Vehicle integrated control device and vehicle integrated control method

Abstract

To provide a vehicle integration control device capable of controlling a posture of a vehicle so as to prevent a motion sickness in advance for a plurality of occupants having different sensibilities to the motion sickness.SOLUTION: The present invention is characterized by including: an occupant monitoring unit that monitors a plurality of occupants; a vehicle movement acquisition unit that acquires information related to current vehicle movement of a vehicle; a motion sickness prediction unit that predicts individual sensibilities of the respective occupants to the motion sickness resulted from motion of the vehicle on the basis of a result of occupant monitoring by the occupant monitoring unit and the information related to the vehicle movement acquired by the vehicle movement acquisition unit; a control target determination unit that integrates motion sickness sensibilities of the respective occupants predicted by the motion sickness prediction unit and determines a control target on the basis of a result of integration; and a vehicle movement control unit that determines contents of vehicle movement control on the basis of the control target decided by the control target decision unit.SELECTED DRAWING: Figure 3

Description

[Technical Field]

[0001] The present invention relates to the configuration of a vehicle integrated control device that controls the momentum of a vehicle and the control thereof, and in particular to a technology for controlling the attitude of a vehicle so as to improve the riding comfort of multiple occupants and prevent the onset of motion sickness (motion sickness). [Background technology]

[0002] Autonomous vehicles, which feature futuristic reconfigurable passenger spaces and no active driver control, are expected to evolve into a new living space for humanity. The rapid evolution of autonomous vehicles will change road transportation and lead to improvements in productivity per hour and quality of life. Passengers in autonomous vehicles are expected to perform a variety of activities (tasks) in the car, such as reading, using a smartphone, watching TV or movies on an in-car monitor, and conversing with other passengers.

[0003] On the other hand, when occupants of autonomous vehicles are engaged in the above-mentioned activities inside the vehicle, it is difficult for them to clearly grasp the driving situation and driving scenario, making them unable to predict the vehicle's behavior and highly susceptible to motion sickness.In addition, the direction and magnitude of vehicle motion, the frequency of rotational and translational vibrations, the direction of the occupants' seats, the condition of the road surface, etc. can also be factors that cause discomfort to occupants and may lead to motion sickness.

[0004] The severity and frequency of motion sickness is expected to increase in autonomous vehicles as occupants perform more activities other than driving. The increased severity and frequency of motion sickness may hinder widespread adoption of autonomous driving technology.

[0005] Background art in this technical field includes, for example, technology such as that disclosed in Patent Document 1. Patent Document 1 discloses "an autonomous vehicle capable of autonomous driving according to a preset driving plan, the autonomous vehicle comprising a physical condition detection means for detecting the car sickness state of a vehicle occupant, and a driving control means for performing automatic driving control in accordance with the car sickness state of the occupant." [Prior art documents] [Patent documents]

[0006] [Patent Document 1] Japanese Patent Application Laid-Open No. 2012-59274 Summary of the Invention [Problem to be solved by the invention]

[0007] In the above-mentioned Patent Document 1, motion sickness characteristic learning is performed by associating a self-report of a specific passenger's onset of motion sickness (motion sickness) with vehicle motion information at that time, and calculating a correlation value between vehicle motion and motion sickness (see paragraphs

[0084] -

[0086] of Patent Document 1, etc.). In addition, in the case of multiple occupants, the maximum vehicle state correlation value (acceleration, etc.) is extracted and the vehicle behavior upper limit value is set (see paragraphs

[0095] -

[0096] of Patent Document 1, etc.). However, Patent Document 1 is a learning control based on self-reporting, and predicts the passenger's motion sickness using a motion sickness estimation model after the passenger has already begun to feel motion sickness, and is therefore unable to predict before the passenger develops motion sickness.

[0008] Furthermore, motion sickness cannot be predicted for passengers who have not self-reported it.

[0009] Therefore, an object of the present invention is to provide a vehicle integrated control device and a vehicle integrated control method using the same that can control the vehicle's attitude so as to prevent motion sickness for multiple occupants with different susceptibilities to motion sickness. [Means for solving the problem]

[0010] In order to solve the above problems, the present invention provides a vehicle motion acquisition unit that acquires information about the current vehicle motion of a vehicle, and a vehicle motion acquisition unit that acquires information about the current vehicle motion of a vehicle based on the results of the occupant monitoring by the occupant monitoring unit and the information about the vehicle motion acquired by the vehicle motion acquisition unit. Estimating the vehicle motion perceived by the occupant , Based on the vehicle motion perceived by the occupantMotion sickness predicting each occupant's individual susceptibility to motion sickness due to vehicle motion sensitivity a prediction unit and the motion sickness sensitivity a control target determination unit that integrates the motion sickness susceptibility of each occupant predicted by the prediction unit and determines a control target based on the integration result; and a vehicle motion control unit that determines the content of vehicle motion control based on the control target determined by the control target determination unit. When it is difficult to estimate the vehicle motion perceived by the occupant, the motion sickness susceptibility prediction unit predicts the motion sickness susceptibility using information about the vehicle motion acquired by the vehicle motion acquisition unit. It is characterized by:

[0011] The present invention also provides a vehicle monitoring system comprising: (a) monitoring a plurality of occupants; and (b) obtaining information about the current vehicle dynamics of the vehicle; and (c) based on the results of the occupant monitoring in step (a) and the information on the vehicle motion obtained in step (b), Estimating the vehicle motion perceived by the occupant , Based on the vehicle motion perceived by the occupant predicting each occupant's individual susceptibility to motion sickness due to vehicle motion; and (d) a step of integrating the motion sickness susceptibility of each occupant predicted in the step (c) and determining a control target based on the integration result. and (e) determining the content of vehicle motion control based on the control target determined in the step (d); and , with If it is difficult to estimate the vehicle motion perceived by the occupant in step (c), the motion sickness susceptibility is predicted using information about the vehicle motion obtained in step (b). It is characterized by: [Effects of the Invention]

[0012] According to the present invention, it is possible to realize a vehicle integrated control device and a vehicle integrated control method using the same that can control the vehicle's attitude so as to prevent motion sickness for multiple occupants with different susceptibilities to motion sickness.

[0013] This allows all crew members to perform tasks according to their needs while preventing motion sickness in advance.

[0014] Problems, configurations, and effects other than those described above will become apparent from the following description of the embodiments. [Brief explanation of the drawings]

[0015] [Figure 1] FIG. 1 is a diagram illustrating the interior of an autonomous driving vehicle equipped with reconfigurable seats according to a first embodiment. [Figure 2] FIG. 1 is a diagram showing the interior of a vehicle with multiple occupants carrying out various activities with various head orientations and gaze angles. [Figure 3] 1 is a diagram showing an overall outline of a vehicle integrated control device according to a first embodiment; [Figure 4] 1 is a diagram illustrating an example of the configuration of a passive occupant monitoring unit and a hybrid occupant monitoring unit according to a first embodiment. [Figure 5] FIG. 2 is a diagram conceptually illustrating an algorithm for predicting the susceptibility of a plurality of occupants to motion sickness according to the first embodiment. [Figure 6] 10 is a flowchart illustrating the selection of a motion sickness susceptibility index in a control target integration unit. [Figure 7] 10 is a flowchart illustrating the formulation of a minimized control cost function in the control target integration unit. [Figure 8] FIG. 10 is a diagram illustrating a driving scenario for navigating a vehicle with multiple passengers on board until the vehicle reaches a destination according to a second embodiment. [Figure 9] FIG. 10 is a diagram illustrating a driving scenario in which a driving action is selected based on the motion sickness susceptibility of a plurality of occupants according to a third embodiment. [Figure 10] FIG. 10 is a diagram showing a state in which a plurality of occupants according to a fourth embodiment are performing various activities (tasks) that are not related to driving behavior. [Figure 11] FIG. 10 is a diagram showing a state in which a plurality of occupants according to a fifth embodiment are performing various activities (tasks) that are not related to driving behavior. [Figure 12] FIG. 13 is a diagram showing an in-vehicle monitor for reducing the susceptibility to motion sickness of a passenger not involved in driving operation according to a sixth embodiment. DETAILED DESCRIPTION OF THE INVENTION

[0016] Hereinafter, an embodiment of the present invention will be described with reference to the drawings. In the drawings, the same components are designated by the same reference numerals, and detailed description of overlapping parts will be omitted. [Example]

[0017] First Embodiment A vehicle integrated control device and a vehicle integrated control method according to a first embodiment of the present invention will be described with reference to FIGS.

[0018] FIG. 1 illustrates the interior of a self-driving vehicle equipped with reconfigurable seats 101, 103, 107, and 109. The orientation of the seats can be changed based on the passengers' needs. While FIG. 1 illustrates a four-seat, four-passenger interior, the number of seats varies depending on the model and type of vehicle 100 and is not necessarily limited to this.

[0019] Also installed in the vehicle cabin are multiple occupant monitoring units 102, 108, and 111. Although Figure 1 shows three sensors for occupant monitoring as multiple occupant monitoring units, the number of multiple occupant monitoring units can be changed according to user requirements.

[0020] The multi-occupant monitoring units 102, 108, 111 can measure various attributes, such as occupant 105 reading a book 115, occupant 104 listening to music on headphones 112, occupant 106 using a smartphone 113, and occupant 110 using a mobile tablet 114.

[0021] The main purpose of the multi-occupant monitoring unit is to detect all occupant-related attributes necessary to predict the occupant's susceptibility to motion sickness (motion sickness). For example, the multi-occupant monitoring unit can detect the occupant's activity, such as whether the occupant 105 is reading a book 115, and can also detect the occupant's head movement and orientation while performing the activity, as well as the occupant's gaze angle.

[0022] The occupant attributes and means described above are merely examples and are not limited to these. For example, the occupant's state can be detected using a wearable sensor worn by the occupant. Furthermore, the occupant's posture can be detected by installing a sensor in the seat belt (not shown) and detecting the seat belt tension, and the occupant's seating posture can be detected using a pressure sensor built into the seat. Furthermore, the occupant can input their own state (activity, posture, head orientation, etc.) using a human-machine interface (HMI) unit.

[0023] Figure 2 shows the interior of a vehicle with multiple occupants 201, 202, 203, and 204 engaged in various activities with various head orientations and gaze angles. To understand the predicted motion sickness (hereafter referred to as "motion sickness") of each occupant, Figure 2 also shows sample values ​​of the motion sickness incidence index (MSI) as an example of the likelihood of developing motion sickness (motion sickness susceptibility). The larger the absolute value of the MSI, the more likely a person is to develop motion sickness.

[0024] 2, the MSIs of occupants 201, 202, 203, and 204 are −10, −5, −11, and −15, respectively. Therefore, occupant 204, who is using smartphone 113 and facing backward (the opposite direction to the traveling direction of vehicle 200), is most likely to develop motion sickness.

[0025] Fig. 3 is a diagram showing an overall outline of the vehicle integrated control device of this embodiment. As shown in Fig. 3, the vehicle integrated control device of this embodiment mainly comprises three modules: a multiple occupant monitoring unit 301 that predicts the motion sickness susceptibility of each occupant, a control target integration unit 302 that integrates various targets to find the optimum control target for the multiple occupants, and a vehicle motion control unit 303 that controls vehicle motion based on the control target 309 integrated by the control target integration unit 302. The multiple occupant monitoring unit 301 corresponds to the multiple occupant monitoring units 102, 108, and 111 in Figs. 1 and 2.

[0026] The multiple occupant monitoring unit 301 has five subunits: an occupant posture / activity determination unit 304 that determines the posture and activity of occupants; a head movement determination unit 305 that determines the movement, direction, and gaze angle of occupants' heads; a vehicle movement determination unit 306 that determines the movement of the vehicle; a motion sickness prediction unit 307 that predicts motion sickness for multiple occupants using a sensory discrepancy model, etc.; and a motion sickness susceptibility index output unit 308.

[0027] The multi-occupant monitoring unit 301 utilizes various occupant attributes and vehicle motion to predict motion sickness susceptibility for multiple occupants.

[0028] The control target integration unit 302 acquires and integrates the motion sickness susceptibility indices of individual occupants to calculate various integrated control targets 313 and estimate the final control target 309. The control target integration unit 302 can also use multiple other vehicle performance control targets, such as crash safety and travel time, to derive the control target 309 and integrate them with the motion sickness susceptibility index output from the motion sickness susceptibility index output unit 308 to estimate the multi-purpose control target 309.

[0029] The vehicle motion control unit 303 takes the estimated control objectives 309 and derives vehicle motion that can limit or reduce the estimated control objectives 309 based on motion sickness prediction 311 and vehicle motion. The optimized vehicle motion is ultimately used to generate actuator inputs 310.

[0030] The 6-degree-of-freedom momentum control section 312 of the vehicle motion control unit 303 controls the vehicle's attitude angles (roll angle, pitch angle, yaw angle, forward / backward angle, left / right angle, up / down angle) so that the vehicle's 6-axis momentum (roll rate, pitch rate, yaw rate, forward / backward acceleration, left / right acceleration, up / down acceleration) is minimized at the position where the controlled object is located.

[0031] Each of the above units will now be described in detail.

[0032] [Multiple Occupant Monitoring Unit 301] The multi-occupant monitoring unit 301 includes one or more sensors capable of detecting various occupant attributes such as occupant activity, line of sight, gaze angle, head movement, head orientation, and posture, as well as the orientation of the vehicle seats and the interior configuration of the vehicle. The sensors used for occupant monitoring may be, for example, one or more cameras with a monocular or stereo configuration. These sensors are not limited to cameras, but may also include LiDAR, seat-embedded pressure / weight sensors, wearable sensors worn by occupants such as smartwatches and smartphones, seatbelt tension sensors, etc.

[0033] Furthermore, even when cameras are used in the multiple occupant monitoring unit 301, there can be multiple variations, such as infrared cameras, thermal cameras that can detect heat, fisheye cameras (360-degree cameras), panoramic cameras, etc., which can be used to detect the required occupant attributes.

[0034] An occupant monitoring unit equipped with active sensors such as those described above to detect occupant attributes required for motion sickness prediction is called an "active occupant monitoring unit."

[0035] However, in some cases, occupants can also input their own information via a human-machine interface (HMI) unit installed in the vehicle. Such systems are called "passive occupant monitoring units." Passive occupant monitoring units allow all occupants, individually or as a group, to input information about their own state (occupant activity, head movement, head orientation, gaze angle, seat orientation, posture, etc.).

[0036] Alternatively, in some cases, active and passive occupant monitoring units may be combined to form a hybrid occupant monitoring unit.

[0037] In the case of a hybrid occupant monitoring unit, if the active occupant monitoring unit is able to detect most of the required occupant attributes but is unable to detect some of the required occupant attributes, the occupant monitoring unit can prompt the required occupant to input the required attributes.

[0038] Therefore, the multiple occupant monitoring unit 301 can have three variations: an active occupant monitoring unit, a passive occupant monitoring unit, and a hybrid occupant monitoring unit. All the above-mentioned occupant monitoring unit configurations can be combined in various ways to meet user requirements.

[0039] [Motion Sickness Prediction Unit 307] The motion sickness prediction unit 307 obtains the outputs of the occupant posture / activity determination unit 304, the head movement determination unit 305, and the vehicle movement determination unit 306, and predicts the susceptibility of each occupant to motion sickness. The motion sickness prediction unit 307 can use learning models such as a six-degree-of-freedom subjective vertical competition motion sickness model or a sensory discrepancy model to predict the susceptibility of each occupant to motion sickness.

[0040] Furthermore, the motion sickness prediction unit 307 can estimate the vehicle motion perceived by each occupant to predict the susceptibility to motion sickness using the detected occupant states (occupant activity, head movement, head orientation, gaze angle, seat direction, posture, etc.). If it is difficult to estimate the vehicle motion perceived by the occupants, the motion of the own vehicle can be detected and used to predict the susceptibility to motion sickness.

[0041] The motion sickness prediction unit 307 may also label each occupant's susceptibility to motion sickness in motion sickness symptoms such as nausea, nausea episodes, headache, headache episodes, vomiting, vomiting episodes, etc.

[0042] The motion sickness prediction unit 307 may also use one or more detected occupant attributes for motion sickness prediction.

[0043] [Motion Sickness Susceptibility Index Output Unit] The motion sickness susceptibility index output unit 308 converts the susceptibility of each occupant to motion sickness predicted by the motion sickness prediction unit 307 into a motion sickness susceptibility index such as a motion sickness incidence rate (MSI), and outputs it to the control target integration unit 302.

[0044] [Control Objective Integration Unit 302] The control target integration unit 302 uses the motion sickness susceptibility of each occupant predicted by the motion sickness prediction unit 307 to integrate and estimate control targets that can limit or reduce the motion sickness susceptibility of multiple occupants.

[0045] Furthermore, the control target integration unit 302 can select passengers who are prone to developing motion sickness as control targets.

[0046] The control target integration unit 302 can also use a rule-based model to estimate the control target, so that if the predicted occupant motion sickness susceptibility is such that one occupant is prone to vomiting while another occupant experiences a mild headache, the occupant who is prone to vomiting is selected as the control target.

[0047] In some cases, if all occupants experience motion sickness to a similar degree, the average motion sickness susceptibility of all occupants can be considered as the control target.

[0048] Furthermore, occupant motion sickness susceptibility as a control objective can be integrated with vehicle performance control objectives such as crash safety, travel time, etc. to formulate a minimization control cost function that can limit occupant motion sickness susceptibility and required vehicle performance.

[0049] [Vehicle Motion Control Unit 303] The vehicle motion control unit 303 takes the output of the control target integration unit 302 to estimate the vehicle motion and reduce or limit the control targets.

[0050] The six-degree-of-freedom momentum control section 312 of the vehicle motion control unit 303 uses the control target 309 to estimate the vehicle's six-axis momentum, namely, roll rate, pitch rate, yaw rate, longitudinal acceleration, lateral acceleration, and vertical acceleration (heave motion).

[0051] These estimated vehicle motions are used to derive actuator inputs 310 such as required suspension stroke, brake commands, throttle commands, steering commands, etc.

[0052] In some cases, the output of the control target integration unit 302 may also be used to estimate the posture of individual occupants to limit their susceptibility to motion sickness. In such cases, individual active suspension or seat actuators positioned specifically to act on a particular occupant may be activated to mitigate the occupant's likelihood of developing motion sickness.

[0053] Additionally, the vehicle motion control unit 303 can notify the occupants to prepare for uncomfortable vehicle behavior when adverse conditions are expected for the vehicle's travel. For example, if the vehicle brakes suddenly to avoid a collision, the occupants' comfort is not guaranteed, so the vehicle motion control unit 303 notifies all passengers about the sudden change in motion.

[0054] Similarly, if the occupants are engaged in tasks unrelated to driving and the multi-occupant monitoring unit 301 is unable to correctly recognize movements that may lead to motion sickness, the on-board monitor can be used to display the situation outside the vehicle (driving scenario) in addition to the intended movements, i.e., the vehicle driving behavior.

[0055] In addition, if the autonomous vehicle supports multiple driving modes such as lane change driving mode, autonomous lane keeping mode, adaptive cruise control, traffic jam driving mode, and highway driving mode, the output of the control target integration unit 302 can be used to select the autonomous driving mode.

[0056] FIG. 4 is a diagram showing an example of the configuration of the passive occupant monitoring unit and the hybrid occupant monitoring unit described above.

[0057] As shown in the left diagram of Figure 4, the passive occupant monitoring unit allows all occupants to input the status information required to estimate their motion sickness susceptibility. Based on the activity predictions input by each occupant using the human-machine interface (HMI) (HMI input 406), the motion sickness susceptibility of all occupants is estimated using information 407 such as occupant activity, head movement, and gaze angle.

[0058] On the other hand, as shown in the right diagram of Figure 4, a hybrid occupant monitoring unit including an active occupant monitoring unit uses on-board sensors such as an occupant activity monitoring sensor 401, an on-board vehicle motion sensor 402, and an occupant posture and eye tracking sensor 405 to detect the occupant's status. The hybrid occupant monitoring unit is composed of both the measurement outputs of each active sensor, such as the occupant activity monitoring sensor 401, the on-board vehicle motion sensor 402, and the occupant posture and eye tracking sensor 405, and a human-machine interface-based input (HMI input 404). Based on all this information, a motion sickness prediction unit 307 estimates the occupant's susceptibility to motion sickness using information 403 such as occupant activity, head movement, and gaze angle.

[0059] FIG. 5 is a conceptual diagram of an algorithm 500 for predicting motion sickness susceptibility for multiple occupants.

[0060] The multiple occupant monitoring unit 501 acquires the measured attributes 511-514 of the multiple occupants in addition to the six-degree-of-freedom vehicle motion 502.

[0061] The vehicle motion acquisition unit 503 acquires the longitudinal acceleration a x , left-right (lateral) direction acceleration a y , vertical acceleration (heave motion) a zSix-degree-of-freedom vehicle motion attributes such as yaw rate, roll rate, and pitch rate are extracted and integrated with occupant attributes (information 510 such as occupant activity, head movement, gaze angle, and posture) obtained by multiple occupant monitoring units 501 to estimate vehicle motion 504 perceived by the occupants.

[0062] A motion sickness prediction unit 505 estimates and outputs individual motion sickness susceptibility indices 506-509 for all occupants based on the vehicle motion 504 perceived by the occupants.

[0063] FIG. 6 is a flowchart showing the selection of a motion sickness susceptibility index as a control target in the control target integration unit 302 when the motion sickness susceptibility indices of all passengers are given.

[0064] When the vehicle is switched on (step S601), in step S602, the multi-occupant monitoring unit 301 acquires information about the occupant's status, such as occupant activity, gaze angle, head direction, seating direction, etc., and information about vehicle motion.

[0065] Next, in step S603, the multiple occupant monitoring unit 301 predicts the motion sickness susceptibility of multiple occupants using a motion sickness prediction model (learning model) such as a six-degree-of-freedom subjective vertical competitive motion sickness model or a sensory discrepancy model.

[0066] Next, in step S604, the control target integration unit 302 searches for occupants who are likely to develop motion sickness based on the motion sickness susceptibility indices of all occupants provided by the multi-occupant monitoring unit 301. If an occupant who is likely to develop motion sickness is found (Yes), the occupant with the worst motion sickness susceptibility is selected as the control target (step S607).

[0067] On the other hand, if no occupant who is prone to motion sickness is found (No), the process proceeds to step S605, where it is determined whether all occupants have the same level of motion sickness susceptibility. If it is determined that all occupants have the same level of motion sickness susceptibility (Yes), the motion sickness susceptibility of all occupants is averaged, and the average motion sickness susceptibility is selected as the control target (step S608).

[0068] If it is determined that the occupants' susceptibility to motion sickness is different (not the same level) (No), the process proceeds to step S606, where it is determined that there is no clear trend in the susceptibility of all occupants to motion sickness, and the occupants are notified and asked for assistance in inputting information about the occupants via a human-machine interface (HMI) unit, etc. Then, a control target is estimated based on the information input from the HMI unit, etc. (step S609).

[0069] Finally, in step S610, it is determined whether the movement by the vehicle is complete, i.e., whether the destination set by the occupant has been reached, and if it is determined that the movement is complete (Yes), the process ends (step S611). If it is determined that the movement is not complete (No), the process returns to step S602, and the processes from step S602 onwards are repeated.

[0070] FIG. 7 is a flowchart illustrating the formulation of a minimized control cost function that can achieve the control objective.

[0071] When the control target integration unit 302 detects a vehicle switch-on signal, it starts the process of formulating a minimization control cost function (step S701).

[0072] First, in step S702, a number of control objectives are obtained, such as travel time, crash safety, and a selected motion sickness susceptibility index.

[0073] Next, in step S703, all the acquired control targets are integrated to estimate a minimization control cost function.

[0074] Next, in step S704, the estimated minimization control cost function is used to calculate the six-degree-of-freedom vehicle motion (front-rear acceleration a x , left-right (lateral) direction acceleration a y , vertical acceleration (heave motion) a z The cost function values ​​for the velocity, yaw rate, roll rate, and pitch rate are estimated.

[0075] Next, in step S705, the vehicle motion profile with the lowest cost is selected.

[0076] Finally, in step S706, it is determined whether the movement by the vehicle is complete, i.e., whether the destination set by the occupant has been reached, and if it is determined that the movement is complete (Yes), the process ends (step S707). If it is determined that the movement is not complete (No), the process returns to step S702, and the processes from step S702 onwards are repeated. [Example]

[0077] Second Embodiment A vehicle integrated control device and a vehicle integrated control method according to a second embodiment of the present invention will be described with reference to FIG.

[0078] FIG. 8 is a diagram showing a driving scenario in which a host vehicle 801 carrying multiple passengers is navigated to a destination.

[0079] 8, the host vehicle 801 must travel within a driving lane defined by lane boundaries 803, 804, and 806. There is also a possibility that an oncoming vehicle 802 may be present, and the host vehicle 801 must avoid a collision with the oncoming vehicle 802 or an obstacle 805.

[0080] For this reason, the control target integration unit 302 of this embodiment further includes a route planning unit 810 that plans a route for the host vehicle 801 to the destination.

[0081] The route planning unit 810 generates a plurality of route candidates 807-809 based on the motion sickness susceptibility of a plurality of occupants. The route planning unit 810 also checks the feasibility of all route candidates with respect to the motion sickness susceptibility of each occupant, and outputs the feasible route candidates as a route candidate table 811. Then, it selects a route that minimizes the motion sickness susceptibility (motion sickness incidence: MSI) of the plurality of occupants. In the example of the route candidate table 811 in FIG. 8, the route candidate 808 is the route that minimizes the motion sickness susceptibility (MSI) of the plurality of occupants.

[0082] The vehicle motion control unit 303 navigates the vehicle 801 according to the selected route candidate 808 until it reaches the destination, while controlling the vehicle's attitude angle so that the vehicle's six-axis momentum (roll rate, pitch rate, yaw rate, forward / backward acceleration, left / right acceleration, and up / down acceleration) is minimized. [Example]

[0083] Third Embodiment A vehicle integrated control device and a vehicle integrated control method according to a third embodiment of the present invention will be described with reference to FIG.

[0084] FIG. 9 is a diagram showing a driving scenario in which a driving action is selected based on the motion sickness susceptibility of multiple occupants.

[0085] In the driving scenario shown in Fig. 9, the host vehicle 901 must brake to stop in front of an obstacle 902. For example, if the host vehicle 901 is traveling at 70 miles per hour and attempts to stop in front of the obstacle 902, there are possible driving actions, such as braking suddenly to stop the vehicle in a braking distance of 60 meters, or braking smoothly to stop the vehicle in a braking distance of 70 meters. Vehicle actions such as braking affect the onset of motion sickness in the occupants.

[0086] For this reason, the control target integration unit 302 of this embodiment further includes a driving behavior selection unit 903 that selects a driving behavior of the host vehicle 901 .

[0087] The driving action selection unit 903 generates a plurality of candidate driving actions based on the motion sickness susceptibility of the plurality of occupants. The driving action selection unit 903 also checks the feasibility of all candidate driving actions related to the motion sickness susceptibility of each occupant and outputs the feasible candidate driving actions as a driving action selection table 904. Then, the driving action that minimizes the motion sickness susceptibility (MSI: Motion Sickness Incidence) of the plurality of occupants is selected. In the example of the driving action selection table 904 in FIG. 9, smooth braking is the driving action that minimizes the motion sickness susceptibility (MSI) of the plurality of occupants.

[0088] The vehicle motion control unit 303 controls the vehicle's attitude angle so that the vehicle's six-axis momentum (roll rate, pitch rate, yaw rate, forward / backward acceleration, left / right acceleration, and up / down acceleration) is minimized, and stops the host vehicle 901 in front of the obstacle 902 using the selected smooth brake. [Example]

[0089] Fourth Embodiment With reference to FIG. 10, a vehicle integrated control device and a vehicle integrated control method according to a fourth embodiment of the present invention will be described.

[0090] 10 is a diagram showing a state in which multiple occupants 1001 to 1004 are performing various activities (tasks) unrelated to driving. As in the first embodiment (FIG. 2), each occupant is assigned a motion sickness susceptibility index (motion sickness incidence rate: MSI) as a measure of their motion sickness susceptibility.

[0091] In the example of FIG. 10, occupant 1004, who has the largest absolute value of MSI, is considered to be the most susceptible to developing motion sickness.

[0092] Therefore, in this embodiment, the vehicle motion control unit 303 activates the active suspension 1006, of the active suspensions 1005 to 1008, which is closest to the occupant 1004 who is most susceptible to developing motion sickness, to locally reduce the shaking acting on the occupant 1004 and reduce the possibility of the occupant 1004 developing motion sickness. [Example]

[0093] Fifth Embodiment A vehicle integrated control device and a vehicle integrated control method according to a fifth embodiment of the present invention will be described with reference to FIG.

[0094] 11 is a diagram showing a state in which multiple occupants 1101 to 1104 are performing various activities (tasks) unrelated to driving. As in the first embodiment (FIG. 2), each occupant is assigned a motion sickness susceptibility index (motion sickness incidence rate: MSI) as a measure of their motion sickness susceptibility.

[0095] In Example 4 (Figure 10), the shaking acting on the occupant 1004 is locally reduced by activating the active suspension 1006 closest to the occupant 1004 who is most susceptible to motion sickness. In this example, in addition to activating the active suspension 1006, the active seats 1105 to 1108 can also be used to change the posture of the occupant.

[0096] Therefore, for the occupant 1104 who is most susceptible to motion sickness, the active suspension 1006 closest to the occupant 1104 is activated, and the active seat 1106 in which the occupant 1104 is seated is activated to change the posture of the occupant 1104, thereby further suppressing the effects of motion sickness on the occupant 1104.

[0097] This reduces the possibility of the occupant 1104 developing motion sickness without affecting the other occupants 1101 to 1103. [Example]

[0098] Sixth Embodiment With reference to FIG. 12, a vehicle integrated control device and a vehicle integrated control method according to a sixth embodiment of the present invention will be described.

[0099] FIG. 12 shows a passenger 1201 not involved in driving and an in-vehicle monitor 1202 for reducing susceptibility to motion sickness.

[0100] Depending on the occupant's activities and the state of the vehicle, the occupant 1201 may not be able to see outside to perceive vehicle motion. In such a situation, there is a concern that unexpected vehicle motion may increase the occupant's 1201 susceptibility to motion sickness and make them more susceptible to developing motion sickness.

[0101] Therefore, in this embodiment, in order to allow the occupant 1201 to recognize the future vehicle behavior, the vehicle driving scenario and the estimated vehicle behavior are displayed on the in-vehicle monitor 1202.

[0102] The occupant 1201 can take a posture to prepare for future vehicle motion by checking the vehicle driving scenario and future vehicle movement displayed on the in-vehicle monitor 1202. This reduces the possibility of the occupant 1201 developing motion sickness.

[0103] In addition to the on-board monitor 1202, audio signals may also be used, for example, to allow the occupant 1201 to more accurately predict the vehicle's movements.

[0104] If the vehicle is a private car regularly used by specific occupants, the multiple occupant monitoring unit 301 can also learn the regular behavior of the occupants. In this case, the control target integration unit 302 uses the occupant behavior data related to the specific vehicle movement to generate a correlation function for presetting the vehicle driving mode, and the vehicle movement control unit 303 can control the vehicle movement based on the correlation function to suppress the effects of motion sickness on the occupants.

[0105] The control target integration unit 302 may also use the recorded travel time history of the occupant to determine the control targets.

[0106] The vehicle motion control unit 303 can also easily switch between various operating modes. The vehicle motion control unit 303 can also preset the vehicle motion when a normal occupant is using the vehicle.

[0107] Additionally, for new occupants or occupants for whom no previous history is available, the control target integration unit 302 operates in a normal mode, predicting each occupant's susceptibility to motion sickness and estimating control targets for deriving vehicle motion.

[0108] Additionally, based on the control objectives, the vehicle motion control unit 303 may warn occupants who are most susceptible to motion sickness before they develop motion sickness.

[0109] The present invention is not limited to the above-described embodiments and includes various modifications. For example, the above-described embodiments have been described in detail to clearly explain the present invention, and the present invention is not necessarily limited to those including all of the described configurations. Furthermore, it is possible to replace part of the configuration of one embodiment with the configuration of another embodiment, or to add the configuration of another embodiment to the configuration of one embodiment. Furthermore, it is possible to add, delete, or replace part of the configuration of each embodiment with other configurations. [Explanation of symbols]

[0110] 100, 200, 1000, 1100...vehicles 101, 103, 107, 109... Seats 102, 108, 111, 301, 501...Multiple Occupant Monitoring Unit 104,105,106,110,201,202,203,204,1001,1002,1003,1004,1101,1102,1103,1104,1201...Crew 112...Headphones 113...Smartphone 114...Mobile tablet 115...books 302...Control Target Integration Unit 303...Vehicle motion control unit 304…Occupant posture and activity determination unit 305...Head motion determination unit 306...Vehicle motion judgment unit 307,505...Motion Sickness Prediction Unit 308...Motion sickness susceptibility index output unit 309...Control target 310...Actuator input 311...Motion sickness prediction 312...6-DOF momentum control unit 313...Integrated control objectives 401...Occupant activity monitoring sensor 402...In-vehicle vehicle motion sensor 403, 407, 510...Information on occupant activity, head movement, gaze angle, etc. 404, 406...HMI input 405...Occupant posture and eye tracking sensor 500...Motion sickness susceptibility prediction algorithm 502...6-DOF vehicle motion 503...Vehicle Motion Acquisition Department 504...Vehicle behavior as perceived by occupants 506~509...Motion sickness susceptibility index 511~514...Crew member attributes 801,901...Own vehicle 802...Oncoming vehicle 803, 804, 806...Lane boundaries 805, 902... Obstacles 807~809...Route candidates 810...Path Planning Unit 811...Route candidate table 903... Driving operation selection unit 904...Driving action selection table 1005~1008...Active suspension 1105~1108...Active Seat 1202...In-vehicle monitor

Claims

1. an occupant monitoring unit that monitors a plurality of occupants; a vehicle motion acquisition unit that acquires information about the current vehicle motion of the vehicle; a motion sickness susceptibility prediction unit that estimates the vehicle motion perceived by the occupants based on the results of occupant monitoring by the occupant monitoring unit and information about the vehicle motion acquired by the vehicle motion acquisition unit, and predicts the individual susceptibility of each occupant to motion sickness caused by vehicle motion based on the vehicle motion perceived by the occupants; a control target determination unit that integrates the motion sickness susceptibility of each occupant predicted by the motion sickness susceptibility prediction unit and determines a control target based on the integration result; a vehicle motion control unit that determines a content of vehicle motion control based on the control target determined by the control target determination unit, The motion sickness susceptibility prediction unit is a vehicle integrated control device that, when it is difficult to estimate the vehicle motion perceived by the occupant, predicts the motion sickness susceptibility using information regarding the vehicle motion acquired by the vehicle motion acquisition unit.

2. The vehicle integrated control device according to claim 1, The vehicle motion control unit is a vehicle integrated control device that controls the attitude angle of the vehicle so that the six-axis momentum of the vehicle, which are roll rate, pitch rate, yaw rate, forward / backward acceleration, left / right acceleration, and up / down acceleration, are minimized.

3. The vehicle integrated control device according to claim 1, the occupant monitoring unit includes one or more sensors; A vehicle integrated control device that detects at least one of an occupant's activity, line of sight, gaze angle, head movement, head direction, posture, seat direction, and vehicle interior configuration.

4. The vehicle integrated control device according to claim 1, The control target determination unit selects the motion sickness susceptibility of the occupant with the worst motion sickness susceptibility predicted by the motion sickness susceptibility prediction unit, and determines a control target based on the selected motion sickness susceptibility.

5. The vehicle integrated control device according to claim 1, The control target determination unit is a vehicle integrated control device that averages the motion sickness susceptibility of each occupant predicted by the motion sickness susceptibility prediction unit and determines a control target based on the averaged motion sickness susceptibility.

6. The vehicle integrated control device according to claim 1, A human-machine interface unit is provided for inputting information about the occupants. The control target determination unit is a vehicle integrated control device that determines a control target based on information input from the human-machine interface unit.

7. The vehicle integrated control device according to claim 1, The control target determination unit determines the control target by selecting and integrating at least one of collision safety and travel time in addition to the motion sickness susceptibility of each occupant predicted by the motion sickness susceptibility prediction unit.

8. The vehicle integrated control device according to claim 1, The control target determination unit determines the control target using a recorded travel time history of the occupant.

9. The vehicle integrated control device according to claim 1, The vehicle motion control unit is a vehicle integrated control device that selects a driving mode including at least one of a lane change driving mode, an autonomous lane keeping driving mode, an adaptive cruise control, a traffic jam driving mode, and a highway driving mode based on the control target.

10. The vehicle integrated control device according to claim 1, The vehicle motion control unit is a vehicle integrated control device that reduces the possibility of motion sickness occurring in the occupant who is most susceptible to developing motion sickness by activating the active suspension near the occupant who is most susceptible to developing motion sickness or the active seat in which the occupant is seated based on the control target.

11. The vehicle integrated control device according to claim 1, The vehicle motion control unit is a vehicle integrated control device that warns an occupant who is most susceptible to motion sickness before the occupant develops motion sickness based on the control target.

12. The vehicle integrated control device according to claim 1, If a particular occupant regularly uses the vehicle, the occupant monitoring unit learns the occupant's behavior regarding the movement of the vehicle; the control target determination unit uses the learned occupant behavior data to generate a correlation function for presetting a driving mode of the vehicle; The vehicle motion control unit is a vehicle integrated control device that controls the vehicle motion of the vehicle based on the correlation function.

13. The vehicle integrated control device according to claim 1, A vehicle integrated control device including an on-board monitor that displays a vehicle driving scenario and estimated vehicle movement, or an audio output device that outputs the vehicle driving scenario and estimated vehicle movement as an audio signal. (a) monitoring a plurality of occupants; (b) obtaining information about the current vehicle dynamics of the vehicle; (c) estimating vehicle motion perceived by the occupants based on the results of the occupant monitoring in step (a) and the information on vehicle motion acquired in step (b), and predicting each occupant's individual susceptibility to motion sickness caused by vehicle motion based on the vehicle motion perceived by the occupants; (d) integrating the motion sickness susceptibility of each occupant predicted in step (c) and determining a control target based on the integration result; (e) determining the content of vehicle motion control based on the control target determined in the step (d), In the step (c), if it is difficult to estimate the vehicle motion perceived by the occupant, the vehicle integrated control method predicts the motion sickness susceptibility using information regarding the vehicle motion obtained in the step (b).

15. The vehicle integrated control method according to claim 14, (f) a step of controlling the attitude angle of the vehicle based on the content of the vehicle motion control determined in step (e) so that the six-axis momentum of the vehicle, namely, roll rate, pitch rate, yaw rate, forward / backward acceleration, left / right acceleration, and up / down acceleration, is minimized.

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