JP7707687B2 - Driving Support Devices - Google Patents

Description

This disclosure relates to a driving assistance device that assists in driving a vehicle.

For example, processing of information related to vehicle travel includes processing of location information where the vehicle exhibits unstable behavior. There are various types of causes for this unstable vehicle behavior. For this reason, for example, Patent Document 1 describes storing in a database in association with unstable behavior information at the behavior occurrence location where the vehicle exhibited unstable behavior, a determination result as to whether or not the unstable behavior was caused by the driver.

JP 2020-052607 A

It is conceivable that location information of unstable behavior could be obtained from a vehicle and collected in a server database, and vehicle assistance content for supporting proper driving of the vehicle could be provided to other vehicles (vehicle groups). However, when a vehicle obtains multiple vehicle assistance content, for example, depending on the type of vehicle assistance content, the information may easily lose its freshness, and such vehicle assistance content may not be able to provide proper driving assistance.

For this reason, in this technical field, when multiple vehicle assistance contents are acquired, there is a need to appropriately set the priority of the vehicle assistance contents and provide driving assistance.

One aspect of the present disclosure is a driving assistance device that acquires vehicle assistance contents associated with a mesh range of a map mesh set to include a predetermined number of positions requiring assistance and a remaining time for assistance at the positions requiring assistance from a server, and performs driving assistance for a vehicle based on the acquired vehicle assistance contents, and includes an assistance content acquisition unit that acquires the vehicle assistance contents from the server, a priority setting unit that sets an execution priority for the acquired vehicle assistance contents, and an assistance execution unit that determines the vehicle assistance contents to be executed based on the priority of the set vehicle assistance contents, and executes driving assistance for the vehicle based on the determined vehicle assistance contents, and when multiple vehicle assistance contents are acquired, the priority setting unit sets a priority for each of the vehicle assistance contents based on the mesh range and remaining time associated with the vehicle assistance contents.

According to the present disclosure, when multiple vehicle assistance contents are acquired, driving assistance can be provided by appropriately setting the priority of the vehicle assistance contents.

FIG. 2 is a diagram illustrating an information processing server and a target vehicle according to the embodiment. FIG. 1 is a diagram illustrating an example of information processing. FIG. 2 is a block diagram showing an example of a configuration of a target vehicle. FIG. 2 is a block diagram showing an example of a configuration of an information processing server. 1A is a diagram for explaining an example of a continuous occurrence state, and FIG. 1B is a diagram for explaining an example of a non-continuous occurrence state. 1A is a table for explaining an example of scene classification of unstable behavior, and FIG. 1B is a diagram for explaining an example of scene classification of unstable behavior. FIG. 1 is a diagram illustrating an example of a mesh. FIG. 13 is a diagram showing an example of a mesh set on a map. FIG. 13 is a diagram for explaining the number of occurrences of unstable behavior positions within a mesh. FIG. 13 is a diagram for explaining enlargement of a mesh. 2 is a block diagram showing an example of a configuration of an automatic driving control unit that performs driving assistance. FIG. 11 is a table showing the priority of driving assistance contents based on remaining time and mesh range. 4 is a flowchart showing the flow of a driving assistance method performed by an autonomous driving control unit.

Embodiments of the present invention will be described below with reference to the drawings. Note that in each drawing, identical or corresponding elements are given the same reference numerals, and duplicated explanations will be omitted.

Figure 1 is a diagram showing an information processing server (server) 10 and a target vehicle (vehicle) 2 according to an embodiment. As shown in Figure 1, the information processing server 10 is communicably connected to target vehicles 2 (2A to 2Z) via a network N. The network N is a wireless communication network. The target vehicles 2 refer to vehicles that are targets of information collection by the information processing server 10. The target vehicles 2 include vehicles that are targets of support for which various types of support are provided by the information processing server 10. When describing the target vehicles 2 individually, the target vehicles 2A to 2Z are used.

Figure 2 is a diagram for explaining an example of information processing. As shown in Figure 2, when a slip occurs in the target vehicle 2A due to a frozen road surface or the like, the target vehicle 2A transmits target vehicle data including an unstable behavior position (assistance required position) D, which is the position where the slip occurred, to the information processing server 10. The information processing server 10 notifies, for example, a target vehicle 2B traveling behind the target vehicle 2A of information on the unstable behavior position as vehicle assistance content. This enables the target vehicle 2B to suppress the occurrence of slip of the target vehicle 2B at the unstable behavior position D. The vehicle assistance content and the unstable behavior position will be described in detail later.

<Applicable vehicle configuration>
First, the configuration of the target vehicle 2 will be described. The target vehicle 2 is assigned an ID (vehicle identification number) for identifying the vehicle. The target vehicle 2 may be one, two or more, several tens or more, or several hundred or more. The target vehicles 2 do not need to be vehicles having the same configuration, and may be of different models. The target vehicle 2 may be an autonomous vehicle having an autonomous driving function, or may be a vehicle without an autonomous driving function.

The target vehicle 2 will be described below with reference to FIG. 3. FIG. 3 is a block diagram showing an example of the configuration of the target vehicle 2. Here, the target vehicle 2 will be described as an autonomous vehicle.

As shown in FIG. 3, the target vehicle 2 is equipped with an autonomous driving ECU 30. The autonomous driving ECU 30 is an electronic control unit having a CPU, ROM, RAM, etc. In the autonomous driving ECU 30, for example, a program stored in the ROM is loaded into the RAM, and the program loaded into the RAM is executed by the CPU to realize various functions. The autonomous driving ECU 30 may be composed of multiple electronic units.

The autonomous driving ECU 30 is connected to a GPS [Global Positioning System] receiver 21, an external sensor 22, an internal sensor 23, a driving operation detector 24, a map database 25, a communication unit 26, an HMI [Human Machine Interface] 27, and an actuator 28.

The GPS receiver 21 measures the position of the target vehicle 2 (e.g., the latitude and longitude of the target vehicle 2) by receiving signals from three or more GPS satellites. The GPS receiver 21 transmits the measured position information of the target vehicle 2 to the autonomous driving ECU 30.

The external sensor 22 is a detection device that detects the external environment of the target vehicle 2. The external sensor 22 includes at least one of a camera and a radar sensor.

The camera is an imaging device that captures images of the external environment of the target vehicle 2. The camera is provided behind the windshield of the target vehicle 2 and captures images of the area in front of the vehicle. The camera transmits imaging information related to the external environment of the target vehicle 2 to the autonomous driving ECU 30. The camera may be a monocular camera or a stereo camera.

The radar sensor is a detection device that detects objects around the target vehicle 2 using radio waves (e.g., millimeter waves) or light. Radar sensors include, for example, millimeter wave radar or LIDAR (Light Detection and Ranging). The radar sensor detects objects by transmitting radio waves or light to the vicinity of the target vehicle 2 and receiving the radio waves or light reflected by the objects. The radar sensor transmits information about the detected objects to the autonomous driving ECU 30. Objects include fixed objects such as guardrails and buildings, as well as moving objects such as pedestrians, bicycles, and other vehicles. The external sensor 22 may include an outside air temperature sensor that detects the outside air temperature of the target vehicle 2. The external sensor 22 may include a light sensor that detects the brightness of the outside.

The internal sensor 23 is a detection device that detects the state of the target vehicle 2. The internal sensor 23 includes a vehicle speed sensor, an acceleration sensor, and a yaw rate sensor as sensors that detect the driving state of the target vehicle 2. The vehicle speed sensor is a detector that detects the speed of the target vehicle 2. As the vehicle speed sensor, a wheel speed sensor that is provided on the wheels of the target vehicle 2 or on a drive shaft that rotates integrally with the wheels and detects the rotational speed of each wheel can be used. The vehicle speed sensor transmits the detected vehicle speed information (wheel speed information) to the autonomous driving ECU 30.

The acceleration sensor is a detector that detects the acceleration of the target vehicle 2. The acceleration sensor includes, for example, a longitudinal acceleration sensor that detects the longitudinal acceleration of the target vehicle 2. The acceleration sensor may include a lateral acceleration sensor that detects the lateral acceleration of the target vehicle 2. The acceleration sensor transmits, for example, acceleration information of the target vehicle 2 to the autonomous driving ECU 30. The yaw rate sensor is a detector that detects the yaw rate (rotational angular velocity) around the vertical axis of the center of gravity of the target vehicle 2. A gyro sensor, for example, can be used as the yaw rate sensor. The yaw rate sensor transmits the detected yaw rate information of the target vehicle 2 to the autonomous driving ECU 30.

The internal sensor 23 detects at least one of the tire pressure, wiper operation status, and lighting status as the vehicle status of the target vehicle 2. The tire pressure is the air pressure of the tires of the target vehicle 2. The wiper operation status may include not only whether the wipers are operating, but also the wiper operation speed. The lighting status includes the lighting status of the turn signal. The lighting status may include whether the headlights are on or off, and whether the fog lights are on or off.

The internal sensor 23 may also detect the brake pressure of a hydraulic brake system from a brake pressure sensor as the vehicle state of the target vehicle 2, and may detect the on/off state of a driving assistance system (for example, a vehicle stability control system described below). The internal sensor 23 may also detect the load state of each wheel from a wheel load sensor as the vehicle state of the target vehicle 2. Additionally, the internal sensor 23 may have a fault detection unit that detects various faults in the target vehicle 2.

The driving operation detection unit 24 detects the operation of the operation unit of the target vehicle 2 by the driver. The driving operation detection unit 24 includes, for example, a steering sensor, an accelerator sensor, and a brake sensor. The operation unit of the target vehicle 2 is a device into which the driver inputs operations for driving the vehicle. The operation unit of the target vehicle 2 includes at least one of the steering unit, the accelerator operation unit, and the brake operation unit. The steering unit is, for example, a steering wheel. The steering unit is not limited to being wheel-shaped, and may be configured to function as a handle. The accelerator operation unit is, for example, an accelerator pedal. The brake operation unit is, for example, a brake pedal. The accelerator operation unit and the brake operation unit do not necessarily have to be pedals, and may be configured to allow the driver to input acceleration or deceleration. The operation unit may be an in-vehicle switch. The driver's information terminal, such as a smartphone, may function as the operation unit.

The steering sensor detects the amount of operation of the steering unit by the driver. The amount of operation of the steering unit includes the steering angle. The amount of operation of the steering unit may include the steering torque. The accelerator sensor detects the amount of operation of the accelerator operation unit by the driver. The amount of operation of the accelerator operation unit includes, for example, the amount of depression of the accelerator pedal. The brake sensor detects the amount of operation of the brake operation unit by the driver. The amount of operation of the brake operation unit includes, for example, the amount of depression of the brake pedal. The brake sensor may be configured to detect the master cylinder pressure of the hydraulic brake system. The amount of operation of the accelerator operation unit and the brake operation unit may include the depression speed. The driving operation detection unit 24 transmits operation amount information regarding the detected amount of operation by the driver to the autonomous driving ECU 30.

The map database 25 is a database that stores map information. The map database 25 is formed, for example, in a storage device such as an HDD mounted on the target vehicle 2. The map information includes road position information, road shape information (e.g., curvature information), intersection and branch point position information, and the like. The map information may include traffic regulation information such as legal speed limits associated with the position information. The map information may include landmark information used to recognize the position of the target vehicle 2 on the map. The landmarks may include lane markings, traffic lights, guard rails, road markings, and the like. The map database 25 may be configured in a server (not limited to the information processing server 10) that can communicate with the target vehicle 2.

The communication unit 26 is a communication device that controls wireless communication with the outside of the target vehicle 2. It transmits and receives various information via the network N. The communication unit 26 transmits various information to the information processing server 10 in response to a signal from the autonomous driving ECU 30.

The HMI 27 is an interface for inputting and outputting information between the autonomous driving ECU 30 and the driver or passengers. The HMI 27 is equipped with, for example, a display, a speaker, etc., provided in the vehicle cabin. The HMI 27 outputs images from the display and sounds from the speaker in response to control signals from the autonomous driving ECU 30.

The actuators 28 are devices used to control the target vehicle 2. The actuators 28 include at least a drive actuator, a brake actuator, and a steering actuator. The drive actuator controls the amount of air supplied to the engine (throttle opening) in response to a control signal from the automatic driving ECU 30, thereby controlling the driving force of the target vehicle 2. If the target vehicle 2 is a hybrid vehicle, in addition to the amount of air supplied to the engine, a control signal from the automatic driving ECU 30 is input to a motor serving as a power source to control the driving force. If the target vehicle 2 is an electric vehicle, a control signal from the automatic driving ECU 30 is input to a motor serving as a power source to control the driving force. The motor serving as a power source in these cases constitutes the actuator 28.

The brake actuator controls the brake system in response to a control signal from the autonomous driving ECU 30, and controls the braking force applied to the wheels of the target vehicle 2. For example, a hydraulic brake system can be used as the brake system. The steering actuator controls the drive of the assist motor, which controls the steering torque of the electric power steering system, in response to a control signal from the autonomous driving ECU 30. In this way, the steering actuator controls the steering torque of the target vehicle 2.

Next, the functional configuration of the autonomous driving ECU 30 will be described. As shown in FIG. 3, the autonomous driving ECU 30 has a target vehicle data acquisition unit 31, a route generation unit 32, and an autonomous driving control unit (driving assistance device) 33. Note that some of the functions of the autonomous driving ECU 30 described below may be executed in a server (not limited to the information processing server 10) capable of communicating with the target vehicle 2.

The target vehicle data acquisition unit 31 acquires target vehicle data, which is data related to the target vehicle 2. The target vehicle data includes position information of the target vehicle 2 on a map and the driving state of the target vehicle 2. The target vehicle data may include the external environment of the target vehicle 2, and may include the route along which the target vehicle 2 is driven. The target vehicle data may include driving operation information by the driver of the target vehicle 2 and the vehicle state of the target vehicle 2. The target vehicle data acquisition unit 31 transmits the acquired target vehicle data to the information processing server 10.

The target vehicle data acquisition unit 31 has a vehicle position acquisition unit 31a, an external environment recognition unit 31b, a driving state recognition unit 31c, a driving operation information acquisition unit 31d, and a vehicle state recognition unit 31e.

The vehicle position acquisition unit 31a acquires the position information of the target vehicle 2 on the map based on the position information of the GPS receiver unit 21 and the map information of the map database 25. The vehicle position acquisition unit 31a may also acquire the position information of the target vehicle 2 by SLAM [Simultaneous Localization and Mapping] technology using the target information included in the map information of the map database 25 and the detection results of the external sensor 22. The vehicle position acquisition unit 31a may recognize the lateral position of the target vehicle 2 relative to the lane (the position of the target vehicle 2 in the lane width direction) from the positional relationship between the lane markings and the target vehicle 2, and include it in the position information. The vehicle position acquisition unit 31a may also acquire the position information of the target vehicle 2 on the map by other well-known methods.

The external environment recognition unit 31b recognizes the external environment of the target vehicle 2 based on the detection results of the external sensor 22. The external environment includes the relative positions of surrounding objects with respect to the target vehicle 2. The external environment may include the relative speed and movement direction of surrounding objects with respect to the target vehicle 2. The external environment may include types of objects such as other vehicles, pedestrians, and bicycles. The types of objects can be identified by well-known techniques such as pattern matching. The external environment may include the results of lane marking recognition (white line recognition) around the target vehicle 2. The external environment may include the outside temperature and weather.

The driving state recognition unit 31c recognizes the driving state of the target vehicle 2 based on the detection result of the internal sensor 23. The driving state includes the vehicle speed and yaw rate of the target vehicle 2. The driving state may include the acceleration of the target vehicle 2. Specifically, the driving state recognition unit 31c recognizes the vehicle speed of the target vehicle 2 based on vehicle speed information from a vehicle speed sensor. The driving state recognition unit 31c recognizes the acceleration of the target vehicle 2 based on vehicle speed information from an acceleration sensor. The driving state recognition unit 31c recognizes the orientation of the target vehicle 2 based on yaw rate information from a yaw rate sensor.

The driving operation information acquisition unit 31d acquires driving operation information of the target vehicle 2 based on the detection result of the driving operation detection unit 24. The driving operation information includes, for example, at least one of the driver's accelerator operation amount, brake operation amount, and steering amount.

If the target vehicle 2 has a personal authentication function, the driving operation information acquisition unit 31d stores the driving operation history for each personally authenticated driver. The driving operation history may be associated with the external environment and driving state of the target vehicle 2. The autonomous driving ECU 30 does not necessarily need to have the driving operation information acquisition unit 31d. In this case, the driving operation detection unit 24 is also not required.

The vehicle state recognition unit 31e recognizes the vehicle state of the target vehicle 2 based on the detection results of the internal sensor 23. The vehicle state may include tire pressure. The vehicle state may include a wiper operation state, a lighting state, and a failure state of the target vehicle 2. The autonomous driving ECU 30 does not necessarily need to have the vehicle state recognition unit 31e.

The trajectory generation unit 32 generates a trajectory to be used for the autonomous driving of the target vehicle 2. The trajectory generation unit 32 generates a trajectory for autonomous driving based on a preset driving route, map information, the position of the target vehicle 2 on the map, the external environment of the target vehicle 2, and the driving state of the target vehicle 2.

The driving route is the route along which the target vehicle 2 travels during autonomous driving. The course generation unit 32 determines the driving route for autonomous driving based on, for example, the destination, map information, and the position of the target vehicle 2 on the map. The driving route may be set by a well-known navigation system. The destination may be set by an occupant of the target vehicle 2, or may be automatically proposed by the autonomous driving ECU 30 or a navigation system, etc.

The course includes the path along which the vehicle travels in autonomous driving and the vehicle speed profile during autonomous driving. The route is the planned trajectory along which the vehicle is traveling in autonomous driving on the travel route. The route can be, for example, data on the change in steering angle of the target vehicle 2 according to the position on the travel route (steering angle profile). The position on the travel route is, for example, a set vertical position set at a predetermined interval (for example, 1 m) in the direction of travel of the travel route. The steering angle profile is data in which a target steering angle is associated with each set vertical position.

The path generation unit 32 generates a path for the vehicle to travel based on, for example, the travel route, map information, the external environment of the target vehicle 2, and the travel state of the target vehicle 2. For example, the path generation unit 32 generates a path so that the target vehicle 2 passes through the center (center in the lane width direction) of the lane included in the travel route.

In place of the steering angle profile, a steering torque profile in which a target steering torque is associated with each set longitudinal position may be used. Also, in place of the steering angle profile, a lateral position profile in which a target lateral position is associated with each set longitudinal position may be used. The target lateral position is a target position in the width direction of the lane. In this case, the set longitudinal position and the target lateral position may be set together as a single position coordinate.

The vehicle speed profile is data in which a target vehicle speed is associated with each set vertical position, for example. The set vertical position may be set based on the vehicle's travel time rather than distance. The set vertical position may be set as the position the vehicle will reach in 1 second, or the position the vehicle will reach in 2 seconds.

The route generation unit 32 generates a vehicle speed profile based on speed-related information, such as the legal speed included in the route and map information. Instead of the legal speed, a preset speed for a position or section on the map may be used. The route generation unit 32 generates a route for automated driving from the route and the vehicle speed profile. Note that the route generation method in the route generation unit 32 is not limited to the above-mentioned method, and other well-known methods may be adopted.

The automatic driving control unit 33 executes automatic driving of the target vehicle 2. The automatic driving control unit 33 executes automatic driving of the target vehicle 2 based on, for example, the external environment of the target vehicle 2, the driving state of the target vehicle 2, and the route generated by the route generation unit 32. The automatic driving control unit 33 executes automatic driving of the target vehicle 2 by sending a control signal to the actuator 28.

In addition, when the autonomous driving control unit 33 acquires vehicle assistance content from the information processing server 10, it performs driving assistance for the target vehicle 2 based on the acquired vehicle assistance content. The driving assistance for the target vehicle 2 based on the vehicle assistance content performed by the autonomous driving control unit 33 will be described in detail later.

Configuration of the Information Processing Server
The information processing server 10 is provided in a facility such as an information management center, and is configured to be able to communicate with the target vehicle 2. Fig. 4 is a block diagram showing an example of the configuration of the information processing server 10. The information processing server 10 shown in Fig. 4 is configured as a general computer including a processor 11, a storage unit 12, a communication unit 13, and a user interface 14.

The processor 11, for example, operates an operating system to control the information processing server 10. The processor 11 is an arithmetic unit such as a CPU [Central Processing Unit] that includes a control device, an arithmetic device, a register, etc. The processor 11 controls the memory unit 12, the communication unit 13, and the user interface 14. The memory unit 12 is configured to include at least one of a memory and a storage. The memory is a recording medium such as a ROM [Read Only Memory] or a RAM [Random Access Memory]. The storage is a recording medium such as a HDD [Hard Disk Drive]. The memory unit 12 may be integrated with a memory database 16 described later.

The communication unit 13 is a communication device for communicating via the network N. A network device, a network controller, a network card, etc. may be used as the communication unit 13. The user interface 14 is a device including an output device such as a display and a speaker, and an input device such as a touch panel. Note that the information processing server 10 does not necessarily need to be installed in a facility, and may be mounted on a moving object such as a vehicle or a ship.

The information processing server 10 is also connected to a map database 15 and a memory database 16. The map database 15 is a database that stores map information. The map database 15 also stores information on meshes (map meshes) that are set in advance on a map. Meshes will be described in detail later. The memory database 16 is a database for storing unstable behavior position information and the like. The memory database 16 can be configured in the same manner as a well-known database in a HDD. The memory database 16 may be provided in a facility away from the information processing server 10. The map database 15 and the memory database 16 may be integrated.

Next, the functional configuration of the processor 11 will be described. As shown in FIG. 4, the processor 11 has a target vehicle data recognition unit 11a, an unstable behavior position recognition unit 11b, a situation determination unit 11c, a driving data acquisition unit 11d, an occurrence count unit 11e, a mesh expansion unit 11f, a recurrence frequency measurement unit 11g, a remaining time setting unit 11h, a memory processing unit 11j, and a vehicle assistance unit 11k.

The target vehicle data recognition unit 11a recognizes the target vehicle data transmitted from the target vehicle 2. The target vehicle data includes the position information of the target vehicle 2 on a map and the driving state of the target vehicle 2. The target vehicle data may include the external environment of the target vehicle 2, and may also include the route on which the target vehicle 2 is driving.

The unstable behavior position recognition unit 11b recognizes an unstable behavior position, which is a position on a map where the target vehicle 2 has become unstable, based on the target vehicle data recognized by the target vehicle data recognition unit 11a. The unstable behavior position recognition unit 11b recognizes the unstable behavior position in association with time. Unstable behavior is vehicle behavior that makes the vehicle's travel unstable. Unstable behavior includes, for example, slipping. Unstable behavior may include sudden deceleration or a sudden change in steering angle. Unstable behavior may include lane departure of the target vehicle 2, or excessive approach of the target vehicle 2 to a structure (such as a guardrail).

First, the determination of unstable behavior will be described. The unstable behavior position recognition unit 11b determines whether the target vehicle 2 has become unstable based on the target vehicle data. The unstable behavior position recognition unit 11b determines that the target vehicle 2 has become slippery, which is an unstable behavior, based on at least one of, for example, the acceleration (longitudinal acceleration and lateral acceleration) detected by the acceleration sensor, the wheel speed of each wheel detected by the wheel speed sensor, the yaw rate detected by the yaw rate sensor, the steering angle of the driver detected by the steering sensor, the amount of braking operation of the driver detected by the brake sensor, and the brake pressure of the brake pressure sensor. The master cylinder pressure of the hydraulic brake system may be used instead of the amount of braking operation of the brake sensor.

The unstable behavior position recognition unit 11b may use the activation conditions of a well-known antilock brake system [ABS: Antilock Brake System] to determine slippage. For example, an antilock brake system compares the wheel speed of each wheel with the estimated vehicle speed and activates when a wheel that is thought to be locked is identified. The estimated vehicle speed may be determined from the wheel speed of each wheel before slippage occurs, or may be determined from the change in acceleration before slippage occurs.

The unstable behavior position recognition unit 11b may use the activation conditions of a well-known vehicle stability control system [VSC: Vehicle Stability Control] or the activation conditions of a well-known traction control system [TRC: Traction Control System] to determine slippage. Traction control may also be activated when a spinning wheel is identified by comparing the wheel speed of each wheel with the estimated vehicle speed. The unstable behavior position recognition unit 11b may determine slippage of the target vehicle 2 using other well-known methods.

The unstable behavior position recognition unit 11b may determine whether the target vehicle 2 has suddenly decelerated as an unstable behavior based on the deceleration detected by the acceleration sensor. In this case, the unstable behavior position recognition unit 11b determines that the target vehicle 2 has suddenly decelerated when, for example, the absolute value of the deceleration becomes equal to or greater than the sudden deceleration threshold. The sudden deceleration threshold is a threshold value that is set in advance. In the following explanation, the threshold value refers to a threshold value that is set in advance.

The unstable behavior position recognition unit 11b may determine whether or not a sudden change in steering angle has occurred in the target vehicle 2 as an unstable behavior based on the yaw rate detected by the yaw rate sensor. In this case, the unstable behavior position recognition unit 11b determines that a sudden change in steering angle has occurred in the target vehicle 2 when, for example, the yaw rate is equal to or greater than a steering angle change threshold. Note that the tire turning angle may be used instead of the yaw rate.

When the turn signal is not on, the unstable behavior position recognition unit 11b may determine whether the target vehicle 2 has deviated from the lane, which is an unstable behavior, based on the lateral position of the target vehicle 2 or the external environment of the target vehicle 2. In this case, the unstable behavior position recognition unit 11b may determine lane departure from the lateral position of the target vehicle 2, for example. Alternatively, the unstable behavior position recognition unit 11b may determine lane departure when it recognizes from the external environment of the target vehicle 2 that the target vehicle 2 has crossed a lane dividing line.

The unstable behavior position recognition unit 11b may determine whether the target vehicle 2 has come too close to an object as an unstable behavior based on the traveling state of the target vehicle 2 and the external environment of the target vehicle 2. In this case, the unstable behavior position recognition unit 11b determines that the target vehicle 2 has come too close to an object when the vehicle speed of the target vehicle 2 is equal to or greater than the vehicle speed threshold and the time to collision [TTC: Time To Collision] between the target vehicle 2 and the object is equal to or less than the TTC threshold, because the behavior is not unstable when the target vehicle 2 is traveling at a low speed even if the distance to the object is small. Instead of the time to collision, the time headway [THW: Time Headway] or distance may be used.

The determination of whether the target vehicle 2 has become unstable may be performed each time the target vehicle data is acquired, or may be performed all at once at regular intervals or for a regular period of time. The determination of whether the target vehicle 2 has become unstable may be performed while the target vehicle 2 is stopped.

Next, the recognition of the unstable behavior position will be described. The unstable behavior position is the position on the map of the target vehicle 2 when the target vehicle 2 becomes unstable. When it is determined that the target vehicle 2 becomes unstable, the unstable behavior position recognition unit 11b recognizes the unstable behavior position.

The unstable behavior position recognition unit 11b recognizes the unstable behavior position based on the position information on the map of the target vehicle 2 when it is determined that the target vehicle 2 has become unstable. The unstable behavior position is recognized separately for each lane. When the unstable behavior is a lane departure, the unstable behavior position may be the position on the driving lane before the lane departure, or may be the position on the dividing line.

The unstable behavior position may be recognized as a section or area, rather than as a point on a map. In a case where the target vehicle 2 slides while slipping, the unstable behavior position recognition unit 11b may determine the start position of the slip as the unstable behavior position, or may recognize all sections through which the target vehicle 2 has moved while being determined to be slipping as unstable behavior positions. The same applies to other unstable behaviors.

The situation determination unit 11c determines whether the unstable behavior position is a continuous occurrence situation or a discontinuous occurrence situation based on the presence or absence of unstable behavior of multiple target vehicles 2 at the unstable behavior position recognized by the unstable behavior position recognition unit 11b.

The situation determination unit 11c determines whether the target vehicle 2 has passed an unstable behavior position, for example, based on the target vehicle data recognized by the target vehicle data recognition unit 11a and the unstable behavior position recognized by the unstable behavior position recognition unit 11b. When the situation determination unit 11c determines that the target vehicle 2 has passed an unstable behavior position, it determines whether the unstable behavior position is in a continuous or discontinuous state based on the presence or absence of unstable behavior of the target vehicle 2. Note that the situation determination unit 11c may perform the above determination by batch processing multiple target vehicle data for a certain period of time.

A continuous occurrence situation is a situation in which unstable behavior occurs continuously. In the case of a continuous occurrence situation, it can be considered that the possibility that unstable behavior has occurred due to individual vehicle factors of the target vehicle 2 is low, and the possibility that unstable behavior has occurred due to external factors such as the road environment is high. A discontinuous situation is a situation that is not a continuous occurrence situation. In the case of a discontinuous situation, it can be considered that the possibility that unstable behavior has occurred due to individual vehicle factors of the target vehicle 2 is high. When the situation determination unit 11c does not determine that the unstable behavior position is a continuous occurrence situation, it determines that the unstable behavior position is a discontinuous situation.

Figure 5(a) is a diagram for explaining an example of a consecutive occurrence situation. As shown in Figure 5(a), as an example, when two target vehicles 2A and 2B exhibit unstable behavior consecutively at unstable behavior position D, the situation determination unit 11c determines that the unstable behavior position is a consecutive occurrence situation. Figure 5(b) is a diagram for explaining an example of a discontinuous situation. As shown in Figure 5(b), even if the target vehicle 2A exhibits unstable behavior at unstable behavior position D, the situation determination unit 11c may determine that the unstable behavior position is a discontinuous situation when the following target vehicle 2B passes by without exhibiting unstable behavior.

The situation determined as a continuous occurrence situation is not limited to the situation in FIG. 5(a). The situation determination unit 11c may determine that the unstable behavior position D is in a continuous occurrence situation when three target vehicles 2A to 2C have exhibited unstable behavior in succession. The situation determination unit 11c may determine that the unstable behavior position D is in a continuous occurrence situation when four or more target vehicles 2 have exhibited unstable behavior in succession. The situation determination unit 11c may determine that the unstable behavior position D is in a continuous occurrence situation when all of the multiple target vehicles 2 that pass through the unstable behavior position D within a certain time period have exhibited unstable behavior.

The situation determination unit 11c may determine that the unstable behavior position D is in a continuous occurrence state even if there is one target vehicle 2 that did not exhibit unstable behavior, if unstable behavior occurs in the target vehicles 2 before and after it. Specifically, the situation determination unit 11c may determine that the unstable behavior position D is in a continuous occurrence state even if the middle target vehicle 2B of the three target vehicles 2A to 2C passes the unstable behavior position D without exhibiting unstable behavior, but if the target vehicle 2A and the target vehicle 2C exhibit unstable behavior. Alternatively, the situation determination unit 11c may determine that the unstable behavior position D is in a continuous occurrence state even if there are multiple target vehicles 2 that did not exhibit unstable behavior, if the number of target vehicles 2 that exhibited unstable behavior within a certain period of time is equal to or greater than a threshold value.

The situation determination unit 11c may determine whether a situation is continuous or non-continuous by further fine-grained classification. Here, FIG. 6(a) is a table for explaining an example of scene classification of unstable behavior. As shown in FIG. 6(a), by focusing on two vehicles, the preceding target vehicle 2 and the following target vehicle 2, with respect to the unstable behavior position, and dividing the scenes into four categories based on whether or not there is unstable behavior, it is possible to perform four scene classifications.

In FIG. 6(a), scene 1 is when both the leading target vehicle 2 and the trailing target vehicle 2 exhibit unstable behavior, scene 2 is when only the leading target vehicle 2 exhibits unstable behavior, scene 3 is when only the trailing target vehicle 2 exhibits unstable behavior, and scene 4 is when neither the leading target vehicle 2 nor the trailing target vehicle 2 exhibits unstable behavior. For example, scene 1 corresponds to a continuous occurrence situation, and scenes 2 to 4 correspond to discontinuous situations.

Figure 6(b) is a diagram for explaining an example of scene classification of unstable behavior. It is assumed that the target vehicles 2A to 2F passed through the same unstable behavior position in this order. In Figure 6(b), of the target vehicles 2A to 2E, only the target vehicles 2B and 2C exhibited unstable behavior, and the remaining vehicles passed through the unstable behavior position without exhibiting unstable behavior.

When attention is focused on two vehicles, target vehicle 2A and target vehicle 2B in FIG. 6(b), this corresponds to scene 3, where only the following target vehicle 2B exhibited unstable behavior. When attention is focused on two vehicles, target vehicle 2B and target vehicle 2C, this corresponds to scene 1, where both the preceding target vehicle 2B and the following target vehicle 2C exhibited unstable behavior. When attention is focused on two vehicles, target vehicle 2C and target vehicle 2D, this corresponds to scene 2, where only the preceding target vehicle 2C exhibited unstable behavior. When attention is focused on two vehicles, target vehicle 2D and target vehicle 2E, this corresponds to scene 4, where neither target vehicle 2 exhibited unstable behavior. In this way, the situation determination unit 11c may make a determination to classify scenes 1 to 4.

The occurrence counting unit 11e counts the number of occurrences of unstable behavior positions within a predetermined period of time within a mesh that is preset on the map, based on the information on the mesh on the map stored in the map database 15 and the unstable behavior positions recognized by the unstable behavior position recognition unit 11b. The occurrence counting unit 11e may count only unstable behavior positions that are determined to be in a continuous occurrence state by the situation determination unit 11c.

A mesh is an area that is preset on a map. A mesh is associated with a mesh position and a mesh range (mesh size). Meshes are used, for example, to collectively manage multiple unstable behavior positions. Management also includes providing appropriate vehicle assistance according to the mesh using the vehicle assistance content (service content) described below. Information about meshes is stored in the map database 15.

Here, FIG. 7 is a diagram showing an example of a mesh. FIG. 7 shows a mesh 50. In FIG. 7, assume that unstable behavior occurs within the mesh 50 as a slip caused by the same road surface freezing. In this case, the position where the slip of the target vehicle 2A occurs (unstable behavior position D) and the position where the slip of the following target vehicle 2B occurs (unstable behavior position D) are not necessarily the same position. It is considered that the unstable behavior position D varies depending on the difference in the vehicle speed of the target vehicle 2A and the target vehicle 2B. Even in such a case, the unstable behavior position D of the target vehicle 2A and the unstable behavior position D of the target vehicle 2B can be managed together by using the mesh 50, and the management can be made more efficient than when the unstable behavior position D is managed individually. In addition, by utilizing the mesh 50 according to the vehicle assistance content described later, appropriate driving assistance for the target vehicle 2 can be realized.

Figure 8 is a diagram showing an example of a mesh 50 set on a map. As shown in Figure 8, the mesh 50 is composed of multiple meshes 50A to 50N, etc.

As an example, the shape of the meshes 50A to 50N is a square. The meshes 50A to 50N may be rectangular, circular, elliptical, or polygonal, such as a hexagon. The shape of the meshes 50A to 50N is not particularly limited. The size of the meshes 50A to 50N is also not particularly limited. The meshes 50A to 50N may be set as an area on the map that is 30 meters square, or 1 kilometer square.

The meshes 50A-50N may be set to overlap each other, or may be spaced apart. The arrangement of the meshes 50A-50N is not particularly limited and may be arbitrary. The meshes 50A-50N may be arranged in a grid pattern, or may be set based on nodes on a map, intersections, traffic lights, or various landmarks. The meshes 50A-50N may be set as sections of a road of a certain distance.

The predetermined period used by the occurrence count unit 11e may be one hour, three hours, or six hours. The predetermined period may be one day, three days, or one week. The predetermined period is not particularly limited. If the mesh 50 corresponds to the vehicle assistance content described below, the predetermined period may be determined for each mesh 50 according to the vehicle assistance content.

Figure 9 is a diagram for explaining the number of occurrences of unstable behavior position D in mesh 50A. In the situation shown in Figure 9, the occurrence counting unit 11e counts the number of occurrences of unstable behavior position D in mesh 50A as 3.

The mesh expansion unit 11f expands the size of the mesh 50 so that the number of occurrences of unstable behavior positions within a specified period counted by the occurrence count unit 11e is equal to or greater than a first threshold value. The value of the first threshold value is not particularly limited. The first threshold value may be 5, 10, or a value of 11 or greater. The first threshold value may be 50 or 100. In other words, the mesh 50 is set to include a predetermined number of unstable behavior positions.

The expansion of the mesh 50 may be performed as a quantitative increase in area, or as a fixed percentage increase in area relative to the area before the expansion. The mesh 50 may be expanded so as to spread outward based on the current center position of the mesh 50, or may be expanded so as to extend along major roads within the mesh 50. There are no particular limitations on the method of expanding the mesh 50.

Figure 10 is a diagram for explaining the expansion of mesh 50A. Figure 10 shows the situation in which the expansion process of mesh 50A has been performed from the situation shown in Figure 9. In the situation shown in Figure 9, since the number of unstable behavior positions D in mesh 50A counted by occurrence counting unit 11e is less than a certain threshold (e.g., 5), mesh expansion unit 11f expands mesh 50A so that the unstable behavior positions D become equal to or greater than the certain threshold. In Figure 10, since the number of unstable behavior positions D in mesh 50A becomes equal to or greater than the certain threshold, mesh expansion unit 11f ends the expansion of mesh 50A.

The mesh expansion unit 11f may perform expansion processing so that the number of occurrences of unstable behavior positions within a specified period of time for each of the meshes 50A to 50N is equal to or greater than a first threshold value. The mesh expansion unit 11f may perform expansion processing only for meshes that include at least one unstable behavior position D among the meshes 50A to 50N, so that the number of occurrences of unstable behavior positions within a specified period of time is equal to or greater than a first threshold value. The mesh expansion unit 11f may perform expansion processing only for meshes that include a certain number or more of unstable behavior positions D among the meshes 50A to 50N.

When the mesh has been expanded up to a predetermined upper limit value without the number of occurrences of unstable behavior positions within a specified period being equal to or greater than the first threshold value, the mesh expansion unit 11f terminates the expansion of the mesh. The upper limit value can be set to any value. The upper limit value may be the area or the number of expansions.

The mesh expansion unit 11f may divide the mesh when a preset mesh division condition is satisfied. For example, the mesh expansion unit 11f counts the number of intermittent operations for each mesh to be used in determining the mesh division condition.

The number of intermittent operations is the number of times that intermittent operations, which are unstable behaviors, occurred multiple times within a mesh due to the same trip of the same target vehicle 2. The mesh expansion unit 11f counts the number of intermittent operations based on the target vehicle data, the unstable behavior position, and the mesh. If the same target vehicle 2 is traveling in a different direction, it is not counted as an intermittent operation. The number of intermittent operations is counted as one intermittent operation whether the same target vehicle 2 slips three times or five times within the same mesh.

The mesh expansion unit 11f determines that the mesh division condition is satisfied if the number of intermittent operations in the mesh is equal to or greater than the intermittent operation number threshold and the interval between multiple occurrences of unstable behavior in intermittent operation by the same target vehicle 2 is equal to or greater than a certain distance. The interval between multiple occurrences of unstable behavior in intermittent operation is the distance between the locations of occurrences of multiple unstable behaviors counted as the number of intermittent operations within the mesh.

The mesh expansion unit 11f divides the mesh so that it includes the occurrence positions of multiple occurrences of unstable behavior during intermittent operation that are separated by a certain distance or more. The size of the mesh (mesh size) is reduced by the division. The mesh expansion unit 11f may divide the mesh equally from the center, or may divide the mesh types so that there are the same number of unstable behavior positions according to the distribution of the unstable behavior positions. The mesh division method is not particularly limited. If there are many intermittent operations in the mesh and the intervals between multiple occurrences of unstable behavior during intermittent operation by the same target vehicle 2 are greater than a certain distance apart, there is a possibility that the unstable behavior is caused by different reasons, so by dividing the mesh, vehicle assistance according to the cause of each unstable behavior can be realized.

The recurrence frequency measurement unit 11g measures the recurrence frequency of unstable behavior within the recurrence frequency measurement area based on the unstable behavior position recognized by the unstable behavior position recognition unit 11b. The recurrence frequency measurement area is an area that is set in advance to include at least one mesh. The recurrence frequency measurement area may be set according to the area of a local government such as a prefecture or a city, town, or village. The recurrence frequency measurement area may be an area that includes meshes 50A to 50N in FIG. 8 (for example, an area that combines meshes 50A to 50N).

The occurrence frequency measurement area may be set as an independent area regardless of the expansion of the mesh, or may be expanded to include the mesh that is originally included in accordance with the expansion of the mesh. The occurrence frequency measurement area may be set as the same area as one mesh. In this case, the mesh can be used as it is as the occurrence frequency measurement area. The occurrence frequency measurement area is set in advance in association with the map in the map database 15 or the storage database 16, for example.

The recurrence frequency is the number of times that unstable behavior recurs during a certain investigation period. The certain period is not particularly limited. The certain period may be one day, one week, or one month. The number of recurrences corresponds to, for example, scene 1 determined by the situation determination unit 11c.

When a sufficient number of scenes 1 are not detected to measure the occurrence frequency, the occurrence frequency measurement unit 11g ensures the number of scenes 1 by extending the investigation period (for example, by 0.5 months). The occurrence frequency measurement unit 11g repeatedly extends the investigation period until a sufficient number of unstable behavior positions are collected. A sufficient number is, for example, a number equal to or greater than a preset threshold value.

If a sufficient number of scenes 1 are not detected even when the investigation period exceeds a preset upper limit, the recurrence frequency measurement unit 11g does not set the remaining time as a non-provisionable period. In addition, the recurrence frequency measurement unit 11g may measure the recurrence frequency by simply using the number of repeated unstable behavior positions as the recurrence number, instead of scenes 1.

The recurrence frequency measurement unit 11g determines an unstable behavior position where the recurrence frequency is equal to or greater than the recurrence frequency threshold as a recurrence point. The recurrence frequency measurement unit 11g determines an unstable behavior position where the recurrence frequency is less than the recurrence frequency threshold as a non-recurrence point. The recurrence frequency measurement unit 11g may determine an unstable behavior position where the recurrence number is equal to or greater than the recurrence number threshold as a recurrence point, instead of the recurrence frequency.

The remaining time setting unit 11h sets the remaining time of the unstable behavior position in the mesh. The remaining time is the remaining time for which the unstable behavior position is used for vehicle assistance. The remaining time setting unit 11h sets the remaining time of the unstable behavior position in the occurrence frequency measurement area based on the occurrence frequency of the unstable behavior in the occurrence frequency measurement area measured by the occurrence frequency measurement unit 11g.

The remaining time setting unit 11h measures the duration during which the recurrence frequency in the recurrence frequency measurement area remains at or above a certain threshold, and if the average duration is, for example, three hours, sets the remaining time of the unstable behavior position in the recurrence frequency measurement area as three hours. The median value may be used instead of the average duration, or the remaining time may be determined from the duration using a predetermined calculation formula.

In addition, the remaining time setting unit 11h may set the remaining time of the unstable behavior position to a longer time as the occurrence frequency of the unstable behavior increases. When the occurrence frequency of the unstable behavior is equal to or greater than a certain threshold, the remaining time setting unit 11h may set the remaining time of the unstable behavior position in the occurrence frequency measurement area to a longer time compared to when the occurrence frequency of the unstable behavior is less than the certain threshold. The remaining time setting unit 11h may set the remaining time in stages using multiple thresholds. When the occurrence frequency value has changed due to a new measurement, the remaining time setting unit 11h may extend or shorten the remaining time.

The memory processing unit 11j stores unstable behavior position information regarding the unstable behavior position recognized by the unstable behavior position recognition unit 11b in the memory database 16. The memory processing unit 11j associates the meshes stored in the map database 15 with the unstable behavior positions within the meshes and stores them in the memory database 16. When the mesh enlargement unit 11f performs mesh enlargement processing, the memory processing unit 11j updates the memory database 16 by associating the enlarged mesh with the unstable behavior positions within the mesh. The memory processing unit 11j may also update the map database 15 for the enlarged mesh.

When a judgment is made by the situation judgment unit 11c, the memory processing unit 11j may associate the unstable behavior position with the judgment result of the situation judgment unit 11c and store it in the memory database 16.

The memory processing unit 11j also stores the remaining time of the unstable behavior position set by the remaining time setting unit 11h in the memory database 16 in association with the unstable behavior position in the mesh. The memory processing unit 11j may delete information about the unstable behavior position whose remaining time has elapsed from the memory database 16. Note that it is not essential to delete information about the unstable behavior position after the remaining time has elapsed.

The vehicle assistance unit 11k provides various types of assistance to the target vehicle 2 by notifying the target vehicle 2 of information and giving instructions. The vehicle assistance unit 11k provides various types of assistance to the target vehicle 2 via the communication unit 13. Here, the vehicle assistance unit 11k generates vehicle assistance content for each unstable behavior position in which the mesh range of the mesh including the unstable behavior position is associated with the remaining time of assistance at the unstable behavior position. The vehicle assistance unit 11k transmits the generated vehicle assistance content to the target vehicle 2 to provide various types of assistance. The vehicle assistance content transmitted by the vehicle assistance unit 11k is content for suppressing the target vehicle 2 from exhibiting unstable behavior at the unstable behavior position. The vehicle assistance unit 11k generates, for example, a notification regarding the unstable behavior position, an instruction to change the driving route of the target vehicle 2, an instruction to cancel automatic driving of the target vehicle 2 that is being automatically driven, and the like, as the vehicle assistance content. The vehicle assistance content (service content) is not particularly limited.

The vehicle assistance unit 11k determines whether or not there is a target vehicle 2 heading toward a mesh that includes an unstable behavior position, for example, based on the target vehicle data recognized by the target vehicle data recognition unit 11a and the stored contents of the storage database 16. The vehicle assistance unit 11k may treat an unstable behavior position with no remaining time as not existing. In this case, there is no need to delete the unstable behavior position with no remaining time from the storage database 16.

For example, when a mesh is present ahead of the target vehicle 2 and the distance between the mesh and the target vehicle 2 is less than a threshold, the vehicle assistance unit 11k determines that a target vehicle 2 is present heading toward the mesh. The determination may be made using arrival time instead of distance. When the vehicle assistance unit 11k has acquired information on the travel route of the target vehicle 2, it may determine that a target vehicle 2 is present heading toward the mesh if the travel route passes through a mesh. Alternatively, the vehicle assistance unit 11k may make the above determination using a well-known method.

When the vehicle assistance unit 11k determines that there is a target vehicle 2 heading toward a mesh that includes an unstable behavior location, it transmits the vehicle assistance content generated for the unstable behavior location within that mesh to the target vehicle 2. For example, the vehicle assistance unit 11k notifies the target vehicle 2 of information related to the unstable behavior location associated with that mesh as the vehicle assistance content. The target vehicle 2 may notify the driver of the information related to the unstable behavior location by image output such as text display and/or sound output from the HMI 27. Note that the target vehicle 2 does not necessarily need to notify the driver.

In addition, the vehicle assistance unit 11k may transmit vehicle assistance content and perform vehicle assistance only when it determines that there is a target vehicle 2 heading toward a mesh that includes an unstable behavior position in a continuous occurrence situation. Even if the vehicle assistance unit 11k determines that there is a target vehicle 2 heading toward a mesh that includes only unstable behavior positions in a discontinuous situation, it may not need to perform vehicle assistance because there is not a high possibility that the target vehicle 2 will exhibit unstable behavior.

Alternatively, the vehicle assistance unit 11k may change the vehicle assistance content based on the ratio of unstable behavior positions in consecutive occurrence situations to unstable behavior positions in discontinuous situations included in the mesh. For example, when the ratio of unstable behavior positions in consecutive occurrence situations is greater, the vehicle assistance unit 11k may instruct the target vehicle 2 to change the driving route to avoid the unstable behavior positions. When the ratio of unstable behavior positions in discontinuous situations is greater, the vehicle assistance unit 11k may simply notify the target vehicle 2 of unstable behavior position information.

In addition, whether a continuous occurrence situation is occurring or not may be determined for each mesh, rather than for each unstable behavior position. The situation determination unit 11c may determine that a mesh is in a continuous occurrence situation when the number of unstable behavior positions in a continuous occurrence situation within a mesh is equal to or greater than a certain threshold. The situation determination unit 11c may determine that a mesh is in a continuous occurrence situation when the proportion of unstable behavior positions in a continuous occurrence situation is higher.

When the target vehicle 2 is in autonomous driving and it is determined that the mesh to which the target vehicle 2 is heading is in a continuous occurrence state, the vehicle assistance unit 11k may issue a command to cancel autonomous driving at the unstable behavior position together with notification of the unstable behavior position information. By canceling autonomous driving and transitioning to manual driving by the driver, the target vehicle 2 can avoid the target vehicle 2 from exhibiting unstable behavior within the mesh while still in autonomous driving.

The vehicle assistance unit 11k may notify the unstable behavior position information when it is determined that the mesh is in a continuous occurrence state, and may not notify the unstable behavior position information when it is determined that the mesh is in a discontinuous state. This makes it possible to suppress unnecessary notifications of unstable behavior position information even in cases where the reproducibility of unstable behavior cannot be said to be high.

The vehicle assistance unit 11k may change the vehicle assistance content depending on the area of the mesh. The vehicle assistance unit 11k may lower the assistance level of the vehicle assistance as the area of the mesh becomes larger. It can be considered that the density of unstable behavior positions within the mesh decreases as the area of the mesh is enlarged by the enlargement process. The assistance level of the vehicle assistance is highest when it is an instruction to change the driving state, such as an instruction to decelerate the target vehicle 2 (vehicle control instruction), followed by notification by text display and sound output (attention warning), and lowest by notification by text display only (information provision).

Specifically, the vehicle assistance unit 11k may change the assistance level of the vehicle assistance by dividing the mesh area into three stages. The vehicle assistance unit 11k may notify (provide information) the target vehicle 2 heading toward the first stage mesh with the largest area by displaying a text of the unstable behavior position, notify (warn) the target vehicle 2 heading toward the intermediate second stage mesh by displaying a text of the unstable behavior position and outputting a sound, and may issue an instruction (vehicle control instruction) to change the driving state, such as an instruction to the target vehicle 2 to decelerate, to the target vehicle 2 heading toward the third stage mesh with the smallest area. When issuing a warning instruction, the text display and the sound output may be executed together. Note that the vehicle assistance content may be changed using the number of times the mesh is expanded instead of the area of the mesh.

<Driving assistance based on vehicle assistance content>
Next, a description will be given of details of the driving assistance performed by the autonomous driving control unit 33 of the target vehicle 2 based on the vehicle assistance content transmitted from the vehicle assistance unit 11k of the information processing server 10. As shown in Fig. 11, the autonomous driving control unit 33 has an assistance content acquisition unit 33a, a priority setting unit 33b, and an assistance execution unit 33c.

The assistance content acquisition unit 33a acquires the vehicle assistance content transmitted from the vehicle assistance unit 11k via the communication unit 26. When multiple vehicle assistance contents are transmitted from the information processing server 10, the assistance content acquisition unit 33a acquires each of these vehicle assistance contents. As described above, the vehicle assistance content is associated with the mesh range of the mesh and the remaining time of assistance at the unstable behavior position.

The priority setting unit 33b sets the execution priority for the acquired vehicle assistance content. When only one vehicle assistance content is acquired, the priority setting unit 33b sets this vehicle assistance content as the vehicle assistance content to be executed. When multiple vehicle assistance contents are acquired, the priority setting unit 33b sets the priority for the vehicle assistance content based on the mesh range and remaining time associated with each assistance content.

Regarding the setting of the priority, the priority setting unit 33b sets a higher priority when the mesh size is smaller than when the mesh size is larger. For example, the smaller the mesh size, the more limited the locations where driving assistance is activated, and the more likely it is that opportunities to provide driving assistance will be missed. For this reason, the priority setting unit 33b can make it easier for this vehicle driving assistance to be executed by setting a higher priority when the mesh size is small and opportunities to provide driving assistance are likely to be missed.

Furthermore, the priority setting unit 33b sets a higher priority when the remaining time of assistance is shorter than when the remaining time is longer. For example, the shorter the remaining time of assistance, the greater the need for driving assistance, such as when there is another vehicle making an unexpected move or when there is a merging vehicle. On the other hand, the longer the remaining time of assistance, the less the need for driving assistance, such as when the location is more likely to cause a slip. For this reason, the priority setting unit 33b can make it easier to execute this vehicle driving assistance by setting a higher priority when the remaining time of assistance is short and the need for driving assistance is greater.

For example, the priority setting unit 33b first assigns a higher priority to vehicle assistance content with a shorter remaining assistance time. Next, when there are multiple vehicle assistance content with the same remaining time (including cases where the time difference is within a predetermined time), the priority setting unit 33b assigns a higher priority to vehicle assistance content with a smaller mesh size among the vehicle assistance content with the same remaining time.

That is, for example, as shown in FIG. 12, when the mesh size is small and the remaining support time is short, the priority setting unit 33b sets the priority to 1st. Note that the lower the priority ranking (the closer to 1st), the higher the priority. When the mesh size is large and the remaining support time is short, the priority setting unit 33b sets the priority to 2nd. When the mesh size is small and the remaining support time is long, the priority setting unit 33b sets the priority to 3rd. When the mesh size is large and the remaining support time is long, the priority setting unit 33b sets the priority to 4th.

The assistance execution unit 33c determines the vehicle assistance content to be executed based on the priority of the vehicle assistance content set by the priority setting unit 33b. Then, the assistance execution unit 33c executes driving assistance for the target vehicle 2 based on the determined vehicle assistance content. For example, the assistance execution unit 33c can execute driving assistance in the order of vehicle assistance content with the highest priority.

For example, when the vehicle assistance content determined based on the priority is an instruction to cancel the automatic driving, the assistance execution unit 33c cancels the automatic driving at the unstable behavior position. In this case, the assistance execution unit 33c may notify the driver of the transition to manual driving via the HMI 27.

For example, if the vehicle assistance content determined based on the priority is an instruction to change the driving route, the route generation unit 32 generates a route for automatic driving in accordance with the determined vehicle assistance content. The assistance execution unit 33c drives the target vehicle 2 based on the route generated in accordance with the vehicle assistance content as driving assistance.

The target vehicle 2 does not necessarily have to be an autonomous vehicle. In this case, the autonomous driving control unit 33 of the target vehicle 2 does not need to execute autonomous driving of the target vehicle 2. The autonomous driving ECU 30 of the target vehicle 2 may notify the driver of unstable behavior position information, etc. through the HMI 27 by the assistance content acquisition unit 33a, the priority setting unit 33b, and the assistance execution unit 33c.

In this way, the autonomous driving control unit 33 functions as a driving assistance device that acquires vehicle assistance content in which the mesh range and the remaining assistance time are associated from the information processing server 10 and provides driving assistance to the vehicle based on the acquired vehicle assistance content.

<Driving assistance method based on vehicle assistance content>
Next, a driving assistance method performed by the automatic driving control unit 33 based on the vehicle assistance content will be described with reference to the flowchart in Fig. 13. Here, a process flow for setting priorities of vehicle assistance content and performing driving assistance when multiple vehicle assistance content is acquired will be described.

As shown in FIG. 13, the assistance content acquisition unit 33a acquires multiple vehicle assistance contents from the vehicle assistance unit 11k of the information processing server 10 (S101). The priority setting unit 33b extracts the remaining time and mesh range (mesh size) associated with each of the acquired vehicle assistance contents (S102).

The priority setting unit 33b assigns a higher priority to vehicle assistance content with a shorter remaining time (S103). Then, when the priority setting unit 33b assigns priorities based on the remaining time, it determines whether or not there are multiple vehicle assistance content with the same remaining time (S104). If there are multiple vehicle assistance content with the same remaining time (S104: YES), the priority setting unit 33b assigns a higher priority to vehicle assistance content with a smaller mesh size among the vehicle assistance content with the same remaining time (S105). The assistance execution unit 33c determines the vehicle assistance content to be executed based on the set priority, and executes driving assistance for the target vehicle 2 (S106).

If there are no vehicle assistance contents with the same remaining time (S104: NO), the assistance execution unit 33c determines the vehicle assistance content to be executed based on the priority set based on the remaining time, and executes driving assistance for the target vehicle 2 (S106).

As described above, when multiple vehicle assistance contents are acquired, the autonomous driving control unit 33 can appropriately set the priority of both assistance contents based on the mesh range and remaining time. Then, the autonomous driving control unit 33 can provide driving assistance to the target vehicle 2 based on the vehicle assistance contents determined based on the priority.

For example, the priority setting unit 33b sets a higher priority for vehicle assistance content the shorter the remaining time. This allows the assistance execution unit 33c to respond in order of the vehicle assistance content with the shortest remaining time, i.e., the highest need for driving assistance. Also, for example, the priority setting unit 33b sets a higher priority for vehicle assistance content the smaller the mesh size. This allows the assistance execution unit 33c to prevent missing driving assistance opportunities even for vehicle assistance content with a small mesh size, i.e., for which the opportunity for driving assistance is likely to be missed.

Although the embodiments of the present invention have been described above, the present invention is not limited to the above-mentioned embodiments. The present invention can be implemented in various forms, including the above-mentioned embodiments, with various modifications and improvements based on the knowledge of those skilled in the art.

2... target vehicle (vehicle), 10... information processing server (server), 33... automatic driving control unit (driving support device), 33a... support content acquisition unit, 33b... priority setting unit, 33c... support execution unit, 50, 50A to 50N... mesh (map mesh).

Claims (2)

A driving assistance device that acquires vehicle assistance content from a server, in which a mesh range of a map mesh that is set to include a predetermined number of assistance required positions is associated with a remaining time of assistance at the assistance required positions, and performs driving assistance for a vehicle based on the acquired vehicle assistance content,
an assistance content acquisition unit that acquires the vehicle assistance content from the server;
a priority setting unit that sets a priority of execution of the acquired vehicle assistance content;
an assistance execution unit that determines the vehicle assistance content to be executed based on the priority of the set vehicle assistance content, and executes driving assistance of the vehicle based on the determined vehicle assistance content;
Equipped with
a remaining time is set such that, as the occurrence frequency of the unstable behavior of the vehicle in a occurrence frequency measurement area that is set to include at least one of the map meshes, a longer remaining time is set as the remaining time of the assistance required position in the occurrence frequency measurement area,
The priority setting unit
When a plurality of vehicle assistance contents are acquired , the priority is set for each of the vehicle assistance contents ;
The shorter the remaining time associated with the vehicle assistance content is, the higher the priority is set compared to when the remaining time is long;
A driving assistance device that sets a higher priority as the size of the mesh range associated with the vehicle assistance content becomes smaller, compared to a case where the size of the mesh range is large . 2. The driving assistance device according to claim 1, wherein the priority setting unit sets the priority based on the remaining time associated with the vehicle assistance content, and when there is a vehicle assistance content with the same remaining time or a time difference within a predetermined time, sets the priority based on the mesh range, and when there is no vehicle assistance content with the same remaining time or a time difference within a predetermined time, does not set the priority based on the mesh range.