control device

Abstract

The present disclosure provides a control device capable of improving safety when a passenger gets off a vehicle compared to the past. The control device (10) of the present disclosure is mounted on a vehicle (1). The control device (10) includes an attention estimation unit (11) and a getting-off restriction unit (12). The attention estimation unit (11) estimates the attention of a passenger to an approaching object approaching the vehicle (1) based on a detection result of at least one of a passenger sensor (3) that detects the action of the passenger of the vehicle (1) or a vehicle sensor (4) that detects the state of the vehicle (1). In a case where the attention of the passenger estimated by the attention estimation unit (11) is lower than a predetermined threshold, the getting-off restriction unit (12) causes at least one of a door opening and closing device (6), a voice output device (7), and an image display device (8) mounted in the vehicle (1) to perform a getting-off restriction operation.

Description

Technical Field

[0001] This disclosure relates to a control device mounted in a vehicle. Background Technology

[0002] There have been known inventions related to exit assist devices that can more reliably detect approaching objects coming towards a vehicle and thus improve the safety of occupants when exiting the vehicle (see Patent Document 1 below). The exit assist device described in Patent Document 1 includes an approach detection unit, an exit restriction unit, an exit action detection unit, a control unit, and multiple first detection units.

[0003] The approach object detection unit is configured to detect an approach object approaching the vehicle from the rear side. The exit restriction unit is configured to perform an action including an alarm action and / or a door opening restriction action, i.e., an exit restriction action. The alarm action is an action to sound an alarm regarding the doors equipped with the vehicle, and the door opening restriction action is an action to restrict the opening of the doors. The exit action detection unit is configured to detect the action of an occupant of the vehicle intending to exit, i.e., an exit action.

[0004] The control unit is configured to, when the disembarkation action detection unit detects the disembarkation action and the approaching object detection unit detects the approaching object, perform disembarkation restriction control, at least for the door closest to the approaching object, by instructing the disembarkation restriction unit to perform the disembarkation restriction action. The first detection unit is configured to detect objects present around the vehicle. At least two of the first detection units are also second detection units, and the second detection units are configured to detect the approaching object approaching the vehicle from the rear.

[0005] The control unit determines, based on at least one detection result from the first detection unit, whether the state of an object obstructing the detection of the approaching object (i.e., a blockage) existing behind the vehicle, i.e., the first state, is established when the vehicle is parked or stopped. The control unit is configured such that, when the first state is determined to be established, the third detection unit (pre-set to function as the approaching object detection unit in the first state) is used as the approaching object detection unit.

[0006] Furthermore, the control unit determines, based on at least one detection result from the first detection unit, whether the second state (i.e., the state in which no obstruction exists behind the vehicle) is established when the vehicle is parked or stopped. The control unit is configured to, when determining that the second state is established, use the fourth detection unit (pre-set to function as the proximity detection unit in the second state) as the proximity detection unit. Existing technical documents Patent documents

[0007] Patent Document 1: Japanese Patent Application Publication No. 2020-093567 Summary of the Invention The problem the invention aims to solve

[0008] The aforementioned conventional exit assist device uses an external electronic rearview mirror (third detection unit) to detect approaching objects in the first state where there are obstructions behind the vehicle, and uses a rear side radar (fourth detection unit) to detect approaching objects in the second state where there are no obstructions behind the vehicle (Patent Document 1, paragraph 0016). However, this conventional exit assist device, for example, has the issue that the external electronic rearview mirror used in the first state may fail to detect approaching objects due to factors such as heavy rain, dense fog, nighttime, or backlighting, which could reduce the safety of passengers when exiting the vehicle.

[0009] This disclosure provides a control device that improves the safety of passengers when disembarking compared to previous methods. Technical means to solve the problem

[0010] One aspect of this disclosure is a control device mounted in a vehicle, characterized by comprising: an attention inference unit that infers the attention level of the occupant to an approaching object approaching the vehicle based on the detection result of at least one of an occupant sensor that detects the occupant's actions or a vehicle sensor that detects the vehicle's state; and an exit restriction unit that, when the attention level inferred by the attention inference unit is lower than a predetermined threshold, causes at least one of a door opening / closing device, a voice output device, and an image display device mounted in the vehicle to perform an exit restriction action. The effects of the invention

[0011] According to this disclosure, a control device can be provided that causes at least one of a door opening / closing device, a voice output device, and an image display device to perform an exit restriction action based on a decrease in the occupant's attention, thereby improving the safety of the occupant when exiting the vehicle compared to the past. Attached Figure Description

[0012] Figure 1 This is a functional block diagram illustrating one embodiment of the control device disclosed herein. Figure 2 To indicate that North Korea carries Figure 1 A top view of an example of a vehicle approaching an object using a control device. Figure 3 To explain Figure 1 A flowchart of the operation of the control device. Detailed Implementation

[0013] Hereinafter, with reference to the accompanying drawings, one embodiment of the vehicle control device disclosed herein will be described. Figure 1 This is a functional block diagram illustrating one embodiment of the control device disclosed herein.

[0014] The control device 10 in this embodiment is, for example, an electronic control unit (ECU) installed in a vehicle 1 such as a gasoline vehicle, diesel vehicle, natural gas vehicle, hybrid vehicle, electric vehicle, fuel cell vehicle, or hydrogen engine vehicle. Although not shown in the figure, the control device 10 is, for example, composed of one or more microcontrollers including an input / output unit, a central processing unit (CPU), a memory, and a timer.

[0015] Vehicle 1 is equipped with, for example, external sensors 2, occupant sensors 3, vehicle sensors 4, a vehicle navigation system (CNS) 5, door opening and closing devices 6, a voice output device 7, and an image display device 8. Furthermore, although not illustrated, vehicle 1 possesses a drive system, a steering system, a braking system, and a control system for driving, turning, decelerating, and parking.

[0016] External sensors 2 include, for example, millimeter-wave radar, monocular cameras, stereo cameras, LiDAR, ultrasonic sensors, road-to-road communication devices, vehicle-to-vehicle communication devices, illuminance sensors, rain sensors, and humidity sensors. External sensors 2 detect objects around vehicle 1, including roads, white lines, signs, traffic lights, vehicles, pedestrians, and obstacles, as well as the surrounding environment, including illuminance, rainfall, humidity, and the visibility distance of obstacles, and output the results to control device 10.

[0017] Occupant sensors 3 include, for example, seating sensors, motion capture systems, eye trackers, facial recognition systems, voice recognition systems, and seatbelt sensors. Occupant sensors 3 detect, for example, the pre-exit actions of occupants of vehicle 1, the occupant's age, etc., and output the detection results to control device 10. The pre-exit actions detected by occupant sensors 3 include, for example, eye movement and body movement towards the door, occupant's speech related to exiting the vehicle, and the loosening of the seatbelt.

[0018] Vehicle sensors 4 include various sensors that detect the vehicle's status, such as wheel speed sensors, acceleration sensors, and gear position sensors. These sensors detect vehicle status including speed, acceleration, transmission gear position, and any abnormalities in vehicle 1. Abnormalities detected by vehicle sensors 4 include, for example, anomalies in tire air pressure, fuel level, engine, ABS (Anti-Lock Brake System), airbags, brakes, oil pressure, battery, and coolant temperature.

[0019] In addition, vehicle sensors 4 include, for example, door handle sensors, door switch sensors, and touch sensors, which detect alighting operations, including occupant operations on door handles and door switches, as well as occupant hand contact with door handles or door switches. Vehicle sensors 4 output the detected vehicle status and alighting operations to control device 10.

[0020] The CNS5 includes, for example, a map information storage device, a route calculation device, a vehicle-to-vehicle communication device, a road-to-road communication device, and a Global Positioning System (GNSS) receiver. Furthermore, the CNS5 includes, for example, an input device for the occupants of vehicle 1 to input their destination. The CNS5 outputs, for example, location information on a map based on the location information of vehicle 1, and route information from the current location of vehicle 1 to the destination, to the control device 10.

[0021] The door opening and closing device 6 includes, for example, one or more actuators and a power transmission mechanism, which automatically unlocks, opens, closes, and locks the hinged doors, sliding doors, or other types of doors of the vehicle 1 according to the control signals input from the control device 10. The voice output device 7 is, for example, a speaker installed in the vehicle 1's interior, which outputs warning sounds or voice guidance according to the control signals input from the control device 10.

[0022] The image display device 8 is, for example, a liquid crystal display, an organic EL display, or a head-up display, and displays images based on control signals input from the control device 10. Additionally, the image display device 8 may also include input devices such as a touch panel or operation buttons. For example, occupants of vehicle 1 can input information such as their destination to the CNS5 via the input devices of the image display device 8.

[0023] The control device 10 of this embodiment is mounted in the vehicle 1 and functions as an alighting assistance device to assist the occupants of the vehicle 1 in disembarking. The control device 10 includes an attention inference unit 11 and an alighting restriction unit 12. In addition, the control device 10 may include at least one of the following: an approach object detection unit 13, an alighting action detection unit 14, an occupant behavior detection unit 15, a vehicle status detection unit 16, an alighting environment detection unit 17, an arrival prediction unit 18, and a work determination unit 19.

[0024] Figure 1 Each part of the control device 10 shown is, for example, a function block representing the function of the control device 10, which is implemented by the CPU constituting the control device 10 executing a program stored in the memory constituting the control device 10. Other functions of the control device 10 besides the attention inference unit 11 and the exit restriction unit 12 may also be implemented by a different ECU or microcontroller than the control device 10.

[0025] Below, for reference Figure 2 and Figure 3 The operation of each part of the control device 10 will be explained. Figure 2 A top view showing the state of the vehicle 1 equipped with the control device 10 parked on the roadside. Figure 3 A flowchart illustrating the operation of control device 10 is provided. For example, when the start switch of vehicle 1 is turned on, control device 10 repeatedly executes the following steps at a predetermined cycle. Figure 3 The processing flow is shown below.

[0026] When control device 10 starts Figure 3 In the processing flow shown, the first step is to determine whether vehicle 1 is parked, process P1. In this process P1, the vehicle status detection unit 16 of the control device 10 determines whether vehicle 1 has stopped, for example, based on the detection results input from the wheel speed sensor or acceleration sensor included in the vehicle sensor 4.

[0027] More specifically, for example, if the speed of vehicle 1, inferred from the wheel speed sensor's detection result (i.e., the rotational speed of the wheels of vehicle 1), is lower than the first threshold used for stopping determination, the vehicle state detection unit 16 determines that vehicle 1 has stopped. Furthermore, the vehicle state detection unit 16 may also determine that vehicle 1 has stopped based on the detection result of the gear position sensor included in vehicle sensor 4. Additionally, the vehicle state detection unit 16 detects, for example, the stopping time of vehicle 1.

[0028] When the vehicle status detection unit 16 determines in process P1 that the vehicle is not in a parking state (No), the control device 10 executes process P2 to determine whether the vehicle 1 is about to stop. In this process P2, for example, if the speed of the vehicle 1 is lower than a second threshold that is higher than a first threshold used for parking determination, the vehicle status detection unit 16 determines that the vehicle 1 is about to stop.

[0029] Furthermore, the vehicle status detection unit 16 can determine whether vehicle 1 is about to stop, for example, based on traffic lights, road signs, and road markings detected by external sensors 2, or map information of the vehicle 1's driving path input from CNS5. When the vehicle status detection unit 16 determines in process P2 that it is not about to stop (no), the control device 10 ends. Figure 3 The processing flow is shown below.

[0030] On the other hand, when the vehicle status detection unit 16 in process P1 determines that the vehicle is parked (yes), or when the occupant behavior detection unit 15 in process P2 determines that the vehicle is about to stop (yes), the control device 10 executes process P3, which detects the exit environment. In this process P3, the control device 10 detects the exit environment, for example, using the exit environment detection unit 17. The exit environment includes, for example, the illumination and weather around the vehicle 1, the status of the vehicle 1 waiting at a traffic light, the traffic conditions around the vehicle 1, including congestion, and location information related to the parking position of the vehicle 1.

[0031] More specifically, the off-vehicle environment detection unit 17 detects the illuminance around the vehicle 1, for example, based on the detection results of external sensors 2 such as illuminance sensors. In addition, the off-vehicle environment detection unit 17 infers the weather around the vehicle 1, such as sunny, cloudy, rainy, snowy, or foggy, based on the detection results of external sensors 2 such as raindrop sensors, monocular cameras, and stereo cameras, as well as the operating status of the vehicle 1's windshield wipers or fog lights.

[0032] Furthermore, the off-vehicle environment detection unit 17 infers the visibility distance of the approaching object O, for example, based on the detection results of the external sensor 2 or weather information received by the receiver mounted on the vehicle 1. Additionally, the off-vehicle environment detection unit 17 detects the waiting status of the vehicle 1 at a traffic light, for example, based on the detection results of the external sensor 2 that detects objects around the vehicle 1 or by recognizing the display of traffic lights in front of the vehicle 1 through inter-vehicle communication, while simultaneously detecting the traffic conditions around the vehicle 1.

[0033] In addition, the exit environment detection unit 17 detects location information of the parking position of vehicle 1, such as parking lots, roundabouts in front of stations, road shoulders, and roads. Furthermore, the location information of vehicle 1's parking position can also be accurate location information based on high-precision 3D map information from CNS5.

[0034] When the process P3, which detects the exit environment, ends, the control device 10 executes the process P4, which determines whether an occupant has exited the vehicle. In this process P4, the exit action detection unit 14 of the control device 10 detects the exit action of the occupant of vehicle 1, for example, based on the detection results of the occupant sensor 3 or the vehicle sensor 4. Here, the exit action refers to, for example, the action taken by the occupant of vehicle 1 before exiting the vehicle.

[0035] The act of getting out of the vehicle includes, for example, preparatory actions and actual actions. Preparatory actions include, for example, the occupant of vehicle 1 removing their seatbelt, the occupant's eye movement, weight shift, or body movement when opening the door, or the occupant uttering keywords or greetings such as "get out" when getting out of the vehicle. Actual actions include, for example, the occupant's hand touching or operating the door opener or handle. Such actions are detected by the occupant sensor 3 or the vehicle sensor 4, and the action detection unit 14 determines whether an action has occurred based on the detection result of at least one of the occupant sensor 3 or the vehicle sensor 4.

[0036] By detecting disembarkation actions, including the occupant's preparatory disembarkation actions, as described above, the disembarkation of occupants can be predicted earlier. Furthermore, the disembarkation action detection unit 14 can predict, for example, the time until the occupant of vehicle 1 disembarks or the time until the door of vehicle 1 is opened based on the detected disembarkation actions, and output the predicted time to the attention inference unit 11 and the arrival prediction unit 18.

[0037] When the exit environment detection unit 17 in P4 determines that the passenger has no intention of exiting the vehicle (no), the control device 10 terminates. Figure 3 The processing flow is shown. On the other hand, when the disembarkation environment detection unit 17 determines that there is a disembarkation action (yes) in processing P4, the control device 10 executes processing P5 to determine whether there is an approaching object O.

[0038] In this process P5, the control device 10 determines the presence or absence of an approaching object O, for example, using a proximity detection unit 13. The proximity detection unit 13 detects the approaching object O based, for example, on the detection results of an external sensor 2 that detects objects around the vehicle 1. More specifically, the proximity detection unit 13 is like... Figure 2 As shown, based on the detection results of the external sensor 2, an object approaching from the rear side of the parked vehicle 1 toward the exit area A of the vehicle 1 will be detected as an approaching object O.

[0039] Here, "rear side" refers, for example, to the rear of the left and right sides of vehicle 1. Furthermore, the exit area A is, for example, the area where the doors of vehicle 1 open and close, and the area where passengers of vehicle 1 get on and off, and is located on the left and right sides and around vehicle 1 depending on the structure and position of the doors. The exit area A can, for example, be located adjacent to each door of vehicle 1. The proximity detection unit 13 calculates the position, speed, and direction of movement of objects around vehicle 1 based on the detection results of the external sensor 2, thereby detecting the approaching object O.

[0040] Objects detected as approaching objects O by the approaching object detection unit 13 include vehicles such as cars, self-propelled two-wheelers, and bicycles, as well as moving objects other than vehicles such as pedestrians and animals. Furthermore, the approaching object detection unit 13 can detect objects approaching drop-off area A whose remaining time to reach drop-off area A is shorter than a predetermined time threshold as approaching object O. The remaining time to reach can be calculated in the same way as the time remaining before collision (TTC). The approaching object detection unit 13 outputs approaching object information such as the position, speed, predicted path, and remaining time to reach corresponding drop-off area A to the arrival prediction unit 18.

[0041] When the proximity detection unit 13 determines in process P5 that there is no proximity object O (No), the control device 10 executes process P6, which determines the attention level of the occupants of vehicle 1. In this process P6, the occupant behavior detection unit 15 of the control device 10 detects at least one of the following based on the detection results of the occupant sensor 3: the type of occupant getting off vehicle 1 or the inattentive behavior when the occupant's attention level decreases.

[0042] More specifically, the occupant behavior detection unit 15 infers the age of the occupant whose disembarkation action is detected, for example, based on the detection results of the occupant sensor 3, such as a facial recognition system or an in-vehicle camera. Furthermore, the occupant behavior detection unit 15 categorizes the occupant whose disembarkation action is detected, for example, into age groups such as toddlers, children, minors, adults, and the elderly, based on the inferred age. The occupant behavior detection unit 15 outputs the inferred age and age group as the disembarking occupant category to the attention inference unit 11, for example. Additionally, the occupant behavior detection unit 15 detects the category of the disembarking occupant, such as the driver or fellow passengers, based on the seating position detected by the occupant sensor 3 or vehicle sensor 4, and outputs this category to the attention inference unit 11.

[0043] Furthermore, the occupant behavior detection unit 15 detects inattentive behavior when the attention of the occupants of vehicle 1 decreases, for example, based on the detection results of at least one of the occupant sensor 3 and the vehicle sensor 4. Inattentive behavior here includes, for example, insufficient safety confirmation by occupants disembarking from vehicle 1, and disembarking while occupants are talking to each other. More specifically, the occupant behavior detection unit 15 detects, for example, a situation where the face or line of sight of an occupant disembarking is not facing the rearview mirror or the rear side of vehicle 1 before or during the disembarking action as insufficient safety confirmation by the disembarking occupant, and outputs this detection result to the attention inference unit 11. Furthermore, the occupant behavior detection unit 15 identifies disembarking actions during conversation between occupants of vehicle 1 by recognizing whether each occupant of vehicle 1 is talking during their disembarking actions, and outputs this detection result to the attention inference unit 11.

[0044] Attention inference unit 11 infers the occupant's attention level to an approaching object O approaching the vehicle 1, for example, based on the detection result of at least one of the occupant sensor 3 that detects the occupant's actions or the vehicle sensor 4 that detects the state of the vehicle 1. Furthermore, in process P6, even if it was determined in the previous process P5 that there was no approaching object O, attention inference unit 11 infers the occupant's attention level to the approaching object O in the same way as in the previous process P5 where it was determined that there was an approaching object O.

[0045] More specifically, the attention inference unit 11 infers the occupant's attention level to the approaching object O based on information input from at least one of the exit action detection unit 14, the occupant behavior detection unit 15, the vehicle state detection unit 16, or the exit environment detection unit 17. The attention inference unit 11 receives, for example, input from the exit action detection unit 14 of the occupant's exit action as described above, and input from the occupant behavior detection unit 15 of at least one of the exit occupant category or inattentive behavior as described above.

[0046] Furthermore, the information input from the vehicle condition detection unit 16 to the attention inference unit 11 includes the following information detected by the vehicle condition detection unit 16. For example, the vehicle condition detection unit 16 detects, based on the detection results of the vehicle sensor 4, whether the vehicle 1 is about to stop, whether the vehicle 1 is stopping, the elapsed time since the vehicle 1 stopped, the gear position of the vehicle 1, and any abnormalities in the vehicle 1, and outputs this information to the attention inference unit 11. Additionally, the abnormalities in the vehicle 1 detected by the vehicle condition detection unit 16 include, for example, abnormalities related to tire air pressure, fuel level, oil pressure, battery, and coolant, collisions between the vehicle 1 and obstacles, and emergency stops caused by the operation of automatic emergency braking (AEB).

[0047] Furthermore, the information input from the exit environment detection unit 17 to the attention inference unit 11 includes the exit environment detected by the exit environment detection unit 17. The exit environment detection unit 17 detects the exit environment based on information input from at least one of the external sensor 2, the vehicle sensor 4, or the CNS5, as described above. As mentioned above, the exit environment includes, for example, the illumination and weather around the vehicle 1, the status of the vehicle 1 waiting at a traffic light, the traffic conditions around the vehicle 1, including congestion, and location information related to the parking position of the vehicle 1.

[0048] For example, if a passenger is detected getting out of the vehicle just before the vehicle 1 stops, or if the time from when the vehicle 1 stops until the passenger is detected getting out is shorter than a predetermined threshold, the attention inference unit 11 infers that the occupant's attention to the approaching object O is low. Furthermore, the attention inference unit 11 infers the occupant's attention to the approaching object O based, for example, on the detection results of the occupant's age, age group, or inattentive behavior by the occupant behavior detection unit 15. More specifically, for example, if the occupant detected getting out of the vehicle is a toddler or child, and inattentive behavior such as making a fuss inside the vehicle 1, indicating a decrease in attention to the surroundings of the vehicle 1, is detected, the attention inference unit 11 infers that the occupant's attention to the approaching object O is low.

[0049] Here, the so-called attention inference inference unit 11 infers that the occupant's attention level is low, for example, by setting the occupant's attention level to a lower level or value. More specifically, the occupant's attention level can be represented by, for example, high, medium, low levels or a value from 0 to 100. For example, while the vehicle 1 is in motion, the attention inference inference unit 1 sets the attention level of each occupant to a predetermined initial value, and while the vehicle 1 is stopped or just before stopping, it reduces the attention level of occupants who meet the aforementioned conditions for inferring low attention level.

[0050] Furthermore, the attention inference unit 11 infers low attention levels if, for example, it detects that an occupant performing the disembarkation action has not adequately confirmed the safety of the approaching object O by visually viewing the vehicle 1's interior rearview mirror, side rearview mirror, or rear side mirror. Additionally, the attention inference unit 11 infers the occupant's attention level to the approaching object O based, for example, on the recognition results of traffic light displays by the disembarkation environment detection unit 17 and the detection results of the vehicle 1's gear position by the vehicle status detection unit 16.

[0051] More specifically, when vehicle 1 is parked, in a gear other than P, and the traffic light is red (no movement allowed), the attention inference unit 11 infers that the occupant's attention to the approaching object O is low. This situation arises because an occupant exiting vehicle 1 rushes to get off before the traffic light turns green (allows passage), thus inferring that the occupant's attention to the approaching object O is low.

[0052] Furthermore, when the traffic around vehicle 1 is congested, the attention inference unit 11 infers that the occupant's attention to the approaching object O is low. This situation occurs when an occupant gets off vehicle 1 in a hurry before the temporarily stopped vehicle 1 moves forward, creating blind spots due to vehicles in front of and behind vehicle 1, thus inferring that the occupant's attention to the approaching object O is low.

[0053] Furthermore, for example, when the vehicle condition detection unit 16 detects an anomaly in vehicle 1, the attention inference unit 11 infers that the occupant's attention to the approaching object O is low, compared to when the vehicle condition detection unit 16 does not detect an anomaly in vehicle 1. The anomalies in vehicle 1 detected by the vehicle condition detection unit 16 include anomalies detected by the vehicle sensor 4 in areas such as tire pressure, fuel level, engine, ABS, airbags, brakes, oil pressure, battery, and coolant temperature. This is because when such anomalies in vehicle 1 are detected, such as a decrease in tire pressure, the driver of vehicle 1 focuses their attention on the location of the anomaly, such as the tires, resulting in decreased attention to the approaching object O.

[0054] Furthermore, for example, when the vehicle status detection unit 16 detects contact between vehicle 1 and other vehicles or objects, the attention inference unit 11 infers that the occupant's attention to the approaching object O is lower than when no contact is detected. This is because, when contact between vehicle 1 and other vehicles or objects is detected, the occupant of vehicle 1 focuses their attention on the vehicle or object that made contact or the contact point of vehicle 1, resulting in a decrease in attention to the approaching object O.

[0055] Furthermore, for example, when the vehicle status detection unit 16 detects the activation or sudden deceleration of the AEB of vehicle 1, the attention inference unit 11 infers that the occupant's attention to the approaching object O is lower than when the activation or sudden deceleration of the AEB of vehicle 1 is not detected. This is because when the AEB of vehicle 1 is activated or suddenly decelerated, the occupant of vehicle 1 will also focus their attention on other vehicles or objects that caused the AEB to activate or suddenly decelerate, or on whether they are in contact with vehicle 1, resulting in a decrease in attention to the approaching object O.

[0056] Here, the vehicle condition detection unit 16 detects, for example, the operation of AEB, rapid deceleration, and contact between vehicle 1 and other vehicles or objects based on the detection results of vehicle sensor 4. For example, the vehicle condition detection unit 16 detects rapid deceleration as a deceleration rate approximately 0.4 [G] to 0.6 [G] higher than the normal deceleration rate of vehicle 1. Furthermore, the vehicle condition detection unit 16 can detect AEB operation if it detects a deceleration rate 0.6 [G] or higher than the deceleration rate of a rapid deceleration performed by the driver of vehicle 1. Additionally, the vehicle condition detection unit 16 can detect contact or collision between vehicle 1 and other vehicles or objects if it detects a deceleration rate higher than the rate at which AEB operation is detected.

[0057] Furthermore, for example, the lower the illuminance around the vehicle 1 detected by the exit environment detection unit 17, the lower the attention level inference unit 11 infers the occupant's attention level to the approaching object O. Furthermore, for example, the shorter the visibility distance of obstacles around the vehicle 1 inferred by the exit environment detection unit 17, the lower the attention level inference unit 11 infers the occupant's attention level to the approaching object O. Such reductions in illuminance and visibility around the vehicle 1 are caused by exit environment conditions such as nighttime, cloudy days, rain, snow, and fog, resulting in reduced visibility of the approaching object O, thus leading to a lower inference of the occupant's attention level to the approaching object O.

[0058] Furthermore, for example, if the exit environment detection unit 17 detects strong winds exceeding a specified wind speed outside the vehicle 1, the attention inference unit 11 infers that the occupant's attention to the approaching object O is low. This is because the opening and closing of the vehicle 1's doors and the occupant's exit are affected by strong winds, causing the occupant to focus their attention on the doors and the exit area A, resulting in reduced attention to the approaching object O.

[0059] Furthermore, for example, the higher the difficulty of getting off the vehicle as determined by the exit environment detection unit 17, the lower the attention inference unit 11 infers the occupant's attention to the approaching object O. As mentioned above, the exit environment detection unit 17 detects the parking position of vehicle 1 based on the output of CNS5 installed in vehicle 1, and determines the difficulty of getting off the vehicle based on the parking position. The difficulty of getting off the vehicle determined by the exit environment detection unit 17 is the lowest in parking lots, and increases in the following order: roundabouts in front of stations, road shoulders, roads, and highways. This is because getting off the vehicle on highway shoulders and on highways involves the danger posed by other vehicles traveling at high speeds.

[0060] exist Figure 3 In the process P6 shown, the attention level inference unit 11 outputs the inferred occupant attention level to the work determination unit 19. If the occupant attention level input from the attention level inference unit 11 is higher than the prescribed attention level or the prescribed attention level threshold, the work determination unit 19 determines that the occupant's attention level is not low (NO). In this case, the control device 10 terminates the process without executing the reminders or door opening restrictions performed by the work determination unit 19 and the disembarkation restriction unit 12. Figure 3 The processing flow is shown below.

[0061] Thus, if no approaching object O is detected in process P5 as described above, and the occupant's level of attention is high in process P6 as described above, no exit restrictions such as reminders or door opening restrictions will be implemented. Therefore, the annoyance to occupants caused by unnecessary exit restrictions when exiting the vehicle in a safe condition can be eliminated. Furthermore, since process P6 as described above confirms that the occupant exiting vehicle 1 has sufficient attention to approaching object O, the safety of occupants exiting vehicle 1 can be improved even if approaching object O is not detected by external sensor 2.

[0062] On the other hand, in the aforementioned process P6, if the occupant's attention level input from the attention level inference unit 11 is below a predetermined attention level or a predetermined attention level threshold, the work judgment unit 19 determines that the occupant's attention level is low (yes). In this case, the control device 10 executes the reminder process P7 as a disembarkation restriction.

[0063] In this process P7, the work determination unit 19 determines the content of the reminder action based on the level or value of the occupant's attention level input from the attention inference unit 11. More specifically, the work determination unit 19 determines, for example, the content of the reminder action performed by at least one of the voice output device 7 and the image display device 8. The reminder action performed by the voice output device 7 includes, for example, the output of a warning tone or voice urging attention to the approaching object O. Furthermore, the reminder action performed by the image display device 8 includes the display of an image or text urging attention to the approaching object O. In addition, the reminder action may also include, for example, the steering of the vehicle 1 or the vibration of the seat performed by a vibration generating device (not shown).

[0064] The operation judgment unit 19 determines, for example, the warning tone output by the voice output device 7 or the image or text displayed by the voice and image display device 8 based on the level or value of the occupant's attention level input from the attention level inference unit 11. More specifically, when the level or value of the occupant's attention level is lower than a predetermined level or value, the operation judgment unit 19 selects, for example, the size, output time, and output frequency of the warning tone or voice or image or text to achieve the maximum reminder action.

[0065] On the other hand, if the occupant's level or value of attention is higher than a predetermined level or value, the operation judgment unit 19 may select a warning action that minimizes the size, output time, and output frequency of the warning tone, voice, image, or text. Furthermore, if the occupant's level or value of attention is below the minimum level or lower limit, the operation judgment unit 19 may determine that the door opening restriction performed by the door opening and closing device 6 serves as a warning action. The operation judgment unit 19 outputs the determined or selected warning action to the exit restriction unit 12.

[0066] exist Figure 3 In the process P7 shown, the exit restriction unit 12 outputs a control signal to at least one of the door opening / closing device 6, the voice output device 7, and the image display device 8 to implement the exit restriction reminder action input from the operation judgment unit 19. As a result, at least one of the door opening / closing device 6, the voice output device 7, and the image display device 8 executes the reminder action selected or determined by the operation judgment unit 19. Afterwards, the control device 10 terminates. Figure 3 The processing flow is shown below.

[0067] On the other hand, when Figure 3 When the proximity detection unit 13 determines that there is a proximity object O (yes) in the aforementioned process P5, the control device 10 executes the process P8 for predicting disembarkation conditions. In this process P8, the arrival prediction unit 18 of the control device 10 predicts the disembarkation conditions, for example, based on the disembarkation action of the occupants of vehicle 1 input from the disembarkation action detection unit 14. The disembarkation conditions include, for example, the disembarkation area A of vehicle 1 where the occupants are disembarking, the open door of vehicle 1, or the time when the occupants are disembarking in the disembarkation area A. After the process P8 for predicting disembarkation conditions is completed, the control device 10 executes the process P9 for calculating the arrival confidence level.

[0068] In this process P9, the arrival prediction unit 18 of the control device 10 predicts the arrival of the approaching object O at the passenger disembarkation area A based, for example, on the disembarkation conditions predicted in the previous process P8 and the approaching object information input from the approaching object detection unit 13. Furthermore, the arrival prediction unit 18 calculates the confidence level of the approaching object O arriving at the predicted disembarkation area A at the predicted disembarkation time based on the disembarkation conditions and the approaching object information. For example, if the approaching object O passes through the predicted disembarkation area A before the predicted disembarkation time, or if the approaching object O is at a predetermined distance from the disembarkation area A at the predicted disembarkation time, the arrival confidence level calculated by the arrival prediction unit 18 decreases.

[0069] On the other hand, when it is predicted that the approaching object O will arrive at the predicted drop-off area A at the predicted drop-off time, or when it is predicted that the approaching object O will be closer to the drop-off area A than the specified distance at the predicted drop-off time, the arrival confidence calculated by the arrival prediction unit 18 increases. Furthermore, when the approaching object O is detected in a low-precision area, such as near the outer edge of the detection range of the external sensor 2, where the detection accuracy is lower than the specified accuracy, the arrival confidence calculated by the arrival prediction unit 18 decreases.

[0070] Furthermore, arrival confidence is an indicator of the probability that an object O will arrive at the predicted drop-off area A at the predicted drop-off time. A higher arrival confidence indicates a greater probability that object O will arrive at the predicted drop-off area A at the predicted drop-off time, while a lower arrival confidence indicates a lower probability. For example, when detecting object O repeatedly at a predetermined period, increasing the number of times object O is detected will improve the arrival confidence.

[0071] Furthermore, for example, when the detection of approaching object O is repeated at a predetermined period, the more times the state continues where the remaining time for the predicted arrival of approaching object O at the drop-off area A is less than a predetermined value, the higher the arrival confidence level can be. Additionally, the arrival confidence level can be improved when multiple sensors in external sensor 2 detect approaching object O, and decreased when only one sensor in external sensor 2 detects approaching object O.

[0072] Furthermore, the arrival prediction unit 18 can, for example, calculate an index of the probability that the occupants of vehicle 1 will disembark, namely the disembarkation confidence level, based on the disembarkation action input from the disembarkation action detection unit 14. For example, if the disembarkation action input to the arrival prediction unit 18 is an operation directly related to disembarkation, such as the occupant's operation of the door opening or closing mechanism or door handle, the disembarkation confidence level calculated by the arrival prediction unit 18 increases. On the other hand, if the disembarkation action input to the arrival prediction unit 18 is a preparatory disembarkation action that is not directly related to disembarkation, such as the occupant's eye movement, weight movement, or body movement, the disembarkation confidence level calculated by the arrival prediction unit 18 decreases.

[0073] Figure 3 After the processing P9 is completed, the control device 10 executes processing P10 to determine the attention level of the occupants of vehicle 1. This processing P10 is the same as the processing P6 described above, but in the processing P5 described above, the approaching object O was detected by the approaching object detection unit 13. Therefore, compared to processing P6 in the case where the approaching object O was not detected in the processing P5 described above, the occupants' attention level to the approaching object O is set to be low. The shorter the remaining time of arrival calculated by the approaching object detection unit 13, the lower the attention level inference unit 11 infers the occupants' attention level to the approaching object O.

[0074] Furthermore, in this process P10, similar to the process P6 described above, the attention inference unit 11 outputs the inferred occupant attention level to the work determination unit 19. If the occupant attention level input from the attention inference unit 11 is below a predetermined attention level or a predetermined attention threshold, the work determination unit 19 determines that the occupant's attention level is low (yes). In this case, the control device 10 executes the process P11 of lowering the threshold X for reaching the confidence level, and then executes the process P12 of determining whether the confidence level has been reached.

[0075] In process P11, the work judgment unit 19 reduces the confidence threshold X used in the confidence determination process P12 based on the occupant's attention level input from the attention inference unit 11. That is, the lower the occupant's attention level to the approaching object O, the lower the confidence threshold X becomes. Furthermore, in process P10 described above, similar to process P6 described above, for example, the more conditions for inferring low occupant attention level are met, the lower the inferred occupant's attention level to the approaching object O becomes.

[0076] On the other hand, in the aforementioned process P10, if the occupant's attention level input from the attention level inference unit 11 is higher than the prescribed attention level or the prescribed attention level threshold, the work judgment unit 19 determines that the occupant's attention level is not low (No). In this case, the control device 10 executes the confidence level determination process P12 without executing the process P11 of lowering the confidence level threshold X. Therefore, the confidence level threshold X will not decrease from its initial value.

[0077] In the confidence level determination process P12, the work determination unit 19 determines, for example, whether the confidence level calculated in the aforementioned process P9 is above the threshold X. When the work determination unit 19 determines in process P12 that the confidence level is below the threshold X (No), the aforementioned reminder process P7 is executed, and the process ends. Figure 3 The processing flow is shown. On the other hand, when the work determination unit 19 in process P12 determines that the confidence level has reached the threshold X or above (yes), the door opening restriction process P13, which serves as a disembarkation restriction, is executed. In addition, the threshold X that represents the confidence level may be different depending on whether the door opening restriction is executed or the reminder is executed.

[0078] In this door opening restriction process P13, the work determination unit 19 determines the content of the door opening restriction action as an exit restriction based on the level or value of the occupant's attention level input from the attention level inference unit 11. More specifically, the work determination unit 19 determines, for example, the door opening restriction action performed by the door opening and closing device 6. The work determination unit 19 determines the door opening restriction action, for example, based on the level of confidence in the arrival of the approaching object O to the exit area A and the remaining time of arrival.

[0079] More specifically, consider, for example, a situation where the confidence level is higher than a first threshold or the remaining time to reach the first threshold is shorter than a first threshold. In this case, the operation judgment unit 19, for example, determines a first door opening restriction action, which means that the door of vehicle 1 is kept closed by means of the door opening and closing device 6 regardless of the operation of the door opening and closing device or the door handle by the occupants of vehicle 1. The first door opening restriction action may include, for example, a reminder action performed by at least one of the voice output device 7 and the image display device 8.

[0080] Furthermore, for example, consider a situation where the confidence level is lower than the first threshold but higher than the second threshold, or the remaining time to reach the threshold is longer than the first threshold but shorter than the second threshold. In this case, the operation judgment unit 19, for example, determines a second door opening restriction action, which is to delay the opening of the vehicle door by the door opening / closing device 6 of the vehicle 1 compared to normal, or to stop the door opening action midway, after the occupant of the vehicle 1 operates the door switch or door handle. Here, the door opening delay time may vary, for example, depending on the confidence level, the remaining time to reach the threshold, or the occupant's attention level. In addition, the second door opening restriction action may also include a reminder action performed by at least one of the voice output device 7 and the image display device 8.

[0081] Furthermore, for example, consider a situation where the confidence level is lower than the second threshold or the remaining time to reach the second threshold is longer. In this case, the operation judgment unit 19, for example, decides to perform a third exit restriction action, prompting an alert from at least one of the voice output device 7 and the image display device 8. The alert from the voice output device 7 includes, for example, the output of a warning tone or voice urging attention to the approaching object O. Furthermore, the alert action from the image display device 8 includes the display of an image or text urging attention to the approaching object O.

[0082] The operation judgment unit 19 then outputs the determined door opening restriction action, which serves as an exit restriction, to the exit restriction unit 12. The exit restriction unit 12 outputs a control signal to implement the door opening restriction action input from the operation judgment unit 19, which serves as an exit restriction, to at least one of the door opening / closing device 6, the voice output device 7, and the image display device 8. Thus, at least one of the door opening / closing device 6, the voice output device 7, and the image display device 8 executes the door opening restriction action selected or determined by the operation judgment unit 19. Afterward, the control device 10 terminates. Figure 3 The processing flow shown is repeated at a specified cycle.

[0083] As described above, the control device 10 of this embodiment is mounted in the vehicle 1 and includes an attention inference unit 11 and an exit restriction unit 12. The attention inference unit 11 infers the occupant's attention level to an approaching object O approaching the vehicle 1 based on the detection result of at least one of the occupant sensor 3 that detects the occupant's movements or the vehicle sensor 4 that detects the state of the vehicle 1. If the occupant's attention level inferred by the attention inference unit 11 is lower than a predetermined threshold, the exit restriction unit 12 causes at least one of the door opening / closing device 6, the voice output device 7, and the image display device 8 mounted in the vehicle 1 to perform an exit restriction action.

[0084] With this configuration, the control device 10 of this embodiment can infer the level of attention of the occupant alighting from the vehicle 1 to the approaching object O using the attention inference inference unit 11. Therefore, even if the vehicle sensor 4 fails to detect the approaching object O due to factors such as heavy rain, dense fog, nighttime, or backlighting, at least one of the door opening / closing device 6, the voice output device 7, and the image display device 8 can perform an exit restriction action based on the decrease in the occupant's attention. This prevents the occupant of the vehicle 1 from alighting without preparation, thus preventing the occupant from contacting the approaching object O when exiting the vehicle 1. Furthermore, it also prevents the occupant of the vehicle 1 from opening the door without preparation, thus preventing the vehicle door from contacting the approaching object O. Therefore, the control device 10 of this embodiment improves the safety of the occupant of the vehicle 1 when alighting compared to conventional methods.

[0085] Furthermore, the control device 10 of this embodiment also includes a vehicle status detection unit 16 and an alighting action detection unit 14. The vehicle status detection unit 16 detects the parking of the vehicle 1 based on the detection results of the vehicle sensor 4, and the alighting action detection unit 14 detects the alighting action of the occupant based on the detection results of the occupant sensor 3 or the vehicle sensor 4. Moreover, the shorter the time from when the vehicle status detection unit 16 detects the parking of the vehicle 1 to when the alighting action detection unit 14 detects the alighting action, the lower the attention level inference unit 11 infers the occupant's attention level.

[0086] With this configuration, in scenarios where passengers rush to get off the vehicle after it stops, resulting in insufficient safety confirmation of the approaching object O near the exit area A, the attention inference unit 11 infers that the passengers' attention is low. Therefore, the attention level of the passengers inferred by the attention inference unit 11 is likely to be lower than the threshold used by the exit restriction unit 12 to determine the execution of the exit restriction action. As a result, in scenarios where the safety of passengers getting off the vehicle is likely to be reduced, exit restrictions performed by at least one of the door opening / closing device 6, the voice output device 7, and the image display device 8 installed in the vehicle 1 can be easily executed.

[0087] Furthermore, the control device 10 of this embodiment also includes an exit environment detection unit 17 and a vehicle status detection unit 16. The exit environment detection unit 17 identifies the display of traffic lights based on the detection results of the external sensor 2 that detects objects around the vehicle 1, and the vehicle status detection unit 16 detects the gear position of the vehicle 1's transmission based on the detection results of the vehicle sensor 4. Moreover, the attention inference unit 11 infers the occupant's attention level based on the traffic light display identification result of the exit environment detection unit 17 and the gear position detection result of the vehicle status detection unit 16.

[0088] With this configuration, in scenarios where passengers in the vehicle 1 are stopped while waiting for a traffic light and are rushing to get off, resulting in insufficient safety confirmation of the approaching object O near the exit area A, the attention inference unit 11 can infer that the passengers' attention is low. Therefore, the attention level of the passengers inferred by the attention inference unit 11 is likely to be lower than the threshold used by the exit restriction unit 12 to determine the execution of the exit restriction action. As a result, in scenarios where the safety of passengers getting off the vehicle 1 is likely to be reduced, exit restrictions performed by at least one of the door opening / closing device 6, the voice output device 7, and the image display device 8 installed in the vehicle 1 can be easily executed.

[0089] Furthermore, the control device 10 of this embodiment also includes a vehicle status detection unit 16, which detects abnormalities in the vehicle 1 based on the detection results of the vehicle sensor 4. Moreover, when the vehicle status detection unit 16 detects an abnormality in the vehicle 1, the attention inference unit 11 infers that the occupant's attention level is low, compared to when the vehicle status detection unit 16 does not detect an abnormality in the vehicle 1.

[0090] With this configuration, in scenarios where an occupant rushes to exit vehicle 1 to confirm an anomaly, resulting in insufficient safety assessment of the approaching object O near the exit area A, the attention inference unit 11 can infer that the occupant's attention level is low. Consequently, the occupant's attention level inferred by the attention inference unit 11 is likely to be lower than the threshold used by the exit restriction unit 12 to determine the execution of the exit restriction action. As a result, in scenarios where the safety of occupants exiting vehicle 1 is likely to be reduced, exit restrictions implemented by at least one of the door opening / closing device 6, voice output device 7, and image display device 8 installed in vehicle 1 can be easily executed.

[0091] Furthermore, the control device 10 of this embodiment also includes a vehicle state detection unit 16, which detects the sudden deceleration of the vehicle 1 based on the detection results of the vehicle sensor 4. Moreover, when the vehicle state detection unit 16 detects the sudden deceleration of the vehicle 1, the attention inference unit 11 infers that the occupant's attention is low compared to when the vehicle state detection unit 16 does not detect the sudden deceleration of the vehicle 1.

[0092] With this configuration, in scenarios where an occupant, in order to confirm the cause of the sudden deceleration of vehicle 1, rushes to exit the vehicle and thus fails to adequately assess the safety of the approaching object O near the exit area A, the attention inference unit 11 can infer that the occupant's attention level is low. Therefore, the occupant's attention level inferred by the attention inference unit 11 is likely to be lower than the threshold used by the exit restriction unit 12 to determine the execution of the exit restriction action. As a result, in scenarios where the safety of occupants exiting vehicle 1 is likely to be reduced, exit restrictions performed by at least one of the door opening / closing device 6, the voice output device 7, and the image display device 8 installed in vehicle 1 can be easily executed.

[0093] Furthermore, the control device 10 of this embodiment also includes a proximity detection unit 13, which detects proximity objects O approaching the vehicle 1 based on the detection results of the external sensor 2 that detects objects around the vehicle 1. Moreover, when proximity object O is detected by proximity detection unit 13, the attention inference unit 11 sets the occupant's attention level to be lower than when proximity object O is not detected.

[0094] With this configuration, in scenarios where the safety of passengers disembarking from vehicle 1 to disembarkation area A is potentially reduced due to an approaching object O near the disembarkation area A of vehicle 1, the attention inference unit 11 can infer that the passenger's attention level is low. Therefore, the passenger's attention level inferred by the attention inference unit 11 is likely to be lower than the threshold used by the disembarkation restriction unit 12 to determine the execution of the disembarkation restriction action. As a result, in scenarios where the safety of passengers disembarking from vehicle 1 is potentially reduced, disembarkation restrictions performed by at least one of the door opening / closing device 6, voice output device 7, and image display device 8 installed in vehicle 1 can be easily executed.

[0095] Furthermore, the control device 10 of this embodiment also includes an exit environment detection unit 17, which detects the illuminance around the vehicle 1 based on the detection results of the external sensor 2 that detects objects around the vehicle 1. Moreover, the lower the illuminance detected by the exit environment detection unit 17, the lower the attention inference inference unit 11 infers the occupant's attention level.

[0096] With this configuration, in scenarios where the illumination around the vehicle 1 is reduced, such as at night, in a tunnel, in a shaded area, or on a cloudy day, leading to decreased detection accuracy of the external sensor 2 for the approaching object O, or where it becomes difficult for the occupant to visually perceive the approaching object O, the attention inference unit 11 can infer that the occupant's attention level is low. Therefore, the occupant's attention level inferred by the attention inference unit 11 is likely to be lower than the threshold used by the exit restriction unit 12 to determine the execution of the exit restriction action. As a result, in scenarios where the safety of the occupant exiting the vehicle 1 is likely to be reduced, exit restrictions performed by at least one of the door opening / closing device 6, the voice output device 7, and the image display device 8 installed in the vehicle 1 can be easily executed.

[0097] Furthermore, the control device 10 of this embodiment also includes an off-vehicle environment detection unit 17, which infers the visibility distance of the approaching object O based on the detection results of the external sensor 2 that detects objects around the vehicle 1 or meteorological information received by a receiver mounted in the vehicle 1. The shorter the visibility distance inferred by the off-vehicle environment detection unit 17, the lower the attention inference inference unit 11 infers the attention level.

[0098] With this configuration, in scenarios where visibility of the approaching object O is reduced due to rain, snow, or fog, the detection accuracy of the external sensor 2 for the approaching object O is reduced, or the occupant has difficulty visually observing the approaching object O, the attention inference unit 11 can infer that the occupant's attention level is low. Therefore, the occupant's attention level inferred by the attention inference unit 11 is likely to be lower than the threshold used by the exit restriction unit 12 to determine the execution of the exit restriction action. As a result, in scenarios where the safety of occupants exiting the vehicle 1 is likely to be reduced, exit restrictions performed by at least one of the door opening / closing device 6, the voice output device 7, and the image display device 8 installed in the vehicle 1 can be easily executed.

[0099] Furthermore, the control device 10 of this embodiment also includes an exit environment detection unit 17, which detects the parking position of the vehicle 1 based on the output of the car navigation system (CNS5) installed in the vehicle 1, and determines the difficulty of exiting the vehicle based on the parking position. Moreover, the higher the difficulty of exiting the vehicle determined by the exit environment detection unit 17, the lower the attention inference unit 11 infers the occupant's attention level.

[0100] With this configuration, in scenarios where getting off the vehicle is difficult, such as on highways or roads, and where there is a risk of reduced safety for passengers disembarking at drop-off area A, the attention inference unit 11 can infer that the passenger's attention level is low. Therefore, the passenger's attention level inferred by the attention inference unit 11 is likely to be lower than the threshold used by the disembarkation restriction unit 12 to determine the execution of the disembarkation restriction action. As a result, in scenarios like the one described above where there is a risk of reduced safety for passengers disembarking from vehicle 1, the disembarkation restriction can be easily executed by at least one of the door opening / closing device 6, the voice output device 7, and the image display device 8 installed in vehicle 1.

[0101] Furthermore, the control device 10 of this embodiment also includes an occupant behavior detection unit 15, which detects at least one of the age of the occupant of the vehicle 1 or the inattentive behavior of the occupant of the vehicle 1 when their attention is reduced, based on the detection results of the occupant sensor 3. Moreover, the attention inference unit 11 infers the attention level of the occupant of the vehicle 1 based on the detection results of the occupant behavior detection unit 15 regarding the age or inattentive behavior of the occupant of the vehicle 1.

[0102] With this configuration, for example, the attention inference unit 11 can infer that the attention level of an infant, child, or occupant who is distracted by events other than the approaching object O and neglects safety checks is low. Therefore, the attention level of the occupant inferred by the attention inference unit 11 is likely to be lower than the threshold used by the disembarkation restriction unit 12 to determine the execution of the disembarkation restriction action. As a result, when such an occupant with low attention to the approaching object O disembarks from the vehicle 1, the disembarkation restriction performed by at least one of the door opening / closing device 6, the voice output device 7, and the image display device 8 installed in the vehicle 1 can be easily executed.

[0103] Furthermore, in the control device 10 of this embodiment, the proximity detection unit 13 calculates the remaining time for the proximity object O to reach the drop-off area A of the vehicle 1. In addition, the shorter the remaining time calculated by the proximity detection unit 13, the lower the attention inference unit 11 infers the occupant's attention level.

[0104] With this configuration, for example, in scenarios where the safety of passengers disembarking from vehicle 1 is compromised due to the proximity of object O to the disembarkation area, the attention inference unit 11 can infer that the passenger's attention level is low. Therefore, the passenger's attention level inferred by the attention inference unit 11 is likely to be lower than the threshold used by the disembarkation restriction unit 12 to determine the execution of the disembarkation restriction action. As a result, in scenarios like the one described above where the safety of passengers disembarking from vehicle 1 is compromised, disembarkation restrictions performed by at least one of the door opening / closing device 6, voice output device 7, and image display device 8 installed in vehicle 1 can be easily executed.

[0105] As explained above, according to this embodiment, a control device 10 can be provided that causes at least one of the door opening / closing device 6, voice output device 7, and image display device 8 to perform an exit restriction action based on the decrease in the attention of the occupants of the vehicle 1, thereby improving the safety of occupants when exiting the vehicle compared to the past.

[0106] The embodiments of the control device disclosed herein have been described in detail above with the aid of the accompanying drawings. However, the specific configuration is not limited to this embodiment. Even if there are design changes that do not depart from the spirit of this disclosure, they are also included in this disclosure. Symbol Explanation

[0107] 1…vehicles 2…External sensors 3… Occupant Sensors 4…Vehicle sensors 5…CNS (Car Navigation System) 6… Door opening and closing device 7… Voice output device 8…Image display device 10…Control device 11…Attention Inference Department 12…Disembarkation Restriction Section 13… Proximity Detection Department 14…Disembarkation Action Detection Department 15…Occupant Behavior Detection Department 16…Vehicle Condition Inspection Department 17…Disembarkation Environmental Inspection Department A…Disembarkation area O…approaching object.

Claims

1. A control device mounted in a vehicle, characterized in that, have: The attention inference unit infers the attention level of the occupant to an approaching object approaching the vehicle based on the detection result of at least one of an occupant sensor that detects the occupant's actions or a vehicle sensor that detects the state of the vehicle. When the attention level inferred by the attention level inference unit is lower than a predetermined threshold, the vehicle exit restriction unit causes at least one of the door opening and closing device, voice output device, and image display device installed in the vehicle to perform an exit restriction action. as well as The system includes a vehicle status detection unit and an exit action detection unit. The vehicle status detection unit detects when the vehicle is parked based on the detection results of the vehicle sensors, and the exit action detection unit detects when an occupant exits the vehicle based on the detection results of the occupant sensors or the vehicle sensors. The shorter the time from when the vehicle status detection unit detects the vehicle stopping to when the disembarkation action detection unit detects the disembarkation action, the lower the attention inference unit infers the attention level.

2. A control device mounted in a vehicle, characterized in that, have: The attention inference unit infers the attention level of the occupant to an approaching object approaching the vehicle based on the detection result of at least one of an occupant sensor that detects the occupant's actions or a vehicle sensor that detects the state of the vehicle. When the attention level inferred by the attention level inference unit is lower than a predetermined threshold, the vehicle exit restriction unit causes at least one of the door opening and closing device, voice output device, and image display device installed in the vehicle to perform an exit restriction action. as well as The system includes an exit environment detection unit and a vehicle status detection unit. The exit environment detection unit identifies traffic light displays based on the detection results of external sensors that detect objects around the vehicle. The vehicle status detection unit detects the gear position of the vehicle's transmission based on the detection results of vehicle sensors. The attention inference unit infers the attention level based on the recognition results of the traffic light display by the exit environment detection unit and the detection results of the gear position by the vehicle status detection unit.

Images