JP2021113041A - Automatic operation assistance device - Google Patents

Abstract

To provide an automatic operation assistance device that is able to specifically and sequentially calculate automatic operation control parameters for a vehicle in order to bring emotion of an occupant such as a driver or a passenger close to an ideal state.SOLUTION: An automatic drive assistance device comprises: an occupant feeling learning unit that constructs an occupant feeling model for estimating an emotion of an occupant from an operating state of a vehicle, based on information on the operating state of the vehicle and information on the emotion of the occupant; and a control parameter setting unit that calculates an ideal operating state of the vehicle, in which the emotion of the occupant approaches a target emotion, based on the occupant feeling model and sets a control parameter for automatic operation control, based on the ideal operating state. The control parameter setting unit inputs a plurality of input values relating to an operating state of the vehicle into the occupant feeling model and sets the control parameter so that, among the input values input to the occupant feeling model, an input value at which the emotion of the occupant is closer to the target emotion than the current emotion is the ideal operating state of the vehicle.SELECTED DRAWING: Figure 3

Description

The present invention relates to an automatic driving support device.

In autonomous vehicles, a technique has been proposed in which negative emotions such as anxiety and discomfort are suppressed by reflecting the driving characteristics of occupants such as drivers and passengers in the driving control of the vehicle. For example, Patent Document 1 describes an individual server that learns a driver-specific individual driver model based on the driver's driving data, and an in-vehicle controller that is provided in the driver's vehicle and executes a predetermined vehicle control process. The personal server is equipped with a recommendation engine that instructs the in-vehicle controller to execute the recommended processing, and the recommendation engine analyzes the current driver's emotional state based on the driver's voice data included in the driving data. A vehicle driving support system that determines recommended processing according to the analyzed emotional state based on an individual driver model is disclosed.

Further, in Patent Document 2, the emotion of the driver or the passenger is estimated by using the biological information acquired from the biological sensor that measures the biological information of the driver or the passenger of the vehicle, and the emotion of the vehicle is estimated based on the estimated emotion. An electronic control device for controlling traveling is disclosed.

JP-A-2018-169704 JP-A-2017-136922

However, in Patent Document 1, the recommendation engine derives an appropriate recommended process, and selects and outputs an appropriate recommendation signal from the vehicle interior space recommendation signal, the traveling route recommendation signal, and the information presentation recommendation signal according to the situation. Although it is described that the control parameters are to be calculated, the procedure for specifically calculating the control parameters is not described. Patent Document 2 also does not describe a procedure for specifically calculating parameters for controlling the running of a vehicle based on an estimated emotion. In order to execute the automatic driving control of the vehicle, the control parameters must be calculated sequentially, and a method of specifically and sequentially calculating the control parameters is required.

The present invention has been made in view of the above problems, and an object of the present invention is to specifically set automatic driving control parameters of a vehicle for bringing the emotions of a occupant such as a driver or a passenger closer to an ideal state. The purpose is to provide an automatic driving support device that can be calculated sequentially.

In order to solve the above problem, according to a certain viewpoint of the present invention, the occupant emotion model for estimating the occupant's emotion from the driving condition of the vehicle is constructed based on the information of the driving condition of the vehicle and the emotion of the occupant. Based on the learning unit and the occupant emotion model, the ideal driving state of the vehicle in which the occupant's emotion approaches the target emotion is calculated, and the control parameter setting unit for setting the control parameter for automatic driving control based on the ideal driving state. The control parameter setting unit inputs a plurality of input values related to the driving state of the vehicle into the occupant emotion model, and among the input values input to the occupant emotion model, the occupant's emotion is higher than the current emotion. An automatic driving support device is provided that sets control parameters with an input value approaching the target emotion as the ideal driving state of the vehicle.

The occupant emotion model is an occupant emotion model that estimates the occupant's emotions based on the information on the surrounding environment of the vehicle and the information on the driving state of the vehicle, and the control parameter setting unit is the current surrounding environment of the vehicle. The control parameter may be set by finding the ideal driving state of the vehicle in the surrounding environment corresponding to.

In addition, the occupant emotion learning unit accumulates a data set that links the estimated occupant emotion information, the information on the surrounding environment of the vehicle, and the information on the driving state of the vehicle. From the accumulated data set, the driving state of the vehicle approaching the target emotion in the surrounding environment corresponding to the current surrounding environment of the vehicle is extracted, and a plurality of input values are input based on the extracted vehicle driving state information. May be created.

Further, the control parameter setting unit may set a plurality of input values between the value of the predetermined data item in the driving state of the extracted vehicle and the value of the predetermined data item in the driving state of the current vehicle.

Further, a predetermined data item in the driving state of the vehicle includes a plurality of data items, at least one of the plurality of data items can be set as a priority item by the user, and the control parameter setting unit is set by the user. If there is a priority item, the value of the priority item among the data items of multiple input values to be input to the occupant emotion model is set to the target emotion in the surrounding environment corresponding to the current surrounding environment of the vehicle. It may be fixed to the value extracted as the driving state of the approaching vehicle, and a plurality of input values may be created for other data items.

In addition, when the control parameter setting unit determines that the occupant's emotions when the automatic driving control is executed by the control parameters obtained by fixing the priority item values are worse than the occupant's emotions calculated using the occupant emotion model. To fix at least one data item that has a large effect on the emotions of the occupant to the value extracted as the driving state of the vehicle approaching the target emotion in the surrounding environment corresponding to the current surrounding environment of the vehicle. It may be presented to the user.

Further, a predetermined data item in the driving state of the vehicle includes a plurality of data items, and the occupant emotion learning unit extracts at least one data item having a large influence on the occupant's emotion based on the accumulated data set. The control parameter setting unit fixes at least one data item that has a large effect on the emotions of the occupants to the value extracted as the driving state of the vehicle that approaches the target emotion in the surrounding environment corresponding to the current surrounding environment of the vehicle. You may obtain a plurality of input values and set control parameters.

Further, the control parameter setting unit may set the number of a plurality of input values to be input to the occupant emotion model based on at least one of the processing speed of the arithmetic processing unit that performs the calculation and the update frequency of the control parameters. ..

As described above, according to the present invention, it is possible to specifically calculate the automatic driving control parameters of the vehicle for bringing the emotions of the occupants such as the driver and passengers closer to the ideal state, and the emotions of the occupants are ideal. It is possible to realize automatic operation control that can approach the state.

It is a block diagram which shows the structural example of the automatic driving support device which concerns on embodiment of this invention. It is explanatory drawing which shows an example of an occupant feeling model. It is explanatory drawing which shows the algorithm which sets the control parameter of a vehicle using an occupant feeling model. It is a flowchart which shows the operation example of the automatic driving support device which concerns on this embodiment. It is a flowchart which shows the occupant emotion model learning process by the automatic driving support device which concerns on the same embodiment. It is a flowchart which shows the driving control processing based on the occupant feeling by the automatic driving support device which concerns on the same embodiment.

Hereinafter, preferred embodiments of the present invention will be described in detail with reference to the accompanying drawings. In the present specification and the drawings, components having substantially the same functional configuration are designated by the same reference numerals, so that duplicate description will be omitted.

<1. Configuration example of automatic driving support device>
First, a configuration example of the automatic driving support device according to the embodiment of the present invention will be described. FIG. 1 is a block diagram showing a configuration example of the automatic driving support device 10 according to the present embodiment.

The automatic driving support device 10 is mounted on the vehicle, detects information on the occupants of the vehicle, the driving state of the vehicle, and the surrounding environment of the vehicle, and executes control to support the driving of the vehicle using the various detected information. It is configured to do. The automatic driving support device 10 includes an occupant detection unit 41, a vehicle information detection unit 43, an input unit 45, an ambient environment detection unit 47, a biological information detection unit 49, an electronic control device 50, a communication device 31, and a vehicle travel control device 35. ing.

(1-1. Crew detection unit)
The occupant detection unit 41 is provided inside the vehicle and detects occupants of the vehicle such as a driver and a passenger. The electronic control device 50 is configured to be able to acquire the information detected by the occupant detection unit 41. The occupant detection unit 41 may at least detect the presence of an occupant in the vehicle, or may identify individual occupants. In the present embodiment, the occupant detection unit 41 includes a camera that photographs the interior of the vehicle and an image processing device that identifies individual occupants based on the image pickup data acquired by the camera. The image processing device calculates the feature amount of the face of a person by performing image processing on the captured data, and identifies each person. The occupant detection unit 41 may specify the position where the detected occupant sits. The electronic control device 50 uses the acquired occupant information for learning the emotions of individual occupants.

(1-2. Vehicle information detection unit)
The vehicle information detection unit 43 detects information on the driving state of the vehicle. The driving state of the vehicle includes the operating state and behavior of the vehicle. The electronic control device 50 is configured to be able to acquire the information detected by the vehicle information detection unit 43. The vehicle information detection unit 43 detects information on vehicle behavior such as vehicle speed, acceleration, and yaw rate. The vehicle information detection unit 43 may include, for example, at least one of an engine speed sensor, a vehicle speed sensor, an acceleration sensor, and an angular velocity sensor. Further, the vehicle information detection unit 43 detects information on the operation state of the vehicle such as the accelerator operation amount, the brake operation amount, and the steering steering angle. The vehicle information detection unit 43 may include, for example, at least one of an accelerator position sensor, a brake stroke sensor, and a steering angle sensor. The electronic control device 50 uses the acquired vehicle information for learning the emotions of individual occupants.

(1-3. Input section)
The input unit 45 accepts input operations of the driver, passengers, and other users. In the present embodiment, the input unit 45 accepts an input operation for switching the operation mode to the manual operation mode or the automatic operation mode. Further, the input unit 45 accepts an input operation for setting a target occupant's emotion when setting a control parameter using the occupant's emotion model 63 when the operation mode is set to the automatic operation mode. As will be described later, in the present embodiment, positive and negative emotions are defined in four stages, and the emotions of the occupants are defined in a total of nine stages including the neutral emotions in between. Therefore, the occupant such as the driver sets the emotion of any level of the nine stages as the target emotion.

The input unit 45 is not particularly limited, and may be an appropriate input device such as a touch panel, a dial switch, or a button switch. Alternatively, the input unit 45 may be a device that accepts input by voice or gesture.

(1-4. Surrounding environment detection unit)
The surrounding environment detection unit 47 detects information on the surrounding environment of the vehicle. The electronic control device 50 is configured to be able to acquire the information detected by the ambient environment detection unit 47. The surrounding environment detection unit 47 detects a person, another vehicle, a bicycle, a building, other obstacles, etc. existing around the vehicle as information on the surrounding environment of the vehicle. In addition, the surrounding environment detection unit 47 detects the traveling position of the vehicle, the weather in the traveling area, the road surface condition, the sunshine condition, and the like. The ambient environment detection unit 47 is among detectors such as a camera that images the surroundings of the vehicle, a radar that detects an object around the vehicle, and a LiDAR that detects the distance and direction to an object around the vehicle. Includes at least one. Further, the surrounding environment detection unit 47 may include a communication device that acquires information from an external device of the vehicle such as vehicle-to-vehicle communication or road-to-vehicle communication. Further, the ambient environment detection unit 47 may include a detector that detects information related to road surface friction. The electronic control device 50 determines the surrounding environment using the acquired information on the surrounding environment.

(1-5. Biological information detection unit)
The biological information detection unit 49 includes one or a plurality of detection devices that detect information for estimating the emotions and sensibilities of the occupants. The electronic control device 50 is configured to be able to acquire the information detected by the occupant detection unit 41. The camera and image processing device constituting the occupant detection unit 41 may function as the biological information detection unit 49. For example, the image processing device can detect biological information such as the occupant's heartbeat, pulse, and body temperature based on the color change of the face image acquired by the camera. In addition, the biometric information detection unit 49 is used, for example, to measure a radio wave Doppler sensor for detecting the occupant's heartbeat, a non-wearable pulse sensor for detecting the occupant's pulse, and a driver's heartbeat or electrocardiogram. Electrodes embedded in the steering wheel, pressure measuring instruments embedded in the driver's seat to measure the seat pressure distribution while the occupant is seated, seat belt to measure the occupant's heart rate or breathing At least one of a device that detects changes in the position of the occupant, a TOF (Time of Flight) sensor that detects information on the position of the occupant (living body position), or a thermography that measures the surface temperature of the occupant's skin. May include one. Further, the occupant detection unit 41 may include a wearable detector such as a wearable device that is attached to the occupant and detects the biological information of the occupant.

(1-6. Communication device)
The communication device 31 is an interface for the electronic control device 50 to send and receive information to and from the external server 20. For example, the communication device 31 may be a communication interface that can access the server 20 via the mobile communication network. The communication device 31 is provided for communicating with an external server 20 in order to share the driving emotion database 61 accumulated in a certain vehicle with a plurality of vehicles, and is omitted when the driving emotion database 61 is not shared. It may have been done.

(1-7. Vehicle running control device)
The vehicle travel control device 35 executes vehicle travel control. The vehicle travel control device 35 includes one or more control devices that perform vehicle travel control, for example, the vehicle travel control device 35 includes an engine and power including one or more drive motors and transmissions. It includes a control device that controls the drive of a transmission mechanism, a steering system, a braking system, and the like. In the present embodiment, the vehicle travel control device 35 is configured to be capable of executing automatic driving control of the vehicle. When the driving mode is set to the automatic driving mode, the vehicle driving control device 35 automatically controls at least a part of the driving control of the vehicle without the driver's operation, and via the set driving route. Drive the vehicle to its destination.

Further, the vehicle travel control device 35 receives a command from the electronic control device 50 and executes vehicle travel control during the automatic driving mode. Specifically, the vehicle travel control device 35 executes automatic driving control of the vehicle by using the control parameters transmitted from the electronic control device 50.

(1-8. Electronic control device)
The electronic control device 50 includes, for example, an arithmetic processing device such as a CPU (Central Processing Unit) or an MPU (Micro Processing Unit), and a storage element such as a RAM (Random Access Memory) or a ROM (Read Only Memory). Will be done. The arithmetic processing unit executes various arithmetic processing by executing a program stored in the storage element. The electronic control device 50 is used in combination with a storage element or in place of a storage element, such as an HDD (Hard Disk Drive), a CD (Compact Disc), a DVD (Digital Versatile Disc), an SSD (Solid State Drive), or a USB (Universal). Serial Bus) A storage medium such as a flash or a storage device may be provided. A part or all of the electronic control device 50 may be configured by an updatable device such as firmware, or may be a program module or the like executed by a command from a CPU or the like.

The electronic control device 50 includes the occupant detection unit 41, the vehicle information detection unit 43, the input unit 45, and the surroundings directly or via a communication line such as CAN (Controller Area Network) or LIN (Local Inter-Net). It is connected to the environment detection unit 47, the biological information detection unit 49, and the vehicle travel control device 35.

In the present embodiment, the electronic control device 50 includes an operation mode setting unit 51, an ambient environment identification unit 53, an occupant emotion estimation unit 55, an occupant emotion learning unit 57, an emotion deterioration determination unit 59, a driving emotion database 61, and an occupant emotion model 63. And a control parameter setting unit 65 is provided. Of these, the operation mode setting unit 51, the surrounding environment identification unit 53, the occupant emotion estimation unit 55, the occupant emotion learning unit 57, the emotion deterioration determination unit 59, and the control parameter setting unit 65 are realized by executing a program by the arithmetic processing unit. It may be a function. Further, the driving emotion database 61 and the occupant emotion model 63 are composed of data stored in the storage unit.

(1-8-1. Operation mode setting unit)
The driving mode setting unit 51 switches the driving mode of the vehicle to the manual driving mode or the automatic driving mode based on the operation input signal transmitted from the input unit 45. The operation mode setting unit 51 may be configured so that the level of the automatic operation mode can be set. In the automatic driving support device 10 according to the present embodiment, the electronic control device 50 learns the emotions of the occupant while the vehicle is traveling in the manual driving mode, and constructs the occupant emotion model 63. On the other hand, the electronic control device 50 estimates the occupant's emotion using the occupant emotion model 63 while the vehicle is traveling in the automatic driving mode, and the occupant's emotion is closer to the target emotion than the current emotion. The ideal operating state of is calculated, and the control parameters for automatic operation control are set based on the ideal operating state.

(1-8-2. Surrounding environment identification part)
The surrounding environment specifying unit 53 identifies the surrounding environment of the vehicle based on the information on the surrounding environment transmitted from the surrounding environment detecting unit 47. Specifically, the surrounding environment identification unit 53 includes the position and size of the vehicle on the map, the position and size of other vehicles including oncoming vehicles, bicycles, pedestrians, buildings, and other obstacles, and these obstacles. Specify the distance between the vehicle and the relative speed between obstacles and the vehicle. The ambient environment specifying unit 53 identifies the ambient environment at predetermined time intervals according to the processing speed of the electronic control device 50.

(1-8-3. Crew Emotion Estimate Department)
The occupant emotion estimation unit 55 estimates the occupant's emotion based on the biometric information transmitted from the biometric information detection unit 49. For example, the occupant emotion estimation unit 55 converts each biological information such as a heartbeat and an electroencephalogram transmitted from the biological information detection unit 49 into preset emotional indexes such as "scary" and "comfortable". It may be configured in. Specifically, the occupant emotion estimation unit 55 may be configured to associate each biometric information with preset two-dimensional coordinates of each emotion. Each emotion may be defined in two levels, positive or negative, and may be defined in multiple levels for each of the positive and negative sides. In the present embodiment, each emotion is defined in four stages, and a total of nine stages including neutral emotions are defined in the middle.

In the present specification, "positive" means a state of "good feelings" such as a safe side or a safe side for each emotion, and "negative" means a state of "bad feelings". It means that there is.

(1-8-4. Crew Emotion Learning Department)
The occupant emotion learning unit 57 learns the occupant emotion model 63 while the operation mode is set to the manual operation mode. The occupant emotion learning unit 57 includes information on the occupant's emotions estimated by the occupant emotion estimation unit 55, information on the driving state of the vehicle detected by the vehicle information detection unit 43, and the surroundings of the vehicle specified by the surrounding environment identification unit 53. The occupant emotion model 63 is constructed based on the information of the environment. Specifically, the occupant emotion learning unit 57 runs a data set including information on the occupant's emotions, information on the driving state of the vehicle time-linked to the information on the occupant's emotions, and information on the surrounding environment. While accumulating in the emotion database 61, the occupant emotion model 63 is constructed using the data set.

FIG. 2 shows an example of the occupant emotion model 63. The occupant emotion model 63 is a learning model for estimating the occupant emotion as an output by inputting information on the driving state of the vehicle and information on the surrounding environment. Since the data set used for constructing the occupant emotion model 63 is a time-series data set, by inputting the time-series data of the vehicle driving state information and the surrounding environment information into the occupant emotion model 63 as input. , The emotions of the occupants can be estimated sequentially.

The information on the driving state of the vehicle as input data includes acceleration in each of the front-rear, left-right, and up-down directions of the vehicle, angular velocity of each of the yaw angle, pitch angle, and roll angle, vehicle speed, steering angle, accelerator operation amount, and brake operation amount. It is preferable to include the time series data of. Further, the information on the driving state of the vehicle may include information such as engine speed, turn signal output, number of occupants, and attributes of individual occupants. In addition, as input data, information on the surrounding environment includes the driving lane of the own vehicle, attributes related to traffic participants such as other vehicles and pedestrians, relative distance, relative speed and traveling direction, and the number of lanes on the road on which the vehicle is traveling. It is preferable to include traffic rule information such as traffic light information and speed limit, and traffic regulation data. Further, as the information of the surrounding environment, information such as the weather, the road surface condition, and the attributes of the building may be included.

Further, the occupant emotion model 63 may receive a number of inputs corresponding to the input data while maintaining the time order of the above time series data. Alternatively, the occupant emotion model 63 extracts, for example, a feature amount by defining a time window from the above time series data, for example, extracts a maximum value, a minimum value, an average value, etc. in the time window, and receives them as input data. You may. In this case, the number of input data is proportional to the number of features extracted from the time series data. Further, the occupant emotion model 63 outputs an estimated value (one value) of the occupant emotion.

The method for constructing the occupant emotion model 63 is not particularly limited, and for example, a known method such as a support vector machine, a neighbor method, a neural network such as deep learning, or a Bayesian network can be appropriately adopted.

(1-8-5. Emotional deterioration judgment unit)
The emotional deterioration determination unit 59 determines whether or not the occupant's emotions have deteriorated while the driving mode is set to the automatic driving mode. In the present embodiment, the emotion deterioration determination unit 59 determines whether or not the emotion level estimated by the occupant emotion estimation unit 55 is on the negative side of the emotion target level set via the input unit 45. do.

(1-8-6. Control parameter setting unit)
The control parameter setting unit 65 sets the control parameters used for the automatic driving control by the vehicle driving control device 35 while the driving mode is set to the automatic driving mode. The control parameter setting unit 65 calculates the ideal driving state of the vehicle in which the emotion of the occupant approaches the target level based on the occupant emotion model 63, and sets the control parameter for automatic driving control based on the ideal driving state. In the present embodiment, the control parameter setting unit 65 inputs a plurality of input values related to the driving state of the vehicle such as the vehicle speed, acceleration / deceleration, and steering angle to the occupant emotion model 63, respectively, and the input values input to the occupant emotion model 63. Among them, the control parameter is set with the input value in which the occupant's emotion is closer to the target level than the current emotion as the ideal driving state of the vehicle.

The control parameter is a variable used for calculating the control amount of each control target when the vehicle travel control device 35 executes the automatic driving control of the vehicle. For example, the control parameters include values such as vehicle speed, acceleration / deceleration, and steering rate.

The emotional target level is set, for example, via the input unit 45. An occupant such as a driver may set an emotional target level by inputting an operation of the input unit 45 in advance. Alternatively, the control parameter setting unit 65 may always set the emotion level on the positive side of one step or a plurality of steps from the emotion level of the occupant estimated by the occupant emotion estimation unit 55 as the target level. Further, the control parameter setting unit 65 may always set the highest emotion level on the positive side as the target level. Further, the control parameter setting unit 65 may set the neutral emotion level as the target level when the emotion level of the occupant estimated by the occupant emotion estimation unit 55 is on the negative side.

Further, when the occupant's emotion estimated by the occupant emotion estimation unit 55 becomes negative when the vehicle travels under a predetermined situation, the control parameter setting unit 65 sets the target level of emotion under a similar situation. You may ask the occupants and set based on the reaction. For example, when the vehicle turns right even though it is close to the oncoming vehicle, the occupant's emotions estimated from the occupant's biometric information by the occupant emotion estimation unit 55 are negative compared to the emotional state before the right turn. When it changes to the side, the control parameter setting unit 65 asks the target level of emotion in the same situation. The content to be asked is set in advance, and when it changes to the negative side, it is played back through an in-vehicle speaker or the like.

Specifically, the control parameter setting unit 65 asks the occupant, "Is it better to drive without fear in the current situation?" Or "Driving with an emphasis on timing even if there is some anxiety in the current situation?" Is it okay? " When the occupant responds positively to "driving is not scary in the current situation", the control parameter setting unit 65 sets the emotional target level to neutral. In addition, when the occupant gives a positive reaction to "Driving with an emphasis on timing is good even if there is some anxiety in the current situation", the control parameter setting unit 65 is set to 1 of the emotion level estimated at that time. Set the emotional level above one or more levels to the target level.

Further, the control parameter setting unit 65 prepares a plurality of input value candidates to be input to the occupant emotion model 63, and sequentially inputs the plurality of input values to the occupant emotion model 63. The control parameter setting unit 65 selects an input value corresponding to the emotion level closest to the target level among the plurality of emotion levels output from the occupant emotion model 63 based on the plurality of input values. Then, the control parameter setting unit 65 sets the input value as an ideal operating state, and sets the control parameter based on the selected input value. As a result, automatic driving control of the vehicle is executed so that the emotions of the occupants approach the target level. When the plurality of input values closest to the target level exist, the input value closest to the current control parameter may be selected from those input values.

FIG. 3 shows an example of an algorithm for setting vehicle control parameters using the occupant emotion model 63. The input value when obtaining the control parameter consists of the input value related to the operating state and behavior of the vehicle during the automatic driving control. Since the input value of the surrounding environment is information that cannot be controlled (fixed value), the information of the surrounding environment (fixed value) detected by the surrounding environment detection unit 47 is used.

The number of candidates for the input value to be prepared is appropriately set based on at least one of the processing speed of the arithmetic processing unit constituting the electronic control device 50 and the update frequency of the control parameters. For example, the number of candidates for a plurality of input values to be prepared is set in advance as follows. First, from the amount of data processing required for the occupant emotion model 63 and the processing capacity of the arithmetic processing device that performs arithmetic processing using the occupant emotion model 63, an input value is input to the occupant emotion model 63 per unit time. The number of calculations that the occupant's emotions are output is calculated. Based on the calculated number of operations and the update speed of the control parameter, the number of operations that can be processed is calculated each time the control parameter is updated. This number of operations is set as the number of input value candidates. In order to execute the automatic operation control precisely, it is preferable to set the maximum number that can be set in consideration of the processing speed of the arithmetic processing unit and the update frequency of the control parameters.

The control parameter setting unit 65 sequentially inputs a plurality of input values into the occupant emotion model 63, obtains each emotion level, and selects the input value closest to the target level. Then, the control parameter setting unit 65 sets the input value as an ideal operating state, and sets the control parameter based on the selected input value. Specifically, the control parameter setting unit 65 matches or resembles and sets the current surrounding environment information detected by the surrounding environment detection unit 47 from the data set stored in the driving emotion database 61. Extract the data set of the driving state of the vehicle when the emotion level is closest to the target level of the emotion being performed. The control parameter setting unit 65 sets the extracted data set of the driving state of the vehicle as the reference operation target value.

The control parameter setting unit 65 sets a plurality of input value candidates corresponding to the above-mentioned number of operations between the current value and the above-mentioned reference operation target value for information on the driving state of the vehicle such as the steering angle and acceleration. create. For example, for vehicle speed data, when the current vehicle speed is 40 km / h, the reference operation target value is 30 km / h, and the number of operations is 3, the candidate vehicle speed input values are 30 km / h, 35 km / h, and 40 km / h. It becomes. The control parameter setting unit 65 executes the same process for all other data and creates a plurality of input value candidates. It should be noted that the reason why multiple input value candidates are prepared is that if the information of the surrounding environment of the data set set as the reference operation target value does not completely match the current surrounding environment, the reference operation target value is not necessarily emotional. This is because it is not always the driving state of the vehicle that can achieve the target level.

The control parameter setting unit 65 sequentially inputs a plurality of created input values to the occupant emotion model 63, and selects a data set of the driving state of the vehicle in which the output occupant emotion is closest to the target level. Then, the control parameter setting unit 65 sets control parameters in automatic driving control such as vehicle speed, acceleration / deceleration, and steering rate based on the selected data set. As described above, the number of input value candidates is set based on at least one of the processing speed of the arithmetic processing unit and the update frequency of the control parameters. Therefore, the control parameter setting unit 65 is set for each processing cycle of the arithmetic processing unit. Control parameters can be updated sequentially. The control parameter setting unit 65 executes the setting of the control parameter using the occupant emotion model 63 for each processing cycle of the arithmetic processing unit, and transmits the set control parameter information to the vehicle travel control device 35. As a result, control parameters for automatic driving control are sequentially obtained so that the emotions of the occupant become the target level, and automatic driving control that is comfortable for the occupant can be executed.

<2. Operation example>
Up to this point, a configuration example of the automatic driving support device 10 according to the present embodiment has been described. Next, an operation example of the automatic driving support device 10 according to the present embodiment will be described based on the flowcharts shown in FIGS. 4 to 6. In the following description, the description of the contents already described in the above configuration example may be omitted.

First, when the electronic control device 50 of the automatic driving support device 10 detects the activation of the system (step S11), the occupant detection unit 41 recognizes the occupant of the vehicle (step S13). Further, the driving mode setting unit 51 sets the driving mode of the vehicle to the manual driving mode or the automatic driving mode according to the driving mode input via the input unit 45 (step S15).

Next, the operation mode setting unit 51 determines whether or not the operation mode is the automatic operation mode (step S17). When the driving mode is not the automatic driving mode (S17 / No), that is, when the driving mode is set to the manual driving mode, the occupant emotion estimation unit 55 is based on the biometric information transmitted from the biometric information detection unit 49. , Estimate the emotions of the occupants (step S27). In this embodiment, the emotional level of the occupant defined in a plurality of stages is estimated. The emotions of the occupants estimated at this time are stored as emotional information at the start of traveling. Next, the vehicle travel control device 35 starts the vehicle travel control according to the driver's driving operation to start the vehicle travel (step S29). After starting the running of the vehicle in the manual driving mode, the electronic control device 50 executes the learning process of the occupant emotion model 63 by the occupant emotion learning unit 57 (step S31). Until the system is stopped (until step S25 is determined affirmatively), the electronic control device 50 repeatedly executes the learning process of the occupant emotion model 63 while the vehicle is set to the manual driving mode. do.

FIG. 5 is a flowchart showing an example of the occupant emotion model learning process by the automatic driving support device 10. First, the surrounding environment specifying unit 53 identifies the current surrounding environment information of the vehicle based on the surrounding environment information transmitted from the surrounding environment detecting unit 47 (step S41). Next, the vehicle information detection unit 43 detects the current driving state of the vehicle (step S43). Next, the occupant emotion estimation unit 55 estimates the occupant's emotion based on the biometric information transmitted from the biometric information detection unit 49 (step S45).

Next, the occupant emotion learning unit 57 acquires information on the occupant's emotions, information on the surrounding environment, and information on the driving state of the vehicle, and is temporally linked to the occupant's emotional information and the occupant's emotional information. The information on the surrounding environment and the information on the driving state of the vehicle are stored in the driving emotion database 61 (step S47). Next, the occupant emotion learning unit 57 uses information on the occupant's emotions, information on the surrounding environment time-linked to the information on the occupant's emotions, and information on the driving state of the vehicle to perform deep learning or the like. The occupant emotion model 63 is constructed or updated using a known method (step S49). The occupant emotion learning unit 57 repeatedly executes these processes from steps S41 to S49 for each processing cycle of the arithmetic processing unit to construct the occupant emotion model 63.

On the other hand, in step S17 described above, when the driving mode is the automatic driving mode (S17 / Yes), the occupant emotion estimation unit 55 estimates the occupant's emotions based on the biological information transmitted from the biological information detection unit 49. (Step S19). The emotions of the occupants estimated at this time are stored as emotional information at the start of traveling. Next, the vehicle travel control device 35 starts traveling control of the vehicle in the automatic driving mode to start traveling of the vehicle (step S21). After starting the running of the vehicle in the automatic driving mode, the electronic control device 50 executes the running control of the vehicle based on the emotions of the occupants (step S23). Until the system is stopped (until step S25 is affirmed), the electronic control device 50 controls the running of the vehicle based on the emotions of the occupants while the vehicle is set to the automatic driving mode. continue.

FIG. 6 shows an example of a flowchart of driving control processing based on driving emotions by the automatic driving support device 10. First, the surrounding environment specifying unit 53 identifies the current surrounding environment information of the vehicle based on the surrounding environment information transmitted from the surrounding environment detecting unit 47 (step S51). Next, the occupant emotion estimation unit 55 estimates the occupant's emotion based on the biometric information transmitted from the biometric information detection unit 49 (step S53). Next, the emotion deterioration determination unit 59 determines whether or not the estimated emotion of the occupant has deteriorated (step S55). In the present embodiment, the emotion deterioration determination unit 59 determines whether or not the estimated emotional level of the occupant has changed to the negative side as compared with the previous time.

When the occupant's emotions have not deteriorated (S55 / No), the automatic driving support device 10 returns to step S51 and repeats the processes of steps S51 to S55. On the other hand, when the emotion of the occupant deteriorates (S55 / Yes), the control parameter setting unit 65 refers to the set target emotion value (step S57). In this embodiment, information on the set emotional target level is referred to.

Next, the control parameter setting unit 65 refers to the driving emotion database 61 and creates candidates for a plurality of input values to be input to the occupant emotion model 63 (step S59). Specifically, the control parameter setting unit 65 refers to the driving emotion database 61 and drives a vehicle in which the emotions of the occupants are closest to the target level from the data set of the surrounding environment that matches or is similar to the current surrounding environment. Extract the state dataset. Next, the control parameter setting unit 65 sets the extracted data set of the driving state of the vehicle as the reference operation target value, and sets in advance between the value of the current driving state of the vehicle and the reference operation target value. Create multiple input value candidates corresponding to the number of operations.

Next, the control parameter setting unit 65 inputs one of the input value candidates into the occupant emotion model 63, and acquires the output occupant emotion information (step S61). Next, the control parameter setting unit 65 calculates the difference between the occupant emotion value and the target emotion value output from the occupant emotion model 63 (step S63). In the present embodiment, the control parameter setting unit 65 calculates the difference between the emotion level output from the occupant emotion model 63 and the emotion target level. Next, the control parameter setting unit 65 determines whether or not the input of all the input value candidates to the occupant emotion model 63 is completed (step S65). When the input of all the input value candidates is not completed (S65 / No), the control parameter setting unit 65 returns to step S61 and inputs the next input value candidate to the occupant emotion model 63. The control parameter setting unit 65 repeatedly executes the processes of steps S61 to S65 until the input of all the input value candidates is completed.

When the input of all the input value candidates is completed (S65 / Yes), the control parameter setting unit 65 sets the input value that minimizes the difference between the emotion level output from the occupant emotion model 63 and the emotion target level. Select (step S67). The input value selected here is the input value at which the emotional level of the occupant is closest to the target level. Next, the control parameter setting unit 65 converts the selected input value into a control parameter for automatic operation control (step S69). Next, the control parameter setting unit 65 transmits the calculated control parameter to the vehicle travel control device 35 and reflects it in the automatic driving control (step S71).

In either case, when the driving control based on the occupant emotion is executed during the automatic driving mode (step S23), or when the learning process of the occupant emotion model 63 is executed during the manual driving mode (step S31). , The automatic driving support device 10 determines whether or not the system has stopped (step S25). When the system is not stopped (S25 / No), the automatic driving support device 10 repeats the processes from step S17 to step S31 described above. On the other hand, when the system is stopped (S25 / Yes), the automatic driving support device 10 ends the control process.

As described above, the automatic driving support device 10 according to the present embodiment temporally links the emotional information of the occupant with the emotional information of the occupant while the driving mode is set to the manual driving mode. The information on the driving state of the vehicle and the information on the surrounding environment are stored in the driving emotion database 61, and the occupant emotion model 63 is constructed by using this information. Further, the automatic driving support device 10 refers to the driving emotion database 61 and selects a plurality of candidates for the input value of the driving state of the vehicle to be input to the occupant emotion model 63 while the driving mode is set to the automatic driving mode. The control parameter of the automatic driving control is set based on the input value created and the emotion level output from the occupant emotion model 63 is closest to the target level.

The driving emotion database 61 is a data set of information linked in time, and the control parameter setting unit 65 sets the occupant from among a plurality of candidates for the input value of the driving state of the vehicle for each predetermined processing cycle. Control parameters are set based on the input value at which the emotional level approaches the target level. Therefore, it is possible to specifically and sequentially set control parameters that can bring the emotions of the occupant closer to the target emotions.

Further, the control parameter setting unit 65 sets the control parameter from the driving emotion database 61 by using the data set of the surrounding environment that matches or is similar to the current surrounding environment of the vehicle. Therefore, even when there is no data set in the driving emotion database 61 that matches the surrounding environment, it is possible to realize driving control that leads to a state close to the target emotion.

<3. Modification example>
Up to this point, the automatic driving support device 10 according to the present embodiment has been described, but the automatic driving support device 10 according to the present embodiment can be variously modified. Hereinafter, a modified example in which the control parameter setting unit 65 sets the control parameters in accordance with each occupant will be described.

In the first modification, for a plurality of input value candidates to be input to the occupant emotion model 63, the occupant determines in advance the value of one or more data items having priority among the data items of the respective input values. This is an example. For example, when a certain occupant attaches importance to the vehicle speed in the automatic driving control, the occupant sets the vehicle speed as a priority item in advance. When creating a plurality of input value candidates, the control parameter setting unit 65 fixes the vehicle speed data to the vehicle speed constituting the reference operation target value extracted from the driving emotion database 61, and inputs other data items. Create value candidates. This makes it possible to set control parameters that bring the occupant's emotions closer to the target emotions while reflecting the occupant's preferences regarding the driving state of the vehicle.

In the second modification, the control parameter setting unit 65 extracts the data item of the driving state of the vehicle having a large influence on the emotion for each occupant based on the driving emotion database 61, and the occupant is the subject. This is an example of fixing data items and creating input value candidates. For example, the occupant detection unit 41 identifies and recognizes each occupant, and creates a driving emotion database 61 in which a data set is accumulated for each occupant. Then, the occupant emotion learning unit 57 analyzes the sensitivity to the occupant emotion model 63 and extracts data items having a large influence on the emotion. Sensitivity analysis analyzes data items whose output emotional level changes significantly when, for example, one item is excluded from the input data items or the numerical value of one item is changed. It may be a method. The control parameter setting unit 65 fixes the specified data item to the input value constituting the reference operation target value extracted from the driving emotion database 61, and creates input value candidates for other data items. As a result, it is possible to set control parameters that bring the emotions of the occupants closer to the target emotions while preferentially setting the input values for the data items that have a large influence on the emotions of the individual occupants.

Further, when the control parameters calculated by using the method of the first modification described above are reflected in the automatic driving control, the emotional level of the occupant estimated based on the biological information detected by the biological information detection unit 49. However, when the emotion level is negative than the emotion level calculated by using the occupant emotion model 63, the occupant is set as the priority data item for the item having a large influence on the emotion obtained by the method of the second modification. You may propose to.

According to these modified examples, the automatic driving control using the occupant emotion model 63 can reflect at least one of the occupant's preference and the objective tendency based on the accumulated driving emotion database 61. , It is possible to execute automatic driving control that reflects the intentions and characteristics of individual occupants.

Although the preferred embodiments of the present invention have been described in detail with reference to the accompanying drawings, the present invention is not limited to such examples. It is clear that a person having ordinary knowledge in the field of technology to which the present invention belongs can come up with various modifications or modifications within the scope of the technical ideas described in the claims. , These are also naturally understood to belong to the technical scope of the present invention.

For example, in the above embodiment, the occupant emotion learning unit 57 accumulates a data set in the driving emotion database 61 and updates the occupant emotion model 63 when the driving mode is the manual driving mode. Not limited. The occupant emotion learning unit 57 may accumulate the data set in the driving emotion database 61 and update the occupant emotion model 63 even when the driving mode is the automatic driving mode.

10 ... Automatic driving support device, 35 ... Vehicle driving control device, 50 ... Electronic control device, 51 ... Driving mode setting unit, 53 ... Surrounding environment identification unit, 55 ... Crew emotion estimation unit, 57 ... Crew emotion learning unit, 59 ... Emotion deterioration judgment unit, 61 ... Driving emotion database, 63 ... Crew emotion model, 65 ... Control parameter setting unit

Claims (8)

An occupant emotion learning unit that builds an occupant emotion model that estimates the occupant's emotion from the vehicle's driving condition based on information on the vehicle's driving condition and the occupant's emotion.
A control parameter setting unit that calculates the ideal driving state of the vehicle in which the emotion of the occupant approaches the target emotion based on the occupant emotion model, and sets control parameters for automatic driving control based on the ideal driving state. And with
The control parameter setting unit inputs a plurality of input values related to the driving state of the vehicle into the occupant emotion model, and among the input values input to the occupant emotion model, the occupant's emotion is higher than the current emotion. An automatic driving support device that sets the control parameters with an input value approaching the target emotion as the ideal driving state of the vehicle. The occupant emotion model includes information on the surrounding environment of the vehicle, information on the driving state of the vehicle, and the like.
It is the occupant emotion model that estimates the occupant's emotion based on
The automatic driving support device according to claim 1, wherein the control parameter setting unit sets the control parameters by obtaining the ideal driving state of the vehicle in the surrounding environment corresponding to the current surrounding environment of the vehicle. The occupant emotion learning unit accumulates a data set in which the estimated emotional information of the occupant, the information on the surrounding environment of the vehicle, and the information on the driving state of the vehicle are linked.
The control parameter setting unit extracts from the accumulated data set the driving state of the vehicle that approaches the target emotion in the surrounding environment corresponding to the current surrounding environment of the vehicle.
The automatic driving support device according to claim 2, wherein the plurality of input values are created based on the extracted information on the driving state of the vehicle. The control parameter setting unit sets the plurality of input values between the extracted values of the predetermined data items in the driving state of the vehicle and the values of the predetermined data items in the current driving state of the vehicle. , The automatic driving support device according to claim 3. The predetermined data item in the driving state of the vehicle includes a plurality of data items.
At least one of the plurality of data items can be set as a priority item by the user.
When there is the priority item set by the user, the control parameter setting unit sets the value of the priority item among the data items of the plurality of input values to be input to the occupant emotion model to the current value of the priority item. 3. The described automatic driving support device. In the control parameter setting unit, the emotion of the occupant when the automatic driving control is executed by the control parameter obtained by fixing the value of the priority item is the emotion of the occupant calculated by using the occupant emotion model. When it becomes worse than The automatic driving support device according to claim 5, which is presented to the user so as to be fixed to the extracted value. The predetermined data item in the driving state of the vehicle includes a plurality of data items.
The occupant emotion learning unit extracts at least one data item having a large influence on the occupant's emotion based on the accumulated data set.
The control parameter setting unit extracts at least one data item having a large influence on the emotions of the occupant as the driving state of the vehicle approaching the target emotions in the surrounding environment corresponding to the current surrounding environment of the vehicle. The automatic driving support device according to claim 3, wherein the plurality of input values are fixed to the specified values, the plurality of input values are obtained, and the control parameters are set. The control parameter setting unit sets the number of the plurality of input values to be input to the occupant emotion model based on at least one of the processing speed of the arithmetic processing unit that performs the calculation and the update frequency of the control parameter. The automatic driving support device according to any one of claims 1 to 7.

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