Information processing device, information processing method, program, and storage medium

Abstract

To provide an information processing device that can reliably detect accident risk locations. [Solution] The information processing device includes an information acquisition means, an identification means, and a detection means. The information acquisition means acquires location information including information relating to the vehicle's position, posture information including information relating to the vehicle's attitude, and speed information including information relating to the vehicle's speed. The identification means identifies changes in the vehicle's attitude that occur due to braking, based on the posture information and speed information. The detection means detects locations among the vehicle's positions included in the location information where the change in attitude satisfies predetermined conditions as accident risk points.

Description

Technical Field

[0001] The present invention relates to a technique for detecting accident risk locations.

Background Art

[0002] Techniques related to the detection of accident risk locations have been proposed.

[0003] Specifically, for example, Patent Document 1 discloses a method of estimating that when a change in the behavior of a host vehicle to avoid a collision is detected in a situation where the current driving environment of the host vehicle is a situation difficult to predict a collision, the change in the behavior is due to a true near-miss event.

Prior Art Documents

Patent Documents

[0004]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0005] However, according to the method disclosed in Patent Document 1, for example, there is a problem that a position where sudden braking is performed during low-speed driving may not be detected as an accident risk location.

[0006] The present invention has been made to solve the above problems, and a main object thereof is to provide an information processing apparatus capable of reliably detecting accident risk locations.

Means for Solving the Problems

[0007] The invention described in the claims is an information processing device comprising: information acquisition means for acquiring location information including information relating to the position of a vehicle; posture information including information relating to the attitude of the vehicle; and speed information including information relating to the speed of the vehicle; identification means for identifying changes in the attitude of the vehicle that occur due to braking, based on the posture information and the speed information; and detection means for detecting, among the positions of the vehicle included in the location information, a position where the change in attitude satisfies predetermined conditions as an accident risk point.

[0008] The invention described in the claims is an information processing method performed by a computer, which acquires location information including information relating to the position of a vehicle, attitude information including information relating to the attitude of the vehicle, and speed information including information relating to the speed of the vehicle, identifies changes in attitude caused by braking of the vehicle based on the attitude information and speed information, and detects as accident risk points the positions of the vehicle included in the location information where the changes in attitude satisfy predetermined conditions.

[0009] The invention described in the claims is a program executed by a computer that acquires location information including information relating to the position of a vehicle, attitude information including information relating to the attitude of the vehicle, and speed information including information relating to the speed of the vehicle, and causes the computer to perform a process to identify changes in the attitude of the vehicle that occur due to braking of the vehicle based on the attitude information and the speed information, and to detect as accident risk points locations among the vehicle's positions included in the location information where the changes in attitude satisfy predetermined conditions. [Brief explanation of the drawing]

[0010] [Figure 1] A diagram showing an example of the configuration of the guidance system according to the embodiment. [Figure 2] A diagram showing an example of the configuration of an information processing device according to the embodiment. [Figure 3] A diagram showing an example of a vehicle's sinking posture. [Figure 4] A diagram showing an example of the vehicle's return posture. [Figure 5]A figure showing a first example of a braking period specified by the information processing device according to the embodiment. [Figure 6] A figure showing a second example of the braking period specified by the information processing device according to the embodiment. [Figure 7] A figure showing a third example of the braking period specified by the information processing device according to the embodiment. [Figure 8A] A figure showing an example of the slope distribution obtained by the information processing device according to the embodiment. [Figure 8B] This figure shows an example of a pseudo-slope distribution generated from the slope distribution in Figure 8A. [Figure 9] A flowchart showing an example of processing performed by the information processing device according to the embodiment. [Figure 10] A diagram showing an example configuration of a guidance system related to a modified version. [Figure 11] A diagram showing the schematic configuration of a modified server device. [Modes for carrying out the invention]

[0011] In one preferred embodiment of the present invention, the information processing device includes: information acquisition means for acquiring location information including information relating to the position of a vehicle; posture information including information relating to the attitude of the vehicle; and speed information including information relating to the speed of the vehicle; identification means for identifying changes in the attitude of the vehicle that occur due to braking, based on the posture information and the speed information; and detection means for detecting, among the positions of the vehicle included in the location information, positions where the change in attitude satisfies predetermined conditions as accident risk points.

[0012] The above information processing apparatus includes an information acquisition means, a specifying means, and a detecting means. The information acquisition means acquires position information including information related to the position of the vehicle, attitude information including information related to the attitude of the vehicle, and speed information including information related to the speed of the vehicle. The specifying means specifies a change in attitude that occurs along with the braking of the vehicle based on the attitude information and the speed information. The detecting means detects, as an accident risk point, a position among the positions of the vehicle included in the position information where the attitude change satisfies a predetermined condition. Thereby, the accident risk point can be reliably detected.

[0013] In one aspect of the above information processing apparatus, the information acquisition means acquires, as the attitude information, information indicating a temporal change in the angular velocity in the pitch direction of the vehicle.

[0014] In one aspect of the above information processing apparatus, the specifying means specifies, as the attitude change, a change in the attitude of the vehicle that shifts from a sinking attitude to a recovery attitude when the speed of the vehicle decreases and becomes less than or equal to a predetermined speed.

[0015] In one aspect of the above information processing apparatus, the apparatus further includes a determining means for determining whether or not the attitude change that occurs from when the attitude of the vehicle starts to shift to the sinking attitude until it finishes shifting to the recovery attitude corresponds to an attitude change pattern indicating sudden braking of the vehicle, and the detecting means detects, as the accident risk point, a position where the attitude change corresponding to the attitude change pattern satisfies the predetermined condition.

[0016] In one aspect of the above information processing apparatus, the determining means determines that the attitude change corresponds to the attitude change pattern when the sum of the amounts of change in the tilt angle in the pitch direction of the vehicle from when it starts to shift to the sinking attitude until a predetermined time has elapsed is greater than or equal to a predetermined value.

[0017] In one aspect of the above information processing apparatus, the determination means determines that the posture change corresponds to the posture change pattern when the similarity between the temporal change of the vehicle posture during the period from when the vehicle posture starts to transition to the sinking posture until it finishes transitioning and the temporal change of the vehicle posture during the period from when the vehicle posture starts to transition to the return posture until it finishes transitioning is high.

[0018] In one aspect of the above information processing apparatus, the detection means accumulates a predetermined parameter obtained when the posture change corresponding to the posture change pattern occurs, and detects the accident risk point by performing statistical processing on the accumulated predetermined parameter.

[0019] In one aspect of the above information processing apparatus, the detection means sets a threshold corresponding to a frequency of occurrence lower than the mode of the distribution according to the frequency of occurrence of the predetermined parameter, and detects a position that satisfies the condition that the frequency of occurrence of the predetermined parameter is below the threshold as the accident risk point.

[0020] In one aspect of the above information processing apparatus, the detection means accumulates the cumulative tilt amount from when the vehicle posture starts to transition to the sinking posture until it finishes transitioning as the predetermined parameter.

[0021] In one aspect of the above information processing apparatus, it further has setting means for setting a reliability corresponding to the degree of necessity for sudden braking at the position detected as the accident risk point.

[0022] In another preferred embodiment of the present invention, an information processing method executed by a computer acquires position information including information related to the position of a vehicle, posture information including information related to the posture of the vehicle, and speed information including information related to the speed of the vehicle, specifies a posture change that occurs with the braking of the vehicle based on the posture information and the speed information, and detects, as an accident risk point, a position among the positions of the vehicle included in the position information where the posture change satisfies a predetermined condition. Thereby, the accident risk point can be reliably detected.

[0023] In yet another preferred embodiment of the present invention, a program executed by a computer acquires position information including information relating to the position of a vehicle, attitude information including information relating to the attitude of the vehicle, and speed information including information relating to the speed of the vehicle. Based on the attitude information and the speed information, the program identifies the change in attitude that occurred due to the braking of the vehicle, and causes the computer to perform a process to detect, among the vehicle positions included in the position information, positions where the change in attitude satisfies predetermined conditions as accident risk points. By executing this program on a computer, the above information processing device can be realized. This program can be stored and used on a storage medium. This makes it possible to reliably detect accident risk points. [Examples]

[0024] Preferred embodiments of the present invention will be described below with reference to the drawings.

[0025] [System Configuration] (Overall structure) Figure 1 shows an example of the configuration of a guidance system according to an embodiment. The guidance system 100 has an information processing device 1 that moves together with the vehicle Ve in which the user is riding. The vehicle Ve can be treated as an example of a moving object.

[0026] (Information processing device) The information processing device 1 can provide the user with information such as the route of the vehicle Ve from its starting point to its destination, and information about accident risk points along the route. The information processing device 1 can also provide route guidance to the user, who is a passenger in the vehicle Ve, to a spot specified by the user. Furthermore, the information processing device 1 can provide route guidance so that the vehicle Ve travels along the guided route. In this embodiment, the information processing device 1 can output various information related to the driving of the vehicle Ve in the form of voice and / or images. For example, the information processing device 1 can output information about guidance points corresponding to points on the route where guidance is needed. Here, guidance points include, for example, intersections where the vehicle Ve turns right or left, and other important passing points for the vehicle Ve to travel along the guided route. The information processing device 1 can provide guidance on guidance points, such as the distance from the vehicle Ve to the next guidance point and the direction of travel at that guidance point.

[0027] The information processing device 1 can acquire location information including information relating to the vehicle's position, attitude information including information relating to the vehicle's posture, and speed information including information relating to the vehicle's speed. Furthermore, the information processing device 1 can identify changes in the vehicle's posture that occur due to braking, based on the attitude information and speed information. In addition, the information processing device 1 can detect locations within the vehicle's position information where the changes in the vehicle's posture due to braking satisfy predetermined conditions as accident risk points.

[0028] The information processing device 1 may be a navigation device installed in the vehicle Ve that provides route guidance to a set destination, or it may be a mobile terminal such as a smartphone carried by the user. Alternatively, the information processing device 1 may be integrated into the vehicle Ve. In this embodiment, unless otherwise specified, the information processing device 1 will be described as a mobile terminal fixedly positioned in a predetermined location on the vehicle Ve.

[0029] Figure 2 shows an example of the configuration of an information processing device according to an embodiment. The information processing device 1 includes a communication unit 11, a storage unit 12, an input unit 13, a control unit 14, a sensor group 15, a display unit 16, a sound collection unit 17, a sound output unit 18, and an in-vehicle imaging unit 19. Each element of the information processing device 1 is interconnected via a bus line 10.

[0030] The communication unit 11 performs data communication with an external device based on the control of the control unit 14. The communication unit 11 can also acquire driving data from an external device that shows the driving status and / or driving history of multiple vehicles, such as probe data. The communication unit 11 can also acquire data from an external device that is used for route guidance, such as map data, road data, and spot data. In this embodiment, the driving status of the vehicles may be read as the movement status of the moving object. Also in this embodiment, the driving history of the vehicles may be read as the movement history of the moving object.

[0031] The memory unit 12 is composed of various storage media such as RAM (Random Access Memory), ROM (Read Only Memory), and non-volatile memory (including hard disk drives, flash memory, etc.). The memory unit 12 also stores programs for the information processing device 1 to execute predetermined processes. Furthermore, the memory unit 12 is used as the working memory for the control unit 14. Note that the programs executed by the information processing device 1 may be stored in storage media other than the memory unit 12.

[0032] The memory unit 12 stores the map DB (DataBase) 4, the spot information DB 5, and the driving DB 6.

[0033] Map DB4 contains map data and road data obtained by the communication unit 11. The map data includes, for example, data necessary for map display based on a predetermined location such as the current location of vehicle Ve. The road data includes, for example, data representing the road network by combinations of nodes and links. The road data also includes, for example, data indicating the link length and attributes of roads corresponding to each link that constitutes the road network. The data indicating road attributes may include, for example, the type of road, facilities on the road, and the name of the road. The map data and road data contained in Map DB4 can be updated to the latest data, for example, at regular intervals, according to the control of the control unit 14. In this embodiment, links can be set as sections that divide the road network in any way. For example, links in this embodiment can be set as sections of any length and / or any shape. Also, links in this embodiment may be set as sections that include nodes, or as sections that do not include nodes.

[0034] The spot information DB5 contains spot data obtained by the communication unit 11. The spot data includes data for each spot that can be set as a destination for vehicle Ve. Specifically, the spot data includes, for example, data indicating the name of the spot, data indicating the type (category) of the spot, and data indicating the evaluation of the spot. The spot data contained in the spot information DB5 can be updated to the latest data, for example, at regular intervals, according to the control of the control unit 14.

[0035] The driving DB6 contains driving data obtained by the communication unit 11. The driving data may include, for example, data related to accident risk locations detected by vehicles other than vehicle Ve. The driving data contained in the driving DB6 can be updated to the latest data, for example, at regular intervals, according to the control of the control unit 14.

[0036] The memory unit 12 stores driving status data 7, which is data showing the current driving status of vehicle Ve, and driving history data 8, which is data showing the past driving status of vehicle Ve.

[0037] The driving status data 7 includes data related to the current trip of vehicle Ve, such as the departure point of vehicle Ve, the departure date and time when vehicle Ve departed from the departure point, and the destination of vehicle Ve. The driving status data 7 also includes data related to the current trip of vehicle Ve, such as the vehicle Ve's position data, attitude data, and speed data. Furthermore, each piece of data included in the driving status data 7 is recorded, for example, when the current trip of vehicle Ve begins, and stored as driving history data 8 when the current trip of vehicle Ve ends.

[0038] The driving history data 8 includes data related to the vehicle Ve's past travels, with data recorded for each individual trip. Each entry in the driving history data 8 also includes information related to one past trip of the vehicle Ve, such as the vehicle Ve's departure point, the date and time of departure from that point, the vehicle Ve's destination, and the route from the departure point to the destination. In addition, the driving history data 8 includes data related to one past trip of the vehicle Ve, such as the vehicle Ve's position data, attitude data, and speed data.

[0039] The input unit 13 has a user interface that accepts user input. The input unit 13 may include at least one user interface, such as a button, touch panel, and remote controller. The display unit 16 displays information based on the control of the control unit 14. The display unit 16 may include at least one device, such as a display and projector. The sound collection unit 17 collects sounds from inside the vehicle Ve, especially the driver's speech. The sound collection unit 17 may include a device such as a microphone. The sound output unit 18 outputs sound based on the control of the control unit 14. The sound output unit 18 may include a device such as a speaker. The interior camera unit 19 has at least one camera for photographing the interior of the vehicle Ve. It is also desirable that the interior camera unit 19 has a camera positioned to photograph at least the area around the driver's seat.

[0040] The sensor group 15 includes various sensors that perform sensing of the vehicle Ve or the environment outside the vehicle. The sensor group 15 has an external sensor 20 and an internal sensor 21.

[0041] The external sensor 20 has one or more sensors for recognizing the surrounding environment of the vehicle Ve. The external sensor 20 may include, for example, a lidar, radar, ultrasonic sensor, infrared sensor, sonar, and camera.

[0042] The internal sensor 21 has one or more sensors for positioning the vehicle Ve. The internal sensor 21 may include, for example, a GNSS (Global Navigation Satellite System) receiver, a gyro sensor, a tilt sensor, an acceleration sensor, an IMU (Inertial Measurement Unit), and a vehicle speed sensor.

[0043] Furthermore, the sensor group 15 only needs to include sensors from which the control unit 14 can directly or indirectly derive the position, attitude, and speed of the vehicle Ve from the output of the sensor group 15 (i.e., by performing estimation processing).

[0044] The control unit 14 includes a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), and other components, and controls the entire information processing device 1. For example, the control unit 14 acquires position data, attitude data, and speed data of the vehicle Ve based on the output of one or more sensors included in the sensor group 15. The control unit 14 may also acquire data including the direction of travel of the vehicle Ve as the position data of the vehicle Ve. Furthermore, when a destination is specified by the input unit 13 or the sound collection unit 17, the control unit 14 generates route information indicating the guidance route to the destination, and provides route guidance based on this route information, the estimated position information of the vehicle Ve, and the map DB4. In this case, the control unit 14 outputs audio related to the guidance route from the sound output unit 18 and displays information related to the guidance route on the display unit 18. The control unit 14 also controls the display unit 16 to display information about the music being played, video content, or a map of the area around the current location. The control unit 14 can also be treated as an example of a computer. Furthermore, the control unit 14 has the functions of an information acquisition means, an identification means, a detection means, a determination means, and a setting means.

[0045] Furthermore, the processing performed by the control unit 14 is not limited to being implemented by software through a program, but may also be implemented by any combination of hardware, firmware, and software. Also, the processing performed by the control unit 14 may be implemented using a user-programmable integrated circuit, such as an FPGA (Field-Programmable Gate Array) or a microcontroller. In this case, the program that the control unit 14 performs in this embodiment may be implemented using this integrated circuit. Thus, the control unit 14 may be implemented using hardware other than a processor.

[0046] The configuration of the information processing device 1 shown in Figure 2 is an example, and various modifications may be made to the configuration shown in Figure 2. For example, instead of the storage unit 12 storing the map DB4 and spot information DB5, the control unit 14 may receive information equivalent to the map DB4 and spot information DB5 from a map management server (not shown) via the communication unit 11. In another example, at least one of the input unit 13, display unit 16, and sound output unit 18 may be provided inside the target vehicle as an external device to the information processing device 1, and the generated signals may be supplied to the information processing device 1. Also, at least some of the sensors in the sensor group 15 may be sensors installed on the vehicle Ve. In this case, the information processing device 1 may acquire information output by the sensors installed on the vehicle Ve from the vehicle Ve based on a communication protocol such as CAN (Controller Area Network).

[0047] [Specific example] Next, we will describe a specific example of the processing performed by the information processing device 1.

[0048] (Data acquisition) The control unit 14 reads the driving history data 8 stored in the memory unit 12 and obtains position data PD, attitude data SD, and speed data VD from the read driving history data 8. Specifically, the control unit 14 obtains, for example, data showing the time change of the latitude and longitude of the vehicle Ve, corresponding to the output of the GNSS receiver of the internal sensor 21, as position data PD. The control unit 14 also obtains, for example, data showing the time change of the attitude of the vehicle Ve in the pitch direction, corresponding to the output of the gyro sensor or tilt sensor of the internal sensor 21, as attitude data SD. The control unit 14 also obtains, for example, data showing the time change of the speed of the vehicle Ve, corresponding to the output of the vehicle speed sensor of the internal sensor 21, as speed data VD. The control unit 14 may also obtain speed data VD based on the time change of the position of the vehicle Ve included in the position data PD.

[0049] (Identification of braking period) At accident risk locations, the driver applies the brakes. Therefore, in this specific example, in order to detect accident risk locations, the process first identifies the period during which braking occurred in vehicle Ve.

[0050] The control unit 14 identifies a braking period BP that corresponds to the period during which the vehicle Ve is estimated to have braked, based on the attitude data SD and the speed data VD. Specifically, the control unit 14 identifies the braking period BP as the period during which the speed of the vehicle Ve decreases to a predetermined speed VT or less or a speed gradient VI or greater, and during which the attitude of the vehicle Ve is estimated to have changed from a sinking attitude to a return attitude. The speed gradient VI can be rephrased as a predetermined speed gradient.

[0051] Figure 3 shows an example of a vehicle's sinking posture. Figure 4 shows an example of a vehicle's return posture. The sinking posture can be represented, for example, as shown in Figure 3, where the axis PA along the pitch direction of the vehicle Ve is inclined with respect to the road surface RS. The return posture can be represented, for example, as shown in Figure 4, where the axis PA is parallel to the road surface RS. The control unit 14 can estimate that the posture of the vehicle Ve has changed from a sinking posture to a return posture if, for example, it detects in the posture data SD that the angular velocity in the pitch direction of the vehicle Ve changes from a negative value to 0 and then to a positive value. In this embodiment, it is desirable that smoothing processing to remove or reduce noise data, such as calculating a moving average, be applied to the posture data SD before processing related to the identification of the braking period BP is performed.

[0052] Figure 5 shows a first example of a braking period identified by the information processing device according to the embodiment. The first example is a case where the vehicle Ve stops due to a sudden braking operation by the driver. According to the processing described above, the control unit 14 can identify a braking period BP1, such as the one shown in Figure 5, from the attitude data SD. The waveform of the braking period BP1 shown in Figure 5 represents the time change of the angular velocity in the pitch direction of the vehicle Ve when noise data included in the attitude data SD is removed.

[0053] The braking period BP1 includes time t11, which corresponds to the moment when the vehicle Ve's attitude begins to shift to a sinking attitude; time t12, which corresponds to the moment when the vehicle Ve's attitude has finished shifting to a sinking attitude; time t13, which corresponds to the moment when the vehicle Ve's attitude begins to shift to a return attitude; and time t14, which corresponds to the moment when the vehicle Ve's attitude has finished shifting to a return attitude. Furthermore, according to the braking period BP1, the vehicle Ve's velocity is 0 at one of the timings included in the period from time t12 to time t13. Also, according to the braking period BP1, the angular velocity of the vehicle Ve in the pitch direction changes from 0 to a negative angular velocity a11 at time t11, changes from a11 to 0 at time t12, changes from 0 to a positive angular velocity a12 at time t13, and changes from a12 to 0 at time t14.

[0054] Figure 6 shows a second example of a braking period identified by the information processing device according to the embodiment. The second example is a case where the speed of the vehicle Ve decreases to below a predetermined speed due to the driver's sudden braking operation. According to the processing described above, the control unit 14 can identify a braking period BP2, such as the one shown in Figure 6, from the attitude data SD. The waveform of the braking period BP2 shown in Figure 6 represents the time change of the angular velocity in the pitch direction of the vehicle Ve when noise data included in the attitude data SD is removed.

[0055] The braking period BP2 includes time t21, which corresponds to the timing when the vehicle Ve's attitude begins to shift to a sinking attitude; time t22, which corresponds to the timing when the vehicle Ve's attitude has finished shifting to a sinking attitude; time t23, which corresponds to the timing when the vehicle Ve's attitude begins to shift to a return attitude; and time t24, which corresponds to the timing when the vehicle Ve's attitude has finished shifting to a return attitude. Furthermore, according to the braking period BP2, at one of the timings included in the period from time t22 to time t23, the speed of the vehicle Ve is greater than 0 and less than or equal to a predetermined speed VT or greater than or equal to a speed gradient VI. Furthermore, according to the braking period BP2, the angular velocity of the vehicle Ve in the pitch direction changes from 0 to a negative angular velocity a21 at time t21, changes from a21 to 0 at time t22, changes from 0 to a positive angular velocity a22 at time t23, and changes from a22 to 0 at time t24.

[0056] Figure 7 shows a third example of a braking period identified by the information processing device according to the embodiment. The third example is a case where the vehicle stops in a place where the driver expects to stop, such as when the traffic light changes to yellow or red. The third example is also a case where a braking operation is performed that corresponds to a sudden braking operation but does not correspond to an unexpected emergency braking operation. According to the above processing, the control unit 14 can identify a braking period BP3, such as the one shown in Figure 7, from the attitude data SD. The waveform of the braking period BP3 shown in Figure 7 represents the time change of the angular velocity in the pitch direction of the vehicle Ve when noise data included in the attitude data SD is removed.

[0057] The braking period BP3 includes time t31, which corresponds to the moment when the vehicle Ve's attitude begins to shift to a lowered position, and time t32, which is later than time t31. The braking period BP3 also includes time t33, which corresponds to the moment when the vehicle Ve's attitude has finished shifting to a lowered position, time t34, which corresponds to the moment when the vehicle Ve's attitude begins to shift to a return position, and time t35, which corresponds to the moment when the vehicle Ve's attitude has finished shifting to a return position. Furthermore, according to the braking period BP3, the vehicle Ve's speed is 0 at some point within the period from time t33 to time t34. Furthermore, during braking period BP3, the angular velocity of the vehicle Ve in the pitch direction changes from 0 to a negative angular velocity a31 between time t31 and time t32, changes from a31 to 0 at time t33, changes from 0 to a positive angular velocity a32 at time t34, and changes from a32 to 0 at time t35.

[0058] According to the process described above, the control unit 14 can identify the change in the vehicle Ve's attitude from a depressed attitude to a return attitude when the vehicle Ve's speed decreases to a predetermined speed VT or less as an attitude change caused by braking of the vehicle Ve.

[0059] The control unit 14 analyzes the waveform of the braking period BP to obtain the recovery time RT, which corresponds to the time required from when the vehicle Ve finishes transitioning to the sinking position until it begins to transition to the recovery position.

[0060] Specifically, the control unit 14 can, for example, acquire the time from time t12 to time t13 in braking period BP1 as the recovery time RT1 corresponding to braking period TB1 (see Figure 5). The control unit 14 can also, for example, acquire the time from time t22 to time t23 in braking period BP2 as the recovery time RT2 corresponding to braking period TB2 (see Figure 6). The control unit 14 can also, for example, acquire the time from time t33 to time t34 in braking period BP3 as the recovery time RT3 corresponding to braking period TB3 (see Figure 7).

[0061] According to the processing described above, the control unit 14 can identify the period during which a change in the vehicle's attitude occurs due to braking as the braking period BP, based on the attitude data SD and the speed data VD.

[0062] (Judgment of sudden braking) In this specific example, the control unit 14 can determine whether a change in the vehicle Ve's posture during the braking period BP was caused by a sudden and unexpected braking operation by the driver by applying the determination method described below to the change in the vehicle Ve's posture. Furthermore, in the determination method described below, the control unit 14 determines that a change in the vehicle Ve's posture that occurs when the driver performs a sudden and unexpected braking operation (first change in posture) corresponds to a change in posture due to sudden braking. Furthermore, in the determination method described below, the control unit 14 determines that a change in the vehicle Ve's posture that occurs when the driver does not perform a sudden and unexpected braking operation (second change in posture) does not correspond to a change in posture due to sudden braking.

[0063] (1) First determination method When the driver applies the brakes, the vehicle Ve sinks. Furthermore, general knowledge suggests that the more sudden and spurt the braking action performed by the driver, the greater the amount of sinking of the vehicle Ve. In this specific example, the control unit 14 determines whether or not sudden braking occurred by focusing on the amount of sinking of the vehicle Ve resulting from the braking action performed by the driver.

[0064] The control unit 14 analyzes the waveform of the braking period BP to obtain a cumulative tilt amount SA, which is equivalent to the sum of the changes in the tilt angle in the pitch direction of the vehicle Ve during the period from when the vehicle Ve begins to transition to a sinking posture until the transition is completed.

[0065] Specifically, in the first example described above, the control unit 14 can obtain the integral value of the angular velocity during the braking period BP1 from time t11 to time t12 as the cumulative slope amount SA1 (see Figure 5). In the second example described above, the control unit 14 can obtain the integral value of the angular velocity during the braking period BP2 from time t21 to time t22 as the cumulative slope amount SA2 (see Figure 6). In the third example described above, the control unit 14 can obtain the integral value of the angular velocity during the braking period BP3 from time t31 to time t33 as the cumulative slope amount SA3 (see Figure 7). In this embodiment, "cumulative slope amount" may be replaced with "sinking amount".

[0066] The control unit 14 determines whether the change in the vehicle Ve's posture that occurred during the braking period BP corresponds to a change in posture due to sudden braking. For example, the control unit 14 determines whether the change in the vehicle Ve's posture corresponds to a change in posture due to sudden braking by performing a threshold check on the sum of the changes in the pitch-direction tilt angle of the vehicle Ve from the time the vehicle Ve begins to transition to a lowered posture until a predetermined time TF has elapsed. The predetermined time TF is set to be a time shorter than the time it takes for the vehicle Ve to transition to a lowered posture from the time it begins to transition to the lowered posture until it has finished, as shown in Figures 5 to 7.

[0067] Specifically, in the first example described above, the control unit 14 can determine that the change in the vehicle Ve's attitude during braking period BP1 is due to sudden braking because the sum of the changes in the pitch angle of the vehicle Ve from time t11 until a predetermined time TF has elapsed is greater than or equal to a predetermined value. Also, in the second example described above, the control unit 14 can determine that the change in the vehicle Ve's attitude during braking period BP2 is due to sudden braking because the sum of the changes in the pitch angle of the vehicle Ve from time t21 until a predetermined time TF has elapsed is greater than or equal to a predetermined value. Also, in the third example described above, the control unit 14 can determine that the change in the vehicle Ve's attitude during braking period BP3 is not due to sudden braking because the sum of the changes in the pitch angle of the vehicle Ve from time t31 until a predetermined time TF has elapsed is less than a predetermined value.

[0068] According to the process described above, the control unit 14 can determine whether the change in the vehicle Ve's posture from the time it begins to transition to a sunk posture until it finishes transitioning to a return posture corresponds to a posture change pattern indicating sudden braking of the vehicle Ve. Furthermore, according to the process described above, the control unit 14 can determine that the change in the vehicle Ve's posture corresponds to a posture change pattern indicating sudden braking if the sum of the changes in the pitch direction of the vehicle Ve from the time it begins to transition to a sunk posture until a predetermined time TF has elapsed is greater than or equal to a predetermined value. Furthermore, according to the process described above, the control unit 14 can determine that the change in the vehicle Ve's posture corresponds to a posture change pattern indicating sudden braking if the pitch direction of the vehicle Ve changes sharply during the period from the time it begins to transition to a sunk posture until it finishes transitioning.

[0069] (2) Second determination method When the driver performs a braking operation, the vehicle Ve sinks. Furthermore, according to the applicant's findings obtained through simulations, the posture change pattern of the vehicle Ve from the time it sinks until it recovers changes depending on the speed of the braking operation performed by the driver. In this specific example, the control unit 14 focuses on the posture change pattern of the vehicle Ve accompanying the braking operation performed by the driver to determine whether or not sudden braking has occurred.

[0070] The control unit 14 may determine whether the change in the vehicle's attitude during the braking period BP corresponds to an attitude change pattern indicating sudden braking, based on the similarity between the time change (waveform) of the vehicle's attitude during the period from when the vehicle's attitude begins to transition to a sinking attitude until the transition is completed, and the time change (waveform) of the vehicle's attitude during the period from when the vehicle's attitude begins to transition to a return attitude until the transition is completed.

[0071] Specifically, in the first example described above, the control unit 14 can determine that the change in the vehicle Ve's posture during braking period BP1 corresponds to a posture change pattern indicating sudden braking because there is a high similarity between the waveform of the posture change during sinking from time t11 to time t12 and the waveform of the posture change during recovery from time t13 to time t14. Also, in the second example described above, the control unit 14 can determine that the change in the vehicle Ve's posture during braking period BP2 corresponds to a posture change pattern indicating sudden braking because there is a high similarity between the waveform of the posture change during sinking from time t21 to time t22 and the waveform of the posture change during recovery from time t23 to time t24. Furthermore, in the third example described above, the control unit 14 can determine that the change in the vehicle Ve that occurred during the braking period BP3 does not correspond to a change in posture pattern indicating sudden braking because the waveform of the change in posture during the sinking period from time t31 to time t33 and the waveform of the change in posture during the recovery period from time t34 to time t35 have low similarity.

[0072] In this embodiment, if the shapes of the waveforms of the attitude change during sinking and the waveform of the attitude change during recovery are similar, it can be said that the similarity is high, and if the shapes of the two waveforms are not similar, it can be said that the similarity is low. In the case of the first and second examples described above, the control unit 14 can determine that the attitude change pattern indicates sudden braking because the shapes of the waveforms during sinking and recovery are both rectangular. In the case of the third example described above, the control unit 14 can determine that the attitude change pattern does not correspond to a sudden braking pattern because the shape of the waveform during sinking is rectangular and the shape of the waveform during recovery is trapezoidal.

[0073] (Removal of slope caused by road gradient) The control unit 14 performs a process to remove the amount of inclination caused by the road gradient from the cumulative inclination amount SA for the braking period BP during which it is determined that a change in the vehicle's attitude occurred due to sudden braking of the vehicle Ve. The control unit 14 can remove the amount of inclination caused by the road gradient from the cumulative inclination amount SA by, for example, performing a process based on acceleration calculated using speed data VD. In the following description, we will explain the case in which the cumulative inclination amount SB is obtained by removing the amount of inclination caused by the road gradient from the cumulative inclination amount SA.

[0074] (Detection of accident risk locations specific to the user) In detecting accident risk points, it is desirable to eliminate differences in individual user driving characteristics, such as the strength and speed of brake application during driving. Therefore, in this specific example, accident risk points are detected by statistically processing data for each user. The control unit 14 stores in the storage unit 12 data in which braking data BD, which includes information related to the sudden braking of the vehicle Ve, is associated with the attitude data SD obtained from the driving history data 8. The braking data BD includes, for example, information relating to the braking period BP during which it is determined that a change in the vehicle Ve's attitude occurred due to sudden braking, the cumulative tilt amount SB and recovery time RT corresponding to the braking period BP, and the braking position BL, which corresponds to the position of the vehicle Ve during the braking period BP, as included in the position data PD. For the sake of explanation, the data in which braking data BD is associated with attitude data SD will be referred to as attitude data SW.

[0075] The control unit 14 reads multiple attitude data SW corresponding to multiple past runs of the vehicle Ve from the storage unit 12, and detects accident risk locations RP specific to the user of the vehicle Ve by applying a predetermined statistical index to the cumulative tilt amount SB of the braking data BD contained in each of the read attitude data SW.

[0076] Here, we will explain a specific example of the process involved in detecting accident risk locations (RPs).

[0077] Figure 8A is a diagram showing an example of a slope amount distribution acquired by the information processing device according to the embodiment. The control unit 14 acquires a slope amount distribution DP1 as a distribution corresponding to the frequency of occurrence of multiple cumulative slope amounts SB, for example, as shown in Figure 8A. The slope amount distribution DP1 is acquired as a distribution that includes cumulative slope amounts SB above a threshold TH, while not including cumulative slope amounts SB below the threshold TH. Furthermore, the slope amount distribution DP1 is acquired as a distribution where, for example, the frequency of occurrence of cumulative slope amounts SB is maximum at the threshold TH, and the frequency of occurrence decreases as the cumulative slope amount SB increases. The threshold TH corresponds to, for example, the value used as a determination criterion for determining whether or not it corresponds to a change in posture associated with sudden braking in the first determination method described above.

[0078] Figure 8B shows an example of a pseudo-slope distribution generated from the slope distribution in Figure 8A. The control unit 14 generates a pseudo-slope distribution DP2, such as the one shown in Figure 8B, by adding a pseudo-distribution to the slope distribution DP1 that shows the frequency of occurrence of cumulative slope amounts SB below the threshold TH. The portion of the pseudo-slope distribution DP2 above the threshold TH has the same distribution as the slope distribution DP1. The portion of the pseudo-slope distribution DP2 below the threshold TH can be obtained, for example, by setting the frequency of occurrence of cumulative slope amounts SB corresponding to the threshold TH of the slope distribution DP1 as a reference axis, and projecting the distribution of cumulative slope amounts SB greater than the threshold TH onto a position symmetrical to the reference axis. In other words, the portion of the pseudo-slope distribution DP2 below the threshold TH represents a pseudo-distribution showing the frequency of occurrence of cumulative slope amounts SB that have not actually been obtained. Furthermore, the pseudo-slope distribution DP2 can be treated as a normal distribution.

[0079] The control unit 14 calculates the standard deviation σ of the pseudo-slope distribution DP2 and sets three types of thresholds corresponding to the calculated standard deviation σ in the portion of the pseudo-slope distribution DP2 that is greater than or equal to the threshold TH. Specifically, the control unit 14 sets a threshold TZ1 corresponding to +1.5σ of the pseudo-slope distribution DP2, a threshold TZ2 corresponding to +2σ of the pseudo-slope distribution DP2, and a threshold TZ3 corresponding to +3σ of the pseudo-slope distribution DP2.

[0080] The control unit 14 acquires the cumulative slope amount SB that falls within the range of threshold TZ1 or greater and threshold TZ2 or less as cumulative slope amount SB1. The control unit 14 also acquires the cumulative slope amount SB that falls within the range of threshold TZ2 or greater and threshold TZ3 or less as cumulative slope amount SB2. The control unit 14 also acquires the cumulative slope amount SB that is greater than or equal to threshold TZ3 as cumulative slope amount SB3. Note that the cumulative slope amount SB that is less than threshold TZ1 is not used in the processing related to the detection of accident risk points RP in this specific example.

[0081] The control unit 14 detects the braking position BL corresponding to the cumulative tilt amount SB1 as the accident risk point RP1 specific to the user of vehicle Ve. The control unit 14 also detects the braking position BL corresponding to the cumulative tilt amount SB2 as the accident risk point RP2 specific to the user of vehicle Ve. The control unit 14 also detects the braking position BL corresponding to the cumulative tilt amount SB3 as the accident risk point RP3 specific to the user of vehicle Ve.

[0082] According to the process described above, the control unit 14 can detect accident risk locations RP by accumulating the cumulative tilt amount SB obtained when a change in posture corresponding to the posture change pattern caused by sudden braking occurs, and by performing statistical processing on the tilt amount distribution DP1 including the accumulated cumulative tilt amount SB. Furthermore, according to the process described above, the control unit 14 can set a threshold TZ corresponding to an occurrence frequency lower than the mode of the pseudo-tilt amount distribution DP2 in the portion of the pseudo-tilt amount distribution DP2 that is above the threshold TH. Furthermore, according to the process described above, the control unit 14 can detect accident risk locations RP that satisfy the condition that the occurrence frequency of the cumulative tilt amount SB is less than or equal to the threshold TZ. In other words, the control unit 14 can detect accident risk locations RP corresponding to the user of the vehicle Ve, among the locations of the vehicle Ve included in the location data PD, where the occurrence frequency of the cumulative tilt amount SB is less than or equal to a predetermined value.

[0083] According to the process described above, the control unit 14 can detect accident risk locations RP while eliminating differences in vehicle-specific performance, such as suspension stiffness. Furthermore, according to the process described above, the control unit 14 can detect accident risk locations RP while eliminating differences in user-specific driving characteristics, such as the strength and speed of brake application during driving.

[0084] (Setting the confidence level) Based on the processing results obtained by applying a predetermined statistical index to the cumulative tilt amount SB, the control unit 14 sets a confidence level RD corresponding to the degree of need for emergency braking at the braking position BL detected as the accident risk point RP corresponding to the cumulative tilt amount SB. Through this processing, for example, if the cumulative tilt amount SB1 is obtained as a processing result, the control unit 14 can set the lowest confidence level (confidence level: low) in three confidence levels as the confidence level RD1 for the accident risk point RP1 corresponding to the cumulative tilt amount SB1. Furthermore, through the aforementioned processing, for example, if the cumulative tilt amount SB2 is obtained as a processing result, the control unit 14 can set the intermediate confidence level (confidence level: medium) in three confidence levels as the confidence level RD2 for the accident risk point RP1 corresponding to the cumulative tilt amount SB2. Furthermore, through the aforementioned processing, if the cumulative tilt amount SB3 is obtained as a processing result, the control unit 14 can set the highest confidence level (confidence level: high) in three confidence levels as the confidence level RD3 for the accident risk point RP3 corresponding to the cumulative tilt amount SB3.

[0085] The control unit 14 adds information related to the reliability level RD as additional information AJ for the accident risk location RP. Through this process, the control unit 14 can, for example, add information indicating reliability level RD1 as additional information AJ1 for accident risk location RP1. Furthermore, through the aforementioned process, the control unit 14 can, for example, add information indicating reliability level RD2 as additional information AJ2 for accident risk location RP2. Furthermore, through the aforementioned process, the control unit 14 can, for example, add information indicating reliability level RD3 as additional information AJ3 for accident risk location RP3.

[0086] Furthermore, the control unit 14 may include in the additional information AJ information an indication of the date and time when the braking period BP corresponding to the cumulative tilt amount SB used to detect the accident risk point RP occurred. The control unit 14 may also include in the additional information AJ information an indication of the recovery time RT corresponding to the accident risk point RP. Furthermore, the control unit 14 may also include in the additional information AJ information an indication of the user of the vehicle Ve in which the accident risk point RP was detected.

[0087] The control unit 14 transmits processing result data DQ, which includes the accident risk location RP with the additional information AJ attached, to an external device such as a cloud server.

[0088] (Processing by external device) The external device stores multiple processing result data DQ transmitted from vehicle Ve and other vehicles. The external device also merges the accident risk location RP contained in each of the stored processing result data DQ based on the additional information AJ contained in each of the processing result data DQ, and distributes the accident risk location data DR, which indicates the merged accident risk location RP, to the information processing device 1 of vehicle Ve and other vehicles.

[0089] The control unit 14 can obtain the latest information regarding accident risk location RP by referring to accident risk location data DR received from an external device. Furthermore, the control unit 14 can store the accident risk location data DR received from an external device in the driving DB6 of the storage unit 12 as data included in the driving data. The control unit 14 can also notify the user, for example, that the vehicle Ve's current position is approaching an accident risk location RP included in the accident risk location data DR, based on the accident risk location data DR received from an external device, through a screen display on the display unit 16 and / or audio output from the sound output unit 18. Additionally, the control unit 14 can display the accident risk location RP included in the accident risk location data DR on a map of the area surrounding the vehicle Ve's current position, based on the accident risk location data DR received from an external device.

[0090] The control unit 14 may, for example, store processing result data similar to the processing result data DQ in the storage unit 12. In such a case, the control unit 14 may, based on the processing result data read from the storage unit 12, notify the user that the current position of the vehicle Ve is approaching the accident risk point RP included in the data, by displaying it on the screen of the display unit 16 and / or by outputting sound from the sound output unit 18.

[0091] [Processing flow] Next, we will explain the processing flow performed by the information processing device 1. Figure 9 is a flowchart showing an example of processing performed by the information processing device according to the embodiment.

[0092] First, the information processing device 1 acquires position data, attitude data, and speed data from the driving history data 8 (step S11).

[0093] Next, the information processing device 1 identifies a braking period corresponding to the period during which the vehicle Ve is estimated to have braked, based on the attitude data and speed data acquired in step S11 (step S12).

[0094] Next, the information processing device 1 determines whether the change in the vehicle Ve's posture that occurred during the braking period identified in step S12 corresponds to a change in posture due to sudden braking (step S13).

[0095] If the information processing device 1 determines that the change in the vehicle Ve's posture that occurred during the braking period corresponds to a change in posture due to sudden braking (step S13: YES), it stores data in the storage unit 12 that associates braking data, including information related to the sudden braking of the vehicle Ve, with the posture data acquired in step S11 (step S14). If the information processing device 1 determines that the change in the vehicle Ve's posture that occurred during the braking period does not correspond to a change in posture due to sudden braking (step S13: NO), it performs the processing in step S18 described below.

[0096] The information processing device 1 detects accident risk locations specific to the user of vehicle Ve by applying predetermined statistical indicators to multiple attitude data read from the storage unit 12 (step S15).

[0097] Next, the information processing device 1 sets the confidence level of the accident risk location detected in step S15 (step S16). The information processing device 1 also transmits processing result data, including the accident risk location detected in step S15 and the confidence level set in step S16, to an external device (step S17).

[0098] After performing the processing in step S13 or step S17, the information processing device 1 receives accident risk location data, which includes accident risk locations merged according to the data transmitted from its own vehicle (vehicle Ve) and other vehicles (vehicles other than vehicle Ve) (step S18), and stores the received accident risk location data in the storage unit 12. The information processing device 1 can, if necessary, inform the user of information related to the accident risk locations included in the accident risk location data stored in the storage unit 12.

[0099] For example, if the information processing device 1 determines in step S13 that the change in posture is not due to sudden braking, it may return to step S11.

[0100] The information processing device 1 may, for example, determine in step S13 that the change in posture due to sudden braking does not apply, and then perform a determination regarding the frequency of receiving accident risk location data. Alternatively, the control unit 14 may, for example, skip step S18 and terminate processing if, in the aforementioned determination regarding the frequency of receiving data, it determines that the interval from the latest receiving date and time of the accident risk location data to the present is less than a predetermined interval. Alternatively, the control unit 14 may, for example, perform the processing in step S18 if, in the aforementioned determination regarding the frequency of receiving data, it determines that the interval from the latest receiving date and time of the accident risk location data to the present is greater than or equal to a predetermined interval.

[0101] As described above, according to this embodiment, it is possible to determine whether or not sudden braking occurred in response to an unexpected and sudden braking operation by the driver, based on the change in the pitch direction attitude of the vehicle Ve that occurred during the braking period. Furthermore, according to this embodiment, by applying a predetermined statistical index to multiple cumulative tilt amounts SB caused by the sudden braking of the vehicle Ve, it is possible to detect accident risk locations specific to the user of the vehicle Ve. Therefore, according to this embodiment, accident risk locations can be reliably detected. In addition, according to this embodiment, for example, locations where sudden braking occurred on roads where low-speed driving is required, such as residential roads, can be detected as accident risk locations. Furthermore, according to this embodiment, since data from locations where sudden braking frequently occurs is excluded when detecting accident risk locations, for example, locations where sudden braking occurred on roads with extremely low traffic volume can be detected as accident risk locations.

[0102] <Variation> Next, we will describe some modifications suitable for the above-described embodiments. For simplicity, detailed explanations of the parts to which the previously described processes can be applied will be omitted as appropriate. Furthermore, the following modifications may be applied in combination to the above-described embodiments.

[0103] [Example 1] The control unit 14 may, for example, if the information processing device 1 is a mobile terminal such as a smartphone, determine whether or not the posture data SD was recorded while the mobile terminal was in a fixed position before performing the processing in step S11, or in conjunction with the processing in step S12.

[0104] The control unit 14 can determine, for example, that the attitude data SD was recorded with the mobile device in a fixed position if it detects, based on the output of the gyro sensor of the internal sensor 21, that a force equivalent to Earth's gravity (1G) is being applied to the mobile device. Alternatively, the control unit 14 can determine, for example, that the attitude data SD was recorded with the mobile device not in a fixed position if it detects, based on the output of the gyro sensor of the internal sensor 21, that no force equivalent to Earth's gravity is being applied to the mobile device.

[0105] If the control unit 14 determines that attitude data SD has been recorded while the mobile terminal is not fixed in place, it may skip the processes from steps S11 to S17 in Figure 9 and proceed to the process in step S18. Alternatively, if the control unit 14 determines that attitude data SD has been recorded while the mobile terminal is not fixed in place, it may set the confidence level RD of the accident risk point RP to a relatively low level in the process in step S16 in Figure 9. Furthermore, if the control unit 14 determines that attitude data SD has been recorded while the mobile terminal is not fixed in place, it may, for example, send data including information indicating that the determination has been made as processing result data DQ to an external device.

[0106] [Differentiation 2] According to the embodiment described above, at least some of the processes performed by the information processing device 1 may be performed by a server device that communicates with the information processing device 1.

[0107] Figure 10 shows an example configuration of a modified guidance system. The guidance system 100A includes an information processing device 1A and a server device 200. The information processing device 1A and the server device 200 communicate data via a network 150.

[0108] Information processing device 1A has the same configuration as information processing device 1 described in the above embodiment (see Figure 2). Note that if the server device 200 performs processing based on data stored in map DB4, spot information DB5, and driving DB6, information processing device 1A does not need to store this data. Furthermore, information processing device 1A transmits information input at the input unit 13, and information obtained by the sensor group 15, etc., to the server device 200.

[0109] Figure 11 is a diagram showing the schematic configuration of a modified server device. As shown in Figure 11, the server device 200 includes a communication unit 301, a storage unit 302, and a control unit 304. The communication unit 301, the storage unit 302, and the control unit 304 are interconnected via a bus line 300.

[0110] The communication unit 301 transmits and receives various data via the network 150 based on the control of the control unit 304. The storage unit 302 is composed of, for example, an HDD. The storage unit 302 also stores data that can be used to detect accident risk locations RP, such as map DB4, spot information DB5, and driving DB6. The control unit 304 has a CPU and memory such as ROM and RAM, and performs overall control of the server device 200 by executing programs stored in memory. The control unit 304 can also be treated as an example of a computer.

[0111] With the configuration described above, the control unit 304 can acquire the position data PD, attitude data SD, and speed data VD of the vehicle Ve transmitted from the information processing device 1A. The control unit 304 can also identify the braking period BP of the vehicle Ve based on the attitude data SD and speed data VD of the vehicle Ve. Furthermore, if the control unit 304 determines that the change in the attitude of the vehicle Ve that occurred during the braking period BP corresponds to a change in attitude due to sudden braking, it can store data associating the braking data BD with the attitude data SD in the storage unit 302. In addition, the control unit 304 can detect accident risk locations RP specific to the user of the vehicle Ve by applying a predetermined statistical index to a plurality of attitude data SDs read from the storage unit 302. The control unit 304 can also set the confidence level RD of the accident risk locations RP. Furthermore, the control unit 304 can merge the accident risk locations RP contained in the data transmitted from the vehicle Ve and the data transmitted from vehicles other than the vehicle Ve, and acquire accident risk location data DR including the merged accident risk locations RP. Accident risk location data (DR) is distributed from the communication unit 301 to the information processing device 1A, such as the vehicle Ve.

[0112] According to this modified example, the same processing performed in server device 200 may be performed in a server system having multiple server devices.

[0113] In each of the embodiments described above, the program can be stored using various types of non-transitory computer-readable medium and supplied to a control unit, which is a computer. Non-transitory computer-readable medium includes various types of tangible storage medium. Examples of non-transitory computer-readable medium include magnetic storage medium (e.g., flexible disks, magnetic tapes, hard disk drives), magneto-optical storage medium (e.g., magneto-optical disks), CD-ROM (Read Only Memory), CD-R, CD-R / W, and semiconductor memory (e.g., mask ROM, PROM (Programmable ROM), EPROM (Erasable PROM), flash ROM, RAM (Random Access Memory)).

[0114] Although the present invention has been described above with reference to embodiments, the present invention is not limited to the above embodiments. Various modifications to the structure and details of the present invention can be made that are understandable to those skilled in the art within the scope of the present invention. That is, the present invention naturally includes the full disclosure, including the claims, and various modifications and alterations that those skilled in the art could make in accordance with the technical idea. Furthermore, each disclosure of the above-mentioned patent documents and other references is incorporated herein by reference. [Explanation of Symbols]

[0115] 1. 1A Information Processing Device 11, 301 Communications Department 12, 302 Storage section 13 Input section 14, 304 Control Unit 15 Sensor Groups

Claims

1. Information acquisition means for acquiring location information including information relating to the position of the vehicle, attitude information including information relating to the attitude of the vehicle, and speed information including information relating to the speed of the vehicle, A means for identifying the change in the vehicle's posture that occurs as a result of braking, based on the aforementioned posture information and speed information, A detection means for detecting, among the vehicle's position included in the position information, a position where the change in attitude satisfies predetermined conditions as an accident risk point, An information processing device having

2. The information processing apparatus according to claim 1, wherein the information acquisition means acquires information indicating the time change of the angular velocity in the pitch direction of the vehicle as attitude information.

3. The information processing device according to claim 2, wherein the identifying means identifies as the change in the vehicle's posture from a lowered posture to a restored posture when the vehicle's speed decreases to below a predetermined speed.

4. The system further includes determination means for determining whether the change in the vehicle's posture from the moment it begins to transition to the lowered posture until it completes its transition to the restored posture corresponds to a change in posture pattern indicating sudden braking of the vehicle. The information processing device according to claim 3, wherein the detection means detects a position where the posture change corresponding to the posture change pattern satisfies the predetermined conditions as the accident risk point.

5. The information processing device according to claim 4, wherein the determination means determines that the change in posture corresponds to the posture change pattern when the sum of the changes in the pitch angle of the vehicle from the time it begins to transition to the sinking posture until a predetermined time has elapsed is greater than or equal to a predetermined value.

6. The information processing device according to claim 4, wherein the determination means determines that the change in posture corresponds to the posture change pattern when there is a high similarity between the time change in the posture of the vehicle during the period from when the posture of the vehicle begins to transition to the sinking posture until the transition is completed and the time change in the posture of the vehicle during the period from when the posture of the vehicle begins to transition to the return posture until the transition is completed.

7. The information processing device according to claim 4, wherein the detection means stores predetermined parameters obtained when a change in posture corresponding to the posture change pattern occurs, and detects the accident risk location by performing statistical processing on the stored predetermined parameters.

8. The information processing device according to claim 7, wherein the detection means sets a threshold corresponding to an occurrence frequency lower than the mode of the distribution according to the occurrence frequency of the predetermined parameter, and detects a location that satisfies the condition that the occurrence frequency of the predetermined parameter is less than or equal to the threshold as the accident risk location.

9. The information processing device according to claim 7, wherein the detection means stores the cumulative amount of inclination from the time the vehicle's posture begins to transition to the sinking posture until the transition is completed, as a predetermined parameter.

10. The information processing device according to any one of claims 1 to 9, further comprising setting means for setting a reliability level corresponding to the degree of need for emergency braking at the location detected as an accident risk point.

11. A method of information processing performed by a computer, Location information including information relating to the vehicle's position, attitude information including information relating to the vehicle's attitude, and speed information including information relating to the vehicle's speed are acquired. Based on the aforementioned attitude information and speed information, the change in attitude that occurred as a result of braking the vehicle is identified. An information processing method for detecting, among the vehicle's position included in the position information, a position where the change in attitude satisfies predetermined conditions as an accident risk point.

12. A program executed by a computer, Location information including information relating to the vehicle's position, attitude information including information relating to the vehicle's attitude, and speed information including information relating to the vehicle's speed are acquired. Based on the aforementioned attitude information and speed information, the change in attitude that occurred as a result of braking the vehicle is identified. A program that causes a computer to perform a process to detect, among the vehicle's positions included in the position information, positions where the change in attitude satisfies predetermined conditions as accident risk points.

13. A storage medium storing the program described in claim 12.

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