VEHICLE CONTROL DEVICE

Abstract

Vehicle driving control device (10) which controls the driving of a vehicle (1), comprising: a sensor (20) configured to detect a driving state of the vehicle (1); and a control device (100) configured to perform a curve following control which generates a target curve (TR) and controls the movement of the vehicle (1) so that the vehicle (1) follows the target curve (TR), wherein A delay time (DL) is a time that represents a control delay of the curve tracking control, a delay compensation time (L) is at least a part of the delay time (DL), which features curve tracking control: an information acquisition processing system that obtains sensor-acquired information (SEN) that indicates a result of the acquisition by the sensor (20); a displacement estimation processing that estimates a displacement of the vehicle (1) in the deceleration compensation time (L) based on the sensor-acquired information (SEN); a delay compensation processing that corrects a deviation (Ed, θd) between the vehicle (1) and the target curve (TR) based on the estimated displacement to compensate for the control delay; and a vehicle control processing system which controls the vehicle's (1) movement in such a way that the deviation (Ed, θd) is reduced after the delay compensation processing, the control device (100) is further configured to determine an effective period (PA) in which the displacement estimation processing is effective and an ineffective period (PB) in which the displacement estimation processing is ineffective, based on a state of the sensor (20) and / or the sensor-detected information (SEN), if the ineffective period (PB) is included in the delay time (DL) of the curve tracking control, the control device (100) performs the displacement estimation processing in a temporary mode, and the control device (100) in the temporary mode performs the displacement estimation processing by using at least the sensor-detected information (SEN) in the effective period (PA), without using the sensor-detected information (SEN) in the ineffective period (PB).

Description

Technical field

[0001] The present disclosure relates to a vehicle driving control device which controls the driving of a vehicle in order to follow a target curve. State of the art

[0002] A curve-following control system, which regulates a vehicle's movement to follow a target curve, is known. In this type of control system, a control delay can occur due to various causes. These causes include computational processing time, information communication time, and so on. For example, calculating the target curve requires a certain amount of time, so this calculation time leads to the control delay. The control delay, in turn, reduces the vehicle's ability to follow the target curve.

[0003] From DE 11 2007 002 946 B4, a vehicle control device is known in which a target path is calculated based on a dynamic vehicle model. Based on this target path, the vehicle control device determines a steering angle for the vehicle to improve its tracking ability. For this purpose, the vehicle control device compares the current vehicle state with a modeled target state and controls the steering angle so that the deviation between the target path and the actual vehicle movement is minimized.

[0004] JP 2018 - 24 295 A and US 2018 / 0 043 934 A1 disclose a driver assistance system designed to eliminate time delays in acquiring a vehicle's driving state in order to execute stable vehicle control. Specifically, the driver assistance system acquires an image of a lane boundary (track boundary) and generates a target curve based on this image. Furthermore, the driver assistance system acquires the vehicle's lateral position within the lane based on the acquired image. The driver assistance system then executes the curve tracking control based on the target curve and the vehicle's lateral position.

[0005] Obtaining the vehicle's lateral position takes time, both to generate and process image data. To compensate for this time delay, the driver assistance system corrects the lateral position obtained from the image. Specifically, the system uses a yaw rate and vehicle speed, detected by sensors, to estimate the vehicle's lateral displacement over a period equal to the time delay. The system then adds this estimated displacement to the lateral position to correct it. Summary

[0006] According to the technique disclosed in the previously described JP 2018 - 24 295 A, a delay compensation processing is performed which compensates for the control delay of the curve following control. For this purpose, the displacement of the vehicle in the period corresponding to the control delay is estimated by using the driving state detected by the sensor.

[0007] However, if the sensor fails, the detected driving condition becomes erroneous. The displacement estimated based on the erroneous driving condition becomes an anomalous value that does not reflect the actual vehicle movement. Consequently, the deceleration compensation processing is executed without reflecting the actual vehicle movement, thus reducing the curve-following performance of the curve-following controller. Disabling the deceleration compensation processing might be considered. However, if the deceleration compensation processing is not executed at all, the curve-following performance of the curve-following controller will ultimately be reduced.

[0008] One objective of the present disclosure is to provide a technique that can prevent a decrease in the curve-following performance of the curve-following control.

[0009] One aspect focuses on a vehicle driving control device, which controls the movement of a vehicle.

[0010] The vehicle driving control device includes a sensor configured to detect the vehicle's driving state; and a control device configured to perform a curve-following control that generates a target curve and controls the vehicle's driving so that the vehicle follows the target curve. A delay time is the time representing a control delay of the curve-following control. A delay compensation time is at least a portion of the delay time.The curve tracking control includes an information gathering process that obtains sensor-acquired information indicating a result of the sensor's acquisition; a displacement estimation process that estimates a displacement of the vehicle during the delay compensation time based on the sensor-acquired information; a delay compensation process that corrects any deviation between the vehicle and the target curve based on the estimated displacement to compensate for the control delay; and a driving control process that controls the vehicle's driving so that the deviation decreases after the delay compensation processing.The control device is further configured to determine an effective period, during which displacement estimation processing is active, and an ineffective period (PB), during which displacement estimation processing is ineffective, based on at least one sensor state and the sensor-detected information. If the ineffective period is included in the delay time of the curve-tracking control, the control device performs the displacement estimation processing in a temporary mode. In temporary mode, the control device performs the displacement estimation processing using at least the sensor-detected information from the effective period, without using the sensor-detected information from the ineffective period.

[0011] A second aspect, in addition to the first, has the following characteristic: If both the effective period and the ineffective period are included in the delay time of the curve tracking control, the control device designates the effective period included in the delay time as the delay compensation time used in temporary mode.

[0012] A third aspect, in addition to the first, has the following characteristic. In temporary mode, the control device is configured to estimate the driving state in the ineffective period based on the sensor-acquired information in the ineffective period; to obtain estimated driving state information that specifies the estimated driving state; to set the delay time as the delay compensation time; and to perform the displacement estimation processing by using the sensor-acquired information in the effective period and the estimated driving state information in the ineffective period.

[0013] A fourth aspect, in addition to the second aspect, has the following feature: If the length of the effective period included in the delay time of the curve tracking control is less than a threshold, the control device is configured to estimate the driving state in the ineffective period based on the sensor-acquired information in the ineffective period; to obtain estimated driving state information that specifies the estimated driving state; to set the delay time as the delay compensation time; and to perform the displacement estimation processing using the sensor-acquired information in the effective period and the estimated driving state information in the ineffective period.

[0014] A fifth aspect, in addition to one of the first four aspects, has the following characteristic: If the ineffective period is not included in the delay time of the curve-following control, the control device performs the displacement estimation processing in a normal mode. In normal mode, the control device sets the delay time as the delay compensation time and performs the displacement estimation processing using the sensor-acquired information during the delay time. The control device switches between a normal mode and a temporary mode for displacement estimation processing, depending on whether the ineffective period is included in the delay time of the curve-following control.

[0015] In addition to the fifth aspect, a sixth aspect has the following characteristic. In vehicle control processing, the control device calculates a target yaw angle based on the deviation between the vehicle and the target curve and executes a control operation such that the actual yaw angle follows the target yaw angle. When the displacement estimation processing is performed in temporary mode, the control device reduces the control gain used to calculate the target yaw angle from the deviation, compared to a case where the displacement estimation processing is performed in normal mode.

[0016] According to the present disclosure, the control device determines the effective period, during which the displacement estimation processing is active, and the ineffective period, during which the displacement estimation processing is ineffective. If the ineffective period is included in the delay time of the curve-tracking control, the control device performs the displacement estimation processing in a temporary mode. In this temporary mode, the control device performs the displacement estimation processing using the sensor-acquired information from the effective period, without using the sensor-acquired information from the ineffective period. Because the sensor-acquired information from the ineffective period is not used, it is possible to prevent a reduction in the accuracy of the displacement estimation processing and, consequently, the delay compensation processing.As a result, a decrease in the curve tracking performance of the curve tracking control is prevented.

[0017] Furthermore, according to the present disclosure, if the ineffective period is included in the delay time of the curve-tracking control, the control device does not completely abandon the displacement estimation processing, but rather performs the displacement estimation processing in temporary mode to the greatest extent possible. Therefore, the reduction in the curve-tracking performance of the curve-tracking control is prevented compared to a case in which the displacement estimation processing and the delay compensation processing are not performed at all. Brief description of the drawings Fig. Figure 1 is a conceptual diagram to illustrate a vehicle driving control device according to an embodiment of the present disclosure; Fig. 2 is a block diagram showing a configuration example of the vehicle driving control device according to the embodiment of the present disclosure; Fig. Figure 3 is a conceptual diagram to explain the basic curve tracking control; Fig. Figure 4 is a conceptual diagram to explain delay compensation processing in curve tracking control; Fig. Figure 5 is a block diagram showing an example of a functional configuration of a control device relating to the curve tracking control according to the embodiment of the present disclosure; Fig. Figure 6 is a flowchart showing the curve tracking control according to the embodiment of the present disclosure; Fig. Figure 7 is a conceptual diagram to illustrate a normal mode of displacement estimation processing according to the embodiment of the present disclosure; Fig. Figure 8 is a conceptual diagram showing an example of an effective period and an ineffective period relating to the displacement estimation processing according to the embodiment of the present disclosure; Fig. Figure 9 is a conceptual diagram to illustrate a first example of a temporary mode of displacement estimation processing according to the embodiment of the present disclosure; Fig. Figure 10 is a conceptual diagram to illustrate a second example of the temporary mode of displacement estimation processing according to the embodiment of the present disclosure; Fig. Figure 11 is a time-lapse diagram to illustrate the effects of the temporary mode of displacement estimation processing according to the embodiment of the present disclosure; Fig. Figure 12 is a block diagram showing an example of a functional configuration relating to displacement estimation processing according to the embodiment of the present disclosure; Fig. Figure 13 is a block diagram to illustrate a modified example of displacement estimation processing according to the embodiment of the present disclosure; Fig. Figure 14 is a flowchart summarizing the displacement estimation processing according to the embodiment of the present disclosure; and Fig. Figure 15 is a block diagram showing a modified example of a vehicle control processing system according to the embodiment of the present disclosure. Examples of implementation

[0018] Exemplary embodiments of the present disclosure are described below with reference to the associated drawings. 1. Vehicle driving control device

[0019] Fig. Figure 1 is a conceptual diagram illustrating a vehicle driving control device 10 according to the present embodiment. The vehicle driving control device 10 is installed on a vehicle 1 and performs vehicle driving control, which controls the driving (i.e., steering, accelerating, and decelerating (braking)) of the vehicle 1. In particular, the vehicle driving control device 10 performs a "curve following control," which is a type of vehicle driving control. In curve following control, the vehicle driving control device 10 periodically generates a target curve TR and controls the driving of the vehicle 1 so that the vehicle 1 follows the target curve TR. Such curve following control is implemented in an automated driving control system, a lane keeping assist system (or lane following assist system), etc.

[0020] Fig. Figure 2 is a block diagram showing a configuration example of the vehicle driving control device 10 according to the present embodiment. The vehicle driving control device 10 comprises a driving condition sensor 20, a driving environment acquisition device 30, a driving device 50, and a control device (control unit) 100.

[0021] The vehicle condition sensor 20 detects a vehicle condition of the vehicle 1. For example, the vehicle condition sensor 20 includes a vehicle speed sensor 21, a yaw rate sensor 22, an acceleration sensor 23, a steering angle sensor 24, and the like. The vehicle speed sensor 21 detects a vehicle speed V, which is the speed of the vehicle 1. The yaw rate sensor 22 detects a yaw rate YR of the vehicle 1. The acceleration sensor 23 detects accelerations (e.g., lateral acceleration, longitudinal acceleration, and vertical acceleration) of the vehicle 1. The steering angle sensor 24 detects a steering angle of a steering wheel and a wheel rotation angle. Sensor-detected information SEN indicates a result of the detection by the vehicle condition sensor 20. The vehicle condition sensor 20 transmits the sensor-detected information SEN to the control device 100.

[0022] The driving environment acquisition device 30 acquires driving environment information ENV, which specifies a driving environment for the vehicle 1. For example, the driving environment acquisition device 30 has a map database 31, a detection sensor 32, a GPS device 33 (Global Positioning System), a communication device 34, and so on.

[0023] Map database 31 is a database containing map information that specifies a lane configuration and road shape. The driving environment acquisition device 30 retrieves the map information for a required area from map database 31. Map database 31 can be stored in a specific storage device attached to vehicle 1 or it can be stored on an administrative server outside of vehicle 1. In the latter case, the driving environment acquisition device 30 communicates with the administrative server via communication device 34 to retrieve the required map information from map database 31 on the administrative server.

[0024] The detection sensor 32 detects (detects) a situation around the vehicle 1. For example, the detection sensor 32 includes a camera, a LiDAR (Laser Imaging Detection and Ranging) system, and a radar. Environmental situation information indicates a result of the detection (perception) by the detection sensor 32. For example, the environmental situation information includes information about a surrounding vehicle and a white line around the vehicle 1.

[0025] The GPS device 33 obtains position information specifying the position and azimuth (orientation) of the vehicle 1. By coordinating a configuration of the white line detected by the detection sensor 32 and the lane configuration specified by the map information, it is possible to obtain further accurate position information. As another example, the position information can be obtained through V2X communication (i.e., vehicle-to-vehicle communication and vehicle-to-infrastructure communication) using the communication device 34.

[0026] The driving environment information (ENV) contains map information, environmental situation information, and the previously described position information. The driving environment acquisition device 30 sends the acquired driving environment information (ENV) to the control device 100.

[0027] The driving device 50 comprises a steering device 51, a drive device 52, and a brake device 53. The steering device 51 rotates the wheel (i.e., changes the wheel's direction). For example, the steering device 51 includes power steering (EPS: Electric Power Steering). The drive device 52 is a power source that generates a driving force. The drive device 52 is represented by an engine and an electric motor. The brake device 53 generates a braking force. Operation of the driving device 50 is controlled by the control device 100.

[0028] The control device (control unit) 100 comprises a microcomputer with a processor 101 and a memory 102. The control device 100 is also referred to as an ECU (Electronic Control Unit). A plurality of processing operations by the control device 100 are achieved by the processor 101 executing a control program stored in the memory 102.

[0029] For example, the control device 100 performs the vehicle driving control, which controls the movement of the vehicle 1 by controlling the driving device 50. The vehicle driving control includes steering control and acceleration / deceleration control. The control device 100 performs the steering control by controlling the steering device 51. In addition, the control device 100 performs the acceleration / deceleration control by controlling the drive device 52 and the brake device 53.

[0030] In particular, the control device 100 performs curve following control as a type of vehicle driving control. Specifically, the control device 100 periodically generates a target curve TR based on the driving environment information ENV. For example, the target curve TR has a line along the center of a lane. The control device 100 can calculate the target curve TR based on map information and position information. As another example, the control device 100 can calculate the target curve TR based on environmental situation information (in particular, the information on the white line). However, the target curve TR and a method for its calculation are not limited to these. The control device 100 generates the target curve TR and then performs vehicle driving control so that the vehicle 1 follows the target curve TR.

[0031] The curve tracking control according to the present embodiment is described in more detail below. 2. Curve Following Control 2-1. Basic Curve Following Control

[0032] Fig. Figure 3 is a conceptual diagram to explain the basic curve tracking control. First, a coordinate system (X, Y) is defined. In the diagram shown... Fig. In the example shown, an origin O is located at the center of vehicle 1. An X-direction is a forward direction of vehicle 1, and a Y-direction is a plane direction perpendicular to the X-direction. However, the coordinate system (X, Y) is not based on the one shown in Fig. The 3 examples shown are limited.

[0033] The target curve TR is defined at a specific time in the coordinate system (X, Y). A point S on the target curve TR is a point located in the Y direction from the origin O. A lateral deviation Ed (i.e., a deviation in the Y direction) is a distance between the origin O and point S, i.e., a distance between vehicle 1 and the target curve TR. A yaw angle deviation θd (i.e., an azimuth angle deviation) is an angle between the X direction and a tangent line TL to the target curve TR at point S.

[0034] The control device 100 executes the vehicle driving control in such a way that the deviation (i.e., the lateral deviation Ed and the yaw angle deviation θd) between the vehicle 1 and the target curve TR decreases. As a result, curve tracking control is achieved.

[0035] In curve-following control, however, control delay can occur due to various causes. These include computational processing time, information communication time, and so on. For example, calculating the target curve (TR) requires a certain amount of time, and this target curve calculation time causes the control delay. The control delay in curve-following control leads to a reduction in the system's ability to follow the target curve (TR), which is undesirable.

[0036] In light of the foregoing, the control device 100 corrects the lateral deviation Ed and the yaw angle deviation θd to compensate for the control delay. The processing that corrects the lateral deviation Ed and the yaw angle deviation θd to compensate for the control delay is referred to below as the "delay compensation processing".

[0037] Fig. Figure 4 is a conceptual diagram illustrating the delay compensation processing. At an initial time T1, the control device 100 acquires the driving environment information ENV required to calculate the target curve TR. The control device 100 then calculates the target curve TR based on the acquired driving environment information ENV. The target curve TR, calculated based on the driving environment information ENV acquired at the initial time T1, is defined in the coordinate system (X, Y) defined at the initial time T1. The lateral deviation Ed and the yaw angle deviation θd at the initial time T1 are lateral deviation Ed1 and yaw angle deviation θd1, respectively.

[0038] Next, a delay time DL is considered, which represents the control delay of the curve-following control system. The delay time DL includes the computation processing time, the information communication time, and the like. A time point later than the first time point T1 by a delay time DL is a second time point T2. The lateral deviation Ed and the yaw angle deviation θd at the second time point T2 are each a lateral deviation Ed2 and a yaw angle deviation θd2, respectively.

[0039] The delay compensation processing includes a step that corrects the lateral deviation Ed1 and the yaw angle deviation θd1 at the first time T1 to the lateral deviation Ed2 and the yaw angle deviation θd2 at the second time T2. For this purpose, a displacement (i.e., a movement amount) of vehicle 1 is required during the delay time DL. The displacement includes changes in the position and yaw angle of vehicle 1.

[0040] In the Fig. In the example shown in Figure 4, a lateral position is a position in the Y-direction, and a yaw angle is an angle with the X-direction. The lateral position and yaw angle of vehicle 1 are both 0 at the first time T1. A yaw angle θ after the first time T1 can be calculated (estimated) by integrating the yaw rate YR detected by the yaw rate sensor 22. A yaw angle θ2 at the second time T2 can be calculated (estimated) by integrating the yaw rate YR over the delay time DL.

[0041] Additionally, a velocity in the X-direction and a velocity in the Y-direction are calculated based on the yaw angle θ and the vehicle speed V. A displacement in the X-direction and a displacement in the Y-direction can be calculated (estimated) by integrating the velocity in the X-direction and the velocity in the Y-direction respectively over the deceleration time DL. The displacement in the Y-direction corresponds to a lateral position E2 of vehicle 1 at the second time T2.

[0042] In this way, it is possible to estimate the displacement of vehicle 1 during the deceleration time DL based on the sensor-acquired information SEN (i.e., the vehicle speed V and the yaw rate YR). This processing is referred to below as "displacement estimation processing." Displacement estimation processing is also known as "deadlock navigation."

[0043] Point S2 on the target curve TR is a point located in the Y-direction relative to vehicle 1 at time T2. The lateral position of point S2 is the target lateral position Et. The yaw angle of a tangent line TL2 to the target curve TR at point S2 is the target yaw angle θt. The target lateral position Et and the target yaw angle θt can be calculated from the displacement in the X-direction and information about the position and curvature of the target curve TR. A difference between the target lateral position Et and the lateral position E2 of vehicle 1 is the lateral deviation Ed2 at time T2. A difference between the target yaw angle θt and the yaw angle θ2 of vehicle 1 is the yaw angle deviation θd2 at time T2.

[0044] In this way, it is possible to calculate the lateral deviation Ed2 and the yaw deviation θd2 at the second time point T2 based on the result of the displacement estimation processing and the information about the target curve TR. In other words, it is possible to correct the lateral deviation Ed and the yaw deviation θd to compensate for the control delay. Furthermore, a correction (i.e., coordinate transformation) of the target curve TR can be performed based on the current coordinate system (X, Y) defined at the second time point T2. The lateral deviation Ed and the yaw deviation θd are also corrected by the correction of the target curve TR.

[0045] The curve tracking control is performed based on the lateral deviation Ed2 and the yaw angle deviation θd2, which are obtained through delay compensation processing. As a result, the curve tracking performance of the curve tracking control is improved. 2-2. Example of processing by a control device

[0046] Fig. Figure 5 is a block diagram showing an example of the functional configuration of the control device 100, which is used for curve tracking control according to the present embodiment. The control device 100 comprises an information reference unit 110, a displacement estimation unit 120, a delay compensation unit 130, and a drive control unit 140 as functional blocks. These functional blocks are obtained by the processor 101 of the control device 100 executing a control program stored in the memory 102. The information reference unit 110 has a buffer 115 for storing information. The buffer 115 is provided by the memory 102.

[0047] Fig. Figure 6 is a flowchart showing the curve tracking control according to the present embodiment. Each processing step in the curve tracking control according to the present embodiment is shown in relation to the Fig. 5 and Fig. 6 described. 2-2-1. Information gathering and processing (Step S110)

[0048] The information reference unit 110 performs information retrieval processing. Specifically, the information reference unit 110 retrieves the sensor-acquired information SEN, which represents the result of the acquisition by the vehicle condition sensor 20. As previously described, the sensor-acquired information SEN includes the vehicle speed V, the yaw rate YR, the acceleration, and so on. The information reference unit 110 stores the sensor-acquired information SEN in the buffer 115. 2-2-2. Displacement Estimation Processing (Step S120)

[0049] The displacement estimation unit 120 performs the displacement estimation processing (i.e., dead reckoning navigation). The basic explanation was given in the previous sections 2-1 and Fig. 4. This is provided by using the delay time DL of the curve-following control. The delay time DL is the actual time of the control delay. For example, the delay time DL is measured beforehand and specified as a preset value. As another example, the delay time DL can be the difference between a timestamp of the target curve TR (i.e., the first time T1) and a current time.

[0050] According to the present embodiment, the delay time DL is not necessarily used as in displacement estimation processing. In displacement estimation processing according to this embodiment, a "delay compensation time L" is used, which is at least a fraction of the delay time DL. The displacement estimation unit 120 sets the delay compensation time L equal to or less than the delay time DL. Examples of setting the delay compensation time L are described in detail below in Section 3.

[0051] The displacement estimator 120 estimates the displacement (i.e., the amount of motion) of vehicle 1 during the deceleration compensation time L based on the sensor-acquired information SEN. Specifically, the displacement estimator 120 obtains the sensor-acquired information SEN during the deceleration compensation time L from buffer 115. Then, the displacement estimator 120 estimates the displacement of vehicle 1 during the deceleration compensation time L based on the sensor-acquired information SEN during the deceleration compensation time L. Note that the "deceleration time DL" in the previous section 2-1 is replaced by the "deceleration compensation time L". As previously described, it is possible to estimate the displacement during the deceleration compensation time L based, for example, on the yaw rate YR and the vehicle speed V. Additionally, a vehicle slip angle can be taken into account.The displacement estimation unit 120 can estimate the displacement by using a predefined displacement estimation model. 2-2-3. Delay compensation processing (step S130)

[0052] The delay compensation unit 130 performs the delay compensation processing. Specifically, the delay compensation unit 130 corrects the deviation (i.e., the lateral deviation Ed and the yaw angle deviation θd) between vehicle 1 and the target curve TR to compensate for the control delay. The displacement of vehicle 1 during the delay compensation time L is obtained through the displacement estimation processing described earlier. The delay compensation unit 130 corrects the lateral deviation Ed and the yaw angle deviation θd based on the estimated displacement and the information about the target curve TR.

[0053] Furthermore, the delay compensation unit 130 can perform a correction (i.e., coordinate transformation) of the target curve TR based on the current coordinate system (X, Y) defined at the second time point T2. The lateral deviation Ed and the yaw angle deviation θd are also corrected by the correction of the target curve TR.

[0054] As a result of the delay compensation processing, the lateral deviation Ed2 and the yaw angle deviation θd2 are obtained at the second time point T2. The lateral deviation Ed2 and the yaw angle deviation θd2 obtained through the delay compensation processing are used in the subsequent flight control processing. 2-2-4. Vehicle control processing (step S140)

[0055] The vehicle control unit 140 performs a vehicle control operation that controls the movement of vehicle 1 in such a way that the lateral deviation Ed2 and the yaw angle deviation θd2 are reduced. Specifically, the vehicle control unit 140 calculates a vehicle control input required to reduce the lateral deviation Ed2 and the yaw angle deviation θd2. The vehicle control unit 140 then actuates the drive device 50 in accordance with the calculated vehicle control input. As a result, it is possible to drive vehicle 1 to follow the target curve TR.

[0056] For example, the steering control using the steering device 51 is represented as follows. The driving control unit 140 calculates a target yaw rate YRt, which is required to reduce the lateral deviation Ed2 and the yaw angle deviation θd2. For example, the target yaw rate YRt is expressed in the following equation (1). YRt=Ga×Ed2+Gb×θd2

[0057] The parameters Ga and Gb in equation (1) are control gains for the lateral deviation Ed2 and the yaw angle deviation θd2, respectively. Equation (1) may also contain a feedforward expression that depends on the curvature of the target curve TR.

[0058] The flight control unit 140 calculates a target yaw angle δt based on a yaw rate deviation, which is the difference between the target yaw rate YRt and the actual yaw rate YR. The actual yaw rate YR is detected by the yaw rate sensor 22. The greater the yaw rate deviation, the greater the target yaw angle δt.

[0059] Furthermore, the vehicle control unit 140 performs feedback control so that the actual rotation angle δ follows the target rotation angle δt. The actual rotation angle δ is detected by the steering angle sensor 24. The feedback control is, for example, a PID controller. For instance, the vehicle control unit 140 performs the feedback control based on a deviation between the target rotation angle δt and the actual rotation angle δ. In this way, curve following control is achieved. 3. Displacement Estimation Processing

[0060] The displacement estimation processing according to the present embodiment is described in more detail below. According to the present embodiment, the displacement estimation processing modes have two types: a "normal mode" and a "temporary mode". 3-1. Normal mode

[0061] Fig. Figure 7 is a conceptual diagram illustrating the normal mode. The control device 100 (the displacement estimation unit 120) sets the delay time DL of the curve tracking control as the delay compensation time L. The delay time DL is measured beforehand and specified as a predetermined value. As another example, the delay time DL could be the difference between a timestamp of the target curve TR (i.e., the first time T1) and an actual time. The control device 100 performs the displacement estimation processing using the sensor-acquired information SEN in the delay compensation time L (= the delay time DL). 3-2. Temporary mode

[0062] If the vehicle condition sensor 20 is functioning normally, the sensor-detected information SEN is also normal. Consequently, the displacement estimation processing is effective. However, if the vehicle condition sensor 20 is faulty, the sensor-detected information SEN becomes incorrect, and thus the displacement estimation processing becomes ineffective. A period during which the displacement estimation processing is effective is subsequently referred to as the "effective period PA." Conversely, a period during which the displacement estimation processing is ineffective is subsequently referred to as the "ineffective period PB."

[0063] Fig. Figure 8 shows an example of the effective period PA and the ineffective period PB. In the Fig. In the example shown, the ineffective period PB is included in the delay time DL of the curve-following control. When the displacement estimation processing is performed in the previously described normal mode, the incorrect sensor-detected information SEN is used in the ineffective period PB. The displacement estimated based on the incorrect sensor-detected information SEN becomes an anomalous value that does not reflect the actual vehicle movement. As a result, the delay compensation processing is performed without reflecting the actual vehicle movement, and thus the curve-following performance of the curve-following control is reduced. To prevent such a reduction in curve-following performance, the "temporary mode" is provided separately from the "normal mode."

[0064] If the ineffective period PB is included in the delay time DL of the curve tracking control, the control device 100 (the displacement estimation unit 120) performs the displacement estimation processing in temporary mode. In temporary mode, the control device 100 performs the displacement estimation processing using the sensor-detected information SEN in the effective period PA, without using the sensor-detected information SEN in the ineffective period PB. 3-2-1. First example of temporary mode

[0065] Fig. Figure 9 is a conceptual diagram illustrating a first example of the temporary mode. In this first example, the control device 100 does not fix the delay compensation time L, but rather sets it variably. Specifically, both the effective period PA and the ineffective period PB are contained within the delay time DL of the curve-tracking control, and the control device 100 designates the effective period PA contained within the delay time DL as the delay compensation time L. The control device 100 then performs the displacement estimation processing using the sensor-acquired information SEN within the delay compensation time L (= the effective period PA). The control device 100 does not use the sensor-acquired information SEN within the ineffective period PB. 3-2-2. Second example of the temporary mode

[0066] Fig. Figure 10 is a conceptual diagram illustrating a second example of the temporary mode. In this second example, the control device 100 estimates the driving state during the inactive period PB based on the normal sensor-acquired information SEN during the active period PA. Specifically, the control device 100 assumes that vehicle behavior present during the active period PA will persist during the inactive period PB and interpolates or extrapolates the driving state during the inactive period PB using the driving state during the active period PA. Estimated driving state information EST indicates the driving state estimated in this way during the inactive period PB.

[0067] In the second example, the control device 100 sets the delay time DL of the curve following control as the delay compensation time L, as in the case of normal mode. The control device 100 then performs the displacement estimation processing using the sensor-acquired information SEN in the active period PA and the estimated driving condition information EST in the inactive period PB. The control device 100 does not use the sensor-acquired information SEN in the inactive period PB.

[0068] In the second example, the delay compensation time L is prevented from becoming too short. Consequently, the delay compensation processing is performed effectively. Furthermore, there is no need to switch (change) the delay compensation time L between normal mode and temporary mode. Accordingly, there is no need to switch the delay compensation processing. 3-2-3. Third example of the temporary mode

[0069] A third example is a combination of the first and the second example described above. The control device 100 can switch between the first and second examples of the temporary mode as needed. For example, if the effective period PA length included in the delay time DL of the curve-following control is equal to or greater than a threshold value, the control device 100 selects the first example of the temporary mode. Conversely, if the effective period PA length included in the delay time DL of the curve-following control is less than the threshold value, the control device 100 selects the second example of the temporary mode.

[0070] According to the third example, the processing for estimating the driving state is prevented during the ineffective period PB, thus reducing the computational load placed on the control device 100. This means it is possible to balance the securing of the delay compensation time L and the reduction of the computational load. 3-2-4. Effects of the temporary mode

[0071] According to the exemplary embodiment described above, if the ineffective period PB is included in the delay time DL of the curve-tracking control, the control device 100 performs the displacement estimation processing in temporary mode. In temporary mode, the control device 100 performs the displacement estimation processing using the sensor-detected information SEN in the effective period PA, without using the sensor-detected information SEN in the ineffective period PB. Since the sensor-detected information SEN in the ineffective period PB is not used, it is possible to prevent a reduction in the accuracy of the displacement estimation processing and thus of the delay compensation processing. Consequently, a reduction in the curve-tracking performance of the curve-tracking control is prevented.

[0072] As a comparative example, we consider a case in which the displacement estimation processing and the delay compensation processing are completely suspended if the ineffective period PB is included in the delay time DL. In this comparative example, the delay compensation processing is not performed at all, and the curve-following performance of the curve-following controller is ultimately reduced. In contrast, according to the present embodiment, if the ineffective period PB is included in the delay time DL, the control device 100 performs the displacement estimation processing in temporary mode to the greatest extent possible. Consequently, a reduction in the curve-following performance of the curve-following controller is prevented.

[0073] The effects of the temporary mode are discussed in relation to Fig. 11 further described. Time changes of a state of the driving condition sensor 20, the delay compensation time L and the lateral deviation Ed are in Fig. 11 shown. The case of the first example of the temporary mode (see Fig. 9) is considered here. The same applies to the case of the second example (see Fig. 10).

[0074] At time t1, the driving condition sensor 20 returns to a normal state. After time t1, the effective period PA contained in the delay time DL gradually increases. At time t2, the effective period PA becomes equal to the delay time DL, and the control device 100 starts executing the displacement estimation processing in normal mode. As in Fig. As shown in Figure 11, the correction amount of the lateral deviation Ed changes gradually during the period from time t1 to time t2 due to the delay compensation processing. In other words, the lateral deviation Ed changes gradually without switching discontinuously.

[0075] At time t3, a fault occurs in the driving condition sensor 20, and the control device 100 starts executing the displacement estimation processing in temporary mode. After time t3, the ineffective period PB contained in the delay time DL gradually increases, and the effective period PA gradually decreases. As a result, the delay compensation time L also gradually decreases. At time t4, the delay compensation time L becomes zero. As in Fig. As shown in Figure 11, the correction amount of the lateral deviation Ed changes gradually during the period from time t3 to time t4 due to the delay compensation processing. In other words, the lateral deviation Ed changes gradually without switching discontinuously.

[0076] In the previously described comparison example, the displacement estimation processing and the delay compensation processing are not executed during the period from time t1 to time t2 and during the period from time t3 to time t4. Consequently, the curve-tracking performance of the curve-tracking controller is reduced during these periods.

[0077] In contrast, according to the present embodiment, the control device 100 performs the displacement estimation processing in temporary mode during the period from time t1 to time t2 and during the period from time t3 to time t4. That is, the control device 100 does not completely abandon the displacement estimation processing, but rather performs it to the greatest extent possible. Consequently, a reduction in the curve-following performance of the curve-following control is prevented compared to the case of the comparison example.

[0078] Furthermore, in the previously described comparison example, the delay compensation processing switches from OFF to ON at time t2, and the delay compensation processing switches from ON to OFF at time t3. As a result, the lateral deviation Ed switches (changes) discontinuously. Because the lateral deviation Ed switches discontinuously, the vehicle tax amount in the driving tax processing (step S140) also switches discontinuously. Such discontinuous switching (changing) of the vehicle tax amount reduces the stability of the vehicle's driving and causes a feeling of strangeness in the vehicle's handling.

[0079] In contrast, according to the present embodiment, the ON / OFF function of the delay compensation processing does not switch abruptly. Because of the temporary mode, the correction amount of the lateral deviation Ed changes gradually through the delay compensation processing, as described previously. The lateral deviation Ed changes gradually without switching discontinuously. Consequently, the vehicle control amount in the driving control processing (step S140) is prevented from switching discontinuously. This helps to increase the stability of the vehicle's handling and reduce the feeling of unfamiliarity. 3-3. Example of processing by a control device

[0080] Fig. Figure 12 is a block diagram showing an example of a functional configuration relating to displacement estimation processing according to the present embodiment. The displacement estimation unit 120 comprises a mode determination unit 121, a data adaptation unit 122, and an estimation execution unit 123. These functional blocks are received by the processor 101 of the control device 100, which executes the control program stored in the memory 102. 3-3-1. Mode determination processing

[0081] Mode Determination Unit 121 performs a mode determination process that determines the mode of the displacement estimation processing. Mode Determination Unit 121 first determines (predicts) the effective period PA and the ineffective period PB. The effective period PA is a period in which the displacement estimation processing is effective. The ineffective period PB is a period in which the displacement estimation processing is ineffective.

[0082] For example, the driving state sensor 20 outputs a sensor state signal ST indicating its own state. The mode determination unit 121 receives the sensor state signal ST from the driving state sensor 20. The mode determination unit 121 then determines whether the driving state sensor 20 is normal or not, based on the sensor state signal ST. The mode determination unit 121 defines a period during which the driving state sensor 20 is normal, known as the effective period PA. Conversely, the mode determination unit 121 defines a period during which the driving state sensor 20 is anomalous, known as the ineffective period PB.

[0083] It should be noted that the driving condition sensor 20 has several types of sensors, as shown in Fig. Figure 2 shows that “The vehicle state sensor 20 is normal” means that all sensors acquiring parameters used for displacement estimation processing are normal. “The vehicle state sensor 20 is anomalous” means that at least one of the sensors acquiring parameters used for displacement estimation processing is anomalous. For example, if vehicle speed V and yaw rate YR are used in displacement estimation processing, a period in which both vehicle speed sensor 21 and yaw rate sensor 22 are normal is the effective period PA.

[0084] As another example, the mode determination unit 121 can determine the effective period PA and the ineffective period PB based on the sensor-detected information SEN stored in buffer 115. If the driving condition sensor 20 is anomalous, a parameter obtained from the sensor-detected information SEN deviates from a normal range. Here, the parameter is illustrated by the detected value itself, a derivative of the detected value, etc. If the parameter is within the normal range, the mode determination unit 121 indirectly determines that the driving condition sensor 20 is normal. Conversely, if the parameter deviates from the normal range, the mode determination unit 121 indirectly determines that the driving condition sensor 20 is anomalous.

[0085] When a predefined displacement estimation model is used for displacement estimation processing, the mode determination unit 121 can determine whether the driving state of vehicle 1 matches the displacement estimation model. For example, consider a case where the displacement estimation model is based on the assumption that vehicle 1 is traveling on a level road surface. The sensor-acquired information SEN includes the acceleration detected by the accelerometer 23. The mode determination unit 121 calculates a road surface gradient based on the acceleration. If the road surface gradient exceeds a permissible range allowed in the displacement estimation model, the mode determination unit 121 determines that the displacement estimation processing will fail.

[0086] In this way, the mode determination unit 121 determines (predicts) the effective period PA and the ineffective period PB based on at least one of the sensor state signals ST and the sensor-acquired information SEN. If the ineffective period PB is not included in the delay time DL of the curve tracking control, the mode determination unit 121 selects the normal mode. Conversely, if the ineffective period PB is included in the delay time DL of the curve tracking control, the mode determination unit 121 selects the temporary mode. That is, the mode determination unit 121 switches the displacement estimation processing mode between the normal mode and the temporary mode depending on whether the ineffective period PB is included in the delay time DL of the curve tracking control or not.

[0087] Furthermore, the mode determination unit 121 sets the delay compensation time L, which is used for displacement estimation processing. In particular, in the case of normal mode (see Fig. 7) The mode determination unit 121 sets the delay time DL as the delay compensation time L. In the case of the first example of the temporary mode (see Fig. 9) The mode determination unit 121 defines the effective period PA as the delay compensation time L. In the case of the second example of the temporary mode (see Fig. 10) The mode determination unit 121 sets the delay time DL as the delay compensation time L. The mode determination unit 121 notifies the estimation execution unit 123 of the set delay compensation time L.

[0088] Furthermore, the mode determination unit 121 notifies the data adjustment unit 122 about the effective period PA and the ineffective period PB. 3-3-2. Data adaptation processing

[0089] The data adaptation unit 122 reads the sensor-detected information SEN stored in buffer 115 in a suitable manner. In normal mode, the data adaptation unit 122 outputs the sensor-detected information SEN to the estimation execution unit 123 within the delay time DL, exactly as it is. In temporary mode, the data adaptation unit 122 performs data adaptation processing.

[0090] In particular, in the case of the first example of the temporary mode, the data fitting unit 122 only outputs the sensor-detected information SEN in the effective period PA to the estimation execution unit 123. In other words, the data fitting unit 122 masks the sensor-detected information SEN in the ineffective period PB.

[0091] In the case of the second example of the temporary mode, the data adaptation unit 122 estimates the driving state in the ineffective period PB based on the normal sensor-acquired information SEN in the effective period PA. Specifically, the data adaptation unit 122 assumes that the vehicle behavior in the effective period PA also persists in the ineffective period PB and interpolates or extrapolates the driving state in the ineffective period PB using the driving state in the effective period PA. The data adaptation unit 122 obtains the estimated driving state information EST, which specifies the driving state in the estimated ineffective period PB. The data adaptation unit 122 then outputs the sensor-acquired information SEN in the effective period PA and the estimated driving state information EST in the ineffective period PB to the estimation execution unit 123. 3-3-3. Estimate execution processing

[0092] The estimation execution unit 123 performs the displacement estimation processing. In the case of normal mode (see Fig. 7) The estimation execution unit 123 performs the displacement estimation processing by using the sensor-acquired information SEN in the delay compensation time L (= the delay time DL).

[0093] In the case of the first example of temporary mode (see Fig. 9) The estimation execution unit 123 performs the displacement estimation processing by using the sensor-acquired information SEN in the delay compensation time L (= the effective period PA).

[0094] In the case of the second example of the temporary mode (see Fig. 10) The estimation execution unit 123 performs the displacement estimation processing by using the sensor-acquired information SEN in the effective period PA and the estimated driving condition information EST in the ineffective period PB. 3-3-4. Variation example

[0095] Fig. Figure 13 is a block diagram illustrating a variation example. In this variation example, the mode determination unit 121 provisionally selects normal mode. The estimation execution unit 123 performs the displacement estimation processing in normal mode to provisionally estimate the displacement. The displacement provisionally estimated in normal mode is fed back to the mode determination unit 121.

[0096] If displacement estimation processing is ineffective, a parameter obtained from the preliminary estimated displacement deviates from a normal range. Here, the parameter is illustrated by the displacement itself, a derivative of the displacement, etc. If the parameter lies within the normal range, mode determination unit 121 determines that displacement estimation processing is effective. Conversely, if the parameter deviates from the normal range, mode determination unit 121 determines that displacement estimation processing is ineffective. 3-3-5. Displacement Estimation Processing Procedure

[0097] Fig. Figure 14 is a flowchart summarizing the displacement estimation processing (step S120) according to the present embodiment.

[0098] In step S121, the control device 100 performs the mode determination processing. In particular, the control device 100 switches the mode of the displacement estimation processing between the normal mode and the temporary mode, depending on whether the ineffective period PB is included in the delay time DL of the curve tracking control or not.

[0099] If the ineffective period PB is included in the delay time DL, the control device 100 selects the temporary mode (step S122; Yes). In this case, the control device 100 performs the data fitting processing (step S123). Then, the control device 100 performs the displacement estimation processing in the temporary mode (step S124).

[0100] If, on the other hand, the ineffective period PB is not included in the delay time DL, the control device 100 selects normal mode (step S122; No). In this case, the control device 100 performs the displacement estimation processing in normal mode (step S125). 4. Variation example of vehicle control processing

[0101] When the displacement estimation processing is performed in temporary mode, the accuracy of the delay compensation processing is reduced compared to when the displacement estimation processing is performed in normal mode. Consequently, the control device 100 (the vehicle control unit 140) can perform the vehicle control processing (step S140) in such a way as to ensure the stability of the vehicle 1.

[0102] For example, notified as in Fig.Figure 15 shows that the displacement estimation unit 120 (the mode determination unit 121) controls the vehicle control unit 140 via the selected mode of displacement estimation processing. The vehicle control unit 140 sets the control gains Ga and Gb in the aforementioned equation (1) according to the selected mode. In particular, when the displacement estimation processing is performed in the temporary mode, the vehicle control unit 140 reduces the control gains Ga and Gb compared to the case where the displacement estimation processing is performed in the normal mode.

[0103] The amounts of the reduction (adjustment) of the control gains Ga and Gb can be variable. For example, the vehicle control unit 140 changes the amounts of the reduction of the control gains Ga and Gb according to the length of the ineffective period PB, which is included in the delay time DL of the curve following control. The amounts of the reduction of the control gains Ga and Gb increase when the ineffective period PB, which is included in the delay time DL, becomes longer (i.e., when the effective period PA becomes shorter).

[0104] Since the tax gains Ga and Gb decrease, the vehicle tax amount is prevented. Even if the displacement estimation processing is executed in temporary mode, vehicle 1's rocking is therefore prevented and the stability of the vehicle's journey is ensured.

[0105] In summary, a vehicle driving control device 10 performs a curve following control to make the vehicle 1 follow a target curve TR. A delay time DL represents the control delay of the curve following control. A delay compensation time L is at least a portion of the delay time DL. The curve following control includes: a displacement estimation process that estimates a displacement of the vehicle 1 during the delay compensation time L; and a delay compensation process that corrects a deviation Ed, θd between the vehicle 1 and the target curve TR based on the estimated displacement to compensate for the control delay. The displacement estimation process is effective during an effective period PA and ineffective during an ineffective period PB.If the ineffective period PB is included in the delay time DL of the curve tracking control, the displacement estimation processing is performed in a temporary mode by using sensor-detected information SEN in the effective period PA without using the sensor-detected information SEN in the ineffective period PB.

Claims

[1] Vehicle driving control device (10) which controls the driving of a vehicle (1), comprising: a sensor (20) configured to detect a driving state of the vehicle (1); and a control device (100) configured to perform a curve following control which generates a target curve (TR) and controls the movement of the vehicle (1) so that the vehicle (1) follows the target curve (TR), wherein A delay time (DL) is a time that represents a control delay of the curve tracking control, a delay compensation time (L) is at least a part of the delay time (DL), which features curve tracking control: an information acquisition processing system that obtains sensor-acquired information (SEN) that indicates a result of the acquisition by the sensor (20); a displacement estimation processing that estimates a displacement of the vehicle (1) in the deceleration compensation time (L) based on the sensor-acquired information (SEN); a delay compensation processing that corrects a deviation (Ed, θd) between the vehicle (1) and the target curve (TR) based on the estimated displacement to compensate for the control delay; and a vehicle control processing system which controls the vehicle's (1) movement in such a way that the deviation (Ed, θd) is reduced after the delay compensation processing, the control device (100) is further configured to determine an effective period (PA) in which the displacement estimation processing is effective and an ineffective period (PB) in which the displacement estimation processing is ineffective, based on a state of the sensor (20) and / or the sensor-detected information (SEN), if the ineffective period (PB) is included in the delay time (DL) of the curve tracking control, the control device (100) performs the displacement estimation processing in a temporary mode, and the control device (100) in the temporary mode performs the displacement estimation processing by using at least the sensor-detected information (SEN) in the effective period (PA), without using the sensor-detected information (SEN) in the ineffective period (PB). [2] Vehicle driving control device (10) according to claim 1, wherein, if both the effective period (PA) and the ineffective period (PB) are included in the delay time (DL) of the curve following control, the control device (100) defines the effective period (PA) included in the delay time (DL) as the delay compensation time (L) used in temporary mode. [3] Vehicle driving control device (10) according to claim 1, wherein the control device (100) is configured in the temporary mode to: to estimate the driving condition in the ineffective period (PB) based on the sensor-acquired information (SEN) in the ineffective period (PA) in order to obtain estimated driving condition information (EST) that indicates the estimated driving condition; to define the delay time (DL) as the delay compensation time (L); and The displacement estimation processing is performed by using the sensor-acquired information (SEN) in the effective period (PA) and the estimated driving condition information (EST) in the ineffective period (PB). [4] Vehicle driving control device (10) according to claim 2, wherein, if the length of the effective period (PA) contained in the delay time (DL) of the curve following control is less than a threshold value, the control device (100) is configured to: to estimate the driving condition in the ineffective period (PB) based on the sensor-acquired information (SEN) in the ineffective period (PA) in order to obtain estimated driving condition information (EST) that indicates the estimated driving condition; to define the delay time (DL) as the delay compensation time (L); and The displacement estimation processing is performed by using the sensor-acquired information (SEN) in the effective period (PA) and the estimated driving condition information (EST) in the ineffective period (PB). [5] Vehicle driving control device (10) according to any one of claims 1 to 4, wherein, if the ineffective period (PB) is not included in the delay time (DL) of the curve following control, the control device (100) performs the displacement estimation processing in a normal mode, In normal mode, the control device (100) sets the delay time (DL) as the delay compensation time (L) and performs the displacement estimation processing by using the sensor-detected information (SEN) in the delay time (DL), and The control device (100) switches a mode of displacement estimation processing between the normal mode and the temporary mode, depending on whether the ineffective period (PB) is included in the delay time (DL) of the curve tracking control or not. [6] Vehicle driving control device (10) according to claim 5, wherein In the vehicle control processing, the control device (100) calculates a target rotation angle (δt) based on the deviation (Ed, θd) between the vehicle (1) and the target curve (TR) and performs a control such that an actual rotation angle (δ) follows the target rotation angle (δt), and When the displacement estimation processing is performed in temporary mode, the control device (100) reduces a control gain (Ga, Gb) used to calculate the target rotation angle (δt) from the deviation (Ed, θd) compared to a case where the displacement estimation processing is performed in normal mode.

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