JP2023016851A - Information processing device, information processing system, information processing method, and program - Google Patents

Abstract

PROBLEM TO BE SOLVED: To provide an information processing device which can easily divide whether a driving state of a moving body is an automatic driving state or a manual driving state with respect to collected probe information to perform appropriate information analysis according to the driving state.

SOLUTION: An information processing device comprises: behavior information acquisition means of acquiring behavior information including acceleration in a longitudinal direction to a movement direction of a moving body; and determination means of determining that at least a part of a driving operation of steering the moving body is automatically performed when the acceleration is a predetermined threshold or less, and determining that the driving operation of the moving body is manually performed when the acceleration is larger than the predetermined threshold on the basis of the acceleration acquired by the behavior information acquisition means.

SELECTED DRAWING: Figure 2

COPYRIGHT: (C)2023,JPO&INPIT

Description

The present invention relates to an information processing device, an information processing system, an information processing method, and a program for providing information to mobile bodies.

Analysis is performed using probe information indicating the traveling history (traveling position, traveling speed, etc.) of a mobile object such as a vehicle.

As a device for analyzing using such probe information, for example, vehicle probe information, VICS (registered trademark) (Vehicle Information and Communication System) information, and information from a road administrator's vehicle detector installed on the roadside Driving equipped with a support device that predicts whether or not there is a high possibility that an event requiring attention will occur in the target vehicle based on the output, and presents information to the on-board device of the target vehicle according to the prediction result. A support system is disclosed.

JP 2010-039992 A

However, the driving support system of Patent Literature 1 collects probe information from a vehicle without distinguishing whether the vehicle is in an automatic driving state or a manual driving state. Therefore, one example of a problem is that the collected probe information could not be properly analyzed.

The present invention has been made in view of the above-mentioned points, and can easily distinguish whether the operating state of a moving object is an automatic operating state or a manual operating state with respect to collected probe information, and according to the operating state, An object is to provide an information processing apparatus that performs appropriate information analysis.

The information processing apparatus according to claim 1, further comprising a behavior information obtaining unit for obtaining behavior information including acceleration in a horizontal direction with respect to a moving direction of a mobile object, and a determining that at least a part of the driving operation of steering the moving body is automatically performed when the acceleration is less than or equal to a predetermined threshold; and determination means for determining that the operation is performed manually.

The information processing system according to claim 9 comprises a measurement terminal that performs measurement including acceleration in a horizontal direction with respect to a moving direction of a mobile body, and behavior information that acquires the acceleration of the mobile body acquired by the measurement terminal. Based on the acquisition means and the acceleration, when the acceleration is equal to or less than a threshold, it is determined that at least a part of the driving operation of steering the moving body is automatically performed, and when the acceleration is greater than the predetermined threshold. and an information processing device having determination means for determining that the driving operation of the moving body is performed manually.

11. The information processing method according to claim 10, wherein the step of acquiring behavior information including acceleration in a horizontal direction with respect to a moving direction of a mobile object; and determining that at least part of the driving operation of steering the moving body is automatically performed, and determining that the driving operation of the moving body is performed manually when the acceleration is greater than a predetermined threshold. and a step of performing.

The program according to claim 11 of the present application is characterized in that the step of obtaining, in a computer, behavior information including an acceleration in a horizontal direction with respect to a moving direction of a mobile body, and determining that the acceleration is equal to or less than a threshold value based on the acceleration of the behavior information in the case of determining that at least part of the driving operation of steering the moving body is automatically performed, and when the acceleration is greater than a predetermined threshold, the driving operation of the moving body is performed manually and a step of determining that

1 is an overall view of an information processing system of Example 1; FIG. FIG. 2 is a block diagram showing configurations of a measurement terminal and a server according to the first embodiment; FIG. 4 is a flowchart showing information processing of the server of Example 1. FIG. FIG. 10 is a flowchart showing another information processing of the server of Example 1; FIG. 11 is a block diagram showing configurations of a measurement terminal and a server of Example 2; FIG. 11 is a flowchart showing information processing of the server of Example 2; FIG. 11 is a block diagram showing the configurations of a measurement terminal and a server according to Example 3; FIG. 11 is a flowchart showing information processing of the server of Example 3; FIG. 11 is a block diagram showing the configurations of a measurement terminal and a server according to Example 4; FIG. 12 is a flowchart showing information processing of the server of Example 4; FIG. 11 is a block diagram showing the configurations of a measurement terminal and a server according to Example 5; FIG. 12 is a flowchart showing information processing of the server of Example 5;

FIG. 1 shows the overall configuration of an information processing system according to the first embodiment. As shown in FIG. 1, an information processing system 100 is configured by connecting a measurement terminal 10 mounted on an automobile M as a mobile body and a server 20 as an information processing device via a network NW. . The moving body may be a moving body other than a car, such as an automobile, a motorcycle, an airplane, a ship, or a moving person.

FIG. 2 shows functional blocks of the measuring terminal 10 and the server 20 of the information processing system 100. As shown in FIG. As shown in FIG. 2, in the information processing system 100, the measuring terminal 10 mounted on each of the plurality of automobiles M and the server 20 are connected so as to be able to communicate with each other.

A measuring terminal 10 is mounted on an automobile M. As shown in FIG. The measurement terminal 10 may be part of the navigation system of the automobile M.

The acceleration sensor 11 is a capacitance type or piezoresistive type acceleration sensor. The acceleration sensor 11 is, for example, a biaxial acceleration sensor, and detects acceleration in the front-rear direction when the vehicle M travels forward and acceleration in the left-right direction perpendicular to the front-rear direction, that is, acceleration in the left-right direction with respect to the moving direction of the vehicle M. to detect

A GPS (Global Positioning System) device 12 is a device configured to receive signals (GPS signals) from GPS satellites, and acquires position information of the vehicle M. As shown in FIG.

The communication unit 13 is an interface communicably connected to the server 20 and the measurement terminals 10 mounted on other automobiles M via the network NW.

The control unit 14 includes, for example, a CPU (Central Processing Unit) that performs arithmetic processing. The control unit 14 can control the operation of each unit of the measuring terminal 10 including the acceleration sensor 11 , the GPS device 12 and the communication unit 13 .

The behavior information calculator 15 is one of functional blocks of the controller 14 . The behavior information calculation unit 15 uses the signals from the acceleration sensor 11 and the GPS device 12 to determine the speed, acceleration, accelerator opening, braking strength, idling distance when the accelerator is off, and the vehicle running in front of the vehicle M. Behavior information including the inter-vehicle distance from the vehicle and the position of the vehicle M can be calculated. That is, the behavior information calculation unit 15 can acquire probe information. The behavior information is, for example, information about the behavior of the automobile M per predetermined period. The acceleration is, for example, the acceleration of the automobile M per 15 seconds. It should be noted that the predetermined period can be arbitrarily determined.

The acceleration and velocity of the automobile M may be calculated and acquired based on the acceleration signal from the acceleration sensor 11 or the GPS signal from the GPS device 12, for example. Further, the speed of the vehicle M may be obtained by receiving a vehicle speed pulse from the vehicle M and calculating it based on the vehicle speed pulse.

Also, the position of the automobile M may be obtained based on GPS signals from the GPS device 12, for example. Further, the position of the vehicle M may be calculated based on the amount of movement from the reference position, the attitude information of the vehicle M from the gyro device, or the vehicle speed information obtained from the vehicle speed pulse of the vehicle M. Also, the behavior information calculation unit 15 may be capable of acquiring map information. That is, the position of the vehicle M can be calculated and obtained by combining at least one of the GPS information from the GPS receiver, the attitude information of the vehicle M from the gyro device, and the vehicle speed information of the vehicle M, and the map information. may

Further, in the following description, the acceleration when the vehicle M accelerates in the traveling direction of the vehicle M is defined as positive acceleration, and the acceleration when decelerated is defined as negative acceleration. Negative acceleration in the traveling direction is also referred to as deceleration. As for lateral acceleration, the acceleration to the left with respect to the traveling direction of the vehicle M is defined as positive acceleration, and the acceleration to the right with respect to the traveling direction is defined as negative acceleration.

The communication unit 21 of the server 20 is communicably connected to the communication unit 13 of the measurement terminal 10 mounted on each of the plurality of automobiles M via the network NW. The communication unit 21 can receive behavior information or probe information including the acceleration, speed and position of the automobile M from the communication unit 13, for example.

The control unit 23 includes, for example, a CPU (Central Processing Unit) that performs arithmetic processing, and is implemented by a computer. The control unit 23 can control operations of each unit of the server 20 including the communication unit 21 . In addition, the control unit 23 can acquire various information from the outside via the communication unit 21 and perform processing such as analysis on the acquired information. The CPU reads a program corresponding to the processing content from the storage unit 22 and executes the read program to realize various functions.

The behavior information acquisition unit 23a is one of the functional blocks of the control unit 23. FIG. The behavior information acquiring means 23a can acquire the behavior information of the automobile M from each measurement terminal 10 mounted on the automobile M. As shown in FIG.

The determination means 23b is one of the functional blocks of the control section 23. FIG. Based on the acceleration included in the behavior information received by the communication unit 21, the determination unit 23b determines whether the vehicle M in which each measurement terminal 10 is mounted is in the automatic driving mode.

For example, the determination means 23b determines that the vehicle is in the automatic driving mode when the acceleration (deceleration) of the vehicle M in the traveling direction is equal to or less than a predetermined threshold value. Further, for example, the determining means 23b determines that the vehicle is in the automatic driving mode when the absolute value of the lateral acceleration of the vehicle M is equal to or less than a predetermined threshold value.

Specifically, the vehicle M running in the automatic driving mode maintains a constant speed on a straight road when there is no vehicle running ahead, and acceleration/deceleration is smooth with minimal variations.

In addition, when the vehicle M running in the automatic driving mode follows the vehicle running ahead, the speed changes in accordance with the vehicle running ahead on the straight road, and the acceleration and deceleration is minimal. It is smooth with little fluctuation.

In addition, when the automobile M traveling in the automatic driving mode follows the automobile traveling in front, the inter-vehicle distance from the automobile traveling in front of the automobile M is constant. In other words, the vehicle M running in the automatic driving mode runs while maintaining a constant inter-vehicle distance regardless of the weather or the time zone (daytime or nighttime).

Incidentally, as the speed range of the automobile M increases, the stopping distance of the automobile M increases. Therefore, the inter-vehicle distance increases as the speed range of the automobile M increases. That is, the automobile M traveling in the automatic driving mode travels at a constant inter-vehicle distance according to the traveling speed.

On the other hand, it is difficult for the automobile M running in the manual operation mode to maintain a strictly constant speed. In addition, the vehicle M traveling in the manual operation mode occasionally shows acceleration indicating sudden deceleration. Furthermore, in the vehicle M running in the manual operation mode, the inter-vehicle distance to the vehicle running in front varies during running and when the vehicle is stopped.

Judgment means 23b judges whether it is automatic operation mode in consideration of these elements. Here, the automatic driving mode is the driving mode of the automobile. The operation mode includes a plurality of operation modes that differ depending on the degree of automation of operations related to running of the automobile M.

For example, the manual driving mode corresponds to automatic driving level 0. It is assumed that the automatic driving mode is a mode corresponding to automatic driving levels 1 to 5. Here, the automated driving level is defined by the Japanese government and the National Highway Traffic Safety Administration (NHTSA) of the US Department of Transportation.

Also, the automatic driving mode includes a mode for assisting at least one of accelerator operation, brake operation, and steering operation. The mode in which the operation is assisted is a mode in which the driver intervenes in the driving operation when the driver's operation does not satisfy a predetermined condition, such as emergency braking.

The determination means 23b determines whether or not at least one driving operation is automatically performed for each of the driving operation of steering the automobile M, the driving operation of accelerating, and the driving operation of braking. That is, the determining means 23b determines that the vehicle is in the automatic driving mode if at least one of the steering operation, the acceleration operation, and the braking operation of the automobile M is automatically controlled.

Note that the determination by the determining means 23b is not limited to this. For example, the determining means 23b determines whether each of the steering operation, the acceleration operation, and the braking operation of the automobile M is automatically performed. You may make it That is, it may be determined that the automatic driving mode is set when each of the steering operation, the acceleration operation, and the braking operation of the automobile M is automatically performed. Further, the automatic driving level does not necessarily have to be determined. For example, it may be determined whether or not the vehicle is in the automatic driving mode for each driving operation such as accelerator operation, brake operation, and steering operation.

The storage unit 22 includes, for example, a hard disk, flash memory, SSD (Solid State Drive), RAM (Random Access Memory), etc., and can store information such as mobile information received by the communication unit 21 . Further, the storage unit 22 can store threshold information used when the determination means 23b determines the operation mode of the automobile M. FIG. In addition, the storage unit 22 can store information that serves as a reference for determination by means of each functional block. The storage unit 22 can also store map information and the like. The storage unit 22 stores various programs such as BIOS (Basic Input Output System) and software. In addition, the storage unit 22 can store the result of determination by the means of each functional block of the control unit 23 such as the behavior information acquisition unit 23a and the determination unit 23b.

FIG. 3 shows operation mode determination processing executed by the server 20 . As shown in FIG. 3, the behavior information acquiring means 23a acquires behavior information of the automobile M from each measurement terminal 10 mounted on the automobile M (step S101).

Based on the behavior information acquired in step S101, the determining means 23b determines whether the driving operation of the automobile M is being performed automatically, that is, determines the driving mode of the automobile M.

Specifically, the determination unit 23b determines whether the longitudinal acceleration of the behavior information is equal to or less than a predetermined threshold (step S102). That is, when the vehicle M is in the automatic driving mode, acceleration or deceleration of the vehicle M is performed based on a predetermined constant reference. For this reason, the automobile M in the automatic driving mode runs with stable acceleration or deceleration according to a certain standard. The determination means 23b utilizes such properties of the automatic driving mode to determine whether at least part of the driving operation related to acceleration and at least part of the driving operation related to braking is automatically performed, that is, the driving mode of the automobile M judge. The fixed reference is, for example, the displacement of longitudinal acceleration during a fixed period (for example, 10 seconds). When the displacement is lower than a certain reference, the automobile M is traveling with stable acceleration or deceleration, and the determining means 23b can determine that the automobile M is traveling in the automatic driving mode. That is, in the case of the automatic driving mode, it is assumed that the longitudinal acceleration is relatively constant without sudden acceleration and braking operations.

In the determination of step S102, when the longitudinal acceleration is equal to or less than the threshold (step S102: Y), the determining means 23b determines that the automobile M is in the automatic driving mode (step S103).

In the determination of step S102, if the longitudinal acceleration exceeds the threshold (step S102: N), the determining means 23b determines whether the lateral acceleration of the behavior information is equal to or less than a predetermined threshold (step S104). That is, when the automobile M is in the automatic driving mode, steering of the automobile M is performed based on a predetermined constant reference. For this reason, the automobile M in the automatic driving mode is traveling with a stable lateral acceleration according to a certain standard. That is, in the automatic driving mode, it is assumed that the left and right acceleration is relatively constant without sudden steering operation.

The determining means 23b determines whether or not at least a part of the driving operation related to steering is performed automatically, that is, determines the driving mode of the automobile M by using the properties of the automatic driving mode. A steering mode of the automobile M is determined. The fixed reference is, for example, the lateral acceleration displacement during a fixed period (for example, 10 seconds). If the displacement is lower than a certain reference, the vehicle M is traveling with a stable lateral acceleration, and the determining means 23b can determine that the vehicle M is in the automatic driving mode.

In the determination of step S104, when the lateral acceleration is equal to or less than the threshold (step S104: Y), the determining means 23b determines that the automobile M is in the automatic driving mode (step S103).

In the determination of step S104, when the lateral acceleration exceeds the threshold (step S104: N), the determining means 23b determines that the automobile M is in the manual driving mode (step S105).

As described above, according to the information processing system of the present embodiment, based on the longitudinal acceleration and lateral acceleration of the automobile M, it is determined whether the automobile M is in the automatic driving mode. Therefore, it is possible to easily distinguish whether the operating state of the moving body is the automatic operating state or the manual operating state with respect to the collected probe information, and it is possible to perform appropriate information analysis according to the operating state.

In this embodiment, when either the longitudinal acceleration or the lateral acceleration is equal to or less than the threshold value, it is determined that the vehicle is in the automatic driving mode. However, the operation mode determination process is not limited to this, and for example, when either the longitudinal acceleration or the lateral acceleration is equal to or less than a threshold value, the automatic driving mode may be determined.

FIG. 4 shows another automatic driving mode determination process executed by the server 20. As shown in FIG. Since step S201 is the same processing as step S101 shown in FIG. 3, description thereof is omitted. As shown in FIG. 4, the determination means 23b determines whether the longitudinal acceleration of the behavior information is equal to or less than a predetermined threshold (step S202). In the determination of step S202, if the longitudinal acceleration is equal to or less than the threshold (step S202: Y), the determining means 23b determines whether the lateral acceleration of the behavior information is equal to or less than the predetermined threshold (step S203).

In the determination of step S203, when the lateral acceleration is equal to or less than the threshold (step S203Y), the determining means 23b determines that the automobile M is in the automatic driving mode (step S204).

In the determination of step S202, when the longitudinal acceleration exceeds the threshold (step S202: N), the determining means 23b determines that the automobile M is in the manual driving mode (step S205).

In the determination of step S203, if the lateral acceleration exceeds the threshold (step S203: N), the determining means 23b determines that the automobile M is in the manual driving mode (step S205).

By determining whether or not the determination means 23b is in the automatic operation mode in this way, it is possible to perform determination with higher accuracy.

An information processing system 100 according to the second embodiment will be described. The information processing system 100 according to the second embodiment differs from the information processing system 100 according to the first embodiment in that the measurement terminal 10 includes a camera and the server 20 includes inter-vehicle distance acquisition means. Other points are the same as the configuration of the information processing system 100 according to the first embodiment.

FIG. 5 shows the configuration of an information processing system 100 according to the second embodiment. As shown in FIG. 5, the measurement terminal 10 includes a camera 17 that captures an image of the vehicle traveling in front of the vehicle M. As shown in FIG.

The server 20 includes inter-vehicle distance acquisition means 23c as inter-moving body distance acquisition means. The inter-vehicle distance acquisition means 23c is one of the functional blocks of the control section 23. FIG. The vehicle-to-vehicle distance acquisition means 23c calculates the vehicle-to-vehicle distance between the vehicle M and the vehicle traveling in front from the imaging information acquired from the measurement terminal 10 .

FIG. 6 shows the operation mode determination process executed by the server 20 . As shown in FIG. 6, the vehicle-to-vehicle distance acquisition means 23c acquires imaged data from the measurement terminal 10, calculates the distance to the vehicle running in front of the vehicle M from the acquired imaged data, and acquires the vehicle-to-vehicle distance ( step S301). The vehicle-to-vehicle distance acquisition means 23c acquires a plurality of vehicle-to-vehicle distances acquired during a predetermined period (for example, 5 minutes). Specifically, the vehicle-to-vehicle distance acquisition means 23c acquires a plurality of vehicle-to-vehicle distances according to the traveling speed of the automobile M. For example, when the automobile M runs at a constant speed of 40 km/h for 5 minutes, the inter-vehicle distance is acquired every predetermined time (for example, 10 seconds). Further, for example, when the vehicle M runs for 5 minutes with the speed fluctuating between 40 km/h and 60 km/h, the inter-vehicle distance corresponding to the speed of the vehicle M is acquired every predetermined time (eg, 10 seconds).

The determining means 23b determines whether the driving operation of the automobile M is automatically performed, that is, the driving mode of the automobile M, based on the plurality of vehicle-to-vehicle distances acquired in step S301.

Specifically, the determining means 23b determines whether or not all of the plurality of vehicle-to-vehicle distances are within a predetermined range (step S302). For example, when the automobile M is traveling at a constant speed of 40 km/h for 5 minutes, the determining means 23b determines whether the inter-vehicle distance obtained at predetermined time intervals is within a predetermined range of 30 to 40 m. Note that the predetermined range of the predetermined time and the inter-vehicle distance may be changed arbitrarily.

That is, when the vehicle M is in the automatic driving mode, the vehicle M is accelerated and braked based on a predetermined standard. The judgment means 23b judges the operation mode of the automobile M by using such properties of the automatic driving mode.

When it is determined in step S302 that all of the distances between the vehicles are within the predetermined range (step S302: Y), the determining means 23b determines that the vehicle M is in the automatic driving mode (step S303). .

In the determination of step S302, if at least one of the distances between the vehicles is outside the predetermined range (step S302: N), the determining means 23b determines that the automobile M is in the manual driving mode (step S304). ).

In this embodiment, the inter-vehicle distance acquisition means 23c acquires the inter-vehicle distance based on the imaging data captured by the camera 17 of the measuring terminal 10. FIG. However, acquisition of the inter-vehicle distance is not limited to being performed based on image data captured by the camera 17, and any data that can acquire the distance to a vehicle traveling ahead may be used. Examples of such data include measurement data of millimeter wave radar, LiDAR (Light Detection and Ranging), and the like.

As described above, according to the information processing system of the present embodiment, based on the inter-vehicle distance to the vehicle running in front of the vehicle M, it is determined whether or not the vehicle M is in the automatic driving mode. Therefore, it is possible to easily distinguish whether the operating state of the moving body is the automatic operating state or the manual operating state with respect to the collected probe information, and it is possible to perform appropriate information analysis according to the operating state.

An information processing system 100 according to the third embodiment will be described. The information processing system 100 according to the third embodiment differs from the information processing system 100 according to the first embodiment in that the server 20 includes road shape acquisition means 23d. Other points are the same as the configuration of the information processing system 100 according to the first embodiment.

FIG. 7 shows the configuration of an information processing system 100 according to the third embodiment. As shown in FIG. 7, the server 20 includes road shape acquisition means 23d. The road shape acquisition means 23d is one of the functional blocks of the control section 23. FIG. The road shape acquisition means 23d acquires the shape of the road on which the automobile M travels from the map information acquired from the measurement terminal 10. FIG.

For example, the behavior information calculation unit 15 of the measurement terminal 10 can acquire map information. The map information is transmitted to the server 20 together with the behavior information. The road shape acquisition means 23d acquires the shape of the road corresponding to the behavior information based on the transmitted map information.

FIG. 8 shows the operation mode determination process executed by the server 20 . As shown in FIG. 8, the behavior information acquiring means 23a acquires the behavior information of the automobile M from each measurement terminal 10 mounted on the automobile M. As shown in FIG. Further, the road shape acquisition means 23d acquires the map data from the measurement terminal 10 and acquires the shape of the road on which the automobile travels (step S401).

The determining means 23b determines whether the driving operation of the automobile M is automatically performed, that is, the driving mode of the automobile M, based on the behavior information and the road shape acquired in step S401.

Specifically, the determination unit 23b determines whether or not the longitudinal acceleration of the behavior information in the specific road configuration among the acquired road configurations is equal to or less than a predetermined threshold value (step S402). Here, the form of a specific road includes entrances and exits of tunnels, inside tunnels, so-called sag points that change from downhill to uphill, expressway toll booths such as ETC (Electronic Toll Collection System), curves, intersections, etc. is.

That is, when the automobile M is in the automatic driving mode, the automobile M is driven based on a predetermined standard. For example, at the entrance/exit of a tunnel, changes in visibility may cause changes in the speed of the vehicle M in manual driving mode. On the other hand, in the automatic driving mode, it is considered that the speed of the vehicle M is kept constant even at the entrance/exit of the tunnel. Also, in the manual driving mode, the vehicle M may be rapidly accelerated when passing through a highway toll gate such as ETC. On the other hand, in the automatic driving mode, the vehicle M is considered to be accelerated at a constant acceleration even when passing through a highway toll gate such as ETC. The judgment means 23b judges the operation mode of the automobile M by using such properties of the automatic driving mode.

In the determination of step S402, if the longitudinal acceleration in the specific road configuration is equal to or less than the predetermined threshold value (step S402: Y), the determining means 23b determines that the automobile M is in the automatic driving mode (step S403).

In the determination of step S402, if the longitudinal acceleration in the specific road configuration exceeds the predetermined threshold value (step S402: N), the determination unit 23b It is determined whether or not the lateral acceleration of the behavior information is equal to or less than a predetermined threshold value (step S404).

That is, when the automobile M is in the automatic driving mode, the automobile M is steered based on a predetermined standard. For example, in the manual driving mode, the steering operation on a curve may be uneven because the steering operation depends on the skill and feeling of the driver. On the other hand, in the automatic driving mode, even if the steering operation is performed on a curve, the vehicle M is steered based on a certain standard, so it is considered that unevenness is less likely to occur. The judgment means 23b judges the operation mode of the automobile M by using such properties of the automatic driving mode.

In the determination of step S404, if the lateral acceleration is equal to or less than the predetermined threshold value (step S404: Y), the determining means 23b determines that the vehicle M is in the automatic driving mode (step S403).

In the determination of step S404, if the lateral acceleration exceeds the predetermined threshold value (step S404: N), the determining means 23b determines that the automobile M is in the manual driving mode (step S405).

Acquisition of the shape of the road by the road shape acquisition means 23d is not limited to map information.

As described above, according to the information processing system of this embodiment, it is determined whether or not the vehicle M is in the automatic driving mode based on the behavior information of the vehicle M when traveling on a specific road shape. . Therefore, it is possible to easily distinguish whether the operating state of the moving body is the automatic operating state or the manual operating state with respect to the collected probe information, and it is possible to perform appropriate information analysis according to the operating state.

The information processing systems according to the first to third embodiments described above may be implemented by combining configurations of the servers 20 respectively. For example, the determination means 23b combines the behavior information of the vehicle M, the inter-vehicle distance from the vehicle running in front of the vehicle M, and the behavior information of the vehicle M on a specific road configuration to determine the automatic driving mode. good too.

An information processing system 100 according to a fourth embodiment will be described. The information processing system 100 according to the fourth embodiment uses the operation mode determination described in the first to third embodiments to estimate the position where an event requiring caution occurs in the automobile M traveling in the automatic driving mode.

The configuration of the information processing system 100 according to the fourth embodiment differs from that of the information processing system 100 according to the first embodiment in that the server 20 includes behavior information collection means and position estimation means. Other points are the same as the configuration of the information processing system 100 according to the first embodiment.

FIG. 9 shows the configuration of an information processing system 100 according to the fourth embodiment. As shown in FIG. 9, the behavior information collecting means 23e is one of the functional blocks of the control section 23. As shown in FIG. The behavior information collecting means 23e can collect behavior information from the measurement terminals 10 mounted on a plurality of automobiles M. FIG.

The behavior information extraction means 23f is one of the functional blocks of the control section 23. FIG. The behavior information extraction means 23f can extract automatic driving behavior information of the automobile M in an automatic driving mode in which at least part of the driving operation of the automobile M is automatically performed from the collected behavior information.

The position estimation means 23g is one of the functional blocks of the control section 23. FIG. The position estimating means 23g estimates the position where the event occurs when the car M has an event requiring attention.

An event requiring attention is, for example, a situation in which any driving operation among sudden steering, sudden acceleration, sudden deceleration, or the like has occurred. In addition, the position where an event requiring caution occurs is, for example, a position where a driver encounters a factor that may require any of the driving operation of abrupt steering, sudden acceleration or sudden deceleration, abrupt steering, sudden acceleration or This is the position at which any driving operation of the sudden deceleration occurs.

For example, the position estimation means 23g estimates that an event requiring attention has occurred when the acceleration (deceleration) of the automobile M in the traveling direction falls below a predetermined threshold value (eg, -0.4G). Then, the position where the threshold value is exceeded is estimated as the position where an event requiring attention has occurred. The threshold for estimating that an event requiring attention has occurred is preferably higher than the threshold for determining the automatic driving mode.

Further, for example, the position estimating means 23g estimates that an event requiring attention has occurred when the absolute value of the acceleration in the lateral direction of the vehicle M exceeds a predetermined threshold value (for example, 0.4 G). Then, the position where the threshold value is exceeded is specified as the position where the event requiring attention has occurred. The threshold for estimating that an event requiring attention has occurred is preferably higher than the threshold for determining the automatic driving mode.

The position estimating means 23g detects the event requiring caution based on the information on the position where the event requiring caution has occurred estimated by the position estimating means 23g and the position information of the vehicle M included in the behavior information received by the communication unit 21. Estimate the origin location. For example, the position estimating means 23g identifies the position of the automobile M at the position where the event requiring attention occurred as the position where the event requiring attention occurred.

FIG. 10 shows the operation mode determination process executed by the server 20 . As shown in FIG. 10, the behavior information collection means 23c collects the behavior information of the automobile M from each of the measurement terminals 10 mounted on the plurality of automobiles M (step S501).

The behavior information extracting means 23f acquires the automatic driving behavior information of the automobile in the automatic driving mode in which at least part of the driving operation of the automobile M is automatically performed from the collected behavior information (step S502).

In the process of acquiring the automatic driving behavior information in step S502, as described in the first to third embodiments, the automatic driving mode is determined based on the behavior information, the inter-vehicle distance, and the map information, and the automatic driving behavior information is acquired. You may Further, when the behavior information generating means 15 of the measurement terminal 10 generates the behavior information, it acquires the operation mode information from the vehicle M, attaches an identifier indicating that it is automatic driving behavior information, and generates the behavior information. You may do so. Furthermore, a camera that captures an image of the interior of the vehicle may be used to recognize the movement and state of the driver and determine whether or not the vehicle is in the automatic driving mode. For example, the driver of the automobile M traveling in the automatic driving mode has a hand movement that is further away from the steering wheel than in the manual driving mode. The driver of the automobile M running in the automatic driving mode may face or look in a direction other than the traveling direction than in the manual driving mode.

The position estimating means 23g estimates the position at which an event affecting the driving operation of the automobile M occurs based on the automatic driving behavior information and the position information of the automobile M.

Specifically, the position estimation means 23g determines whether the longitudinal acceleration of the behavior information is equal to or greater than a predetermined threshold (step S503). That is, the position estimating means 23g determines whether an event requiring attention has occurred by determining whether longitudinal acceleration corresponding to sudden deceleration or sudden acceleration has occurred.

In the judgment of step S503, if the longitudinal acceleration is equal to or greater than the threshold (step S503: Y), the position estimation means 23g estimates that an event requiring caution has occurred in the vehicle M (step S504). The position estimating means 23g estimates the position where the event that should be noted occurs at the position exceeding the threshold (step S505), and records the position (step S506).

In the determination of step S503, if the longitudinal acceleration does not exceed the threshold (step S503: N), the position estimation means 23g determines whether the lateral acceleration of the behavior information is equal to or less than a predetermined threshold (step S507). That is, the position estimating means 23g determines whether an event requiring attention has occurred by determining whether or not lateral acceleration corresponding to a sharp steering wheel has occurred.

In the judgment of step S507, if the lateral acceleration is equal to or greater than the threshold (step S507: Y), the position estimation means 23g estimates that an event requiring attention has occurred in the vehicle M (step S504). The position estimating means 23g estimates the position where the event that should be noted occurs at the position exceeding the threshold (step S505), and records the position (step S506).

In the determination of step S507, if the lateral acceleration is less than the threshold (step S507: N), the position estimation means 23g estimates that no event requiring attention has occurred in the vehicle M, that is, no event has occurred. (Step S508).

In step S502, the automatic driving behavior information of the vehicle M for which at least part of the driving operation related to acceleration is automatically performed, the automatic driving behavior of the vehicle M for which at least part of the driving operation related to braking is automatically performed The information and the automatic driving behavior information of the vehicle M in which at least part of the driving operation related to steering is automatically performed may be acquired separately. By performing the processing of the present embodiment in this manner, it is possible to grasp the position where an event requiring attention occurs for each type of automatic driving operation.

As described above, according to the information processing system of the present embodiment, based on the automatic driving behavior information of the vehicle M, the position is estimated when an event requiring caution has occurred in the vehicle M. Therefore, it is possible to perform appropriate information analysis using the behavior information in the automatic driving state.

For example, by excluding the behavior information sent from the vehicle in "manual driving mode" from the acquired behavior information, events requiring attention with high accuracy due to factors in the surrounding environment of the vehicle that do not depend on individual driving skills can occur. can generate information about the location of the

An information processing system 100 according to a fifth embodiment will be described. The information processing system 100 according to the fifth embodiment differs from the information processing system 100 according to the fourth embodiment in that the measurement terminal 10 includes a camera. In other words, the position estimating means 23g adds the driving conditions of the cars located around the car M to estimate the position. Other points are the same as the configuration of the information processing system 100 according to the fourth embodiment.

FIG. 11 shows the configuration of an information processing system 100 according to the fifth embodiment. As shown in FIG. 11, the measurement terminal 10 includes a camera 17 that captures an image of the surroundings of the automobile M. As shown in FIG.

FIG. 12 shows the operation mode determination process executed by the server 20 . Note that steps S601 and S602 are the same processing as steps S501 and S502, so description thereof will be omitted.

As shown in FIG. 12, the position estimation means 23g determines whether the longitudinal acceleration of the behavior information is equal to or greater than a predetermined threshold (step S603).

If it is determined in step S603 that the longitudinal acceleration is greater than or equal to the threshold value (step S603: Y), it is determined whether or not the running state of surrounding moving bodies has affected the behavior of the automobile M (step S604). That is, in estimating the position, the position estimation means 23g excludes the position estimated due to the influence of the running state of the vehicles located around the vehicle M from the estimated position. For example, when another vehicle located around the vehicle M makes a sudden lane change or cuts in, there is a possibility that the vehicle M will be subjected to a driving operation such as sudden braking. Therefore, even if an event requiring attention occurs, the position estimating means 23g can analyze the event that requires attention peculiar to the automatic driving mode by excluding the event due to such an artificial operation. Become.

When the position estimating means 23g determines in step S604 that the driving conditions of the surrounding automobiles do not affect the behavior of the automobile M (step S604: N), it is determined that an event requiring caution has occurred in the automobile M. Estimate (step S605). The position estimating means 23g estimates a position exceeding the threshold as a position where an event requiring attention has occurred (step S606), and records the position (step S607).

If the position estimating means 23g determines in step S604 that the driving conditions of other cars in the vicinity have affected the behavior of the car M (step S604: Y), the position exceeding the threshold is regarded as an event requiring caution. is excluded from the position where is generated (step S608).

If it is determined in step S603 that the longitudinal acceleration is less than the threshold value (step S603: N), it is determined whether or not the behavior of the automobile M is affected by the running state of other mobile bodies in the vicinity (step S604). Since the description of the subsequent steps S606 to S608 is redundant, it will be omitted. Further, the processing of steps S609 to S610 is the same as the processing of steps S507 to S508 described with reference to FIG. 10, so description thereof will be omitted.

As described above, according to the information processing system of this embodiment, the position estimating means 23g excludes the position of other automobiles when the behavior of the automobile M is affected by the driving conditions of other automobiles in the vicinity. Estimate the position where the event that should occur occurred. Therefore, it is possible to perform appropriate information analysis using the behavior information in the automatic driving state while excluding the positions where the events that occurred due to human factors but should be noted occurred.

In addition, in Examples 4 and 5, the behavior information collecting means 23e may request a plurality of automobiles M to transmit probe information. Specifically, the behavior information collecting means 23e requests the automobile M traveling in the automatic driving mode to continue transmitting the behavior information to the server 20 for a predetermined time during which the automobile M travels in the automatic driving mode. may By doing so, it is possible to collect automatic driving behavior information.

100 Information processing system 10 Measurement terminal 20 Server 23a Behavior information acquisition means 23b Judgment means 23c Inter-vehicle distance acquisition means 23d Road shape acquisition means 23e Behavior information collection means 23f Behavior information extraction means 23g Position estimation means

Claims (11)

behavior information acquisition means for acquiring behavior information including acceleration in the horizontal direction with respect to the moving direction of the mobile body;
Based on the acceleration acquired by the behavior information acquisition means, when the acceleration is equal to or less than a predetermined threshold, it is determined that at least a part of the driving operation of steering the moving body is automatically performed, and the acceleration is greater than a predetermined threshold, determining means for determining that the driving operation of the moving object is being performed manually. 2. The information processing apparatus according to claim 1, wherein the behavior information is information including the acceleration of the mobile object per predetermined period. the behavior information includes the acceleration of the moving body in the longitudinal direction of the moving body;
The determining means determines whether or not at least part of the driving operation relating to acceleration of the moving body is automatically performed based on the acceleration of the moving body in the longitudinal direction of the moving body. Item 3. The information processing apparatus according to item 2. the behavior information includes the acceleration of the moving body in the longitudinal direction of the moving body;
The determination means determines whether at least a part of the driving operation relating to braking of the moving body is automatically performed based on the acceleration of the moving body in the longitudinal direction of the moving body. The information processing apparatus according to claim 2 or 3. an inter-moving body distance obtaining means for obtaining an inter-moving body distance from a moving body traveling in front of the moving body;
5. The information according to any one of claims 1 to 4, wherein said determination means determines whether said driving operation of said moving object is automatically performed based on said inter-moving object distance and said acceleration. processing equipment. Having road configuration acquisition means for acquiring road configuration information,
6. The information processing apparatus according to any one of claims 1 to 5, wherein said determination means determines whether said driving operation of said moving body is automatically performed based on the shape of said road. 7. The information processing apparatus according to claim 6, wherein the road configuration information is acquired based on map information. 7. The information processing apparatus according to claim 6, wherein the road configuration information is acquired based on image information around the moving object. a measurement terminal that measures acceleration in the left-right direction with respect to the moving direction of the mobile object;
behavior information acquisition means for acquiring the acceleration of the mobile body acquired by the measurement terminal; and an information processing device having determination means for determining that the driving operation of the moving object is being performed manually when the acceleration is greater than a predetermined threshold value. information processing system. a step of acquiring behavior information including acceleration in the horizontal direction with respect to the moving direction of the mobile object;
Based on the acceleration of the behavior information, when the acceleration is equal to or less than a threshold, it is determined that at least a part of the driving operation of steering the moving body is automatically performed, and when the acceleration is greater than a predetermined threshold. and a step of determining that the driving operation of the moving body is performed manually. to the computer,
a step of acquiring behavior information including acceleration in the horizontal direction with respect to the moving direction of the mobile object;
Based on the acceleration of the behavior information, when the acceleration is equal to or less than a threshold, it is determined that at least a part of the driving operation of steering the moving body is automatically performed, and when the acceleration is greater than a predetermined threshold. and a step of determining that the driving operation of the moving object is being manually performed.

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