Vehicle driving assistance device

Abstract

To provide a vehicle driving support device capable of generating proper braking force even in the case that stepping-in timing of a brake pedal of a driver is late during execution of a manual driving mode.SOLUTION: A travel_ECU 14 acquires a brake fluid pressure characteristic learning value on the basis of a brake fluid pressure generated from a braking start to a braking end by brake operation when a driver performs the brake operation at timing when a collision prediction time TTC between an own vehicle M and a brake object Trg is equal to or more than a threshold TTCx_range to the brake object Trg in front recognized on the basis of travel environment information, and compensates a brake fluid pressure generated from a braking start to a matching end by brake operation when the driver starts the brake operation at timing when the collision prediction time TTC is less than the threshold TTCX_range.SELECTED DRAWING: Figure 5

Description

[Technical Field]

[0001] The present invention relates to a driving assistance device for a vehicle that is capable of performing braking control against an obstacle such as a preceding vehicle. [Background technology]

[0002] In recent years, driving assistance devices for assisting a driver in driving operations have been put into practical use in vehicles such as automobiles, with the aim of reducing the burden of driving operations on the driver and improving safety. This type of driving assistance device has set driving modes, such as a manual driving mode in which steering and acceleration / deceleration are performed according to the driver's proactive driving operations, a driving assistance mode in which steering assistance control and acceleration / deceleration control are performed on the premise that the driver actively drives the vehicle, and a driving assistance mode (so-called automatic driving mode) in which the vehicle runs without the need for driver's driving operations.

[0003] The driving assistance control in each driving assistance mode is basically realized by providing an adaptive cruise control (ACC) function, an active lane keep centering control (ALKC) function, etc. Such driving assistance control enables the vehicle to automatically travel along the driving lane while maintaining a distance from the vehicle ahead.

[0004] Additionally, as a technology related to active safety for driving assistance devices, a technology has been put into practical use in which, when an obstacle requiring an emergency stop, such as a vehicle or pedestrian, is recognized ahead of the vehicle in each driving mode, emergency braking (AEB (Autonomous Emergency Braking)) control is performed against the obstacle as an interruption control, and the vehicle decelerates until the relative speed between the vehicle and the obstacle becomes zero.

[0005] Furthermore, with regard to brake control, as a technology for promoting safe driving even in the pre-active safety stage, for example, Patent Document 1 discloses a technology in which the brake start TTC is recorded for each driver based on input from a driver identification unit, a vehicle driving information acquisition unit, and a TTC calculation unit, a default TTC is learned and calculated for each driver based on the recorded default TTC, and vehicle control (braking control) is initiated by operating a vehicle control unit according to the control start TTC determined based on the default TTC. [Prior art documents] [Patent documents]

[0006] [Patent Document 1] Japanese Patent Application Laid-Open No. 2014-109989 Summary of the Invention [Problem to be solved by the invention]

[0007] However, when the technology disclosed in the above-mentioned Patent Document 1 is applied while the vehicle is in manual driving mode, braking may be initiated at a timing not intended by the driver, which may cause the driver to feel uncomfortable.

[0008] On the other hand, if the driver is distracted while in manual driving mode and delays the timing of depressing the brake pedal, the braking force may be insufficient, which may result in unintended intervention of emergency brake control.

[0009] The present invention has been made in consideration of the above circumstances, and aims to provide a vehicle driving assistance device that can generate appropriate braking force even if the driver delays pressing the brake pedal while the manual driving mode is being executed. [Means for solving the problem]

[0010] A driving assistance device for a vehicle according to one aspect of the present invention includes: a driving environment recognition means for recognizing driving environment information outside the vehicle;of the vehicle forward to Braking target When the vehicle is recognized as a target vehicle, and and calculating a collision prediction time based on the relative distance and relative speed of the vehicle, and if the collision prediction time at the time of starting the braking operation is equal to or greater than a preset threshold value, The braking force generated from the start of braking to the end of braking due to the brake operation Trends a braking force learning means for acquiring a braking force characteristic learning value based on the If the collision prediction time at the time when the brake operation is started is less than a preset threshold value, The braking force generated during the period from the start of braking to the end of braking The aforementioned When the braking force is less than the braking force of the braking force characteristic learned value ,before The above brake operation The aforementioned braking force shortage of to the braking force of the braking force characteristic learning value based on Completion do and braking force supplementary means. [Effects of the Invention]

[0011] According to the vehicle driving assistance device of the present invention, it is possible to generate an appropriate braking force even when the driver delays the depression of the brake pedal while the manual driving mode is being executed. [Brief explanation of the drawings]

[0012] [Figure 1] Overall configuration of the driving assistance device [Figure 2] An explanatory diagram showing the monitoring areas of the stereo camera, radar, and sonar. [Figure 3] Flowchart showing emergency brake control routine [Figure 4] A flowchart showing a routine for learning brake fluid pressure characteristics in response to a driver's brake operation. [Figure 5] Flowchart showing a braking force assist control routine [Figure 6] Flowchart showing brake fluid pressure control subroutine [Figure 7] FIG. 10 is an explanatory diagram showing the behavior of a vehicle when learning brake fluid pressure characteristics. [Figure 8] FIG. 10 is an explanatory diagram showing the behavior of a vehicle during braking force assist control. [Figure 9]Brake fluid pressure, ideal brake fluid pressure, and brake fluid pressure learning value [Figure 10] Brake fluid pressure, ideal brake fluid pressure, and brake fluid pressure learning value DETAILED DESCRIPTION OF THE INVENTION

[0013] DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS The following describes embodiments of the present invention with reference to the drawings. The drawings relate to one embodiment of the present invention, and Fig. 1 is a diagram showing the overall configuration of a driving assistance device.

[0014] As shown in FIG. 1, the driving assistance device 1 includes a camera unit 10 fixed to the center of the upper front part of the interior of a vehicle (host vehicle) M, for example.

[0015] The camera unit 10 includes a stereo camera 11, an image processing unit (IPU) 12, an image recognition unit (image recognition_ECU) 13, and a driving control unit (driving_ECU) 14.

[0016] The stereo camera 11 has a main camera 11a and a sub-camera 11b. The main camera 11a and the sub-camera 11b are arranged, for example, at symmetrical positions with respect to the center in the vehicle width direction. The main camera 11a and the sub-camera 11b are configured, for example, with CMOS or the like, and capture stereo images of the driving environment in an area Af (see FIG. 2) outside the vehicle from different viewpoints at a predetermined imaging period that is synchronized with each other.

[0017] The IPU 12 performs predetermined image processing on the driving environment images captured by the stereo camera 11 to detect the edges of various objects such as three-dimensional objects and road markings displayed on the images. The IPU 12 then calculates distance information from the positional deviation of corresponding edges on the left and right images, and generates image information including the distance information (distance image information).

[0018] Based on distance image information received from the IPU 12, the image recognition_ECU 13 calculates the road curvature [1 / m] of the marking lines dividing the left and right sides of the roadway on which the vehicle M is traveling (the host vehicle roadway) and the width between the left and right marking lines (lane width). Various methods are known for calculating the road curvature and lane width. For example, the image recognition_ECU 13 recognizes the left and right marking lines by binarizing the road curvature based on the driving environment information using brightness differences, and calculates the curvatures of the left and right marking lines for each predetermined section using a curve approximation formula based on the least squares method. Furthermore, the image recognition_ECU 13 calculates the lane width from the difference in curvature between the left and right marking lines.

[0019] Then, the image recognition_ECU 13 calculates the lane center, the lateral position deviation of the vehicle M, which is the distance from the lane center to the center of the vehicle M in the vehicle width direction, etc. based on the curvature of the left and right lane markings and the lane width.

[0020] Furthermore, the image recognition_ECU 13 performs predetermined pattern matching on the distance image information to recognize three-dimensional objects such as guardrails extending along the road, curbs, and surrounding vehicles. Here, when recognizing three-dimensional objects in the image recognition_ECU 13, for example, the type of the three-dimensional object, the height of the three-dimensional object, the distance to the three-dimensional object, the speed of the three-dimensional object, and the relative speed Vrel between the three-dimensional object and the host vehicle M are recognized.

[0021] The various pieces of information recognized by the image recognition_ECU 13 are output to the traveling_ECU 14 as traveling environment information.

[0022] In this manner, in this embodiment, the image recognition_ECU 13, together with the stereo camera 11 and the IPU 12, realizes the function of a driving environment recognition unit that recognizes driving environment information outside the vehicle.

[0023] The traveling_ECU 14 is a control unit for controlling the driving assistance device 1 in an integrated manner.

[0024] This traveling_ECU 14 is connected to various control units, such as a cockpit control unit (CP_ECU) 21, an engine control unit (E / G_ECU) 22, a transmission control unit (T / M_ECU) 23, a brake control unit (BK_ECU) 24, and a power steering control unit (PS_ECU) 25, via an in-vehicle communication line such as a CAN (Controller Area Network).

[0025] Furthermore, various sensors, such as a locator unit 36, a left front side sensor 37lf, a right front side sensor 37rf, a left rear side sensor 37lf, a right rear side sensor 37rr, and a rear sensor 38, are connected to the travel_ECU 14.

[0026] A human-machine interface (HMI) 31 disposed near the driver's seat is connected to the CP_ECU 21. The HMI 31 includes, for example, a switch for issuing an instruction to execute various driving assistance controls, a mode selector switch for switching driving assistance modes, a steering touch sensor for detecting the driver's steering state, a driver monitoring system (DMS) for detecting the driver's facial recognition and line of sight, a touch panel display, a combination meter, a speaker, and the like.

[0027] When the CP_ECU 21 receives a control signal from the travel_ECU 14, it notifies the driver of various types of information, such as various warnings for preceding vehicles, the implementation status of driving assistance control, and the driving environment of the host vehicle M, as appropriate, by displaying, audibly, or the like via the HMI 31. In addition, the CP_ECU 25 outputs to the travel_ECU 14 various types of input information, such as the on / off operation status of various driving assistance controls, input by the driver via the HMI 31.

[0028] The output side of the E / G_ECU 22 is connected to a throttle actuator 32 of an electronically controlled throttle, etc. The input side of the E / G_ECU 22 is connected to various sensors such as an accelerator sensor (not shown).

[0029] The E / G_ECU 22 controls the operation of the throttle actuator 32 based on a control signal from the travel_ECU 14 or detection signals from various sensors. In this way, the E / G_ECU 22 adjusts the amount of intake air into the engine to generate a desired engine output. The E / G_ECU 22 also outputs signals such as the accelerator opening detected by the various sensors to the travel_ECU 14.

[0030] An output side of the T / M_ECU 23 is connected to a hydraulic control circuit 33. Furthermore, various sensors such as a shift position sensor (not shown) are connected to an input side of the T / M_ECU 23. The T / M_ECU 23 performs hydraulic control for the hydraulic control circuit 33 based on an engine torque signal estimated by the E / G_ECU 22 and detection signals from various sensors. As a result, the T / M_ECU 23 operates friction engagement elements, pulleys, and the like provided in the automatic transmission, and shifts the engine output at a desired gear ratio. Furthermore, the T / M_ECU 23 outputs signals such as the shift position detected by the various sensors to the travel_ECU 14.

[0031] A brake actuator 34 for adjusting the brake fluid pressure output to the brake wheel cylinders provided on the respective wheels is connected to the output side of the BK_ECU 24. In addition, various sensors such as a brake pedal sensor, a yaw rate sensor, a longitudinal acceleration sensor, and a vehicle speed sensor (not shown) are connected to the input side of the BK_ECU 24.

[0032] The BK_ECU 24 performs drive control on the brake actuator 34 based on control signals from the travel_ECU 14 or detection signals from various sensors. As a result, the BK_ECU 24 appropriately generates braking force on each wheel to perform forced braking control, yaw rate control, etc. on the host vehicle M. In addition, the BK_ECU 24 outputs signals of the brake operation state, yaw rate, longitudinal acceleration, vehicle speed (host vehicle speed), etc. detected by the various sensors to the travel_ECU 14.

[0033] An electric power steering motor 35, which applies steering torque to the steering mechanism by the rotational force of the motor, is connected to the output side of the PS_ECU 25. In addition, various sensors such as a steering torque sensor and a steering angle sensor are connected to the input side of the PS_ECU 25.

[0034] The PS_ECU 25 controls the drive of the electric power steering motor 35 based on control signals from the travel_ECU 14 or detection signals from various sensors. As a result, the PS_ECU 25 generates a steering torque for the steering mechanism. The PS_ECU 25 also outputs signals of the steering torque, steering angle, etc. detected by the various sensors to the travel_ECU 14.

[0035] The locator unit 36 ​​includes a GNSS sensor 36a and a high-precision road map database (road map DB) 36b.

[0036] The GNSS sensor 36a receives positioning signals transmitted from a plurality of positioning satellites to determine the position (latitude, longitude, altitude, etc.) of the vehicle M.

[0037] The road map DB 36b is a large-capacity storage medium such as an HDD, and stores high-precision road map information (dynamic map). This road map DB 36b stores lane data required for autonomous driving, such as lane width data, lane center position coordinate data, lane travel azimuth data, and speed limits. This lane data is stored at intervals of several meters for each lane on the road map. The road map DB also stores information on various facilities, parking lots, and the like. For example, based on a request signal from the traveling_ECU 14, the road map DB 36b outputs road map information for a set range based on the vehicle position measured by the GNSS sensor 36a to the traveling_ECU 14 as traveling environment information.

[0038] In this manner, in this embodiment, the road map DB 36b, together with the GNSS sensor 36a, functions as a driving environment recognition means for recognizing driving environment information outside the vehicle.

[0039] The left front side sensor 37lf and the right front side sensor 37rf are configured by, for example, millimeter-wave radars. These left front side sensor 37lf and right front side sensor 37rf are disposed, for example, on the left and right sides of the front bumper, respectively. The left front side sensor 37lf and the right front side sensor 37rf detect, as driving environment information, three-dimensional objects present in areas Alf, Arf (see FIG. 2) diagonally forward and to the left and right of the vehicle M, which are difficult to recognize in the image from the stereo camera 11.

[0040] The left rear side sensor 37lr and the right rear side sensor 37rr are configured, for example, by millimeter-wave radar. The left rear side sensor 37lr and the right rear side sensor 37rr are disposed, for example, on the left and right sides of the rear bumper, respectively. The left rear side sensor 37lf and the right rear side sensor 37rf detect, as driving environment information, three-dimensional objects present in areas Alr, Arr (see FIG. 2) diagonally to the left and right sides and rear of the vehicle M that are difficult to recognize with the left front side sensor 37lf and the right front side sensor 37rf.

[0041] Here, the millimeter wave radar constituting each radar mainly detects three-dimensional objects such as adjacent vehicles by analyzing the waves reflected from the objects in response to the output radio waves. Specifically, each radar detects information about the three-dimensional object, such as the width of the three-dimensional object, the position of a representative point of the three-dimensional object (the relative position with respect to the vehicle M), and the speed.

[0042] In this manner, in this embodiment, the front side sensor 37lf, the right front side sensor 37rf, the left rear side sensor 37lr, and the right rear side sensor 37rr function as a driving environment recognition means for recognizing driving environment information outside the vehicle.

[0043] The rear sensor 38 is configured by, for example, a sonar. The rear sensor 38 is disposed, for example, on the rear bumper. The rear sensor 38 detects, as driving environment information, three-dimensional objects present in an area Ar (see FIG. 2) behind the vehicle M that are difficult to recognize with the left rear side sensor 37lr and the right rear side sensor 37rr.

[0044] In this way, in this embodiment, the rear sensor 38 functions as a driving environment recognition means that recognizes driving environment information outside the vehicle.

[0045] In addition, the coordinates of each object outside the vehicle included in the driving environment information recognized by the image recognition_ECU 13, the driving environment information recognized by the locator unit 36, the driving environment information recognized by the left front side sensor 37lf, the driving environment information recognized by the right front side sensor 37rf, the driving environment information recognized by the left rear side sensor 37lf, the driving environment information recognized by the right rear side sensor 37rr, and the driving environment information recognized by the rear sensor 38 are all converted by the driving_ECU 14 into coordinates of a three-dimensional coordinate system (see Figure 2) with the center of the vehicle M as the origin.

[0046] The driving modes set in the travel_ECU 14 include a manual driving mode, a first driving control mode and a second driving control mode for driving control, and an evacuation mode. These driving modes can be selectively switched in the travel_ECU 14 based on, for example, the operation status of a mode selector switch provided in the HMI 31.

[0047] Here, the manual driving mode is a driving mode that requires the driver to maintain steering, and is a driving mode in which the vehicle M is driven according to driving operations such as steering, accelerator, and brake operations by the driver.

[0048] Similarly, the first driving control mode is a driving mode that requires the driver to maintain steering. That is, the first driving control mode is a so-called semi-automatic driving mode in which the host vehicle M travels along a target driving route by appropriately combining mainly adaptive cruise control (ACC), active lane keep centering (ALKC), and active lane keep bouncing (ALKC) controls through control of the E / G_ECU 22, BK_ECU 24, PS_ECU 25, etc., while reflecting the driving operation by the driver.

[0049] Here, the control for following the preceding vehicle is basically performed based on the traveling environment information input from the image recognition_ECU 13. That is, the control for following the preceding vehicle is performed based on, for example, the preceding vehicle information included in the traveling environment information from the image recognition_ECU 13.

[0050] Furthermore, the lane centering control and lane departure prevention control are basically performed based on the driving environment information input from at least one of the image recognition_ECU 13 and the locator unit 36. That is, the lane centering control and the lane departure prevention control are performed based on, for example, lane marking information and the like included in the driving environment information from the image recognition_ECU 13 or the locator unit 36.

[0051] The second driving control mode is an autonomous driving mode in which the vehicle M is driven along a target route (route map information) without requiring the driver to maintain steering, operate the accelerator, or operate the brakes, and is mainly driven by an appropriate combination of preceding vehicle following control, lane centering control, and lane departure prevention control through control of, for example, the E / G_ECU22, BK_ECU24, PS_ECU25, etc.

[0052] The evacuation mode is a mode for automatically stopping the vehicle M on a roadside or the like, for example, when, while driving in the second driving control mode, driving in that mode cannot be continued and the driver is unable to take over driving operations (i.e., when it is not possible to transition to manual driving mode or the first driving control mode).

[0053] In addition, in each of the above-mentioned driving modes, the driving_ECU 14 appropriately performs emergency braking (AEB (Autonomous Emergency Braking): collision damage mitigation braking) control against obstacles such as preceding vehicles on the vehicle's driving path that are highly likely to collide with the vehicle M.

[0054] That is, based on driving environment information, the driving_ECU14 extracts, for example, three-dimensional objects such as preceding vehicles and stopped vehicles that are in front of the vehicle M on the vehicle's driving path, and three-dimensional objects such as bicycles and pedestrians that have entered in front of the vehicle M on the vehicle's driving path from the side of the road.

[0055] In addition, the travel_ECU14 determines the possibility of a collision with the vehicle M for each extracted three-dimensional object, and sets the three-dimensional object closest to the vehicle M among those determined to have a high possibility of collision with the vehicle M as the braking target Trg (obstacle) for emergency braking control.

[0056] Furthermore, the traveling_ECU 14 calculates a predicted time to collision TTC (=(relative distance from the braking object) / (relative speed from the braking object)) with respect to the braking object Trg.

[0057] When the collision prediction time TTC becomes equal to or less than a first threshold value Tth1 set in advance, the travel_ECU 14 issues a warning to the driver to urge him / her to avoid a collision with the braking target Trg. Note that the warning may include warning braking (gentle braking) using a preset deceleration a1, in addition to a warning by voice or display.

[0058] Also, if, due to this warning, the driver fails to perform an appropriate collision avoidance operation and the time to collision (TTC) becomes less than or equal to a preset second threshold value Tth2 (Tth2 < Tth1), the driving ECU 14 performs an emergency brake (strong brake) on the host vehicle M with respect to the braking target Trg using a preset deceleration a2 (a2 > a1).

[0059] These warning controls and emergency brake controls are not limited to, for example, the case where the driving mode is the first driving support mode and the second driving support mode, but are also applicable when the driving mode is the manual driving mode.

[0060] Furthermore, when the driving ECU 14 determines that it is difficult to avoid a collision with an obstacle by the emergency brake control, it is also possible to perform an emergency steering control for avoiding a collision with the obstacle instead of or in combination with the emergency brake control.

[0061] Furthermore, when the manual driving mode is selected, the driving ECU 14 performs braking force assist control (braking force complementary control) to ensure safety even when the driver's braking operation for the front braking target Trg is delayed due to inattention such as looking away. This braking force assist control is realized, for example, by complementing the brake hydraulic pressure generated by the brake actuator 34 when the driver depresses the brake pedal.

[0062] Here, the braking force assist control is a control on the premise of fully respecting the driver's main driving operation in the manual driving mode. Therefore, the driving ECU 14 appropriately performs the assist control of the brake hydraulic pressure only when the driver performs a braking operation in the manual driving mode.

[0063] Note that when the manual driving mode is selected and the driver does not perform a braking operation on the front obstacle and there is a possibility that the host vehicle M will collide with the front obstacle, the above-described emergency brake control is forcibly intervened.

[0064] Prior to the assist control of the brake fluid pressure, when the driver applies the brakes at an appropriate timing to a forward obstacle (braking target Trg) recognized based on the driving environment information, the traveling_ECU 14 acquires a braking force characteristic learned value resulting from the brake operation. Specifically, when the driver starts the brake operation before a timing preset according to the relative relationship between the host vehicle M and the braking target Trg, the traveling_ECU 14 acquires, as braking force characteristic learned values, a learned value of the brake fluid pressure characteristic (brake fluid pressure characteristic learned value) and a learned value of the jerk characteristic of the brake fluid pressure (jerk characteristic learned value) based on the transition of the brake fluid pressure from the start of braking to the end of braking due to the brake operation.

[0065] Here, the driving_ECU14 determines that the driver performed the brake operation at the appropriate timing, for example, when the predicted time TTC of collision with the object when the driver starts the brake operation is greater than a predetermined threshold TTCx_range (TTCx_range>Tth1).

[0066] The travel_ECU 14 may be configured to, for example, determine the vehicle M at the timing when the driver starts braking. Braking target Trg It is desirable to acquire a brake characteristic learning value for each range of the relative speed Vrel with respect to the vehicle. In addition, it is desirable for the travel_ECU 14 to acquire a brake fluid pressure characteristic learning value and a jerk characteristic learning value for each driver whose face has been authenticated by the driver monitoring system of the HMI 31, for example.

[0067] When the driver starts braking after the appropriate timing, the traveling_ECU 14 complements the brake fluid pressure generated by the braking operation from the start to the end of braking based on the brake fluid pressure characteristic learned value. That is, in the manual driving mode, even if the timing of the braking operation is delayed due to the driver looking away, the traveling_ECU 14 complements the brake fluid pressure on the assumption that the driver has performed the braking operation.

[0068] Here, it is desirable to keep this brake fluid pressure supplementation to a minimum necessary to respect the driver's intention. For this reason, the travel_ECU 14 stores an ideal brake fluid pressure characteristic (ideal braking force characteristic) as an ideal braking force characteristic that is set in advance based on experiments, simulations, etc. Then, the travel_ECU 14 determines whether the ideal brake fluid pressure characteristic is greater than the brake fluid pressure characteristic learned value. Also low When the brake fluid pressure is not sufficient, the brake fluid pressure is supplemented with the brake fluid pressure characteristic learning value. Brake fluid pressure with ideal brake fluid pressure characteristics This is based on the following.

[0069] In addition, this ideal brake fluid pressure characteristic is also determined based on the predetermined vehicle M. Braking target Trg It is desirable that the relative speed Vrel is set for each range of the relative speed Vrel.

[0070] In this manner, in this embodiment, the travel_ECU 14 realizes the functions of braking force learning means, braking force complementing means, and storage means.

[0071] Next, the emergency brake control executed by the travel_ECU 14 will be described with reference to the flowchart of the emergency brake control routine shown in Fig. 3. This routine is repeatedly executed at set time intervals.

[0072] When the routine starts, the travel_ECU 14 sets a braking target Trg for emergency brake control based on the driving environment information. That is, for example, when there are three-dimensional objects, such as a preceding vehicle or a stopped vehicle, which are likely to collide with the host vehicle M, and three-dimensional objects, such as a bicycle or a pedestrian, which are likely to collide with the host vehicle M, ahead of the host vehicle M on the vehicle driving path, the travel_ECU 14 sets the three-dimensional object that is closest to the host vehicle M among these three-dimensional objects as a braking target Trg for emergency brake control.

[0073] In the following step S102, the traveling_ECU 14 checks whether or not a braking target Trg is set ahead on the traveling path of the host vehicle.

[0074] Then, in step S102, if it is determined that no braking target Trg is set ahead on the roadway of the host vehicle, the traveling_ECU 14 exits the routine.

[0075] On the other hand, if it is determined in step S102 that a braking target Trg is set ahead on the vehicle's driving path, the driving_ECU14 proceeds to step S103 and checks whether the collision prediction time TTC for the braking target Trg is less than or equal to a predetermined first threshold value Tth1.

[0076] Then, in step S103, if it is determined that the collision prediction time TTC is greater than the first threshold value, the traveling_ECU 14 exits the routine.

[0077] On the other hand, if it is determined in step S103 that the collision prediction time TTC is equal to or less than the first threshold, the traveling_ECU 14 proceeds to step S104 and checks whether the collision prediction time TTC is equal to or less than a preset second threshold Tth2.

[0078] Then, in step S104, if it is determined that the collision prediction time TTC is greater than the second threshold, the travel_ECU 14 proceeds to step S105, issues a warning for the braking target Trg through the CP_ECU 21, BK_ECU 24, etc., and then exits the routine.

[0079] On the other hand, if it is determined in step S104 that the collision prediction time TTC is equal to or less than the second threshold value Tth2, the traveling_ECU 14 proceeds to step S106, executes emergency braking on the braking target Trg via the BK_ECU 24 etc., and then exits the routine.

[0080] Next, learning of the brake fluid pressure characteristics in response to the brake operation by the driver, which is executed in the travel_ECU 14, will be described with reference to the flowchart showing the learning routine for the brake fluid pressure characteristics shown in Fig. 4. This routine is repeatedly executed at set time intervals.

[0081] When the routine starts, the traveling_ECU 14 checks in step S201 whether the current driving mode is the manual driving mode.

[0082] Then, in step S201, if it is determined that the current driving mode is other than the manual driving mode, the traveling_ECU 14 exits the routine.

[0083] On the other hand, if it is determined in step S201 that the current driving mode is manual driving mode, the driving_ECU14 proceeds to step S202 and recognizes the driver driving the vehicle M based on information from a driver monitoring system or the like provided in the HMI31.

[0084] In the following step S203, the traveling_ECU 14 checks whether or not the driver has started to apply the brakes, based on information from the brake pedal sensor or the like.

[0085] Then, in step S203, if it is determined that the driver has not started braking, the traveling_ECU 14 exits the routine.

[0086] On the other hand, if it is determined in step S203 that the driver has started a braking operation, the travel_ECU 14 proceeds to step S204 and determines a braking target Trg for the braking operation performed by the driver. That is, for example, based on the driving environment information, the travel_ECU 14 extracts three-dimensional objects, such as preceding vehicles and stopped vehicles, that exist ahead of the host vehicle M on the host vehicle driving path, and three-dimensional objects, such as bicycles and pedestrians that have come out from the side of the road. The travel_ECU 14 also determines the possibility of a collision with the host vehicle M for each of the extracted three-dimensional objects, and sets the three-dimensional object that is closest to the host vehicle M among the three-dimensional objects that it has determined to have a high possibility of colliding with the host vehicle M as a braking target Trg for the braking operation performed by the driver.

[0087] In the following step S205, the traveling_ECU 14 determines whether or not the travel_ECU 14 has performed the above-described step S204. Braking target TrgIf set, Braking target Trg The predicted collision time TTC is obtained when the driver starts braking.

[0088] In the following step S206, the travel_ECU 14 checks whether the collision prediction time TTC at the start of the braking operation is equal to or greater than a preset threshold value TTCx_range.

[0089] Then, in step S206, if it is determined that the collision prediction time TTC at the start of braking is less than the threshold value TTCx_range, the travel_ECU 14 exits the routine.

[0090] On the other hand, if it is determined in step S206 that the collision prediction time TTC at the start of braking is equal to or greater than the threshold TTCx_range (see FIG. 7), the travel_ECU 14 proceeds to step S207 and checks whether the driver's braking operation has been released.

[0091] Then, in step S207, if it is determined that the brake operation by the driver has been released, the traveling_ECU 14 exits the routine as is.

[0092] On the other hand, if it is determined in step S207 that the brake operation by the driver has not been released, the current brake fluid pressure and the jerk of the brake fluid pressure (fluid pressure jerk) are acquired as the brake fluid pressure characteristics by the driver.

[0093] In the following step S209, the travel_ECU 14 Braking target Trg It is checked whether the relative velocity Vrel with respect to the object has become "0".

[0094] Then, in step S209, if it is determined that the relative speed Vrel is not "0", the traveling_ECU 14 returns to step S207.

[0095] On the other hand, if it is determined in step S209 that the relative speed Vrel has become "0", the travel_ECU 14 proceeds to step S210, where it reflects the brake fluid pressure and fluid pressure jerk acquired from the start of braking to the end of braking in the brake fluid pressure characteristic learned value and fluid pressure jerk characteristic learned value, and then exits the routine.

[0096] Next, the braking force assist control executed by the travel_ECU 14 will be described with reference to a braking force assist control routine shown in Fig. 5. This routine is repeatedly executed at set time intervals.

[0097] When the routine starts, the driving_ECU 14 checks in step S301 whether the current driving mode is the manual driving mode.

[0098] Then, in step S301, if it is determined that the current driving mode is other than the manual driving mode, the traveling_ECU 14 exits the routine.

[0099] On the other hand, if it is determined in step S301 that the current driving mode is manual driving mode, the driving_ECU14 proceeds to step S302 and recognizes the driver driving the vehicle M based on information from a driver monitoring system or the like provided in the HMI31.

[0100] In the following step S303, the traveling_ECU 14 checks whether or not the driver has started to apply the brakes, based on information from the brake pedal sensor or the like.

[0101] Then, in step S303, if it is determined that the driver has not started braking, the traveling_ECU 14 exits the routine.

[0102] On the other hand, if it is determined in step S303 that the driver has started a braking operation, the travel_ECU 14 proceeds to step S304 and determines a braking target Trg for the braking operation performed by the driver. That is, for example, the travel_ECU 14 extracts, based on the driving environment information, three-dimensional objects such as preceding vehicles and stopped vehicles present ahead of the host vehicle M on the host vehicle driving path, and three-dimensional objects such as bicycles and pedestrians that have come out from the side of the road. The travel_ECU 14 also determines the possibility of a collision with the host vehicle M for each of the extracted three-dimensional objects, and sets the three-dimensional object closest to the host vehicle M among the three-dimensional objects determined to have a high possibility of collision with the host vehicle M as a braking target Trg for the driver's braking operation.

[0103] In the following step S305, the traveling_ECU 14 determines whether the Braking target Trg If set, Braking target Trg The predicted collision time TTC is obtained when the driver starts braking.

[0104] In the following step S306, the travel_ECU 14 checks whether the collision prediction time TTC at the start of the braking operation is less than a preset threshold value TTCx_range.

[0105] Then, in step S306, if it is determined that the collision prediction time TTC is equal to or greater than the threshold value TTCx_range, the travel_ECU 14 exits the routine.

[0106] On the other hand, if it is determined in step S306 that the collision prediction time TTC is less than the threshold value TTCx_range (see FIG. 8), the travel_ECU 14 proceeds to step S307 and checks whether the brake fluid pressure characteristic learning value corresponding to the relative speed Vrel at the time of braking start is greater than the current brake fluid pressure.

[0107] Then, if it is determined in step S307 that the brake fluid pressure characteristic learned value is equal to or less than the current brake fluid pressure, the traveling_ECU 14 proceeds to step S310.

[0108] On the other hand, if it is determined in step S307 that the brake fluid pressure characteristic learning value is greater than the current brake fluid pressure, the traveling_ECU 14 proceeds to step S308 and checks whether the fluid pressure jerk characteristic learning value corresponding to the relative speed Vrel at the time of braking start is greater than the current fluid pressure jerk.

[0109] If it is determined in step S308 that the hydraulic pressure jerk characteristic learned value is equal to or less than the current hydraulic pressure jerk, the travel_ECU 14 determines that the driver intends to increase the braking force, and proceeds to step S310.

[0110] On the other hand, if it is determined in step S308 that the hydraulic pressure jerk characteristic learned value is greater than the current hydraulic pressure jerk, the traveling_ECU 14 proceeds to step S309 and performs brake hydraulic pressure control.

[0111] This brake fluid pressure control is performed, for example, in accordance with the flowchart of a brake fluid pressure control subroutine shown in FIG.

[0112] When the subroutine starts, in step S401, the traveling_ECU 14 checks whether the brake fluid pressure of the ideal brake fluid pressure characteristic corresponding to the current relative speed Vrel between the vehicle M and the braking target Trg is greater than the brake fluid pressure of the brake fluid pressure characteristic learning value.

[0113] Then, in step S401, if it is determined that the brake fluid pressure of the ideal brake fluid pressure characteristic is greater than the brake fluid pressure of the brake fluid pressure characteristic learning value (see FIG. 10), the traveling_ECU 14 proceeds to step S402, sets the brake fluid pressure of the brake fluid pressure characteristic learning value as the reference brake fluid pressure, and then proceeds to step S404.

[0114] On the other hand, if it is determined in step S401 that the brake fluid pressure of the ideal brake fluid pressure characteristics is equal to or lower than the brake fluid pressure of the brake fluid pressure characteristics learning value (see FIG. 9), the traveling_ECU 14 proceeds to step S403, sets the brake fluid pressure of the ideal brake fluid pressure characteristics as the reference brake fluid pressure, and then proceeds to step S404.

[0115] When the process proceeds from step S402 or step S403 to step S404, the travel_ECU 14 checks whether the current brake fluid pressure is lower than the reference brake fluid pressure.

[0116] Then, in step S404, if it is determined that the current brake fluid pressure is equal to or greater than the reference brake fluid pressure, the travel_ECU 14 determines that a sufficient braking force is being generated, and exits the subroutine.

[0117] On the other hand, if it is determined in step S404 that the current brake fluid pressure is lower than the reference brake fluid pressure, the traveling_ECU 14 proceeds to step S405 and calculates a fluid pressure correction value ΔP (see Figures 9 and 10) for bringing the brake fluid pressure closer to the reference brake fluid pressure.

[0118] In the following step S406, the traveling_ECU 14 performs upper limit processing on the hydraulic pressure correction amount ΔP using a preset upper limit value.

[0119] In the following step S407, the travel_ECU 14 adds the upper limit processed hydraulic pressure correction amount ΔP to the current brake hydraulic pressure, and then exits the subroutine.

[0120] In the main routine of FIG. 5, when the process proceeds from step S307, step S308, or step S309 to step S310, the traveling_ECU 14 checks whether the collision prediction time TTC remains less than the threshold value TTCx_range.

[0121] If it is determined in step S310 that the collision prediction time TTC is equal to or greater than the threshold TTCx_range, it is determined that braking force assist control is no longer required, and the routine is terminated.

[0122] On the other hand, if it is determined in step S310 that the collision prediction time TTC remains below the threshold TTCx_range, the driving_ECU14 proceeds to step S311 and checks whether the relative speed Vrel between the host vehicle M and the braking target Trg has become "0".

[0123] Then, in step S311, if it is determined that the relative speed Vrel has become "0", the travel_ECU 14 determines that braking of the braking target Trg has ended, and exits the routine.

[0124] On the other hand, if it is determined in step S311 that the relative speed Vrel is greater than "0", the traveling_ECU 14 returns to step S307.

[0125] According to this embodiment, when the driver applies a brake to a front braking target Trg recognized based on the driving environment information at a timing when the predicted collision time TTC between the host vehicle M and the braking target Trg is equal to or greater than the threshold value TTCx_range, the travel_ECU 14 acquires a brake fluid pressure characteristic learning value based on the brake fluid pressure generated by the brake operation from the start of braking to the end of braking, and ... is less than the threshold value TTCX_range, braking The brake fluid pressure generated until the end of the manual driving mode is compensated for based on the brake fluid pressure characteristic learning value. This allows appropriate braking force to be generated even if the driver delays the brake pedal depression timing while in manual driving mode.

[0126] In other words, even if the driver presses the brake pedal late, the timing at which braking of the braking target is initiated is left to the driver, and the lack of brake fluid pressure (lack of braking force) caused by the delay in pressing the brake pedal can be compensated for, thereby generating an appropriate braking force that matches the driver's feeling.

[0127] Furthermore, the brake fluid pressure (braking force) is complemented based on the brake fluid pressure characteristic learning value obtained based on the driver's brake operation, so that complementation that matches the driver's feeling can be performed.

[0128] In this case, the travel_ECU 14 has a preset ideal brake fluid pressure characteristic (ideal braking force characteristic) as the ideal brake fluid pressure characteristic (braking force characteristic) from the start of braking to the end of braking, and when the ideal brake fluid pressure characteristic is relatively lower than the learned brake fluid pressure characteristic value, the travel_ECU 14 supplements the brake fluid pressure based on the ideal brake fluid pressure characteristic. This prevents excessive brake fluid pressure supplementation and allows the supplementation of the brake fluid pressure to be kept to the minimum necessary.

[0129] 9 and 10, the travel_ECU 14 does not supplement the brake fluid pressure after the current brake fluid pressure exceeds the brake fluid pressure characteristic learned value or the ideal brake fluid pressure characteristic. Therefore, the brake fluid pressure can be supplemented while leaving room for the driver to apply more pressure through a proactive brake operation.

[0130] In the above-described embodiment, the IPU 12, image recognition_ECU 13, driving_ECU 14, CP_ECU 21, E / G_ECU 22, T / M_ECU 23, BK_ECU 24, and PS_ECU 25 are configured by well-known microcomputers equipped with a CPU, RAM, ROM, non-volatile storage, etc., and their peripheral devices, and the ROM stores programs to be executed by the CPU and fixed data such as data tables in advance. Note that all or part of the functions of the processor may be configured by logic circuits or analog circuits, and the processing of various programs may be realized by electronic circuits such as FPGAs.

[0131] The invention described in the above embodiments is not limited to those embodiments, and various modifications can be made in the implementation stage without departing from the gist of the invention. Furthermore, the above embodiments include inventions at various stages, and various inventions can be extracted by appropriate combinations of the disclosed multiple constituent elements.

[0132] For example, in the above embodiment, an example in which the driving assistance device 1 is applied to an engine vehicle that runs using the driving force of the engine has been described, but the present invention is not limited to this. For example, the driving assistance device 1 can also be applied to a hybrid vehicle, an electric vehicle, or the like. In this case, the traveling_ECU 14 can acquire, as the braking force characteristic learned value, a brake fluid pressure characteristic learned value and a fluid pressure jerk characteristic learned value, as well as a regenerative torque characteristic learned value and a regenerative torque jerk characteristic learned value. Furthermore, with regard to braking force complementation, in addition to complementation using brake fluid pressure, complementation using regenerative torque can also be performed.

[0133] Furthermore, if the stated problem can be solved and the stated effect can be obtained even if some of the constituent elements are deleted from all the constituent elements shown in the embodiment, the configuration from which these constituent elements are deleted can be extracted as an invention. [Explanation of symbols]

[0134] 1. Driving assistance devices 10...Camera unit 11...Stereo camera 11a ... Main camera 11b ... Sub camera 13...Image Recognition_ECU 14 … Driving_ECU 21 … CP_ECU 22 ... E / G_ECU 23 ... Transmission ECU 24 … BK_ECU 25 … PS_ECU 31...HMI 32 ... Throttle actuator 33... Hydraulic control circuit 34... Brake actuator 35... Electric power steering motor 36 ... Locator unit 36a … GNSS sensor 36b ... Road map DB 37lf ... Left front side sensor 37rf ... Right front side sensor 37lr ... Left rear side sensor 37rr ... Right rear side sensor 38 ... Rear sensor Af … area Alf, Arf … area Alr, Arr… area Ar … area

Claims

1. a driving environment recognition means for recognizing driving environment information outside the vehicle; a braking force learning means for calculating a collision prediction time based on a relative distance and a relative speed between the host vehicle and the braking object when the host vehicle recognizes a braking object in front of the host vehicle based on the driving environment information, and for acquiring a braking force characteristic learning value based on a transition of the braking force generated by the braking operation from the start to the end of braking when the collision prediction time is equal to or greater than a predetermined threshold value at the time when the host vehicle starts braking; and braking force supplementation means for supplementing the insufficient braking force generated by the brake operation based on the braking force of the braking force characteristic learning value when the collision prediction time at the time the brake operation is started is less than a predetermined threshold value and the braking force generated from the start to end of braking is less than the braking force of the braking force characteristic learning value.

2. 2. The vehicle driving assistance device according to claim 1, wherein the braking force characteristic learned value is acquired for each driver.

3. 3. The vehicle driving assistance device according to claim 1, wherein the braking force characteristic learned value is acquired for each range of the relative speed between the host vehicle and the object to be braked at the timing when the brake operation is started.

4. a storage means for storing a braking force of a preset ideal braking force characteristic as an ideal braking force characteristic from the start of braking to the end of braking; 4. The vehicle driving assistance device according to claim 1, wherein when the braking force generated by the brake operation is lower than the braking force of the ideal braking force characteristic and the braking force of the ideal braking force characteristic is lower than the braking force of the braking force characteristic learned value, the braking force complementing means complements the shortage of braking force generated by the brake operation based on the braking force of the ideal braking force characteristic instead of the braking force of the braking force characteristic learned value.

5. 5. The vehicle driving assistance device according to claim 4, wherein the ideal braking force characteristic is set for each of a predetermined range of the relative speed between the host vehicle and the object to be braked.

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