Control device and control method

Abstract

The present invention obtains a control device and a control method that can appropriately assist with driving by a rider. In a control device (20) and a control method according to the present invention, an execution unit of the control device (20) executes a control mode in which a rider assistance operation for assisting a rider is executed. The execution unit acquires first turning posture information as turning posture information about a leaning vehicle (1) on the basis of map information and speed information about the leaning vehicle (1), and executes the control mode on the basis of the first turning posture information.

Description

[0001]

Document Name

[0002]

Title of the Invention

[0003]

Technical Field

[0004]

.001

[0005] This disclosure relates to a control device and a control method that can appropriately assist a rider in driving.

[0006]

Background Art

[0007]

.002

[0008] Conventionally, various technologies for assisting a rider in driving a lean vehicle such as a motorcycle have been proposed. For example, in Patent Document 1, a driver assistance system is disclosed that warns a rider of a motorcycle when approaching an obstacle inappropriately based on information detected by a sensor device that detects an obstacle in the traveling direction or substantially in the traveling direction.

[0009]

Prior Art Documents

[0010]

Patent Documents

[0011]

〇003

[0012]

Patent Document 1

[0013]

Summary of the Invention

[0014]

Problems to be Solved by the Invention

[0015]

〇004

[0016] Here, in a lean vehicle, compared to a four - wheeled automobile or the like, the behavior is unstable and the posture is likely to change sensitively. And in a control mode in which a rider assistance operation for assisting the rider is executed, it is desirable to appropriately grasp the posture of the lean vehicle and then appropriately assist the rider in driving.

[0017]

〇005

[0018] This invention was made against the backdrop of the above-mentioned problems, and aims to provide a control device and control method that can appropriately support driving by a LiDAR user.

[0019] [Means for solving the problem]

[0020]

〇 0 0 6

[0021] The control device according to the present invention is a control device for a rider assistance system that assists the rider of a leaning vehicle, and comprises an execution unit that executes a control mode in which rider assistance operations are performed to assist the rider, the execution unit acquires first turning posture information as turning posture information of the leaning vehicle based on map information and speed information of the leaning vehicle, and executes the control mode based on the first turning posture information.

[0022]

〇 0 0 7

[0023] The control method according to the present invention is a control method for a rider assistance system that assists the rider of a leaning vehicle, wherein the execution unit of the control device executes a control mode in which rider assistance operations are performed to assist the rider, and the execution unit acquires first turning posture information as turning posture information of the leaning vehicle based on map information and the speed information of the leaning vehicle, and executes the control mode based on the first turning posture information.

[0024] [Effects of the Invention]

[0025]

〇 0 0 8

[0026] In the control device and control method according to the present invention, the execution unit of the control device executes a control mode in which rider assistance operations are performed to assist the rider. The execution unit acquires first turning posture information as turning posture information of the leaning vehicle based on map information and speed information of the leaning vehicle, and executes a control mode based on the first turning posture information. As a result, the control mode can be executed after appropriately understanding the posture of the leaning vehicle. Therefore, it is possible to appropriately assist the rider in driving.

[0027] [Brief explanation of the drawing]

[0028]

〇 0 0 9

[0029] [Figure 1] A schematic diagram showing the general configuration of a lean vehicle according to an embodiment of the present invention. [Figure 2] A block diagram showing an example of the functional configuration of a control device according to an embodiment of the present invention. [Figure 3] A diagram showing a lean vehicle according to an embodiment of the present invention traveling behind a preceding vehicle.

[0030] [Figure 4] This figure illustrates an example of the target vehicle determination process performed by a control device according to an embodiment of the present invention.

[0031] [Figure 5] This is a flowchart showing an example of the processing flow performed by the control device according to an embodiment of the present invention.

[0032] [Figure 6] This is a schematic diagram showing an example of a road through which a lean vehicle according to an embodiment of the present invention passes.

[0033] [Figure 7] This figure shows a lean vehicle according to an embodiment of the present invention performing a turning maneuver.

[0034] [Figure 8] A graph showing an example of the driving characteristics of a lidar according to an embodiment of the present invention. [Figure 9] A graph showing an example of the driving characteristics of a lidar according to an embodiment of the present invention. [Figure 1 ○] A schematic diagram showing the general configuration of a lean vehicle according to a modified example of the present invention.

[0035] [Modes for carrying out the invention]

[0036] [ 0 0 1 0 ]

[0037] The control device and control method according to the present invention will be described below with reference to the drawings.

[0038] [ 0 0 1 1 ]

[0039] In the following description, a control device used for a two-wheeled motorcycle will be described (refer to the lean vehicle 1 in FIG. 1). However, the vehicle to be controlled by the control device according to the present invention may be any lean vehicle, and may be a lean vehicle other than a two-wheeled motorcycle. A lean vehicle means a vehicle in which the vehicle body leans to the right when turning right and leans to the left when turning left. Examples of lean vehicles include motorcycles (motorcycles, motor tricycles), bicycles, etc. Motorcycles include vehicles with an engine as a power source, vehicles with an electric motor as a power source, etc. Examples of motorcycles include motorcycles, scooters, electric scooters, etc. A bicycle means a vehicle that can be propelled on the road by the pedaling force of a rider applied to the pedals. Bicycles include electric assist bicycles, electric bicycles, etc.

[0040]

[0012]

[0041] In addition, in the following description, a case where an engine (specifically, the engine 11 in FIG. 1 described later) is mounted as a drive source capable of outputting power for driving the drive wheels is described. However, other drive sources (for example, an electric motor) other than the engine may be mounted as the drive source, or a plurality of drive sources may be mounted.

[0042]

[0013]

[0043] In addition, in the following description, a case where a control unit that controls the hydraulic pressure of brake fluid (specifically, the hydraulic pressure control unit 12 in FIG. 1 described later) is adopted as a control unit for the braking force generated on the wheels is described. However, as a control unit for the braking force generated on the wheels, a control unit that controls the position of the braking part of the wheel itself by an electrical signal (so-called brake-by-wire) may be adopted.

[0044]

[0014]

[0045] In addition, the configurations and operations described below are examples, and the control device and control method according to the present invention are not limited to such configurations and operations.

[0046]

[0015]

[0047] In the following description, the same or similar explanations are appropriately simplified or omitted. In each figure, for the same or similar members or parts, the assignment of reference numerals is omitted or the same reference numerals are used. For the detailed structure, the illustration is appropriately simplified or omitted.

[0048]

[0016]

[0049] <Configuration of a Lean Vehicle> The configuration of the lean vehicle 1 according to an embodiment of the present invention will be described.

[0050]

[0017]

[0051] FIG. 1 is a schematic diagram showing a schematic configuration of the lean vehicle 1. The lean vehicle 1 is a two-wheeled motorcycle corresponding to an example of the lean vehicle according to the present invention. As shown in FIG. 1, the lean vehicle 1 includes an engine 11, a hydraulic control unit 12, a display device 13, an input device 14, a surrounding environment sensor 15, a front wheel speed sensor 16, a rear wheel speed sensor 17, a navigation device 18, and a control device (ECU) 20.

[0052]

[0018]

[0053] The lean vehicle 1 includes a rider support system 100 that supports the rider of the lean vehicle 1. The rider support system 100 includes the above-described components (specifically, the engine 11, the hydraulic control unit 12, the display device 13, the input device 14, the surrounding environment sensor 15, the front wheel speed sensor 16, the rear wheel speed sensor 17, the navigation device 18, and the control device 20).

[0054]

[0019]

[0055] Engine 11 is an example of a drive source for lean vehicle 1 and is capable of outputting power to drive the drive wheels (specifically, the rear wheels). For example, engine 11 is provided with one or more cylinders in which combustion chambers are formed, a fuel injector that injects fuel into the combustion chamber, and a spark plug. When fuel is injected from the fuel injector, a mixture of air and fuel is formed in the combustion chamber, and this mixture is ignited by the spark plug and combusted. As a result, a piston located in the cylinder reciprocates and the crankshaft rotates. In addition, a throttle valve is provided in the intake manifold of engine 11, and the amount of intake air into the combustion chamber changes according to the throttle opening, which is the opening degree of the throttle valve. [0 0 2 0]

[0056] The hydraulic control unit 1 2 is a unit responsible for controlling the braking force generated in the wheels. For example, the hydraulic control unit 1 2 is installed on the oil passage connecting the master cylinder and the wheel cylinder and includes components (e.g., a control valve and a pump) for controlling the brake fluid pressure of the wheel cylinder. The braking force generated in the wheels is controlled by controlling the operation of the components of the hydraulic control unit 1 2. The hydraulic control unit 1 2 may control the braking force generated in both the front and rear wheels, or it may control the braking force generated in only one of the front or rear wheels.

[0057] [ 0 0 2 1 ]

[0058] The display device 13 has a display function that visually displays information to the rider. Examples of the display device 13 include a liquid crystal display. The display device 13 is, for example, located in front of the handlebars in a lean vehicle 1. However, the placement of the display device 13 on the vehicle body is not particularly limited.

[0059] [ 0 0 2 2 ]

[0060] The input device 14 is a device that receives input from the rider. The input device 14 includes, for example, a push button provided on the handlebars and used for the rider's operation. Information regarding the rider's operation using the input device 14 is output to the control device 2.

[0061] [ 0 0 2 3 ]

[0062] The ambient environment sensor 15 detects ambient environment information regarding the environment surrounding the lean vehicle 1. Specifically, the ambient environment sensor 15 is located at the front of the lean vehicle 1 and detects ambient environment information in front of the lean vehicle 1. The ambient environment information detected by the ambient environment sensor 15 is output to the control device 20.

[0063] [ 0 0 2 4 ]

[0064] The ambient environment information detected by the ambient environment sensor 1 5 may be information related to the distance or direction to the subject located around the lean vehicle 1 (e.g., relative position, relative distance, relative speed, relative acceleration, etc.), or it may be the characteristics of the subject located around the lean vehicle 1 (e.g., type of subject, shape of the subject itself, marks attached to the subject, etc.). The ambient environment sensor 1 5 is, for example, a radar, Lidar sensor, ultrasonic sensor, camera, etc.

[0065] [ 0 0 2 5 ]

[0066] Furthermore, ambient environmental information can also be detected by ambient environmental sensors mounted on other vehicles or by infrastructure equipment. In other words, the control device 20 can also acquire ambient environmental information via wireless communication with other vehicles or infrastructure equipment.

[0067] [ 0 0 2 6 ]

[0068] The front wheel speed sensor 16 is a wheel speed sensor that detects the wheel speed of the front wheel (for example, the number of rotations per unit time of the front wheel [rpm] or the distance traveled per unit time [km / h], etc.) and outputs the detection result. The front wheel speed sensor 16 may also detect other physical quantities that can be substantially converted to the wheel speed of the front wheel. The front wheel speed sensor 16 is installed on the front wheel.

[0069] [ 0 0 2 7 ]

[0070] The rear wheel speed sensor 17 is a wheel speed sensor that detects the wheel speed of the rear wheel (for example, the number of rotations per unit time of the rear wheel [rpm] or the distance traveled per unit time [km / h], etc.) and outputs the detection result. The rear wheel speed sensor 17 may also detect other physical quantities that can be substantially converted to the wheel speed of the rear wheel. The rear wheel speed sensor 17 is installed on the rear wheel.

[0071] [ 0 0 2 8 ]

[0072] Navigation device 18 is a device that guides the rider on a route from the current position of lean vehicle 1 to a desired destination. Navigation device 18 displays various information related to route guidance (for example, the current position of lean vehicle 1, the driving route to be guided, the location of the destination, the distance on the driving route from the current position of lean vehicle 1 to the destination, and the estimated time to reach the destination). Navigation device 18 can also acquire the position information of lean vehicle 1 based on information transmitted from GPS (Global GPS System) satellites.

[0073] [ 0 0 2 9 ]

[0074] The control device 20 controls the operation of the LiDAR assistance system 100. For example, part or all of the control device 20 is composed of a microcontroller, microprocessor unit, etc. Also, for example, part or all of the control device 20 may be composed of updatable firmware, etc., or a program module executed by commands from a CPU, etc. The control device 20 may be, for example, one unit, or it may be divided into multiple units. [0 0 3 0]

[0075] Figure 2 is a block diagram showing an example of the functional configuration of the control device 20. As shown in Figure 2, the control device 20 comprises, for example, an acquisition unit 21 and an execution unit 22. The control device 20 communicates with each device of the lean vehicle 1 (for example, the engine 11, the hydraulic control unit 12, the display device 13, the input device 14, the ambient environment sensor 15, the front wheel speed sensor 16, the rear wheel speed sensor 17, and the navigation device 18). The control device 20 can also control the operation of each device of the lean vehicle 1 (for example, the engine 11, the hydraulic control unit 12, and the display device 13).

[0076] [ 0 0 3 1 ]

[0077] The acquisition unit 21 acquires information from each device of the lean vehicle 1 and outputs it to the execution unit 22. For example, the acquisition unit 21 acquires information from the input device 14, the ambient environment sensor 15, the front wheel speed sensor 16, the rear wheel speed sensor 17, and the navigation device 18. In this specification, information acquisition may include information extraction or generation (e.g., calculation).

[0078] [ 0 0 3 2 ]

[0079] The execution unit 22 can execute a control mode in which rider assistance operations are performed to support the rider. In other words, the execution unit 22 performs rider assistance operations in the above control mode. The execution unit 22 can perform various rider assistance operations, for example, by controlling the operation of the engine 11, the hydraulic control unit 12, and the display device 13.

[0080] [ 0 0 3 3 ]

[0081] In particular, the execution unit 22 can perform a positional relationship adjustment operation as a rider assistance operation. The positional relationship adjustment operation is an operation to adjust the positional relationship between the leaning vehicle 1 and a target vehicle traveling ahead of the leaning vehicle 1 to the target positional relationship. In addition, the execution unit 22 may also adjust the positional relationship between the leaning vehicle 1 and an object other than a vehicle (for example, a traffic light, etc.) to the target positional relationship during the positional relationship adjustment operation.

[0082] [ 0 0 3 4 ]

[0083] The following primarily describes examples where positional adjustment actions are performed as rider assistance actions. However, as will be discussed later, actions other than positional adjustment actions may also be performed as rider assistance actions.

[0084] [ 0 0 3 5 ]

[0085] Furthermore, the following describes an example in which adaptive cruise control is performed as a positional relationship adjustment operation. However, the positional relationship adjustment operation does not have to be an adaptive cruise control operation; it does not have to be an operation that adjusts the positional relationship between lean vehicle 1 and the target vehicle to the target positional relationship. For example, the positional relationship adjustment operation may be an operation in which the target positional relationship changes according to the amount of accelerator operation performed by the rider.

[0086] [ 0 0 3 6 ]

[0087] Specifically, the execution unit 22 can execute a control mode in which adaptive cruise control is performed. In such a control mode, the execution unit 22 can perform adaptive cruise control. For example, when the power to the lean vehicle 1 is turned on, the above control mode is not executed, and the control mode is executed when the rider operates a switch using the input device 14. During the execution of the control mode, the state of the control mode can transition between a state in which adaptive cruise control is actually being performed and a state in which adaptive cruise control is temporarily suspended.

[0088] [ 0 0 3 7 ]

[0089] Figure 3 shows a lean vehicle 1 traveling behind a preceding vehicle 2. In the example in Figure 3, the lane 3 in which the lean vehicle 1 is traveling is straight and not curved, and the lean vehicle 1 and the preceding vehicle 2 are traveling side by side in the front-to-back direction in such a lane 3. The preceding vehicle 2 is detected by the surrounding environment sensor 15 and set as the target vehicle. Once the target vehicle is set in this way, adaptive cruise control is executed, and the positional relationship between the lean vehicle 1 and the preceding vehicle 2 (as the target vehicle) is adjusted to the target positional relationship. As a result, the lean vehicle 1 achieves follow-the-leading driving, following the preceding vehicle 2.

[0090] [ 0 0 3 8 ]

[0091] In adaptive cruise control, for example, a target passing time difference is set, which is the target value of the difference in passing time between the lean vehicle 1 and the target vehicle (specifically, the time it takes for the lean vehicle 1 to pass the target vehicle's current position from the current point in time). The execution unit 22 controls the speed of the lean vehicle 1 so that the above passing time difference is maintained at the target passing time difference. In other words, the positional relationship in which the above passing time difference becomes the target passing time difference corresponds to the target positional relationship. For example, the acquisition unit 21 acquires the above passing time difference based on the surrounding environment information of the lean vehicle 1, and the execution unit 22 can control the speed of the lean vehicle 1 as described above based on the passing time difference thus acquired.

[0092] [ 0 0 3 9 ]

[0093] However, in adaptive cruise control, for example, a target distance is set, which is the target distance between the lean vehicle 1 and the target vehicle, and the execution unit 22 may control the speed of the lean vehicle 1 so that the above distance is maintained at the target distance. In this case, the positional relationship in which the above distance becomes the target distance corresponds to the target positional relationship. Note that the distance may mean the distance in the direction along the lane 3 in which the lean vehicle 1 is traveling, or it may mean the straight-line distance between the lean vehicle 1 and the target vehicle. For example, the acquisition unit 21 acquires the above distance based on the surrounding environment information of the lean vehicle 1, and the execution unit 22 can control the speed of the lean vehicle 1 as described above based on the distance thus acquired.

[0094] [ 0 0 4 0 ]

[0095] The execution unit 22 can control the speed of the lean vehicle 1 based on information about the speed of the lean vehicle 1, which is obtained based on the wheel speeds of the front and rear wheels, for example. For example, the execution unit 22 can control the driving force acting on the lean vehicle 1 by controlling the operation of the engine 11. Also, for example, the execution unit 22 can control the braking force acting on the lean vehicle 1 by controlling the operation of the hydraulic control unit 12. As a result, in adaptive cruise control, the execution unit 22 can automatically control the speed of the lean vehicle 1 without relying on acceleration and deceleration operations (i.e., accelerator and brake operations) by the rider.

[0096] [ 0 0 4 1 ]

[0097] Furthermore, if there is no preceding vehicle 2 in front of lean vehicle 1 and within a predetermined range relative to lean vehicle 1, and if no preceding vehicle 2 is detected, the adaptive cruise control is temporarily suspended. In this case, the execution unit 22 adjusts the speed of lean vehicle 1 to the target speed. As a result, lean vehicle 1 travels at a nearly constant speed. The target speed is, for example, pre-set and stored in the memory element of the control device 20. The rider may also be able to manually set the target speed.

[0098] [ 0 0 4 2 ]

[0099] <Operation of the control device>

[0100] The operation of control device 2〇 according to an embodiment of the present invention will be described.

[0101] [ 0 0 4 3 ]

[0102] As described above, the execution unit 22 of the control device 20 can execute a control mode in which adaptive cruise control is performed. In adaptive cruise control, the preceding vehicle 2 is detected by the surrounding environment sensor 15 and set as the target vehicle, and the positional relationship between the leaning vehicle 1 and the preceding vehicle 2 is adjusted to the target positional relationship.

[0103] [ 0 0 4 4 ]

[0104] Figure 4 is a diagram illustrating an example of the target vehicle determination process performed by the control device 20. For example, the execution unit 22 estimates the future trajectory 4 of the lean vehicle 1 and determines the target vehicle based on the estimation result of the trajectory 4. Specifically, the execution unit 22 estimates the future trajectory 4 of the lean vehicle 1 and determines an expanded region 5, which is an area that extends the trajectory 4 in a direction perpendicular to the trajectory 4 (specifically, in the horizontal direction), based on the estimation result of the trajectory 4. The expanded region 5 is an area with the trajectory 4 as its center in the lane width direction and a width in the lane width direction that is approximately the same as the width of the lean vehicle 1. In other words, the expanded region 5 corresponds to the area that the lean vehicle 1 will pass through in the future. Then, the execution unit 22 determines the target vehicle based on the expanded region 5. For example, the execution unit 22 determines a preceding vehicle 2 that is at least partially located within the expanded area 5 as the target vehicle.

[0105] [ 0 0 4 5 ]

[0106] In the example in Figure 4, similar to the example in Figure 3, the lane 3 in which lean vehicle 1 is traveling is straight and not curved. In other words, lean vehicle 1 is traveling in a straight line. On the other hand, there may also be a situation in which lane 3 in which lean vehicle 1 is traveling is curved, and lean vehicle 1 is traveling in a turn. In such a situation, in order to determine the preceding vehicle 2 traveling in lane 3 in which lean vehicle 1 is traveling as the target vehicle, it becomes necessary to understand the attitude of lean vehicle 1 and then appropriately determine the travel trajectory 4 and the expanded area 5.

[0107] [ 0 0 4 6 ]

[0108] As described above, in the control mode in which the positional relationship adjustment operation is performed, it is desirable to appropriately support the rider's driving after understanding the attitude of the lean vehicle 1. Therefore, in this embodiment, by making improvements to the processing performed by the execution unit 22, it becomes possible to execute the control mode after appropriately understanding the attitude of the lean vehicle 1, thereby achieving appropriate support for the rider's driving. The details of the processing example performed by the control device 20 are described below. [0 0 4 7]

[0109] Figure 5 is a flowchart showing an example of the processing flow performed by the control device 20. The control flow shown in Figure 5 starts during the execution of a control mode in which adaptive cruise control is performed and ends when the control mode ends. Step S10I in Figure 5 corresponds to the start of the control flow shown in Figure 5.

[0110] [ 0 0 4 8 ]

[0111] When the control flow shown in Figure 5 begins, in step S102, the execution unit 22 acquires the turning attitude information of the lean vehicle 1.

[0112] [ 0 0 4 9 ]

[0113] In step S102, the execution unit 22 acquires the turning attitude information of the lean vehicle 1 based on the map information and the speed information of the lean vehicle 1.

[0114] [ 0 0 5 0 ]

[0115] Furthermore, the execution unit 22 can acquire map information, for example, based on the output of the navigation device 18. The map information includes information about the shape of the road, including the curvature of the road. In addition, the execution unit 22 can acquire speed information of the lean vehicle 1, for example, based on the wheel speed of the front wheels and the wheel speed of the rear wheels, as described above. The speed information may be information that directly indicates the speed of the lean vehicle 1, or it may be information that can be substantially converted to the speed of the lean vehicle 1.

[0116] [ 0 0 5 1 ]

[0117] Turning attitude information is information about physical quantities that reflect the attitude of lean vehicle 1 as it turns. Examples of turning attitude information include the lean angle of lean vehicle 1, the yaw rate of lean vehicle 1, and the lateral acceleration of lean vehicle 1, which will be explained below. The turning attitude information acquired in step S102 (i.e., the turning attitude information acquired based on map information and speed information) is also called the first turning attitude information. An example of the process for acquiring turning attitude information is described below.

[0118] [ 0 0 5 2 ]

[0119] For example, the execution unit 22 can first determine the driving position of the lean vehicle 1 based on the output of the navigation device 18. Then, the execution unit 22 uses map information to obtain the radius of curvature at the driving position of the lean vehicle 1 on the road on the map. Note that the radius of curvature of lane 3 is equivalent to the reciprocal of the curvature of lane 3. Based on the obtained radius of curvature and the speed of the lean vehicle 1, the execution unit 22 can obtain the lean angle of the lean vehicle 1, the yaw rate of the lean vehicle 1, and the lateral acceleration of the lean vehicle 1, respectively.

[0120] [ 0 0 5 3 ]

[0121] In the lean angle acquisition process, the execution unit 2 can acquire the lean angle of the lean vehicle 1 using, for example, a known method. For example, if the lean angle of the lean vehicle 1 is set to "0", the velocity of the lean vehicle 1 is set to "V", the acceleration due to gravity is set to "g", and the radius of curvature of the lean vehicle 1 is set to "RJ", the lean angle is expressed by the following equation (1).

[0122] Garden / (― g XR) ) •• - ( 1 )

[0123]

[0124] Section 22 can obtain the lean angle of lean vehicle 1 based on the radius of curvature of lean vehicle 1 and the speed of lean vehicle 1 by using equation (1).

[0125] [ 0 0 5 6 ]

[0126] In the yaw rate acquisition process, the execution unit 2 can acquire the yaw rate of the lean vehicle 1 using, for example, a known method. For example, if the yaw rate of the lean vehicle 1 is "© dt", the yaw rate is expressed by the following equation (2).

[0127] [ 0 0 5 7 ]

[0128] 4) dt = V / R ••• (2)

[0129] [ 0 0 5 8 ]

[0130] Therefore, the execution unit 22 can obtain the yaw rate of the lean vehicle 1 based on the radius of curvature of the lean vehicle 1 and the speed of the lean vehicle 1 by using equation (2).

[0131] [ 0 0 5 9 ]

[0132] In the process of acquiring lateral acceleration, the execution unit 22 can acquire the lateral acceleration of the lean vehicle 1 using, for example, a known method. For example, if the lateral acceleration of the lean vehicle 1 is "A_La", the lateral acceleration is expressed by the following equation (3).

[0133] [ 0 0 6 0 ]

[0134] A — L a = VX ( / > dt ••• ( 3 )

[0135] [ 0 0 6 1 ]

[0136] Therefore, the execution unit 22 can obtain the lateral acceleration of the lean vehicle 1 based on the speed of the lean vehicle 1 and the yaw rate of the lean vehicle 1 by using equation (3).

[0137] [ 0 0 6 2 ]

[0138] The above describes an example of the process for acquiring each turning attitude information. However, the process for acquiring each turning attitude information is not limited to the above example. For example, the execution unit 22 may acquire each turning attitude information with greater accuracy by taking other information (e.g., tire radius) into consideration in addition to the above example. Also, for example, the execution unit 22 may acquire each turning attitude information using a different formula than the above example.

[0139] [ 0 0 6 3 ]

[0140] Regarding the process of acquiring turning attitude information, the execution unit 22 may, for example, acquire the radius of curvature at the travel position of the lean vehicle 1 at each point in time, and acquire turning attitude information based on the acquired radius of curvature and the speed of the lean vehicle 1. However, the execution unit 22 may divide the road through which the lean vehicle 1 travels into regions of a certain length and acquire turning attitude information for each region. This eliminates the need to strictly consider the radius of curvature at the travel position at each point in time, thereby reducing the computational load.

[0141] [ 0 0 6 4 ]

[0142] Figure 6 is a schematic diagram showing an example of a road through which lean vehicle 1 travels. The execution unit 22 can identify the road through which lean vehicle 1 travels, for example, based on the setting information of the lean vehicle 1's travel route. The setting information is information related to the setting of the travel route by the rider, for example, information indicating the travel route set by the rider using the navigation device 18 (i.e., the travel route to be guided). The execution unit 22 can acquire such information based on the output of the navigation device 18. Then, the execution unit 22 can identify the road through which lean vehicle 1 travels, assuming that lean vehicle 1 travels along the travel route set by the rider.

[0143] [ 0 0 6 5 ]

[0144] The execution unit 22 divides the road through which the lean vehicle 1 passes into multiple regions where the lean vehicle 1 passes at different points in time. For example, in the example shown in Figure 6, regions R1, R2, R3, and R4 are shown as regions divided by the execution unit 22. For example, the execution unit 22 divides the road through which the lean vehicle 1 passes by at points where the radius of curvature changes significantly. Note that the method of dividing the regions is not limited to this example; for example, the road may be divided evenly so that the distance between each region is the same.

[0145] [ 0 0 6 6 ]

[0146] In the example in Figure 6, lean vehicle 1 is traveling in region R1. Region R1 is the region up to point P1 in front of lean vehicle 1. Region R2 is continuous with region R1 in front and extends from point P1 to point P2, which is ahead of point P1. Region R3 is continuous with region R2 in front and extends from point P2 to point P3, which is ahead of point P2. Region R4 is continuous with region R3 in front and extends from point P3. Regions R1 and R4 are straight and not curved. On the other hand, regions R2 and R3 are curved.

[0147] [ 0 0 6 7 ]

[0148] The execution unit 22 acquires turning attitude information for each of the multiple regions that divide the road through which the lean vehicle 1 passes. For example, in the example shown in Figure 6, the execution unit 22 acquires turning attitude information for each of the regions R1, R2, R3, and R4. For example, the execution unit 22 uses map information to acquire the radius of curvature for each region. Then, assuming that the speed of the lean vehicle 1 is maintained at the current speed, the execution unit 22 acquires turning attitude information for each region based on the radius of curvature and the speed of the lean vehicle 1, as described above. Note that in the process of acquiring turning attitude information, for regions that are not curved but straight, such as region R1 and region R4, the execution unit 22 sets the curvature to ○, and the lean angle, yaw rate, and lateral acceleration to ○.

[0149] [ 0 0 6 8 ]

[0150] As will be explained later, turning attitude information is used to determine the target vehicle in adaptive cruise control. In the example in Figure 6, lean vehicle 1 is traveling in region R1, so the execution unit 22 uses the turning attitude information of region R1 to determine the target vehicle in adaptive cruise control. After some time has passed and lean vehicle 1 enters region R2, the execution unit 22 uses the turning attitude information of region R2 to determine the target vehicle in adaptive cruise control. In this way, the turning attitude information used changes each time the region in which lean vehicle 1 is traveling changes.

[0151] [ 0 0 6 9 ]

[0152] Here, as described above, when turning attitude information is acquired for each of the multiple regions, the turning attitude information used may change abruptly as the region in which the lean vehicle 1 travels changes. In that case, problems may arise such as the target vehicle determined using the turning attitude information changing abruptly. Therefore, it is preferable for the execution unit 22 to determine the turning attitude information in adjacent regions among the multiple regions so that it changes gradually as time passes as the lean vehicle 1 passes through.

[0153] [ 0 0 7 0 ]

[0154] For example, in the example shown in Figure 6, the execution unit 22 determines that the turning attitude information will gradually change over time (i.e., in accordance with the change in the driving position of the lean vehicle 1) as the lean vehicle 1 enters region R2 from region R1. In this case, the execution unit 22 gradually changes the turning attitude information used to determine the target vehicle, from the turning attitude information acquired for region R1 to the turning attitude information acquired for region R2.

[0155] [ 0 0 7 1 ]

[0156] For example, when the lean vehicle 1 is traveling in area R1, the execution unit 22 acquires turning attitude information in area R2 based on the current speed of the lean vehicle 1 when the distance from the lean vehicle 1's position to point P1 (i.e., the boundary between area R1 and area R2) reaches a predetermined distance. Then, after the lean vehicle 1 enters area R2 from area R1, the execution unit 22 gradually changes the turning attitude information used to determine the target vehicle so that the turning attitude information used to determine the target vehicle becomes the turning attitude information in area R2. Furthermore, the execution unit 22 may begin changing the turning attitude information used to determine the target vehicle when the lean vehicle 1 is traveling in region R1, or it may begin changing the turning attitude information used to determine the target vehicle after the lean vehicle 1 has entered region R2 from region R1. When the lean vehicle 1 enters region R3 from region R2, and when the lean vehicle 1 enters region R4 from region R3, the execution unit 22 gradually changes the turning attitude information used to determine the target vehicle in the same manner as described above. This suppresses abrupt changes in the turning attitude information used to control the control mode.

[0157] [ 0 0 7 2 ]

[0158] Following step S! 2 in Figure 5, in step S! 3, the execution unit 22 determines the expanded region 5 based on the rotational attitude information acquired in step S1 0 2.

[0159] [ 0 0 7 3 ]

[0160] In step S103, the execution unit 22 estimates the future travel trajectory 4 of the lean vehicle 1 based on the turning attitude information, and determines the expansion area 5 based on the estimated travel trajectory 4. This makes it possible to appropriately determine the travel trajectory 4 and the expansion area 5 while understanding the attitude of the lean vehicle 1, even when the lean vehicle 1 is performing a turning maneuver. The details of the process for determining the travel trajectory 4 and the expansion area 5 will be explained below with reference to Figure 7.

[0161] [ 0 0 7 4 ]

[0162] Figure 7 shows a lean vehicle 1 in motion while turning. In the example in Figure 7, the lane 3 in which lean vehicle 1 is traveling is curved, and in such a lane 3, lean vehicle 1 and the preceding vehicle 2 are moving in a curved direction side by side.

[0163] [ 0 0 7 5 ]

[0164] As described above, the execution unit 22 estimates the future travel trajectory 4 of the lean vehicle 1 based on the turning attitude information. For example, the execution unit 22 may estimate the travel trajectory 4 based on the lean angle of the lean vehicle 1. In this case, the execution unit 22 estimates the travel trajectory 4 based on the direction of travel of the lean vehicle 1 estimated from the lean angle of the lean vehicle 1. As a result, as shown in Figure 7, the travel trajectory 4 can be estimated to be the trajectory that the lean vehicle 1 performing turning travels is expected to take in the future (for example, a trajectory along the direction of extension of lane 3).

[0165] [ 0 0 7 6 ]

[0166] Here, the execution unit 22 may use any of the turning attitude information mentioned above when estimating the travel trajectory 4. For example, the execution unit 22 may estimate the travel trajectory 4 based on the yaw rate of the lean vehicle 1 or the lateral acceleration of the lean vehicle 1. In this case, the execution unit 22 estimates the travel trajectory 4 based on the direction of travel of the lean vehicle 1 estimated from the yaw rate of the lean vehicle 1 or the lateral acceleration of the lean vehicle 1. In this way, as shown in Figure 7, the trajectory that the lean vehicle 1 performing turning travels is expected to take in the future (for example, a trajectory along the direction of extension of lane 3) can be estimated as the travel trajectory 4.

[0167] [ 0 0 7 7 ]

[0168] Furthermore, the execution unit 22 may estimate the travel trajectory 4 by comprehensively considering multiple types of turning attitude information. For example, the travel trajectory 4 may be estimated by comprehensively considering all or any part of the turning attitude information mentioned above. In addition, the execution unit 22 may estimate the travel trajectory 4 using the target vehicle's travel position information in addition to the turning attitude information.

[0169] [ 0 0 7 8 ]

[0170] As described above, the execution unit 22 determines the expanded area 5 based on the estimation result of the driving trajectory 4. In the example in Figure 7, the execution unit 22 determines the expanded area 5 as the area obtained by extending the driving trajectory 4 along the direction of extension of lane 3 in a direction perpendicular to the driving trajectory 4. As a result, at least a part of the preceding vehicle 2 traveling in lane 3 on which the lean vehicle 1 is traveling can be placed within the expanded area 5, so the preceding vehicle 2 can be determined as the target vehicle. Therefore, the positional relationship between the lean vehicle 1 and the preceding vehicle 2 is adjusted by adaptive cruise control to the target positional relationship. As a result, follow driving in which the lean vehicle 1 follows the preceding vehicle 2 is realized.

[0171] [ 0 0 7 9 ]

[0172] As described above, in this embodiment, since the attitude of the lean vehicle 1 can be grasped and the travel trajectory 4 and the expanded area 5 can be appropriately determined, even when the lean vehicle 1 is turning, the preceding vehicle 2 traveling in the lane 3 on which the lean vehicle 1 is traveling can be determined as the target vehicle. However, if the attitude of the lean vehicle 1 cannot be grasped, for example, a situation may arise where the travel trajectory 4 is determined to be a trajectory that deviates significantly from the direction of extension of lane 3, as shown by the dashed line 6 in Figure 7. In that case, the preceding vehicle 2 traveling in the lane 3 on which the lean vehicle 1 is traveling is located outside the expanded area 5, making it impossible to determine the preceding vehicle 2 as the target vehicle, or a situation may arise where a vehicle traveling in a different lane than the lane 3 on which the lean vehicle 1 is traveling is determined as the target vehicle. On the other hand, in this embodiment, since the attitude of the leaning vehicle 1 can be grasped and the travel trajectory 4 and the expanded area 5 can be appropriately determined, such a situation can be avoided.

[0173] [ 0 0 8 0 ]

[0174] Following step S! 3 in Figure 5, in step S104, the execution unit 22 determines the target vehicle based on the enlarged area 5 determined in step S103, and returns to step S102

[0081] .

[0175] In step S! 4, as described above, the execution unit 22 determines, for example, a preceding vehicle 2 that is at least partially located within the expanded area 5 as the target vehicle. As a result, as described above, in the example of Figure 7, the preceding vehicle 2 traveling in the lane 3 on which the lean vehicle 1 is traveling can be determined as the target vehicle.

[0176] [ 0 0 8 2 ]

[0177] The above describes an example in which the execution unit 22 determines the target vehicle based on the expanded area 5. However, the execution unit 22 may also determine the target vehicle based on lane data. Lane data is data indicating the lane 3 in which the lean vehicle 1 is traveling. Lane data may include, for example, data indicating the relative positions of the left and right boundary lines of lane 3 with respect to the lean vehicle 1. Specifically, the execution unit 22 may determine the lane data based on the estimation result of the travel trajectory 4 and determine the target vehicle based on the lane data. Alternatively, the execution unit 22 may determine the target vehicle using lane data indicating the lane adjacent to the lane 3 in which the lean vehicle 1 is traveling.

[0178] [ 0 0 8 3 ]

[0179] Here, as described above, the execution unit 22 acquires the turning attitude information of the lean vehicle 1 based on the map information and speed information, and estimates the driving trajectory 4 based on the turning attitude information thus acquired. Then, the execution unit 22 determines the lane data based on the estimation result of the driving trajectory 4 thus estimated.

[0180] [ 0 0 8 4 ]

[0181] For example, the execution unit 22 assumes that the position of the leaning vehicle 1 in the lane width direction in lane 3 is in the center of lane 3, and that the leaning vehicle 1 will travel along the driving trajectory 4 in the future while maintaining that position in the lane width direction, and determines the lane data. For example, the execution unit 22 determines the lane data to show that the left boundary line of lane 3 is located on a trajectory that is offset to the left of the driving trajectory 4 by half the width of lane 3, and the right boundary line of lane 3 is located on a trajectory that is offset to the right of the driving trajectory 4 by half the width of lane 3. Then, for example, the execution unit 22 determines the preceding vehicle 2, which is at least partially located within the area demarcated by the left and right boundary lines of lane 3 indicated by the lane data, as the target vehicle.

[0182] [ 0 0 8 5 ]

[0183] As described above, in this embodiment, in the example where the target vehicle is determined based on lane data, the attitude of the leaning vehicle 1 can be grasped and the driving trajectory 4 and lane data can be appropriately determined. Therefore, even when the leaning vehicle 1 is turning, the preceding vehicle 2 traveling in the lane 3 in which the leaning vehicle 1 is traveling can be determined as the target vehicle. [0 0 8 6]

[0184] As described above, the execution unit 22 of the control device 20 of this embodiment acquires turning attitude information of the lean vehicle 1 based on map information and speed information, and executes a control mode based on the turning attitude information. As a result, the control mode can be executed after understanding the attitude of the lean vehicle 1. Therefore, it is possible to appropriately support the rider's driving.

[0185] [ 0 0 8 7 ]

[0186] Specifically, in the above example, the execution unit 22 estimates the future trajectory 4 of the lean vehicle 1 based on the turning attitude information, and executes a control mode based on the estimated trajectory 4. As a result, as in the above example, in the control mode described above, the attitude of the lean vehicle 1 can be grasped, and the preceding vehicle 2 traveling in the lane 3 on which the lean vehicle 1 is traveling can be determined as the target vehicle. Therefore, appropriate support can be provided to the rider's driving. [0 0 8 8]

[0187] In this embodiment, the inertial measuring device is not provided on the lean vehicle 1. The inertial measuring device is, for example, a device that detects acceleration in the three axes and angular velocity around the three axes. If the lean vehicle 1 is provided with an inertial measuring device, the lean vehicle 1's turning attitude information (specifically, lean angle, lateral acceleration, yaw rate, etc.) can be obtained based on the output of the inertial measuring device. In this regard, even in the case of a lean vehicle 1 that is not provided with an inertial measuring device, the above processing by the execution unit 22 allows the attitude of the lean vehicle 1 to be grasped and the above control mode to be executed, thereby appropriately supporting driving by the lidar.

[0188] [ 0 0 8 9 ]

[0189] In the above, as an example of a process that executes a control mode based on turning attitude information, an example of a process that estimates the future travel trajectory 4 of the lean vehicle 1 based on turning attitude information and executes a control mode based on the estimated travel trajectory 4 was described. However, the example of a process that executes a control mode based on turning attitude information is not limited to the above example. Below, the first, second, and third examples of processes that execute a control mode based on turning attitude information, other than the above example, will be described.

[0190] [ 0 0 9 0 ]

[0191] The first processing example is a processing example in which, in control mode, the speed, acceleration, and deceleration of the lean vehicle 1 are controlled based on the turning attitude information and the driving characteristics information of the rider of the lean vehicle 1. In other words, in control mode, the execution unit 22 may control the speed, acceleration, and deceleration of the lean vehicle 1 based on the turning attitude information and the driving characteristics information of the rider of the lean vehicle 1.

[0192] [ 0 0 9 1 ]

[0193] Figure 8 is a graph showing an example of the driving characteristics of a lidar. In Figure 8, the vertical axis A_L a represents the lateral acceleration of lean vehicle 1, and the horizontal axis v represents the speed of lean vehicle 1, showing the relationship between lateral acceleration and speed during driving of lean vehicle 1 as a driving characteristic. As shown in Figure 8, the relationship between lateral acceleration and speed as a driving characteristic can be broadly classified into three driving characteristics, shown by graphs such as solid lines, dashed lines, and dashed lines. The solid line driving characteristic is a general driving characteristic. The dashed line driving characteristic is a sportier driving characteristic compared to the general driving characteristic. The dashed line driving characteristic is a milder driving characteristic compared to the general driving characteristic.

[0194] [ 0 0 9 2 ]

[0195] For example, the LiDAR can use the input device 14 to select one of the three driving characteristics shown in Figure 8. The driving characteristic selected by the LiDAR is stored in the memory element of the control device 20. The execution unit 22 then acquires the lateral acceleration of the lean vehicle 1 as turning attitude information based on the map information and speed information, and controls the speed of the lean vehicle 1 so that the relationship between the lateral acceleration and speed of the lean vehicle 1 approaches the driving characteristic selected by the LiDAR (that is, so that the points showing lateral acceleration and speed in Figure 8 approach the selected graph). In this way, while taking the LiDAR's driving characteristics into consideration, situations where the speed of the lean vehicle 1 is excessively high or excessively low relative to the lateral acceleration can be suppressed.

[0196] [ 0 0 9 3 ]

[0197] Figure 9 is a graph different from Figure 8, which shows an example of a rider's driving characteristics. In Figure 9, the vertical axis A - L o shows the longitudinal acceleration of lean vehicle 1, and the horizontal axis A - L a shows the lateral acceleration of lean vehicle !, showing the relationship between longitudinal acceleration and lateral acceleration during driving of lean vehicle 1 as a driving characteristic. As shown in Figure 9, the relationship between longitudinal acceleration and lateral acceleration as a driving characteristic can be broadly classified into three driving characteristics, shown by graphs such as solid lines, dashed lines, and dashed lines. The solid line driving characteristic is a general driving characteristic. The dashed line driving characteristic is a sportier driving characteristic compared to the general driving characteristic. The dashed line driving characteristic is a milder driving characteristic compared to the general driving characteristic.

[0198] [ 0 0 9 4 ]

[0199] For example, the LiDAR can use the input device 14 to select one of the three driving characteristics shown in Figure 9. The driving characteristic selected by the LiDAR is stored in the memory element of the control device 20. The execution unit 22 then acquires the lateral acceleration of the lean vehicle 1 as turning attitude information based on the map information and speed information, and controls the longitudinal acceleration (i.e., acceleration or deceleration) of the lean vehicle 1 so that the relationship between the longitudinal acceleration and lateral acceleration of the lean vehicle 1 approaches the driving characteristic selected by the LiDAR (i.e., so that the points showing longitudinal acceleration and lateral acceleration in Figure 9 approach the selected graph). This makes it possible to suppress situations where the longitudinal acceleration of the lean vehicle 1 is excessively high or excessively low relative to the lateral acceleration, while taking the LiDAR's driving characteristics into consideration.

[0200] [ 0 0 9 5 ]

[0201] In the above description, an example was given in which the execution unit 22 controls at least one of the speed, acceleration, and deceleration of the lean vehicle 1 in control mode based on lateral acceleration as turning attitude information and the driving characteristics information of the ridor of the lean vehicle 1. However, the execution unit 22 may also control at least one of the speed, acceleration, and deceleration of the lean vehicle 1 in control mode based on turning attitude information other than lateral acceleration (e.g., lean angle, yaw rate) and the driving characteristics information of the ridor of the lean vehicle 1. Specifically, the execution unit 22 may control at least one of the speed, acceleration, and deceleration of the lean vehicle 1 so that the relationship between at least one of the speed, acceleration, and deceleration of the lean vehicle 1 and turning attitude information other than lateral acceleration (e.g., lean angle, yaw rate) approaches the driving characteristics selected by the ridor.

[0202] [ 0 0 9 6 ]

[0203] The above describes an example in which the driving characteristics are selected by the LiDAR. However, the execution unit 22 may automatically determine the LiDAR's driving characteristics. For example, the execution unit 22 may automatically determine the LiDAR's driving characteristics based on the behavior of the lean vehicle 1 or the past history of driving operations performed by the LiDAR.

[0204] [ 0 0 9 7 ]

[0205] The second processing example is a processing example in which, in control mode, a notification operation is performed to notify the rider of lean vehicle 1 based on the turning attitude information. In other words, the execution unit 22 may perform a notification operation in control mode to notify the rider of lean vehicle 1 based on the turning attitude information.

[0206] [ 0 0 9 8 ]

[0207] The execution unit 22 provides the rider with various information regarding the turning posture during the notification operation described above. For example, the notification operation can be performed by displaying information on the display device 13. However, the execution unit 22 may perform the notification operation by a method other than displaying information on the display device 13. For example, the execution unit 22 may perform the notification operation using a display device provided on the rider's equipment (e.g., a helmet). Alternatively, the execution unit 22 may perform the notification operation using a sound output device or vibration generating device provided on the lean vehicle 1 or the rider's equipment.

[0208] [ 0 0 9 9 ]

[0209] For example, in the notification operation described above, the execution unit 22 may notify the rider of the turning attitude information itself, which is obtained based on the map information and speed information.

[0210] [ 0 1 0 0 ]

[0211] Furthermore, for example, in the notification operation described above, the execution unit 22 may notify the rider of information regarding the travel trajectory 4 estimated based on the turning posture information (for example, information regarding at least one of the extension direction and shape of the travel trajectory 4).

[0212] [ 0 1 0 1 ]

[0213] Furthermore, for example, in the notification operation described above, the execution unit 22 may notify the rider of information regarding the expanded area 5 or lane data determined based on the estimation result of the driving trajectory 4 (for example, information regarding at least one of the extension direction and shape of the expanded area 5 or lane data).

[0214] [ 0 1 0 2 ]

[0215] Furthermore, for example, in the notification operation described above, the execution unit 22 may also notify the LiDAR of information regarding the target vehicle determined based on the expanded area 5 or lane data (for example, information indicating which vehicle has been determined to be the target vehicle).

[0216] [ 0 1 0 3 ]

[0217] Furthermore, for example, in the notification operation described above, the execution unit 22 may also notify the LiDAR of the relationship between at least one of the lean vehicle 1's speed, acceleration, and deceleration and the turning attitude information (e.g., lateral acceleration, lean angle, yaw rate) and the driving characteristics selected by the LiDAR (for example, information showing how much the relationship between the lean vehicle 1's speed and lateral acceleration deviates from the graph selected in Figure 8).

[0218] [ 0 1 0 4 ]

[0219] Furthermore, in control mode, the execution unit 22 may suppress notification during the notification operation if the turning posture information indicates that the lean vehicle 1 is turning at a degree exceeding the standard. Here, if the turning degree of the lean vehicle 1 is high (for example, the lean angle is large), a situation may arise where the notification during the notification operation is likely to be perceived as bothersome to the rider. Therefore, for example, if the turning degree indicated by the turning posture information is high enough to cause such a situation, the execution unit 22 will determine that the turning posture information indicates that the lean vehicle 1 is turning at a degree exceeding the standard. In that case, the execution unit 22 will suppress notification during the notification operation. Furthermore, suppressing notification during the notification operation may also mean prohibiting notification during the notification operation, or it may also mean weakening the perceptibility of the notification during the notification operation (for example, making the display area smaller, lowering the display brightness, or changing the display color).

[0220] [ 0 1 0 5 ]

[0221] The third processing example is a processing example in which, in control mode, when the turning attitude information indicates that the lean vehicle 1 is turning at a degree exceeding a standard, braking is suppressed in the braking operation performed in response to the possibility of collision. Specifically, the braking operation is an operation that automatically brakes the lean vehicle 1 in response to the possibility of collision of the lean vehicle 1. In other words, in control mode, the execution unit 22 may suppress braking in the braking operation when the turning attitude information indicates that the lean vehicle 1 is turning at a degree exceeding a standard.

[0222] [ 0 1 0 6 ]

[0223] The execution unit 22 can perform a braking operation that automatically brakes the lean vehicle 1 according to the likelihood of collision with the lean vehicle 1. In the braking operation, for example, a threshold value is set for the likelihood of collision between the lean vehicle 1 and surrounding objects (e.g., a target vehicle). For example, when the likelihood of collision exceeds the threshold value, the execution unit 22 performs a braking operation that automatically generates a braking force on the lean vehicle 1. The execution unit 22 can determine the likelihood of collision based, for example, on the distance between the lean vehicle 1 and surrounding objects, and the relative speed of the lean vehicle 1 with respect to the surrounding objects. The likelihood of collision can be expressed, for example, by dividing the relative speed of the lean vehicle 1 with respect to the surrounding objects by the distance between the lean vehicle 1 and the surrounding objects. Furthermore, the collision probability described above may be expressed by a value that takes into account not only the distance between the leaning vehicle 1 and the surrounding objects, and the relative velocity of the leaning vehicle 1 with respect to the surrounding objects, but also the relative acceleration of the leaning vehicle 1 with respect to the surrounding objects.

[0224] [ 0 1 0 7 ]

[0225] Here, if the lean vehicle 1 has a high degree of turning (for example, a large lean angle), braking during the braking operation may actually induce the lean vehicle 1 to tip over, potentially reducing safety. Therefore, for example, if the degree of turning indicated by the turning posture information is high enough to cause such a situation, the execution unit 22 determines that the turning posture information indicates that the lean vehicle 1 is turning at a degree exceeding the standard. In that case, the execution unit 22 suppresses braking during the braking operation. Suppressing braking during the braking operation may mean prohibiting braking during the braking operation, or it may mean reducing the braking force generated on the lean vehicle 1 by the braking operation.

[0226] [ 0 1 0 8 ]

[0227] The above describes an example of processing performed by the control device 20. However, the processing performed by the control device 20 may be a modified version of the processing example described above.

[0228] [ 0 1 0 9 ]

[0229] For example, the above mainly described an example in which a positional relationship adjustment operation is performed as a rider support operation. However, operations other than positional relationship adjustment operations may also be performed as rider support operations. For example, the execution unit 22 may perform a collision avoidance support operation as a rider support operation to help the leaning vehicle 1 avoid a collision. The execution unit 22 may then acquire turning attitude information of the leaning vehicle 1 based on map information and speed information, and execute a control mode in which a collision avoidance support operation is performed based on the turning attitude information.

[0230] [ 0 1 1 0 ]

[0231] For example, the collision avoidance support operation may be the braking operation described above (specifically, an operation that automatically brakes the leaning vehicle 1 according to the likelihood of a collision with the leaning vehicle 1). In the braking operation, for example, the future travel trajectory 4 of the leaning vehicle 1 is estimated, and the likelihood of a collision between the leaning vehicle 1 and an object determined based on the estimation result of the travel trajectory 4 is identified. For example, the execution unit 22 may estimate the future travel trajectory 4 of the leaning vehicle 1 based on the turning posture information, and determine the above object based on the estimation result of such a travel trajectory 4. Also, for example, as described above, the execution unit 22 may suppress braking in the above braking operation if the turning posture information indicates that the leaning vehicle 1 is turning at a degree exceeding a standard.

[0232] [ 0 1 1 1 ]

[0233] Furthermore, for example, the collision avoidance support operation may be an operation that notifies the rider according to the likelihood of a collision with the leaning vehicle 1. In such an operation, for example, similar to the braking operation described above, the future trajectory 4 of the leaning vehicle 1 is estimated, and the likelihood of a collision between the leaning vehicle 1 and an object determined based on the estimated trajectory 4 is identified. For example, the execution unit 22 may estimate the future trajectory 4 of the leaning vehicle 1 based on the turning posture information, and determine the above object based on the estimated result of such trajectory 4. Also, for example, the execution unit 22 may suppress notification in the above operation if the turning posture information indicates that the leaning vehicle 1 is turning at a degree exceeding a standard.

[0234] [ 0 1 1 2 ]

[0235] It should be noted that the rider assistance actions performed in the control mode, which is executed based on the turning attitude information, are not limited to the examples above. For example, such rider assistance actions include behavior stabilization actions to stabilize the behavior of leaning vehicle 1 (e.g., anti-lock brake control, traction control, etc.).

[0236] [ 0 1 1 3 ]

[0237] Furthermore, the above description refers to a lean vehicle 1 that is not equipped with an inertial measuring device. However, the lean vehicle according to the present invention may be equipped with an inertial measuring device. Figure 10 is a schematic diagram showing the general configuration of a modified lean vehicle 1A. As shown in Figure 10, the modified lean vehicle 1A differs from the lean vehicle 1 described above in that it is additionally equipped with an inertial measuring device 19.

[0238] [ 0 1 1 4 ]

[0239] In the lean vehicle 1A, the execution unit 22 can acquire turning attitude information of the lean vehicle 1A based on the output information of the inertial measuring device 19 mounted on the lean vehicle 1A. Here, the turning attitude information acquired based on the output information of the inertial measuring device 19 is also called the second turning attitude information. The execution unit 22 may then execute a control mode based on the first turning attitude information (i.e., the turning attitude information acquired based on the map information and speed information as described above) and the second turning attitude information.

[0240] [ 0 1 1 5 ]

[0241] For example, if the execution unit 22 cannot successfully acquire the first turning attitude information, it may acquire the second turning attitude information based on the output information of the inertial measuring device 19, and if it cannot successfully acquire the second turning attitude information, it may acquire the first turning attitude information based on map information and speed information. The execution unit 22 may then execute a control mode based on the turning attitude information that was acquired from the first turning attitude information and the second turning attitude information.

[0242] [ 0 1 1 6 ]

[0243] Furthermore, for example, the execution unit 22 may execute a control mode based on the comparison result between the first rotation attitude information and the second rotation attitude information. For example, the execution unit 22 evaluates the reliability of the second rotation attitude information based on the comparison result between the first rotation attitude information and the second rotation attitude information. For example, if the discrepancy between the first rotation attitude information and the second rotation attitude information is excessively large, the execution unit 22 evaluates the reliability of the second rotation attitude information as being lower than the standard. In that case, the execution unit 22 prohibits, for example, processing that utilizes the second rotation attitude information (for example, processing that executes a control mode based on the second rotation attitude information). In this case, the execution unit 22 may, for example, execute a control mode based on the first rotation attitude information. Furthermore, if the discrepancy between the first turning posture information and the second turning posture information is excessively large, the execution unit 22 may inform the rider that the reliability of the second turning posture information is lower than the standard.

[0244] [ 0 1 1 7 ]

[0245] Furthermore, if there is rotational attitude information included in the first rotational attitude information but not in the second rotational attitude information, the execution unit 22 may supplement the second rotational attitude information with such rotational attitude information. Also, if, with respect to specific information, the information included in the first rotational attitude information is more accurate than the information included in the second rotational attitude information, the execution unit 22 may prioritize using the information included in the first rotational attitude information for such specific information.

[0246] [ 0 1 1 8 ]

[0247] <Effects of the control device>

[0248] The effects of the control device 2〇 according to the embodiment of the present invention will be described.

[0249] [ 0 1 1 9 ]

[0250] The control device 2 includes an execution unit 22 that executes a control mode in which rider assistance actions are performed to support the rider. The execution unit 22 acquires first turning posture information as turning posture information of the lean vehicle 1 based on map information and the speed information of the lean vehicle 1, and executes a control mode based on the first turning posture information. This allows the control mode to be executed after appropriately understanding the posture of the lean vehicle 1. Therefore, it is possible to appropriately support the rider's driving.

[0251] [ 0 1 2 0 ]

[0252] Preferably, in the control device 20, the rider assistance operation includes a positional relationship adjustment operation that adjusts the positional relationship between the leaning vehicle 1 and a target vehicle traveling ahead of the leaning vehicle 1 to the target positional relationship. This allows the control mode to be executed in which the positional relationship adjustment operation is performed after appropriately understanding the attitude of the leaning vehicle 1. Thus, appropriate assistance to rider driving is appropriately realized.

[0253] [ 0 1 2 1 ]

[0254] Preferably, in the control device 20, the execution unit 22 estimates the future travel trajectory 4 of the lean vehicle 1 based on the first turning attitude information, and executes a control mode based on the estimated travel trajectory 4. As a result, as in the example described above, for example, in the control mode described above, the attitude of the lean vehicle 1 can be grasped, and the preceding vehicle 2 traveling in the lane 3 on which the lean vehicle 1 is traveling can be determined as the target vehicle. Thus, appropriate support for driving by a rider can be more appropriately realized.

[0255] [ 0 1 2 2 ]

[0256] Preferably, in the control device 20, the execution unit 22 determines an expanded region 5, which is an area extended in a direction perpendicular to the travel trajectory 4, based on the estimation result of the travel trajectory 4, and in the control mode, determines the target vehicle based on the expanded region 5. As a result, in the control mode described above, the attitude of the lean vehicle 1 is grasped, and the preceding vehicle 2 traveling in the lane 3 on which the lean vehicle 1 is traveling is appropriately determined as the target vehicle. Thus, appropriate support for driving by LiDAR is further appropriately realized.

[0257] [ 0 1 2 3 ]

[0258] Preferably, in the control device 20, the execution unit 22 determines lane data, which is data indicating the lane 3 in which the lean vehicle 1 is traveling, based on the estimation result of the travel trajectory 4, and in the control mode, determines the target vehicle based on the lane data. This appropriately enables the system to determine the preceding vehicle 2 traveling in the lane 3 in which the lean vehicle 1 is traveling as the target vehicle, after understanding the attitude of the lean vehicle 1 in the control mode. Therefore, it is even more appropriately enabled to support driving by the LiDAR system. [0 1 2 4]

[0259] Preferably, in the control device 20, the execution unit 22 controls at least one of the speed, acceleration, and deceleration of the lean vehicle 1 based on the first turning posture information and the rider's driving characteristics information in the control mode. This allows, for example, in the control mode, to adjust the relationship between the first turning posture information and at least one of the speed, acceleration, and deceleration of the lean vehicle 1 to closely match the rider's driving characteristics. In this way, in the control mode described above, the behavior of the lean vehicle 1 can be controlled after understanding the posture of the lean vehicle 1. Therefore, appropriate support for rider driving is more effectively realized.

[0260] [ 0 1 2 5 ]

[0261] Preferably, in the control device 20, the execution unit 22 performs a notification operation to notify the rider based on the first turning attitude information in the control mode. As a result, various information regarding the first turning attitude information can be notified to the rider in the control mode. In this way, in the control mode described above, the attitude of the lean vehicle 1 can be grasped and then notified to the rider. Therefore, appropriate support for the rider's driving can be more effectively realized.

[0262] [ 0 1 2 6 ]

[0263] Preferably, in the control device 20, the execution unit 22 suppresses notification during the notification operation when the first turning posture information indicates that the lean vehicle 1 is turning at a degree exceeding a standard in the control mode. This suppresses notification during the notification operation in situations where it would likely be perceived as bothersome to the rider, thereby reducing the likelihood of the notification being perceived as bothersome to the rider. Thus, rider comfort can be improved.

[0264] [ 0 1 2 7 ]

[0265] Preferably, in the control device 20, the execution unit 22 performs a braking operation to automatically brake the leaning vehicle 1 according to the likelihood of collision of the leaning vehicle 1, and in the control mode, if the first turning posture information indicates that the leaning vehicle 1 is turning at a degree exceeding a standard, braking in the braking operation is suppressed. As a result, braking in the braking operation can be suppressed in situations where braking in the braking operation would likely induce the leaning vehicle 1 to tip over and thus reduce safety, thereby improving safety.

[0266] [ 0 1 2 8 ]

[0267] Preferably, in the control device 20, the rider assistance operation includes a collision avoidance assistance operation that assists in avoiding a collision with the leaning vehicle 1. This allows the control mode to be executed in which the collision avoidance assistance operation is performed after appropriately understanding the attitude of the leaning vehicle 1. Thus, appropriate assistance for rider driving is appropriately realized.

[0268] [ 0 1 2 9 ]

[0269] Preferably, in the control device 20, the execution unit 22 divides the road through which the lean vehicle 1 passes into multiple regions (regions R1, R2, R3, and R4 in the example of Figure 6 above) where the lean vehicle 1 passes through at different times, and acquires first turning attitude information for each of the multiple regions. This reduces the computational load.

[0270] [ 0 1 3 0 ]

[0271] Preferably, in the control device 20, the execution unit 22 determines that the first turning attitude information in adjacent regions among a plurality of regions (in the example of Figure 6 above, regions R1, R2, R3, R4) changes gradually as time passes while the lean vehicle 1 passes through. This suppresses abrupt changes in the first turning attitude information used for controlling the control mode.

[0272] [ 0 1 3 1 ]

[0273] Preferably, in the control device 20, the execution unit 22 acquires second turning attitude information as turning attitude information of the lean vehicle 1A based on the output information of the inertial measuring device 19 mounted on the lean vehicle 1A, and executes a control mode based on the first turning attitude information and the second turning attitude information. Thus, when the lean vehicle 1A is equipped with an inertial measuring device 19, the control mode can be executed using the first turning attitude information acquired based on map information and speed information, in addition to the second turning attitude information acquired based on the output information of the inertial measuring device 19. [0 1 3 2]

[0274] Preferably, in the control device 20, the execution unit 22 executes a control mode based on the comparison result between the first rotation attitude information and the second rotation attitude information. This allows the control mode to be executed, for example, based on the reliability of the second rotation attitude information.

[0275] [ 0 1 3 3 ]

[0276] The present invention is not limited to the descriptions of embodiments. For example, only a portion of the embodiments may be implemented.

[0277] [Explanation of symbols]

[0278] [ 0 1 3 4 ]

[0279] 1 Lean vehicle, 1A Lean vehicle, 2 Preceding vehicle, 3 Lane, 4 Driving trajectory, 5 Enlarged area, 6 Trajectory, 11 Engine, 12 Hydraulic control unit, 13 Display device, 14 Input device, 15 Surrounding environment sensor, 16 Front wheel speed sensor, 17 Rear wheel speed sensor, 18 Navigation device, 19 Inertial measurement device, 20 Control device, 21 Acquisition unit, 22 Execution unit, 100 LiDAR support system, P! Point, P2 Point, P3 Point, R1 Area, R2 Area, R3 Area, R4 Area.

Claims

1. [Document Name] Scope of Claim 2.

1. 3. A control device (2) for a rider assistance system (100) that assists the rider of a lean vehicle (1), 4. The system includes an execution unit (22) that executes a control mode in which rider assistance operations are performed to assist the rider, 5. The execution unit (22) is, 6. Based on the map information and the speed information of the lean vehicle (1), first turning attitude information is acquired as turning attitude information of the lean vehicle (1).

7. Based on the aforementioned first rotational attitude information, the control mode is executed.

8. Control device.

9.

2. 10. The control device according to claim 1, wherein the rider assistance operation includes a positional relationship adjustment operation that adjusts the positional relationship between the leaning vehicle (1) and a target vehicle traveling ahead of the leaning vehicle (1) to a target positional relationship.

11.

3. 12. The execution unit (22) is, 13. Based on the aforementioned first turning posture information, the future travel trajectory (4) of the lean vehicle (1) is estimated.

14. Based on the estimation result of the travel trajectory (4), the control mode is executed.

15. The control device according to claim 2.

16.

4. 17. The execution unit (22) is, 18. Based on the estimation result of the travel trajectory (4), an expanded region (5) is determined, which is the region obtained by extending the travel trajectory (4) in a direction perpendicular to the travel trajectory (4).

19. The control device according to claim 3, wherein in the control mode, the target vehicle is determined based on the expanded region (5).

20.

5. 21. The execution unit (22) is, 22. Based on the estimation result of the travel trajectory (4), lane data, which is data indicating the lane (3) in which the lean vehicle (1) is traveling, is determined.

23. The control device according to claim 3, wherein, in the control mode, the target vehicle is determined based on the lane data.

24.

6. 25. The execution unit (22) controls, in the control mode, at least one of the speed, acceleration, and deceleration of the lean vehicle (1) based on the first turning attitude information and the rider's driving characteristics information.

26. The control device according to claim 2.

27.

7. 28. The execution unit (22) in the control mode performs a notification operation to notify the rider based on the first turning attitude information.

29. The control device according to claim 2.

30.

8. 31. In the control mode, the execution unit (22) suppresses notification in the notification operation when the first turning posture information indicates that the lean vehicle (1) is turning at a degree exceeding the standard.

32. The control device according to claim (?).

33.

9. 34. The execution unit (22) is, 35. Execute a braking action to automatically brake the leaning vehicle (1) in accordance with the likelihood of collision of the leaning vehicle (1).

36. The control device according to claim 2, wherein in the control mode, if the first turning posture information indicates that the lean vehicle (1) is turning to a degree exceeding a standard, the braking in the braking operation is suppressed.

37. [Claim 1 〇] 38. The rider assistance operation includes a collision avoidance assistance operation that assists the leaning vehicle (1) in avoiding a collision.

39. The control device according to claim 1.

40. [Claim 1 1] 41. The execution unit (22) is, 42. The road through which the lean vehicle (1) passes is divided into multiple regions (R1, R2, R3, R4) where the timing of the lean vehicle (1) passing through each region is different from each other.

43. A control device according to any one of claims 1 to 10, which acquires the first rotational attitude information for each of the plurality of regions (R1, R2, R3, R4).

44. [Claim 1 2] 45. The execution unit (22) determines that the first turning attitude information in adjacent regions among the plurality of regions (R1, R2, R3, R4) changes gradually as time passes while the lean vehicle (1) passes through.

46. ​​The control device according to claim 11.

47. [Claim 1 3] 48. The execution unit (22) is, 49. Based on the output information of the inertial measuring device (19) mounted on the lean vehicle (1A), second turning attitude information is acquired as turning attitude information of the lean vehicle (1A).

50. The control mode is executed based on the first rotational attitude information and the second rotational attitude information.

51. The control device according to any one of claims 1 to 10.

52. [Claim 1 4] 53. The execution unit (22) executes the control mode based on the comparison result between the first rotational attitude information and the second rotational attitude information.

54. The control device according to claim 13.

55. [Claim 1 5] 56. A control method for a rider assistance system (100) that assists the rider of a lean vehicle (1), 57. The execution unit (22) of the control device (20) executes a control mode in which rider assistance operations are performed to assist the rider.

58. The execution unit (22) is, 59. Based on the map information and the speed information of the lean vehicle (1), first turning attitude information is obtained as turning attitude information of the lean vehicle (1).

60. Based on the first rotational attitude information, the control mode is executed.

61. Control method.

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