. 2011-

When the host vehicle travels at an intersection on a route on which the host vehicle is traveling, if another vehicle enters the intersection from a route different from the route on which the host vehicle is traveling, there is a possibility that the other vehicle will be a following vehicle. In such a case, even if it is found that the other vehicle entering the intersection does not interfere with the travel of the own vehicle, the own vehicle may not travel in the intersection in some cases because there is a possibility that the following vehicle, which may be present behind the other vehicle, passes through the side of the other vehicle and enters the intersection.

Disclosure of Invention

An object of the present invention is to determine whether or not there is a possibility that a following vehicle will pass through the side of another vehicle even when the other vehicle enters an intersection on a route where the own vehicle is traveling from a route different from the route where the own vehicle is traveling and there is a possibility that the following vehicle will exist in the other vehicle.

In a driving assistance method according to an aspect of the present invention, a first another vehicle entering an intersection on a first route on which a host vehicle travels from a second route different from the first route is detected, and it is predicted whether or not the first another vehicle stops in the intersection, predicting a stop position of the first another vehicle when the first another vehicle is predicted to stop in the intersection, calculating a minimum distance of a first interval, which is an interval between a vehicle body of the first another vehicle and a peripheral object of the first another vehicle or between the vehicle body of the first another vehicle and a road end of a traveling lane of the first another vehicle when the first another vehicle stops at the predicted stop position, based on the calculated minimum distance, a likelihood is predicted whether a subsequent vehicle, i.e., a second other vehicle, having the first other vehicle passes through the first interval from behind the first other vehicle.

ADVANTAGEOUS EFFECTS OF INVENTION

According to one aspect of the present invention, even when another vehicle enters an intersection on a route where the host vehicle travels from a route different from the route where the host vehicle travels and there is a possibility that the another vehicle has a following vehicle, it is possible to determine whether there is a possibility that the following vehicle passes through a side of the another vehicle.

The objects and advantages of the invention may be realized and attained by means of the elements and combinations particularly pointed out in the appended claims. The general description above and the detailed description below are only exemplary and explanatory, and should not be construed as limiting the invention as claimed.

Drawings

Fig. 1 is a block diagram showing an example of a driving assistance device according to an embodiment.

Fig. 2 is an explanatory diagram of an example of the driving assistance method according to the embodiment.

Fig. 3 is a block diagram showing an example of a functional configuration of the controller shown in fig. 1.

Fig. 4 is an explanatory diagram of an example of a driving scene in which an obstacle on the course of another vehicle is a pedestrian.

Fig. 5 is an explanatory diagram of a first example of a driving scene in which an obstacle on the course of another vehicle is a congested vehicle ahead of the course of another vehicle.

Fig. 6 is an explanatory diagram of a second example of a driving scene in which an obstacle on the course of another vehicle is a congested vehicle ahead of the course of another vehicle.

Fig. 7 is an explanatory diagram of a second example of a driving scene in which an obstacle on the course of another vehicle intersects the course of another vehicle.

Fig. 8 is an explanatory diagram of an example of a driving assistance method in the T-shaped road.

Fig. 9 is an explanatory diagram of an example of a road end of a travel lane of another vehicle.

Fig. 10 is an explanatory diagram of another example of the interval with the possibility of subsequent vehicle passing.

Fig. 11A is (a) an explanatory diagram of a minimum distance between the vehicle body of another vehicle and the road end.

Fig. 11B is an explanatory diagram (second) of the minimum distance of the interval between the vehicle body of the other vehicle and the road end.

Fig. 11C is (a) an explanatory diagram of the minimum distance of the interval between the vehicle body of the other vehicle and the surrounding object.

Fig. 11D is an explanatory diagram (second) of the minimum distance of the interval between the vehicle body of the other vehicle and the surrounding object.

Fig. 12 is an explanatory diagram of an example of the driving assistance method in a case where the following vehicle of the other vehicle and the following vehicle are also considered.

Fig. 13A is (a) a flowchart of a driving assistance method according to an embodiment.

Fig. 13B is a flowchart of the driving assistance method of the embodiment (second).

Detailed Description

Hereinafter, embodiments will be described with reference to the drawings. In the description of the drawings below, the same or similar reference numerals are given to the same or similar parts. However, the drawings are schematic. The technical idea of the present invention can be variously modified within the technical scope defined by the claim described in the claim.

(Structure)

The driving assistance device according to the embodiment is mounted on, for example, a vehicle (hereinafter, the vehicle on which the driving assistance device according to the embodiment is mounted is referred to as "own vehicle"). The driving support device of the embodiment can execute, as driving support, automatic driving in which driving is automatically performed so that the host vehicle travels along the travel route, and guidance for prompting the driver to travel so that the host vehicle travels along the travel route.

The automated driving includes a case where the occupant (driver) performs all the controls of driving, braking, and steering of the vehicle without participating in the automated driving, and also includes a case where at least one of the controls of driving, braking, and steering of the vehicle is performed. The automatic driving may also be preceding vehicle following control, inter-vehicle distance control, lane departure prevention control, or the like.

As shown in fig. 1, the driving assistance device 1 of the embodiment includes: a sensor unit 2, a positioning unit 3, a map database (labeled as "map DB" in the drawing) 4, a communication unit 5, a navigation device 6, an output unit 7, a controller 8, a travel control device 9, and an actuator 10.

The sensor unit 2 detects the surroundings of the own vehicle, for example, objects around the own vehicle. The sensor unit 2 detects the environment around the host vehicle, such as an object existing around the host vehicle, a relative position between the host vehicle and the object, a distance between the host vehicle and the object, and a direction in which the object exists.

The sensor section 2 may be provided with a distance measuring device such as a laser distance measuring viewfinder (LRF) and radar, or a camera. The camera may be a stereo camera, for example. The camera may be a monocular camera, or the same object may be photographed at a plurality of viewpoints by the monocular camera, and the distance to the object may be calculated. Further, the distance to the object may be calculated based on the ground contact position of the object detected from the captured image. The sensor unit 2 outputs ambient environment information, which is information of the detected ambient environment, to the controller 8.

The positioning unit 3 measures the current position of the vehicle. The positioning unit 3 may be provided with a global positioning system (GNSS) receiver, for example. The GNSS receiver is, for example, a Global Positioning System (GPS) receiver or the like, and measures the current position of the own vehicle by receiving radio waves from a plurality of navigation satellites.

The positioning unit 3 may measure the current position of the vehicle by an odometer, for example. The positioning unit 3 outputs the acquired current position of the own vehicle to the controller 8.

The map database 4 is high-precision map data (hereinafter simply referred to as "high-precision map") suitable for a map for automatic driving. The high-accuracy map is map data having higher accuracy than map data for navigation (hereinafter, simply referred to as "navigation map"), and includes information on a lane unit, which is more detailed than information on a road unit.

For example, the high-accuracy map includes, as information on a lane unit, information on a lane node indicating a reference point on a lane reference line (for example, a central line in a lane) and information on a lane link indicating a section state of a lane between the lane nodes.

The information of the lane nodes includes identification numbers of the lane nodes, position coordinates, the number of connected lane links, and identification numbers of the connected lane links. The information on the lane link includes the identification number of the lane link, the type of the lane, the width of the lane, the type of the lane boundary line, the shape of the lane marking line, and the shape of the lane reference line. The high-accuracy map also includes information on the land objects such as traffic signals, stop lines, signs, buildings, utility poles, curbs, crosswalks, and the like, which are present on the lane or in the vicinity thereof, and identification numbers of lane nodes and lane links corresponding to the position coordinates of the land objects.

Since the high-accuracy map includes the node and the link information in units of lanes, the lane on which the host vehicle travels can be specified in the travel route. The high-precision map has coordinates capable of representing positions in the extending direction and the width direction of the lane. The high-precision map has coordinates (for example, longitude, latitude, and altitude) that can represent a position in a three-dimensional space, and the lane and the above-described terrestrial object can be described as shapes in the three-dimensional space.

In addition, the map database 4 may store a navigation map. The navigation map contains information in road units. For example, the navigation map includes, as information on a road unit, information on road nodes indicating reference points on a road reference line (for example, a line at the center of a road) and information on road links indicating the section state of the road between the road nodes. The information of the road node includes an identification number of the road node, position coordinates, the number of connected road links, and an identification number of the connected road links.

The information on the road link includes an identification number of the road link, a road specification, a link length, the number of lanes, a width of the road, and a speed limit.

In addition to these map information, the map database 4 may include priority information or the like, which is information of priority between roads intersecting at an intersection.

The communication unit 5 performs wireless communication with a communication device outside the vehicle. The communication method of the communication unit 5 may be, for example, wireless communication by a public mobile telephone network, car-to-car communication, road-to-car communication, or satellite communication.

The driving assistance device 1 may acquire a high-precision map or navigation map by a remote communication service such as vehicle-to-vehicle communication or road-to-vehicle communication by the communication unit 5 instead of the map database 4.

By using the remote communication service, the host vehicle does not need to have map data with a large data capacity, and the capacity of the memory can be reduced. Further, since the updated map data can be acquired by using the remote communication service, it is possible to accurately grasp a change in road structure, the presence or absence of a construction site, and the like, and to accurately grasp an actual traveling situation. Further, by using the remote communication service, map data created based on data collected from a plurality of other vehicles other than the vehicle can be used, and therefore, accurate information can be grasped.

The navigation device 6 calculates a route from the current position of the own vehicle to the destination. When the occupant operates the navigation device 6 to input a destination, a travel route from the current position to the destination is set by a method based on a graph search theory such as the Dijkstra's algorithm or a ×. The navigation device 6 provides route guidance to the occupant via the output unit 7 according to the travel route.

The set travel route is output to the controller 8 for automatic driving or driving assistance of the vehicle.

The output unit 7 outputs various visual information and audio information. For example, the output unit 7 may display a map screen around the host vehicle or visual information of guidance of a recommended route. The output unit 7 may output voice guidance such as driving guidance based on a set travel route or road guidance based on road map data around the host vehicle, for example.

For example, the output unit 7 may display a guidance display for assisting the driver in driving or output an audio guidance message via the controller 8.

The controller 8 is an Electronic Control Unit (ECU) that performs driving assistance of the own vehicle. The controller 8 includes peripheral components such as a processor 11 and a storage device 12. The processor 11 may be, for example, a CPU or MPU. The storage device 12 may include any one of a semiconductor storage device, a magnetic storage device, and an optical storage device. The storage device 12 may include registers, cache memory, ROM serving as a main storage device, and RAM and the like. The controller 8 may be implemented by a functional logic circuit provided in a general-purpose semiconductor integrated circuit. For example, the controller 8 may include a Programmable Logic Device (PLD) such as a Field Programmable Gate Array (FPGA).

The controller 8 generates a travel locus for causing the host vehicle to travel on the travel route set by the navigation device 6 based on the surrounding environment information input from the sensor unit 2 and the current position of the host vehicle measured by the positioning unit 3. The controller 8 outputs the generated travel locus to the travel control device 9.

The travel control device 9 is an ECU that performs travel control of the vehicle. The travel control device 9 includes peripheral components such as a processor and a storage device. The processor may be, for example, a CPU or MPU. The storage device may have any one of a semiconductor storage device, a magnetic storage device, and an optical storage device. The storage means may include registers, cache memories, ROM and RAM, etc., which serve as main storage means.

The travel control device 9 may be implemented by a functional logic circuit provided in a general-purpose semiconductor integrated circuit. For example, the travel control device 9 may include a PLD such as an FPGA. The travel control device 9 may be an electronic control unit integrated with the controller 8, or may be a separate electronic control unit. The travel control device 9 drives the actuator 10 to cause the host vehicle to automatically travel so as to cause the host vehicle to travel on the travel trajectory generated by the controller 8.

The actuator 10 operates a steering, an accelerator opening, and a brake device of the host vehicle in accordance with a control signal from the travel control device 9, and generates a vehicle operation of the host vehicle. The actuators 10 may include, for example, a steering actuator, an accelerator opening degree actuator, and a brake control actuator. The steering actuator controls the steering direction and the steering amount of a steering gear of the own vehicle. The accelerator opening actuator controls an accelerator opening of the vehicle. The brake control actuator controls a braking operation of a brake device of the vehicle.

Referring to fig. 2, an outline of the driving assistance method of the driving assistance device 1 will be described.

There is an intersection (crossroad) ahead of the first route 21 on which the host vehicle 20 travels, and the first another vehicle v1 enters the intersection from the second route 22 different from the first route 21. Further, a second another vehicle v2, which is a vehicle following the first another vehicle v1, runs behind the first another vehicle v 1.

The following predetermined route p0 on which the host vehicle 20 is traveling at the intersection is a right turn, and the route p1 of the first another vehicle v1 is also a right turn. Therefore, the first other vehicle v1 does not obstruct the traveling route of the own vehicle 20.

However, the priority of the travel of the host vehicle 20 on the route p0 that the intersection turns right to pass through is lower than the priority of the travel of the second another vehicle v2 on the travel lane of the first another vehicle v 1. That is, at the intersection, the priority of the second another vehicle v2 traveling straight is higher than the priority of the host vehicle 20 traveling on the path p0 while turning right at the intersection. Therefore, the second another vehicle v2 may go straight at the intersection. Therefore, even if it is found that the first another vehicle v1 does not interfere with the course of the host vehicle 20, there is a possibility that the second another vehicle v2 passes between the first another vehicle v1 and the road end and travels straight in the intersection, and the host vehicle cannot travel to the predetermined route p0 for traveling at the intersection.

Then, the controller 8 first determines whether or not the first another vehicle v1 is stopped, based on the state where the first another vehicle v1 passes through a point in front of the travel route p1 of the intersection.

In the example of fig. 2, the following vehicle o1 becomes an obstacle on the course of the first another vehicle v1 because the course 23 on which the following vehicle o1 of the host vehicle 20 travels straight at the intersection intersects with the course p1 on which the first another vehicle v1 turns right. Therefore, the controller 8 determines that the first another vehicle v1 is stopped, and predicts the stop position of the first another vehicle v 1.

Next, the controller 8 predicts whether or not there is a possibility that the second another vehicle v2 passes between the first another vehicle v1 and the road end of the traveling lane from behind the stopped first another vehicle v1 and enters the intersection. Specifically, first, the minimum distance d1 of the interval between the stopped first another vehicle v1 and the road end of the traveling lane is calculated. Hereinafter, the interval between the first another vehicle v1 and the road end of the travel lane will also be referred to as "first interval".

The first interval may be, for example, an interval between the vehicle body of the first another vehicle v1 and the road end of the driving lane of the first another vehicle v1 shown in fig. 2, an interval between the vehicle body of the first another vehicle v1 and a curb, an interval between the vehicle body of the first another vehicle v1 and another object (for example, a wall, a guardrail, a utility pole, a sign, or the like provided at the same road end), or an interval between the vehicle body of the first another vehicle v1 and another plurality of objects.

The controller 8 predicts whether there is a possibility that the second another vehicle v2 passes through the first interval from behind the first another vehicle v1, based on the calculated minimum distance d 1. For example, when the minimum distance d1 of the first gap is equal to or less than a threshold value (for example, equal to or less than a predetermined size sufficiently smaller than the vehicle width size of the two-wheeled vehicle), the controller 8 determines that there is no possibility that the second another vehicle v2 passes through the first gap from behind the first another vehicle v 1.

Further, for example, in a case where the minimum distance d1 of the first interval is smaller than the vehicle width w1 of the second another vehicle v2, the controller 8 determines that there is no possibility that the second another vehicle v2 passes through the first interval. In contrast, when the minimum distance d1 of the first interval is equal to or greater than the vehicle width w1, the controller 8 determines that there is a possibility that the second another vehicle v2 passes through the first interval.

In this way, by determining the possibility that the second another vehicle v2 passes through the first interval from behind the first another vehicle v1, it is possible to determine whether or not the second another vehicle v2 obstructs the course of the own vehicle 20.

Thus, even if the first another vehicle v1 enters the intersection ahead of the route 21 on which the host vehicle 20 travels from the route 22 different from the route 21, and there is a possibility that the first another vehicle v1 will have a following vehicle, the host vehicle 20 can be caused to travel to the route p0 on which the intersection travels.

Next, an example of the functional configuration of the controller 8 will be described with reference to fig. 3. The controller 8 includes: an object recognition unit 30, a self-position estimation unit 31, a driving action determination unit 32, and a trajectory generation unit 33. The functions of the object recognition unit 30, the self-position estimation unit 31, the driving action determination unit 32, and the trajectory generation unit 33 can be realized, for example, by the processor 11 of the controller 8 executing a computer program stored in the storage device 12.

The object recognition unit 30 recognizes an object around the host vehicle 20 based on the surrounding environment information output from the sensor unit 2. The object recognized by the object recognition unit 30 may be, for example, the first another vehicle v1, a vehicle following the first another vehicle v1, an object around the first another vehicle v1, an object on the route of the first another vehicle v1 passing through the intersection, and a road end (e.g., a curb, a guardrail, a utility pole, a road sign) of the travel lane of the first another vehicle v 1.

For example, the object recognition unit 30 recognizes an object around the host vehicle 20 by integrating the recognition result of the object detected by performing image processing on the image of the camera of the sensor unit 2 and the detection result of the object by a distance measuring device such as a laser range finder or a radar using a known sensor fusion technique.

In this case, the object recognition portion 30 tracks the recognized object. Specifically, the identity of an object recognized at different times is verified (correlated), and the behavior of the object is predicted from the correlation.

The object recognition unit 30 may acquire information such as the position, size, and behavior of an object around the host vehicle 20 by vehicle-to-vehicle communication and road-to-vehicle communication.

The object recognition unit 30 outputs the recognition result to the driving action determination unit 32.

The self-position estimating unit 31 estimates the position and orientation of the vehicle 20 on the map based on the current position of the vehicle 20 obtained by the positioning unit 3 and the map data stored in the map database 4. The self-position estimating unit 31 specifies the road on which the vehicle 20 travels, and further, the lane in which the vehicle 20 travels on the road.

The self-position estimating unit 31 outputs the estimation result to the driving action determining unit 32.

The driving action determination unit 32 determines whether or not there is a possibility that a vehicle behind the first another vehicle v1 (for example, a second another vehicle v2 that is a vehicle following the first another vehicle v1) passes by the first another vehicle v1 and interferes with the travel of the host vehicle 20, based on the recognition result of the object recognition unit 30, the estimation result of the own position estimation unit 31, and the like.

The driving action specifying unit 32 determines whether or not to cause the host vehicle 20 to travel along the route p0 running at the intersection, based on whether or not there is a possibility that the vehicle behind the first another vehicle v1 interferes with the travel of the host vehicle 20.

The driving action specifying unit 32 includes: the intersection information management unit 40, another vehicle course prediction unit 41, another vehicle/surrounding information management unit 42, interval calculation unit 43, and crossing prediction unit 44.

The intersection information management unit 40 acquires the own vehicle priority information 50 relating to the priority of traveling on the route p0 where the own vehicle 20 passes through the intersection, based on the travel route set by the navigation device 6, the map data stored in the map database 4, and the recognition result of the object recognition unit 30.

For example, when the host vehicle 20 turns right at the intersection based on the travel route set by the navigation device 6, the intersection information management unit 40 determines that the priority of traveling on the route p0 of the host vehicle 20 is lower than the priority of traveling on the travel lane of the oncoming vehicle (i.e., the priority of traveling straight at the intersection).

When the host vehicle 20 makes a straight-ahead or a left-turn at the intersection, the intersection information management unit 40 determines that the priority of traveling on the route p0 of the host vehicle 20 is not lower than the priority of traveling on the traveling lane of the oncoming vehicle.

The intersection information management unit 40 may determine whether or not the intersection ahead of the route p0 of the host vehicle 20 specifies that the host vehicle 20 should stop temporarily, based on the map data stored in the map database 4. When it is specified that the host vehicle 20 should stop temporarily, the intersection information management unit 40 may determine that the priority of traveling on the path p0 of the host vehicle 20 is lower than the priority of traveling on a road intersecting the traveling road of the host vehicle 20.

Further, when the temporary stop mark and the temporary stop line 24 shown in fig. 6, 7, and 9 are detected from the recognition result of the object recognition unit 30, the intersection information management unit 40 may determine that the priority of traveling on the route p0 of the host vehicle 20 is lower than the priority of traveling on the road intersecting the traveling road of the host vehicle 20. The intersection information management unit 40 outputs the own vehicle priority information 50 to the crossing prediction unit 44.

The intersection information management unit 40 estimates the position on the map of the road edge of the travel lane of the first another vehicle v1 based on the estimation result of the own position of the host vehicle 20, the map data stored in the map database 4, and the recognition result of the object recognition unit 30, and acquires the road edge information 51 relating to the position and shape of the road edge. The intersection information management unit 40 can recognize the position of an object placed at the end of a road, such as a curb, guardrail, utility pole, road sign, as the position of the end of the road.

The intersection information management unit 40 outputs the road end information 51 to the interval calculation unit 43.

The other-vehicle/surrounding-information management unit 42 estimates the position of the object around the host vehicle 20 on the map based on the estimation result of the own position and the recognition result of the object recognition unit 30, and acquires the surrounding object information 54 related to the position of the object around the host vehicle 20. The peripheral object information 54 may include position information of each point of the object surface around the host vehicle 20.

The other-vehicle/periphery information management unit 42 estimates the position of the other vehicle (for example, the first other vehicle v1 or the second other vehicle v2) around the host vehicle 20 on the map based on the estimation result of the own position and the recognition result of the object recognition unit 30, and acquires the other-vehicle end information 55 concerning the position of each point on the body surface of the other vehicle.

The another-vehicle route predicting unit 41 determines whether or not the first another vehicle v1 is stopped based on the estimation result of the own position and the recognition result of the object recognizing unit 30, and predicts the stop position of the first another vehicle v 1. The other-vehicle course prediction unit 41 includes a course prediction unit 52 and a stop prediction unit 53.

The another-vehicle route prediction unit 41 predicts the route p1 of the first another vehicle v1 on the map based on the estimation result of the own position and the recognition result of the object recognition unit 30. For example, the other-vehicle route prediction unit 41 may predict the route p1 of the first other vehicle v1 based on the movement history of the first other vehicle v1 predicted by the object recognition unit 30, the positional relationship between the objects around the first other vehicle v1 and the first other vehicle v1 recognized by the object recognition unit 30, and the like.

The stop prediction unit 53 determines whether or not the predicted course p1 of the first another vehicle v1 interferes with the course of the own vehicle 20.

For example, in the driving scenario of fig. 2, the following predetermined route p0 on which the host vehicle 20 is traveling at the intersection is a right turn, and the route p1 of the first another vehicle v1 is also a right turn. Therefore, the first other vehicle v1 does not obstruct the traveling route of the own vehicle 20.

When the course p1 of the first another vehicle v1 does not interfere with the course of the host vehicle 20, the stop prediction unit 53 acquires information on an object existing in front of the course p1 where the first another vehicle v1 passes through the intersection, from the surrounding object information 54 acquired by the another vehicle/surrounding information management unit 42, based on the course p1 of the first another vehicle v1 predicted by the another vehicle course prediction unit 41.

The stop prediction unit 53 determines the state of the first another vehicle v1 passing through the point ahead of the travel route p1 of the intersection, based on the information acquired from the surrounding object information 54. The stop prediction unit 53 determines whether the first another vehicle v1 is stopped and the stop position of the first another vehicle v1 based on the state of the point ahead of the travel route p 1.

The stop prediction section 53 may predict the stop position of the first another vehicle v1, for example, in a case where an obstacle (object) exists on the traveling route p1 of the first another vehicle v1, based on the surrounding object information 54.

As shown in fig. 2, the obstacle on the route p1 of the first another vehicle v1 may be, for example, another vehicle o1 traveling on a route 23 intersecting the route p1 on which the first another vehicle v1 turns right.

As shown in fig. 4, the obstacle on the traveling route p1 of the first another vehicle v1 may also be, for example, a pedestrian o2 on the traveling route p1 of the first another vehicle v 1.

The obstacle on the route p1 of the first another vehicle v1 may be a preceding vehicle of the first another vehicle v1 or a congested vehicle in front of the route p1 of the first another vehicle v 1.

For example, in the driving scenario of fig. 5, there is a vehicle congestion ahead of the travel route p1 of the first another vehicle v1, and the preceding vehicle o3 stops. Therefore, the stop prediction unit 53 predicts that the first another vehicle v1 stops at a position in front of the intersection. At this time, the first another vehicle v1 does not interfere with the path p0 of the host vehicle 20 turning right.

In the driving scenario of fig. 6, the first route 21 traveled by the host vehicle 20 and the second route 22 traveled by the first another vehicle v1 intersect at the intersection. Since there is a vehicle congestion ahead of the route p1 of the first another vehicle v1 and the preceding vehicle o3 stops, the first another vehicle v1 needs to stop in front of the intersection. Therefore, the first another vehicle v1 does not obstruct the traveling path of the straight-traveling host vehicle 20. In this case, the stop prediction unit 53 also determines that the preceding vehicle of the first another vehicle v1 and the congested vehicle ahead of the route p1 of the first another vehicle v1 are obstacles on the route p1 of the first another vehicle v1, and predicts the position in front of the intersection as the stop position of the first another vehicle v 1.

In the driving scenario of fig. 7, the first route 21 traveled by the host vehicle 20 and the second route 22 traveled by the first another vehicle v1 also intersect at the intersection. The following predetermined route p0 on which the own vehicle 20 is traveling at the intersection is a left turn, and the route p1 of the first another vehicle v1 is a right turn. Therefore, the first other vehicle v1 does not obstruct the traveling route of the own vehicle 20.

The course p1 of the first another vehicle v1 turning right at the intersection intersects with the course 23 of the oncoming vehicle o1 of the first another vehicle v1 going straight at the intersection. Therefore, the stop prediction unit 53 determines that the oncoming vehicle o1 is an obstacle on the course p1 of the first another vehicle v1, and predicts the position at which the oncoming vehicle o1 was waiting in the intersection before passing as the stop position of the first another vehicle v 1.

The driving action determination unit 32 determines whether or not the intersection where the host vehicle 20 is to travel is not limited to an intersection. In the driving scenario of fig. 8, the driving action determination unit 32 determines whether or not the host vehicle 20 is traveling on a T-shaped path that intersects the first path 21 on which the host vehicle 20 travels and the second path 22 on which the first another vehicle v1 travels.

The first another vehicle v1 approaches from the right of the host vehicle 20, and when attempting to turn left to enter (enter) the road on which the host vehicle 20 travels, the host vehicle 20 attempts to turn left to exit in a direction opposite to the direction in which the first another vehicle v1 arrived. At this time, the first another vehicle v1 does not interfere with the path p0 of the host vehicle 20 turning left.

When the road on which the host vehicle 20 travels (i.e., the road on which the first another vehicle v1 is scheduled to travel) is narrow and it is difficult for the host vehicle 20 and the first another vehicle v1 to pass by, the first another vehicle v1 cannot travel on the road on which the host vehicle 20 is located. Therefore, the stop prediction unit 53 determines that the own vehicle 20 is an obstacle on the course p1 of the first another vehicle v1, and predicts the position in front of the T-shaped road as the stop position of the first another vehicle v 1.

See fig. 3. The interval calculation unit 43 calculates the minimum distance d1 of the first interval, which is considered as a candidate of the interval through which the second another vehicle v2 passes from the side of the stopped first another vehicle v1, based on the road end information acquired by the intersection information management unit 40 and the other vehicle end information 55 acquired by the other vehicle/surrounding information management unit 42.

For example, in the driving scenario of fig. 2 and 4 to 7 (i.e., the driving scenario in which the first another vehicle v1 turns right or travels straight), the interval calculator 43 may calculate the minimum distance of the interval between the end of the vehicle body of the first another vehicle v1 and the road end on the left side of the traveling lane of the first another vehicle v1 as the minimum distance d 1.

In addition, for example, in the driving scenario of fig. 8 (i.e., the driving scenario in which the first another vehicle v1 makes a left turn), the minimum distance of the interval between the end of the body of the first another vehicle v1 and the end of the road on the right side of the traveling lane of the first another vehicle v1 may be calculated as the minimum distance d1 by the interval calculator 43.

In the driving scene in which the first another vehicle v1 turns left as shown in fig. 9, a lane boundary line (yellow line in japan) 25 that prohibits a lane change is provided between the traveling lane and the opposite lane of the first another vehicle v 1. In this case, it is considered that the second another vehicle v2 hardly crosses the lane boundary line 25 to pass by the first another vehicle v 1.

Therefore, the interval calculation section 43 may calculate the minimum distance of the interval between the end of the vehicle body of the first another vehicle v1 and the lane boundary line 25 on the right side of the traveling lane of the first another vehicle v1, taking the lane boundary line 25 as the road end, as the minimum distance d 1.

The interval calculation unit 43 may detect the minimum distance of the interval between the vehicle body of the first another vehicle v1 and the peripheral object of the first another vehicle v1 as the minimum distance d1 of the first interval.

In the driving scenario of fig. 10, it is predicted that the host vehicle 20 traveling on the predetermined route p0 turns right at the intersection to enter the lane 26, and the first another vehicle v1 traveling in the oncoming lane advances on the travel route p1 to turn left at the intersection to enter the lane 27 adjacent to the lane 26. In addition, since there is an obstacle (pedestrian o2) on the course p1 of the first another vehicle v1, it is predicted that the first another vehicle v1 stops in front of the crosswalk.

On the other hand, in the intersection, another vehicle s1 is present around the first another vehicle v1 (on the right side of the first another vehicle v 1). The course of the other vehicle s1 turning right at the intersection intersects with the course of the vehicle following the host vehicle 20 traveling straight at the intersection, and the vehicle following the host vehicle 20 becomes an obstacle on the course of the other vehicle s 1. Therefore, the other vehicle s1 cannot travel and stop in the intersection.

In this case, the second other vehicle v2 may pass through the space between the first other vehicle v1 and the other vehicle s 1.

Therefore, the interval calculation unit 43 may detect the minimum distance of the interval between the vehicle body of the first another vehicle v1 and the another vehicle s1 as the minimum distance d1 of the first interval.

The minimum distance to detect the interval between the vehicle body of the first other vehicle v1 and the other vehicle s1 is not limited to the case where the other vehicle s1 is stopped. The interval calculation unit 43 may detect the minimum distance of the interval between the vehicle body of the first another vehicle v1 and the another vehicle s1 as the minimum distance d1 when the another vehicle s1 decelerates due to an obstacle on the route.

The obstacle on the travel route of the other vehicle s1 may be, for example, a preceding vehicle of the other vehicle s1, a congested vehicle ahead of the travel route of the other vehicle s1, another vehicle traveling on a travel route intersecting the travel route of the other vehicle s1, or a pedestrian on the travel route of the other vehicle s 1.

Next, a method of calculating the minimum distance d1 of the interval between the end of the vehicle body of the first another vehicle v1 and the road end of the traveling lane of the first another vehicle v1 will be described. Refer to fig. 11A. First, the interval calculator 43 selects the point p1 from a plurality of points p1 to p7 on the outer peripheral surface of the vehicle body of the first another vehicle v1 included in the information detected by the object recognition unit 30. The interval calculator 43 determines combinations of the selected point p1 and the plurality of points p11 to p16 of the road end 28, respectively, and calculates distances between the points of the determined combinations, respectively.

See fig. 11B. Next, the interval calculator 43 selects the point p2 from the plurality of points p1 to p 7. The interval calculator 43 determines combinations of the selected point p2 and the plurality of points p11 to p16, and calculates distances between the points of the determined combinations.

Similarly, the interval calculator 43 identifies combinations of the plurality of points p3 to p7 on the vehicle body outer periphery of the first another vehicle v1 with the plurality of points p11 to p16 of the road end 28, and calculates the distances between the points of the combinations.

The interval calculation unit 43 selects the smallest distance among these calculated distances as the minimum distance d1 of the first interval.

Next, a method of calculating the minimum distance d1 between the end of the vehicle body of the first another vehicle v1 and the object s1 around the first another vehicle v1 will be described. Refer to fig. 11C. First, the interval calculator 43 selects the point p1 from a plurality of points p1 to p6 on the outer peripheral surface of the vehicle body of the first another vehicle v1 included in the information detected by the object recognition unit 30. The interval calculator 43 determines combinations of the selected point p1 and the plurality of points p21 to p26 of the surrounding object s1, respectively, and calculates distances between the points of the determined combinations, respectively.

See fig. 11D. Next, the interval calculator 43 selects the point p2 from the plurality of points p1 to p 6. The interval calculator 43 determines combinations of the selected point p2 and the plurality of points p21 to p26, and calculates distances between the points of the determined combinations.

Similarly, the interval calculator 43 identifies combinations of the plurality of points p3 to p6 on the outer periphery of the vehicle body of the first another vehicle v1 with the plurality of points p21 to p26 of the surrounding object s1, and calculates the distances between the points of the combinations.

The interval calculation unit 43 selects the smallest distance among these calculated distances as the minimum distance d1 of the first interval.

See fig. 3. The interval calculation unit 43 outputs the calculated minimum distance d1 to the passage prediction unit 44. The penetration prediction unit 44 predicts whether or not there is a possibility that the second another vehicle v2 passes through the first interval from behind the first another vehicle v1, based on the own-vehicle priority information 50, the prediction result of the stop prediction unit 53, and the minimum distance d1 of the first interval calculated by the interval calculation unit 43.

The crossing prediction unit 44 determines whether or not the priority of the own vehicle 20 traveling on the route p0 passing through the intersection is higher than the priority of the own vehicle traveling on the traveling lane of the first another vehicle v1 (i.e., the traveling lane of the second another vehicle v2 which is a vehicle following the first another vehicle v1) based on the own vehicle priority information 50.

When the priority of the host vehicle 20 traveling on the route p0 passing through the intersection is higher than the priority of the host vehicle 20 traveling on the traveling lane of the first another vehicle v1, the host vehicle 20 can travel at the intersection in preference to the second another vehicle v 2. Therefore, in this case, the crossing prediction portion 44 does not predict whether there is a possibility that the second another vehicle v2 crosses the first interval.

On the other hand, in the case where the priority of the host vehicle 20 traveling on the route p0 passing through the intersection is not higher than the priority of the host vehicle 20 traveling on the traveling lane of the first another vehicle v1 (that is, in the case where the priority of the host vehicle 20 traveling on the route p0 passing through the intersection is equal to or lower than the priority of the host vehicle traveling on the traveling lane of the first another vehicle v1), the crossing prediction unit 44 predicts whether or not there is a possibility that the second another vehicle v2 will cross the first gap.

Next, the penetration prediction unit 44 determines whether or not the minimum distance d1 of the first interval calculated by the interval calculation unit 43 is equal to or less than a predetermined threshold value. The threshold value is set to be smaller than a width that the motorcycle can pass through, for example.

When the minimum distance d1 of the first interval is equal to or less than a predetermined threshold value, the passage prediction unit 44 predicts that there is no possibility that the second another vehicle v2 passes through the first interval. In the case where it is predicted that there is no possibility that the second another vehicle v2 passes through the first interval, the passing prediction section 44 predicts that there is no possibility that the vehicle behind the first another vehicle v1 passes through the first another vehicle v 1.

When the minimum distance d1 of the first interval is greater than the predetermined threshold value, the passage prediction unit 44 determines whether the object recognition unit 30 can detect the second other vehicle v2 based on the peripheral object information 54.

When the object recognition unit 30 cannot detect the second another vehicle v2, the passage prediction unit 44 predicts that there is a possibility that the vehicle behind the first another vehicle v1 passes through the first another vehicle v 1. This is because the second other vehicle v2 is likely to enter a blind spot of the first other vehicle v1 or objects around the first other vehicle v 1.

On the other hand, when the object recognition unit 30 detects the second another vehicle v2, the crossing prediction unit 44 measures the vehicle width w1 of the second another vehicle v 2.

For example, the penetration prediction section 44 may measure the vehicle width w1 of the second another vehicle v2 based on the information of the size of the second another vehicle v2 identified by the object identification section 30. The vehicle width w1 may be calculated by adding a predetermined margin to the width of the second another vehicle v2 measured based on the information recognized by the object recognition unit 30.

For example, the passing prediction unit 44 may determine the vehicle type of the second another vehicle v2 by pattern matching using an image of the whole or a part of the vehicle body of the second another vehicle v 2. In this case, for example, the passing prediction unit 44 may compare vehicle data stored in advance including vehicle width information of each vehicle type or vehicle data that can be acquired by the communication unit 5 with the specified vehicle type to acquire the vehicle width information of the specified vehicle type.

The passing prediction unit 44 determines whether the vehicle width w1 of the second another vehicle v2 is shorter than the minimum distance d1 of the first interval. When the vehicle width w1 of the second another vehicle v2 is longer than the minimum distance d1 of the first interval, the passage prediction unit 44 predicts that there is no possibility that the second another vehicle v2 passes through the first interval. In the case where it is predicted that there is no possibility that the second another vehicle v2 passes through the first interval, the passing prediction section 44 predicts that there is no possibility that the vehicle behind the first another vehicle v1 passes through the first another vehicle v 1.

On the other hand, when the vehicle width w1 of the second another vehicle v2 is equal to or less than the minimum distance d1 of the first interval, the passage prediction unit 44 determines whether or not the second another vehicle v2 is stopped. When the vehicle width w1 of the second another vehicle v2 is equal to or less than the minimum distance d1 of the first interval and the second another vehicle v2 does not stop, the passage prediction unit 44 predicts that there is a possibility that the second another vehicle v2 may pass through the first interval.

In the case where it is predicted that there is a possibility that the second another vehicle v2 passes through the first interval, the passing prediction section 44 predicts that there is a possibility that the vehicle behind the first another vehicle v1 passes through the first another vehicle v 1.

Next, as shown in fig. 12, the penetration prediction unit 44 calculates a minimum distance d2 of a distance (hereinafter referred to as a "second distance") between the vehicle body of the second another vehicle v2 and the road end of the traveling lane of the second another vehicle v2 (or between the vehicle body of the second another vehicle v2 and the object around the second another vehicle v 2). The method of calculating the minimum distance D2 of the second interval is the same as the method of calculating the minimum distance D1 of the first interval described with reference to fig. 11A to 11D.

When a part of the vehicle body of the second another vehicle v2 is blocked by the surrounding objects of the first another vehicle v1 or the first another vehicle v1, a vehicle model of a vehicle type specified by pattern matching of the image of the second another vehicle v2 (a virtual object whose size in the front-rear-left-right direction is substantially equal to the specified vehicle type) is virtually arranged in the map data, and the distance to the road end or the surrounding objects is calculated.

When the minimum distance d2 of the second interval is, for example, equal to or less than a predetermined threshold value smaller than the width-directional dimension of the motorcycle, the passing prediction unit 44 predicts that there is no possibility that the third another vehicle v3, which is a vehicle following the second another vehicle v2, will pass through the second interval. In the case where it is predicted that there is no possibility that the third another vehicle v3 passes through the second interval, the passing prediction section 44 predicts that there is no possibility that the vehicle behind the first another vehicle v1 passes through the first another vehicle v 1.

When the minimum distance d2 of the second interval is greater than the predetermined threshold value, the passage prediction unit 44 determines whether or not the object recognition unit 30 can detect the third another vehicle v 3. When the object recognition unit 30 cannot detect the third another vehicle v3, the passage prediction unit 44 predicts that there is a possibility that the third another vehicle v3 passes through the first interval and the second interval. In the case where there is a possibility that the third another vehicle v3 passes through the first interval and the second interval, the passage prediction section 44 predicts that there is a possibility that the vehicle behind the first another vehicle v1 passes through the first another vehicle v 1.

When the object recognition unit 30 detects the third another vehicle v3, the crossing prediction unit 44 measures the vehicle width w2 of the third another vehicle v 3. The method of measuring the vehicle width w2 may be the same as the method of measuring the vehicle width w1 of the second another vehicle v 2.

The penetration prediction unit 44 selects the smaller one of the minimum distance D1 of the first interval and the minimum distance D2 of the second interval as the attention minimum distance D.

The passing prediction unit 44 determines whether or not the vehicle width w2 of the third another vehicle v3 is shorter than the attention minimum distance D. When the vehicle width w2 of the third another vehicle v3 is longer than the attention minimum distance D, the passage prediction unit 44 predicts that there is no possibility that the third another vehicle v3 passes through the first interval and the second interval. In the case where it is predicted that there is no possibility that the third another vehicle v3 passes through the first interval and the second interval, the passing prediction section 44 predicts that there is no possibility that the vehicle behind the first another vehicle v1 passes through the first another vehicle v 1.

On the other hand, when the vehicle width w2 of the third another vehicle v3 is equal to or less than the attention minimum distance D, the passage prediction unit 44 determines whether or not the third another vehicle v3 is stopped. When the vehicle width w2 of the third another vehicle v3 is equal to or less than the attention minimum distance D and the third another vehicle v3 is not stopped, it is predicted that there is a possibility that the third another vehicle v3 passes through the first interval and the second interval. In the case where it is predicted that there is a possibility that the third another vehicle v3 passes through the first interval and the second interval, the passing prediction unit 44 predicts that there is a possibility that the vehicle behind the first another vehicle v1 passes through the first another vehicle v 1.

Similarly, the passage prediction unit 44 repeats the same processing for each vehicle behind the third another vehicle v3 until it is predicted that there is a possibility or no possibility that the vehicle behind the first another vehicle v1 passes through the first another vehicle v 1.

When it is predicted that there is a possibility that the vehicle behind the first another vehicle v1 passes through the first another vehicle v1, the passing prediction unit 44 determines to stop the own vehicle 20 before the own vehicle 20 is caused to travel to the path p0 running at the intersection.

In the case where it is predicted that there is no possibility that the vehicle behind the first another vehicle v1 passes through the first another vehicle v1, the passing prediction unit 44 determines to cause the own vehicle 20 to travel to the path p0 traveling at the intersection.

See fig. 3. The penetration prediction unit 44 outputs the determination result to the trajectory generation unit 33.

The trajectory generation unit 33 generates a travel trajectory for traveling the vehicle based on the ambient environment information output from the sensor unit 2, the travel route set by the navigation device 6, and the map data stored in the map database 4.

The trajectory generation unit 33 generates the travel trajectory so as to include a curve of the speed at which the host vehicle stops at the parking position or passes through the parking position while decelerating.

When the crossing prediction unit 44 determines that the own vehicle 20 is stopped before the own vehicle 20 travels the route p0 traveled at the intersection, the trajectory generation unit 33 generates a travel trajectory in which the vehicle behind the first another vehicle v1 is stopped at a position waiting to cross and overtaking the first another vehicle v1 before the own vehicle 20 travels the route p0 traveled at the intersection.

The travel control device 9 controls the actuator 10 based on the travel locus generated by the locus generation unit 33, thereby stopping the own vehicle 20 at a position where the vehicle behind the first another vehicle v1 waits to pass through and overtake the first another vehicle v 1.

When the crossing prediction unit 44 determines that the host vehicle 20 is traveling along the route p0 traveled at the intersection, the trajectory generation unit 33 generates the travel trajectory of the host vehicle 20 traveling along the route p0 traveled at the intersection.

The travel control device 9 controls the actuator 10 based on the travel locus generated by the locus generation unit 33, thereby causing the host vehicle 20 to travel to the route p0 traveled at the intersection.

In addition, instead of automatically driving the host vehicle 20 by the travel control device 9, the passing prediction unit 44 may assist the driving operation of the driver by outputting guidance information for prompting the driving of the host vehicle 20 from the output unit 7.

For example, when it is predicted that the vehicle behind the first another vehicle v1 passes by the first another vehicle v1, the passing prediction unit 44 may output, from the output unit 7, guidance information notifying that the vehicle behind the first another vehicle v1 passes by the first another vehicle v1 and interferes with the host vehicle, and urging the host vehicle 20 to stop before the host vehicle 20 travels the route p0 running at the intersection.

For example, when it is predicted that there is no possibility that the vehicle behind the first another vehicle v1 passes by and overtakes the first another vehicle v1, the passing prediction unit 44 may output, from the output unit 7, guidance information notifying that there is no possibility that the vehicle behind the first another vehicle v1 overtakes the first another vehicle v1, and urge the host vehicle 20 to travel along the route p0 traveling at the intersection.

(Driving assistance method)

Next, an example of the driving assistance method according to the embodiment will be described with reference to the flowcharts of fig. 13A and 13B.

In step S1, the driving action determination portion 32 acquires object information regarding the position of the object around the host vehicle 20 based on the recognition result of the object recognition portion 30, and acquires map information based on the estimation result of the own position and the map database 4.

In step S2, the driving action specifying unit 32 determines whether or not the vehicle is approaching an intersection. When the host vehicle approaches the intersection (step S2: Y), the process proceeds to step S3. If the host vehicle does not approach the intersection (step S2: N), the process returns to step S1.

In step S3, the crossing prediction unit 44 determines whether the priority of the host vehicle 20 traveling on the route p0 passing through the intersection is higher than the priority of the host vehicle traveling on the traveling lane of the first another vehicle v 1.

If the priority of the host vehicle 20 traveling on the route p0 passing through the intersection is higher than the priority of the host vehicle traveling on the traveling lane of the first other vehicle v1 (step S3: Y), the process proceeds to step S14 of fig. 13B. In this case, the crossing prediction unit 44 determines that the host vehicle 20 is traveling along the route p0 that is traveled at the intersection. As a result, the travel control device 9 causes the host vehicle 20 to travel along the route p0 that travels at the intersection.

If the priority of the host vehicle 20 traveling on the route p0 passing through the intersection is not higher than the route traveling on the traveling lane of the first another vehicle v1 (step S3: N), the process proceeds to step S4.

In step S4, the crossing prediction unit 44 determines whether or not the first another vehicle v1 approaching the intersection is detected. When the first another vehicle v1 approaching the intersection is detected (step S4: Y), the process proceeds to step S5.

In the case where the first other vehicle v1 approaching the intersection is not detected (step S4: N), the process proceeds to step S14 of fig. 13B. In this case, the travel control device 9 causes the host vehicle 20 to travel along a route p0 that travels at the intersection.

In step S5, the stop prediction unit 53 determines whether or not the course p1 of the first another vehicle v1 interferes with the course of the own vehicle 20. In the case where the course p1 of the first another vehicle v1 interferes with the course of the own vehicle 20 (step S5: at Y), after waiting for the first another vehicle v1 to pass through the intersection, the process returns to step S1. In the case where the course p1 of the first other vehicle v1 does not interfere with the course of the own vehicle 20 (step S5: N), the process advances to step S6.

In step S6, the stop prediction unit 53 determines whether there is an obstacle on the course p1 of the first another vehicle v 1. In the case where there is an obstacle on the course p1 of the first other vehicle v1 (step S6: Y), the process advances to step S7. If there is no obstacle on the course p1 of the first another vehicle v1 (step S6: N), the process returns to step S1 after waiting for the first another vehicle v1 to pass through the intersection.

In step S7, the stop prediction unit 53 determines whether or not the first another vehicle v1 actually stops based on the movement history of the first another vehicle v 1. In the case where the first other vehicle v1 is stopped (step S7: Y), the process advances to step S8. In the case where the first another vehicle v1 does not stop (step S7: N), after waiting for the first another vehicle v1 to pass through the intersection, the process returns to step S1.

In step S8, the interval calculation section 43 calculates the minimum distance d1 of the first interval between the end of the vehicle body of the first another vehicle v1 and the peripheral object of the first another vehicle v1 (or the first interval between the end of the vehicle body of the first another vehicle v1 and the road end of the traveling lane of the first another vehicle v 1). Then, the interval calculation unit 43 sets the calculated minimum distance D1 as the attention minimum distance D.

In step S9, the penetration prediction unit 44 determines whether or not the attention minimum distance D is equal to or less than a predetermined threshold value.

When the attention minimum distance D is equal to or less than the threshold (step S9: Y), the process proceeds to step S13 of fig. 13B. In the case where the attention minimum distance D is larger than the threshold (step S9: N), the process advances to step S10.

In step S10, the penetration prediction unit 44 determines whether or not the second another vehicle v2 that is a vehicle following the first another vehicle v1 can be detected. In the case where the second another vehicle v2 can be detected (step S10: Y), the process proceeds to step S11 of fig. 13B. In the case where the second other vehicle v2 cannot be detected (step S10: N), the process proceeds to step S16 of fig. 13B.

See fig. 13B. In step S11, the penetration prediction unit 44 sets the second another vehicle V2, which is a vehicle subsequent to the first another vehicle V1, as the attention vehicle V.

The penetration prediction unit 44 measures the vehicle width of the vehicle V of interest (i.e., the vehicle width W1 of the second another vehicle V2) and sets the vehicle width W of interest.

In step S12, the penetration prediction unit 44 determines whether the vehicle width W of interest is longer than the minimum distance D of interest. When the vehicle width W of interest is longer than the minimum distance D of interest (step S12: Y), the process proceeds to step S13. When the vehicle width W of interest is equal to or less than the minimum distance D of interest (step S12: N), the process proceeds to step S15.

In step S13, since the possibility that the vehicle V passes through the first interval from behind the first another vehicle V1 is not concerned, the passing prediction unit 44 determines that there is no possibility that the vehicle behind the first another vehicle V1 passes through the first another vehicle V1. The crossing prediction unit 44 determines that the own vehicle 20 is to travel to the route p0 that is traveling at the intersection.

In step S14, the trajectory generation unit 33 generates a travel trajectory for the host vehicle 20 to travel along the route p0 traveling at the intersection. The travel control device 9 controls the actuator 10 based on the travel locus generated by the locus generation unit 33, thereby causing the host vehicle 20 to travel to the route p0 traveled at the intersection. After that, the process ends.

On the other hand, in step S15, the penetration prediction unit 44 determines whether or not the vehicle of interest V is stopped. In the case where the vehicle V of interest is stopped (step S15: Y), the process proceeds to step S17. In the case where the vehicle of interest V is not stopped (step S15: N), the process proceeds to step S16.

In step S16, the penetration prediction unit 44 determines that there is a possibility that the subject vehicle V passes through the first interval from behind the first another vehicle V1. That is, it is determined that there is a possibility that the vehicle behind the first another vehicle v1 passes through the first another vehicle v 1. It is determined that the host vehicle 20 is stopped before the host vehicle 20 is caused to travel to the route p0 that is traveling at the intersection.

Therefore, the trajectory generation unit 33 generates a travel trajectory for stopping the vehicle behind the first another vehicle v1 at a position that is waiting to pass through and exceeds the first another vehicle v1 before the host vehicle 20 is caused to travel along the route p0 that travels at the intersection.

The travel control device 9 controls the actuator 10 based on the travel locus generated by the locus generation unit 33, thereby stopping the own vehicle 20 at a position where the vehicle behind the first another vehicle v1 waits to pass through and overtake the first another vehicle v 1. After that, the process ends.

In step S17, the interval calculation section 43 detects the minimum distance of the interval between the end of the vehicle body of the vehicle of interest V and the surrounding objects of the vehicle of interest V (or the interval between the end of the vehicle body of the vehicle of interest V and the road end of the travel lane of the vehicle of interest V).

For example, in the case where the vehicle of interest V is the second another vehicle V2, the interval calculation section 43 detects the minimum distance d2 of the second interval between the end of the vehicle body of the second another vehicle V2 and the surrounding objects of the second another vehicle V2 (or the second interval between the end of the vehicle body of the second another vehicle V2 and the road end of the traveling lane of the second another vehicle V2).

In step S18, the penetration prediction unit 44 determines whether or not the minimum distance calculated in step S17 is equal to or less than a predetermined threshold. If the minimum distance is equal to or less than the threshold value (step S18: Y), the process proceeds to step S13. In the case where the minimum distance is greater than the threshold value (step S18: N), the process advances to step S19.

In step S19, the passage prediction unit 44 determines whether or not a vehicle following the vehicle V of interest can be detected. For example, when the focused-on vehicle V is the second another vehicle V2, the vehicle subsequent to the focused-on vehicle V is the third another vehicle V3.

If a vehicle following the vehicle V of interest can be detected (step S19: Y), the process proceeds to step S20. In the case where the following vehicle of the noted vehicle V cannot be detected (step S19: N), the process proceeds to step S16.

In step S20, the penetration prediction unit 44 measures the vehicle width of the following vehicle of the vehicle of interest V (vehicle width w2 in the case where the following vehicle of the vehicle of interest V is the third another vehicle V3).

In step S21, the penetration prediction unit 44 determines whether or not the minimum distance calculated in step S17 is shorter than the attention minimum distance D. In the case where the minimum distance calculated in step S17 is shorter than the attention minimum distance D (step S21: Y), the process advances to step S22. If the minimum distance calculated in step S17 is equal to or greater than the attention minimum distance D, step S22 is skipped and the process proceeds to step S23.

In step S22, the penetration prediction unit 44 sets the minimum distance calculated in step S17 as the attention minimum distance D. After that, the process advances to step S23.

In step S23, the passage prediction unit 44 sets the following vehicle of the vehicle V of interest as the vehicle V of interest, and sets the vehicle width of the following vehicle of the vehicle V of interest as the vehicle width W of interest.

Then, the process returns to step S12. Therefore, the vehicles in the direction of the first another vehicle V1 are sequentially set as the vehicle of interest V, and steps S12 to S23 are repeated, and finally it is predicted in step S16 that there is a possibility that a vehicle behind the first another vehicle V1 passes through the first another vehicle V1 or it is predicted in step S13 that there is no such possibility.

(effects of the embodiment)

(1) The crossing prediction unit 44 detects a first another vehicle v1 that enters an intersection on the first route 21 where the own vehicle 20 travels from the second route 22 different from the first route 21. The stop prediction unit 53 predicts whether or not the first another vehicle v1 is stopped inside the intersection, and when it is predicted that the vehicle is stopped inside the intersection, predicts the stop position of the first another vehicle v 1. The interval calculation unit 43 calculates the minimum distance d1 of the first interval, which is between the body of the first another vehicle v1 and the surrounding objects of the first another vehicle v1, or between the body of the first another vehicle v1 and the road end of the traveling lane of the first another vehicle v1 when the first another vehicle v1 stops at the predicted stop position. The passing prediction unit 44 predicts whether or not there is a possibility that the second another vehicle, which is a vehicle subsequent to the first another vehicle, passes through the first interval from behind the first another vehicle, based on the calculated minimum distance.

Thus, the first another vehicle v1 can be detected at the intersection, and it can be estimated whether or not the distance through which the following vehicle of the first another vehicle v1 can pass is left beside the first another vehicle v1, based on the first distance between the first another vehicle v1 and the surrounding object (or between the first another vehicle v1 and the road edge). Therefore, for example, even in a state where the following vehicle is not seen, it is possible to predict whether or not there is a possibility that the vehicle behind the first another vehicle v1 passes through the first another vehicle v1, and it is possible to confirm the safety when the vehicle enters the own vehicle path with higher accuracy.

As described above, since it is possible to predict whether or not there is a possibility that the following vehicle of the first another vehicle v1 passes through the first another vehicle v1, when the following vehicle of the first another vehicle v1 approaches or when there is no possibility that the following vehicle passes through the first another vehicle v1 even if the following vehicle is not seen, the host vehicle 20 can be made to travel to the intersection without waiting for the following vehicle. This can shorten the time required to reach the destination in automatic driving. Thus, an improved travel locus generation technique that improves the quality of the travel locus of the autonomous driving of the host vehicle 20 can be provided. Further, since it is possible to avoid wasteful stop of the host vehicle 20 for waiting for a following vehicle, it contributes to improvement of the fuel consumption rate of the host vehicle 20.

(2) In the case where the priority of the host vehicle 20 traveling on the route passing through the intersection is lower than the priority of the first another vehicle v1 traveling on the lane, the crossing prediction part 44 may predict whether or not there is a possibility that the second another vehicle v2 crosses the first gap from behind the first another vehicle v 1.

When the priority of the passage of the host vehicle 20 through the intersection is high, the host vehicle 20 can pass through the intersection regardless of the second another vehicle v 2. In such a case, the calculation load of the controller 8 can be reduced by omitting the prediction of the possibility that the second another vehicle v2 passes through the first interval from behind the first another vehicle v 1.

(3) When the calculated minimum distance d1 is equal to or less than a predetermined prescribed threshold value, the crossing prediction unit 44 may predict that there is no possibility that the second another vehicle v2 will cross the first interval from behind the first another vehicle v 1. Thus, it is possible to predict the possibility that no second another vehicle v2 will pass through the first interval from behind the first another vehicle v 1.

(4) The passing prediction unit 44 detects the vehicle width w1 of the second another vehicle v2, and when the detected vehicle width w1 of the second another vehicle v2 is longer than the calculated minimum distance d1, it can be predicted that there is no possibility that the second another vehicle v2 passes through the first interval from the rear of the first another vehicle v 1. Thus, it is possible to predict the possibility that no second another vehicle v2 will pass through the first interval from behind the first another vehicle v 1.

(5) In the case where there is an obstacle on the course of the first another vehicle v1, the stop prediction unit 53 may predict that the first another vehicle v1 stops within the intersection. Thus, it is possible to determine whether the first another vehicle v1 is stopped, and it is possible to determine whether the second another vehicle v2 is traveling through the first another vehicle v1, or is waiting for the first another vehicle v1 to travel.

(6) The obstacle on the traveling route of the first other vehicle v1 may be a preceding vehicle of the first other vehicle v1, a congested vehicle ahead of the traveling route of the first other vehicle v1, another vehicle traveling on a traveling route intersecting the traveling route of the first other vehicle v1, the own vehicle 20, or a pedestrian on the traveling route of the first other vehicle v 1.

Thus, it is possible to determine whether the first another vehicle v1 is stopped or not, and it is possible to determine whether the second another vehicle v2 is traveling through the first another vehicle v1 or waiting for the first another vehicle v1 to travel, by these listed obstacles.

(7) In the case where the first interval is the interval between the vehicle body of the first another vehicle v1 and the surrounding object, the interval calculating part 43 may sequentially select each of the plurality of points p1 to p6 on the outer peripheral surface of the vehicle body of the first another vehicle v1, determine combinations of the selected points and the plurality of points p21 to p26 on the outer peripheral surface of the surrounding object, respectively, and calculate the smallest distance among the distances between the points of the determined combinations as the minimum distance d1 of the first interval.

This makes it possible to appropriately determine the distance of the interval for predicting whether or not the following vehicle can pass through.

(8) In the case where the first interval is the interval between the vehicle body of the first another vehicle v1 and the road end of the traveling lane of the first another vehicle v1, the interval calculation section 43 may sequentially select each of the plurality of points p1 to p7 on the outer peripheral surface of the vehicle body of the first another vehicle v1, determine a combination of the selected point and the plurality of points p11 to p16 on the road end, respectively, and calculate the smallest distance among the distances between the points of the determined combination as the minimum distance d1 of the first interval.

This makes it possible to appropriately determine the distance of the interval for predicting whether or not the following vehicle can pass through.

(9) The end of the road may be a wall, a kerb, a guardrail, a utility pole, a road sign. Thus, in the case where the road end is demarcated by these objects that physically obstruct the travel of the following vehicle, it can be predicted whether or not the following vehicle can pass through the interval between the first other vehicle v1 and the road end.

The road end may be a lane boundary line that prohibits lane change. Thus, in the case where the crossing of the lane boundary line is prohibited, it can be predicted whether or not the following vehicle can pass through the interval between the first another vehicle v1 and the lane boundary line.

(10) The crossing prediction unit 44 may detect the vehicle width w2 of the third another vehicle v3 that is a vehicle following the second another vehicle v 2. The interval calculating part 43 may calculate the minimum distance d2 of the second interval, which is between the vehicle body of the second another vehicle v2 and the surrounding objects of the second another vehicle v2, or between the vehicle body of the second another vehicle v2 and the road end of the driving lane of the second another vehicle v 2. In the case where the vehicle width w2 of the third another vehicle is longer than the smaller one of the minimum distance d1 of the first interval and the minimum distance d2 of the second interval, the passage prediction portion 44 may predict that there is no possibility that the third another vehicle v3 passes through the first interval from the rear of the first another vehicle v 1.

Thus, when the third another vehicle v3, which is a following vehicle, is present behind the second another vehicle v2, it can be estimated whether or not the third another vehicle v3 can exceed the interval of the first another vehicle v 1. Therefore, since it can be predicted whether or not there is a possibility that the third another vehicle v3 passes through the first another vehicle v1, it is possible to confirm the safety when entering the own vehicle path with higher accuracy.

(11) In the case where the passing prediction unit 44 predicts that there is no possibility that another vehicle passes through the first interval from behind the first another vehicle v1, the travel control device 9 may cause the own vehicle 20 to travel to a predetermined path traveling within the intersection.

This enables the host vehicle 20 to travel while ensuring the safety of the route of the host vehicle 20.

All terms of examples and conditions described herein are intended to help the reader understand the concepts provided by the inventors for the present invention and the progress of the technology, and are intended for educational purposes. It should be understood that the present invention is not limited to the specific examples and conditions described above, and the structures of the examples in the present specification which show the superiority and inferiority of the present invention. Although the embodiments of the present invention have been described in detail, it should be understood that various changes, substitutions, and alterations can be made hereto without departing from the spirit and scope of the invention.

Description of the symbols

1: driving assistance device, 2: sensor unit, 3: positioning part, 4: map database, 5: communication unit, 6: navigation device, 7: output unit, 8: controller, 9: travel control device, 10: actuator, 11: processor, 12: storage device, 30: object recognition unit, 31: self-position estimation unit, 32: driving action determination unit, 33: trajectory generation unit, 40: intersection information management unit, 41: other vehicle route prediction unit, 42: surrounding information management unit, 43: interval calculation unit, 44: prediction unit, 50: own vehicle priority information, 51: road end information, 52: travel route prediction unit, 53: stop prediction unit, 54: surrounding object information, 55: other vehicle end information