JP7390884B2 - Driving environment estimation method, driving support method, and driving environment estimation device - Google Patents

Description

The present invention relates to a driving environment estimation method, a driving support method, and a driving environment estimation device.

Patent Document 1 listed below describes an environment estimation device that estimates the environment of a blind spot area based on the behavior of other nearby vehicles when a blind spot area of the own vehicle exists. This environment estimating device assumes the environmental state of the blind spot area and predicts the behavior of other vehicles in the assumed environmental state. Then, based on the comparison result between the predicted behavior of the other vehicle and the actual behavior of the other vehicle, it is estimated whether the assumed environmental state is the environmental state of the blind spot area.

Japanese Patent Application Publication No. 2013-140515

In the environment estimation device of Patent Document 1, when a lane change of a preceding vehicle traveling in front of the own vehicle is detected, whether the lane change was made to avoid a factor that would impede the traveling of the preceding vehicle, or for any other purpose. It is not possible to determine whether the driver changed lanes or not.
An object of the present invention is to estimate the presence or absence of a factor that impedes the running of the preceding vehicle when a lane change of the preceding vehicle traveling in front of the host vehicle is detected.

In the driving environment estimation method according to one aspect of the present invention, the position of a preceding vehicle traveling in front of the own vehicle is detected on the road on which the own vehicle is traveling, and an area that is visible to the occupants of the preceding vehicle or an object possessed by the preceding vehicle is detected. The detection unit estimates the detectable area, which is the area where objects around the preceding vehicle can be detected, and calculates the amount of change in the detectable area over a predetermined period of time, or the amount of change in the detectable area while the preceding vehicle travels a predetermined distance. If it is detected that the preceding vehicle has changed lanes from the first lane to the second lane on the road within a first predetermined time after detecting a certain area change amount and detecting an area change amount that is equal to or greater than a threshold value, It is estimated that there is a driving inhibiting factor that inhibits the driving of the vehicle on one lane and in front of the preceding vehicle.
In a driving support method according to another aspect of the present invention, when it is estimated that a driving inhibiting factor exists in the driving environment estimation method described above, driving of the own vehicle is supported so that the own vehicle runs on the second lane. do.

According to the present invention, when a lane change of a preceding vehicle traveling in front of the own vehicle is detected, it is possible to estimate whether there is a factor inhibiting the traveling of the preceding vehicle.

1 is a diagram illustrating an example of a schematic configuration of a vehicle equipped with a driving support device according to an embodiment. FIG. 2 is an explanatory diagram of an example of a driving environment estimation method according to an embodiment. FIG. 2 is a diagram illustrating an example of a functional configuration of a controller in FIG. 1. FIG. It is a figure which shows an example of a destination display. FIG. 7 is a diagram showing another example of destination display. FIG. 3 is an explanatory diagram of an example of a method for estimating lane selection intention. FIG. 7 is an explanatory diagram of another example of a method for estimating lane selection intention. FIG. 3 is an explanatory diagram of an example of a change in a detectable area. FIG. 3 is an explanatory diagram of an example of a change in a detectable area. FIG. 7 is an explanatory diagram of another example of change in the detectable area. FIG. 7 is an explanatory diagram of another example of change in the detectable area. It is a flowchart which shows an example of the whole flow of the driving support method of an embodiment. 9 is a flowchart illustrating an example of the lane selection intention estimation process of FIG. 8. 9 is a flowchart showing an example of the driving inhibiting factor estimation process of FIG. 8;

Embodiments of the present invention will be described below with reference to the drawings. In the description of the drawings, the same or similar parts are given the same or similar symbols, and overlapping explanations are omitted. Each drawing is schematic and may differ from the actual drawing. The embodiments shown below illustrate devices and methods for embodying the technical idea of the present invention, and the technical idea of the present invention is specific to the devices and methods illustrated in the embodiments below. It's not something you do. The technical idea of the present invention can be modified in various ways within the technical scope described in the claims.

Embodiments of the present invention will be described below with reference to the drawings.
(composition)
The own vehicle 1 includes a driving support device 10 that supports driving of the own vehicle 1. The driving support device 10 detects the current position of the own vehicle 1, and supports the traveling of the own vehicle 1 based on the detected own position.
For example, the driving support device 10 supports the driving of the own vehicle 1 by automatically controlling the driving of the own vehicle 1 based on the detected own position and the surrounding driving environment.
The automatic control of the own vehicle 1 may include, for example, autonomous driving control in which the own vehicle 1 is automatically driven without involvement of an occupant (for example, a driver). For example, the automatic control of the own vehicle 1 may include automatically controlling at least one of steering, acceleration, and deceleration of the own vehicle 1.

Further, for example, the driving support device 10 may support the driving of the own vehicle 1 by assisting the driver in driving the own vehicle 1 according to the driving environment around the own vehicle 1. The driving support device 10 may support driving by the driver by outputting a message prompting the driver to perform a steering operation or deceleration operation based on the estimated own position and the surrounding driving environment.

The driving support device 10 includes an object sensor 11, a vehicle sensor 12, a positioning device 13, a map database 14, a communication device 15, a navigation system 16, a controller 17, an actuator 18, and an output device 19. In the drawings, the map database is expressed as "map DB".
Note that the object sensor 11 and the controller 17 are an example of a "driving environment estimation device" described in the claims.

The object sensor 11 includes a plurality of different types of sensors that detect objects around the own vehicle 1.
For example, the object sensor 11 includes a camera mounted on the own vehicle 1. The camera captures an image in a predetermined viewing angle range (photography range) in front of the host vehicle 1 and outputs the captured image to the controller 17 .
Further, the object sensor 11 may include a distance measuring sensor such as a laser radar, a millimeter wave radar, or LIDAR (Light Detection and Ranging, Laser Imaging Detection and Ranging).

The vehicle sensor 12 is mounted on the own vehicle 1 and detects various information (vehicle signals) obtained from the own vehicle 1. The vehicle sensor 12 includes, for example, a vehicle speed sensor that detects the running speed (vehicle speed) of the own vehicle 1, a wheel speed sensor that detects the rotational speed of each tire included in the own vehicle 1, and an acceleration ( A 3-axis acceleration sensor (G sensor) that detects the steering angle (including deceleration), a steering angle sensor that detects the steering angle (including the turning angle), a gyro sensor that detects the angular velocity generated in the own vehicle 1, and a yaw rate that detects the yaw rate. The sensor includes an accelerator sensor that detects the accelerator opening of the host vehicle, and a brake sensor that detects the amount of brake operation by the occupant.

The positioning device 13 includes a global positioning system (GNSS) receiver, and measures the current position of the own vehicle 1 by receiving radio waves from a plurality of navigation satellites. The GNSS receiver may be, for example, a Global Positioning System (GPS) receiver. The positioning device 13 may be, for example, an inertial navigation device.
The map database 14 may store high-precision map data (hereinafter simply referred to as "high-precision map") suitable as map information for automatic driving. A high-precision map is map data with higher precision than map data for navigation (hereinafter simply referred to as a "navigation map").
The road information included in the high-definition map includes information for each lane, which is more detailed than information for each road. Hereinafter, information for each lane included in high-precision map data may be referred to as "lane information."

For example, a high-precision map includes, as lane information, lane node information that indicates the reference point on the lane reference line (for example, the center line within the lane) and lane link information that indicates the mode of the lane section between lane nodes. include.
The information on the lane node includes the identification number of the lane node, the position coordinates, the number of connected lane links, and the identification number of the connected lane link. The lane link information includes the identification number of the lane link, the type of lane, the width of the lane, the type of lane marking, the shape of the lane, the slope of the lane, and the shape of the lane marking.
The high-definition map further includes the types and location coordinates of features such as stop lines, signs, buildings, utility poles, curbs, crosswalks, buildings, etc. that exist on or near the lanes, and the lanes corresponding to the location coordinates of the features. Contains feature information such as node identification numbers and lane link identification numbers.

The communication device 15 performs wireless communication with a communication device external to the vehicle 1 . The communication method by the communication device 15 may be, for example, wireless communication using a public mobile telephone network, vehicle-to-vehicle communication, road-to-vehicle communication, or satellite communication.
The navigation system 16 recognizes the current position of the own vehicle 1 using the positioning device 13 and acquires map information at the current position from the map database 14 . The navigation system 16 sets a driving route to a destination input by the occupant, and provides route guidance to the occupant in accordance with this driving route.
The navigation system 16 also outputs information about the set travel route to the controller 17. When performing autonomous driving control, the controller 17 automatically drives the own vehicle 1 so as to travel along the travel route set by the navigation system 16.

The controller 17 is an electronic control unit (ECU) that performs driving support control of the own vehicle 1.
The controller 17 automatically controls the running of the own vehicle 1 based on the surrounding driving environment when controlling the running support of the own vehicle 1 . Alternatively, the driving of the own vehicle 1 by the occupant is supported according to the driving environment around the own vehicle 1.
For this reason, the controller 17 executes the driving environment estimation method of the embodiment when executing the driving support control of the host vehicle 1. Details of the driving environment estimation method will be described later.

The controller 17 includes a processor 21 and peripheral components such as a storage device 22. The processor 21 may be, for example, a CPU (Central Processing Unit) or an MPU (Micro-Processing Unit).
The storage device 22 may include a semiconductor storage device, a magnetic storage device, an optical storage device, or the like. The storage device 22 may include memories such as a register, a cache memory, a ROM (Read Only Memory) used as a main storage device, and a RAM (Random Access Memory).
The functions of the controller 17 described below are realized, for example, by the processor 21 executing a computer program stored in the storage device 22.

Note that the controller 17 may be formed of dedicated hardware for executing each information process described below.
For example, the controller 17 may include a functional logic circuit set in a general-purpose semiconductor integrated circuit. For example, the controller 17 may include a programmable logic device (PLD) such as a field-programmable gate array (FPGA).

The actuator 18 operates the steering mechanism, accelerator opening, and brake device of the host vehicle 1 in response to a control signal from the controller 17 to generate the vehicle behavior of the host vehicle 1 . The actuator 18 includes a steering actuator, an accelerator opening actuator, and a brake control actuator. The steering actuator controls the steering direction and amount of steering of the steering mechanism of the own vehicle 1.

The accelerator opening actuator controls the accelerator opening of the host vehicle 1 . The brake control actuator controls the amount of braking by the brake device of the own vehicle 1.
The output device 19 outputs information (for example, a message prompting a steering operation or a deceleration operation) that the driving support device 10 presents to the occupant for driving support. The output device 19 may include, for example, a display device, a lamp or a meter that outputs visual information, or a speaker that outputs audio information.

Next, with reference to FIG. 2, an overview of the driving environment estimation method according to the embodiment using the controller 17 will be described.
In the example of FIG. 2, the host vehicle 1 is traveling on a road 2. The road 2 has at least a first lane 2a in which the host vehicle 1 is currently traveling, and a second lane 2b which is an adjacent lane to the first lane 2a. The directions are the same. A preceding vehicle 3 is traveling in front of the host vehicle 1 on the road 2, and is located at a point P1 at a first time t1.

Thereafter, the preceding vehicle 3 travels to point P2 at a second time t2 after the first time t1. Then, the preceding vehicle 3 changes lanes from the first lane 2a to the second lane 2b and travels to point P3 at third time t3 after second time t2.
There are various possible purposes for the preceding vehicle 3 to change lanes from the first lane 2a to the second lane 2b. For example, the preceding vehicle 3 had the intention of continuing to drive in the first lane 2a, but there was a factor that impeded the running of the preceding vehicle 3 in the first lane 2a and in front of the preceding vehicle 3 (the preceding vehicle 3 was traveling in the first lane 2a). It is conceivable that the driver changed lanes to the second lane 2b in order to avoid a factor that inhibits the vehicle from continuing to travel in the lane 2a (hereinafter sometimes referred to as a "driving inhibiting factor"). An example of a travel inhibiting factor in FIG. 2 is a traffic jam of other vehicles 5a and 5b at the intersection 4.

On the other hand, purposes other than avoiding driving-hindering factors may also be considered. For example, it is conceivable that the preceding vehicle 3 originally planned to turn left at the intersection 4 and changed lanes to the second lane 2b even if there were no travel-impeding factors.
In the environment estimation device of Patent Document 1, even if a lane change of the preceding vehicle 3 from the first lane 2a to the second lane 2b is detected, whether the lane change is to avoid a driving impediment factor or not It is not possible to determine whether the lane change was intended. Therefore, even if a lane change of the preceding vehicle 3 is detected, there is a problem in that it is difficult to control the own vehicle 1 based on the result of estimating the environment of the blind spot area of the own vehicle 1.

For example, if it is estimated that there is a driving impediment factor based on the implementation of a lane change by the preceding vehicle 3, and the vehicle 1 is provided with driving support to change lanes from the first lane 2a to the second lane 2b, the vehicle 1 Even though there is actually no driving inhibiting factor in the blind spot area, driving assistance may occur that causes the vehicle 1 to change lanes to the second lane 2b needlessly. On the other hand, if we assume that there are no driving impeding factors based on the fact that the preceding vehicle 3 does not change lanes, and perform driving support to continue driving the own vehicle 1 in the first lane 2a, in reality, Despite the presence of a driving impediment factor, the driving support that causes the vehicle 1 to change lanes to the second lane 2b is delayed, resulting in a waiting time due to the driving impediment factor and the need for braking operations that involve large decelerations. This may cause the occupants to feel uncomfortable.

Therefore, the controller 17 estimates a detectable area, which is an area in which surrounding objects in front of the preceding vehicle 3 can be detected from the preceding vehicle 3 . The dotted line 6a indicates the detectable area (at the point P1) at the first time t1. A dotted line 6b indicates the detectable area (at point P2) at the second time t2.
For example, the detectable area may be an area that can be visually recognized by the occupant (for example, the driver) of the preceding vehicle 3 while monitoring (or gazing at) the front. Further, for example, the detectable area may be an area where an object detection unit mounted on the preceding vehicle 3 and used for the automatic driving device or driving support device of the preceding vehicle 3 can detect surrounding objects in front of the preceding vehicle 3. good.

When the detectable area of the preceding vehicle 3 changes from the detectable area 6a at the first time t1 to the detectable area 6b at the second time t2, the occupant or object detection unit of the preceding vehicle 3 detects a new field of view. means obtained. As a result, in the example of FIG. 2, it becomes possible to detect traffic congestion caused by other vehicles 5a and 5b, which is a factor that inhibits travel.
Therefore, if the preceding vehicle 3 changes lanes from the first lane 2a to the second lane 2b immediately after a change in the detectable areas 6a, 6b occurs, the driving inhibiting factor is detected in the newly obtained detectable area. There is a high probability that the driver discovered this and changed lanes to avoid this road-impeding factor.

Therefore, when the controller 17 detects that the preceding vehicle 3 has changed lanes from the first lane 2a to the second lane 2b on the road 2 within the first predetermined time after detecting the change in the detectable area, It is estimated that there is a travel inhibiting factor that inhibits the vehicle from traveling on the first lane 2a and in front of the preceding vehicle 3.
Thereby, it becomes possible to detect a lane change at a timing when there is a high probability of avoiding a travel-hindering factor, and it is possible to accurately estimate the presence or absence of a travel-hindering factor ahead on the first lane 2a.

Next, the functions of the controller 17 will be explained in detail with reference to FIG. The controller 17 includes a self-position estimation section 30, an object detection section 31, a lane structure acquisition section 32, a lane change detection section 33, a destination display acquisition section 34, a lane selection intention estimation section 35, and a three-dimensional object detection section. 36, a detectable area estimating section 37, an area change amount detecting section 38, a lane change inhibiting factor determining section 39, a driving inhibiting factor estimating section 40, and a vehicle controlling section 41.

The self-position estimating unit 30 estimates the current position of the own vehicle 1, the attitude of the own vehicle 1 (for example, the traveling direction of the own vehicle 1), and the speed on the map stored in the map database 14. do.
The self-position estimating unit 30 estimates the self-position of the own vehicle 1 based on, for example, the positioning result of the positioning device 13, odometry by the vehicle sensor 12, and the detection result of targets around the own vehicle 1 by the object sensor 11. .

The object detection unit 31 detects objects around the own vehicle 1 using the object sensor 11, and acquires the position, speed, and size of the objects. The object detection unit 31 determines whether the detected object is a vehicle. For example, the object detection unit 31 determines that the detected object is a vehicle when the position of the detected object is on the road and the size of the object is within a predetermined range assumed as the size of a vehicle.

The object detection unit 31 detects the position, posture (for example, direction of travel), and speed of other vehicles around the detected own vehicle 1. Furthermore, the object detection unit 31 determines whether the detected other vehicle is the preceding vehicle 3 traveling in front of the own vehicle 1 based on the position, attitude, and speed of the detected other vehicle and the own vehicle 1. , the position of the preceding vehicle 3 is detected.
The lane structure acquisition unit 32 determines the lane, intersection, and surrounding area in front of the vehicle 1 on the road 2 on which the vehicle 1 is traveling, from the map database 14 based on the self-position of the vehicle 1 estimated by the self-position estimation unit 30. Information on the lane structure, which is a structure such as a feature (for example, a curb), is acquired.

The lane change detection unit 33 compares the position, attitude, and speed of the preceding vehicle 3 detected by the object detection unit 31 with the lane structure in front of the own vehicle 1 acquired by the lane structure acquisition unit 32, and It is determined whether the preceding vehicle 3 traveling on the road 2 in front of the vehicle has changed lanes. For example, the lane change detection unit 33 determines whether the preceding vehicle 3 has changed lanes from the first lane 2a in which the own vehicle 1 is currently traveling to the second lane 2b which is an adjacent lane to the first lane 2a. Alternatively, the lane change detection unit 33 determines whether the preceding vehicle 3 has changed lanes from the second lane 2b to the first lane 2a.

For example, the lane change detection unit 33 changes from the first lane 2a to the second lane 2b or from the second lane 2b based on the position where the preceding vehicle 3 is traveling at the current time and the trajectory the preceding vehicle 3 has traveled in the past. A lane change may be detected by determining whether the vehicle has moved from the vehicle to the first lane 2a.
For example, the lane change detection unit 33 may predict the future position of the preceding vehicle 3 from the attitude and speed of the preceding vehicle 3, and determine whether the preceding vehicle should change lanes based on the predicted position of the preceding vehicle 3 and the lane position. good.

The destination display acquisition unit 34 acquires information on destination displays that indicate the destinations of the lanes of the road 2 that exist around the vehicle 1 based on the self-position of the own vehicle 1 estimated by the self-position estimating unit 30. Get from.
See FIG. 4A. For example, the destination display may be a guide sign painted on the road surface of the first lane 2a and the second lane 2b, indicating the place name of each destination of each lane. The guide sign is not limited to the place name, but may be a display indicating the destination of the lane (for example, "Shito Expressway", "○○ Street", "National Highway").

See FIG. 4B. For example, the destination display may be a road marking painted on the road surface of the first lane 2a and the second lane 2b, indicating the traffic classification according to the direction of travel of each lane.
Furthermore, the destination display is not limited to road markings, and may be signboards such as road signs. For example, the destination display may be a guide sign indicating the place name or name of each destination of each lane, or may be a road sign indicating traffic classification by direction of travel.
Note that the destination display acquisition unit 34 may acquire destination display information based not only on the self-position and the map database 14 but also on the detection results of the object sensor 11.

See FIG. 3. The lane selection intention estimating unit 35 determines whether the preceding vehicle 3 traveling in the first lane 2a selects the first lane 2a and travels based on some intention.
That is, when the occupant of the preceding vehicle 3 is manually driving the preceding vehicle 3, the first lane 2a is selected based on the intention of the occupant of the preceding vehicle 3, and the preceding vehicle 3 is driven on the first lane 2a. Determine whether or not the vehicle is running.
Furthermore, when the preceding vehicle 3 is being automatically driven by an automatic driving device or a driving support device, the first lane 2a is selected based on the determination by these devices, and the preceding vehicle 3 is driven on the first lane 2a. Determine whether or not.
In this way, the intention or decision by the occupant of the preceding vehicle 3, the automatic driving device, or the driving support device to select the first lane 2a as the lane in which the preceding vehicle 3 travels is expressed as a "lane selection intention."

For example, the lane selection intention may be an intention or decision to select the first lane 2a depending on the planned destination of the preceding vehicle 3.
For example, in a situation where the destination display acquisition unit 34 has acquired destination display information (i.e., a situation where destination displays exist around the own vehicle 1 (that is, around the preceding vehicle 3)), the preceding vehicle 3 is located in the first lane 2a. If the vehicle is traveling in the first lane 2a, it is considered that there is a lane selection intention to select the first lane 2a.
Therefore, if the lane selection intention estimation unit 35 detects that the preceding vehicle 3 continues to travel in the first lane 2a after the destination display acquisition unit 34 acquires the destination display information, the lane selection intention estimation unit 35 It is assumed that there is a lane selection intention to select .

For example, as shown in FIG. 5A, the lane selection intention estimating unit 35 detects whether the lane change detecting unit 33 selects the first lane after the destination display obtaining unit 34 obtains destination display information (preferably within a predetermined time). When a lane change of the preceding vehicle 3 to 2a is detected, it may be estimated that there is a lane selection intention to select the first lane 2a. In this case, a more aggressive lane selection intention can be estimated.
For example, as shown in FIG. 5B, when the number of lanes on the road 2 increases, the lane selection intention estimation unit 35 detects a lane change when the preceding vehicle 3 changes to the newly increased first lane 2a. If the unit 33 detects this, it may be estimated that there is a lane selection intention to select the first lane 2a.

See FIG. 3. The three-dimensional object detection unit 36 detects three-dimensional objects around the host vehicle 1 and the preceding vehicle 3. Here, the three-dimensional object is a structure such as a wall or a building that obstructs the view from the own vehicle 1 and the preceding vehicle 3.
For example, the three-dimensional object detection unit 36 may detect three-dimensional objects around the own vehicle 1 and the preceding vehicle 3 based on the detection results of the object sensor 11. For example, when using point cloud data output by the LIDAR of the object sensor 11, the point cloud data is input into a known method such as occupancy grid, which is known in robotics, to detect a moving object such as a preceding vehicle. You may generate a three-dimensional object map with the three-dimensional object removed.
Furthermore, for example, the three-dimensional object detection unit 36 may acquire information on three-dimensional objects around the own vehicle 1 and the preceding vehicle 3 from the map database 14 based on the own position of the own vehicle 1 .

The detectable area estimating unit 37 estimates the detectable area of the preceding vehicle 3 based on the position and orientation of the preceding vehicle 3 detected by the object detecting unit 31 and the information on the three-dimensional object detected by the three-dimensional object detecting unit 36. do.
For example, the detectable area estimation unit 37 estimates, as the detectable area, an area that a typical driver can visually recognize while monitoring or gazing forward. For example, the area excluding the blind spot caused by the three-dimensional object detected by the three-dimensional object detection unit 36 is estimated as the detectable area from the range of the visual field of the driver who is monitoring or gazing forward.
Alternatively, assuming that the preceding vehicle 3 is automatically driven by an automatic driving device or a driving support device, an object detection unit such as a sensor installed in the preceding vehicle 3 detects surrounding objects in front of the preceding vehicle 3. The detectable area is estimated as the detectable area.
For example, the area determined by the azimuth angle range, vertical angle range, and distance range that can be detected by the object detection unit, excluding the blind spot caused by the three-dimensional object detected by the three-dimensional object detection unit 36, is estimated as the detectable area.

The area change amount detection unit 38 detects whether the detectable area of the preceding vehicle 3 has changed over time. That is, it is determined whether a new detectable area has been created.
An example of changes over time in the detectable area is shown in FIGS. 6A and 6B. The hatched area 6a indicates the detectable area at the first time t1, and the hatched area 6b indicates the detectable area at the second time t2 after the first time t1. Points P1 and P2 are the locations of the preceding vehicle 3 at the first time t1 and the second time t2, respectively. The same applies to FIGS. 7A and 7B, which will be described later.

In the example of FIGS. 6A and 6B, as the attitude of the preceding vehicle 3 changes, the azimuth angle range (yaw angle range , and a detectable direction) changes over time.
Other examples of changes over time in the detectable area are shown in FIGS. 7A and 7B. Reference numerals 7a and 7b indicate three-dimensional objects around the preceding vehicle 3.
In the examples shown in FIGS. 7A and 7B, the detectable region (detectable angular range) changes over time due to changes in the relative positional relationship between the preceding vehicle 3 and the three-dimensional objects 7a and 7b.

See FIG. 3. For example, the area change amount detection unit 38 detects the amount of change in the detectable area over a predetermined long period of time (unit period) or the amount of change in the detectable area while the preceding vehicle 3 travels a predetermined distance as the "area change amount." , it may be detected whether or not a change over time has occurred in the detectable area according to the amount of area change.
For example, the area change amount detection unit 38 detects the detectable area from the area covered by the detectable area 6a at the first time t1 and the detectable area 6b at the second time t2 after a predetermined period of time from the first time t1. The area of the area excluding the overlapping area of 6a and 6b may be detected as the area change amount.

For example, the area change amount detection unit 38 detects the detectable area 6a from the area covered by the detectable area 6a at point P1 and the detectable area 6b at point P2 where the preceding vehicle 3 has advanced a predetermined distance from point P1. The area of the region excluding the overlapping region of and 6b may be detected as the amount of region change.
The area change amount detection unit 38 detects the occurrence of a change over time in the detectable area when the area change amount is equal to or greater than the threshold value (that is, when the area change amount equal to or greater than the threshold value is detected).
Alternatively, the area change amount detection unit 38 may detect the occurrence of a change over time in the detectable area when the overlapping area between the detectable area 6a and the detectable area 6b is less than or equal to a predetermined value. In other words, how close the overlapping area is to zero may be determined as the area change amount, and when the overlapping area is less than or equal to a predetermined value, it may be detected that the area change amount is greater than or equal to a threshold value.

The lane change inhibiting factor determining unit 39 determines whether or not there is a "lane change inhibiting factor" that is a factor inhibiting a lane change from the first lane 2a to the second lane 2b.
For example, when a vehicle running parallel to the preceding vehicle 3 running in the first lane 2a runs in the second lane 2b, such a vehicle running parallel to the preceding vehicle 3 may obstruct the lane change from the first lane 2a to the second lane 2b. sell. Therefore, the lane change inhibiting factor determination unit 39 determines that a lane change inhibiting factor exists when such a parallel vehicle exists.
For example, the lane change inhibiting factor determination unit 39 determines that when there is a parallel vehicle traveling in the second lane 2b within a predetermined distance in the longitudinal direction or within a predetermined inter-vehicle time in the longitudinal direction of the preceding vehicle 3 traveling in the first lane 2a. , it is determined that there is a factor inhibiting lane change.

For example, if the speed change or acceleration change of the preceding vehicle 3 when changing lanes from the first lane 2a to the second lane 2b is a predetermined change or more, the lane change inhibiting factor determination unit 39 determines that the lane change is not allowed. It is considered that there was some reason that required speed or acceleration adjustment, and therefore, it is determined that there is a factor that inhibits the lane change.

The driving impediment factor estimating section 40 is based on the estimation result of the lane selection intention estimating section 35, the detection result of the area change amount detecting section 38, and the determination result of the lane change impeding factor determining section 39. It is also estimated whether or not there is a driving inhibiting factor that inhibits the driving of the preceding vehicle 3 in front of the preceding vehicle 3.
Specifically, the driving impediment factor estimating unit 40 detects the detectable region of the preceding vehicle 3 within a first predetermined time after a change over time occurs (for example, after detecting the amount of change in the region equal to or greater than a threshold value). , when the preceding vehicle 3 changes lanes from the first lane 2a to the second lane 2b, and it is estimated that there is an intention to select a lane within the second predetermined time period before the temporal change in the detectable area occurs. In this case, it is assumed that there is a driving-impeding factor.

On the other hand, even if the preceding vehicle 3 changes lanes from the first lane 2a to the second lane 2b, if the first predetermined time has elapsed since the temporal change in the detectable area of the preceding vehicle 3 occurs. It is estimated that there is no probability that a driving impediment factor exists.
Even if it is not estimated that there is an intention to select a lane during the period from the time when a change in the detectable area occurs over time to before the second predetermined time, it is also estimated that there is no probability that a driving impediment factor exists.

Further, the driving impediment factor estimating unit 40 determines that the preceding vehicle 3 has changed lanes from the first lane 2a to the second lane 2b within a first predetermined time after the occurrence of a change over time in the detectable area of the preceding vehicle 3. If it is estimated that there is an intention to select a lane during the period from the time when a change in the detectable area occurs over time to before the second predetermined time, and if it is determined that there is a lane change inhibiting factor, the driving It may be assumed that an inhibiting factor exists.
When determining that a lane change inhibiting factor does not exist, the driving inhibiting factor estimating unit 40 may determine that a driving inhibiting factor does not exist.

Further, the driving impediment factor estimating unit 40 determines that the preceding vehicle 3 has changed lanes from the first lane 2a to the second lane 2b within a first predetermined time after the occurrence of a change over time in the detectable area of the preceding vehicle 3. If it is estimated that there is an intention to select a lane during the period from the time when the change over time in the detectable area occurs to before the second predetermined time, it is estimated that there is a driving inhibiting factor, and the lane change inhibiting factor is determined. The probability of existence of the driving-hindering factor may be estimated depending on whether or not the driving-hindering factor exists.

For example, the driving impediment factor estimating unit 40 determines that there is a parallel vehicle traveling in the second lane 2b within a predetermined distance in the longitudinal direction or within a predetermined inter-vehicle time in the longitudinal direction of the preceding vehicle 3 traveling in the first lane 2a, and If the speed change or acceleration change of the preceding vehicle 3 when changing lanes from the first lane 2a to the second lane 2b is greater than a predetermined change, the driver is taking a risk in changing lanes, which is a driving impediment factor. It can be estimated that there is a high probability that there exists.

On the other hand, if there is no parallel vehicle traveling in the second lane 2b within a predetermined distance in the longitudinal direction or within a predetermined inter-vehicle time in the longitudinal direction of the preceding vehicle 3 traveling in the first lane 2a, or if there is a preceding vehicle when changing lanes. If the speed change or acceleration change in No. 3 is less than the predetermined change, it may be estimated that the probability of the presence of a travel inhibiting factor is medium. In this manner, the driving impediment factor estimating unit 40 may estimate that the probability that a driving impediment factor exists is medium when a lane change impeding factor does not exist.

Furthermore, even if the preceding vehicle 3 changes lanes from the first lane 2a to the second lane 2b, if the first predetermined time has elapsed since the temporal change in the detectable area of the preceding vehicle 3 occurs, , it may be estimated that the probability of the presence of a driving-hindering factor is low.
Even if it is not estimated that there is an intention to select a lane within the second predetermined time period before the temporal change in the detectable area occurs, it may be estimated that the probability that a driving-hindering factor exists is low.

The vehicle control unit 41 supports the running of the own vehicle 1 by controlling the running of the own vehicle 1 according to the estimation result by the running inhibiting factor estimating unit 40.
Specifically, when the driving inhibiting factor estimating unit 40 estimates that a driving inhibiting factor exists, the host vehicle 1 changes lanes from the first lane 2a to the second lane 2b similarly to the preceding vehicle 3. Controls the running of the own vehicle 1. The same applies when the running inhibiting factor estimating unit 40 estimates that there is a high possibility that a running inhibiting factor exists. The vehicle control unit 41 generates a target travel trajectory and a target speed profile for changing lanes from the first lane 2a to the second lane 2b.

On the other hand, when the travel inhibiting factor estimating unit 40 estimates that the traveling inhibiting factor does not exist, the vehicle 1 is controlled to continue traveling in the first lane 2a. The same applies when the running inhibiting factor estimating unit 40 estimates that there is a low possibility that the running inhibiting factor exists. The vehicle control unit 41 generates a target travel trajectory and a target speed profile for continuing to travel in the first lane 2a.

Further, when the driving impeding factor estimating unit 40 estimates that the driving impeding factor exists to a moderate degree, the preceding vehicle 3 changed lanes from the first lane 2a to the second lane 2b for reasons other than the driving impeding factor. There may be cases.
In this case, the vehicle control unit 41 controls the vehicle 1 traveling in the first lane 2a and the parallel vehicle traveling in the first lane 2a so that the vehicle 1 can easily change lanes to the second lane 2b. The traveling of the host vehicle 1 is controlled so that the distance or time between the vehicles in the longitudinal direction with respect to the vehicle 1 becomes a predetermined length or more.
The vehicle control unit 41 generates a target travel trajectory so as to continue traveling in the first lane 2a, and sets a target speed so that the distance or time between the vehicle 1 and the vehicle 1 in the longitudinal direction becomes longer than a predetermined length. Generate a profile.

The vehicle control unit 41 causes the own vehicle 1 to automatically travel along the target travel trajectory by driving the actuator 18 so that the own vehicle 1 travels on the target travel trajectory at a speed according to the generated target speed profile. Controls the steering direction and steering speed of the steering mechanism of the own vehicle 1. Further, the accelerator opening degree of the own vehicle 1 or the braking amount of the brake device is controlled according to the target speed profile.

Note that instead of or in addition to controlling the traveling of the own vehicle 1 so as to change the lane from the first lane 2a to the second lane 2b, the vehicle control unit 41 changes the lane from the first lane 2a to the second lane 2b. The driving of the host vehicle 1 may be supported by outputting a message from the output device 19 urging the driver to change lanes.
Further, instead of or in addition to controlling the driving of the own vehicle 1 so as to continue driving in the first lane 2a, by outputting a message from the output device 19 urging the vehicle 1 to continue driving in the first lane 2a, The driving of the own vehicle 1 may be supported.

Further, the driving of the own vehicle 1 is controlled so that the distance or time between vehicles in the longitudinal direction between the parallel vehicle running on the second lane 2b and the own vehicle 1 running on the first lane 2a is equal to or longer than a predetermined length. Instead or in addition, the output device 19 outputs a message urging the user to adjust the speed of the host vehicle 1 so that the following distance or inter-vehicle time becomes longer than a predetermined length, thereby controlling the running of the host vehicle 1. You may support them.

(motion)
Next, an example of the driving support method according to the embodiment will be described with reference to FIGS. 8 to 10. FIG. 8 shows the overall flow of the driving support method according to the embodiment.
In step S1, the self-position estimating unit 30 estimates the current position of the own vehicle 1, the attitude of the own vehicle 1, and the speed on the map stored in the map database 14.

In step S2, the object detection unit 31 detects an object around the own vehicle 1 using the object sensor 11, and obtains the position, speed, and size of the object. Further, it is determined whether the detected object is the preceding vehicle 3, and the position of the preceding vehicle 3 is detected.
In step S3, the lane structure acquisition unit 32 acquires information about the lane structure in front of the own vehicle 1 on the road 2 on which the own vehicle 1 travels from the map database 14 based on the own position of the own vehicle 1.
In step S4, the lane change detection section 33, destination display acquisition section 34, and lane selection intention estimation section 35 execute lane selection intention estimation processing. In the lane selection intention estimation process, it is estimated whether or not there is a lane selection intention to select the first lane 2a as the lane in which the preceding vehicle 3 will travel, depending on the planned destination of the preceding vehicle 3.
The lane selection intention estimation process will be described with reference to FIG.

In step S10, the destination display acquisition unit 34 acquires information on destination displays of lanes of the road 2 around the vehicle 1 based on the self-position of the vehicle 1 estimated by the self-position estimating unit 30. It is determined whether or not it has been detected. If destination display information is detected (step S10: Y), the process advances to step S11. If destination display information is not detected (step S10: N), step S11 is skipped and the process proceeds to step S12.

In step S11, the destination display acquisition unit 34 acquires information on the destination display of the lanes of the road 2 from the map database 14.
In step S12, the lane selection intention estimation unit 35 determines whether the lane change detection unit 33 has detected a lane change of the preceding vehicle 3 to the first lane 2a. If a lane change is detected (step S12: Y), the process advances to step S13. If a lane change is not detected (step S12: N), the process proceeds to step S14.

In step S13, the lane selection intention estimating unit 35 determines whether the number of lanes on the road 2 has increased and the detected lane change is a lane change to the newly increased first lane 2a. If the lane change is to the newly added first lane 2a (step S13: Y), the process proceeds to step S15. If the lane change is not to the newly increased first lane 2a (step S13: N), the process proceeds to step S14.

In step S14, the lane selection intention estimation unit 35 determines whether the preceding vehicle 3 is traveling in the first lane 2a after the destination display acquisition unit 34 acquires the destination display information. If the preceding vehicle 3 is traveling in the first lane 2a after acquiring the destination display information (step S14: Y), the process proceeds to step S15. If destination display information has not been acquired (step S14: N), the process advances to step S16.
In step S15, the lane selection intention estimating unit 35 estimates that there is an intention to select a lane. Thereafter, the process proceeds to step S5 in FIG.
In step S16, the lane selection intention estimating unit 35 estimates that there is no intention to select a lane. Thereafter, the process proceeds to step S5 in FIG.

Refer to FIG. In step S5, the lane change detection unit 33, the three-dimensional object detection unit 36, the detectable area estimation unit 37, the area change amount detection unit 38, the lane change inhibition factor determination unit 39, and the driving inhibition factor estimation unit 40, Execute driving-hindering factor estimation processing. In the travel inhibiting factor estimation process, the probability of existence of a traveling inhibiting factor that inhibits the traveling of the preceding vehicle 3 on the first lane 2a and in front of the preceding vehicle 3 is estimated.
The driving inhibiting factor estimation process will be explained with reference to FIG.

In step S20, the three-dimensional object detection unit 36 detects three-dimensional objects around the host vehicle 1 and the preceding vehicle 3. The detectable area estimating unit 37 estimates the detectable area of the preceding vehicle 3 based on the position and orientation of the preceding vehicle 3 detected by the object detecting unit 31 and the information on the three-dimensional object detected by the three-dimensional object detecting unit 36. do.
In step S21, the area change amount detection unit 38 detects whether a new detectable area of the preceding vehicle 3 has been created, that is, whether there is a change over time in the detectable area. If a change over time in the detectable area occurs (step S21: Y), the process proceeds to step S22. If the detectable area does not change over time (step S21: N), the process returns to step S20.

However, if the lane selection intention estimating unit 35 does not estimate that there is an intention to select a lane, or if the occurrence of a change over time in the detectable area occurs after a second predetermined period of time has elapsed since it was estimated that there was an intention to select a lane. If it is later than that, the running inhibiting factor estimating unit 40 estimates that the probability that the running inhibiting factor exists is low, and the process proceeds to step S6 in FIG. 8.
In step S22, the driving impediment factor estimating unit 40 starts counting the time that has elapsed since the occurrence of a change over time in the detectable area.

In step S23, the driving impediment factor estimation unit 40 determines whether the lane change detection unit 33 has detected a lane change of the preceding vehicle 3 from the first lane 2a to the second lane 2b. If a lane change of the preceding vehicle 3 is detected (step S23: Y), the process proceeds to step S24. If the lane change of the preceding vehicle 3 is not detected (step S23: N), the process proceeds to step S28.
In step S24, the lane change inhibiting factor determining unit 39 determines that there is a parallel vehicle traveling in the second lane 2b within a predetermined distance in the longitudinal direction or within a predetermined inter-vehicle time in the longitudinal direction of the preceding vehicle 3 traveling in the first lane 2a. Determine whether or not. If a parallel vehicle exists (step S24: Y), the process advances to step S25. If there is no parallel vehicle (step S24: N), the process proceeds to step S27.

In step S25, the lane change inhibiting factor determination unit 39 determines whether or not the speed change and acceleration change of the preceding vehicle 3 when changing lanes from the first lane 2a to the second lane 2b are greater than or equal to a predetermined change. If the speed change or acceleration change is greater than or equal to the predetermined change (step S25: Y), the process proceeds to step S26. If the speed change or acceleration change is not greater than the predetermined change (step S25: N), the process proceeds to step S27.

In step S26, the running inhibiting factor estimating unit 40 estimates that there is a high probability that a running inhibiting factor exists. Thereafter, the process proceeds to step S6 in FIG.
In step S27, the running inhibiting factor estimating unit 40 estimates that the probability that the running inhibiting factor exists is medium. Thereafter, the process proceeds to step S6 in FIG.

On the other hand, if the lane change detection unit 33 does not detect the lane change of the preceding vehicle 3 from the first lane 2a to the second lane 2b (step S23: N), the driving impediment factor estimation unit 40 in step S28 It is determined whether or not exceeds a threshold value, that is, whether or not a first predetermined period of time has elapsed since the time-dependent change in the detectable area occurred. If the first predetermined time has not elapsed since the occurrence of the change over time in the detectable area (step S28: N), the process returns to step S23.

If the first predetermined time period has elapsed since the occurrence of a change over time in the detectable area (step S28: Y), the process proceeds to step S29.
In step S29, the running inhibiting factor estimating unit 40 estimates that the probability that the running inhibiting factor exists is low. Thereafter, the process proceeds to step S6 in FIG.
Refer to FIG. In step S6, the vehicle control unit 41 supports the running of the own vehicle 1 by controlling the running of the own vehicle 1 according to the estimation result by the running inhibiting factor estimating unit 40.

Specifically, when the driving inhibiting factor estimating unit 40 estimates that there is a high possibility that a driving inhibiting factor exists, the vehicle control unit 41 causes the own vehicle 1 to move from the first lane 2a to the second lane similarly to the preceding vehicle 3. The driving of the own vehicle 1 is controlled so as to change lanes to lane 2b.
Instead of or in addition to the driving control of the own vehicle 1, the driving of the own vehicle 1 may be supported by outputting from the output device 19 a message prompting to change lanes from the first lane 2a to the second lane 2b. good.

When the running inhibiting factor estimating unit 40 estimates that there is a medium possibility that a running inhibiting factor exists, the vehicle control unit 41 determines whether a parallel vehicle running in the second lane 2b and a vehicle running in the first lane 2a are present. The traveling of the host vehicle 1 is controlled so that the distance or time between the vehicles in the longitudinal direction with respect to the vehicle 1 becomes a predetermined length or more.
Instead of or in addition to the driving control of the own vehicle 1, the own vehicle 1 may be supported.

When the driving inhibiting factor estimating unit 40 estimates that the possibility of the existence of the driving inhibiting factor is low, the vehicle control unit 41 controls the driving of the host vehicle 1 so as to continue driving in the first lane 2a.
Instead of or in addition to the driving control of the own vehicle 1, the driving of the own vehicle 1 may be supported by outputting a message from the output device 19 urging the user to continue driving in the first lane 2a.
The process then ends.

(Effects of embodiment)
(1) The object detection unit 31 detects the position of objects existing around the own vehicle 1 and the position of the preceding vehicle 3 traveling in front of the own vehicle 1 on the road on which the own vehicle 1 is traveling. The detectable area estimating unit 37 estimates a detectable area, which is an area that can be visually recognized by the occupant of the preceding vehicle 3 or an area in which an object detection unit included in the preceding vehicle 3 can detect surrounding objects in front of the preceding vehicle 3. The area change amount detection unit 38 detects the amount of change in the detectable area over a predetermined long period of time, or the amount of change in the detectable area while the preceding vehicle 3 travels a predetermined distance. When the driving impediment factor estimating unit 40 detects that the preceding vehicle 3 has changed lanes from the first lane 2a to the second lane 2b on the road within a first predetermined time after detecting the area change amount that is equal to or greater than the threshold value. It is estimated that there is a travel inhibiting factor that inhibits the vehicle's travel on the first lane 2a and in front of the preceding vehicle 3.
As a result, it is possible to determine whether or not the lane change has been made at a timing when there is a high probability of avoiding the travel-inhibiting factor, so it is possible to accurately estimate the presence or absence of the travel-inhibiting factor ahead on the first lane 2a.

(2) When the driving impediment factor estimating unit 40 detects the area change amount equal to or greater than the threshold value and within a first predetermined time period, the preceding vehicle 3 changes lanes from the first lane 2a to the second lane 2b, And if a lane change of the preceding vehicle 3 to the first lane 2a or a destination display of the first lane 2a is detected during the period from the time when the amount of area change equal to or greater than the threshold value is detected until the second predetermined time period, the driving is inhibited. Presuming that a factor exists.
As a result, if a lane change is made due to a change in the detectable area in a situation where it is possible to estimate the lane selection intention of the preceding vehicle 3 to drive on the first lane 2a, it is possible to avoid driving impediments. It is considered to be highly probable. By detecting such a lane change, it is possible to accurately estimate the presence or absence of a driving impediment factor.

(3) The lane selection intention estimating unit 35 indicates that the occupant of the preceding vehicle 3 or the automatic driving device of the preceding vehicle 3 intends to select the first lane 2a and cause the preceding vehicle 3 to drive according to the destination of the preceding vehicle 3. Estimating the presence or absence of lane selection intention. When the preceding vehicle 3 changes lanes from the first lane 2a to the second lane 2b within a first predetermined time after detecting the area change amount that is equal to or greater than a threshold value, the driving impediment factor estimating unit 40 detects a change amount equal to or greater than the threshold value. If it is estimated that there is an intention to select a lane during the period from the time when the amount of change in the area is detected to before the second predetermined time, it is estimated that a driving inhibiting factor exists.
As a result, if a lane change is made due to a change in the detectable area in a situation where it is possible to estimate the lane selection intention of the preceding vehicle 3 to drive on the first lane 2a, it is possible to avoid driving impediments. It is considered to be highly probable. By detecting such a lane change, it is possible to accurately estimate the presence or absence of a driving impediment factor.

(4) The lane change inhibiting factor determination unit 39 determines whether there is a lane change inhibiting factor that inhibits a lane change from the first lane 2a to the second lane 2b. The driving impediment factor estimating unit 40 determines that there is a lane change impeding factor when the preceding vehicle 3 changes lanes from the first lane 2a to the second lane 2b within a first predetermined time after detecting the area change amount equal to or greater than a threshold value. If it is determined that there is a driving inhibiting factor, it is estimated that there is a driving inhibiting factor.
By determining that a lane change has been made despite the presence of a lane change inhibiting factor, it is possible to more accurately estimate the presence or absence of a travel inhibiting factor.

(5) When the lane change inhibiting factor determination unit 39 detects another vehicle traveling in the second lane 2b within a predetermined distance in the longitudinal direction or within a predetermined inter-vehicle time in the longitudinal direction of the preceding vehicle 3 traveling in the first lane 2a. It is estimated that there are factors that inhibit lane changes.
Thereby, it is possible to estimate the presence or absence of a lane change inhibiting factor, and by determining that a lane change has been made despite the presence of such a lane change inhibiting factor, it is possible to estimate the presence or absence of a travel inhibiting factor with higher accuracy.

(6) The lane change inhibiting factor determination unit 39 estimates that a lane change inhibiting factor exists if the speed change of the preceding vehicle 3 when changing lanes from the first lane 2a to the second lane 2b is equal to or greater than a predetermined change. do.
Thereby, it is possible to estimate the presence or absence of a lane change inhibiting factor, and by determining that a lane change has been made despite the presence of such a lane change inhibiting factor, it is possible to estimate the presence or absence of a travel inhibiting factor with higher accuracy.

(7) The lane change inhibiting factor determination unit 39 estimates that a lane change inhibiting factor exists when the change in acceleration of the preceding vehicle 3 when changing lanes from the first lane 2a to the second lane 2b is equal to or greater than a predetermined change. do.
Thereby, it is possible to estimate the presence or absence of a lane change inhibiting factor, and by determining that a lane change has been made despite the presence of such a lane change inhibiting factor, it is possible to estimate the presence or absence of a travel inhibiting factor with higher accuracy.

(8) When the driving inhibiting factor estimating unit 40 estimates that a driving inhibiting factor exists, the vehicle control unit 41 supports the driving of the own vehicle 1 so that the own vehicle 1 runs on the second lane 2b.
As a result, when there is a high possibility that a running inhibiting factor exists, it is possible to support the running of the host vehicle 1 so that the running inhibiting factor can be avoided and the vehicle 1 can be driven smoothly.

(9) It is determined that the preceding vehicle 3 changes lanes from the first lane 2a to the second lane 2b within the first predetermined time after detecting the area change amount equal to or greater than the threshold value, and that there is no lane change inhibiting factor. In this case, the vehicle control unit 41 controls the own vehicle 1 so that the distance between the other vehicles traveling in the second lane 2b and the own vehicle 1 traveling in the first lane 2a in the longitudinal direction or the inter-vehicle time becomes a predetermined length or more. to support running.
As a result, if there is still a possibility that a driving impediment factor exists, it is possible to detect the driving impediment factor and then smoothly change lanes to avoid the driving impediment factor. Vertical spacing can be secured.

DESCRIPTION OF SYMBOLS 1... Own vehicle, 2... Road, 2a... 1st lane, 2b... 2nd lane, 3... Leading vehicle, 6a, 6b... Detectable area, 10... Driving support device, 11... Object sensor, 12... Vehicle sensor, 13... Positioning device, 14... Map database, 15... Communication device, 16... Navigation system, 17... Controller, 18... Actuator, 19... Output device, 21... Processor, 22... Storage device, 30... Self-position estimation unit, 31 ...Object detection section, 32... Lane structure acquisition section, 33... Lane change detection section, 34... Ahead display acquisition section, 35... Lane selection intention estimation section, 36... Three-dimensional object detection section, 37... Detectable area estimation section, 38 ...Area change amount detection unit, 39...Lane change inhibiting factor determining unit, 40...Driving inhibiting factor estimating unit, 41...Vehicle control unit

Claims (10)

an object detection sensor detects the position of a preceding vehicle traveling in front of the host vehicle on the road on which the host vehicle is traveling;
The controller is
estimating a detectable area that is an area that is visible to a passenger of the preceding vehicle or an area where an object detection unit of the preceding vehicle can detect surrounding objects in front of the preceding vehicle;
detecting an amount of change in the detectable area over a predetermined period of time or an amount of change in the detectable area while the preceding vehicle travels a predetermined distance;
If it is detected that the preceding vehicle has changed lanes from the first lane to the second lane on the road within a first predetermined time after detecting the area change amount that is equal to or greater than the threshold value, A driving environment estimation method characterized by estimating the presence of a driving inhibiting factor that is a factor that inhibits the driving of a vehicle in front of the preceding vehicle. When the preceding vehicle changes lanes from the first lane to the second lane within the first predetermined time after detecting the area change amount that is equal to or greater than the threshold value, the controller detects the area change amount that is equal to or greater than the threshold value. If a lane change of the preceding vehicle to the first lane or a destination display of the first lane is detected during a period from the time when the area change amount of is detected to a second predetermined time before, the driving inhibiting factor 2. The driving environment estimation method according to claim 1, further comprising estimating the existence of a vehicle. The controller includes:
Estimating whether or not an occupant of the preceding vehicle or an automatic driving device of the preceding vehicle has a lane selection intention that is an intention to select the first lane and cause the preceding vehicle to drive according to the destination of the preceding vehicle;
The preceding vehicle changes lanes from the first lane to the second lane within the first predetermined time after detecting the area change amount that is greater than or equal to the threshold value, and the area change is greater than or equal to the threshold value. 2. The vehicle according to claim 1, wherein if it is estimated that the intention to select the lane exists during a period from when the amount is detected to before a second predetermined time, it is estimated that the driving impediment factor exists. Driving environment estimation method. The controller includes:
Determining whether a lane change inhibiting factor exists that is a factor inhibiting a lane change from the first lane to the second lane;
When it is determined that the lane change inhibiting factor exists when the preceding vehicle changes lanes from the first lane to the second lane within the first predetermined time after detecting the area change amount that is equal to or greater than the threshold value; The driving environment estimation method according to any one of claims 1 to 3, further comprising estimating the existence of the driving inhibiting factor. When the controller detects another vehicle traveling in the second lane within a predetermined distance in the longitudinal direction or within a predetermined inter-vehicle time in the longitudinal direction of the preceding vehicle traveling in the first lane, the controller detects that the lane change inhibiting factor is detected. The driving environment estimation method according to claim 4, characterized in that the driving environment is estimated to exist. The controller estimates that the lane change inhibiting factor exists if a speed change of the preceding vehicle when changing lanes from the first lane to the second lane is a predetermined change or more. The driving environment estimation method according to item 4 or 5. The controller estimates that the lane change inhibiting factor exists if a change in acceleration of the preceding vehicle when changing lanes from the first lane to the second lane is greater than or equal to a predetermined change. The driving environment estimation method according to any one of items 4 to 6. When the controller estimates that the travel inhibiting factor exists by the driving environment estimation method according to any one of claims 1 to 7, the controller controls the host vehicle so that the host vehicle runs on the second lane. A driving support method that supports driving of a vehicle. The controller may cause the preceding vehicle to move to the first lane within the first predetermined time after detecting the area change amount that is equal to or greater than the threshold value using the driving environment estimation method according to any one of claims 4 to 7. in the longitudinal direction between another vehicle traveling in the second lane and the own vehicle traveling in the first lane when the vehicle changes lanes from A driving support method for supporting the driving of the host vehicle so that the following distance or the following time becomes a predetermined length or more. an object detection sensor that detects the position of a preceding vehicle traveling in front of the host vehicle on a road on which the host vehicle is traveling;
Estimate a detectable area that is an area that is visible to the occupants of the preceding vehicle or an area where an object detection unit of the preceding vehicle can detect surrounding objects in front of the preceding vehicle; or an area change amount that is the amount of change in the detectable area while the preceding vehicle travels a predetermined distance, and detects the area change amount that is the amount of change in the detectable area while the preceding vehicle travels a predetermined distance. When it is detected that the vehicle has changed lanes from the first lane to the second lane on the road, there is a travel inhibiting factor that inhibits the vehicle's travel on the first lane and in front of the preceding vehicle. a controller that estimates that
A driving environment estimation device comprising:

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