JP2021091336A - Vehicle control device - Google Patents

Abstract

To provide a device which enables a travel trajectory contributing to improvement in ride quality of an occupant to be set while preventing the travel trajectory from being unnecessarily changed.SOLUTION: A vehicle control device enabling a vehicle to travel through automatic control comprises: state detection means which detects a state of a travel route in a moving direction of the vehicle; acquisition means which acquires information on the vehicle and an occupant therein; estimation means which estimates a degree of oscillation of the occupants in the vehicle assuming that the vehicle travels along a candidate travel trajectory on the travel route on the basis of a detection result of the state detection means and the information on the vehicle and the occupant therein acquired with the acquisition means; and travel trajectory setting means which sets the travel trajectory on the travel route on the basis of an estimation result of the estimation means.SELECTED DRAWING: Figure 6

Description

The present invention relates to a vehicle control device.

In the automatic driving of a vehicle, the traveling track of the vehicle is set from map information and the like to automatically drive the vehicle. At that time, a technique for setting a more suitable traveling track in the same traveling path section has been proposed. For example, Patent Document 1 proposes a technique for changing a traveling track according to the presence of a rut in front of the traveling direction.

Japanese Unexamined Patent Publication No. 2016-172,500

Vehicle vibration affects the ride quality of occupants. Bypassing the undulations of the road surface that vibrates the vehicle, such as ruts, helps improve the ride quality of the occupants, but circumventing any undulations unnecessarily changes the vehicle's trajectory and complicates control. ..

An object of the present invention is to provide a device capable of setting a traveling track that contributes to improvement of riding comfort of an occupant while avoiding an unnecessary change of the traveling track.

According to the present invention
It is a vehicle control device that can drive a vehicle by automatic driving.
A state detecting means for detecting the state of the traveling path in the traveling direction of the vehicle, and
The first acquisition means for acquiring the information of the occupants of the vehicle,
A second acquisition means for acquiring the vehicle information, and
Based on the detection result of the state detecting means, the information of the occupant acquired by the first acquisition means, and the information of the vehicle acquired by the second acquisition means, the traveling track candidate on the traveling road is selected as the vehicle. And an estimation means for estimating the degree of shaking of the occupants of the vehicle when the vehicle travels.
A traveling track setting means for setting a traveling track on the traveling path based on the estimation result of the estimating means is provided.
A vehicle control device is provided.

According to the present invention, it is possible to provide a device capable of setting a traveling track that contributes to an improvement in riding comfort of an occupant while avoiding an unnecessary change in the traveling track.

The block diagram of the vehicle and the control device which concerns on embodiment. (A) and (B) are flowcharts showing a processing example executed by the vehicle control device of FIG. (A) to (D) are diagrams showing an example of the state of the occupant. (A) to (D) are diagrams showing an example of the state of the occupant. (A) and (B) are diagrams showing an example of the state of the traveling path. FIG. 5 is a flowchart showing a processing example executed by the vehicle control device of FIG. (A) is a diagram showing an example of a traveling track, and (B) and (C) are diagrams showing an example of undulations on a traveling track candidate. (A) is a diagram showing an example of a method of estimating the degree of shaking of an occupant, and (B) and (C) are explanatory diagrams of other estimation methods. FIG. 5 is a flowchart showing another processing example executed by the vehicle control device of FIG. (A) and (B) are flowcharts showing another processing example executed by the vehicle control device of FIG. 1, and (C) is an explanatory diagram of conversion coefficients. FIG. 5 is a flowchart showing another processing example executed by the vehicle control device of FIG. (A) and (B) are flowcharts showing another processing example executed by the vehicle control device of FIG.

Hereinafter, embodiments will be described in detail with reference to the accompanying drawings. The following embodiments do not limit the invention according to the claims, and not all combinations of features described in the embodiments are essential to the invention. Two or more of the plurality of features described in the embodiments may be arbitrarily combined. Further, the same or similar configuration will be given the same reference number, and duplicate description will be omitted.

<First Embodiment>
FIG. 1 is a block diagram of a vehicle V and a control device 1 thereof according to an embodiment of the present invention. In FIG. 1, the outline of the vehicle V is shown in a plan view and a side view. Vehicle V is, for example, a sedan-type four-wheeled passenger car.

The vehicle V of the present embodiment is, for example, a parallel hybrid vehicle. In this case, the power plant 50 that outputs the driving force for rotating the driving wheels of the vehicle V can be composed of an internal combustion engine, a motor, and an automatic transmission. The motor can be used as a drive source for accelerating the vehicle V and also as a generator during deceleration or the like (regenerative braking).

<Control device>
The configuration of the control device 1 which is an in-vehicle device of the vehicle V will be described with reference to FIG. The control device 1 includes an ECU group (control unit group) 2. The ECU group 2 includes a plurality of ECUs 20 to 28 configured to be able to communicate with each other. Each ECU includes a processor typified by a CPU, a storage device such as a semiconductor memory, an interface with an external device, and the like. The storage device stores programs executed by the processor, data used by the processor for processing, and the like. Each ECU may include a plurality of processors, storage devices, interfaces, and the like. The number of ECUs and the functions in charge can be appropriately designed, and can be subdivided or integrated from the present embodiment. In FIG. 1, the names of typical functions of the ECUs 20 to 29 are given. For example, the ECU 20 is described as "operation control ECU".

The ECU 20 executes control related to driving support including automatic driving of the vehicle V. In automatic driving, the driving of the vehicle V (acceleration of the vehicle V by the power plant 50, etc.), steering, and braking are automatically performed without the operation of the driver. Further, the ECU 20 can execute driving support control such as collision mitigation braking and lane deviation suppression in manual operation. The collision mitigation brake assists in avoiding a collision by instructing the operation of the braking device 51 when the possibility of collision with an obstacle in front increases. The lane deviation suppression supports the avoidance of lane deviation by instructing the operation of the electric power steering device 41 when the possibility that the vehicle V deviates from the traveling lane increases.

The ECU 21 is an environment recognition unit that recognizes the traveling environment of the vehicle V based on the detection results of the detection units 31A, 31B, 32A, and 32B that detect the surrounding conditions of the vehicle V. In the case of the present embodiment, the detection units 31A and 31B are cameras for photographing the front of the vehicle V (hereinafter, may be referred to as a camera 31A and a camera 31B), and are provided on the front portion of the roof of the vehicle V. There is. By analyzing the images taken by the cameras 31A and 31B, it is possible to extract the outline of the target and the lane markings (white lines, etc.) on the road.

In the case of the present embodiment, the detection unit 32A is a lidar (Light Detection and Ranging) (hereinafter, may be referred to as a lidar 32A), detects a target around the vehicle V, and is a distance from the target. To measure the distance. In the case of the present embodiment, five riders 32A are provided, one at each corner of the front portion of the vehicle V, one at the center of the rear portion, and one at each side of the rear portion. The detection unit 32B is a millimeter-wave radar (hereinafter, may be referred to as a radar 32B), detects a target around the vehicle V, and measures a distance from the target. In the case of the present embodiment, five radars 32B are provided, one in the center of the front portion of the vehicle V, one in each corner of the front portion, and one in each corner of the rear portion.

The cameras 31A and 31B and the rider 32A can detect the state of the traveling path ahead of the vehicle V in the traveling direction, and the ECU 21 recognizes the state of the traveling path. The state of the running path is mainly the uneven state, and the uneven state includes undulations (holes, ruts, swelling) of the surface layer of the running path itself, undulations due to a fixed structure such as a manhole, or dust. Ups and downs due to falling objects may be included. The state of such a traveling path may be detected by any one of the cameras 31A and 31B and the rider 32A.

The ECU 22 is a steering control unit that controls the electric power steering device 41. The electric power steering device 41 includes a mechanism for steering the front wheels in response to a driver's driving operation (steering operation) with respect to the steering wheel ST. The electric power steering device 41 includes a drive unit 41a including a motor that exerts a driving force for assisting steering operation or automatically steering the front wheels (sometimes referred to as steering assist torque), a steering angle sensor 41b, and a driver. It includes a torque sensor 41c and the like for detecting the steering torque to be borne (referred to as steering burden torque and distinguished from steering assist torque). The ECU 22 can also acquire the detection result of the sensor 36 that detects whether or not the driver is gripping the steering handle ST, and can monitor the gripping state of the driver.

The ECU 23 is a braking control unit that controls the hydraulic device 42. The driver's braking operation on the brake pedal BP is converted into hydraulic pressure in the brake master cylinder BM and transmitted to the hydraulic device 42. The hydraulic device 42 is an actuator capable of controlling the hydraulic pressure of the hydraulic oil supplied to the brake devices (for example, disc brake devices) 51 provided on each of the four wheels based on the hydraulic pressure transmitted from the brake master cylinder BM. , The ECU 23 controls the drive of the solenoid valve and the like included in the hydraulic device 42. Further, the ECU 23B can turn on the brake lamp 43B during braking. As a result, the attention to the vehicle V can be increased with respect to the following vehicle.

The ECU 23 and the hydraulic device 23 can form an electric servo brake. The ECU 23 can control, for example, the distribution of the braking force by the four braking devices 51 and the braking force by the regenerative braking of the motor included in the power plant 50. The ECU 23 also has an ABS function, traction control, and a vehicle based on the detection results of the wheel speed sensor 38, the yaw rate sensor (not shown), and the pressure sensor 35 that detects the pressure in the brake master cylinder BM provided for each of the four wheels. It is also possible to realize the attitude control function of V.

The ECU 24B is a stop maintenance control unit that controls an electric parking brake device (for example, a drum brake) 52 provided on the rear wheels. The electric parking brake device 52 includes a mechanism for locking the rear wheels. The ECU 24 can control the locking and unlocking of the rear wheels by the electric parking brake device 52.

The ECU 25 is an in-vehicle notification control unit that controls an information output device 43A that notifies information in the vehicle. The information output device 43A includes, for example, a display device provided on a head-up display or an instrument panel, or an audio output device. Further, a vibrating device may be included. The ECU 25 causes the information output device 43A to output various information such as vehicle speed and outside air temperature, information such as route guidance, and information regarding the state of the vehicle V, for example.

The ECU 26 includes a communication device 26a for vehicle-to-vehicle communication. The communication device 26a wirelessly communicates with other vehicles in the vicinity and exchanges information between the vehicles.

The ECU 27 is a drive control unit that controls the power plant 50. In the present embodiment, one ECU 27 is assigned to the power plant 50, but one ECU may be assigned to each of the internal combustion engine, the motor, and the automatic transmission. The ECU 27 controls the output of the internal combustion engine or the motor in response to the driver's driving operation, vehicle speed, etc. detected by the operation detection sensor 34a provided on the accelerator pedal AP or the operation detection sensor 34b provided on the brake pedal BP, for example. Or switch the gear of the automatic transmission. The automatic transmission is provided with a rotation speed sensor 39 for detecting the rotation speed of the output shaft of the automatic transmission as a sensor for detecting the traveling state of the vehicle V. The vehicle speed of the vehicle V can be calculated from the detection result of the rotation speed sensor 39.

The ECU 28 is a position recognition unit that recognizes the current position and course of the vehicle V. The ECU 28 controls the gyro sensor 33, the GPS sensor 28b, and the communication device 28c, and processes the detection result or the communication result. The gyro sensor 33 detects the rotational movement of the vehicle V. The course of the vehicle V can be determined from the detection result of the gyro sensor 33 or the like. The GPS sensor 28b detects the current position of the vehicle V. The communication device 28c wirelessly communicates with a server that provides map information and traffic information, and acquires such information. Highly accurate map information can be stored in the database 28a, and the ECU 28 can more accurately identify the position of the vehicle V on the lane based on the map information and the like.

The map information acquired by the ECU 28 may be used when the ECU 21 recognizes the state of the traveling path.

The input device 45 is arranged in the vehicle so that the driver can operate it, and receives instructions and information input from the driver.

The ECU 29 is an occupant recognition unit that recognizes the occupant's state and the like based on the detection results of the detection units 29a to 29d that detect the occupant of the vehicle V and outputs the occupant information. In the case of the present embodiment, the detection units 29a to 29d are cameras that photograph the interior of the vehicle (hereinafter, may be referred to as cameras 29a to 29d). The occupants present in the vehicle interior can be recognized from the captured images of the cameras 29a to 29d. In the case of the present embodiment, the occupant information includes the occupant's state such as the occupant's posture and action (second task). The occupant information may include occupant attributes (physical constitution, gender, age, generation (children, adults, elderly people), etc.).

The cameras 29a and 29b are arranged so as to photograph the occupants seated in the front row seats (driver's seat and passenger seat), the camera 29a photographs the front row seats from the front, and the camera 29b photographs the front row seats from the side. It is arranged like this. The cameras 29c and 29d are arranged so as to photograph the occupant seated in the back row seat (rear seat), the camera 29c is arranged so as to photograph the rear row seat from the front, and the camera 29d is arranged so as to photograph the rear row seat from the side. Has been done.

The number and arrangement of the cameras 29a to 29d for detecting the occupant is not limited to the illustrated example, and the occupant may be detected by a detection unit other than the camera.

<Control example>
A control example of the control device 1 will be described. FIG. 2A is a flowchart showing a mode selection process of operation control executed by the ECU 20.

In S1, it is determined whether or not the driver has performed a mode selection operation. The driver can instruct to switch between the automatic operation mode and the manual operation mode by, for example, operating the input device 45. If there is a selection operation, the process proceeds to S2, and if not, the process ends.

In S2, it is determined whether or not the selection operation is an instruction for automatic operation, and if it is an instruction for automatic operation, the process proceeds to S3, and if it is an instruction for manual operation, the process proceeds to S4. In S3, the automatic operation mode is set and the automatic operation control is started. In S4, the manual operation mode is set and the manual operation control is started. The current setting regarding the operation control mode is notified from the ECU 20 to each of the ECUs 21 to 29 and recognized.

In the manual driving control, the vehicle V is driven, steered, and braked according to the driving operation of the driver, and the ECU 20 appropriately executes the driving support control. In the automatic driving control, the ECU 20 outputs a control command to the ECU 22, the ECU 23, and the ECU 27 to control the steering, braking, and driving of the vehicle V, and automatically drives the vehicle V regardless of the driving operation of the driver. The ECU 20 sets the traveling path and the traveling track of the vehicle V, and causes the vehicle V to travel along the set traveling path and the traveling track with reference to the position recognition result of the ECU 28 and the recognition result of the target. The target is recognized based on the detection results of the detection units 31A, 31B, 32A, and 32B.

In the present embodiment, the traveling route means, for example, the order of the roads on which the vehicle V travels. The traveling track means a position where the vehicle V moves on the road specified by the traveling route, and if the vehicle V is traveling on a one-lane road, the traveling track is determined by the position in the road width direction such as the left side, the center, and the right side. On a road having a plurality of lanes, the traveling track can be further distinguished by the lane.

<Reduction of occupant shaking>
Depending on the condition of the traveling path, the vehicle V vibrates up and down, and the occupants of the vehicle V also vibrate. Such shaking affects the ride quality of the occupants. As a measure for reducing the vibration of the vehicle V during automatic driving, it is conceivable to set the traveling track of the vehicle V so as to bypass the undulations on the traveling path. However, if any undulations are bypassed, the traveling track of the vehicle is unnecessarily changed, and the control becomes complicated.

This embodiment focuses on the fact that the degree of shaking of the occupant does not depend only on the vibration of the vehicle V but also on the state of the occupant, etc., and not only the vibration of the vehicle V but also the state of the occupant. Set the traveling track in consideration of such factors. As a result, it is possible to set a traveling track that contributes to the improvement of the ride quality of the occupant while avoiding the unnecessary change of the traveling track. Hereinafter, a specific description will be given.

<Generation of occupant information>
In the case of the present embodiment, the cameras 29a to 29d detect the posture, action, or attribute of the occupant seated on the seat. FIG. 2B is a flowchart showing an example of processing related to the generation of occupant information, and shows an example of processing that the ECU 29 periodically executes. In S11, the detection results (captured images) of the cameras 29a to 29d are acquired, and in S12, the occupant information is generated from the acquired captured images. Of the occupant information, the occupant's condition can be specified according to a predetermined classification.

3 (A) to 3 (D) show examples of occupant postures and classifications. FIG. 3A shows an example of a standard posture. The occupant 100 is seated on the seat surface of the seat 101 in a well-balanced manner and is in contact with the backrest of the seat 101. In FIG. 3B, the occupant 100 holds the handrail 102 in the vehicle while taking a standard posture. According to the posture of FIG. 3 (B), since the number of support points of the body is larger than that of the example of FIG. 3 (A), the posture of the occupant 100 is more stable and the posture of the occupant 100 is more stable with respect to the vibration of the vehicle V. It is considered that the occupant's shaking is smaller than that of the posture of.

FIG. 3C shows an example in which the posture of the occupant is unstable. FIG. 3C illustrates a posture in which the occupant bends his upper body forward and his arms extend downward. In the figure, the broken line shows the standard posture before the posture change. According to the posture of FIG. 3 (C), since the support points of the body are smaller than those of the example of FIG. 3 (A), the posture of the occupant 100 becomes unstable, and the posture of the occupant 100 becomes unstable with respect to the vibration of the vehicle V (A). It is considered that the occupant's shaking is larger than that of the posture of. The postures of FIGS. 3 (A) and 3 (C) can be distinguished by, for example, the inclination angle θ of the upper body. FIG. 3D shows an example in which the posture of the occupant is more unstable. FIG. 3D shows a posture in which the occupant twists his upper body and extends his arms to the rear seat. According to the posture of FIG. 3 (D), it is considered that the occupant's vibration becomes larger than the posture of FIG. 3 (C) with respect to the vibration of the vehicle V.

4 (A) to 4 (D) show examples of occupant actions and classification. FIG. 4 (A) shows an example of a standard action (doing nothing). Crew 100 is awake, although he has not taken any special action such as looking out of the car. FIG. 4B shows a state in which the occupant 100 is sleeping. In this embodiment, sleep is classified as one of the actions of the occupants. According to the posture of FIG. 4 (B), since the occupant 100 is less conscious of balancing than the example of FIG. 4 (A), it is considered that the occupant 100 sways more with respect to the vibration of the vehicle V. On the other hand, since the occupant 100 is less conscious, it is considered that the discomfort to the shaking is lower than that in the example of FIG. 4 (A).

FIG. 4C shows a state in which the occupant 100 is reading the magazine 103. According to the posture of FIG. 4 (C), since the consciousness of the occupant 100 is directed to the magazine 103 rather than the balance of the body as compared with the example of FIG. 4 (A), the occupant 100 sways slightly with respect to the vibration of the vehicle V. It is thought that it will grow to. On the other hand, when the vehicle V vibrates, the magazine 103 becomes difficult to read, so that the discomfort of the occupant 100 due to the shaking is considered to be higher than that in the example of FIG. 4 (A).

FIG. 4C shows a state in which the occupant 100 is reading the magazine 103. According to the posture of FIG. 4C, the consciousness of the occupant 100 is directed toward the magazine 103 rather than the balance of the body as compared with the example of FIG. 4A, so that the occupant 100 sways slightly with respect to the vibration of the vehicle V. It is thought that it will grow to. On the other hand, when the vehicle V vibrates, the magazine 103 becomes difficult to read, so that the discomfort of the occupant 100 due to the shaking is considered to be higher than that in the example of FIG. 4 (A).

FIG. 4D shows a state in which the occupant 100 is operating the notebook computer 104. According to the posture of FIG. 4D, the consciousness of the occupant 100 is directed toward the notebook computer 104 rather than the balance of the body as compared with the example of FIG. 4A, so that the occupant 100 sways with respect to the vibration of the vehicle V. It is expected to be slightly larger. On the other hand, when the vehicle V vibrates, it becomes difficult to operate the notebook computer 104, so that the discomfort of the occupant 100 due to the shaking is considered to be higher than in the examples of FIGS. 4 (A) and 4 (C).

In addition to the state of the occupant, the difference in the attributes of the occupant may cause the difference in the occupant's vibration with respect to the vibration of the vehicle V. For example, a occupant with a large physique may shake less than an occupant with a small physique. Elderly people may also shake more than young people.

As described above, even if the vibration of the vehicle V is the same, it is considered that the degree of shaking caused to the occupant differs depending on the posture of the occupant. Therefore, by setting the traveling track in consideration of not only the vibration of the vehicle V but also the condition and attributes of the occupant, the traveling track is prevented from being changed unnecessarily, and the traveling contributes to the improvement of the riding comfort of the occupant. It is possible to set the trajectory.

<Detection of road condition>
The detection of the state of the traveling path will be described. FIG. 2C is a flowchart showing an example of processing related to detection of the state of the traveling path ahead of the vehicle V in the traveling direction, and shows an example of processing periodically executed by the ECU 21. In S21, the detection results of the cameras 31A and 31B and the rider 32A are acquired, and in S22, road surface condition information indicating the state of the traveling road is generated from the acquired detection results. The road surface condition information of the present embodiment is information indicating the unevenness of the traveling path on three-dimensional coordinates. 5 (A) and 5 (B) are explanatory views thereof.

FIG. 5A shows an example of the detection result of the traveling path ahead of the vehicle V in the traveling direction, and is a diagram schematically showing the captured images of the cameras 31A and 31B, for example. The structure 111 exists in the traveling path 110. The structure 111 is, for example, a manhole, which is raised on the traveling path 110 to cause unevenness. The state information is configured as, for example, numerical information on the unevenness of the road surface in the road width direction at an arbitrary position (each position in front of the traveling direction) in the extending direction of the traveling road 110. FIG. 5B shows an example of state information at the position Pk of FIG. 5A. It is shown that the road surface is largely convex upward at the position of the structure 111 and is substantially flat in other parts in the road width direction.

With such road surface condition information, the unevenness of the road surface when traveling on a specific traveling track can be specified, and the vibration of the vehicle V can be estimated.

<Example of running track setting>
An example of setting a traveling track will be described. FIG. 6 is a flowchart showing an example of the process, and shows an example of the process periodically executed by the ECU 20 during the automatic operation. The ECU 20 sets, for example, a traveling track to be traveled in a predetermined distance unit, and causes the vehicle V to travel on the set traveling track.

In S30, a candidate for a traveling track is set. Candidates for the traveling track can be, for example, an extension of the traveling track currently being traveled. FIG. 7A shows an example of a candidate for a traveling track. In the illustrated example, a traveling track L1 through which the left wheel passes and a traveling track R1 through which the right wheel passes are illustrated. The traveling tracks L1 and R1 are separated by the distance between the left and right wheels of the vehicle V, and these are combined to define the traveling track.

In S31 of FIG. 6, occupant information and vehicle information are acquired. The occupant information is the information generated by the process of FIG. 2 (B). The vehicle information is, for example, vehicle speed, vehicle type, and suspension information.

In S32 of FIG. 6, the degree of sway of the occupant when the candidate of the traveling track set in S30 is adopted is estimated. In this estimation, first, information on the unevenness of the traveling path along the candidate of the traveling track set in S30 is generated by using the road surface condition information. 7 (B) and 7 (C) show the unevenness of the traveling path in the traveling tracks L1 and R1 derived from the road surface condition information. Since there are two structures 111 on the traveling track L1, the road surface is convexly raised at the position corresponding to the structure 111. Then, the degree of shaking of the occupant is estimated based on the generated unevenness on the traveling track and the occupant information and the like.

FIG. 8A shows an example of estimating the degree of shaking of the occupant by artificial intelligence. In this example, the relationship between the state of the occupant and the unevenness on the traveling track and the degree of swaying of the occupant is specified in advance by machine learning using the teacher data, which is performed at the development stage of the vehicle V. Estimate the degree of occupant shaking using the learning results. Machine learning may be performed in parallel with the use of the vehicle V after sale.

FIG. 8A shows a machine learning architecture (network) showing a calculation algorithm for calculating the degree of sway of the occupant from the state of the occupant and the unevenness on the traveling track. There are no restrictions on the machine learning method, but the example in the figure illustrates the case of deep learning.

The example of FIG. 8A shows an input layer LY1, an intermediate layer (hidden layer) LY2, and an output layer LY3. The input layer LY1 exemplifies occupant information, vehicle information, and unevenness on the traveling tracks L1 and R1 illustrated in FIGS. 7 (A) to 7 (C) as input data. The occupant information as input data includes, for example, the occupant's state. The occupant information as input data may include the above-mentioned occupant attributes. The state of the occupant may be only the posture of the occupant, or only the action of the occupant, or may be a combination of the attitude of the occupant and the action of the occupant.

The vehicle information as input data includes, for example, a vehicle speed. The vehicle speed may be the vehicle speed of the vehicle V at the time of estimation, or may be the estimated vehicle speed at the time of traveling in the sections of the traveling tracks L1 and R1. The vehicle information as input data may include vehicle type and suspension information in addition to the vehicle speed. As the suspension information, for example, when the suspension performance is variable, the input data may include information indicating the suspension performance of the vehicle V at the time of estimation. By including such vehicle information in the input data, it is possible to improve the estimation accuracy of the degree of shaking of the occupant. The input data can be used as a function of time. In that case, it is assumed that the state of the occupant and the vehicle speed, which are the input data, are maintained constant, and the unevenness on the traveling tracks L1 and R1 is specified by the vehicle speed and time. It may be calculated as the amount of unevenness at a position on the traveling direction.

The output layer LY3 outputs the degree of shaking of the occupant as output data. In the present embodiment, the degree of sway of the occupant is the maximum amount of displacement of the occupant in the vertical direction when the candidate of the traveling track set in S31 is traveled. However, the degree of shaking may be the maximum amount of displacement of the occupant in the left-right direction or the front-rear direction. The degree of shaking may also be the maximum displacement of the occupant per unit time. The degree of shaking may also be the number of times the amount of displacement of the occupant per unit time is equal to or greater than a predetermined amount.

The intermediate layer LY2 is formed from, for example, a plurality of LY2-1 to LY2-n layers. For example, the connection relationship between the front layer and the rear layer and the weighting coefficient for the data are set for each layer. As the layer structure, for example, a plurality of combinations of a folding layer and a pooling layer may be included. The intermediate layer LY2 may be a forward propagation type network in which data flows in one direction from the input side to the output side, or may be a neural network (for example, RNN, LSTM) that depends on the time series of the input data.

In this way, it is possible to estimate the degree of sway of the occupant that reflects the state of the occupant when the candidate of the traveling track is traveled.

8 (B) and 8 (C) are diagrams for explaining an example of another estimation method of the degree of shaking of the occupant. In this estimation example, the vibration of the vehicle V is estimated from the unevenness of the traveling path, and the degree of shaking of the occupant is estimated by multiplying by a coefficient according to the occupant information (here, the state of the occupant). FIG. 8B shows a method of estimating the vibration of the vehicle V from the unevenness of the traveling path.

In this estimation method, the difference H of the unevenness at the distance obtained by multiplying the vehicle speed v by the unit time t is obtained by using the information of the unevenness of the traveling path in the traveling tracks L1 and R1 illustrated in FIGS. 7 (B) and 7 (C). , The basic value of the vibration amplitude of the vehicle V at that position, and this is multiplied by a coefficient related to the suspension characteristics of the vehicle V to obtain the estimated vibration value of the vehicle V, and further multiplied by a conversion coefficient related to the state of the occupant. Calculate the degree of shaking of the occupant.

FIG. 8C exemplifies an example of deriving the conversion coefficient with respect to the state of the occupant. In this example, the conversion coefficient of the occupant's condition is set in four stages of "stable", "standard", "slightly unstable", and "unstable" based on the occupant's posture. In the example of FIGS. 3 (A) to 3 (D), "standard" corresponds to the posture of FIG. 3 (A), and the conversion coefficient is 1.0. That is, it is estimated that the vibration of the vehicle V equals the vibration of the occupant to the vibration of the vehicle V. “Stable” corresponds to the posture shown in FIG. 3 (B), and the conversion coefficient is 0.8. That is, the degree of vibration of the occupant is estimated to be smaller than the vibration of the vehicle V. “Slightly unstable” corresponds to the posture shown in FIG. 3C, and the conversion coefficient is 1.4. That is, the degree of vibration of the occupant is estimated to be larger than the vibration of the vehicle V. “Unstable” corresponds to the posture shown in FIG. 3 (D), and the conversion coefficient is 1.8. That is, the degree of vibration of the occupant is estimated to be larger than the vibration of the vehicle V.

According to the estimation method illustrated above, the degree of shaking of the occupant is estimated in S32 of FIG. The degree of shaking of the occupant may be the degree of shaking of the entire body of the occupant, or may be a part of the occupant's body (for example, the head or the upper body). When there are a plurality of occupants in the vehicle V, the state of the occupants is detected for each occupant and the degree of shaking is estimated. Then, the traveling track may be set based on the largest degree of shaking of each occupant. Alternatively, the traveling track may be set based on the average value of the degree of shaking of each occupant.

Returning to FIG. 6, in S33, it is determined whether or not the degree of sway of the occupant estimated in S32 satisfies a predetermined allowable condition. The permissible condition is, for example, the upper limit of the degree of shaking of the occupant. If the permissible condition is satisfied, the process of S34 is executed. In S34, the candidate of the current traveling track is set as the traveling track that actually travels.

If the permissible condition is not satisfied, a process of changing the candidate of the traveling track is performed. First, the process of S35 is executed, and it is determined whether or not the number of changes has reached the specified number of times. When the specified number of times is reached, the process of S37 is executed, and when the specified number of times is not reached, the process of S36 is executed.

In S36, the specified number of times is added by one, and the candidates for the traveling track are changed. In the example of FIG. 7A, if the current running track candidate is a set of L1 and R1, it is changed to another set of running tracks L2 and R2 and a set of running tracks L3 and R3. Orbit. The candidate of the traveling track can be changed, for example, by moving the traveling track by a predetermined distance in the road width direction. The specified number of times is, for example, about 3 to 6 times. When the candidate of the traveling track is changed, the process returns to S32 and the same process is repeated.

In S37, the candidate having the smallest degree of sway of the occupant among the candidates for the traveling track so far is set as the traveling track that actually travels. It does not meet the permissible conditions, but selects the best running track among them.

As described above, one traveling track is set, and the vehicle V travels on the traveling track. By setting the traveling track based on the occupant information, a candidate for the traveling track is selected when the occupant's shaking degree is substantially small with respect to the vibration of the vehicle V, while the traveling track candidate is selected when the occupant's shaking degree is large. Another candidate is selected. As a result, it is possible to set a traveling track that contributes to the improvement of the ride quality of the occupant while avoiding the unnecessary change of the traveling track.

<Second embodiment>
Regarding the setting of the traveling track, in the first embodiment, one candidate is first determined, the degree of shaking of the occupant is estimated, it is determined whether or not the allowable condition is satisfied, and if it is not satisfied, it is changed to another candidate. did. In the present embodiment, a plurality of candidates are determined from the beginning, the degree of sway of the occupant is estimated for each candidate, and the best candidate is set as a traveling track that actually travels. FIG. 9 is a flowchart showing a processing example instead of the processing example of FIG.

In S40, candidates for a plurality of traveling tracks are set. For example, in the example of FIG. 7A, a set of traveling tracks L1, R1, a set of L2, R2, and a set of L3, R3 are set as candidates. In S41, occupant information and vehicle information are acquired. In S42, the degree of swaying of the occupant is estimated for each candidate set in S40. As the estimation method, the same estimation method as in the first embodiment can be adopted. In S43, the candidate of the traveling track with the smallest degree of shaking estimated in S42 is set as the traveling track that actually travels.

According to this embodiment, the traveling track having the smallest degree of shaking can be selected in a relatively short time.

<Third Embodiment>
In the first embodiment, the allowable condition of S33 is a fixed condition, but it may be a condition that is changed according to the actions of the occupant. In the present embodiment, among the occupant information, the posture of the occupant is used for estimating the shaking condition of the occupant, and the action of the occupant is used for setting the allowable condition. By changing the permissible conditions according to the actions of the occupants, it is possible to set the traveling track that reflects the actions of the occupants.

FIG. 10A is a flowchart showing an example of a process related to generation of occupant information instead of FIG. 2B, and shows an example of a process periodically executed by the ECU 29. The processing example of FIG. 10A is characterized in that it distinguishes between the posture and the action of the occupant.

In S51, the detection results (captured images) of the cameras 29a to 29d are acquired, and in S52, the posture of the occupant is specified from the acquired captured images. Further, in S53, the action of the occupant is specified from the acquired captured image. The posture and behavior of the occupant can be specified according to a predetermined classification as illustrated in FIGS. 3 (A) to 3 (D) and FIGS. 4 (A) to 4 (D). ..

FIG. 10B is a flowchart showing an example of a process of setting an allowable condition for the degree of shaking of the occupant, and shows an example of a process executed periodically by the ECU 20. In S61, the specific result of the occupant's action is acquired from the ECU 29. In S62, the permissible condition is set based on the specific result of the occupant's action acquired in S61. As an example, the permissible condition is set by multiplying the basic value of the upper limit of the degree of shaking of the occupant by the conversion coefficient related to the action of the occupant. FIG. 10C illustrates an example of deriving the conversion coefficient.

In this example, the actions of the occupants are classified into five categories: "doing nothing", "listening to music", "sleeping", "watching / reading movies", and "working", and conversion factors are set for each. .. “Doing nothing” corresponds to the act shown in FIG. 4 (A), and the conversion coefficient is 1.0. That is, the permissible condition is set to the basic value. "Music appreciation" is a case where the occupant is listening to music or the like, and the conversion coefficient is 1.2. Since it is considered that the shaking is not so noticeable while listening to music, the permissible condition is set in the direction to allow the shaking. “Sleep” corresponds to the act shown in FIG. 4 (B), and is the case where the occupant is sleeping, and the conversion coefficient is 1.5. Since it is considered that the shaking is not so noticeable during sleep, the permissible condition is set in the direction of further allowing the shaking.

“Video viewing / reading” corresponds to the act shown in FIG. 4 (C) or a similar act, and the conversion coefficient is 0.7. During video viewing / reading, the viewpoint may not be stable due to shaking, which may be annoying. Therefore, the permissible condition is set in a direction that does not allow shaking. “Work” corresponds to the act shown in FIG. 4 (D) or a similar act, and the conversion coefficient is 0.5. During work such as moving the fingertips, it is considered that the fingertips are shaken due to the shaking, so the permissible condition is set in a direction that further does not allow the shaking.

The allowable condition is set by the above. The traveling track setting process in the present embodiment may be the same as the process illustrated in FIG. In this case, the specific result of the posture of the occupant may be used for estimating the degree of shaking of the occupant in S32, and the allowable condition set in the process of FIG. 10B may be used as the allowable condition in S33.

When there are a plurality of occupants in the vehicle V, the state of the occupants is detected for each occupant, allowable conditions are set for each occupant, and the degree of shaking is estimated. Then, when the degree of shaking does not satisfy the permissible condition for any of the occupants, the candidate of the traveling track is changed. For all occupants, if there is no candidate for a traveling track whose degree of shaking satisfies the allowable condition, the best candidate may be set as the traveling track that actually travels. Alternatively, while the permissible condition is calculated for each occupant, the average value may be set as a common permissible condition for all occupants. Then, the traveling track may be set based on the largest shaking degree of each occupant, or the traveling track may be set based on the average value of the shaking degree of each occupant.

Further, as the traveling track setting process in the present embodiment, when a plurality of candidates are determined from the beginning and the degree of sway of the occupant is estimated for each candidate as in the second embodiment, the processing example of FIG. 11 may be adopted. it can.

In S70, candidates for a plurality of traveling tracks are set. For example, in the example of FIG. 7A, a set of traveling tracks L1, R1, a set of L2, R2, and a set of L3, R3 are set as candidates. In S71, occupant information and vehicle information are acquired. In S72, the degree of swaying of the occupant is estimated for each candidate set in S70. As the estimation method, the same estimation method as in the first embodiment can be adopted.

In S73, it is determined whether or not there is a candidate among the plurality of candidates for the traveling track that satisfies the degree of shaking estimated in S72 for the permissible condition set in the process of FIG. 10B. If there is a candidate satisfying the permissible condition, the process of S74 is executed, and if not, the process of S75 is executed.

In S74, if there is only one candidate satisfying the permissible condition, that candidate is set as a traveling track that actually travels. If there are a plurality of candidates satisfying the permissible conditions, one of them is set as the actual traveling track. At that time, the candidate of the traveling track with the minimum estimated degree of shaking may be selected, but the candidate of the traveling track that is the best in terms of other requirements such as a short mileage may be selected. Good.

In S75, among the plurality of running track candidates set in S70, the candidate with the smallest degree of shaking estimated in S72 is set as the running track that actually runs.

When there are a plurality of occupants in the vehicle V, the state of the occupants is detected for each occupant, allowable conditions are set for each occupant, and the degree of shaking is estimated. Then, in S73, if it is determined that the degree of shaking does not satisfy the permissible condition for any of the occupants, the processing of S75 is executed, and if it is determined that all the occupants satisfy the permissible degree of shaking, S74. The process may be executed. Alternatively, while the permissible condition is calculated for each occupant, the average value may be set as a common permissible condition for all occupants. Then, the traveling track may be set based on the largest shaking degree of each occupant, or the traveling track may be set based on the average value of the shaking degree of each occupant.

<Fourth Embodiment>
When the permissible conditions are changed according to the actions of the occupant as in the third embodiment, the vibration of the vehicle V is used as the occupant's sway degree without considering the occupant's posture in the estimation of the occupant's sway degree (S32, S42). You may estimate. This is because the condition of the occupant can be reflected in the setting of the traveling track by changing the allowable condition according to the action of the occupant.

<Fifth Embodiment>
When actually traveling on the set traveling track, the actual degree of shaking of the occupant may be larger than the estimated result. In this case, the traveling control may be changed so that the degree of shaking of the occupant is reduced.

FIG. 12A is a flowchart showing a processing example for detecting the actual degree of shaking of the occupant. For example, after setting the traveling track, the ECU 29 executes the process shown in the figure while traveling on the traveling track. In S81, the detection results (captured images) of the cameras 29a to 29d are acquired, and in S82, the actual degree of shaking of the occupant is specified from the acquired captured images. The degree of shaking of the occupant is, for example, the maximum amount of displacement of the occupant in the vertical direction.

FIG. 12B is a flowchart showing an example of traveling control change processing based on the actual degree of shaking of the occupant. For example, after setting the traveling track, the ECU 20 executes the process shown in the figure while traveling on the traveling track.

In S81, information on the degree of shaking of the occupant specified in S82 is acquired. In S82, it is determined whether or not the degree of shaking of the occupant acquired in S81 satisfies the allowable condition. The permissible condition is the upper limit of the degree of shaking of the occupant. The permissible conditions here may be the same as or different from the permissible conditions (S33, etc.) at the time of setting the traveling track.

If the allowable condition is not satisfied, the travel control change process is performed in S83, and if it is satisfied, the process ends without changing the travel control. As the traveling control change processing of S83, for example, a change of the traveling track can be mentioned. The travel track to be changed may be a travel track selected from the travel tracks (S30, S36, S40, S70) that are candidates during the travel track setting process, and may be, for example, the next travel track. There may be. As the travel control change process of S83, for example, deceleration of the vehicle V can be mentioned. As the vehicle speed of the vehicle V decreases, the vibration of the vehicle V becomes gentle, and the degree of shaking of the occupant may be reduced. The travel control change process of S83 may be a change other than a change of the travel track or deceleration, or may be a combination of a plurality of types of control changes.

Further, in the present embodiment, the traveling control change processing is performed when the degree of shaking of the occupant does not satisfy the permissible condition, but when the permissible condition is satisfied, the traveling control such as acceleration of the vehicle V is changed. You may go.

<Summary of Embodiment>
The above embodiment discloses at least the following vehicle control device.

1. 1. The vehicle control device (1) of the above embodiment is
It is a vehicle control device that can drive a vehicle by automatic driving.
State detecting means (31A, 31B, 32A) for detecting the state of the traveling path in the traveling direction of the vehicle, and
The first acquisition means (20) for acquiring information on the occupants of the vehicle, and
The second acquisition means (20) for acquiring the vehicle information and
Based on the detection result of the state detecting means, the information of the occupant acquired by the first acquisition means, and the information of the vehicle acquired by the second acquisition means, the traveling track candidate on the traveling road is selected as the vehicle. Estimating means (20) for estimating the degree of shaking of the occupants of the vehicle when the vehicle travels, and
A traveling track setting means (20) for setting a traveling track on the traveling path based on the estimation result of the estimation means is provided.
According to this embodiment, it is possible to provide a device capable of setting a traveling track that contributes to the improvement of the ride quality of the occupant while avoiding the unnecessary change of the traveling track.

2. In the above embodiment
Among the plurality of travel track candidates, the travel track setting means sets the travel track candidate estimated by the estimation means to have the smallest degree of shaking of the occupant as the travel track (S43).
According to this embodiment, it is possible to select a traveling track having the minimum degree of shaking of the occupant in a relatively short time.

3. 3. In the above embodiment
The first acquisition means acquires at least information on the posture of the occupant as information on the occupant.
According to this embodiment, the degree of shaking caused by the posture of the occupant can be reflected in the setting of the traveling track.

4. The vehicle control device of the above embodiment is
A permissible condition setting means (20, S62) for setting the permissible condition of the degree of shaking of the occupant of the vehicle is provided.
The permissible condition setting means sets the permissible condition based on the information of the occupant detected by the first acquisition means.
The traveling track setting means sets a traveling track based on whether or not the estimation result of the estimation means satisfies the allowable condition.
According to this embodiment, it is possible to determine the magnitude of the degree of shaking according to the actions of the occupants and set the traveling track.

5. In the above embodiment
When there are a plurality of occupants, the first acquisition means acquires the information of each occupant, and the estimation means estimates the degree of shaking for each occupant.
The traveling track setting means sets the traveling track based on the largest degree of shaking among the estimation results of the estimation means for each occupant.
According to this embodiment, it is possible to set a traveling track that is comfortable for all occupants.

6. In the above embodiment
The state of the traveling path is an uneven state of the traveling path.
According to this embodiment, it is possible to set a traveling track with a small degree of swaying of the occupant due to the unevenness of the road surface.

7. The vehicle control device of the above embodiment is
The shaking detecting means (29a-29d) for detecting the degree of shaking of the occupant of the vehicle while the vehicle is traveling on the traveling track set by the traveling track setting means.
A changing means (20, S83) for changing the traveling control of the vehicle based on the detection result of the shaking detecting means is provided.
According to this embodiment, when the actual degree of shaking is larger than the estimated degree of shaking, it is possible to reduce the degree of shaking of the occupant by the traveling control.

8. In the above embodiment
The changing means changes at least one of a traveling track and a vehicle speed as a change of the traveling control.
According to this embodiment, when the actual degree of shaking is larger than the estimated degree of shaking, it is possible to reduce the degree of shaking of the occupant by the traveling control.

9. In the above embodiment
The second acquisition means acquires at least information on the vehicle speed of the vehicle as information on the vehicle.
According to this embodiment, the accuracy of estimating the degree of shaking of the occupant can be improved.

Although the embodiments of the invention have been described above, the invention is not limited to the above-described embodiments, and various modifications and changes can be made within the scope of the gist of the invention.

V vehicle, 1 control device, 31A and 31B detection unit, 32A detection unit, 29a to 29d detection unit

Claims (9)

It is a vehicle control device that can drive a vehicle by automatic driving.
A state detecting means for detecting the state of the traveling path in the traveling direction of the vehicle, and
The first acquisition means for acquiring the information of the occupants of the vehicle,
A second acquisition means for acquiring the vehicle information, and
Based on the detection result of the state detecting means, the information of the occupant acquired by the first acquisition means, and the information of the vehicle acquired by the second acquisition means, the traveling track candidate on the traveling road is selected as the vehicle. And an estimation means for estimating the degree of shaking of the occupants of the vehicle when the vehicle travels.
A traveling track setting means for setting a traveling track on the traveling path based on the estimation result of the estimating means is provided.
A vehicle control device characterized by this. The vehicle control device according to claim 1.
The traveling track setting means sets the traveling track candidate, which is estimated by the estimating means to have the smallest degree of shaking of the occupant, as the traveling track among the plurality of traveling track candidates.
A vehicle control device characterized by this. The vehicle control device according to claim 1.
The first acquisition means acquires at least information on the posture of the occupant as information on the occupant.
A vehicle control device characterized by this. The vehicle control device according to claim 1.
A means for setting an allowable condition for setting an allowable condition for the degree of shaking of the occupant of the vehicle is provided.
The permissible condition setting means sets the permissible condition based on the information of the occupant acquired by the first acquisition means.
The traveling track setting means sets a traveling track based on whether or not the estimation result of the estimation means satisfies the allowable condition.
A vehicle control device characterized by this. The vehicle control device according to claim 1.
When there are a plurality of occupants, the first acquisition means acquires the information of each occupant, and the estimation means estimates the degree of shaking for each occupant.
The traveling track setting means sets the traveling track based on the largest degree of shaking among the estimation results of the estimation means for each occupant.
A vehicle control device characterized by this. The vehicle control device according to claim 1.
The state of the running path is an uneven state of the running path.
A vehicle control device characterized by this. The vehicle control device according to claim 1.
A shaking detecting means for detecting the degree of shaking of the occupant of the vehicle while the vehicle is traveling on the traveling track set by the traveling track setting means.
A changing means for changing the traveling control of the vehicle based on the detection result of the shaking detecting means is provided.
A vehicle control device characterized by this. The vehicle control device according to claim 7.
The changing means changes at least one of a traveling track and a vehicle speed as a change of the traveling control.
A vehicle control device characterized by this. The vehicle control device according to claim 1.
The second acquisition means acquires at least information on the vehicle speed of the vehicle as information on the vehicle.
A vehicle control device characterized by this.

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