Vehicle control method and vehicle control device

Abstract

To provide a vehicle control method and a vehicle control device capable of further improving drivability of a vehicle by reducing pedal operations required of a driver in low vehicle speed range driving scenes.SOLUTION: A vehicle control method for controlling a vehicle 100 that outputs a driving torque when an accelerator is off by a driver, the method comprising learning a vehicle speed V when the vehicle 100 traveled in the past in a low vehicle speed range at or below a predetermined vehicle speed, calculating a target vehicle speed Vt during creep based on a learning result of the vehicle speed V, and determining the driving torque to be output when the accelerator is off based on the target vehicle speed Vt during creep.SELECTED DRAWING: Figure 3

Description

Technical Field

[0001] The present invention relates to a vehicle control method and a vehicle control device.

Background Art

[0002] Patent Document 1 discloses a control method for adjusting the drive torque (creep torque) applied to a vehicle when the accelerator is off in consideration of the vehicle's acceleration.

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] In a driving scene at a low vehicle speed such as when driving in a parking lot, if the driver feels that the vehicle speed is insufficient only with the creep torque, it is assumed that the driver will perform an accelerator operation. On the other hand, a situation may occur where a driver is required to perform a quick braking operation, such as when a pedestrian jumps out or another vehicle is discovered. In such a situation, it is necessary to appropriately switch the driver from an accelerator operation to a braking operation, and frequent pedal operations are required.

[0005] Therefore, an object of the present invention is to provide a vehicle control method and a vehicle control device that can improve the drivability of a vehicle by reducing the pedal operations required of the driver in a driving scene at a low vehicle speed range.

Means for Solving the Problems

[0006] According to an aspect of the present invention, there is provided a vehicle control method for controlling a vehicle that outputs driving torque when the driver releases the accelerator. In this vehicle control method, the vehicle speed when the vehicle has traveled in a low vehicle speed range of a predetermined vehicle speed or less in the past is learned, a target vehicle speed during creep is calculated based on the learning result of the vehicle speed, and based on the target vehicle speed during creep, the driving torque output when the accelerator is off is determined.

Effect of the Invention

[0007] According to the present invention, in a driving scene in a low vehicle speed range, the drivability of the vehicle can be further improved by reducing the pedal operation required of the driver.

Brief Description of the Drawings

[0008]

Figure 1

Figure 2

Figure 3

Figure 4

Figure 5

Figure 6

Mode for Carrying Out the Invention

[0009] Hereinafter, each embodiment of the present invention will be described with reference to the drawings.

[0010] [First Embodiment] FIG. 1 is an example of a schematic configuration diagram of a vehicle 100 to which a vehicle control method according to an embodiment of the present invention is applied, as viewed from above. In FIG. 1, the forward direction (upper side of the paper) when the vehicle 100 is moving forward is defined as the front, the backward direction (lower side of the paper) when moving backward is defined as the rear, the left side when facing forward is defined as the left, and the right side is defined as the right. FIG. 2 is an example of a schematic configuration diagram of a control system for controlling the vehicle 100.

[0011] In this embodiment, the case where the vehicle 100 is a so-called battery electric vehicle (BEV) will be described. However, the vehicle 100 may be a series hybrid electric vehicle (HEV), a parallel hybrid electric vehicle, or an automobile driven by an internal combustion engine. The type of the drive source for driving the wheels of the vehicle 100 is not limited.

[0012] The vehicle 100 includes a brake / drive actuator 1, a controller 2, a radar 3, a front camera 4, side cameras 5L and 5R, a navigation system 6, an accelerator pedal opening sensor (hereinafter also referred to as an APO sensor) 7, a brake switch 8, a steering sensor 9, an acceleration sensor 10, a vehicle speed detection unit 11, and a select switch 12.

[0013] The brake / drive actuator 1 is a unit including an electric motor that is a drive source of the vehicle 100 and an inverter or the like that controls the electric motor. The electric motor operates by power supplied from a battery (not shown) and drives wheels (not shown). Further, the electric motor generates a braking force by regenerating the kinetic energy of the vehicle 100 as electric power during deceleration. When the vehicle 100 is driven by an internal combustion engine, the brake / drive actuator 1 is the internal combustion engine.

[0014] The controller 2 as a vehicle control device is composed of a microcomputer equipped with a central processing unit (CPU), a read-only memory (ROM), a random access memory (RAM), and an input / output interface (I / O interface). It is also possible to configure the controller 2 with a plurality of microcomputers. In particular, the controller 2 is composed of a vehicle controller that comprehensively controls the operation of the vehicle 100, a motor controller that controls the operation of the electric motor, and an in-vehicle ECU for executing various other processes.

[0015] The radar 3 is arranged, for example, near the front end of the vehicle body, and uses radio waves to detect the distance to an object around the vehicle 100 and its direction.

[0016] The front camera 4 is arranged, for example, near the rearview mirror facing the vehicle traveling direction, and captures the front of the vehicle 100 (region F1 in the figure). Note that the front camera 4 may be a camera unit composed of a camera that captures the above region F1 and a wide-angle camera that captures the side of the vehicle 100 (region F2 in the figure).

[0017] The side cameras 5L and 5R are provided, for example, with the side camera 5L on the left door mirror and the side camera 5R on the right door mirror, and capture the left side (region SL in the figure) and the right side (region SR in the figure) of the vehicle 100. Note that the side cameras 5L and 5R may also be collectively referred to as the side camera 5.

[0018] The information detected by the radar 3 and the image information captured by the front camera 4 and the side cameras 5 are read into the controller 2. The controller 2 identifies the surrounding situation of the vehicle 100 based on this information, such as the distance to the target object, the relative distance to the target object, the relative speed to the target object, the attributes of the target object, etc.

[0019] The navigation system 6 is arranged, for example, in the vehicle interior, and performs functions such as setting and guiding the driving route to the destination set by the driver based on the pre-stored map information and the position information obtained from artificial satellites.

[0020] In addition, the navigation system 6 identifies the surrounding situation of the vehicle 100, for example, the attributes of the road during driving, curvature, width, speed limit, the position and content of traffic signs, and the position of signals, etc., based on the pre-stored map information and the position information obtained from artificial satellites. Here, the attributes of the road referred to here are highways, congested roads, winding roads, roads in densely populated areas, narrow roads, within parking lots, etc. Note that the curvature and width of the road during driving can also be identified using the image information captured by the front camera 4 and the side camera 5.

[0021] Note that the vehicle 100 of the present embodiment includes the radar 3, the front camera 4, the side camera 5, and the navigation system 6 as devices for identifying the surrounding situation, but is not limited thereto. For example, instead of or in addition to any of the radar 3, the front camera 4, and the side camera 5, it may be provided with a lidar (Laser Imaging Detection and Ranging). Also, instead of or in addition to the navigation system 6, it may be provided with a communication device capable of V2X (Vehicle to Everything) communication such as vehicle-to-vehicle communication or road-to-vehicle communication.

[0022] The accelerator pedal sensor 7 detects the opening degree of the accelerator pedal (not shown. Hereinafter, it may be simply referred to as the "accelerator"). A state where the opening degree of the accelerator pedal is not zero is called accelerator on, and a state where the opening degree of the accelerator pedal is zero is called accelerator off. The detected accelerator pedal opening degree is read into the controller 2.

[0023] The brake switch 8 detects the operation state of the brake pedal (not shown. Hereinafter, it may be simply referred to as the "brake"). A state where the brake pedal is depressed is called brake on, and a state where the brake pedal is not depressed is called brake off. The detected operation state of the brake pedal (brake on / brake off) is read into the controller 2.

[0024] The steering sensor 9 detects the operating state (steering angle, steering force) of a steering wheel (not shown) operated by the driver. The detected operating state of the steering wheel is read into the controller 2.

[0025] The acceleration sensor 10 detects the acceleration A of the vehicle 100. The detected acceleration A is read into the controller 2.

[0026] The vehicle speed detection unit 11 includes, for example, a rotational speed sensor that detects the rotational speed of a wheel. The detected rotational speed of the wheel is read into the controller 2. The vehicle speed detection unit 11 may be configured to estimate the vehicle speed V based on the output torque of the drive source, or may be configured to estimate the vehicle speed V based on the position information of the vehicle 100 acquired from the navigation system 6, or may be configured to estimate the vehicle speed V based on the information acquired from the cameras 4, 5 and the radar 3.

[0027] The select switch 12 detects the operation mode (forward mode, reverse mode, neutral mode, parking mode, etc.) of the vehicle 100 selected by the driver using a shifter (not shown). The detected operation mode is read into the controller 2.

[0028] The controller 2 reads the surrounding situation information, which is information about the surrounding situation of the vehicle 100 described above, the information detected by various sensors, etc., and controls the braking / driving actuator 1 based on this information.

[0029] In the present embodiment, when the controller 2 detects a scene where the vehicle 100 is traveling in a low vehicle speed range of a predetermined vehicle speed or less, the controller 2 executes automatic creep control to output drive torque (hereinafter, also referred to as "creep torque") to the electric motor, which is the drive source, when the driver releases the accelerator (when the operation amount with respect to the accelerator pedal is zero).

[0030] Here, the significance of executing automatic creep control in a low vehicle speed range will be described. When driving in a parking lot, which is an example of a driving scene in the low vehicle speed range, the vehicle 100 may be driven only by the creep torque (the creep torque that inevitably occurs due to the structure of an AT vehicle, or the torque at the time of releasing the accelerator operation that is pseudo-replicated in an electric vehicle) determined as a basic value, and the required vehicle speed V may be obtained.

[0031] On the other hand, some drivers may not feel that the vehicle speed V obtained only by this basic creep torque is sufficient and may execute an accelerator operation. In this case, for example, when the driver discovers a pedestrian trying to pass in front of the vehicle 100, it is assumed that the driver will release the accelerator operation and execute a brake operation. However, the time required to switch from an accelerator operation to a brake operation greatly depends on the driver's driving skill and reaction speed.

[0032] In view of such a situation, in the present embodiment, as will be described with reference to FIGS. 3 to 6 below, in a driving scene in the low vehicle speed range (particularly when driving in a parking lot), automatic creep control is executed that can obtain the vehicle speed V desired by the driver without requiring the driver to switch from an accelerator operation to a brake operation.

[0033] In particular, in the present embodiment, the above object is achieved by appropriately executing the following learning phase, normal phase, and verification phase in a driving scene in the low vehicle speed range.

[0034] FIG. 3 is a diagram showing the transition of the learning phase, normal phase, and verification phase. As shown in the figure, the vehicle control method of the present embodiment includes a learning phase, a normal phase, and a verification phase.

[0035] The learning phase is a phase for executing learning to determine the target vehicle speed V at creep V t which is the target value of the vehicle speed V when executing automatic creep control in the vehicle 100. The normal phase is the target vehicle speed V at creep V tThis is the phase of executing automatic creep control using [it]. The verification phase is the phase of determining the necessity of relearning by referring to whether a correction operation by the driver is executed during the execution of the automatic creep control or the like.

[0036] In this embodiment, first, the target vehicle speed V at the time of creep used in the automatic creep control is set or updated by learning in the learning phase, and the normal phase is executed with the target vehicle speed V at the time of creep obtained by learning as an input. Also, the verification phase is executed in parallel with the execution of the normal phase. Hereinafter, the details in each phase will be described. Note that each process in each phase is executed by the controller 2. t In the learning phase, the target vehicle speed V at the time of creep used in the automatic creep control is set or updated by learning, and the normal phase is executed with the target vehicle speed V at the time of creep obtained by learning as an input. Also, the verification phase is executed in parallel with the execution of the normal phase. Hereinafter, the details in each phase will be described. Note that each process in each phase is executed by the controller 2. t In the learning phase, the target vehicle speed V at the time of creep used in the automatic creep control is set or updated by learning, and the normal phase is executed with the target vehicle speed V at the time of creep obtained by learning as an input. Also, the verification phase is executed in parallel with the execution of the normal phase. Hereinafter, the details in each phase will be described. Note that each process in each phase is executed by the controller 2.

[0037] FIG. 4 is a flowchart for explaining the learning phase.

[0038] As shown in the figure, in the learning phase, in step S10, it is determined whether the vehicle 100 is traveling in a parking lot. More specifically, by referring to the number of other vehicles included in the surrounding image acquired by the cameras 4 and 5, it is determined whether the current location of the vehicle 100 is a parking lot. Also, this determination may be executed by referring to the current vehicle speed V detected by the vehicle speed detection unit 11 and the position information of the vehicle 100 obtained by the navigation system 6.

[0039] If it is determined that the vehicle 100 is traveling in the parking lot, the process of step S11 is executed. In step S11, the vehicle speed V of the vehicle 100 is recorded. More specifically, the controller 2 records the vehicle speed V detected by the vehicle speed detection unit 11 in the internal memory for a predetermined number of samplings k (k = 1, 2, 3 ···). Hereinafter, the recorded vehicle speed V will be described as "recorded vehicle speed V k " using the character k representing the number of recordings.

[0040] Next, in step S12, the recorded vehicle speed V kDetermine whether the number (i.e., the number of samplings k) has reached a certain value or more. If it is determined that the number of samplings k has reached a certain value or more, the process of step S13 is executed.

[0041] In step S13, the controller 2 associates the record vehicle speed V k with the identification information I D of the driver driving the vehicle 100 and the driving location information I P to generate driving vehicle speed data D(V k ,I D ,I P ).

[0042] Here, the driver identification information I D can be obtained, for example, by storing the driver information pre-input via a predetermined input interface arranged in the vehicle interior in the internal memory of the controller 2 and reading out the information. Also, for the driver identification information I D , a configuration may be adopted in which the driver identification information I D pre-recorded in an external server (such as a predetermined cloud) arranged outside the vehicle 100 is obtained by V2X communication with the external server. Also, as the driving location information I P , the current position of the vehicle 100 obtained by the navigation system 6 can be used.

[0043] In step S14, referring to the driving vehicle speed data D(V k ,I D ,I P ), determine the target vehicle speed V D at creep associated with the driver identification information I t (I D ,I P ). More specifically, the controller 2 applies a predetermined statistical process (such as an operation to obtain the average value per sampling number k) to the record vehicle speed V k to obtain the target vehicle speed V t (I D ,I P) can be obtained. As a result, the vehicle speed V to be aimed at in the automatic creep control executed in the normal phase can be determined as a value considering the preferences according to the driving location of each driver.

[0044] Note that the driver's preference is considered to be affected by the degree of congestion and the size of the parking lot where the vehicle is traveling. Considering this point, parameters indicating the degree of congestion and the size of the parking lot are defined, and with reference to these parameters, the traveling vehicle speed data D(V k ,I D ,I P ) is used to calculate the target vehicle speed V during creep t (I D ,I P ). An algorithm may be adopted. More specifically, by using the external recognition sensors such as the cameras 4 and 5, the radar 3, and the lidar mounted on the vehicle 100, and / or V2X communication, the number of surrounding vehicles and pedestrians, and the distance and density between the vehicle 100 and other traffic participants are calculated, and the parameters can be determined by quantifying the degree of congestion and the size of the parking lot from these calculated values. Furthermore, by appropriately correcting the traveling vehicle speed data D(V k ,I D ,I P ) using the parameters, the target vehicle speed V during creep t (I D ,I P ) considering the influence of the degree of congestion and the size of the parking lot can be determined.

[0045] Next, in step S15, it is determined whether the target vehicle speed V during creep t (I D ,I P ) is less than a predetermined upper vehicle speed. The upper vehicle speed is the upper limit value of the vehicle speed V determined in consideration of safety during driving in the low vehicle speed range. Although not limited to specific numerical values, as an example, the upper vehicle speed can be set to about 20 [km / h].

[0046] And the target vehicle speed V during creep t (I D ,IP ) is less than the upper limit value, the target vehicle speed V during creep calculated in step S14 t (I D ,I P ) is recorded as the latest value, and this learning phase is terminated. On the other hand, when the target vehicle speed V during creep t (I D ,I P ) exceeds the upper limit value, the target vehicle speed V during creep calculated in step S14 t (I D ,I P ) is discarded (step S16), and this learning phase is terminated. Note that when the target vehicle speed V during creep calculated in this learning phase t (I D ,I P ) is discarded, the target vehicle speed V during creep determined in the learning phase before the previous time t (I D ,I P ) is output as the learning result in this learning phase and can be used in the normal phase.

[0047] Then, with the target vehicle speed V during creep obtained in the learning phase t (I D ,I P ) as the input, the normal phase is executed.

[0048] FIG. 5 is a flowchart for explaining the normal phase.

[0049] As shown in the figure, in step S20 of the normal phase, it is determined whether the vehicle 100 is traveling in the parking lot, in the same manner as step S10 in the learning phase. When it is determined that the vehicle 100 is traveling in the parking lot, the process of step S21 is executed.

[0050] In step S21, a process of requesting permission to execute the automatic creep control is performed for the driver. More specifically, for example, the text display including the proposal to execute the automatic creep control and the content for confirming whether to permit its execution is performed on the display in the vehicle interior.

[0051] When the driver permits the execution of the automatic creep control, the automatic creep control is executed (Yes in step S22 and step S23). More specifically, when the driver performs an operation indicating the intention of permission through the input interface in the vehicle interior, the current vehicle speed V approaches the target vehicle speed V during creep determined in the learning phase t (I D ,I P ). The creep torque is determined so as to approach, and the braking / driving actuator 1 is operated based on the determined creep torque.

[0052] Next, in step S24, it is determined whether or not the slip ratio of the vehicle 100 is equal to or less than a predetermined value in the situation where the automatic creep control is being executed. If the slip ratio is equal to or less than the predetermined value, the automatic creep control is maintained and this normal phase is terminated. On the other hand, if the slip ratio exceeds the predetermined value, the automatic creep control is stopped (step S25) and this normal phase is terminated.

[0053] That is, when the automatic creep control is executed to promote an increase in the creep torque, it is assumed that an unintended difference occurs between the wheel speed and the vehicle body speed (the slip ratio increases). In contrast, by executing the processes of step S24 and step S25, the automatic creep control can be stopped when the slip ratio becomes larger than the allowable range.

[0054] When stopping the automatic creep control based on the determination in step S24 or step S25 described above, it is preferable to execute a process for notifying the driver of the stop (for example, display on the in-vehicle display).

[0055] Further, in a situation where the automatic creep control is being executed, if it is detected that the accelerator operation and / or the brake operation has been executed a certain number of times or more, control may be adopted to stop the automatic creep control. That is, when the automatic creep control is being executed and the driver executes the accelerator operation and / or the brake operation a certain number of times or more, it is assumed that it is a scene where it is not desirable to continue the automatic creep control due to the influence of the surrounding environment (such as the presence of obstacles and pedestrians) in the vehicle 100. For this reason, by executing the processes of step S25 and step S26 above, the automatic creep control can be stopped in this scene, and interference with the driver's operation can be avoided. Further, regarding the above automatic creep control, it is preferable that its operation and non-operation can be switched as appropriate by the driver's manual operation.

[0056] Next, the verification phase executed in parallel with the above normal phase will be described.

[0057] FIG. 6 is a flowchart for explaining the verification phase.

[0058] In step S30 of the verification phase, in the same manner as step S10 in the learning phase, it is determined whether the vehicle 100 is traveling in a parking lot. And if it is determined that the vehicle 100 is traveling in a parking lot, the process of step S31 is executed.

[0059] In step S31, the accelerator operation, the brake operation, the vehicle speed V, and the acceleration A are recorded. More specifically, the controller 2 records the accelerator operation detected by the accelerator pedal sensor 7, the brake operation detected by the brake switch 8, the vehicle speed V detected by the vehicle speed detection unit 11, and the acceleration A detected by the acceleration sensor 10 in the internal memory over a predetermined number of calculation sampling times.

[0060] Then, based on each recorded quantity, it is determined whether the number of correction operations by the driver is equal to or greater than a certain number. More specifically, when the number of accelerator operations or brake operations in which the change amount of the vehicle speed V or the acceleration A is equal to or less than a predetermined value is equal to or greater than a predetermined number, it is determined that the correction operation by the driver is equal to or greater than a certain level. Here, the accelerator operation or brake operation (operation involving acceleration or deceleration equal to or greater than a certain level) when the change amount of the vehicle speed V or the acceleration A exceeds the predetermined value is considered to be executed due to factors other than the vehicle speed V not reaching the desired value, such as avoiding an obstacle. Therefore, by excluding such accelerator operations or brake operations involving a change in the vehicle speed V or the acceleration A equal to or greater than a certain level from the count of the correction operations by the driver, the necessity of relearning can be determined with higher accuracy.

[0061] Also, for example, a scene is assumed in which an obstacle exists in the vicinity of the vehicle 100 (within a predetermined distance range from the vehicle 100), and the driver performs an accelerator operation or a brake operation for the purpose of avoiding the obstacle. On the other hand, in this case, the driver's operation is not due to the vehicle speed V not reaching the desired value. Therefore, if the operation is included in the correction operation and the necessity of relearning is determined, it is assumed that the learning accuracy will decrease. Therefore, it is preferable to determine whether an obstacle exists within a predetermined distance range from the vehicle 100 at the time of detecting each quantity together with the recording of each quantity in step S31, and count only the accelerator operations and brake operations when no obstacle exists as the number of correction operations by the driver. The determination of whether an obstacle exists within the predetermined distance range can be executed using the surrounding situation of the vehicle 100 obtained by the above-described external recognition sensor and / or V2X communication as an input.

[0062] When it is determined that the number of correction operations by the driver is equal to or greater than a certain number, it is determined that relearning is necessary (step S33), and the relearning phase (Figure 3) is executed again. In the relearning phase again, the vehicle speed V recorded in step S31 may be used as the recorded vehicle speed V in the learning phase (particularly step S12). k It may be used.

[0063] The operational effects of the vehicle control method according to the present embodiment described above will be collectively described.

[0064] In the present embodiment, there is provided a vehicle control method for controlling a vehicle 100 that outputs driving torque (creep torque) when the driver releases the accelerator. In this vehicle control method, when the vehicle 100 has traveled in a low vehicle speed range of a predetermined vehicle speed or less in the past, the vehicle speed V (recorded vehicle speed V k ) is learned, the target vehicle speed V t during creep of the vehicle 100 is calculated, and the creep torque is determined based on the target vehicle speed V t during creep.

[0065] As a result, by learning the record of the vehicle speed V when the vehicle 100 has actually traveled in the low vehicle speed range, the vehicle speed V (target vehicle speed V t ) during creep, which is estimated to be suitable during creep running, is determined, and the creep torque can be adjusted based on the target vehicle speed V t during creep. Therefore, in a driving scene in a low vehicle speed range such as when driving in a parking lot, it is possible to ensure the necessary vehicle speed V without requiring an accelerator operation or a brake operation by the driver, and the drivability of the vehicle 100 can be further improved.

[0066] In particular, in the present embodiment, the vehicle speed V (recorded vehicle speed V k ) when traveling in the low vehicle speed range is associated with the information of the driver (identification information I D ) who was driving the vehicle 100 and the information of the driving location (driving location information I P ) where the vehicle 100 was traveling and learned.

[0067] As a result, it is possible to obtain the target vehicle speed V t (I D , I P ) during creep associated with a plurality of drivers who drive the vehicle 100 and the driving location. That is, the vehicle speed V during creep running can be adjusted to a value that takes into account the preferences of each driver who drives the vehicle 100 and the driving location.

[0068] In order to simplify the calculation, only one of the record vehicle speed V k is associated with the driver identification information I D and the driving location information I P for learning. Alternatively, a configuration may be adopted in which learning is performed without associating any of the record vehicle speed V k with the driver identification information I D and the driving location information I P to further simplify the calculation.

[0069] Also, in this embodiment, when the vehicle 100 is controlled by the creep target vehicle speed V t determined based on the learning result of the vehicle speed V, it is determined whether a correction operation for correcting the driving force and / or the braking force is performed by the driver. Then, relearning is performed according to the result of the execution determination of the correction operation.

[0070] Thereby, after detecting a situation where the creep target vehicle speed V t determined according to the learning result does not match the driver's preference, the creep target vehicle speed V t can be appropriately adjusted (updated) by relearning.

[0071] Furthermore, in this embodiment, the surrounding environment of the vehicle 100 is acquired, and it is determined whether there is an obstacle within a predetermined distance range from the vehicle 100 with reference to the surrounding environment. Then, it is determined whether relearning is necessary based on the determination result of whether there is an obstacle.

[0072] Thereby, it is possible to detect a situation where an accelerator operation and / or a brake operation is performed by the driver due to the presence of an obstacle around the vehicle 100. Therefore, the necessity of relearning can be determined in consideration of the fact that the operation is performed in the situation where the obstacle exists. Accordingly, it is possible to appropriately estimate a situation where the vehicle speed V during creep driving is not a desirable value for the driver, and to determine that relearning is necessary for the situation, thereby preventing the occurrence of mislearning.

[0073] Moreover, in this embodiment, a controller 2 is provided that functions as a vehicle control device suitable for executing the above vehicle control method.

[0074] In particular, the controller 2 detects the vehicle speed V (recorded vehicle speed V) when the vehicle 100 was traveling in a low vehicle speed range below a predetermined vehicle speed in the past. k ) based on the learning result of the vehicle speed V, and t and a target vehicle speed calculation unit that calculates the creep target vehicle speed V t It functions as a drive torque setting unit that determines the drive torque (creep torque) to be output when the accelerator is released based on the above.

[0075] [Second embodiment] The second embodiment will be described below, with the same elements as those in the first embodiment being given the same reference numerals and their description omitted.

[0076] In this embodiment, in step S11 of the learning phase in FIG. 2, in addition to the vehicle speed V of the vehicle 100, the acceleration A and jerk J are recorded. The acceleration A can be acquired as a detection value of the acceleration sensor 10, and the jerk J can be obtained by differentiating the acquired acceleration A with respect to time. Alternatively, the acceleration A may be obtained by differentiating the vehicle speed V with respect to time, and the jerk J may be obtained by further differentiating the acceleration A thus obtained with respect to time. In the following, the recorded acceleration A and jerk J will be referred to as "recorded acceleration A" and "jerk J," respectively. k " and "Record Jump J k " should be written.

[0077] Then, when it is determined that the number of samplings k of each value has reached a certain value or more (Yes in step S12), the record vehicle speed V k Identification information I of the driver who drives the vehicle 100 D and driving location information I P Vehicle speed data D(V k ,I D ,I P ), record acceleration A k Identification information I D and driving location information IP associated with the running acceleration data D(A k ,I D ,I P ), and the record jerk J k with the identification information I D and the running location information I P associated with the running jerk data D(J k ,I D ,I P ) are generated.

[0078] Furthermore, in step S14, referring to the running vehicle speed data D(V k ,I D ,I P ), the running acceleration data D(A k ,I D ,I P ), and the running jerk data D(J k ,I D ,I P ), respectively, the target vehicle speed V during creep t (I D ,I P ), the target acceleration A during creep t (I D ,I P ), and the target jerk J during creep t (I D ,I P ) are determined. Note that the target acceleration A during creep t (I D ,I P ) and the target jerk J during creep t (I D ,I P ) are, respectively, the target values of the acceleration A and jerk J when approaching the vehicle speed V to the target vehicle speed V during creep t (I D ,I P ). More specifically, for example, by applying a predetermined statistical process (such as an operation to obtain the average value per sampling number k) to each of the record acceleration A k and the record jerk J k ), the target acceleration A during creep t (I D ,I P ), and the target jerk J during creep t (ID , I P ) can be set as follows.

[0079] And in step S23 of the normal phase in FIG. 5, the controller 2 executes automatic creep control. More specifically, the controller 2 determines whether the current vehicle speed V, acceleration A, and jerk J are the above-mentioned target vehicle speed V during creep determined in the learning phase t (I D , I P ), target acceleration A during creep t (I D , I P ), and target jerk J during creep t (I D , I P ), calculates the creep torque so as to approach them, and operates the braking / driving actuator 1 based on the calculated creep torque.

[0080] As a result, in addition to learning the vehicle speed V, the acceleration A and the jerk J are simultaneously learned, and by determining the creep torque according to the result, during the automatic creep control, the acceleration A and the jerk J until the vehicle speed V reaches the target vehicle speed V during creep t (I D , I P ) can be determined in consideration of the individual preferences of the driver specified by the identification information I. D

[0081] As described above, in this embodiment, in addition to the vehicle speed V when driving in the low vehicle speed range, the acceleration A and the jerk J are learned, and based on the learning results of the vehicle speed V, acceleration A, and jerk J, the target vehicle speed V during creep t (I D , I P ), target acceleration A during creep t (I D , I P ), and target jerk J during creep t (I D , I P ) are calculated. Then, the target vehicle speed V during creep t (I D , I P ), target acceleration A during creep t (ID , I P ), and the target jerk J during creep t (I D , I P ), determine the creep torque based on this.

[0082] Thus, in a situation where no accelerator operation is being performed by the driver, while adjusting the vehicle speed V to the desired target vehicle speed V during creep t , the acceleration A and the jerk J during the period until the vehicle speed V reaches the target vehicle speed V during creep t can also be adjusted to values desired by the driver.

[0083] In addition, in step S11 above, it is further determined whether there is a factor that restricts the behavior of the vehicle 100, such as an obstacle existing within a predetermined distance range from the vehicle 100. If it is determined that such a factor exists, a configuration may be adopted in which the vehicle speed V, acceleration A, and jerk J detected at that time are excluded from the records. That is, in this case, the accelerator operation and / or brake operation (changes in the vehicle speed V, acceleration A, and / or jerk J) performed are considered to be mainly due to safety reasons such as avoiding a collision with an obstacle and not in line with the driver's preference. Therefore, by excluding each quantity detected in this scene from the data used for learning, mislearning can be prevented.

[0084] Alternatively, instead of or together with determining whether an obstacle exists within a predetermined distance range from the vehicle 100, the pitch amount of the vehicle 100 and / or the moment acting on the vehicle occupants are estimated from the recorded acceleration A, jerk J, and vehicle specifications, and the estimated results are referred to and, as appropriate, the vehicle speed V, acceleration A, and jerk J that are recorded are excluded from the data used for learning. For example, in a situation where a deceleration stronger than a certain level occurs, the vehicle 100 will exhibit uncomfortable behavior such as the driver having to lift their head for the occupants. Therefore, the situation showing such behavior can be regarded as not conforming to at least the driver's preferences. Accordingly, the situation showing such behavior is estimated according to the comparison result between the estimated pitch amount and / or moment and a predetermined determination value, and the vehicle speed V, acceleration A, and jerk J detected when such a situation occurs are excluded from the data used for learning, thereby enabling the learning accuracy to be further improved.

[0085] As described above, the embodiments of the present invention have been explained. However, the configurations described in each of the above embodiments merely show a part of the application examples of the present invention and are not intended to limit the technical scope of the present invention.

Explanation of Reference Numerals

[0086] 2 Driving force calculation unit (vehicle control device, drive torque control unit) 100 Vehicle

Claims

1. A vehicle control method for controlling a vehicle that outputs driving torque when the driver releases the accelerator, comprising: learning the vehicle speed when the vehicle has traveled in a low vehicle speed range of a predetermined vehicle speed or less in the past; calculating a target vehicle speed during creep based on the learning result of the vehicle speed; determining the driving torque output when the accelerator is off based on the target vehicle speed during creep; a vehicle control method.

2. The vehicle control method according to claim 1, comprising: learning the vehicle speed when traveling in the low vehicle speed range in association with information on the driver who was driving the vehicle and / or information on the driving location where the vehicle was traveling; a vehicle control method.

3. The vehicle control method according to claim 2, comprising: the information on the driving location includes: parameters indicating the degree of congestion and / or the size at the driving location; a vehicle control method.

4. The vehicle control method according to claim 1, comprising: when controlling the vehicle according to the target vehicle speed during creep determined based on the learning result of the vehicle speed, determining whether a correction operation for correcting the driving force and / or the braking force by the driver has been executed; performing re-learning according to the result of the determination of the execution of the correction operation; a vehicle control method.

5. The vehicle control method according to claim 4, comprising: acquiring the surrounding environment of the vehicle; determining whether there is an obstacle within a predetermined distance range from the vehicle with reference to the surrounding environment; judging the necessity of the re-learning based on the determination result of whether the obstacle exists; a vehicle control method.

6. The vehicle control method according to claim 1, comprising: in addition to the vehicle speed when traveling in the low vehicle speed range, learning the acceleration and the jerk; calculating a target vehicle speed during creep, a target acceleration during creep, and a target jerk during creep based on the learning results of the vehicle speed, the acceleration, and the jerk; determining the driving torque output when the accelerator is off based on the target vehicle speed during creep, the target acceleration during creep, and the target jerk during creep; a vehicle control method.

7. A vehicle control device for controlling a vehicle that outputs driving torque when the driver releases the accelerator, comprising: a vehicle speed learning unit that learns the vehicle speed when the vehicle has traveled in a low vehicle speed range of a predetermined vehicle speed or less in the past; a target vehicle speed calculation unit that calculates a target vehicle speed during creep based on the learning result of the vehicle speed; a driving torque setting unit that determines the driving torque output when the accelerator is off based on the target vehicle speed during creep; Vehicle control device.

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