Notification device

Abstract

To provide a notification device capable of suppressing troublesome feeling and anxiety given to an occupant due to a temporary malfunction of an external sensor.SOLUTION: A notification device 1 in a vehicle 2 capable of executing drive support control or automatic drive control on an object road, comprises: a malfunction recognition part 13 for recognizing a malfunction of an external sensor 4 used for the drive support control or the automatic drive control; and a notification control part 14 for notifying an occupant of the vehicle 2 of the malfunction of the external sensor 4 when the malfunction of the external sensor 4 is recognized. The notification control part 14 evaluates whether or not the vehicle 2 is expected to travel on the object road based on a vehicle position, a target route or a travel history of the vehicle 2, notifies the occupant of the vehicle 2 of the malfunction of the external sensor 4 in a suppression mode in comparison with a case where the vehicle 2 is expected to travel on the object road when the vehicle 2 is not expected to travel on the object road, or does not notify the occupant of the vehicle 2 of the malfunction of the external sensor 4.SELECTED DRAWING: Figure 1

Description

[Technical Field]

[0001] The present disclosure relates to an alarm device. [Background technology]

[0002] A vehicle control system has been disclosed that includes a definition module that defines an operational design domain (ODD) of a vehicle, and a control module that controls the operation of the vehicle based on the ODD (for example, Patent Document 1). [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Japanese Patent Publication No. 2021-043896 Summary of the Invention [Problem to be solved by the invention]

[0004] In the past, in a vehicle capable of executing driving assistance control or autonomous driving control on a target road, a notification regarding a malfunction of an external sensor may be issued. The malfunction of the external sensor may include, for example, a temporary malfunction such as adhesion of water droplets to the external sensor. If the malfunction of the external sensor is notified due to such a temporary malfunction of the external sensor, for example, when the vehicle is not located on the target road, the notification may cause annoyance and anxiety to the vehicle occupants. [Means for solving the problem]

[0005] One aspect of the present disclosure is an alarm device for a vehicle capable of performing driving assistance control or automatic driving control on a target road, comprising: a malfunction recognition unit that recognizes a malfunction of an external sensor used for driving assistance control or automatic driving control; and an alarm control unit that notifies an occupant of the vehicle of the malfunction of the external sensor when a malfunction of the external sensor is recognized, wherein the alarm control unit evaluates whether or not the vehicle is likely to travel on the target road based on the vehicle's position, target route, or driving history, and when the vehicle is not likely to travel on the target road, alerts the occupant of the vehicle of the malfunction of the external sensor in a more restrained manner than when the vehicle is likely to travel on the target road, or does not alert the occupant of the vehicle of the malfunction of the external sensor.

[0006] In a notification device according to an aspect of the present disclosure, when the vehicle is not expected to travel on a target road, the malfunction of the external sensor is suppressed or not notified. This prevents the malfunction of the external sensor from being notified even when the vehicle is not expected to travel on the target road. As a result, it is possible to prevent the inconvenience and anxiety caused to the occupant due to a temporary malfunction of the external sensor.

[0007] In one embodiment, the notification control unit may evaluate that the vehicle is unlikely to travel on the target road if the target route does not include the target road or if the vehicle's location is away from the target road by a predetermined distance threshold or more. In this case, the notification control unit can evaluate the likelihood that the vehicle will travel on the target road depending on whether the target route includes the target road or whether the vehicle's location is away from the target road by a predetermined distance threshold or more.

[0008] In one embodiment, the notification control unit may estimate the probability that the vehicle will travel on the target road at a timing corresponding to the same day of the week and time period based on the past driving history, and may evaluate that the vehicle is unlikely to travel on the target road if the estimated probability is less than a predetermined probability threshold. In this case, the notification control unit can evaluate the likelihood that the vehicle will travel on the target road according to the probability that the vehicle will travel on the target road at a timing corresponding to the same day of the week and time period.

[0009] In one embodiment, the notification control unit may estimate the probability that the vehicle will travel on the target road at a corresponding timing during the holiday period based on the past driving history, and may evaluate that the vehicle is unlikely to travel on the target road if the estimated probability is less than a predetermined probability threshold. In this case, the notification control unit can evaluate the likelihood that the vehicle will travel on the target road according to the probability that the vehicle will travel on the target road at a corresponding timing during the holiday period.

[0010] In one embodiment, the notification control unit may estimate a probability that the vehicle will travel on a target road along a target route to the destination based on schedule information including the occupant's destination that can be acquired on an information terminal carried by the occupant, and may evaluate that the vehicle is unlikely to travel on the target road if the estimated probability is less than a predetermined probability threshold. In this case, the schedule information including the destination can be used to evaluate the likelihood that the vehicle will travel on the target road. [Effects of the Invention]

[0011] According to various aspects of the present disclosure, it is possible to prevent the inconvenience and anxiety that a passenger may experience due to a temporary malfunction of an external sensor. [Brief explanation of the drawings]

[0012] [Figure 1] 1 is a functional block diagram of an example of a vehicle including a notification device according to an embodiment; [Figure 2] FIG. 10 is a diagram for explaining learning of the probability that a vehicle will travel on a target road at a timing corresponding to the same day of the week and time period. [Figure 3] 10 is a diagram for explaining learning of the probability that a vehicle will travel on a target road at a corresponding timing during a holiday period. FIG. [Figure 4] This is a diagram for explaining learning of the probability that a vehicle will travel on a target road along a target route to a destination based on schedule information including the occupant's destination that can be obtained on an information terminal carried by the occupant. [Figure 5] 10 is a flowchart illustrating an example of processing by the notification device. [Figure 6]6 is a flowchart illustrating an example of the likelihood evaluation process of FIG. 5. DETAILED DESCRIPTION OF THE INVENTION

[0013] Hereinafter, exemplary embodiments will be described with reference to the drawings. In the following description, the same or equivalent elements will be denoted by the same reference numerals, and redundant description may be omitted.

[0014] [Configuration of vehicle and alarm device] FIG. 1 is a functional block diagram of an example of a vehicle including a notification device according to an embodiment. As shown in FIG. 1, the notification device 1 is mounted on a vehicle 2, such as a passenger car, and notifies information to vehicle occupants. The vehicle 2 is a vehicle equipped with a vehicle control system capable of executing driving assistance control or automatic driving control on a target road. The target road is a road included in the operation design domain (ODD) of the vehicle control system capable of executing driving assistance control or automatic driving control. The ODD is the range in which the vehicle control system operates as designed. As an example, the ODD can be an expressway (national expressway) or a motorway (national highway) for exclusive use by automobiles.

[0015] As an example, the vehicle 2 is equipped with an automated driving system. The automated driving system drives the vehicle 2 autonomously on roads included in the ODD. Autonomous driving is a driving state in which the vehicle 2 drives automatically along the road on which the vehicle 2 is traveling. Autonomous driving includes, for example, a driving state in which the vehicle 2 drives automatically toward a predetermined destination without the driver performing any driving operation. Autonomous driving includes, for example, automated driving levels 2 to 4 in SAE [Society of Automotive Engineers] J3016. The destination may be set by a passenger such as the driver, or may be set automatically by the vehicle 2. In automated driving, the vehicle 2 drives automatically without the driver having to perform any driving operation.

[0016] The vehicle 2 includes an internal sensor 3, an external sensor 4, a GNSS receiver 5, a map database 6, a driving history database 7, an HMI (Human Machine Interface) 8, an actuator 9, and an autonomous driving ECU (Electronic Control Unit) 10.

[0017] The internal sensor 3 is a detection device that detects the driving state of the vehicle 2. The internal sensor 3 includes a vehicle speed sensor. The vehicle speed sensor is a detector that detects the speed of the vehicle 2. As the vehicle speed sensor, for example, a wheel speed sensor that detects the rotational speed of the wheels of the vehicle 2 or a drive shaft that rotates integrally with the wheels is used. The internal sensor 3 may also include an acceleration sensor and a yaw rate sensor. The internal sensor 3 transmits detection information related to the driving state of the vehicle 2 to the autonomous driving ECU 10.

[0018] The external sensor 4 includes at least either a camera or a radar sensor. The camera is an imaging device that captures images of the environment around the vehicle 2. The camera is provided, for example, behind the windshield of the vehicle 2, and captures images in front of the vehicle. The radar sensor is a detection device that detects objects around the vehicle 2 using radio waves (for example, millimeter waves) or light. Radar sensors include, for example, radar (millimeter wave radar) or LiDAR (Light Detection And Ranging). The external sensor 4 transmits detection information about objects around the vehicle 2 to the autonomous driving ECU 10.

[0019] The GNSS receiver 5 receives signals from positioning satellites to measure the position of the vehicle 2 (for example, the latitude and longitude of the vehicle 2). The GNSS receiver 5 transmits the measured position information of the vehicle 2 to the autonomous driving ECU 10.

[0020] The map database 6 is a storage device that stores map information. The map database 6 is formed, for example, in a storage medium such as an HDD (Hard Disk Drive) mounted on the vehicle 2. The map information includes road position information, road shape information (for example, type of curve, straight section, etc., radius of curvature of curve, shape of intersection, width of lane, condition of shoulder outside the roadway, emergency parking area, etc.), position information of intersections and branch points, position information of structures, etc. The map database 6 may be formed in a server that can communicate with the vehicle 2.

[0021] The driving history database 7 is a database that stores the driving history of the vehicle 2. The driving history is a history of positions on a map that the vehicle 2 has driven to in the past. The driving history database 7 may be stored in a server that can communicate with the vehicle.

[0022] The HMI 8 is an interface for inputting and outputting information between the autonomous driving ECU 10 and the occupants. The HMI 8 includes, for example, a display, a speaker, a microphone, and the like provided in the vehicle cabin. The HMI 8 outputs images from the display and audio from the speaker in response to control signals from the autonomous driving ECU 10. The display may function as a touch panel. The display may be a center display, a navigation display, or a HUD [Head Up Display]. The HUD presents information to the occupants by projecting images onto the windshield of the vehicle 2.

[0023] The HMI 8 presents information about the malfunction of the external sensor 4 to the occupant. The information about the malfunction of the external sensor 4 may be presented to the occupant by image output or by audio output. The image output may be, for example, a pop-up display on the speedometer screen containing text information such as "Automated driving cannot be used. System malfunction." The image output may also be an indicator display using a predetermined icon indicating the malfunction of the external sensor 4.

[0024] The actuators 9 are devices used to control the driving of the vehicle 2, and operate in response to control signals from the autonomous driving ECU 10. The actuators 9 include at least a drive actuator, a brake actuator, and a steering actuator. The drive actuator is provided, for example, in an engine or motor serving as a power source, and controls the driving force of the vehicle 2. The brake actuator is provided, for example, in a hydraulic brake system, and controls the braking force applied to the wheels of the vehicle 2. The steering actuator is, for example, an assist motor in an electric power steering system, and controls the steering torque of the vehicle 2.

[0025] The autonomous driving ECU 10 controls the autonomous driving system. The autonomous driving ECU 10 is an electronic control unit having a central processing unit (CPU) and a storage unit. The storage unit is composed of, for example, read-only memory (ROM), random access memory (RAM), and electrically erasable programmable read-only memory (EEPROM). The autonomous driving ECU 10 realizes various functions by, for example, executing programs stored in the storage unit with the CPU. The autonomous driving ECU 10 may be composed of multiple electronic units.

[0026] The functions of the autonomous driving ECU 10 will be described below. As shown in Fig. 1, the autonomous driving ECU 10 has, as its functional configuration, a target route setting unit 11, an autonomous driving control unit 12, a malfunction recognition unit 13, and a notification control unit 14. Note that the functions of the autonomous driving ECU 10 may be realized using a server with which the vehicle 2 can communicate. Of these functional configurations, at least the malfunction recognition unit 13 and the notification control unit 14 constitute the notification device 1.

[0027] The target route setting unit 11 sets a target route for guiding the vehicle 2 to a preset destination. The target route is a route on a map from the vehicle position measured by the GNSS receiving unit 5 to the destination. The target route setting unit 11 recognizes the roads and driving lanes on which the vehicle 2 is traveling, based on the vehicle position measured by the GNSS receiving unit 5 and the map information in the map database 6. The target route setting unit 11 may use the functions of a navigation system of the vehicle 2.

[0028] The target route may be a road included in the ODD, or may be a road not included in the ODD. If the target route is a road included in the ODD, the portion of the target route included in the ODD can be used to generate a path for the vehicle 2 to perform automated driving. If the target route is a road not included in the ODD, automated driving is not performed, but the target route may be displayed on the display of the HMI 8 to guide the driver.

[0029] The target route setting unit 11 may set a target route using a destination input by the occupant via the HMI 8. The target route setting unit 11 may acquire the occupant's destination using an information terminal carried by the occupant, with the occupant's permission. The target route setting unit 11 may acquire a destination associated with the smartphone user's schedule information, for example, using a communication unit that communicates with the smartphone carried by the occupant directly or via a communication network. The user's schedule information may be recorded on the user's smartphone or on a cloud service accessible from the user's smartphone.

[0030] The target route setting unit 11 stores routes that the vehicle 2 has actually traveled in the past as a travel history in the travel history database 7 according to past vehicle positions. For example, based on past vehicle positions, the target route setting unit 11 stores whether the vehicle 2 has traveled on a road included in the ODD in the past as a travel history in the travel history database 7 in association with a date and time. Instead of based on past vehicle positions, the target route setting unit 11 may store whether a target route used in the past was on a road included in the ODD as a travel history in the travel history database 7.

[0031] For example, the autonomous driving control unit 12 recognizes objects (including the positions of the objects) around the vehicle 2 based on at least one of the detection results of the external sensor 4 and the map database 6. The objects include stationary objects that do not move, such as utility poles, guardrails, trees, and buildings, as well as dynamic objects, such as pedestrians, bicycles, and other vehicles. The autonomous driving control unit 12 recognizes objects, for example, every time it acquires a detection result from the external sensor 4. The autonomous driving control unit 12 recognizes objects around the vehicle 2 based on the detection results of the external sensor 4 (image capture information from a camera, object detection results from a radar sensor), for example, using pattern matching or a machine learning model. The autonomous driving control unit 12 may also recognize objects around the vehicle 2 using other well-known methods.

[0032] The automatic driving control unit 12 recognizes the running state of the vehicle 2 based on the detection results of the internal sensors 3 (for example, vehicle speed information from a vehicle speed sensor, acceleration information from an acceleration sensor, yaw rate information from a yaw rate sensor, etc.). The running state of the vehicle 2 includes, for example, the vehicle speed, acceleration, and yaw rate.

[0033] The autonomous driving control unit 12 recognizes the position of the vehicle 2 on a map (vehicle position) based on the detection results of the external sensor 4, position information from the GNSS receiving unit 5, and map information in the map database 6. The autonomous driving control unit 12 may recognize the position of the vehicle 2 using SLAM (Simultaneous Localization And Mapping) technology, using position information of stationary objects such as utility poles included in the map information in the map database 6 and the detection results of the external sensor 4. The autonomous driving control unit 12 may also recognize the vehicle position using other well-known methods.

[0034] The autonomous driving control unit 12 generates a path for the vehicle 2 so that the vehicle 2 travels automatically along the target route based on, for example, the target route, the detection results of the external sensor 4, map information in the map database 6, the recognized vehicle position, information on recognized objects, and the recognized driving state of the vehicle 2. The autonomous driving control unit 12 generates a driving plan according to the path of the vehicle 2 based on, for example, the detection results of the external sensor 4 and the map database 6. The driving plan is not particularly limited as long as it describes the behavior of the vehicle 2. As part of the driving plan for the vehicle 2, the autonomous driving control unit 12 may use the speed limit stored in the map database 6 to generate a speed plan within a range that does not exceed the speed limit of the driving lane.

[0035] When the vehicle position is located on a road included in the ODD, the automatic driving control unit 12 automatically controls the driving of the vehicle 2 based on the generated driving plan. The automatic driving control unit 12 outputs a control signal according to the driving plan to the actuator 9. As a result, the automatic driving control unit 12 controls the driving of the vehicle 2 so that the vehicle 2 automatically drives along the route. On the other hand, when the vehicle position is not located on a road included in the ODD, the automatic driving control unit 12 does not perform automatic driving.

[0036] The malfunction recognition unit 13 recognizes a malfunction of the external sensor 4 used for driving assistance control or autonomous driving control. A malfunction of the external sensor 4 means that a malfunction has occurred in the function of the external sensor 4. An example of a malfunction of the external sensor 4 is a malfunction of the function of the external sensor 4 that makes it impossible to execute autonomous driving, or a malfunction of the function of the external sensor 4 that makes it impossible to continue autonomous driving without a degenerate function using an alternative means. Such malfunctions include, for example, an actual failure of the external sensor 4 itself and a degradation of function due to a foreign object attached to the external sensor 4.

[0037] Actual failures of the external sensor 4 itself include physical failures of the external sensor 4 itself and failures in the internal processing of the external sensor 4 itself. Foreign matter adhering to the external sensor 4 may be objects such as water droplets, water stains, or mud adhering to the window portion of the external sensor 4 that faces the outside world. For example, water droplets may adhere to the window portion of the external sensor 4 that faces the outside world during heavy rainy weather or after washing the car in a car wash. A decrease in function due to foreign matter adhering to the external sensor 4 can be considered a temporary malfunction of the external sensor 4.

[0038] The malfunction recognition unit 13 can use a known method to recognize whether or not these external sensors 4 are malfunctioning. However, the malfunction recognition unit 13 does not distinguish a decrease in function due to a foreign object attached to the external sensor 4 from an actual malfunction of other external sensors 4, or mistakenly recognizes it as a malfunction of the external sensor 4 that is the same as an actual malfunction.

[0039] When a malfunction of the external sensor 4 is recognized, the notification control unit 14 notifies the vehicle occupants of the malfunction of the external sensor 4. For example, when a malfunction of the external sensor 4 is recognized, the notification control unit 14 may display a pop-up message including text information such as "Autonomous driving cannot be used. System malfunction" on the speedometer screen of the HMI 8. For example, when a malfunction of the external sensor 4 is recognized, the notification control unit 14 may display an indicator using a predetermined icon indicating the malfunction of the external sensor 4 on the display of the HMI 8.

[0040] The notification control unit 14 evaluates whether or not there is a possibility that the vehicle 2 will travel on the target road (ODD) based on the vehicle position, the target route, or the travel history. The evaluation of whether or not there is a possibility will be described later.

[0041] When the vehicle 2 is not expected to travel on the target road, the notification control unit 14 notifies the occupants of the vehicle 2 of a malfunction of the external sensor 4 in a more suppressed manner than when the vehicle 2 is expected to travel on the target road. The "suppressed manner" refers to a manner in which the level of urgency felt by the occupants of the vehicle 2 is reduced. The "suppressed manner" may, for example, use text information such as "Use of autonomous driving is temporarily restricted" or "Please check the external sensor" instead of text information such as "Automated driving cannot be used. System malfunction." The "suppressed manner" may, for example, display only an indicator using an icon without displaying a pop-up containing text information on the speedometer screen of the HMI 8. Alternatively, the notification control unit 14 may not notify the occupants of the vehicle 2 of a malfunction of the external sensor 4 when the vehicle 2 is not expected to travel on the target road.

[0042] As an example of the evaluation of the possibility, when the target route does not include an ODD, the notification control unit 14 evaluates that there is no possibility that the vehicle 2 will travel on the target road. When the target route does not include an ODD, for example, the navigation setting (setting of a destination, setting of a passing point, etc.) is such that the vehicle 2 will not travel on the target road.

[0043] The notification control unit 14 may evaluate that the vehicle 2 is unlikely to travel on the target road when the vehicle position is away from the ODD by a predetermined distance threshold or more. The distance threshold is a predetermined distance threshold for evaluating whether the vehicle 2 is likely to travel on the target road. The notification control unit 14 may evaluate that the vehicle 2 is unlikely to travel on the target road when the vehicle position is away from the nearest interchange on the expressway by a predetermined distance threshold or more (for example, about several kilometers).

[0044] The notification control unit 14 may estimate the probability that the vehicle will travel on the target road from a predetermined perspective, and may evaluate that there is no likelihood that the vehicle will travel on the target road if the estimated probability is less than a predetermined probability threshold. The probability threshold is a predetermined probability threshold for evaluating whether there is a likelihood that the vehicle 2 will travel on the target road. The notification control unit 14 may evaluate that there is no likelihood that the vehicle 2 will travel on the target road if the estimated probability is less than the probability threshold.

[0045] The notification control unit 14 estimates, for example, a probability P1 that the vehicle will travel on the target road at a timing corresponding to the same day of the week and time period based on past driving history. The notification control unit 14 estimates a probability P2 that the vehicle will travel on the target road at a corresponding timing during a holiday period based on past driving history. The notification control unit 14 estimates a probability P3 that the vehicle will travel on the target road along a target route to the destination based on schedule information including the occupant's destination, which is available on an information terminal carried by the occupant. The probability P, which corresponds to the likelihood that the vehicle 2 will travel on the target road, estimated from the above information may be calculated using, for example, the following formula (1). The probabilities P1, P2, and P3 are estimated based on the learning results shown in FIGS. 2(a) and 2(b), 3(a) and 3(b), and 4, respectively. α, β, and γ are weighting coefficients for weighting the probabilities P1, P2, and P3, and the relationship α>β>γ may be satisfied. P = αP1 + βP2 + γP3 (1)

[0046] 2(a) and (b) are diagrams for explaining learning of the probability that a vehicle will travel on a target road at a timing corresponding to the same day of the week and time period. FIG. 2(a) shows an example of the probability P1 before learning. FIG. 2(b) shows an example of the probability P1 after learning. FIGS. 2(a) and (b) show an example of learning the probability that a vehicle 2 will travel on a target road (e.g., a highway) at each time period on each day of the week. Such learning may be performed for each vehicle 2. The notification control unit 14 calculates the probability P1 of the above formula (1) using the learning results.

[0047] As shown in the tables of Figures 2(a) and (b), the probability P1 that vehicle 2 will be traveling on the expressway on the day being estimated is stored individually in each box for each day of the week and time period based on the vehicle position, map information, and past driving history including date and time. The initial value of the probability P1 may be zero, as shown in Figure 2(a).

[0048] The probability P1 within each frame may increase by Δp1 (e.g., 0.1) each time the vehicle 2 travels on the expressway on the corresponding day of the week and time period. The probability P1 within each frame may decrease by Δpd1 (e.g., 0.01) if the vehicle 2 does not travel on the expressway for a certain period of time.

[0049] The training examples in Figures 2(a) and (b) may reflect the following situations: The driver of vehicle 2 regularly commuted to work using the expressway from morning to evening on Mondays, Tuesdays, and Fridays. The driver of vehicle 2 commuted to work less frequently on Fridays than on Mondays and Tuesdays, for example, due to vacation or teleworking. The driver of vehicle 2 rarely used the expressway on Wednesdays and Thursdays, for example, due to a business trip or teleworking. The driver of vehicle 2 sometimes took long trips on the expressway on Saturdays during the weekend.

[0050] In this way, the results of daily driving history are accumulated as probability P1 within each frame and learning proceeds. Of the probability P1 within each frame, the value within the frame for the day of the week and time period corresponding to the current day to be estimated is read out, multiplied by the weighting coefficient α, and used to calculate the probability P.

[0051] 3(a) and (b) are diagrams for explaining learning of the probability that a vehicle will travel on a target road at a corresponding timing during a holiday period. FIG. 3(a) shows an example of the probability P2 before learning. FIG. 3(b) shows an example of the probability P2 after learning. FIGS. 3(a) and (b) show an example of learning the probability that a vehicle 2 will travel on a target road (e.g., an expressway) on which day during each holiday period for which the time and number of days are set in advance. Such learning may be performed for each vehicle 2. The notification control unit 14 uses the learning results to calculate the probability P2 in the above formula (1).

[0052] As shown in the tables of Figures 3(a) and (b), the probability P2 that vehicle 2 will be traveling on the expressway on the day being estimated is stored individually in each box corresponding to the day of each holiday period, based on the vehicle position, map information, and past driving history including date and time. The initial value of probability P2 may be zero, as shown in Figure 3(a).

[0053] The probability P2 within each frame may increase by Δp2 (e.g., 0.1) each time the vehicle 2 travels on the expressway for the holiday period and the frame of days corresponding to which day of each holiday period it is. The probability P2 within each frame may decrease by Δpd2 (e.g., 0.01) if the vehicle 2 does not travel on the expressway for a certain period of time.

[0054] The learning examples in Figures 3(a) and (b) may reflect the following situation when taking Japanese holiday periods as an example. The driver of vehicle 2 regularly traveled long distances using the expressway on the first and fifth days of the winter holiday for the New Year's holiday to return home and make a U-turn. The driver of vehicle 2 rarely uses the expressway during spring and summer holidays for children or students, for example, because work is still a normal working day. Another example of a holiday period in Japan is the Golden Week holiday in May. In this case, the driver of vehicle 2 regularly traveled long distances using the expressway on the first and second days and the fourth and fifth days of the Golden Week holiday in May.

[0055] Note that the holiday periods in Figures 3(a) and (b), when taking holiday periods in the United States as an example, may be spring break, summer vacation, winter break including Christmas holidays, and other holiday periods. Other holiday periods may be, for example, a certain period including a public holiday, and several consecutive days before and after the holiday when there is a certain probability that Americans will take a holiday. Examples of public holidays in the United States may include Thanksgiving Day and Independence Day. In the learning examples in the United States, freeway usage may also be reflected.

[0056] In this way, the results of the driving history during major holidays are accumulated as probability P2 within each frame, and learning proceeds. Of the probability P2 within each frame, the value within the frame for the holiday period and the day corresponding to the current day to be estimated is read out, multiplied by the weighting coefficient β, and used to calculate the probability P.

[0057] FIG. 4 is a diagram illustrating learning of the probability that a vehicle will travel on a target road along a target route to a destination, based on schedule information including the occupant's destination, which can be acquired on an information terminal carried by the occupant. Probability P3 is learned based on the schedule information of the driver of vehicle 2, depending on whether the driver of vehicle 2 has driven vehicle 2 on a highway according to the schedule. Probability P3 may increase by Δp3 (e.g., 0.1) each time vehicle 2 drives on a highway according to the schedule, following the target route to the destination acquired from the schedule information. Probability P3 may decrease by Δpd3 (e.g., 0.01) if, contrary to the schedule, vehicle 2 does not drive on a highway even once.

[0058] In this way, learning progresses by accumulating the actual results of whether or not the driver of vehicle 2 drove vehicle 2 on the expressway according to the schedule as probability P3. The latest value of probability P3 corresponding to the day to be estimated is read out, multiplied by weighting coefficient γ, and used to calculate the probability P.

[0059] Next, the processing of the notification device 1 will be described with reference to Fig. 5 and Fig. 6. Fig. 5 is a flowchart showing an example of processing of the notification device. The flowchart shown in Fig. 5 is executed, for example, when a malfunction of the external sensor 4 is recognized, and is repeatedly executed at predetermined intervals.

[0060] 5, the autonomous driving ECU 10 of the notification device 1 evaluates the likelihood that the vehicle 2 will travel on the target road in step S11. Specifically, the autonomous driving ECU 10 may perform the process shown in FIG. 6 as the likelihood evaluation process.

[0061] FIG. 6 is a flowchart showing an example of the likelihood evaluation process of FIG. The process of FIG. 6 is executed at least after the movement of the vehicle 2 for evacuation or emergency stop of the vehicle 2 is completed.

[0062] 6, in S21, the autonomous driving ECU 10 causes the notification control unit 14 to determine whether or not the target road is included in the target route. For example, if the set target route is not included in an expressway as an ODD (S21: YES), the notification control unit 14 proceeds to processing in S22. If the set target route is included in an expressway as an ODD (S22: NO), the notification control unit 14 proceeds to processing in S26.

[0063] In S22, the autonomous driving ECU 10 determines, via the notification control unit 14, whether the position of the vehicle 2 is at a distance greater than or equal to a predetermined distance threshold from the target road. For example, if the vehicle position of the vehicle 2 is at a distance greater than or equal to the predetermined distance threshold from an interchange on the expressway (S22: YES), the notification control unit 14 proceeds to processing of S23. If the vehicle position of the vehicle 2 is not at a distance greater than or equal to the predetermined distance threshold from the interchange on the expressway (S22: NO), the notification control unit 14 proceeds to processing of S26.

[0064] In S23, the autonomous driving ECU 10 estimates the probability that the vehicle 2 will travel on the target road using the notification control unit 14. The notification control unit 14 calculates the above-mentioned probabilities P1 to P3 based on, for example, the past travel history, and estimates the probability P that the vehicle 2 will travel on the expressway according to the above formula (1).

[0065] In S24, the autonomous driving ECU 10 determines whether the estimated probability P is less than a predetermined probability threshold value using the notification control unit 14. For example, if the estimated probability P is less than the predetermined probability threshold value (S24: YES), the notification control unit 14 proceeds to processing of S25. If the estimated probability P is equal to or greater than the predetermined probability threshold value (S24: NO), the notification control unit 14 proceeds to processing of S26.

[0066] In S25 and S26, the autonomous driving ECU 10 causes the notification control unit 14 to evaluate the likelihood that the vehicle 2 will travel on the target road. In S24, the notification control unit 14 evaluates that there is no likelihood that the vehicle 2 will travel on the target road (expressway). In S25, the notification control unit 14 evaluates that there is a likelihood that the vehicle 2 will travel on the target road. Thereafter, the processing of FIG. 6 ends and the process returns to FIG. 5.

[0067] Returning to Fig. 5, in S12, the autonomous driving ECU 10 causes the notification control unit 14 to determine whether or not there is no prospect that the vehicle 2 will travel on the target road. If it is determined that there is no prospect that the vehicle 2 will travel on the target road (S12: YES), the notification control unit 14 proceeds to processing of S14. If it is determined that there is a prospect that the vehicle 2 will travel on the target road (S12: NO), the notification control unit 14 proceeds to processing of S13.

[0068] In S13, the autonomous driving ECU 10 notifies the driver of a malfunction of the external sensor 4 in a normal manner without suppressing the malfunction, using the notification control unit 14. For example, when a malfunction of the external sensor 4 is recognized, the notification control unit 14 may display a pop-up message including text information such as "Autonomous driving cannot be used. System malfunction" on the speedometer screen of the HMI 8. Then, the processing of FIG. 5 ends.

[0069] In S14, the autonomous driving ECU 10 causes the notification control unit 14 to notify the driver of a malfunction of the external sensor 4 in a more restrained manner than in the processing of S13. For example, when a malfunction of the external sensor 4 is recognized, the notification control unit 14 may display an indicator using a predetermined icon representing the malfunction of the external sensor 4 on the display of the HMI 8. Alternatively, the notification control unit 14 may not notify the driver of the malfunction of the external sensor 4. Thereafter, the processing of FIG. 5 ends.

[0070] As described above, in the notification device 1, when there is no prospect that the vehicle 2 will travel on the target road, the malfunction of the external sensor 4 is notified in a suppressed manner, or the malfunction of the external sensor 4 is not notified at all. This prevents the malfunction of the external sensor 4 from being notified even when there is no prospect that the vehicle 2 will travel on the target road. As a result, it is possible to prevent the occupants from feeling annoyed and anxious due to a temporary malfunction of the external sensor 4.

[0071] In the notification device 1, if the target route does not include the target road, or if the vehicle's position is away from the target road by a predetermined distance threshold or more, the notification control unit 14 evaluates that there is no likelihood that the vehicle will travel on the target road. This makes it possible to evaluate the likelihood that the vehicle will travel on the target road depending on whether the target route includes the target road or whether the vehicle's position is away from the target road by a predetermined distance threshold or more.

[0072] In the notification device 1, the notification control unit 14 estimates the probability that the vehicle 2 will travel on the target road at a timing corresponding to the same day of the week and time period based on the past driving history, and evaluates that there is no likelihood that the vehicle 2 will travel on the target road if the estimated probability is less than a predetermined probability threshold. This makes it possible to evaluate the likelihood that the vehicle 2 will travel on the target road according to the probability that the vehicle 2 will travel on the target road at a timing corresponding to the same day of the week and time period.

[0073] In the notification device 1, the notification control unit 14 estimates the probability that the vehicle 2 will travel on the target road at the corresponding timing during the holiday period based on the past driving history, and evaluates that there is no likelihood that the vehicle 2 will travel on the target road if the estimated probability is less than a predetermined probability threshold. This makes it possible to evaluate the likelihood that the vehicle 2 will travel on the target road according to the probability that the vehicle 2 will travel on the target road at the corresponding timing during the holiday period.

[0074] In the notification device 1, the notification control unit 14 estimates probabilities P1, P2, and P3 that the vehicle 2 will travel on a target road along a target route to the destination based on schedule information including the occupant's destination that can be obtained on an information terminal carried by the occupant, and evaluates that there is no likelihood that the vehicle 2 will travel on the target road if the probability P calculated from the probabilities P1, P2, and P3 is less than a predetermined probability threshold. This makes it possible to evaluate the likelihood that the vehicle 2 will travel on the target road using schedule information including the destination.

[0075] [Variations] Although various exemplary embodiments have been described above, various omissions, substitutions, and modifications may be made without being limited to the above-described exemplary embodiments.

[0076] For example, in the above embodiment, the probabilities P1, P2, and P3 that the vehicle 2 will travel on the target road along the target route to the destination are estimated, and the probability P is calculated from the probabilities P1, P2, and P3 according to the above formula (1), but the evaluation of the likelihood is not limited to this. For example, one or two of the probabilities P1, P2, and P3 may be omitted from the calculation of the probability P, or the calculation of the probability P may be omitted and one of the probabilities P1, P2, and P3 may be compared with a probability threshold.

[0077] In the above embodiment, the probabilities P1, P2, and P3 are calculated by a learning method as shown in the examples of Figures 2 to 4, but this is not limiting. Other information (for example, past weather history, etc.) may be used to learn the probability that the vehicle 2 will travel on the target road and to estimate the probability.

[0078] In the above embodiment, expressways and motorways are exemplified as ODDs, but this is not limiting. Other ODD types include general national highways, prefectural roads, municipal roads, and private roads. For example, if the ODD is a variable type that selects a different type from among the ODD types depending on the time of day or the environment, the notification control unit 14 may notify the vehicle 2 when the vehicle 2 is located outside the currently selected ODD in a manner that suppresses malfunctions of the external sensor 4. For example, at night (time of day) or in rainy weather (environment), only expressways may be selected as ODDs, and general national highways and lower roads, including motorways, may be deselected. Furthermore, some of the above road types may be individually set as ODDs. Specifically, some roads with sharp curves, steep inclines, poor visibility, or areas where frequent accidents are expected may be deselected as ODDs.

[0079] In the above embodiment, a malfunction of the external sensor 4 is handled uniformly, but whether or not to notify in a manner that suppresses a malfunction of the external sensor 4 may be switched depending on the type of external sensor 4 and the target road, even if the target road is included in the ODD. For example, in a vehicle that requires a rider to travel on expressways but not to travel on general national roads, when the rider malfunctions, a notification may be made in a manner that does not suppress a malfunction of the rider while traveling on expressways, and a notification may be made in a manner that suppresses a malfunction of the rider while traveling on general national roads, even if the general national road is included in the ODD.

[0080] In addition to the above embodiment, when the driving assistance control or the automatic driving control cannot be started due to the vehicle state, even if the target road is included in the ODD, the notification control unit 14 may issue a notification in a manner that suppresses malfunction of the external sensor 4. For example, even if the target road is included in the ODD, such as when the vehicle 2 is in the P range state on the shoulder of a general road included in the ODD, or when the vehicle speed of the vehicle 2 exceeds the upper limit vehicle speed at which driving assistance control or the automatic driving control can be executed, the notification may be issued in a manner that suppresses malfunction of the external sensor 4.

[0081] The probability threshold may be set to an arbitrary value by the occupant via the HMI 8. The probability threshold may be selected from one of multiple levels (e.g., low probability, medium probability, high probability) by the occupant via the HMI 8. The probability threshold may be varied depending on the weather or time of day. Specifically, in bad weather or at night, the probability threshold may be changed to a smaller value in order to minimize the suppression of malfunctions in the external sensors 4. Furthermore, as the mileage of the vehicle 2 increases and the driver becomes more accustomed to the driving assistance control or the autonomous driving control, the probability threshold may be changed to a larger value so that malfunctions in the external sensors 4 are more likely to be suppressed. The probability threshold may be different for each autonomous driving level, for example, from autonomous driving level 2 to autonomous driving level 4. Specifically, in a configuration in which autonomous driving levels 2 and 3 can be switched between, the probability threshold for autonomous driving level 3 may be set to a smaller value than the probability threshold for autonomous driving level 2 in order to minimize the suppression of malfunctions in the external sensors 4.

[0082] The constituent elements of various aspects of the present disclosure will be described below. [1] A notification device for a vehicle that can execute driving assistance control or automatic driving control on a target road, a malfunction recognition unit that recognizes a malfunction of an external sensor used in the driving assistance control or the automatic driving control; a notification control unit that notifies an occupant of the vehicle of a malfunction of the external sensor when the malfunction of the external sensor is recognized, The notification control unit Evaluating whether or not the vehicle is likely to travel on the target road based on the vehicle position, target route, or travel history of the vehicle; A vehicle warning device that, when there is no prospect of the vehicle traveling on the target road, warns the occupants of the vehicle of a malfunction of the external sensor in a more restrained manner than when there is a prospect of the vehicle traveling on the target road, or does not warn the occupants of the vehicle of a malfunction of the external sensor. [2] The notification control unit evaluates that the vehicle is unlikely to travel on the target road if the target route does not include the target road, or if the vehicle's position is more than a predetermined distance threshold away from the target road. [3] The steering control device described in [1] or [2], wherein the notification control unit estimates the probability that the vehicle will travel on the target road at a time corresponding to the same day of the week and time period based on the past driving history, and evaluates that the vehicle is likely to travel on the target road if the estimated probability is greater than or equal to a predetermined probability threshold. [4] The steering control device described in any one of [1] to [3], wherein the notification control unit estimates the probability that the vehicle will travel on the target road at a corresponding timing during a holiday period based on the past driving history, and evaluates that the vehicle is likely to travel on the target road if the estimated probability is greater than or equal to a predetermined probability threshold. [5] The steering control device described in any one of [1] to [4], wherein the notification control unit estimates the probability that the vehicle will travel on the target road along the target route to the destination based on schedule information including the occupant's destination that can be obtained on an information terminal carried by the occupant, and evaluates that the vehicle is likely to travel on the target road if the estimated probability is greater than or equal to a predetermined probability threshold. [Explanation of symbols]

[0083] 1...alarm device, 2...vehicle, 4...external sensor, 13...malfunction recognition unit, 14...alarm control unit.

Claims

1. A notification device for a vehicle that can execute driving assistance control or automatic driving control on a target road, a malfunction recognition unit that recognizes a malfunction of an external sensor used in the driving assistance control or the automatic driving control; a notification control unit that notifies an occupant of the vehicle of a malfunction of the external sensor when the malfunction of the external sensor is recognized, The notification control unit Evaluating whether or not the vehicle is likely to travel on the target road based on the vehicle position, the target route, or the travel history of the vehicle; An alarm device that alerts the occupants of the vehicle to a malfunction of the external sensor in a more restrained manner when there is no prospect that the vehicle will travel on the target road compared to when there is a prospect that the vehicle will travel on the target road, or that does not alert the occupants of the vehicle to a malfunction of the external sensor.

2. 2. The notification device according to claim 1, wherein the notification control unit evaluates that the vehicle is unlikely to travel on the target road if the target route does not include the target road or if the vehicle's position is away from the target road by more than a predetermined distance threshold.

3. The notification device described in claim 1 or 2, wherein the notification control unit estimates the probability that the vehicle will travel on the target road at a time corresponding to the same day of the week and time period based on the past driving history, and evaluates that the vehicle is unlikely to travel on the target road if the estimated probability is less than a predetermined probability threshold.

4. The notification device according to claim 1 or 2, wherein the notification control unit estimates the probability that the vehicle will travel on the target road at a corresponding time during a holiday period based on the past driving history, and evaluates that the vehicle is unlikely to travel on the target road if the estimated probability is less than a predetermined probability threshold.

5. The notification control unit estimates the probability that the vehicle will travel on the target road along the target route to the destination based on schedule information including the occupant's destination that can be obtained on an information terminal carried by the occupant, and evaluates that the vehicle is unlikely to travel on the target road if the estimated probability is less than a predetermined probability threshold.

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