JP7615982B2 - Determination device, determination method, and determination program - Google Patents

Description

This disclosure relates to a determination device, a determination method, and a determination program for controlling a vehicle.

Patent Document 1 discloses a technology that reduces the possibility of a decrease in the accuracy of driving diagnosis. This technology acquires the relative relationship between the vehicle ahead and the vehicle itself, diagnoses the driving behavior of the vehicle based on the relative relationship, and excludes the vehicle ahead from the diagnosis if there is a sudden change in the relative relationship caused by the vehicle ahead.

JP 2020-38513 A

The technology of Patent Document 1 describes that the vehicle distance becomes small due to the behavior of other vehicles. Here, when diagnosing driving content, it is important to what extent the driver of the vehicle is able to operate the vehicle in a way that allows foresight. A driving operation that allows foresight here refers to a driving operation that is necessary from the current time on the road being traveled at a future time. It is thought that to some extent it is possible to determine whether a driving operation is one that can be foreseen from the driver's driving conditions. However, as in the prior art, it is not possible to determine whether a driving operation is one that can be foreseen from the behavior of other vehicles.

The present disclosure aims to provide a determination device, a determination method, and a determination program that can determine whether a driver is performing predictable driving operations.

The determination device described in claim 1 includes a scene processing unit that acquires vehicle driving scenes of a level preset according to the road , and a determination unit that sets a reference value for a maximum vehicle speed and a reference value for a time during which a speed within a specified maximum vehicle speed is maintained for each level of the driving scene as predetermined criteria for the driving scenes, and determines whether the vehicle speed of the vehicle has reached the reference value for maximum vehicle speed for the acquired driving scene, and if the reference value for maximum vehicle speed has been reached, determines whether the time during which a speed within the specified maximum vehicle speed is maintained is equal to or longer than a certain period of time and satisfies the reference value for the maintained time , and determines that a driving operation that can be predicted is being performed if the reference value for the maintained time is satisfied.

The determination device according to claim 1 determines that the driver is performing a predictable driving operation when the vehicle speed reaches a predetermined maximum vehicle speed and the time that the maximum vehicle speed is maintained within the predetermined speed is equal to or longer than a certain period of time. In this way, the driving operation status of the driver can be grasped from the transition of the vehicle speed, such as the vehicle speed and the time that the vehicle speed is maintained. In other words, it is possible to determine whether the driver is performing a predictable driving operation from the transition of the vehicle speed.
Furthermore, the determination device can set a standard according to the level of the driving scene.

According to a second aspect of the present invention, in the determination device according to the first aspect, the level of the driving scene is set in accordance with a shape of a road, and the flatter the shape of the road is, the larger the reference value of the maximum vehicle speed of the reference is set, and the longer the reference value of the maintained time is set.

According to the determination device of the second aspect, the level of a driving scene can be set according to the shape of the road, and an appropriate standard can be set according to the level.

The determination device of claim 3 is the determination device of claim 1 or claim 2 , in which the criteria include a criterion regarding the user state of the user driving the vehicle, and the determination unit acquires the user state of the user driving the vehicle, and when the user state and the vehicle speed satisfy the criteria, determines that the driving operation is one that can be predicted in advance.

According to the determination device of the third aspect, it is possible to more reliably determine whether a driving operation is one that can be predicted in advance, taking into account the user's state.

The determination device according to claim 4 is the determination device according to claim 3 , wherein, in a case where the user state is stagnant, the reference value of the maintained time of the criterion is updated to be longer in accordance with the user state.

According to the determination device of the fourth aspect, it is possible to perform the determination process taking into consideration the user's level of awakening.

The determination device according to claim 5 is the determination device according to any one of claims 1 to 4 , wherein when the weather is bad in the driving scene, the reference value of the criterion is corrected so as to reduce the maximum vehicle speed and to shorten the maintained time.

According to the determination device of the fifth aspect, it is possible to perform the determination process using an appropriate criterion depending on the environment.

The determination method described in claim 6 is a process performed by a computer to acquire a vehicle driving scene of a level that is preset according to a road , and as predetermined criteria for the driving scene, a reference value for a maximum vehicle speed and a reference value for a time during which a speed within a specified maximum vehicle speed is maintained are set for each level of the driving scene, and for the acquired driving scene, determine whether the vehicle speed of the vehicle has reached the reference value for maximum vehicle speed, and if the reference value for maximum vehicle speed has been reached, determine whether the time during which a speed within the specified maximum vehicle speed is maintained is equal to or longer than a certain period of time and satisfies the reference value for the maintenance time , and determine that a driving operation that can be predicted is being performed if the reference value for the maintenance time is satisfied.

The judgment program described in claim 7 causes a computer to execute a process of acquiring a vehicle driving scene of a level preset according to a road, and setting a reference value for a maximum vehicle speed and a reference value for a time during which a speed within a specified maximum vehicle speed is maintained for each level of the driving scene as predetermined criteria for the driving scene, and determining whether the vehicle speed of the vehicle has reached the reference value for maximum vehicle speed for the acquired driving scene, and if the reference value for maximum vehicle speed has been reached, determining whether the time during which a speed within the specified maximum vehicle speed is maintained is a certain period of time or longer and satisfies the reference value for the maintenance time , and determining that a driving operation that can be predicted is being performed if the reference value for the maintenance time is satisfied.

The technology disclosed herein makes it possible to determine whether the driver is performing predictable driving operations.

FIG. 13 is a graph showing the relationship between vehicle speed and time, comparing a case of driving with and without predictability. 1 is a diagram showing a schematic configuration of a vehicle control system according to an embodiment; 1 is a block diagram showing a hardware configuration of a vehicle according to an embodiment; FIG. 2 is a block diagram showing a hardware configuration of a center server according to an embodiment. FIG. 2 is a block diagram showing a functional configuration of a center server according to an embodiment. FIG. 2 is a sequence diagram showing a process flow in the vehicle control system according to the embodiment. 11 is a flowchart showing the flow of a determination process executed in the center server of the embodiment. FIG. 13 is a block diagram showing a functional configuration of a center server in a modified example. FIG. 11 is a sequence diagram showing a process flow in a vehicle control system according to a modified example. 13 is a flowchart showing the flow of a determination process executed in a center server in a modified example.

A vehicle control system including a determination device according to an embodiment of the present invention will be described. The vehicle control system is a system that determines whether the driver is performing a driving operation that can be predicted.

In the vehicle control system of this embodiment, the vehicle speed transition is judged using a standard for vehicle speed determined for each level of the driving scene, and whether the driving operation is predictable or not is judged. In this embodiment, the driving scene refers to a driving scene of a certain section where the vehicle is driving. A level is set for the driving scene according to the flatness of the road shape, that is, the ease of driving. In addition, the vehicle speed standard is set as a first standard for a standard value of the maximum vehicle speed, and as a second standard, a standard value of the maintenance time within a predetermined speed from the maximum vehicle speed is set. The maximum vehicle speed of the first standard here is a vehicle speed that is assumed to be achievable in the case of predictable driving, and may be set appropriately by experiments, etc. In addition, the second standard is set as the maintenance time of the maximum vehicle speed, since it is necessary to determine to what extent the maximum vehicle speed can be maintained. Note that setting a level for the driving scene is one example, and the ease of driving of the driving scene may be quantified.

As for the levels of driving scenes, for example, since the flatness of the road varies depending on the shape of the road, it is assumed that the degree of ease of driving changes depending on this, and a tiered level is set according to the flatness of the road shape. The shape of the road being driven on is obtained from map data, etc., to be either "flat," "curvy road," or "mountain road." As for the levels of driving scenes, three levels are set for the shape of the road: level 1 for a "flat road" such as an urban area, level 2 for a "curvy road" with a curved road shape, and level 3 for a "mountain road" that is assumed to have a steep slope. The flatter the road shape is, i.e., the smaller the level, the higher the reference value for the maximum vehicle speed of the first criterion is set, and the longer the reference value for the maintenance time of the second criterion is set.

An example of the criteria will be described. When the driving scene is level 1, in the first criterion, the reference value of the maximum vehicle speed is set to 40 km/h, and the condition for satisfying the first criterion is that the vehicle speed reaches 40 km/h. In the second criterion, the reference value of the maintenance time for maintaining a maximum vehicle speed of 40 km/h or less within -5 km/h is set to 10 seconds, and the condition for satisfying the second criterion is that the maximum vehicle speed is maintained within -5 km/h for 10 seconds or more. These reference values are examples, and can be set appropriately for each level of the driving scene. Note that a reference value within a predetermined speed may also be set in the second criterion. In addition, if the road is well-visible, the maintenance time may include the case where the maximum vehicle speed is maintained within +5 km/h of 40 km/h or more. However, in the case of a normal flat road, the second criterion is not satisfied because it is determined that the speed is excessive, and the condition for the maintenance of the vehicle speed from the maximum vehicle speed may be set according to the specific road shape of the driving scene.

Figure 1 is a graph showing the relationship between vehicle speed and time, comparing driving with and without predictability. (A) in Figure 1 is a case of driving with and without predictability, and (B) is a case of driving without predictability. (A) reaches the maximum vehicle speed and meets the first criterion, and also meets the second criterion because the maximum vehicle speed of 40 km/h is kept within -5 km/h for 10 seconds or more. Therefore, it can be determined that the driving is capable of predicting. (B) reaches the maximum vehicle speed and meets the first criterion, but does not meet the second criterion because the maximum vehicle speed of 40 km/h is not kept within -5 km/h for 10 seconds or more. Therefore, it is determined that the driving is not capable of predicting.

The judgment of predictable driving operations obtained by the method of this embodiment as described above can be used, for example, for scoring the diagnosis of driving contents. In the diagnosis of driving contents, if predictable driving operations are performed, the driver is diagnosed as having driven safely and given a high score, and conversely, if predictable driving operations are not performed, the driver is diagnosed as having driven unsafely and given a low score.

(Overall composition)
As shown in Fig. 2, a vehicle control system 10 according to an embodiment of the present invention includes a vehicle 12, a center server 30 serving as a determination device, and a terminal 40. The vehicle 12 is also equipped with an in-vehicle device 20. The in-vehicle device 20, the center server 30, and the terminal 40 are connected to one another via a network N. Note that, although Fig. 2 illustrates one vehicle 12, one in-vehicle device 20, and one terminal 40 for one center server 30, the numbers of vehicles 12, in-vehicle devices 20, and terminals 40 are not limited to this.

The center server 30 is installed, for example, at the manufacturer that produces the vehicle 12 or at a car dealership affiliated with the manufacturer. Examples of the terminal 40 include a smartphone or personal computer owned by an administrator or owner who is aware of the vehicle operation status of the driver of the vehicle 12. A request for determining vehicle operation is sent from the terminal 40 to the center server 30.

(vehicle)
As shown in FIG. 3 , the vehicle 12 according to this embodiment is configured to include an in-vehicle device 20 , a plurality of ECUs (Electronic Control Units) 22 , and a plurality of in-vehicle devices 24 .

The vehicle-mounted device 20 includes a CPU (Central Processing Unit) 20A, a ROM (Read Only Memory) 20B, a RAM (Random Access Memory) 20C, an in-vehicle communication I/F (Interface) 20D, and a wireless communication I/F 20E. The CPU 20A, the ROM 20B, the RAM 20C, the in-vehicle communication I/F 20D, and the wireless communication I/F 20E are connected to each other so as to be able to communicate with each other via an internal bus 20G.

The CPU 20A is a central processing unit that executes various programs and controls each part. That is, the CPU 20A reads the programs from the ROM 20B and executes the programs using the RAM 20C as a working area.

The ROM 20B stores various programs and data. In this embodiment, the ROM 20B stores a control program 50 that collects vehicle information related to the state and control of the vehicle 12 from the ECU 22 and permits or restricts the use of functions or the application of equipment of the vehicle 12. The ROM 20B also stores history information 110, which is backup data of the vehicle information.
The RAM 20C temporarily stores programs or data as a working area.

The in-vehicle communication I/F 20D is an interface for connecting to each ECU 22. This interface uses a communication standard based on the CAN protocol. The in-vehicle communication I/F 20D is connected to the external bus 20H.

The wireless communication I/F 20E is a wireless communication module for communicating with the center server 30. The wireless communication module uses communication standards such as 5G, LTE, and Wi-Fi (registered trademark). The wireless communication I/F 20E is connected to the network N.

The ECU 22 includes at least an ADAS (Advanced Driver Assistance System)-ECU 22A, a steering ECU 22B, a brake ECU 22C, and an engine ECU 22D.

The ADAS-ECU 22A controls the advanced driving assistance system. The ADAS-ECU 22A is connected to a vehicle speed sensor 24A, a yaw rate sensor 24B, and an external sensor 24C that constitute the in-vehicle equipment 24. The external sensor 24C is a group of sensors used to detect the surrounding environment of the vehicle 12. The external sensor 24C includes, for example, a camera that captures images of the surroundings of the vehicle 12, a millimeter wave radar that transmits detection waves and receives reflected waves, and a lidar (Laser Imaging Detection and Ranging) that scans the area ahead of the vehicle 12.

The steering ECU 22B controls the power steering. A steering angle sensor 24D that constitutes the in-vehicle equipment 24 is connected to the steering ECU 22B. The steering angle sensor 24D is a sensor that detects the steering angle of the steering wheel.

The brake ECU 22C controls the brake system of the vehicle 12. The brake actuator 24E, which constitutes the in-vehicle equipment 24, is connected to the brake ECU 22C.

The engine ECU 22D controls the engine of the vehicle 12. The engine ECU 22D is connected to a throttle actuator 24F and sensors 24G that constitute the in-vehicle equipment 24. The sensors 24G include an oil temperature sensor for measuring the temperature of the engine oil, an oil pressure sensor for measuring the oil pressure of the engine oil, and a rotation sensor for detecting the engine speed.

The information system ECU 22E controls the car navigation system, audio, etc. A GPS device 29 constituting the in-vehicle equipment 24 is connected to the information system ECU 22E. The GPS device 29 is a device that measures the current position of the vehicle 12. The GPS device 29 includes an antenna (not shown) that receives signals from GPS satellites. The GPS device 29 may be directly connected to the in-vehicle device 20.

(Center server)
As shown in Fig. 4, the center server 30 includes a CPU 30A, a ROM 30B, a RAM 30C, a storage 30D, and a communication I/F 30E. The CPU 30A, the ROM 30B, the RAM 30C, the storage 30D, and the communication I/F 30E are connected to each other via an internal bus 30G so as to be able to communicate with each other. The functions of the CPU 30A, the ROM 30B, the RAM 30C, and the communication I/F 30E are the same as those of the CPU 20A, the ROM 20B, the RAM 20C, and the wireless communication I/F 20E of the vehicle-mounted device 20 described above. The communication I/F 30E may perform wired communication.

The storage 30D as a memory is configured with a HDD (Hard Disk Drive) or SSD (Solid State Drive) and stores various programs and various data. In this embodiment, the storage 30D stores a processing program 100, a vehicle information DB (database) 110, a map information DB 120, and a judgment information DB 130. Note that the ROM 30B may store the processing program 100, the vehicle information DB 110, the map information DB 120, and the judgment information DB 130.

The processing program 100, which serves as a judgment program, is a program for controlling the center server 30. When the processing program 100 is executed, the center server 30 executes a judgment process to determine whether or not the operation can be predicted in advance.

The vehicle information DB 110 stores vehicle information for each time acquired from the vehicle 12. The vehicle information includes information such as vehicle speed, acceleration, yaw rate, steering angle, accelerator opening, brake pedal force or stroke, etc. The vehicle information also includes captured images of the outside of the vehicle 12 captured by a camera serving as the external sensor 24C, and the current position acquired from the GPS device 29.
The map information DB 120 stores map data for acquiring a driving scene from the vehicle's position. The map data is assigned with a road shape for each position coordinate, and the road shape can be acquired as a driving scene. In this embodiment, as an example, the road shapes are assigned with "flat roads,""curvedroads," and "mountain roads."
The determination information DB 130 stores driving scene levels set according to the shape of the road and vehicle speed standards for each driving scene level. The vehicle speed standards include a first standard (a standard value for the maximum vehicle speed) and a second standard (a standard value for the time during which the vehicle speed is maintained within a predetermined speed from the maximum vehicle speed) for each driving scene level.

As shown in FIG. 5, in the center server 30 of this embodiment, the CPU 30A executes the processing program 100 to function as an acquisition unit 200, a scene processing unit 202, a determination unit 204, and an output unit 206.

The acquisition unit 200 has a function of acquiring vehicle information of the vehicle 12 from the vehicle-mounted device 20 of the vehicle 12. The acquisition unit 200 acquires vehicle information transmitted from the vehicle-mounted device 20 at any timing, and stores it in the vehicle information DB 110. The acquisition unit 200 also has a function of accepting a vehicle operation judgment request from the terminal 40. The judgment request includes time information at which the vehicle operation judgment is to be made, and the center server 30 judges the vehicle operation at the time of the time information.

The scene processing unit 202 receives a judgment request as an input. The scene processing unit 202 acquires the position of the vehicle information in the vehicle information DB at the time of the judgment request and the map data in the map information DB 120. The scene processing unit 202 compares the position of the vehicle 12 included in the acquired vehicle information with the shape of the road included in the map data to acquire the level of the driving scene at the position where the vehicle 12 was traveling. Note that the process of acquiring the driving scene by the scene processing unit 202 is not limited to the example of acquiring the driving scene using the position of the vehicle information and the map data, and may be appropriately modified in design. For example, the driving scene may be acquired by analyzing the shape of the road from the captured image included in the vehicle information, or the driving scene may be acquired by analyzing the shape of the road from the detection result of the surrounding environment by the external sensor 24C of the vehicle 12.

The determination unit 204 accepts the input of the driving scene acquired by the scene processing unit 202. The determination unit 204 acquires the vehicle speed of the vehicle information in the vehicle information DB for a certain time interval with respect to the time of the judgment request. In addition, the determination unit 204 acquires the vehicle speed criteria (first criterion and second criterion) corresponding to the level of the driving scene from the judgment information DB 130 for the received driving scene. The determination unit 204 uses the vehicle speed criteria to determine whether the driver of the vehicle 12 is performing a driving operation that can be predicted. Specifically, the determination unit 204 determines whether the vehicle speed satisfies the first criterion and the second criterion, respectively. The determination unit 204 uses the first criterion to determine whether the vehicle speed of the vehicle 12 in the driving scene has reached the reference value of the maximum vehicle speed set in the first criterion. If the first criterion is satisfied, the determination unit 204 uses the second criterion to determine whether the time during which the vehicle speed of the vehicle 12 was maintained within a predetermined speed of the maximum vehicle speed was a certain time or more. If the second criterion is met, the determination unit 204 determines that the driver of the vehicle 12 is performing a predictable driving operation in the driving scene. The output unit 206 transmits the determination result of the determination unit 204 to the terminal 40.

(Flow of Control)
A process flow as a control method executed in the vehicle control system 10 of this embodiment will be described with reference to the sequence diagram of Fig. 6 and the flowchart of Fig. 7. The process in the center server 30 is executed by the CPU 30A functioning as each part of the center server 30.

In step S10 in FIG. 6, the CPU 20A in the vehicle-mounted device 20 transmits vehicle information to the center server 30. The vehicle information is transmitted at any timing, such as when the ignition in the vehicle 12 is turned ON or OFF, or when a command requesting the transmission of vehicle information is received from the center server 30.

In step S11, the terminal 40 transmits a judgment request to the center server 30. Note that the processes of steps S10 and S11 are not essential processes, and may be executed in advance and the process may start from step S12. Also, if the process of accepting the transmission of the judgment request at the center server 30 is executed in advance, multiple times to be subject to the judgment process may be determined in advance, and the judgment process may be periodically performed for the multiple times to obtain the judgment result of the driving operation.

In step S12, the CPU 30A of the center server 30 executes a determination process. Details of the determination process will be described later.

In step S13, the CPU 30A of the center server 30 transmits the determination result to the terminal 40.

Next, the determination process in step S12 will be described in detail.
In step S100 in FIG. 7, CPU 30A obtains the position of the vehicle information from vehicle information DB 110 and map data from map information DB 120 at the time of the determination request obtained in step S12.

In step S101, the CPU 30A compares the position of the vehicle 12 contained in the acquired vehicle information with the shape of the road contained in the map data to acquire the driving scene of the position where the vehicle 12 was traveling. The driving scene is acquired as level 1 if the shape of the road is a "flat road", as level 2 if the shape of the road is a "curving road", and as level 3 if the shape of the road is a "mountain road".

In step S102, CPU 30A acquires the vehicle speed from the vehicle information DB for a certain time interval with respect to the time of the judgment request. For example, if the time of the judgment request requests that the judgment be made around "14:05", the vehicle speed may be acquired for a certain time interval including the time of the judgment request, such as "14:04:00 to 14:06:00". Note that the acquired time interval may be changed depending on the driving scene acquired in step S101.

In step S103, the CPU 30A obtains vehicle speed criteria (first and second criteria) corresponding to the level of the driving scene obtained in step S101 from the judgment information DB 130.

In step S104, the CPU 30A uses the first criterion to determine whether or not the vehicle speed of the vehicle 12 in the driving scene has reached the reference value of the maximum vehicle speed set in the first criterion. If it is determined that the vehicle speed has reached the reference value of the maximum vehicle speed, the process proceeds to step S105, and if it is determined that the vehicle speed has not reached the reference value, the process proceeds to step S107.

In step S105, the CPU 30A uses the second criterion to determine whether the time during which the vehicle speed of the vehicle 12 was maintained within a predetermined maximum vehicle speed was equal to or longer than a certain time. If it is determined that the time was equal to or longer than the certain time, the process proceeds to step S106, and if it is determined that the time was not equal to or longer than the certain time, the process proceeds to step S107.

In step S106, the CPU 30A determines that the driver of the vehicle 12 in the driving scene is performing a driving operation that can be predicted. In this manner, it is determined that the driver is performing a driving operation that can be predicted when the first and second criteria are satisfied.

In step S107, CPU 30A determines that the driver of vehicle 12 in the driving scene did not perform a driving operation that could be predicted by the driver of vehicle 12.

(summary)
The center server 30 as the determination device of this embodiment uses the first criterion to determine whether or not the vehicle speed of the vehicle 12 reaches the reference value of the maximum vehicle speed set in the first criterion for the driving scene. If the maximum vehicle speed is reached, the center server 30 uses the second criterion to determine whether or not the time during which the vehicle speed of the vehicle 12 is maintained within a predetermined speed of the maximum vehicle speed is equal to or longer than a certain time. In this way, the driving operation situation of the driver can be grasped from the transition of the vehicle speed, such as the vehicle speed and the time the vehicle speed is maintained. In other words, it can be determined from the transition of the vehicle speed whether the driver is performing a driving operation that can be predicted.

In addition, in the center server 30 of this embodiment, by setting a reference value for vehicle speed for each driving scene level, it is possible to determine whether the driver is performing driving operations that allow for predicting the future depending on the driving scene. In addition, by setting a reference value depending on the flatness of the road, appropriate standards can be set.

[Modification]
In the above embodiment, the case where the vehicle speed transition is used for the determination is described as an example, but the present invention is not limited thereto, and the user state may be further considered to determine whether the driving operation is predictable. As shown in FIG. 8, in the center server 30 of the modified example, the CPU 30A executes the processing program 100 to function as an acquisition unit 200, a user state identification unit 300, a scene processing unit 202, a determination unit 204, and an output unit 206. In addition, a sensor or a camera for monitoring the user who is the driver is installed in the in-vehicle device 24 of the vehicle 12, and user monitoring information is transmitted to the center server 30. The user monitoring information is, for example, an image capturing an area including the upper half of the user's body, information on the movement of the user's line of sight, and the like.

The user state identification unit 300 identifies the user state of the driver from the received user monitoring information. The user state is, for example, the user's wakefulness state, and whether the user is wakeful is identified using known technology. It is assumed that the judgment information DB 130 stores user criteria for judging the user state. The user criteria is a criterion for judging whether the user is wakeful or not, and an index is defined for judging whether the wakefulness state is a certain level or above as wakeful, and whether the wakefulness state is below a certain level as not wakeful. The judgment unit 204 uses the user state and the user criteria to judge whether the user state meets the user criteria, i.e., whether the user is wakeful or not.

FIG. 9 shows a sequence in the modified example, and FIG. 10 shows a flowchart in the modified example.
As shown in FIG. 9, in the modified example, after step S10, the CPU 20A of the vehicle-mounted device 20 transmits the user monitoring information to the center server 30 in step S20.
As shown in FIG. 10, in the modified example, step S200 is executed before step S100 (note that steps S200 to S202 may be executed after step S105).
In step S200, CPU 30A identifies the user state (awake state) of the user who is the driver from the received user monitoring information.
In step S201, CPU 30A acquires a user criterion from determination information DB 130.
In step S202, the CPU 30A uses the user state and the user criterion to determine whether or not the user state satisfies the user criterion. If it is determined that the user criterion is satisfied, the process proceeds to step S100. If it is determined that the user criterion is not satisfied, the process proceeds to step S107. By making the determination using the user state in this manner, the determination process can be performed more reliably, taking into account not only the vehicle speed but also the user state.

In addition, when the user state is used, other modified examples can be assumed. For example, when identifying an awakening state as the user state, it is possible to determine whether the user is stagnant or not from the awakening state. Therefore, in the determination unit 204, when the user state is stagnant, the reference value of the maintenance time of the second criterion may be updated to be longer. This is because when the user state is stagnant, drowsiness occurs and there is a possibility that a driving operation that can be predicted is not performed. In this way, the determination process can be performed taking into consideration the degree of awakening of the user. In addition to awakening and stagnation due to the awakening state, an index of a user state that causes driving problems such as an excited state may be used as the user state. In addition, the first criterion and the second reference value may be weighted based on the degree of awakening of the user state.
The above is a modified example that takes the user state into consideration.

In addition, since it is considered that the degree of drivability changes depending on the weather during driving, a modified example may be used in which the reference value is corrected according to the weather in the driving scene. For example, in bad weather with rain, it is assumed that the vehicle speed will be slow and the maintenance time will be shortened. Therefore, in bad weather, the reference value of the maximum vehicle speed set for each level of the driving scene may be lowered and the maintenance time may be shortened. Conversely, in good weather, the reference value of the maximum vehicle speed may be raised and the maintenance time may be lengthened. By taking the weather into consideration in this way, the judgment process can be performed using appropriate criteria according to the environment.

In the above embodiment, the various processes executed by CPU 20A and CPU 30A by reading software (programs) may be executed by various processors other than the CPU. Examples of processors in this case include PLDs (Programmable Logic Devices) such as FPGAs (Field-Programmable Gate Arrays) whose circuit configuration can be changed after manufacture, and dedicated electrical circuits such as ASICs (Application Specific Integrated Circuits) that are processors with circuit configurations designed specifically to execute specific processes. The above-mentioned processes may be executed by one of these various processors, or by a combination of two or more processors of the same or different types (e.g., multiple FPGAs, a combination of a CPU and an FPGA, etc.). The hardware structure of these various processors is, more specifically, an electrical circuit that combines circuit elements such as semiconductor elements.

In the above embodiment, each program has been described as being pre-stored (installed) in a non-transitory computer-readable recording medium. For example, the control program 50 in the vehicle-mounted device 20 is pre-stored in ROM 20B, and the processing program 100 in the center server 30 is pre-stored in storage 30D. However, this is not limiting, and each program may be provided in a form recorded on a non-transitory recording medium such as a CD-ROM (Compact Disc Read Only Memory), a DVD-ROM (Digital Versatile Disc Read Only Memory), or a USB (Universal Serial Bus) memory. The program may also be downloaded from an external device via a network.

The process flow described in the above embodiment is an example, and unnecessary steps may be deleted, new steps may be added, or the process order may be rearranged, without departing from the spirit of the invention.

10 Vehicle control system 12 Vehicle 30 Center server (determination device)
30A CPU (processor)
100 Processing program (judgment program)

Claims (7)

a scene processing unit that acquires a vehicle driving scene having a level that is preset according to a road ;
a reference value for a maximum vehicle speed and a reference value for a time during which the vehicle speed is maintained within a predetermined speed range of the maximum vehicle speed are set for each level of the driving scene as the predetermined criteria for the driving scene,
a determination unit which determines, for the acquired driving scene , whether or not the vehicle speed of the vehicle has reached a reference value of a maximum vehicle speed, and if the reference value of the maximum vehicle speed has been reached, determines whether or not a time during which the vehicle has maintained a speed within a predetermined maximum vehicle speed is equal to or longer than a certain time and satisfies the reference value of the maintained time, and determines that the vehicle is performing a predictable driving operation if the reference value of the maintained time is satisfied;
A determination device comprising: 2. The determination device according to claim 1, wherein the level of the driving scene is set according to the shape of the road, and the flatter the road shape is, the higher the reference value of the reference maximum vehicle speed and the longer the reference value of the maintained time are set. The criteria include a criterion regarding a user state of a user who drives the vehicle,
3 . The determination device according to claim 1 , wherein the determination unit acquires a user state of a user driving the vehicle, and determines that the driving operation is a predictable driving operation when the user state and the vehicle speed satisfy the criteria. 4 . The determination device according to claim 3 , wherein when the user state is stagnant, the determination device updates the reference value of the maintained time of the criterion so as to be longer, according to the user state. 5. The determination device according to claim 1, wherein when the weather in the driving scene is bad, the reference value of the criterion is corrected so as to reduce the maximum vehicle speed and to shorten the maintained time. Acquire a vehicle driving scene having a level that is preset according to a road ;
a reference value for a maximum vehicle speed and a reference value for a time during which the vehicle speed is maintained within a predetermined speed range of the maximum vehicle speed are set for each level of the driving scene as the predetermined criteria for the driving scene,
For the acquired driving scene, a determination is made as to whether the vehicle speed of the vehicle has reached a reference value of the maximum vehicle speed, and if the reference value of the maximum vehicle speed has been reached, a determination is made as to whether the time during which the vehicle has maintained a speed within a predetermined maximum vehicle speed is equal to or longer than a certain time and satisfies the reference value of the maintained time , and if the reference value of the maintained time is satisfied, it is determined that the vehicle is performing a driving operation that can be predicted.
A method for determining whether a process is to be performed by a computer. Acquire a vehicle driving scene having a level that is preset according to a road ;
a reference value for a maximum vehicle speed and a reference value for a time during which the vehicle speed is maintained within a predetermined speed range of the maximum vehicle speed are set for each level of the driving scene as the predetermined criteria for the driving scene,
For the acquired driving scene, a determination is made as to whether the vehicle speed of the vehicle has reached a reference value of the maximum vehicle speed, and if the reference value of the maximum vehicle speed has been reached, a determination is made as to whether the time during which the vehicle has maintained a speed within a predetermined maximum vehicle speed is equal to or longer than a certain time and satisfies the reference value of the maintained time , and if the reference value of the maintained time is satisfied, it is determined that the vehicle is performing a driving operation that can be predicted.
A judgment program that causes a computer to execute a process.