Driving Support Device

Abstract

To provide a driving assist system capable of performing driving assist on which a driver's emotion is reflected.SOLUTION: A driving assist system 40 including a processor acquires manipulation information on a manipulation a driver performs on a vehicle 1 at a time of intervention in the vehicle 1 by driving assist intended to sustain a lane, environment information on an environment encompassing another vehicle around the vehicle 1, and living body information on the driver, estimates a driver's emotion on the basis of the manipulation information, environment information, and living body information, estimates a control parameter concerning an intervention quantity required at the time of intervention by driving assist on the basis of a result of the estimation of the driver's emotion, and controls the vehicle 1 on the basis of the control parameter.SELECTED DRAWING: Figure 1

Description

Technical Field

[0001] The present disclosure relates to a driving support device.

Background Art

[0002] Patent Document 1 discloses a technique for controlling the driving position of a host vehicle so as to move away from a vehicle in an adjacent lane when the vehicle in the adjacent lane is at a position closer than a predetermined distance.

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] However, Patent Document 1 does not consider the driver's feelings, and there is a problem that the host vehicle moves to a driving position unintended by the driver, which rather gives fear to the driver.

[0005] The present disclosure has been made in view of the above, and an object thereof is to provide a driving support device capable of performing driving support that reflects the driver's feelings.

Means for Solving the Problems

[0006] In order to solve the above-described problems and achieve the object, a driving support device according to the present disclosure is a driving support device including a processor. The processor acquires operation information of a driver on the host vehicle during driving support intervention for lane keeping in the host vehicle, environment information including other vehicles around the host vehicle, and biometric information of the driver, estimates the emotion of the driver based on the operation information, the environment information, and the biometric information, estimates a control parameter related to an intervention amount at the next driving support intervention based on an estimation result of the emotion of the driver, and controls the host vehicle based on the control parameter.

Effect of the Invention

[0007] According to the present disclosure, there is an effect that driving support reflecting the emotion of the driver can be performed.

Brief Description of the Drawings

[0008] [Figure 1] FIG. 1 is a block diagram showing a functional configuration of a vehicle according to an embodiment. [Figure 2] FIG. 2 is a diagram schematically showing an outline of information flow in each part of a driving support device according to an embodiment. [Diagram 3] FIG. 3 is a flowchart showing an outline of processing executed by a driving support device according to an embodiment.

Embodiments for Carrying Out the Invention

[0009] Hereinafter, a vehicle including a driving support device according to an embodiment of the present disclosure will be described with reference to the drawings. Note that the present disclosure is not limited by the following embodiments. In the following, the same parts will be described with the same reference numerals.

[0010] 〔Functional Configuration of Vehicle〕 FIG. 1 is a block diagram showing a functional configuration of a vehicle according to an embodiment. The vehicle 1 shown in FIG. 1 is assumed to be an HEV (Hybrid Electric Vehicle), PHEV (Plug-in Hybrid Electric Vehicle), BEV (Battery Electric Vehicle), FCEV (Fuel Cell Electric Vehicle), or the like. Also, the vehicle 1 is assumed to be capable of performing steering operation support for maintaining the lane of the vehicle 1 by performing driving support for cruise control that automatically maintains a constant speed while following a preceding vehicle at a predetermined inter-vehicle distance or for the driver's steering operation. The vehicle 1 includes a sensor group 10, a drive unit 20, a storage unit 30, and a driving support device 40.

[0011] The sensor group 10 is configured using a temperature sensor, a pulse sensor, an imaging device, a millimeter-wave radar, a speed sensor, an acceleration sensor, a gyro sensor, and the like. The sensor group 10 detects various information regarding the vehicle 1 and outputs the detected information to the driving support device 40. The detected information includes the driver's biometric information inside the vehicle 1, image information obtained by imaging the driver, operation information such as the driver's steering operation and accelerator operation of the vehicle 1, and environmental information around the vehicle 1. The biometric information is the driver's pulse, presence or absence of sweating, body temperature, and the like. Also, the environmental information includes the road width of the lane on which the vehicle 1 is traveling and the number of lanes of the lane on which the vehicle 1 is traveling, distances to other vehicles such as preceding vehicles, following vehicles, and adjacent vehicles located around the vehicle 1 and structures, and the speeds of other vehicles located around the vehicle 1. Here, other vehicles such as preceding vehicles, following vehicles, and adjacent vehicles include micro-mobility such as trucks, motorcycles, bicycles, and electric kick scooters in addition to automobiles. Also, the structures include guardrails, utility poles, traffic signals, and the like.

[0012] The drive unit 20 is realized using an engine, a motor, or the like. The drive unit 20 accelerates the vehicle 1 by driving under the control of the driving support device 40.

[0013] The storage unit 30 is realized using a ROM (Read Only Memory), a RAM (Random Access Memory), an SSD (Solid State Drive), an HDD (Hard Disk Drive), etc. The storage unit 30 stores an operating system (OS), various programs, various tables, various databases, etc. The storage unit 30 may also store estimation results from an emotion estimation unit 41 and a control parameter estimation unit 42 (described later). The storage unit 30 may also store machine-learned learned models (trained models) used in the emotion estimation unit 41 and the control parameter estimation unit 42 (described later).

[0014] The driving assistance device 40 is realized using a processor having hardware. The hard disk includes, for example, a memory, a CPU (Central Processing Unit), a DSP (Digital Signal Processor), an FPGA (Field-Programmable Gate Array), and a GPU (Graphics Processing Unit). The driving assistance device 40 controls each component of the vehicle 1. The driving assistance device 40 loads a program stored in the storage unit 30 into a working area of the memory, executes it, and controls each component through the execution of the program to realize a function that meets a predetermined purpose. The driving assistance device 40 includes an emotion estimation unit 41, a control parameter estimation unit 42, a driving control unit 43, and a determination unit 44.

[0015] The emotion estimation unit 41 acquires the biometric information of the driver who drives the vehicle 1, and estimates the emotion of the driver based on this biometric information. Specifically, the emotion estimation unit 41 estimates the emotion of the driver who drives the vehicle 1 based on a pre-trained learned model or rules by machine learning. When using a learned model in the emotion estimation unit 41, the input data is the biometric information, operation information, and environment information of the driver acquired from the sensor group 10. Here, the biological state includes, for example, the driver's heartbeat, presence or absence of sweating, body temperature, facial expression information, and line-of-sight information measured by the sensor group 10. The facial expression information is a numerical value of the degree of match based on the driver's face and a predetermined pattern (for example, a smiling face). Also, the emotion of the driver is either positive (comfortable), normal (ordinary), or negative (uncomfortable).

[0016] In addition, in Embodiment 1, the emotion estimation unit 41 outputs the emotion of the driver in three levels, but it is not limited to this, and at least two levels of comfortable and uncomfortable are sufficient. Of course, the emotion estimation unit 41 may output the emotion of the driver in three or more levels, for example, "positive (comfortable)", "slightly positive (slightly comfortable)", "normal (ordinary)", "slightly negative (slightly uncomfortable)", and "negative (uncomfortable)" in five levels. Also, although the emotion estimation unit 41 outputs the emotion of the driver in three levels, it is not limited to this, and for example, it may output a numerical value (probability) of the driver's comfort or discomfort. Note that the numerical value of comfort or discomfort indicates, for example, a numerical index indicating comfort or discomfort. Also, the probability of comfort or discomfort indicates the probability of a specific emotion indicating comfort or discomfort.

[0017] Also, the method for constructing the learned model used in the emotion estimation unit 41 is not particularly limited, and for example, various machine learning methods such as deep learning using a neural network, support vector machine, decision tree, naive Bayes, k-nearest neighbor method, etc. can be used.

[0018] The control parameter estimation unit 42 estimates a control parameter regarding the intervention amount at the next driving support intervention based on the driver's emotion, operation information, and environmental information estimated by the emotion estimation unit 41. This control parameter is a parameter for controlling the driving position of the lane in which the vehicle 1 travels. Specifically, the control parameter is a parameter regarding the intervention amount such as the steering operation amount and the accelerator operation amount at the time of driving support intervention with respect to the operation by the driver of the vehicle 1. The control parameter estimation unit 42 estimates a control parameter regarding the intervention amount at the next driving support intervention based on the driver's emotion, operation information, and environmental information according to a pre-learned learned model or rule by machine learning. When using a learned model in the control parameter estimation unit 42, the input data is the estimation result of the driver's emotion, operation information, and environmental information. And the output data is a control parameter regarding the intervention amount at the next driving support intervention. For example, the control parameter is the steering operation amount and the accelerator operation amount at the next driving support intervention. Also, the method for constructing the learned model used in the control parameter estimation unit 42 is not particularly limited, and for example, various machine learning methods such as deep learning using a neural network, support vector machine, decision tree, naive Bayes, k-nearest neighbor method, etc. can be used.

[0019] The driving control unit 43 controls the driving of the vehicle 1 by driving the driving unit 20 based on the control parameter input from the control parameter estimation unit 42. Specifically, the driving control unit 43 controls the driving position of the vehicle 1 at the time of driving support intervention by driving the driving unit 20 based on the control parameter input from the control parameter estimation unit 42. For example, the driving control unit 43 drives the driving unit 20 based on the control parameter input from the control parameter estimation unit 42 to maintain the distance between the vehicle 1 (own vehicle) and other vehicles constant and maintain the lane in which the vehicle 1 travels. Also, when it is determined by the determination unit 44 described later that the distance between the vehicle 1 and other vehicles is within a predetermined distance, and when it is determined by the determination unit 44 that the estimation result of the driver's emotion by the emotion estimation unit 41 is negative, the driving control unit 43 performs an avoidance operation with respect to the other vehicle.

[0020] Based on the environmental information detected by the sensor group 10, the determination unit 44 determines whether the distance between the vehicle 1 and other vehicles is within a predetermined distance. Further, the determination unit 44 determines whether the estimation result of the driver's emotion estimated by the emotion estimation unit 41 is negative.

[0021] 〔Overview of information flow in each part of the driving support device〕 Next, an overview of the information flow in each part of the driving support device 40 will be described. FIG. 2 is a diagram schematically showing the overview of the information flow in each part of the driving support device 40.

[0022] As shown in FIG. 2, the emotion estimation unit 41 acquires the biometric information of the driver P100, the operation information on the vehicle 1 by the driver P100, and the environmental information of the vehicle 1 from the sensor group 10. Then, the emotion estimation unit 41 estimates the emotion of the driver P100 based on the biometric information, operation information, and environmental information.

[0023] Subsequently, based on the estimation result estimated by the emotion estimation unit 41, the operation information of the driver P100 acquired from the sensor group 10, and the environmental information of the vehicle 1, the control parameter estimation unit 42 estimates the control parameter regarding the intervention amount at the time of driving support intervention for lane keeping in the vehicle 1. Further, the control parameter estimation unit 42 estimates the control parameter regarding the intervention amount at the next driving support intervention based on the emotion estimation result of the driver P100 estimated by the emotion estimation unit 41, the operation information of the driver P100 acquired from the sensor group 10, the environmental information of the vehicle 1, and the control signal input from the driving control unit 43.

[0024] Thereafter, based on the control parameter input from the control parameter estimation unit 42, the driving control unit 43 outputs a control signal for controlling the vehicle 1 to the driving unit 20 and the control parameter estimation unit 42.

[0025] 〔Processing of the driving support device〕 Next, the processes executed by the driving support device 40 will be described. FIG. 3 is a flowchart showing an overview of the processes executed by the driving support device 40.

[0026] As shown in FIG. 3, first, the emotion estimation unit 41 acquires biometric information of the driver P100 in the vehicle 1, operation information on the vehicle 1 by the driver P100, and environmental information around the vehicle 1 from the sensor group 10 (step S1).

[0027] Subsequently, the emotion estimation unit 41 estimates the emotion of the driver P100 based on the biometric information of the driver P100 acquired from the sensor group 10, the operation information on the vehicle 1 by the driver P100, and the environmental information including other vehicles around the vehicle 1 (step S2).

[0028] Thereafter, the control parameter estimation unit 42 estimates control parameters regarding the intervention amount at the time of driving support intervention based on the estimation result estimated by the emotion estimation unit 41, the operation information, environmental information acquired from the sensor group 10, and the control signal input from the driving control unit 43 (step S3).

[0029] Subsequently, the driving control unit 43 controls the driving of the vehicle 1 at the time of driving support intervention by outputting a control signal for controlling the vehicle 1 to the drive unit 20 based on the control parameters input from the control parameter estimation unit 42 (step S4). Specifically, the driving control unit 43 controls the driving position of the vehicle 1 at the time of driving support intervention by driving the drive unit 20 based on the control parameters input from the control parameter estimation unit 42. For example, the driving control unit 43 maintains the distance between the vehicle 1 (own vehicle) and other vehicles constant and maintains the lane in which the vehicle 1 travels by driving the drive unit 20 based on the control parameters input from the control parameter estimation unit 42. Further, the driving control unit 43 outputs the control signal to the control parameter estimation unit 42.

[0030] Subsequently, the control parameter estimation unit 42 estimates control parameters regarding the driving intervention amount at the next driving support intervention based on the biometric information of the driver P100 acquired from the sensor group 10, the operation information of the vehicle 1 by the driver P100, the environmental information including other vehicles around the vehicle 1, and the control signal input from the driving control unit 43 (step S5).

[0031] Subsequently, the determination unit 44 determines whether the distance between the other vehicle detected by the sensor group 10 and the vehicle 1 is within a predetermined distance (step S6). Note that the determination unit 44 determines whether the distance between the other vehicle detected by the sensor group 10 and the host vehicle is within a predetermined distance. However, in addition to other vehicles, it may also be determined whether the distance between structures such as guardrails, utility poles, and plantings and the vehicle 1 is within a predetermined distance. When the determination unit 44 determines that the distance between the other vehicle and the host vehicle is within a predetermined distance (step S6: Yes), the driving support device 40 proceeds to step S7. On the other hand, when the determination unit 44 determines that the distance between the other vehicle and the host vehicle is not within a predetermined distance (step S6: No), the driving support device 40 proceeds to step S9.

[0032] In step S7, the determination unit 44 determines whether the emotion of the driver P100 estimated by the emotion estimation unit 41 is negative (unhappy). When the determination unit 44 determines that the emotion of the driver P100 estimated by the emotion estimation unit 41 is negative (step S7: Yes), the driving support device 40 proceeds to step S8. On the other hand, when the determination unit 44 determines that the emotion of the driver P100 estimated by the emotion estimation unit 41 is not negative (step S7: No), the driving support device 40 proceeds to step S9.

[0033] In step S8, the driving control unit 43 performs an avoidance operation to avoid the host vehicle from the other vehicle by controlling the drive unit 20. After step S7, the driving support device 40 proceeds to step S9.

[0034] In step S9, the determination unit 44 determines, based on the detection results input from the sensor group 10, whether or not the driving operation of the driver P100 has ended due to the vehicle 1 stopping. When it is determined by the determination unit 44 that the driving operation of the driver P100 has ended due to the vehicle 1 stopping (step S9: Yes), the driving support device 40 ends this process. On the other hand, when it is determined by the determination unit 44 that the driving operation of the driver P100 has not ended due to the vehicle 1 stopping (step S9: No), the driving support device 40 returns to step S1.

[0035] According to the embodiment described above, since the driving control unit 43 controls the vehicle 1 based on the control parameters input from the control parameter estimation unit 42, it is possible to perform driving support that reflects the feelings of the driver P100.

[0036] Also, according to one embodiment, since the control parameter estimation unit 42 estimates a parameter for controlling the traveling position of the lane in which the vehicle 1 travels as a control parameter, it is possible to perform driving support that reflects the feelings of the driver P100.

[0037] Also, according to one embodiment, the control parameter estimation unit 42 estimates a control parameter regarding the amount of driving intervention at the time of the next driving support intervention based on the biometric information of the driver P100 acquired from the sensor group 10, the operation information on the vehicle 1 by the driver P100, the environmental information including other vehicles around the vehicle 1, and the control signal input from the driving control unit 43. Thereby, the control parameter estimation unit 42 can estimate the control parameter of the vehicle 1 that reflects the feelings of the driver P100 at the time of driving intervention.

[0038] Furthermore, according to one embodiment, when the determination unit 44 determines that the distance between the vehicle 1 and another vehicle is within a predetermined distance, and the determination unit 44 determines that the estimation result of the driver's emotion by the emotion estimation unit 41 is negative, the driving control unit 43 performs an avoidance operation against the other vehicle. As a result, when the driver P100 feels fear towards another vehicle that is tailgating or the like, the psychological burden on the driver P100 can be reduced by intervening in the driving of the vehicle 1.

[0039] Furthermore, according to one embodiment, the emotion estimation unit 41 acquires image information of the driver captured from the sensor group 10, pulse rate, body temperature, and presence or absence of sweating as the biological condition, and therefore can accurately estimate the emotion of the driver P100.

[0040] (Other embodiments) In the embodiment, the emotion estimation unit estimates the emotion of one driver, but the present invention is not limited to this, and the emotion estimation unit may estimate the emotion of all passengers in the vehicle.

[0041] In addition, although the driving assistance device is provided in the vehicle in one embodiment, the functions of the driving assistance device may be realized by a single server. Also, the emotion estimation unit, the control parameter estimation unit, and the driving control unit constituting the driving assistance device may each be realized by a plurality of separate servers.

[0042] Furthermore, in the driving assistance device according to an embodiment, the above-described "unit" can be read as "means" or "circuit." For example, the emotion estimation unit can be read as emotion estimation means or emotion estimation circuit.

[0043] In addition, the program to be executed by the driving assistance device of one embodiment is provided as file data in an installable format or an executable format, recorded on a computer-readable recording medium such as a CD-ROM, a flexible disk (FD), a CD-R, a DVD (Digital Versatile Disk), a USB medium, or a flash memory.

[0044] In the description of the flowchart in this specification, expressions such as "first", "then", and "subsequently" are used to clarify the sequence of processing between steps. However, the order of processing necessary to implement this embodiment is not uniquely determined by these expressions. That is, the order of processing in the flowchart described in this specification can be changed within a non - conflicting range.

[0045] Further effects and modifications can be easily derived by those skilled in the art. The broader aspects of the present invention are not limited to the specific details and representative embodiments represented and described as above. Therefore, various changes can be made without departing from the spirit or scope of the general inventive concept defined by the appended claims and their equivalents.

[0046] As described above, some of the embodiments of the present application have been described in detail with reference to the drawings. However, these are merely examples, and the present invention can be implemented in other forms with various modifications and improvements based on the knowledge of those skilled in the art, starting from the aspects described in the disclosure column of the present invention.

Explanation of Reference Numerals

[0047] 1 Vehicle; 10 Sensor group; 20 Driving unit; 30 Storage unit; 40 Driving support device; 41 Emotion estimation unit; 42 Control parameter estimation unit; 43 Driving control unit; 44 Judgment unit

Claims

1. A driving support device including a processor, wherein the processor acquires operation information of the driver on the host vehicle during driving support intervention for lane keeping in the host vehicle, environmental information including other vehicles around the host vehicle, and biometric information of the driver, estimates the emotion of the driver based on the operation information, the environmental information, and the biometric information, estimates a control parameter regarding an intervention amount during driving support intervention based on the estimation result of the emotion of the driver, estimates a parameter for controlling a traveling position of a lane in which the host vehicle travels as the control parameter, controls the host vehicle based on the control parameter, after controlling the host vehicle, estimates the control parameter at the next driving support intervention based on the estimation result of the emotion of the driver, the operation information, and the environmental information, after controlling the host vehicle, determines whether a distance between the host vehicle and the other vehicle is within a predetermined distance based on the environmental information, after controlling the host vehicle, determines whether the estimation result of the emotion of the driver is negative, when it is determined that the distance between the host vehicle and the other vehicle is within a predetermined distance after controlling the host vehicle and it is determined that the estimation result of the emotion of the driver is negative, performs an avoidance operation on the other vehicle, a driving support device.

2. The driving support device according to claim 1, wherein the biometric information includes image information obtained by imaging the driver, pulse, body temperature, and presence or absence of sweating, a driving support device.

Images