JP2019185100A - Device, system, method, and program for information processing - Google Patents

Abstract

To provide an information processing device capable of accurately generating information pertaining to a location at which an event to be watched out has occurred due to a factor in an environment surrounding a vehicle.SOLUTION: An information processing device (server device 20) is provided, comprising: behavioral information collection means for collecting behavioral information of a mobile body; behavioral information extraction means configured to extract automatic driving behavior information of the mobile body in an automatic driving mode, in which at least some of driving operations for the mobile body is automatically done, from the collected behavioral information; and location estimation means configured to estimate a location at which an event that affects driving has occurred using the automatic driving behavior information and information on a location of the mobile body at which the automatic driving behavior information was collected.SELECTED DRAWING: Figure 11

Description

  The present invention relates to an information processing apparatus, an information processing system, an information processing method, and a program that provide information to a moving object.

  Analysis is performed using probe information indicating a travel history (travel position, travel speed, etc.) of a moving body such as a vehicle.

  As an apparatus for analyzing using such probe information, for example, vehicle probe information, VICS (registered trademark) (Vehicle Information and Communication System) information, and road detectors installed on roadside from vehicle detectors Driving with a support device that predicts whether or not there is a high possibility that an event that should be noted in the target vehicle will occur based on the output, and that presents information to the in-vehicle 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 Document 1 collects probe information without collecting whether the automobile is in an automatic driving state or a manual driving state in collecting probe information from a vehicle.

  For example, the position where an event that requires attention in the “manual driving state” occurs is greatly influenced by the driving operation of the driver who drives the vehicle. For this reason, the position where the conventional event that should be noted includes the influence of the driving operation of the driver who drives such a vehicle. Therefore, an example of the problem is that it is difficult to generate with high accuracy a position where an event that requires attention only due to factors in the surrounding environment of the vehicle occurs.

  The present invention has been made in view of the above points, and it is an object of the present invention to provide an information processing apparatus that generates, with high accuracy, positions at which events that should be watched only due to factors in the surrounding environment of the vehicle. .

  The information processing apparatus according to claim 1 of the present invention includes a behavior information collecting unit that collects behavior information of a mobile object, and a mobile object in an automatic operation mode in which at least a part of the driving operation of the mobile object is automatically performed. Based on the behavior information extracting means for extracting the automatic driving behavior information from the collected behavior information, and the position information of the moving body when the automatic driving behavior information and the automatic driving behavior information are collected. And a position estimating means for estimating a position where an event having an influence has occurred.

  An information processing system according to a thirteenth aspect of the present invention is a measurement terminal that performs measurement relating to a traveling state of a moving body, behavior information collecting means that is transmitted from the measurement terminal and collects behavior information of the moving body, and the behavior information Behavior information extracting means for extracting automatic driving behavior information of the moving body in an automatic driving mode in which at least a part of the driving operation of the moving body is automatically performed from the behavior information collected by the collecting means, and automatic driving behavior information And an information processing apparatus comprising position estimation means for estimating a position where an event affecting driving operation has occurred based on position information of the moving body when the automatic driving behavior information is collected. Features.

An information processing method according to claim 14 of the present invention includes a step of collecting behavior information of a moving object;
Extracting the automatic driving behavior information of the moving body from the collected behavior information in the automatic driving mode in which at least a part of the driving operation of the moving body is automatically performed; the automatic driving behavior information and the automatic And a step of estimating a position where an event affecting the driving operation has occurred, based on the position information of the moving body when the driving behavior information is collected.

  According to a fifteenth aspect of the present invention, there is provided a program that collects behavior information of a moving body in a computer and an automatic operation of the moving body in an automatic operation mode in which at least a part of the driving operation of the moving body is performed automatically. The step of extracting behavior information from the collected behavior information, and the event affecting the driving operation based on the automatic driving behavior information and the position information of the moving body when the automatic driving behavior information is collected. And a step of estimating the generated position.

1 is an overall view of an information processing system according to a first embodiment. It is a block diagram which shows the structure of the measurement terminal of Example 1, and a server. It is a flowchart which shows the information processing of the server of Example 1. It is a flowchart which shows the other information processing of the server of Example 1. It is a block diagram which shows the structure of the measurement terminal of Example 2, and a server. FIG. 10 is a flowchart illustrating information processing of a server according to the second embodiment. It is a block diagram which shows the structure of the measurement terminal of Example 3, and a server. FIG. 10 is a flowchart illustrating information processing of a server according to the third embodiment. It is a block diagram which shows the structure of the measurement terminal of Example 4, and a server. FIG. 10 is a flowchart illustrating information processing performed by a server according to a fourth embodiment. It is a block diagram which shows the structure of the measurement terminal of Example 5, and a server. FIG. 10 is a flowchart illustrating information processing of a server according to a fifth embodiment.

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

  FIG. 2 shows functional blocks of the measurement terminal 10 and the server 20 of the information processing system 100. As shown in FIG. 2, in the information processing system 100, the measurement terminal 10 and the server 20 that are mounted on each of the plurality of automobiles M are connected to be communicable.

  The measurement terminal 10 is mounted on the automobile M. The measurement terminal 10 may be a 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 the acceleration in the front-rear direction when the automobile M travels forward, and the acceleration in the left-right direction perpendicular to the front-rear direction, that is, the movement direction of the automobile M Is detected.

  The GPS (Global Positioning System) device 12 is a device configured to receive a signal (GPS signal) from a GPS satellite, and acquires position information of the automobile M.

  The communication unit 13 is an interface that is communicably connected to the measurement terminal 10 mounted on the server 20 and another vehicle 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 measurement terminal 10 including the acceleration sensor 11, the GPS device 12, and the communication unit 13.

  The behavior information calculation unit 15 is one of functional blocks of the control unit 14. The behavior information calculation unit 15 travels in front of the vehicle M from the signals of the acceleration sensor 11 and the GPS device 12, the speed of the vehicle M, the acceleration, the accelerator opening, the braking strength, the free running distance when the accelerator is off. Behavior information including the distance between 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 information relating to the behavior of the automobile M per predetermined period, for example. In the case of acceleration, for example, the acceleration of the automobile M per 15 seconds. The predetermined period can be arbitrarily determined.

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

  Further, the position of the automobile M may be acquired based on a GPS signal from the GPS device 12, for example. The position of the automobile M may be calculated based on the amount of movement from the reference position, the attitude information of the automobile M from the gyro device, or the vehicle speed information obtained from the vehicle speed pulse of the automobile M. Moreover, the behavior information calculation unit 15 may be able to acquire map information. That is, the position of the automobile M can be calculated and acquired by combining the map information with at least one of GPS information from the GPS receiver, attitude information of the automobile M from the gyro device, and vehicle speed information of the automobile M. May be.

  In the following description, the acceleration when the automobile M accelerates in the traveling direction of the automobile M is a positive acceleration, and the acceleration when the automobile M decelerates is a negative acceleration. The negative acceleration in the traveling direction is also referred to as deceleration. As for the lateral acceleration, the acceleration toward the left with respect to the traveling direction of the automobile M will be described as a positive acceleration, and the acceleration toward the right with respect to the traveling direction will be described as a negative acceleration.

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

  The control unit 23 includes, for example, a CPU (Central Processing Unit) that performs arithmetic processing, and is realized by a computer. The control unit 23 can control the operation 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 23 a is one of functional blocks of the control unit 23. The behavior information acquisition unit 23a can acquire the behavior information of the automobile M from each measurement terminal 10 mounted on the automobile M.

  The determination unit 23b is one of functional blocks of the control unit 23. The determination unit 23b determines whether or not the automobile M on which each measurement terminal 10 is mounted is in the automatic driving mode based on the acceleration included in the behavior information received by the communication unit 21.

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

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

  In addition, when the vehicle M traveling in the automatic driving mode is traveling following a vehicle traveling in front, the speed fluctuates according to the vehicle traveling ahead on a straight road, and acceleration / deceleration is minimized. There is little variation and it is smooth.

  In addition, when the vehicle M traveling in the automatic driving mode is traveling following the vehicle traveling in front, the distance between the vehicle M traveling in front of the vehicle M is constant. That is, the automobile M traveling in the automatic operation mode travels while maintaining a certain inter-vehicle distance without being influenced by the weather or time zone (daytime or nighttime).

  Note that the stopping distance of the automobile M increases as the speed range of the automobile M increases. For this reason, the inter-vehicle distance becomes longer as the speed range of the automobile M becomes faster. That is, the automobile M traveling in the automatic driving mode travels at a constant inter-vehicle distance corresponding to the traveling speed.

  On the other hand, it is difficult for the automobile M traveling in the manual operation mode to maintain a strictly constant speed. In addition, the automobile M that travels in the manual operation mode often has acceleration indicating rapid deceleration. Further, the automobile M traveling in the manual operation mode varies when the distance between the automobile and the automobile traveling in front is running and stopped.

  The determination unit 23b determines whether or not the automatic operation mode is in consideration of these factors. Here, the automatic driving mode is a driving mode of the automobile. The maneuvering mode includes a plurality of maneuvering modes that differ depending on the degree of automation of operations related to the traveling of the automobile M.

  For example, the manual operation mode corresponds to the automatic operation level 0. The automatic operation mode is assumed to be a mode corresponding to automatic operation levels 1 to 5. Here, it is assumed that the automatic driving level is an automatic driving level defined by the Japanese government or the US Department of Transportation Road Traffic Safety Administration (NHTSA).

  The automatic driving mode includes a mode for assisting at least one of an accelerator operation, a brake operation, and a steering operation (steering operation). The mode for assisting the operation is a mode for intervening in the driving operation when the driver's operation does not satisfy a predetermined condition, such as an emergency brake.

  The determination unit 23b determines whether at least one driving operation is automatically performed for each of the steering driving operation, the acceleration driving operation, and the braking driving operation of the automobile M. That is, the determination unit 23b determines that the automatic driving mode is in effect when at least one of the steering driving operation, the acceleration driving operation, and the braking driving operation of the automobile M is automatically controlled.

  The determination by the determination unit 23b is not limited to this. For example, the determination unit 23b determines whether each of the steering driving operation, the acceleration driving operation, and the braking driving operation of the automobile M is automatically performed. You may make it do. That is, it may be determined that the automatic driving mode is set when each of the steering driving operation, the acceleration driving operation, and the braking driving operation of the automobile M is automatically operated. Further, the automatic driving level may not necessarily be determined, and for example, it may be determined whether or not the automatic driving mode is set for each driving operation of an accelerator operation, a brake operation, and a steering operation.

  The storage unit 22 includes, for example, a hard disk, a flash memory, an SSD (Solid State Drive), a RAM (Random Access Memory), and the like, and can store information such as mobile object information received by the communication unit 21. Moreover, the memory | storage part 22 can memorize | store the threshold value information used when the determination means 23b determines the operation mode of the motor vehicle M. FIG. In addition, the storage unit 22 can store information serving as a reference when the means of each functional block determines. The storage unit 22 can 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 determination result by each functional block unit of the control unit 23 such as the behavior information acquisition unit 23a and the determination unit 23b.

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

  The determination unit 23b determines whether the driving operation of the automobile M is automatically performed based on the behavior information acquired in step S101, that is, the operation 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). In other words, when the automobile M is in the automatic driving mode, the acceleration or deceleration of the automobile M is operated based on a predetermined standard. For this reason, the automobile M in the automatic operation mode is traveling at a stable acceleration or deceleration along a certain standard. The determination means 23b uses such a property of the automatic driving mode to determine whether at least a part of the driving operation related to acceleration and at least a part of the driving operation related to braking are automatically performed, that is, the driving mode of the automobile M. Determine. The fixed reference is, for example, the displacement of the 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 determination unit 23b can determine that the automobile M is traveling in the automatic operation mode. That is, in the automatic operation mode, it is assumed that the acceleration is not constant and the braking operation is relatively constant, and the acceleration is relatively constant.

  If it is determined in step S102 that the longitudinal acceleration is equal to or less than the threshold (step S102: Y), the determination unit 23b determines that the vehicle M is in the automatic driving mode (step S103).

  In the determination in step S102, when the longitudinal acceleration exceeds the threshold (step S102: N), the determination unit 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 vehicle M is in the automatic driving mode, the steering of the vehicle M is operated based on a predetermined standard. For this reason, the automobile M in the automatic driving mode is traveling at a stable lateral acceleration along a certain standard. That is, in the automatic driving mode, it is assumed that a sudden steering operation (steering operation) is not performed and the acceleration is relatively constant.

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

  If it is determined in step S104 that the lateral acceleration is equal to or less than the threshold value (step S104: Y), the determination unit 23b determines that the vehicle M is in the automatic driving mode (step S103).

  If it is determined in step S104 that the lateral acceleration exceeds the threshold (step S104: N), the determination unit 23b determines that the vehicle M is in the manual operation mode (step S105).

  As described above, according to the information processing system of the present embodiment, whether or not the automobile M is in the automatic driving mode is determined based on the longitudinal acceleration and the lateral acceleration of the automobile M. Therefore, it is possible to easily determine whether the operation state of the moving body is the automatic operation state or the manual operation state with respect to the collected probe information, and it is possible to perform appropriate information analysis according to the operation 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 automatic operation mode is set. However, the determination process of the steering mode is not limited to this. For example, when either the longitudinal acceleration or the lateral acceleration is equal to or less than the threshold value, the automatic driving mode may be determined.

  FIG. 4 shows another automatic operation mode determination process executed by the server 20. Step S201 is the same process as step S101 shown in FIG. 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). If it is determined in step S202 that the longitudinal acceleration is equal to or less than the threshold (step S202: Y), the determination unit 23b determines whether the lateral acceleration of the behavior information is equal to or less than a predetermined threshold (step S203).

  If it is determined in step S203 that the lateral acceleration is equal to or less than the threshold value (step S203Y), the determination unit 23b determines that the vehicle M is in the automatic driving mode (step S204).

  If it is determined in step S202 that the longitudinal acceleration exceeds the threshold (step S202: N), the determination unit 23b determines that the vehicle M is in the manual operation mode (step S205).

  If it is determined in step S203 that the lateral acceleration exceeds the threshold value (step S203: N), the determination unit 23b determines that the automobile M is in the manual operation mode (step S205).

  Thus, by determining whether or not the automatic operation mode is set, 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 is different 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 an inter-vehicle distance acquisition unit. Other points are the same as those of the information processing system 100 according to the first embodiment.

  FIG. 5 illustrates a configuration of the 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 a car traveling in front of the car M.

  The server 20 includes an inter-vehicle distance acquisition unit 23c as a moving body distance acquisition unit. The inter-vehicle distance acquisition unit 23 c is one of functional blocks of the control unit 23. The inter-vehicle distance acquisition unit 23 c calculates the inter-vehicle distance between the automobile M and the automobile traveling ahead from the imaging information acquired from the measurement terminal 10.

  FIG. 6 shows the operation mode determination process executed by the server 20. As illustrated in FIG. 6, the inter-vehicle distance acquisition unit 23 c acquires imaging data from the measurement terminal 10, calculates a distance from the acquired imaging data to the automobile traveling in front of the automobile M, and acquires the inter-vehicle distance ( Step S301). The inter-vehicle distance acquisition unit 23c acquires a plurality of inter-vehicle distances acquired during a predetermined period (for example, 5 minutes). Specifically, the inter-vehicle distance acquisition unit 23c acquires a plurality of inter-vehicle distances according to the traveling speed of the automobile M. For example, when the automobile M travels at a constant speed of 40 km / h for 5 minutes, the inter-vehicle distance is acquired every predetermined time (for example, 10 seconds). In addition, for example, when the vehicle M travels for 5 minutes at a speed of 40 km to 60 km per hour, an inter-vehicle distance corresponding to the speed of the vehicle M is acquired every predetermined time (for example, 10 seconds).

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

  Specifically, the determination unit 23b determines whether any of the plurality of inter-vehicle distances is 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 determination unit 23b determines whether each inter-vehicle distance acquired every predetermined time is within a predetermined range of 30 to 40 m. Note that the predetermined time and the predetermined range of the inter-vehicle distance may be arbitrarily changed.

  That is, when the automobile M is in the automatic operation mode, the acceleration operation and the braking operation are performed on the automobile M based on a predetermined constant. The determination unit 23b determines the operation mode of the automobile M using such a property of the automatic driving mode.

  If it is determined in step S302 that any of the plurality of inter-vehicle distances is within a predetermined range (step S302: Y), the determination unit 23b determines that the vehicle M is in the automatic driving mode (step S303). .

  If it is determined in step S302 that at least one of the plurality of inter-vehicle distances is outside a predetermined range (step S302: N), the determination unit 23b determines that the vehicle M is in the manual operation mode (step S304). ).

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

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

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

  FIG. 7 illustrates a configuration of the 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 unit 23d is one of functional blocks of the control unit 23. The road shape acquisition unit 23d acquires the shape of the road on which the automobile M travels from the map information acquired from the measurement terminal 10.

  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 unit 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 illustrated in FIG. 8, the behavior information acquisition unit 23 a acquires behavior information of the automobile M from each measurement terminal 10 mounted on the automobile M. Further, the road shape acquisition unit 23d acquires map data from the measurement terminal 10 and acquires a road shape on which the automobile travels (step S401).

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

  Specifically, the determination unit 23b determines whether the longitudinal acceleration of the behavior information in the specific road form among the acquired road forms is equal to or less than a predetermined threshold value (step S402). Here, specific road forms include the entrance and exit of tunnels, tunnels, so-called sag points that change from downhill to uphill, highway tollgates such as ETC (Electronic Toll Collection System), curves, intersections, etc. It is.

  That is, when the automobile M is in the automatic driving mode, the driving operation is performed on the automobile M based on a predetermined standard. For example, at the entrance / exit of the tunnel, in the manual operation mode, the speed of the automobile M may change due to a change in the field of view. On the other hand, in the automatic operation mode, the speed of the automobile M is considered to be kept constant even at the entrance / exit of the tunnel. Further, when passing through a toll gate on an expressway such as ETC, the automobile M can be accelerated rapidly in the manual operation mode. On the other hand, in the automatic driving mode, it is considered that the automobile M is accelerated at a constant acceleration even when passing through a toll gate on an expressway such as ETC. The determination unit 23b determines the operation mode of the automobile M using such a property of the automatic driving mode.

  If it is determined in step S402 that the longitudinal acceleration in the form of the specific road is equal to or less than a predetermined threshold value (step S402: Y), the determination unit 23b determines that the vehicle M is in the automatic driving mode (step S402). S403).

  In the determination in step S402, when the longitudinal acceleration in the specific road form exceeds a predetermined threshold value (step S402: N), the determination unit 23b determines whether the specific road form is the same among the acquired road forms. It is determined whether 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 steering operation is performed on the automobile M based on a predetermined standard. For example, in a steering operation on a curve, unevenness may occur in the manual driving mode because the steering operation depends on the skill and sense of the driver. On the other hand, in the automatic driving mode, even if the steering operation is in a curve, the steering of the automobile M is driven based on a certain standard, so that it is considered that unevenness is unlikely to occur. The determination unit 23b determines the operation mode of the automobile M using such a property of the automatic driving mode.

  If it is determined in step S404 that the lateral acceleration is equal to or less than a predetermined threshold value (step S404: Y), the determination unit 23b determines that the vehicle M is in the automatic driving mode (step S403).

  If it is determined in step S404 that the lateral acceleration exceeds a predetermined threshold value (step S404: N), the determination unit 23b determines that the vehicle M is in the manual operation mode (step S405).

  The road shape acquisition by the road shape acquisition unit 23d is not limited to map information, and for example, the road shape may be acquired by imaging data captured by a camera, LiDAR (Light Detection and Ranging).

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

  In addition, you may implement the information processing system which concerns on the above-mentioned Example 1 thru | or Example 3 combining the structure of the server 20, respectively. For example, the determination unit 23b determines the automatic driving mode by combining each of the behavior information of the automobile M, the inter-vehicle distance with the automobile traveling in front of the automobile M, and the behavior information of the automobile M in the form of a specific road. Also good.

  An information processing system 100 according to a fourth embodiment will be described. The information processing system 100 according to the fourth embodiment estimates the position where an event that should be noted in the automobile M traveling in the automatic driving mode has occurred using the determination of the steering mode described in the first to third embodiments.

  The information processing system 100 according to the fourth embodiment is different from 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 those of the information processing system 100 according to the first embodiment.

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

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

  The position estimation unit 23g is one of functional blocks of the control unit 23. The position estimating means 23g estimates the position where the event has occurred when an event that should be noted in the automobile M occurs.

  The event to be noted is, for example, a situation in which any one of driving operations such as sudden steering, rapid acceleration, or rapid deceleration has occurred. In addition, the position where an event to be noted has occurred is, for example, a position where a factor that may require a driving operation of sudden steering, sudden acceleration, or sudden deceleration, sudden steering, sudden acceleration, or This is the position where any driving operation of sudden deceleration has occurred.

  For example, the position estimating unit 23g estimates that an event to be noted has occurred when the acceleration (deceleration) in the traveling direction of the automobile M is lower than a predetermined threshold (for example, -0.4G). Then, a position that falls below the threshold is estimated as a position where an event requiring attention has occurred. It should be noted that the threshold for estimating that an event to be noted has occurred is preferably higher than the threshold for determining the automatic operation mode.

  Further, for example, the position estimating unit 23g estimates that an event to be noted has occurred when the absolute value of the acceleration in the lateral direction of the automobile M exceeds a predetermined threshold (for example, 0.4G). Then, a position that exceeds the threshold is specified as a position where an event requiring attention has occurred. It should be noted that the threshold for estimating that an event to be noted has occurred is preferably higher than the threshold for determining the automatic operation mode.

  The position estimation unit 23g determines whether the event to be noted is based on the position information of the vehicle M included in the behavior information received by the communication unit 21 and the information on the position where the event to be noted estimated by the position estimation unit 23g has occurred. Estimate the position where it occurred. For example, the position estimating unit 23g specifies the position of the automobile M at the position where the event requiring attention has occurred as the position where the event requiring attention has occurred.

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

  The behavior information extraction unit 23f acquires the automatic driving behavior information of the automobile in the automatic driving mode in which at least a 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 information is acquired by determining the automatic driving mode based on the behavior information, the inter-vehicle distance, and the map information. May be. Further, when the behavior information generation means 15 of the measurement terminal 10 generates the behavior information, the operation mode information is acquired from the automobile M, and the behavior information is generated with an identifier indicating that it is the automatic driving behavior information. You may do it. Furthermore, it may be determined whether the driver is in the automatic driving mode by recognizing the movement or state of the driver by a camera that captures the interior of the vehicle. For example, in the driver of the automobile M traveling in the automatic driving mode, the hand movement is at a position farther from the steering wheel than in the manual driving mode. There is a possibility that the driver of the automobile M traveling in the automatic driving mode has the face direction and the line of sight facing other than the traveling direction than in the manual driving mode.

  The position estimation unit 23g estimates a position where an event affecting the driving operation of the automobile M has occurred based on the automatic driving behavior information and the position information of the automobile M.

  Specifically, the position estimation unit 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 or not an event to be noted has occurred by determining whether or not a longitudinal acceleration corresponding to rapid deceleration or rapid acceleration has occurred.

  If it is determined in step S503 that the longitudinal acceleration is equal to or greater than the threshold (step S503: Y), the position estimating unit 23g estimates that an event that should be noted in the vehicle M has occurred (step S504). The position estimating unit 23g estimates a position that exceeds the threshold as a position where an event to be noted has occurred (step S505), and records the position (step S506).

  If it is determined in step S503 that the longitudinal acceleration does not exceed the threshold (step S503: N), the position estimating unit 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 unit 23g determines whether or not an event to be noted has occurred by determining whether or not the lateral acceleration corresponding to the sudden handle has occurred.

  If it is determined in step S507 that the lateral acceleration is equal to or greater than the threshold value (step S507: Y), the position estimation unit 23g estimates that an event that should be noted in the car M has occurred (step S504). The position estimating unit 23g estimates a position that exceeds the threshold as a position where an event to be noted has occurred (step S505), and records the position (step S506).

  If it is determined in step S507 that the lateral acceleration is less than the threshold value (step S507: N), the position estimating unit 23g estimates that no event that should be noted in the car M has occurred, that is, no event has occurred. (Step S508).

  In step S502, the automatic driving behavior information of the automobile M in which at least part of the driving operation related to acceleration is automatically performed, and the automatic driving behavior of the automobile M in which at least part of the driving operation related to braking is automatically performed. The information and the automatic driving behavior information of the automobile M in which at least a part of the driving operation related to steering is automatically performed may be separately obtained. In this way, by performing the processing of the present embodiment, it is possible to grasp the position where an event to be noted has occurred for each type in which the driving operation is automatically performed.

  As described above, according to the information processing system of this embodiment, based on the automatic driving behavior information of the automobile M, the position is estimated that an event that should be noted in the automobile M has occurred. Therefore, it is possible to perform appropriate information analysis using behavior information that is in an automatic driving state.

  For example, by excluding the behavior information transmitted from the car in the “manual driving mode” from the acquired behavior information, a highly accurate cautionary event occurs due to factors in the surrounding environment of the car that do not depend on the individual driving skills. Information about the selected position can be generated.

  An information processing system 100 according to a fifth embodiment will be described. The information processing system 100 according to the fifth embodiment is different from the information processing system 100 according to the fourth embodiment in that the measurement terminal 10 includes a camera. That is, the position estimation unit 23g adds the traveling state of the automobile located around the automobile M and estimates the position. Other points are the same as those of the information processing system 100 according to the fourth embodiment.

  FIG. 11 illustrates a configuration of the 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 around the automobile M.

  FIG. 12 shows the control mode determination process executed by the server 20. Steps S601 to S602 are the same as steps S501 to S502, and thus the description thereof is omitted.

  As shown in FIG. 12, the position estimation unit 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 equal to or greater than the threshold value (step S603: Y), it is determined whether the traveling state of the surrounding moving body has affected the behavior of the automobile M (step 604). That is, the position estimation unit 23g excludes the position estimated by the influence of the traveling state of the automobile located around the automobile M from the estimated position in the estimation of the position. For example, when a lane change or so-called interruption is performed when another vehicle located around the vehicle M suddenly travels, a driving operation such as sudden braking may be performed on the vehicle M. Therefore, the position estimation unit 23g can analyze a specific event to be noted in the automatic operation mode by removing such an event caused by an artificial operation even if an event to be noted occurs. Become.

  When the position estimation unit 23g determines that the driving state of the surrounding automobile does not affect the behavior of the automobile M in the determination of step S604 (step S604: N), an event that requires attention to the automobile M has occurred. Estimate (step S605). The position estimation unit 23g estimates a position that exceeds the threshold as a position where an event to be noted has occurred (step S606), and records the position (step S607).

  When the position estimation means 23g determines in step S604 that the driving state of other surrounding vehicles has affected the behavior of the vehicle M (step S604: Y), an event that requires attention to a position that exceeds the threshold value Is excluded from the position where the error occurred (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 the running state of other surrounding moving bodies has affected the behavior of the automobile M (step 604). Subsequent processes in steps S606 to S608 are omitted because they are redundantly described. Moreover, since the process of step S609-610 is the same as the process of step S507-508 demonstrated in FIG. 10, description is abbreviate | omitted.

  As described above, according to the information processing system of the present embodiment, the position estimating unit 23g excludes the position when the driving state of another surrounding car affects the behavior of the car M, Estimate the position where the event to be performed has occurred. Accordingly, it is possible to perform appropriate information analysis using the behavior information in the automatic driving state while excluding the position where an event that should be noted but occurred due to human factors occurs.

  In the fourth and fifth embodiments, the behavior information collecting unit 23e may request a plurality of automobiles M to transmit probe information. Specifically, the behavior information collecting unit 23e requests the vehicle M traveling in the automatic driving mode to continue to transmit the behavior information to the server 20 for a predetermined time during the traveling in the automatic driving mode. May be. In this way, it is possible to collect automatic driving behavior information.

DESCRIPTION OF SYMBOLS 100 Information processing system 10 Measuring terminal 20 Server 23a Behavior information acquisition means 23b Determination 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 (15)

Behavior information collecting means for collecting behavior information of a moving object;
Behavior information extracting means for extracting the automatic driving behavior information of the moving body in the automatic driving mode in which at least a part of the driving operation of the moving body is automatically performed from the collected behavior information;
Position estimation means for estimating a position where an event affecting driving operation has occurred, based on the automatic driving behavior information and the positional information of the moving body when the automatic driving behavior information is collected. Information processing apparatus. The behavior information extraction means acquires automatic driving behavior information indicating that at least a part of the driving operation related to acceleration is automatically performed,
The position estimation means estimates the position where an event affecting driving operation has occurred based on the automatic driving behavior information and the positional information of the moving body when the automatic driving behavior information is collected. The information processing apparatus according to claim 1. The behavior information extraction means acquires automatic driving behavior information indicating that at least a part of the driving operation related to braking is automatically performed,
The position estimation means estimates the position where an event affecting driving operation has occurred based on the automatic driving behavior information and the positional information of the moving body when the automatic driving behavior information is collected. The information processing apparatus according to claim 1. The behavior information extraction means acquires automatic driving behavior information indicating that at least a part of the driving operation related to steering is automatically performed,
The position estimation means estimates the position where an event affecting driving operation has occurred based on the automatic driving behavior information and the positional information of the moving body when the automatic driving behavior information is collected. The information processing apparatus according to claim 1.   5. The information processing apparatus according to claim 1, wherein the position estimating unit estimates the position by adding a traveling state of another moving body located around the moving body. 6. .   The position estimation means, in the estimation of the position, excludes a position estimated by an influence of a traveling state of another moving body located around the moving body from the estimated position. 5. The information processing apparatus according to 5.   The information processing apparatus according to claim 1, wherein the behavior information extraction unit requests the moving body in the automatic operation mode to transmit the behavior information.   The information processing apparatus according to claim 1, wherein the behavior information includes an identifier indicating that the behavior information is the automatic driving behavior information.   The information processing apparatus according to claim 1, wherein the position estimation unit determines whether the moving body is in an automatic driving mode based on the automatic driving behavior information. The behavior information includes information on the behavior of the moving body in the front-rear direction of the moving body,
The behavior information extracting means determines whether at least a part of the driving operation related to acceleration of the moving body is automatically performed based on information on the behavior of the moving body in the front-rear direction of the moving body. The information processing apparatus according to claim 9. The behavior information includes information on the behavior of the moving body in the front-rear direction of the moving body,
The behavior information extracting means determines whether at least a part of the driving operation related to braking of the moving body is automatically performed based on information about the behavior of the moving body in the front-rear direction of the moving body. The information processing apparatus according to claim 9. The behavior information includes information on the behavior of the moving body in the left-right direction with respect to the moving direction of the moving body,
The behavior information extraction unit determines whether at least a part of the driving operation related to steering of the moving body is automatically performed based on information about the behavior of the moving body in a lateral direction with respect to a moving direction of the moving body. The information processing apparatus according to claim 9. A measuring terminal for measuring the traveling state of the moving object;
Behavior information collecting means for collecting behavior information of the mobile body transmitted from the measurement terminal, and at least a part of the driving operation of the mobile body is automatically performed from the behavior information collected by the behavior information collection means. Behavior information extracting means for extracting automatic driving behavior information of the moving body in the automatic driving mode;
An information processing apparatus comprising: position estimation means for estimating a position where an event affecting driving operation has occurred based on the automatic driving behavior information and position information of the moving body when the automatic driving behavior information is collected And an information processing system comprising: Collecting behavior information of the moving object;
Extracting the automatic driving behavior information of the moving body in the automatic driving mode in which at least a part of the driving operation of the moving body is automatically performed from the collected behavior information;
Estimating the position where an event affecting driving operation has occurred based on the automatic driving behavior information and the position information of the moving body when the automatic driving behavior information is collected. Information processing method. On the computer,
Collecting behavior information of the moving object;
Extracting the automatic driving behavior information of the moving body in the automatic driving mode in which at least a part of the driving operation of the moving body is automatically performed from the collected behavior information;
A program for executing a step of estimating a position where an event affecting driving operation has occurred based on the automatic driving behavior information and the positional information of the moving body when the automatic driving behavior information is collected.

Images