Vehicle control system

Abstract

To reduce discomfort and anxiety of an occupant when vehicle traveling control causes generation of a vehicle behavior that cannot be predicted by the occupant.SOLUTION: A vehicle control system generates a target trajectory on the basis of a driving environment of a vehicle and executes vehicle traveling control for controlling the vehicle to follow the target trajectory. The vehicle control system calculates a deviation degree between a prediction trajectory or a predicted vehicle state predicted from a current vehicle state of the vehicle and the target trajectory. When the deviation degree satisfies a notification provision condition, the vehicle control system provides an occupant of the vehicle with notification indicating target behavior of the vehicle caused by the vehicle traveling control.SELECTED DRAWING: Figure 3

Description

[Technical Field]

[0001] The present disclosure relates to techniques for providing a notification to a vehicle occupant indicating a target behavior of a cruise-controlled vehicle. [Background technology]

[0002] Patent Document 1 discloses a technique for providing information in advance as to whether a target vehicle can travel a target road in a predetermined travel pattern. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Japanese Patent Publication No. 2023-023538 Summary of the Invention [Problem to be solved by the invention]

[0004] Consider a situation where a passenger is in a vehicle under vehicle cruise control. If the vehicle cruise control causes vehicle behavior that the passenger cannot anticipate, the passenger may feel uncomfortable or uneasy.

[0005] One object of the present disclosure is to reduce the discomfort and anxiety felt by occupants when vehicle driving control causes vehicle behavior that cannot be predicted by the occupants. [Means for solving the problem]

[0006] The first aspect relates to a vehicle control system that controls a vehicle. The vehicle control system includes a control device. The control device generates a target trajectory based on the driving environment of the vehicle, and executes vehicle driving control to control the vehicle so as to follow the target trajectory. The control device calculates a predicted trajectory predicted from the current vehicle state of the vehicle or a deviation between the predicted vehicle state and the target trajectory. When the deviation degree satisfies the notification provision condition, the control device provides a notification indicating the target behavior of the vehicle resulting from the vehicle driving control to an occupant of the vehicle. [Effects of the Invention]

[0007] According to a first aspect, the vehicle control system provides a notification indicating the target behavior of the vehicle to the occupant in accordance with the degree of deviation between the predicted trajectory or the predicted vehicle state and the target trajectory. This allows the occupant to know how the vehicle will behave in the future. Therefore, discomfort and anxiety about the vehicle behavior caused by the vehicle driving control are reduced. [Brief explanation of the drawings]

[0008] [Figure 1] 1 is a conceptual diagram for explaining an overview of a vehicle control system according to an embodiment of the present invention; [Figure 2] FIG. 2 is a block diagram showing an example of driving environment information. [Figure 3] FIG. 10 is a schematic diagram showing a case where a vehicle control system performs notification. [Figure 4] 10A to 10C illustrate various examples of notifications. [Figure 5] FIG. 2 is a block diagram showing a detailed configuration example of the vehicle control system. [Figure 6] 10 is a flowchart illustrating an outline of a process for notifying a target behavior. DETAILED DESCRIPTION OF THE INVENTION

[0009] Embodiments of the present disclosure will be described with reference to the accompanying drawings.

[0010] 1. Vehicle Control System 1 is a conceptual diagram for explaining an overview of a vehicle control system 10 according to this embodiment. The vehicle control system 10 controls a vehicle 1. Typically, the vehicle control system 10 is mounted on the vehicle 1.

[0011] The vehicle control system 10 includes a sensor group 20, an HMI (Human-Machine Interface) unit 30, a traveling device 50, a communication device 60, and a control device 70. At least the sensor group 20, the HMI unit 30, the traveling device 50, and the communication device 60 are mounted on a vehicle 1. The sensor group 20 includes a recognition sensor 21, a vehicle state sensor 22, and a position sensor 23.

[0012] The recognition sensor 21 recognizes (detects) the situation around the vehicle 1. Examples of the recognition sensor 21 include a camera, a LIDAR (Laser Imaging Detection and Ranging), and a radar. The vehicle state sensor 22 detects the state of the vehicle 1. For example, the vehicle state sensor 22 includes a speed sensor, an acceleration sensor, a yaw rate sensor, a steering angle sensor, and the like. The position sensor 23 detects the position and orientation of the vehicle 1. For example, the position sensor 23 includes a GNSS (Global Navigation Satellite System).

[0013] The HMI unit 30 is an interface for providing information to an occupant (e.g., the driver) of the vehicle 1 and for receiving information from the occupant. Specifically, the HMI unit 30 has an input device and an output device. Examples of the input device include a touch panel, a switch, a microphone, etc. Examples of the output device include a display device, a speaker, etc. Examples of the display device include a liquid crystal panel, an organic EL panel, etc.

[0014] The traveling device 50 (actuator) includes a steering device, a drive device, and a braking device. The steering device steers the wheels. For example, the steering device includes an electric power steering (EPS) device. The drive device is a power source that generates driving force. Examples of the drive device include an engine, an electric motor, and an in-wheel motor. The braking device generates braking force.

[0015] The communication device 60 communicates with the outside via a communication network. Examples of communication methods include mobile communication such as 5G and wireless LAN.

[0016] The control device 70 is a computer that controls the vehicle 1. Typically, the control device 70 is mounted on the vehicle 1. However, a part of the control device 70 may be disposed in an external device and control the vehicle 1 remotely. The control device 70 executes various processes. For example, the control device 70 includes processing circuitry such as a CPU (Central Processing Unit). The processing circuitry may also be called a processor. The control device 70 includes one or more storage devices 72 (hereinafter simply referred to as storage devices 72). The storage devices 72 store various information. Examples of the storage devices 72 include volatile memory, non-volatile memory, HDD (Hard Disk Drive), SSD (Solid State Drive), etc.

[0017] The control program 80 is a computer program for controlling the vehicle 1. The functions of the control device 70 may be realized by cooperation between the control device 70, which executes the control program 80, and the storage device 72. The control program 80 is stored in the storage device 72. Alternatively, the control program 80 may be recorded on a computer-readable recording medium.

[0018] The control device 70 acquires driving environment information 90 that indicates the driving environment of the vehicle 1. The driving environment information 90 is stored in the storage device 72.

[0019] 2 is a block diagram showing an example of driving environment information 90. The driving environment information 90 includes map information 91, surrounding situation information 92, vehicle state information 93, and vehicle position information 94.

[0020] The map information 91 includes a general navigation map. The map information 91 may indicate lane layouts and road shapes. The map information 91 may also include location information for structures, traffic lights, signs, and the like. The control device 70 acquires the map information 91 for a required area from a map database. The map database may be stored in the storage device 72, or may be stored in a map management device external to the vehicle 1. In the latter case, the control device 70 communicates with the map management device via the communication device 60 to acquire the required map information 91.

[0021] The surrounding situation information 92 is information obtained based on the recognition result by the recognition sensor 21, and indicates the situation around the vehicle 1. The control device 70 recognizes the situation around the vehicle 1 using the recognition sensor 21 and acquires the surrounding situation information 92. For example, the surrounding situation information 92 includes an image IMG captured by a camera. As another example, the surrounding situation information 92 includes point cloud information obtained by LIDAR.

[0022] The surrounding situation information 92 further includes object information OBJ related to objects (targets) around the vehicle 1. Examples of objects include pedestrians, bicycles, motorcycles, other vehicles (preceding vehicles, parked vehicles, etc.), white lines, traffic lights, structures (e.g., utility poles, pedestrian bridges), signs, and obstacles. The object information OBJ indicates the relative position and relative speed of the object with respect to the vehicle 1. For example, by analyzing images IMG acquired by a camera, it is possible to identify the object and calculate the relative position of the object. It is also possible to identify the object and obtain the relative position and relative speed of the object based on point cloud information acquired by LIDAR. The control device 70 may track the recognized object. In this case, the object information OBJ also includes trajectory information of the recognized object.

[0023] The vehicle state information 93 is information detected by the vehicle state sensor 22 and indicates the state of the vehicle 1. The state of the vehicle 1 includes the vehicle speed, acceleration, yaw rate, steering angle, etc. The control device 70 acquires the vehicle state information 93 from the vehicle state sensor 22. The vehicle state information 93 may indicate the driving state (automatic driving / manual driving) of the vehicle 1.

[0024] The vehicle position information 94 is information indicating the current position of the vehicle 1. The control device 70 acquires the vehicle position information 94 from the detection results of the position sensor 23. The control device 70 may also acquire highly accurate vehicle position information 94 by a well-known self-position estimation process (Localization) that uses the object information OBJ and the map information 91.

[0025] The control device 70 also performs vehicle driving control to control the driving of the vehicle 1. The vehicle driving control includes steering control, acceleration control, and deceleration control. The control device 70 performs vehicle driving control by controlling the traveling device 50 (steering device, drive device, braking device). More specifically, the control device 70 calculates the control amount (actuator control amount) of the traveling device 50 and controls the traveling device 50 in accordance with the actuator control amount.

[0026] Furthermore, the control device 70 performs automatic driving control to control automatic driving of the vehicle 1. Here, automatic driving means that at least a portion of the steering, acceleration, and deceleration of the vehicle 1 is performed automatically, independent of the driver's operation. As an example, automatic driving of level 3 or higher may be performed. The control device 70 generates a driving plan for the vehicle 1 based on the driving environment information 90. Examples of driving plans include maintaining the current driving lane, changing lanes, making right or left turns, and avoiding collisions with objects. More specifically, the driving plan includes a route plan and a speed plan for the vehicle 1. The route plan is a set of target positions for the vehicle 1. The speed plan is a set of target speeds for each target position. The combination of the route plan and the speed plan is also called a "target trajectory." In other words, the target trajectory includes the target position and target speed of the vehicle 1. The control device 70 performs vehicle driving control so that the vehicle 1 follows the target trajectory TTR. The control device 70 may perform automatic driving control while performing optimization using model predictive control (MPC).

[0027] 2. Notification of vehicle target behavior Assume that the vehicle 1 is under vehicle driving control (particularly, automatic driving control) by the control device 70, and an occupant is on board the vehicle 1. In such a situation, it may be desirable to notify the occupant in advance of a target behavior of the vehicle 1 resulting from the vehicle driving control. As an example, consider a case where the vehicle control system 10 recognizes an obstacle that the occupant cannot see. For example, the vehicle control system 10 can acquire information about the obstacle via a camera mounted on the vehicle 1. The vehicle control system 10 may also acquire information about the obstacle captured by another camera through communication via the communication device 60. The vehicle control system 10 generates a target trajectory TTR that avoids the obstacle and causes the vehicle 1 to follow the target trajectory TTR. The behavior of the vehicle 1 indicated by the generated target trajectory TTR is likely to be different in tendency from the behavior of the vehicle 1 up to the present time. In this case, the occupant may feel uncomfortable or uneasy because the vehicle 1 behaves differently from its previous tendency because the occupant is unable to recognize the obstacle. In addition, the occupants may feel uncomfortable or anxious due to sudden vehicle behavior, unexpected vehicle behavior, or unique vehicle behavior caused by vehicle driving control. Therefore, the vehicle control system 10 notifies the occupants of the target behavior of the vehicle 1 caused by vehicle driving control (especially automatic driving control) via the HMI unit 30 as necessary. This is expected to have the effect of reducing the discomfort and anxiety that the occupants may feel. In this embodiment, specific aspects thereof will be described below.

[0028] 2-1. Overview of notifications showing target behavior FIG. 3 is a schematic diagram showing a case where the vehicle control system 10 performs notification. The predicted trajectory PTR is a hypothetical trajectory that the vehicle 1 will travel based on the current state of the vehicle 1. The predicted trajectory PTR includes a predicted position and a predicted speed of the vehicle 1. The control device 70 can predict (calculate) the predicted trajectory PTR based on a vehicle motion model and current vehicle state information 93 (vehicle speed, acceleration, yaw rate, steering angle, etc.). The predicted trajectory PTR in FIG. 3 indicates a straight-line behavior.

[0029] On the other hand, the target trajectory TTR in Fig. 3 deviates from the predicted trajectory PTR in the direction of steering to the right. Since the vehicle 1 follows the target trajectory TTR, Fig. 3 shows a situation in which a deviation occurs between the predicted trajectory PTR and the target behavior (target trajectory TTR) of the vehicle 1. A specific example of a situation in Fig. 3 occurs when the vehicle control system 10 recognizes an obstacle that is not visible to the occupants, as described above. The control device 70 generates a target trajectory TTR to avoid the obstacle.

[0030] The control device 70 calculates the deviation DIV between the target trajectory TTR and the predicted trajectory PTR. A simple example of the deviation DIV is the distance between the target trajectory TTR and the predicted trajectory PTR. In the example of FIG. 3, the control device 70 sets time steps and acquires a position Xti at each time step on the target trajectory TTR. Similarly, the control device 70 acquires a position Xpi of the vehicle 1 at each time step on the predicted trajectory PTR. The control device 70 calculates the deviation DIV between the position Xti and the position Xpi.

[0031] There are various other examples of methods for calculating the deviation DIV. For example, the difference in vehicle parameters (e.g., speed, steering angle, etc.) between the target trajectory TTR and the predicted trajectory PTR may be calculated as the deviation DIV. As yet another example, autonomous driving control may be performed while performing optimization using model predictive control (MPC). In this case, the error between the target value (target vehicle state corresponding to the target trajectory TTR) and the predicted value (predicted vehicle state predicted from the current vehicle state) in the MPC may be used as the deviation DIV.

[0032] Next, the control device 70 determines whether the deviation DIV satisfies a specific condition. If the deviation DIV satisfies the specific condition, a notification indicating the target behavior is provided to the occupant via the HMI unit 30. The condition under which the control device 70 provides a notification indicating the target behavior is referred to as a "notification provision condition." For example, as shown in FIG. 3, the notification provision condition may be a case in which the deviation DIV1 between the position Xt1 of the vehicle 1 on the target trajectory TTR and the position Xp1 of the vehicle 1 on the predicted trajectory PTR at a specific timing (first timing) is equal to or greater than a predetermined threshold value TH1. The deviation DIV considered as the notification provision condition does not have to be for a single timing. For example, the notification provision condition may be determined based on the average value of the deviation DIV at multiple timings or the integrated value of the deviation DIV over multiple time steps. Other examples of the deviation DIV and the notification provision condition will be described later.

[0033] It is desirable that the content of the target behavior notified via the HMI unit 30 be content that the occupant can intuitively understand and that corresponds to the operation that the occupant would perform when driving the vehicle 1. In the example of FIG. 3, the HMI unit 30 displays a message to steer to the right, which corresponds to the steering operation. In addition, the notification may include the reason for performing vehicle driving control that leads to such a target behavior. Note that the notification indicating the target behavior may be provided by audio through a speaker, or may be a combination of a visual display and audio.

[0034] FIG. 4 is a diagram illustrating various examples of notifications. It shows the vehicle 1 passing through a curve following a straight section. As illustrated, the vehicle control system 10 can also notify the target behavior of the vehicle 1 that cannot be predicted from the road shape alone. For example, acceleration in a straight section, acceleration / deceleration before and after a curve, and steering in accordance with the curve shape are behaviors that the occupant can predict from the road shape. For example, if acceleration in a straight section is large and deceleration control is executed to safely pass through the following curve, the timing of deceleration of the vehicle 1 may occur earlier than the occupant expects. In this way, the vehicle control system 10 can also notify the behavior of the vehicle 1 that cannot be predicted from the road shape alone.

[0035] 2-2.Effects As described above, the vehicle control system 10 calculates the deviation DIV between the target trajectory TTR and the predicted trajectory PTR or the predicted vehicle state. Furthermore, the vehicle control system 10 provides the occupant with a notification indicating the target behavior of the vehicle 1 resulting from the vehicle cruise control, according to the deviation DIV. This allows the occupant to know how the vehicle 1 will behave in the future. This reduces discomfort and anxiety caused by sudden vehicle behavior, unexpected vehicle behavior, peculiar vehicle behavior, etc. resulting from the vehicle cruise control.

[0036] Furthermore, by allowing the occupant to change the notification provision conditions, it is possible to display notifications that are more suited to the occupant (details will be described later). This will prevent situations such as "not being notified when the occupant wants to be notified" or "unnecessary notifications being displayed when the occupant does not need to be notified." This will contribute to reducing occupant anxiety and preventing unnecessary notifications.

[0037] 3. Examples of deviations and notification conditions In the example of Fig. 3, the notification provision condition is based on the positional deviation DIV between the target trajectory TTR and the predicted trajectory PTR, but the notification provision condition and the deviation DIV are not limited to this case.

[0038] The deviation DIV may be calculated based on the difference between the "target vehicle parameter TPA" and the "predicted vehicle parameter PPA." The target vehicle parameter TPA defines a target vehicle state. The target vehicle state refers to the state of the vehicle 1 at each time step on the target trajectory TTR. In other words, the target vehicle parameter TPA indicates the vehicle state required for the vehicle 1 to travel while following the target trajectory TTR. Similarly, the predicted vehicle parameter PPA defines a predicted vehicle state. In other words, the predicted vehicle parameter PPA indicates the vehicle state when it is assumed that the vehicle 1 travels along the predicted trajectory PTR. Examples of each parameter (target vehicle parameter TPA, predicted vehicle parameter PPA) include position, vehicle speed, acceleration, yaw rate, steering angle, actuator control amount, actuator operation amount, etc.

[0039] In this case, the control device 70 calculates the deviation DIV based on the difference between the target vehicle parameter TPA and the predicted vehicle parameter PPA. The deviation DIV is an index that includes a composite of information on each parameter. The deviation DIV is calculated based on the difference between the target vehicle parameter TPA and the predicted vehicle parameter PPA at a first future timing. Typically, when the deviation DIV at the first future timing is equal to or greater than a predetermined value, the control device determines that the notification provision condition is met.

[0040] Furthermore, a machine learning model that uses the deviation DIV as input data may determine the notification provision conditions and the content of the notification. As described above, the calculation of the deviation DIV is a complex index involving various parameters. Therefore, it may be more appropriate to generate notification provision conditions that take into consideration each parameter in a complex manner using a machine learning model, rather than based on a preset threshold. The content of the notification may also be content that is taken into consideration in a complex manner by the machine learning model. In other words, by using a machine learning model in combination, the notification provision conditions and the content of the notification can be determined more flexibly.

[0041] The notification provision conditions may also be set by the occupant. For example, the threshold level of the deviation degree DIV that defines the notification provision conditions may be adjustable by the occupant. Alternatively, the difference between the target vehicle parameter TPA and the predicted vehicle parameter PPA may be taken into consideration only for specific parameters selected by the occupant. In this case, the deviation degree DIV is calculated only for the parameters selected by the occupant and is taken into consideration in determining the notification provision conditions. Through such settings, the occupant can adjust the frequency and content of notifications appropriately for themselves.

[0042] 4.Configuration example FIG. 5 is a block diagram showing a detailed configuration example of the vehicle control system 10. As shown in FIG.

[0043] The vehicle control unit 71 acquires driving environment information 90 from the sensor group 20. The target trajectory generation unit 71a generates a target trajectory TTR based on the driving environment information 90. The target vehicle parameter acquisition unit 71b acquires a target vehicle parameter TPA based on the generated target trajectory TTR.

[0044] The behavior prediction unit 73 acquires various information including vehicle state information 93 from the sensor group 20. The predicted trajectory calculation unit 73a calculates a predicted trajectory PTR based on the various information from the sensor group 20 and a vehicle motion model. The vehicle motion model is stored in advance in the storage device 72. The predicted vehicle parameter acquisition unit 73b acquires predicted vehicle parameters PPA based on the generated predicted trajectory PTR.

[0045] The deviation calculation unit 74 receives information from the vehicle control unit 71 and the behavior prediction unit 73. The deviation calculation unit 74 performs a "trajectory comparison" that compares a target trajectory TTR with a predicted trajectory PTR. The deviation calculation unit 74 may also perform a "parameter comparison" that compares a target vehicle parameter TPA with a predicted vehicle parameter PPA. The deviation calculation unit 74 calculates a deviation DIV through the trajectory comparison and parameter comparison.

[0046] The notification determination unit 75 receives information regarding the deviation DIV from the deviation calculation unit 74. The notification determination unit 75 determines whether or not the notification provision conditions are met based on the deviation DIV. Examples of the notification provision conditions are as described in Sections 2 and 3. If the notification provision conditions are met, the notification determination unit 75 provides the occupant with a notification indicating the target behavior of the vehicle 1 via the HMI unit 30.

[0047] FIG. 6 is a flowchart showing an outline of the process of notifying a target behavior.

[0048] In step S10, the control device 70 acquires various information including the driving environment information 90 and the vehicle state information 93 from the sensor group 20. Thereafter, the process proceeds to step S20.

[0049] In step S20, the control device 70 generates a target trajectory TTR and calculates a predicted trajectory PTR based on various information acquired from the sensor group 20. In addition, the control device 70 acquires a target vehicle parameter TPA and a predicted vehicle parameter PPA based on the target trajectory TTR and the predicted trajectory PTR. Thereafter, the process proceeds to step S30.

[0050] In step S30, the control device 70 executes trajectory comparison and parameter comparison. Furthermore, based on the results of the trajectory comparison and parameter comparison, the degree of deviation DIV is calculated. Thereafter, the process proceeds to step S40.

[0051] In step S40, the control device 70 determines whether the notification provision condition is met. If the notification provision condition is met (step S40; YES), the process proceeds to step S50. On the other hand, if the notification provision condition is not met (step S40; NO), the process returns to step S10.

[0052] In step S50, the control device 70 provides the occupant with a notification indicating the planned behavior of the vehicle 1. The notification is provided via the HMI unit 30 in the vehicle 1. Thereafter, the process ends. [Explanation of symbols]

[0053] 1: vehicle, 10: vehicle control system, 20 sensor group, 30: HMI unit, 70: control device, 71: vehicle control unit, 71a: target trajectory generation unit, 71b: target vehicle parameter acquisition unit, 73: behavior prediction unit, 73a: predicted trajectory calculation unit, 73b: predicted vehicle parameter acquisition unit, 74: deviation calculation unit, 75: notification determination unit, DIV: deviation, PPA: predicted vehicle parameter, PTR: predicted trajectory, TPA: target vehicle parameter, TTR: target trajectory

Claims

1. A vehicle control system for controlling a vehicle, A control device is provided, The control device generating a target trajectory based on a driving environment of the vehicle, and performing vehicle driving control to control the vehicle so as to follow the target trajectory; Calculating a predicted trajectory predicted from a current vehicle state of the vehicle or a deviation between the predicted vehicle state and the target trajectory; If the deviation degree satisfies a notification provision condition, a notification indicating a target behavior of the vehicle resulting from the vehicle driving control is provided to an occupant of the vehicle. It was configured as Vehicle control system.

2. 2. The vehicle control system according to claim 1, The control device further acquiring target vehicle parameters necessary for the vehicle to travel following the target trajectory; obtaining predicted vehicle parameters that would be predicted if the vehicle were to travel along the predicted trajectory; The deviation is calculated based on a difference between the target vehicle parameter and the predicted vehicle parameter at a first future timing. Vehicle control system.

3. 2. The vehicle control system according to claim 1, The notification provision condition includes a case where the deviation is equal to or greater than a predetermined threshold. Vehicle control system.

4. 2. The vehicle control system according to claim 1, The control device Using a machine learning model, the conditions for providing the notification and the content of the notification are determined. Vehicle control system.

5. 5. A vehicle control system according to claim 1, The notification provision conditions can be set by the occupant. Vehicle control system.

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