JP7236279B2 - Driving support method and driving support device - Google Patents

Description

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

A method of determining whether or not a vehicle can travel on a road when an obstacle exists in front of the vehicle is known (Patent Document 1). The invention described in Patent Document 1 extracts feature points that characterize the shape of an assumed route from detection points representing boundaries of a travel path and detection points representing obstacles, and calculates the distance between the feature points and the assumed route. Then, based on the calculated distance, it is determined whether or not the vehicle can travel on the travel road.

JP 2015-36842 A

When a plurality of assumed routes are generated, the invention described in Patent Literature 1 compares the distances between the assumed routes and feature points, and selects the assumed route with the maximum distance. However, the assumed route with the maximum distance is not necessarily the most efficient route.

SUMMARY OF THE INVENTION The present invention has been made in view of the above problems, and an object of the present invention is to provide a driving assistance method and a driving assistance device capable of generating an efficient route when an obstacle exists in front of the own vehicle. is to provide

A driving support method according to an aspect of the present invention detects obstacles, sets a travelable area within a roadway excluding the obstacles, and creates a plurality of line segments connecting points on the borderline of the sensor and the travelable area. set, select the longest line segment from the set multiple line segments, classify whether the obstacle is on the left or right side of the selected longest line segment in the vehicle width direction as seen from the sensor, Based on the result of classification, the drivable area is reset, and a travel route for the vehicle is generated within the reset drivable area.

According to the present invention, an efficient route can be generated when an obstacle exists in front of the own vehicle.

FIG. 1 is a schematic configuration diagram of a driving support device according to an embodiment of the present invention. FIG. 2 is a diagram illustrating an example of a travelable area according to the embodiment of the invention. FIG. 3 is a diagram illustrating an example of a driving scene according to the embodiment of the invention. FIG. 4 is a diagram illustrating an example of an obstacle classification method according to the embodiment of the present invention. FIG. 5 is a diagram illustrating an example of an obstacle classification method according to the embodiment of the present invention. FIG. 6 is a diagram illustrating an example of a method for resetting the travelable area according to the embodiment of the present invention. FIG. 7 is a flow chart illustrating an operation example of the driving support device according to the embodiment of the present invention. FIG. 8 is a diagram illustrating an example of a driving scene according to another embodiment of the invention. FIG. 9 is a diagram illustrating an example of a method for resetting the travelable area according to another embodiment of the present invention. FIG. 10 is a diagram illustrating an example of a detection point storage method according to the embodiment of the present invention. FIG. 11 is a diagram illustrating an example of a driving scene according to another embodiment of the invention. FIG. 12 is a diagram illustrating an example of an obstacle classification method according to another embodiment of the present invention. FIG. 13 is a diagram illustrating an example of a method for resetting the travelable area according to another embodiment of the present invention.

BEST MODE FOR CARRYING OUT THE INVENTION Hereinafter, embodiments of the present invention will be described with reference to the drawings. In the description of the drawings, the same parts are denoted by the same reference numerals, and the description thereof is omitted.

(Configuration example of driving support device 1)
A configuration example of the driving support device 1 will be described with reference to FIG. 1 . As shown in FIG. 1, the driving support device 1 includes a sensor 10, a camera 11, a GPS receiver 12, a map database 13, and a controller 20.

The driving support device 1 may be mounted in a vehicle having an automatic driving function, or may be mounted in a vehicle without an automatic driving function. Further, the driving support device 1 may be installed in a vehicle capable of switching between automatic driving and manual driving. Note that automatic driving in this embodiment refers to, for example, a state in which at least one of actuators such as a brake, an accelerator, and a steering is controlled without being operated by a passenger. Therefore, other actuators may be operated by the passenger's operation. Further, automatic operation may be a state in which any control such as acceleration/deceleration control or lateral position control is being executed. Further, manual driving in this embodiment refers to a state in which the driver is operating the brake, accelerator, and steering, for example.

The sensor 10 is a device that is mounted on the own vehicle and detects objects around the own vehicle. The sensor 10 includes laser radar, millimeter wave radar, laser range finder, sonar, and the like. The sensor 10 detects moving objects including other vehicles, motorcycles, bicycles and pedestrians, and stationary objects including obstacles, falling objects and parked vehicles as objects around the own vehicle. The sensor 10 also detects the position, orientation (yaw angle), size, speed, acceleration, deceleration, and yaw rate of the moving and stationary objects with respect to the host vehicle. Also, the sensor 10 may include a wheel speed sensor, a steering angle sensor, a gyro sensor, and the like. The sensor 10 outputs detected information to the controller 20 .

The camera 11 is mounted on the own vehicle and photographs the surroundings of the own vehicle. The camera 11 has an imaging device such as a CCD (charge-coupled device) or a CMOS (complementary metal oxide semiconductor). The camera 11 has an image processing function, and detects white lines, road boundaries, road edges, targets, etc. from captured images (camera images). A target is an object provided on a road or sidewalk, such as a traffic light, a utility pole, or a traffic sign. The camera 11 outputs captured images, image analysis results, and the like to the controller 20 . Note that the camera 11 can also detect obstacles around the own vehicle in the same manner as the sensor 10 . The camera 11 will be described below as being included in the sensor 10 .

The GPS receiver 12 detects the position of the vehicle on the ground (hereinafter sometimes referred to as self-position) by receiving radio waves from satellites. The GPS receiver 12 outputs the detected position information of the own vehicle to the controller 20 .

The map database 13 is a database stored in a car navigation device or the like, and stores various data necessary for route guidance such as road information and facility information. The map database 13 also stores information such as the number of road lanes, road boundaries, and targets. The map database 13 outputs map information to the controller 20 in response to requests from the controller 20 . Various types of data such as road information and target information are not necessarily acquired from the map database 13, but may be acquired by the sensor 10, or may be acquired using vehicle-to-vehicle communication or road-to-vehicle communication. good too. In addition, when various data such as road information and target information are stored in a server installed outside, the controller 20 may acquire these data from the server at any time through communication. Further, the controller 20 may periodically acquire the latest map information from an externally installed server and update the map information it holds.

The controller 20 is a general-purpose microcomputer having a CPU (Central Processing Unit), memory, and an input/output unit. A computer program is installed in the microcomputer to function as the driving support device 1 . By executing the computer program, the microcomputer functions as a plurality of information processing circuits included in the driving assistance device 1 . Here, an example of realizing a plurality of information processing circuits provided in the driving support device 1 by software will be shown. It is also possible to construct a circuit. Also, a plurality of information processing circuits may be configured by individual hardware. The controller 20 includes a plurality of information processing circuits including a stationary object recognition unit 21, a self-position estimation unit 22, a road boundary line acquisition unit 23, a travelable area setting unit 24, a far point setting unit 25, and a left/right classification unit. , a travelable area resetting unit 27 , a target route generating unit 28 , and a vehicle control unit 29 .

The stationary object recognition unit 21 recognizes objects around the vehicle based on information acquired from the sensor 10 . The object here is a stationary object (hereinafter simply referred to as a stationary object). Stationary objects include parked vehicles, utility poles, falling objects, and the like. Stationary objects may also include construction sites.

The self-position estimation unit 22 estimates the self-position on the map based on the information acquired from the GPS receiver 12 . The road boundary acquisition unit 23 acquires road boundaries from the map database 13 or the sensor 10 . A road boundary line is a traffic division line that divides a roadway, and is mainly a white line.

The travelable area setting unit 24 sets a travelable area in which the vehicle can travel. Details of the travelable area will be described later. The far point setting unit 25 sets a virtual point in a space that is farthest from the sensor 10 within the travelable area. The left/right classification unit 26 classifies whether the obstacle in front of the vehicle is on the left or right side as viewed from the sensor 10 .

The travelable area resetting unit 27 resets the travelable area based on the result of the classification by the left/right classifying unit 26 . The target route generator 28 generates a route for the host vehicle in the drivable area reset by the drivable area resetter 27 . The vehicle control unit 29 controls the actuator 40 so that the route set by the target route generation unit 28 is passed. The actuator 40 includes a brake actuator, an accelerator actuator, a steering actuator, and the like.

Next, referring to FIG. 2, the travelable area in this embodiment will be described. As shown in FIG. 2, the drivable area R in this embodiment is an area on a road, such as a roadway, on which the vehicle can travel, and is a predetermined area centered on the vehicle 50 . The road means a passage on which a vehicle can travel, such as a roadway or a roadway in a parking lot. The predetermined area may be set according to the performance (resolution) of the sensor 10, or an initial value may be set. In this embodiment, it is assumed that the travelable region R is set according to the performance of the sensor 10 . For example, when the detection distance of the sensor 10 is 200 m, the roadway included in a circle with a radius of 200 m centered on the vehicle 50 is the travelable area R. Note that the travelable area R is not limited to a circular shape, and may be a square shape centered on the vehicle 50 or a polygonal shape. 60 shown in FIG. 2 is a boundary line forming the travelable area R. As shown in FIG.

Next, an example of a driving scene according to this embodiment will be described with reference to FIG.

As shown in FIG. 3, two obstacles 70 and 71 exist in front of the host vehicle 50 . Obstacles include falling objects, parked vehicles, and the like. In this embodiment, the obstacle 70 is a falling object, and the obstacle 71 is a parked vehicle. Obstacles 70 and 71 are objects on the roadway on which the vehicle 50 travels.

As shown in FIG. 3, an obstacle 70 exists near the center of the roadway, and an obstacle 71 exists at the edge of the roadway. More specifically, the obstacle 70 exists slightly to the left of the center of the roadway. In other words, the distance L1 from the obstacle 70 to the road boundary line 90 is shorter than the distance L2 from the obstacle 70 to the road boundary line 91 . Also, the distances L1 and L2 are longer than the vehicle width of the own vehicle 50 . Note that left and right in FIG. 3 are defined as left and right when the traveling direction of the own vehicle 50 is forward. In the following description, left and right mean left and right directions when the traveling direction is forward.

In the driving scene shown in FIG. 3, there are two routes on which the vehicle 50 can travel. One is a route 80 that passes through the left side of the obstacle 70 . The other is path 81 that passes on the right side of obstacle 70 and then passes between obstacles 70 and 71 .

Route 81 is less efficient than route 80 because it has a longer travel distance and a larger amount of steering operation. Therefore, the driving support device 1 according to the present embodiment classifies whether the obstacles 70 and 71 are on the left or right side of the longest line segment 100 as seen from the sensor 10 with respect to the longest line segment (described later). , to generate efficient routes. Details will be described with reference to FIGS. 4 to 6. FIG.

4 and subsequent drawings, the sensor 10 is mounted on the front portion of the own vehicle 50. FIG. Further, the sensor 10 will be described as a device that emits radio waves radially forward in the direction of travel of the vehicle and detects the position of an object using reflected waves from the object.

First, an example of the longest line segment will be described with reference to FIG. As shown in FIG. 4, the far point setting unit 25 sets a plurality of line segments 200 radially extending from the sensor 10 toward the boundary line 60 of the travelable area R, and out of the set line segments, Select the longest line segment 100. As shown in FIG. 4 , the plurality of line segments 200 includes line segments connecting the plurality of detection points 120 to 121 of the obstacle 70 and the sensor 10 . The plurality of line segments 200 also include line segments connecting the plurality of detection points 122 to 125 of the obstacle 71 and the sensor 10 . Further, as shown in FIG. 4 , the longest line segment 100 is, for example, a line segment connecting the farthest point 110 farthest from the sensor 10 in the travelable region R and the sensor 10 . The farthest point 110 does not indicate the position of an object, but is a virtual point set in space. The far point setting unit 25 sets the farthest point 110 to a space that is farthest from the sensor 10 in the travelable area R. Also, the longest line segment 100 is a line segment that is not blocked by the obstacles 70 and 71 . In this embodiment, the travelable region R is set based on the detection distance of the sensor 10, so the length of the longest line segment 100 is the same distance as the detection distance of the sensor 10. FIG. In the example shown in FIG. 4, since there are no other obstacles within the travelable area R in the area to the left of the obstacle 71, the farthest point 110 is set in the space where the distance from the sensor 10 is the furthest. Although it is a point, the farthest point 110 may be an obstacle detection point. That is, in the example shown in FIG. 4, if another obstacle exists in the area to the left of the obstacle 71 and farther than the obstacle 71, the detected point of the other obstacle becomes the farthest point. . In addition, in FIG. 4, the travelable area R is an area excluding the obstacles 70 and 71 .

Next, with reference to FIG. 5, an example method of classifying obstacles 70 and 71 will be described.

The left/right classification unit 26 determines whether the obstacle is the closest to the sensor 10 based on the sign of the angle formed by the line segment connecting the sensor 10 and the obstacle (detection points 120 to 125) and the longest line segment 100. It is classified whether it is on the left or right with respect to the long line segment 100 .

With the longest line segment 100 as a reference, it is assumed that clockwise angles are positive and counterclockwise angles are negative. If the angle is positive, the detection point is assumed to be on the right of the longest line segment 100 as seen from the sensor 10. If the angle is negative, the detection point is assumed to be on the longest line segment 100 as seen from the sensor 10. Suppose you are on the left with respect to As shown in FIG. 5, the angle θ1 formed by the longest line segment 100 and the line segment connecting the sensor 10 and the detection point 120 of the obstacle 70 is positive. The angle θ3 formed by the longest line segment 100 and the line segment connecting the sensor 10 and the detection point 121 of the obstacle 70 is also positive. Based on this result, the left/right classification unit 26 classifies the obstacle 70 as being on the right side of the longest line segment 100 as viewed from the sensor 10 .

Also, as shown in FIG. 5, the angle θ2 formed by the longest line segment 100 and the line segment connecting the sensor 10 and the detection point 122 of the obstacle 71 is positive. The angle θ4 formed by the longest line segment 100 and the line segment connecting the sensor 10 and the detection point 123 of the obstacle 71 is also positive. Similarly, the angle θ5 formed by the longest line segment 100 and the line segment connecting the sensor 10 and the detection point 124 of the obstacle 71 is also positive. Similarly, the angle θ6 formed by the longest line segment 100 and the line segment connecting the sensor 10 and the detection point 125 of the obstacle 71 is also positive. Based on this result, the left/right classification unit 26 classifies the obstacle 70 as being on the right side of the longest line segment 100 as viewed from the sensor 10 .

Next, with reference to FIG. 6, an example of a method of resetting the travelable area using obstacles 70 and 71 classified into left and right will be described. Since the obstacles 70 and 71 are classified as being on the right side of the longest line segment 100 as seen from the sensor 10, the travelable area is reset except for the area on the right side including the obstacles 70 and 71. be. That is, it is determined that the obstacles 70 and 71 and the right side of the obstacles 70 and 71 are not the travelable area, and the left side of the obstacles 70 and 71 is set as the travelable area.

As shown in FIG. 6, the travelable area resetting unit 27 selects a detection point 120 having the shortest distance from the longest line segment 100 among the detection points of the obstacle 70, and the road boundary line 91 forming the roadway. Tie and reset the drivable area. R2 shown in FIG. 6 is the travelable area after resetting. Note that in the example shown in FIG. 6 , the travelable area resetting unit 27 also connects the detection point 120 and the detection point 122 .

Then, as shown in FIG. 6, the target route generator 28 generates a travel route (route 80) for the host vehicle 50 within the reset travelable region R2. As a result, since the route 81 shown in FIG. 3 is not generated, only the efficient route 80 is generated.

Next, an operation example of the driving support device 1 will be described with reference to the flowchart of FIG.

In step S<b>101 , the self-position estimation unit 22 estimates the self-position on the map based on the information acquired from the GPS receiver 12 . The process proceeds to step S103, and the map database 13 acquires map information indicating the structure of the road on which the vehicle 50 travels. The road boundary acquisition unit 23 acquires road boundaries based on the map information. Note that the road boundary line may be acquired by the sensor 10 .

The process proceeds to step S105, and the travelable area setting unit 24 sets the travelable area R (see FIG. 2). The process proceeds to step S107, and the sensor 10 detects obstacles 70 and 71 in front of the host vehicle 50 (see FIG. 4).

The process proceeds to step S<b>109 , and the far point setting unit 25 sets the farthest point 110 in the space at which the distance from the sensor 10 is the furthest in the travelable area R. Further, the far point setting unit 25 sets a plurality of line segments 200 radially extending from the sensor 10 toward the boundary line 60 of the travelable area R, and selects the longest line segment 100 from among the plurality of set line segments. to select. The longest line segment 100 is a line segment connecting the farthest point 110 and the sensor 10 . The process proceeds to step S111, and the left/right classification unit 26 determines whether the angle between the line segment connecting the sensor 10 and the obstacle (detection points 120 to 125) and the longest line segment 100 is positive or negative. It is classified whether the object is on the left or right with respect to the longest line segment 100 as viewed from the sensor 10 (see FIG. 5).

The process proceeds to step S113, and the travelable area resetting unit 27 determines the detection point 120 having the shortest distance from the longest line segment 100 among the detection points of the obstacle 70, and the road boundary line 91 forming the roadway. to reset the travelable area (see FIG. 6). The process proceeds to step S115, and the target route generator 28 generates a route 80 for the own vehicle 50 within the reset travelable region R2 (see FIG. 6). The process proceeds to step S117, and the vehicle control unit 29 controls the actuator 40 so that the route 80 set by the target route generation unit 28 is passed.

As described above, according to the driving support device 1 according to the present embodiment, the following effects are obtained.

When an obstacle (obstacle 70) is detected in front of the vehicle 50 on the road on which the vehicle 50 travels, the driving support device 1 detects a point on the boundary line 60 between the sensor 10 and the travelable area R. A plurality of connecting line segments 200 are set, and the longest line segment 100 is selected from among the set plurality of line segments. The driving support device 1 classifies the selected longest line segment 100 as to whether the obstacle is on the left or right side of the longest line segment 100 in the vehicle width direction as viewed from the sensor 10, and based on the classification result. to reset the drivable area. Then, the driving support device 1 generates a driving route (route 80) for the own vehicle 50 within the reset driving range R2. As a result, since the route 81 shown in FIG. 3 is not generated, only the efficient route 80 is generated.

In addition, the driving support device 1 connects a detection point (detection point 120) having the shortest distance from the longest line segment 100 among the obstacle detection points to the road boundary line 91 forming the roadway, so that the vehicle can travel. Reconfigure the region. As a result, as shown in FIG. 6, the travelable area is reset except for the area on the right side including the obstacle 70 .

Further, the driving support device 1 determines whether the obstacle is visible from the sensor 10 based on the sign of the angle formed by the line segment connecting the sensor 10 and the obstacle (detection points 120 to 125) and the longest line segment 100. to classify whether it is on the left or right with respect to the longest line segment 100. As a result, the left and right positions expressed two-dimensionally are classified by one-dimensional information, so that the processing load when classifying the left and right is reduced.

Each function described in the above embodiments may be implemented by one or more processing circuits. Processing circuitry includes programmed processing devices, such as processing devices that include electrical circuitry. Processing circuitry also includes devices such as application specific integrated circuits (ASICs) and circuit components arranged to perform the described functions. Also, the driving support device 1 can improve the function of the computer.

While embodiments of the present invention have been described above, the discussion and drawings forming part of this disclosure should not be construed as limiting the invention. Various alternative embodiments, implementations and operational techniques will become apparent to those skilled in the art from this disclosure.

The present invention may be applied to curves as well as straight roads. For example, as shown in FIGS. 8 and 9, when one obstacle 70 exists on a curve, there are two routes that the vehicle 50 can travel. One is a route 80 that passes through the left side of the obstacle 70 . The other is a path 81 passing through the right side of the obstacle 70 . Route 81 is less efficient than route 80 because it has a longer travel distance and a larger amount of steering operation. Therefore, the driving support device 1 generates only the route 80 as shown in FIG. 9 using a method similar to the method described with reference to FIGS. As a result, since the route 81 shown in FIG. 8 is not generated, only the efficient route 80 is generated. Thus, the present invention is applicable even when there is only one obstacle in front of the vehicle 50. FIG. Of course, as explained with reference to FIGS. 4 to 6, the present invention can also be applied when there are multiple obstacles in front of the vehicle 50. FIG.

As described above, the sensor 10 radially emits radio waves and detects the position of the object using the reflected waves from the object. As shown in FIG. 10, when the sensor 10 detects a plurality of obstacles, the positions of the obstacle detection points may be stored in the storage device in the order in which the obstacle detection points are detected. If the detection point of the n+1th detected obstacle shown in FIG. The detection point of the th detected obstacle and the detection point of the (n+4)th detected obstacle are automatically classified as being on the right side of the nth detected detection point. The n+2th detected obstacle detection point, the n+3th detected obstacle detection point, and the n+4th detected obstacle detection point correspond to the remaining obstacle detection points. . By storing the detection points in the storage device in accordance with the order in which they are detected, the positions of the obstacles are collectively classified, thereby reducing the processing load when classifying the left and right. That is, if the order in which the detection points are detected is stored in the storage device, the detection points stored in the order after the order in which the longest line segment 100 was determined will naturally be to the right of the longest line segment 100. It can be determined that it is a detection point that exists, and the processing load when classifying left and right is reduced.

As a result of the obstacles being classified into left and right, there is a possibility that a route through which the own vehicle 50 cannot pass is generated. For example, in the example shown in FIG. 11, it is considered that there are multiple routes for the own vehicle 50 . One is a route 80 that passes through the left side of the obstacle 70 . The other is a path 81 passing through the right side of the obstacle 70 . 4-6, the obstacles 70, 71 shown in FIG. 11 are classified as being to the right of the longest line segment 100 as seen from the sensor 10. In FIG. As a result, path 80 is generated. However, if distance L3 shown in FIG. If the route 80 based on the classification result is shorter than the vehicle width of the vehicle 50 and the vehicle 50 cannot pass through it, the driving support device 1 reduces the travelable area R as shown in FIG. good too. Then, in the reduced travelable region R, the driving support device 1 again uses the method described with reference to FIGS. classified as being in In the example shown in FIG. 12, the obstacle 70 is classified as being to the left of the longest line segment 100 as seen from the sensor 10 . Based on this result, as shown in FIG. 13, the driving support device 1 resets the travelable area. R2 shown in FIG. 13 is the travelable area after resetting. Then, as shown in FIG. 13, the driving support device 1 sets the driving route (route 81) for the own vehicle 50 within the reset possible driving region R2. Thereby, a route through which the own vehicle 50 can pass is generated.

1 Driving support device 10 Sensor 11 Camera 12 Receiver 13 Map database 20 Controller 21 Stationary object recognition unit 22 Self-position estimation unit 23 Road boundary line acquisition unit 24 Travelable area setting unit 25 Far point setting unit 26 Left/right classification unit 27 Travelable Region resetting unit 28 Target route generating unit 29 Vehicle control unit 40 Actuator

Claims (6)

Driving assistance by a driving assistance device that is mounted on a vehicle and includes a sensor that detects the position of an object in front of the vehicle and a controller that sets a driving route for the vehicle based on the position of the object detected by the sensor. a method,
Detecting an obstacle on the track on which the vehicle travels from the position of the object detected using the sensor,
Based on the position of the obstacle, a drivable area in which the vehicle can travel, excluding the obstacle, is set within the track;
setting a plurality of line segments connecting points on the boundary line of the sensor and the travelable area, selecting the longest line segment from among the plurality of set line segments,
Classifying whether the obstacle is on the left or right in the vehicle width direction as viewed from the sensor with respect to the selected longest line segment,
resetting the drivable area based on the classified result;
A travel support method, comprising generating a travel route for the vehicle within the reset travelable area. Among the detection points of the obstacle, a detection point having the shortest distance from the longest line segment is connected to a road boundary line forming the running path to reset the travelable area. Item 1. The driving support method according to item 1. Based on the sign of the angle formed by the line segment connecting the sensor and the obstacle and the longest line segment, it is classified whether the obstacle is on the left or right side as viewed from the sensor. The driving support method according to claim 1 or 2. The sensor is a device that emits radio waves radially and detects the position of the object using reflected waves from the object,
when the sensor detects a plurality of obstacles, storing the positions of the obstacles in the order in which the obstacles are detected;
The traveling according to any one of claims 1 to 3, characterized in that the remaining obstacles are classified based on the result of classification as to whether one obstacle is on the left or right side as viewed from the sensor. how to help. In the drivable area, if there are a plurality of drivable routes for the vehicle, and if the drivable route based on the result of the classification is shorter than the vehicle width of the vehicle and the vehicle cannot pass, the drivable region is reduced. death,
Classify again whether the obstacle is on the left or right side as viewed from the sensor in the travelable area after the reduction,
resetting a travelable area that does not include the obstacle based on the classification result;
The driving support method according to any one of claims 1 to 4, wherein the driving route of the vehicle is set within the reset driving range. a sensor mounted on a vehicle for detecting the position of an object in front of the vehicle;
a controller that sets a travel route of the vehicle based on the position of the object detected by the sensor;
The controller is
Detecting an obstacle on the track on which the vehicle travels from the position of the object detected using the sensor,
Based on the position of the obstacle, a drivable area in which the vehicle can travel, excluding the obstacle, is set within the track;
setting a plurality of line segments connecting points on the boundary line of the sensor and the travelable area, selecting the longest line segment from among the plurality of set line segments,
Classifying whether the obstacle is on the left or right in the vehicle width direction as viewed from the sensor with respect to the selected longest line segment,
resetting the drivable area based on the classified result;
A travel support device, wherein a travel route for the vehicle is generated within the reset travelable area.

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