Information processor, information processing method, and information processing program

Abstract

To provide an information processor, an information processing method, and an information processing program for estimating traffic conditions on roads.SOLUTION: An information processor includes: an acquisition unit for acquiring a plurality of vehicle travel information of vehicles that have traveled along a road segment; a first identification unit that obtains a travel speed for each vehicle based on each of the plurality of vehicle travel information obtained by the acquisition unit, and identifies a first travel speed that is a predetermined upper vehicle speed fraction from a maximum speed among the travel speeds in the road segment for each vehicle; a second identification unit that identifies a first traveling speed that is a predetermined selected fraction of the first travel speed for each of the plurality of vehicles identified by the first identification unit; and an estimation unit that estimates a traffic condition of the vehicles on the road segment based on the first travel speed identified by the second identification unit.SELECTED DRAWING: Figure 1

Description

[Technical field]

[0001] The present disclosure relates to an information processing device, an information processing method, and an information processing program. [Background technology]

[0002] Conventionally, there exists a device that acquires multiple probe raw information (see Patent Document 1). The device creates multiple pieces of time-series trip information based on the probe raw information. The time-series trip information excludes information on long-term parking, etc. The device creates road traffic information based on the time-series trip information. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] JP 2010-205089 A Summary of the Invention [Problem to be solved by the invention]

[0004] Road traffic information is generated based on vehicle travel information generated by vehicles that actually travel on roads. However, among the multiple vehicles traveling on a road, there are vehicles that travel at various speeds, such as vehicles that travel at relatively fast speeds and vehicles that travel at relatively slow speeds. Therefore, even when road traffic information for a certain road section is generated, the accuracy of the road traffic information may be reduced due to differences in the travel speeds of the multiple vehicles traveling on the road section.

[0005] The present disclosure provides an information processing device, an information processing method, and an information processing program for estimating a traffic condition of a road. [Means for solving the problem]

[0006] An information processing device of one embodiment includes an acquisition unit that acquires multiple pieces of vehicle driving information of vehicles that have traveled through a road section, a first identification unit that acquires the driving speed of each vehicle based on each of the multiple pieces of vehicle driving information acquired by the acquisition unit and identifies a first driving speed that is a predetermined upper vehicle speed quantile from the maximum speed among the driving speeds of each vehicle in the road section, a second identification unit that identifies a first driving speed that is a predetermined selection quantile among the first driving speeds of each of the multiple vehicles identified by the first identification unit, and an estimation unit that estimates vehicle traffic conditions in the road section based on the first driving speed identified by the second identification unit. Effect of the Invention

[0007] The information processing device, the information processing method, and the information processing program disclosed herein can estimate the degree of congestion of a road. [Brief description of the drawings]

[0008] [Figure 1] FIG. 1 is a diagram illustrating an information processing device according to an embodiment. [Diagram 2] FIG. 1 is a block diagram illustrating an information processing device according to an embodiment. [Diagram 3] 1A is a diagram for explaining an example of identifying a first traveling speed, in which (A) is a diagram for explaining a transition of the vehicle speed of each of a plurality of vehicles, and a maximum speed and a first traveling speed in each vehicle speed transition, and (B) is a diagram for explaining the first traveling speed identified by a second identification unit. [Figure 4] 1 is a flowchart illustrating an information processing method according to an embodiment. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0009] An embodiment will be described below.

[0010] [Overview of information processing device 100] First, an overview of an information processing device 100 according to an embodiment will be described. FIG. 1 is a diagram illustrating an information processing device 100 according to an embodiment.

[0011] The information processing device 100 may be configured as an estimation device or the like that estimates the traffic conditions (congestion level) of the vehicle 300 traveling on a road (for example, a general road, etc.). The information processing device 100 may also be configured as a guidance device or the like that provides various kinds of guidance based on the traffic conditions (congestion level) of the vehicle 300. The information processing device 100 is not limited to the device of the above example, and may constitute various kinds of devices, etc. The information processing device 100 may be a computer such as a server, a desktop, a laptop, a tablet, or a smartphone.

[0012] The information processing device 100 acquires a plurality of pieces of vehicle travel information 400 of the vehicle 300 that has traveled a road section. That is, the information processing device 100 acquires a plurality of pieces of vehicle travel information 400 (for example, 400A, 400B, 400C, etc.) generated by one or a plurality of vehicles 300 (for example, 300A, 300B, 300C, etc.) that have traveled the same road section. The road section may be, for example, a section obtained by dividing a road into predetermined sections.

[0013] The vehicle travel information 400 is information generated by the vehicle 300, and may be referred to as probe information, CAN information, etc. The vehicle travel information 400 may include, for example, position information and time information. The vehicle travel information 400 may also include, for example, travel speed information.

[0014] The vehicle 300 may transmit the vehicle driving information 400 to the information processing device 100 (or the server 200, etc.) at predetermined times (predetermined timing). The predetermined time may be various times, such as 1 minute, 2 minutes, 3 minutes, 5 minutes, 8 minutes, and 10 minutes. That is, as an example, when the vehicle 300 travels one trip from the departure point to the destination, it uploads the vehicle driving information 400 summarized in units of 1 minute to the information processing device 100 (or the server 200, etc.).

[0015] The information processing device 100 acquires the travel speed of each vehicle 300 (300A, 300B, 300C) based on each of the multiple vehicle travel information 400 (400A, 400B, 400C). When the vehicle travel speed information includes position information and time information, the information processing device 100 can acquire the travel speed of the vehicle 300 based on the position information and time information. That is, the information processing device 100 acquires the travel speed of each vehicle 300 (300A, 300B, 300C) based on each of the multiple vehicle travel information 400 (400A, 400B, 400C) corresponding to the same road section.

[0016] The information processing device 100 identifies a first traveling speed (V1, V2, V3) that is a predetermined upper vehicle speed quantile from the maximum speed among the traveling speeds in the same road section for each vehicle 300 (300A, 300B, 300C). Here, a quantile is a number used in statistical analysis to see the relative position of data. That is, a quantile is a point into which all data given in a frequency distribution is divided equally, and a 10th division is called a decile, and a 100th division is called a percentile. The quantiles used in this embodiment are used to arrange multiple target values ​​(target values) from highest to lowest (descending order) (or arrange multiple target values ​​from lowest to highest (ascending order)), and identify the target value that is a specified value from the highest (or lowest) of the multiple target values. That is, the upper vehicle speed quantile is a quantile for identifying a predetermined value of a traveling speed (vehicle speed) from the highest traveling speed (maximum speed) among the traveling speeds that are discrete data among the transition of the traveling speed of the vehicle, which are arranged in descending order. In other words, the upper vehicle speed quantile is a quantile for identifying a predetermined value of a traveling speed (vehicle speed) from the lowest traveling speed (maximum speed) among the traveling speeds that are discrete data among the transition of the traveling speed of the vehicle, which are arranged in ascending order.

[0017] The information processing device 100 identifies a first traveling speed that is a predetermined upper vehicle speed quantile from the maximum speed of the same vehicle 300 in the road section among the transitions of the traveling speed of the same vehicle 300 that has traveled in the road section. As a specific example, when the traveling speed of the vehicle 300 in the road section transitions between 40 and 60 km / h, the information processing device 100 rearranges the transitions of the traveling speed (information on the traveling speed corresponding to the traveling position of the vehicle, i.e., the traveling speed that is discrete data corresponding to a plurality of traveling positions in the road section) in descending order (or ascending order), and identifies a traveling speed of vehicle speed quantile 0.2 (20th percentile) from the fastest traveling speed among the descending order (or ascending order). Furthermore, the information processing device 100 identifies multiple first driving speeds (V1, V2, V3) using the driving speeds of multiple vehicle driving information 400 (multiple vehicles 300) corresponding to the same road section. That is, the information processing device identifies one first driving speed for each vehicle for the same road section.

[0018] The information processing device 100 identifies a first traveling speed that is a predetermined selection quantile from the first traveling speeds (V1, V2, V3) of each of the plurality of vehicles 300 (300A, 300B, 300C) identified as described above. The selection quantile is a quantile used when arranging a plurality of first running speeds in descending order (or ascending order) and selecting a first running speed of a predetermined value from the fastest first running speed. That is, the information processing device 100 identifies a first running speed that is a predetermined selected quantile from among the multiple first running speeds (V1, V2, V3). As a specific example, when the multiple first running speeds (V1, V2, V3) are 56 km / h, 52 km / h, and 50 km / h, and the selected quantile is 0.5, the information processing device 100 identifies the first running speed of 52 km / h.

[0019] The information processing device 100 estimates the traffic conditions of the vehicle 300 in the road section based on the first traveling speed (for example, 52 km / h) identified as described above. The number of pieces of vehicle travel information 400 (the number of vehicles 300 traveling in the same road section) is not limited to three as described above, and may be multiple (two, four or more).

[0020] [Details of the information processing device 100] Next, the information processing device 100 according to an embodiment will be described in detail. FIG. 2 is a block diagram illustrating the information processing device 100 according to an embodiment. Fig. 3 is a diagram for explaining an example of identifying the first traveling speed. Fig. 3(A) is a diagram for explaining the vehicle speed transition 310 (310A, 310B, 310C) of each of the multiple vehicles 300 (300A, 300B, 300C) and the maximum speeds M1, M2, M3 and the first traveling speeds V1, V2, V3 in each vehicle speed transition 310A, 310B, 310C, and Fig. 3(B) is a diagram for explaining the first traveling speed identified by the second identification unit 113.

[0021] 2, the information processing device 100 includes, for example, a communication unit 121, a storage unit 122, a display unit 123, and a control unit 110. The communication unit 121, the storage unit 122, and the display unit 123 may be an embodiment of an output unit. The control unit 110 includes, for example, an acquisition unit 111, a first identification unit 112, a second identification unit 113, an adjustment unit 114, an estimation unit 115, an output control unit 116, a guidance unit 117, a map matching unit (not shown), and a division unit (not shown). The control unit 110 may be configured by, for example, an arithmetic processing unit of the information processing device 100. The control unit 110 (e.g., a calculation processing unit, etc.) may realize the functions of each unit (e.g., the acquisition unit 111, the first identification unit 112, the second identification unit 113, the adjustment unit 114, the estimation unit 115, the guidance unit 117, the map matching unit, the division unit, etc.) by, for example, appropriately reading and executing various programs, etc. stored in the memory unit 122, etc.

[0022] The communication unit 121 is, for example, a communication interface capable of transmitting and receiving various information to and from a device (external device) outside the information processing device 100. The external device may be, for example, a vehicle 300, a server 200, a user terminal (not shown), etc. The user terminal is, for example, a terminal used by a user of the information processing device 100, and may be a mobile terminal (mobile terminal) such as a laptop, tablet, or smartphone, or a stationary terminal such as a desktop.

[0023] The storage unit 122 may store, for example, various information and programs. Examples of the storage unit 122 may be a memory, a solid state drive, a hard disk drive, etc. Note that the storage unit 122 may be, for example, a storage area and a server on a cloud.

[0024] The display unit 123 is, for example, a display capable of displaying various characters, symbols, images, and the like.

[0025] The acquisition unit 111 acquires a plurality of pieces of vehicle travel information 400 of the vehicle 300 that has traveled through a road section. That is, the acquisition unit 111 acquires a plurality of pieces of vehicle travel information 400 that correspond to the same road section.

[0026] A road section may be, for example, a section obtained by dividing a road into predetermined sections. As one example, a road section may be a section represented by one link in a road network including nodes and links, or a section represented by a plurality (two or more) of adjacent links. As another example, a road section may be a section between two specific points on a road, etc. As another example, a road section may be a section obtained by dividing a road into predetermined distances, etc. Road sections are not limited to the above example, and may be sections obtained by dividing a road according to various conditions.

[0027] The vehicle travel information 400 is information generated by the vehicle 300, and may be referred to as probe information, CAN information, etc. The vehicle travel information 400 may include, for example, position information and time information. The vehicle travel information 400 may also include, for example, information related to the travel speed of the vehicle 300 (travel speed information).

[0028] For example, the vehicle 300 may acquire position information based on receiving a GNSS signal, and further acquire the time when the position information was acquired (time information), and generate the vehicle driving information 400 including the position information and the time information. Also, the vehicle 300 may acquire the driving speed of the vehicle 300 (driving speed information), and generate the vehicle driving information 400 including the driving speed information. The vehicle 300 may transmit the vehicle driving information 400 to the information processing device 100 (or the server 200, etc.) at predetermined times (predetermined timing). The predetermined time may be various times, such as 1 minute, 2 minutes, 3 minutes, 5 minutes, 8 minutes, and 10 minutes. That is, as an example, when the vehicle 300 travels one trip from the departure point to the destination, it uploads the vehicle driving information 400 summarized in units of 1 minute to the information processing device 100 (or the server 200, etc.).

[0029] The acquisition unit 111 may acquire in real time the vehicle driving information 400 transmitted from the vehicle 300 at predetermined intervals. That is, the acquisition unit 111 may acquire the vehicle driving information 400 transmitted from the vehicle 300 at predetermined intervals without delay. The acquisition unit 111 acquires the vehicle driving information 400 from the vehicle 300 (or the server 200, etc.) via the communication unit 121, for example.

[0030] The first identification unit 112 acquires the driving speed of each vehicle 300 based on each of the multiple vehicle driving information 400 acquired by the acquisition unit 111, and identifies a first driving speed that is a predetermined upper vehicle speed quantile from the maximum speed among the driving speeds of each vehicle 300 within the road section.

[0031] That is, the first identification unit 112 identifies a first traveling speed that is a predetermined upper vehicle speed quantile from the maximum speed of the same vehicle 300 within the road section, among the changes in the traveling speed of the same vehicle 300 traveling within the road section. As a specific example, when the same vehicle 300 travels in a road section at a travel speed in the range of 40 to 60 km / h, the information processing device 100 rearranges the travel speeds (information on travel speeds corresponding to the travel positions of the vehicle, i.e., travel speeds that are discrete data corresponding to a plurality of travel positions in the road section) in descending (or ascending) order, and identifies a travel speed with a vehicle speed quantile of 0.2 (20th percentile) from the fastest travel speed in the descending (or ascending) order. In this way, the first identification unit 112 may identify the first travel speed by using, for example, 0.2 as a predetermined upper vehicle speed quantile. Alternatively, the first identification unit 112 is not limited to the upper vehicle speed quantile of 0.2 in the above-mentioned example, and may use various values ​​including 0.1 or 0.3 as the upper vehicle speed quantile.

[0032] The first identifying unit 112 identifies a plurality of first traveling speeds by using the traveling speeds of the plurality of vehicle traveling information 400 (the plurality of vehicles 300) corresponding to the same road section. That is, the first identifying unit 112 identifies, for each of the plurality of vehicles 300, a first traveling speed that is a predetermined upper vehicle speed quantile from the maximum speed in the road section, among the transitions of the traveling speeds of the plurality of vehicles 300 that have traveled the same road section. As an example here, when there are five vehicles 300 that have traveled the same road section, the first identifying unit 112 identifies five first traveling speeds. As a more specific example, as illustrated in FIG. 1, when there are three vehicles 300 (300A, 300B, 300C) traveling on a road section, the first identification unit 112 identifies first driving speeds V1, V2, V3 that are the vehicle speed quantile (upper vehicle speed quantile) of 0.2 from the maximum speeds M1, M2, M3 of the driving speed trends 310 (310A, 310B, 310C) of each of the three vehicles 300 (300A, 300B, 300C) on that road section (see FIG. 3(A)). The number of vehicles 300 traveling is not limited to five or three as described above, and may be any number more than one.

[0033] The second identifying unit 113 identifies a first traveling speed that is a predetermined selected quantile among the first traveling speeds of each of the multiple vehicles 300 identified by the first identifying unit 112. That is, the second identifying unit 113 identifies a first traveling speed that is a predetermined selected quantile among the multiple first traveling speeds.

[0034] As a specific example, when there are multiple (five as an example here) first running speeds, 60km / h, 56km / h, 52km / h, 48km / h, and 40km / h, and the selected quantile is 0.5, the second identification unit 113 identifies the first running speed of 52km / h, which is the middle one, from the five first running speeds. Note that in this example, when the selected quantile is 0.3 (0.25), the second identification unit 113 identifies the first running speed of 56km / h. Similarly, as an example in this case, when the selected quantile is 0.8 (0.75), the second identification unit 113 identifies the first running speed of 48km / h. Similarly, as a more specific example, when there are three vehicles 300 traveling on a road section as illustrated in FIG. 1, and the first identification unit 112 identifies the first traveling speeds V1 (56 km / h), V2 (52 km / h), and V3 (50 km / h) of each of the three vehicles 300 on that road section (see FIG. 3(A)), the second identification unit 113 sorts the first traveling speeds V1, V2, and V3 in order of speed, and identifies the first traveling speed V2 (52 km / h) that has a selection quantile of 0.5 (see FIG. 3(B)).

[0035] In this manner, the second determination unit 113 may determine the first traveling speed by using, for example, 0.5 as the predetermined selected quantile. Alternatively, the second determination unit 113 may use various values ​​such as 0.6 or 0.4 as the selected quantile without being limited to the selected quantile of 0.5 as the above-mentioned example.

[0036] The adjustment unit 114 adjusts at least one of the predetermined upper vehicle speed quantiles used by the first identification unit 112 and the predetermined selected quantiles used by the second identification unit 113. In this case, in particular, the adjustment unit 114 adjusts the value of the upper vehicle speed quantile, thereby making it possible to change the resolution of the congestion degree (traffic conditions of the vehicle 300) in the road section estimated by the estimation unit 115 described later.

[0037] The adjustment unit 114 does not need to change the conditions (at least one of the upper vehicle speed quantiles and the selection quantiles) according to the driving environment, such as the traffic volume and the time of day in the road section.

[0038] Alternatively, the adjustment unit 114 may change the conditions (at least one of the upper vehicle speed quantile and the selected quantile) according to the driving environment such as the traffic volume and the time of day in the road section. As an example of this case, the adjustment unit 114 may change the value of at least one of the upper vehicle speed quantile and the selected quantile according to various conditions (road section conditions) of the road section, including the road standard in the road section, the number of lanes in the road section, the number of vehicles 300 traveling in the road section, the speed limit of the road section, and the road classification such as whether the road section is a main road or a community road.

[0039] As a specific example, when the road standard of the road section is relatively high (for example, an expressway, etc.), the adjustment unit 114 may relatively increase the value of the upper vehicle speed quantile in the main line of the expressway, i.e., in the road section with a relatively large number of lanes, since the traveling speed is stable. On the other hand, the adjustment unit 114 may relatively decrease the value of the upper vehicle speed quantile in the road section including a merging point such as an interchange or junction of the expressway, i.e., in the road section with a change in the number of lanes, since the traveling speed is likely to become unstable due to merging from an acceleration lane or changing course, but the data includes data in which the influence of merging is minor and the traveling speed is stable. In other words, the adjustment unit 114 may change the upper vehicle speed quantile in the road section that is a merging point on the expressway, since the traveling environment is different from that of the road section that is the main line. By changing in this way, it may be difficult to determine that a traffic jam occurs even if the traveling speed at the merging point is slower than the traveling speed on the main line.

[0040] Alternatively, as a specific example, when at least one of the following conditions is met: the number of vehicles 300 traveling on the road section is relatively large, the speed limit of the road section is relatively high, and the road section is a trunk road, the value of at least one of the upper vehicle speed quantile and the selected quantile may be adjusted to be relatively large. Alternatively, as a specific example, when at least one of the following applies: the number of vehicles 300 traveling on the road section is relatively small, the speed limit of the road section is relatively slow, and the road section is a residential road, the value of at least one of the upper vehicle speed quantile and the selection quantile may be adjusted to be relatively small.

[0041] The estimation unit 115 estimates the traffic conditions of the vehicle 300 in the road section based on the first traveling speed identified by the second identification unit 113. When using the example of Fig. 3 described above, the estimation unit 115 estimates the traffic conditions of the vehicle 300 in the road section based on the first traveling speed identified by the second identification unit 113 (52 km / h as an example here).

[0042] The estimation unit 115 may estimate the traffic conditions of the vehicle 300 in real time. That is, as described above, the acquisition unit 111 may acquire the vehicle travel information 400 transmitted from the vehicle 300 at predetermined intervals in real time. Therefore, the estimation unit 115 (control unit 110) may estimate the traffic conditions of the vehicle 300 in the road section without delay based on the vehicle travel information 400 acquired in real time.

[0043] As an example, the estimation unit 115 may estimate that the traffic conditions of the vehicle 300 in the road section are smooth when the first traveling speed identified by the second identification unit 113 is equal to or greater than a threshold. As another example, the estimation unit 115 may estimate that the traffic conditions of the vehicle 300 in the road section are congested when the first traveling speed identified by the second identification unit 113 is less than a threshold.

[0044] The threshold value is not limited to one value, and may be multiple values. The estimation unit 115 can estimate the traffic situation of the vehicle 300 in the road section in multiple stages based on multiple threshold values. As an example, the estimation unit 115 may estimate that the traffic conditions of the vehicle 300 in the road section are smooth when the first traveling speed is equal to or greater than the first threshold. As another example, the estimation unit 115 may estimate that the traffic conditions of the vehicle 300 in the road section are congested when the first traveling speed is less than the first threshold and equal to or greater than the second threshold (first threshold>second threshold). As another example, the estimation unit 115 may estimate that the traffic conditions of the vehicle 300 in the road section are jammed when the first traveling speed is less than the second threshold.

[0045] The output control unit 116 may control the output unit to output the traffic conditions of the vehicle 300 in the road section estimated by the estimation unit 115. The output unit may be, for example, a communication unit 121, a storage unit 122, a display unit 123, etc. That is, the output control unit 116 may, for example, control the communication unit 121 to transmit the traffic conditions of the vehicle 300 in the road section estimated by the estimation unit 115 to an external device. The external device here may be, for example, the server 200 and a user terminal (not shown), etc. The server 200 (external device) here may be, for example, a server owned by an organization (for example, a traffic information center, etc.) that provides road traffic conditions to users. Furthermore, the output control unit 116 may control the storage unit 122 to store, for example, the traffic conditions of the vehicle 300 in the road section estimated by the estimation unit 115. In this case, the output control unit 116 may control the storage unit 122 to store, for example, a history (history information) of the traffic conditions of the vehicle 300 divided by time period or by day of the week. Furthermore, for a road section where the number of times that congestion or congestion is estimated to be equal to or exceeds a threshold based on the history information, the output control unit 116 may control the storage unit 122 to record attribute information indicating that congestion or congestion is frequent on the road map (map information) on which the road section is recorded (add attribute information to the road section on the road map). In addition, the output control unit 116 may control the display unit 123 to display the traffic conditions of the vehicle 300 in the road section estimated by the estimation unit 115, for example.

[0046] The guidance unit 117 may have a function of providing guidance on a route when moving from a departure point to a destination, etc. The guidance unit 117 may provide various types of guidance using the traffic conditions of the vehicle 300 in the road section estimated by the estimation unit 115. As an example, when the traffic conditions of a road section estimated by the estimation unit 115 are congested or jammed (or smooth), the guidance unit 117 may provide a traffic condition guidance to vehicles currently or in the future traveling on that road section that the traffic conditions are congested or jammed (or smooth). As another example, when the traffic conditions in a road section estimated by the estimation unit 115 are congested, the guidance unit 117 may provide guidance to vehicles currently or in the future traveling on that road section about a travel route that bypasses that road section.

[0047] The guidance unit 117 may be configured as a function of one control unit 110 together with the acquisition unit 111, the first identification unit 112, the second identification unit 113, the adjustment unit 114, the estimation unit 115, the output control unit 116, and the like. In this case, the information processing device 100 (the guidance unit 117) can provide various services (e.g., guidance on traffic conditions and routes, etc.) to an external device (not shown) connected via the communication unit 121 for a vehicle that will travel in the future, using the traffic conditions of the vehicle 300 in the road section estimated by the estimation unit 115. In this case, the external device may be, for example, a user terminal used by a user, a route guidance device (navigation device) mounted on the vehicle, and the like. Alternatively, the guidance unit 117 may be configured as a function of another control unit (another arithmetic processing device, etc.) (not shown) different from the control unit 110 including the acquisition unit 111, the first identification unit 112, the second identification unit 113, the adjustment unit 114, the estimation unit 115, and the output control unit 116. That is, the other control unit (another arithmetic processing device, etc.) may realize the function of each unit (for example, the guidance unit 117, etc.) by appropriately reading and executing various programs, etc. stored in the memory. The other control unit may be mounted on a user terminal, a route guidance device (navigation device) (not shown), etc. In this case, the user terminal and the route guidance device (navigation device) mounted with the other control unit may be included in the concept of the "information processing device" of the present disclosure.

[0048] [Information processing method] Next, an information processing method according to an embodiment will be described. FIG. 4 is a flowchart illustrating an information processing method according to an embodiment.

[0049] In step ST101, the acquisition unit 111 acquires a plurality of pieces of vehicle travel information 400 of the vehicle 300 that has traveled the same road section. The acquisition unit 111 may acquire the vehicle travel information 400 transmitted from the vehicle 300 at predetermined intervals in real time.

[0050] In step ST102, the first identification unit 112 acquires the driving speed of each vehicle 300 based on each of the multiple vehicle driving information 400 acquired in step ST101, and identifies a first driving speed that is a predetermined upper vehicle speed quantile from the maximum speed among the driving speeds within the road section for each vehicle 300. As an example of this case, the first identifying unit 112 may identify the first traveling speed by using 0.2 as the predetermined upper vehicle speed quantile. The adjusting unit 114 may adjust (change) the value of the predetermined upper vehicle speed quantile used by the first identifying unit 112.

[0051] In step ST103, the second identification unit 113 identifies a first traveling speed that is a predetermined selection quantile from among the first traveling speeds of the plurality of vehicles 300 identified in step ST102. As an example of this case, the second identifying unit 113 may identify the first traveling speed using 0.5 as the predetermined selected quantile. The adjusting unit 114 may adjust (change) the value of the predetermined selected quantile used by the second identifying unit 113.

[0052] In step ST104, the estimation unit 115 estimates the traffic conditions of the vehicle 300 in the road section, based on the first traveling speed identified in step ST103. The estimation unit 115 may estimate the traffic conditions of the vehicle 300 in the road section in real time based on acquiring in real time the vehicle driving information 400 transmitted at predetermined intervals from the vehicle 300 traveling in the road section in step ST101.

[0053] After the process of step ST104, the output control unit 116 may control the output unit to output the traffic conditions of the vehicle 300 in the road section estimated in step ST104. In addition, after processing of step ST104, the guidance unit 117 may use the traffic conditions for the vehicle 300 in the road section estimated in step ST104 to provide various types of guidance (e.g., traffic condition guidance and route guidance) to vehicles that will be traveling in the road section in the future or currently.

[0054] [Variations] Next, a modified example will be described.

[0055] (First Modification) First, the first modified example will be described.

[0056] As described above, the information processing device 100 estimates the traffic conditions (congestion level) of the vehicle 300 in the road section. As an example of this case, the information processing device 100 may estimate the traffic conditions (congestion level) of the vehicle 300 for each lane in the road section. The control unit 110 may include a map matching unit (not shown) to estimate the traffic conditions (congestion level) of the vehicle 300 for each lane in the road section.

[0057] The map matching unit matches the position of the vehicle 300 to a road map based on the multiple pieces of vehicle travel information 400 (position information) acquired by the acquisition unit 111 and map information related to a road map. In this case, the map information may be information on a road network in units of lanes. The road network in units of lanes may be a road network in which nodes and links are arranged for each lane. The map matching unit matches the position information (position of the vehicle 300) based on each of the multiple pieces of vehicle travel information 400 to the road network in units of lanes (map information) and associates the position of the vehicle 300 with the lane.

[0058] The first identification unit 112 acquires the travel speed of each vehicle 300 that has been map matched by the map matching unit to each of the multiple lanes in the road section, and identifies a first travel speed that is a predetermined upper vehicle speed quantile from the maximum speed among the travel speeds of each vehicle 300 that has traveled on each lane. In other words, the first identification unit 112 identifies, for each lane in the road section, the first travel speed of each vehicle 300 that has traveled on each lane.

[0059] The second identifying unit 113 identifies, for each lane in the road section, a first traveling speed that is a predetermined selection quantile among the first traveling speeds of each of the multiple vehicles 300 identified by the first identifying unit 112.

[0060] The adjustment unit 114 may adjust at least one of the predetermined top vehicle speed quantiles used by the first identification unit 112 and the predetermined selected quantiles used by the second identification unit 113 for each lane in the road section. As a specific example, in a road section with two lanes in each direction, the first lane may have stopped vehicles, parked vehicles, and left-turning vehicles, so the speed of vehicles traveling in the first lane may be slower than the speed of vehicles traveling in the second lane. Similarly, as an example, the number of vehicles traveling in the first lane may be greater than the number of vehicles traveling in the second lane. Therefore, as an example, the adjustment unit 114 may adjust the predetermined upper vehicle speed quantile used by the first identification unit 112 so that it is lower in the first lane in the same road section than in other lanes (e.g., the second lane, etc.) other than the first lane in the same road section. Similarly, as an example, the adjustment unit 114 may adjust the predetermined selection rank used by the second identification unit 113 so that it is higher for the first lane in the same road section than for other lanes (e.g., the second lane, etc.) other than the first lane in the same road section.

[0061] As another example, the adjustment unit 114 may adjust the predetermined upper vehicle speed quantile used by the first identification unit 112 so that it is the same for a first lane in the same road section and other lanes (e.g., a second lane, etc.) other than the first lane in the same road section. Similarly, as an example, the adjustment unit 114 may adjust the predetermined selection rank used by the second identification unit 113 so that it is the same for the first lane in the same road section and other lanes (e.g., the second lane, etc.) other than the first lane in the same road section.

[0062] The estimation unit 115 estimates the traffic conditions of the vehicle 300 for each lane in the same road section, based on the first traveling speed for each lane identified by the second identification unit 113.

[0063] The guidance unit 117 may provide various kinds of guidance (e.g., lane guidance, etc.) using the traffic conditions of the vehicle 300 for each lane in the same road section estimated by the estimation unit 115. As an example, the guidance unit 117 may provide guidance such as "The first lane is congested due to a vehicle turning left at an upcoming intersection, but the second lane is running smoothly."

[0064] That is, the information processing device of the first modification example is An acquisition unit that acquires a plurality of pieces of vehicle travel information of vehicles that have traveled along a road section; a map matching unit that matches a vehicle travel position recorded in each of the plurality of pieces of vehicle travel information to a lane based on the plurality of pieces of vehicle travel information acquired by the acquisition unit and map information on a road map in which lanes are recorded; a first determination unit that acquires a driving speed for each vehicle based on the vehicle driving information for each vehicle whose driving position has been matched for each lane by the map matching unit, and determines a first driving speed that is a predetermined upper vehicle speed quantile from a maximum speed among the driving speeds of the vehicle in the road section; A second identification unit that identifies, for each lane, a first travel speed that is a predetermined selection quantile among the first travel speeds for each of the plurality of vehicles identified by the first identification unit; The road section may further include an estimation unit that estimates a vehicle traffic condition for each lane in the road section based on the first travel speed for each lane identified by the second identification unit. In this case, the information processing device may include an adjustment unit that adjusts at least one of a predetermined upper vehicle speed quantile used by the first identification unit and a predetermined selected quantile used by the second identification unit for each lane in the road section. The information processing device may further include a guidance unit that provides guidance using the vehicle traffic conditions for each lane in the same road section estimated by the estimation unit. In this case, the guidance unit may provide guidance on the traffic conditions for each lane and guidance on a travel route for each lane.

[0065] (Second Modification) Next, a second modified example will be described.

[0066] As described above, the acquisition unit 111 acquires a plurality of pieces of vehicle travel information 400 of the vehicle 300 that has traveled through the road section. The acquisition unit 111 is not limited to this embodiment.

[0067] That is, when the vehicle driving information 400 is generated at predetermined times (predetermined timings) when the same vehicle 300 performs a series of driving, the acquisition unit 111 may acquire the vehicle driving information 400 generated by a plurality of vehicles 300. The series of driving may be, for example, driving when the vehicle 300 moves from a departure point to a destination. The predetermined time (predetermined timing) may be, for example, various times such as 1 minute, 2 minutes, 3 minutes, 5 minutes, 8 minutes, and 10 minutes.

[0068] In this case, a map matching unit (not shown) matches the driving position of the vehicle 300 with a road map (performs map matching) based on the position information contained in each of the multiple vehicle driving information 400 acquired by the acquisition unit 111 and map information regarding the road map. The map matching unit may match the travel position of the vehicle 300 recorded in each of the vehicle travel information 400 to a lane based on the vehicle travel information 400 acquired by the acquisition unit 111 and map information related to a road map in which lanes are recorded. The map matching unit may match the lane in the same manner as in the first modified example.

[0069] A dividing unit (not shown) generates divided driving information by dividing the vehicle driving information 400 corresponding to each of the multiple road sections recorded in the road map based on the result of matching the driving position of the vehicle 300 to the road map by the map matching unit. That is, the dividing unit divides the vehicle driving information 400 resulting from the map matching into each of the multiple road sections using the position information recorded in the vehicle driving information 400. The road sections may be, for example, sections obtained by dividing a road into predetermined sections.

[0070] The first identification unit 112 acquires the driving speed of each vehicle 300 based on each of the multiple divided driving information divided by the dividing unit for each road section, and identifies a first driving speed that is a predetermined upper vehicle speed quantile from the maximum speed among the driving speeds within the same road section for each vehicle 300. The second identifying unit 113 identifies a first traveling speed that is a predetermined selection quantile among the first traveling speeds in the same road section for each of the multiple vehicles 300 identified by the first identifying unit 112. The estimation unit 115 estimates the traffic conditions of the vehicle 300 in the same road section based on the first traveling speed identified by the second identification unit 113. The first identification unit 112, the second identification unit 113, and the estimation unit 115 may have the same configuration as in the above-described embodiment.

[0071] That is, the information processing device of the second modification example is An acquisition unit that acquires vehicle driving information generated by a plurality of vehicles when the same vehicle generates vehicle driving information at predetermined time intervals during a series of driving of the same vehicle; a map matching unit that matches a vehicle travel position with a road map based on location information included in each of the plurality of pieces of vehicle travel information acquired by the acquisition unit and map information related to a road map; a division unit that generates divided travel information by dividing the vehicle travel information into a plurality of road sections recorded on a road map based on a result of matching the travel position of the vehicle to a road map by the map matching unit; a first determination unit that acquires a travel speed for each vehicle based on each of a plurality of pieces of divided travel information divided for each road section by the dividing unit, and determines a first travel speed that is a predetermined upper vehicle speed quantile from a maximum speed among the travel speeds for each vehicle in the same road section; A second identification unit that identifies a first travel speed that is a predetermined selection quantile among the first travel speeds in the same road section for each of the multiple vehicles identified by the first identification unit; The vehicle may further include an estimation unit that estimates a traffic condition of vehicles in the same road section based on the first traveling speed identified by the second identification unit. The map matching unit may match the vehicle's travel position recorded in each of the plurality of pieces of vehicle travel information to a lane based on the plurality of pieces of vehicle travel information acquired by the acquisition unit and map information on a road map in which lanes are recorded. In this case, the first identification unit and the second identification unit can identify a first travel speed for each lane, similar to the first modification example described above. Similarly, the estimation unit can estimate the vehicle's traffic condition for each lane in the same road section.

[0072] [Functions and circuits] Next, the functions and circuits of the above-mentioned information processing device 100 will be described. Each unit of the information processing device 100 may be realized as a function of a computer arithmetic processing device or the like. That is, the acquisition unit 111, the first identification unit 112, the second identification unit 113, the adjustment unit 114, the estimation unit 115, the output control unit 116, the guidance unit 117, the map matching unit (not shown), and the division unit (not shown) (control unit 110) of the information processing device 100 may be realized as an acquisition function, a first identification function, a second identification function, an adjustment function, an estimation function, an output control function, a guidance function, a map matching function, and a division function (control function) by the computer arithmetic processing device or the like, respectively. The information processing program can cause a computer to realize each of the above-mentioned functions. The information processing program may be recorded in a non-transitory computer-readable storage medium, such as a memory, a solid-state drive, a hard disk drive, or an optical disk. The storage medium may be rephrased as a non-transitory computer-readable medium that stores the information processing program. As described above, each unit of the information processing device 100 may be realized by a computer arithmetic processing device or the like. The arithmetic processing device or the like is configured by, for example, an integrated circuit or the like. Therefore, each unit of the information processing device 100 may be realized as a circuit constituting the arithmetic processing device or the like. That is, the acquisition unit 111, the first identification unit 112, the second identification unit 113, the adjustment unit 114, the estimation unit 115, the output control unit 116, the guidance unit 117, the map matching unit (not shown), and the division unit (not shown) (control unit 110) of the information processing device 100 may be realized as an acquisition circuit, a first identification circuit, a second identification circuit, an adjustment circuit, an estimation circuit, an output control circuit, a guidance circuit, a map matching circuit, and a division circuit (control circuit) constituting the arithmetic processing device or the like of a computer. The communication unit 121, the storage unit 122, and the display unit 123 (output unit) of the information processing device 100 may be realized as a communication function, a storage function, and a display function (output function) including the functions of an arithmetic processing device, etc. The communication unit 121, the storage unit 122, and the display unit 123 (output unit) of the information processing device 100 may be realized as a communication circuit, a storage circuit, and a display circuit (output circuit) by being configured, for example, by an integrated circuit, etc. The communication unit 121, the storage unit 122, and the display unit 123 (output unit) of the information processing device 100 may be realized as a communication device, a storage device, and a display device (output device) by being configured, for example, by being configured by a plurality of devices.

[0073] The information processing device 100 can combine one or any two or more of the above-mentioned units. In this disclosure, the term "information" is used, but the term "information" can be replaced with "data" and the term "data" can be replaced with "information."

[0074] [Aspects and Effects of the Present Embodiment] Next, one aspect of this embodiment and the effects of each aspect will be described. Note that each aspect described below is an example at the time of filing, and this embodiment is not limited to the aspects described below. In other words, this embodiment is not limited to each aspect described below, and may be realized by appropriately combining each of the above-mentioned parts. In addition, a lower aspect may be able to cite any of the higher aspects. The effects described below are merely examples, and the effects of each aspect are not limited to those described below. Each aspect may, for example, have at least one of the effects described below.

[0075] (Aspect 1) An information processing device of one embodiment includes an acquisition unit that acquires multiple pieces of vehicle driving information of vehicles that have traveled through a road section, a first identification unit that acquires the driving speed of each vehicle based on each of the multiple pieces of vehicle driving information acquired by the acquisition unit and identifies a first driving speed that is a predetermined upper vehicle speed quantile from the maximum speed among the driving speeds of each vehicle in the road section, a second identification unit that identifies a first driving speed that is a predetermined selection quantile among the first driving speeds of each of the multiple vehicles identified by the first identification unit, and an estimation unit that estimates vehicle traffic conditions in the road section based on the first driving speed identified by the second identification unit. This enables the information processing device to estimate the traffic conditions (degree of congestion) in the road section. In addition, by using the upper vehicle speed quantiles and the selection quantile, the information processing device can avoid the driving tendencies of some vehicles among the multiple vehicles traveling in the road section being reflected relatively significantly. In other words, the information processing device can estimate the vehicle traffic situation in the road section based on the driving tendencies of a vehicle that is considered to be general among the multiple vehicles traveling in the road section. In addition, on general roads, changes in vehicle speed tend to be relatively large, and since information such as traffic lights, waiting for pedestrians to cross, and waiting to turn right are mixed in, judging based on a simple average driving speed within a road section does not match the traffic conditions of that road section, and the traffic conditions cannot be judged appropriately. In this regard, the information processing device of this embodiment can appropriately estimate the traffic conditions of a road section by using the top vehicle speed quantiles and the selection quantiles. That is, in order to achieve both freshness and accuracy of vehicle traffic conditions (live traffic information) in a road section, the information processing device of this embodiment is able to determine the degree of congestion by prioritizing data representing smooth driving conditions belonging to a higher vehicle speed quantile, which reduces the influence of vehicles being stopped, rather than judging based on the average driving speed in the road section. If the road section is in a "congested" state, the number of vehicle driving information (number of vehicles) will be relatively large, and the vehicle driving information indicating a low speed state will be relatively large. If the road section is "smooth", the vehicle driving information indicating a vehicle driving speed above a certain value will be relatively large, regardless of the number of vehicle driving information (number of vehicles). The information processing device specifies the first driving speed based on the upper vehicle speed quantile rather than the maximum speed in the road section, and further specifies the first driving speed based on a selection quantile from among the specified first driving speeds, so that it is possible to prevent vehicle driving information generated by a vehicle that has only traveled a relatively short distance through a portion of a road section from being used to estimate the traffic conditions of that road section. Since a vehicle traveling through a portion of a road section may only use a portion of the section where it can travel smoothly, the information processing device can avoid using vehicle driving information generated by such a vehicle by using the upper vehicle speed quantile and the selection quantile. In other words, the average vehicle driving speed is relatively more susceptible to the influence of abnormal values, whereas the quantiles used by the information processing device have the advantage that the influence of abnormal values ​​is relatively less.

[0076] (Aspect 2) An information processing device according to one embodiment may include an adjustment unit that adjusts at least one of a predetermined upper vehicle speed quantile used by the first identification unit and a predetermined selected quantile used by the second identification unit. In particular, the information processing device can thereby change the congestion level resolution by adjusting the value of the upper vehicle speed quantile. The information processing device may not change the upper vehicle speed quantile number and the selection quantile number, or may change them, depending on various conditions such as the road in the road section and the number of traveling vehicles.

[0077] (Aspect 3) In one embodiment of the information processing device, the first identification unit identifies the first driving speed using 0.2 as a predetermined upper vehicle speed quantile, the second identification unit identifies the first driving speed using 0.5 as a predetermined selection quantile, and the estimation unit estimates the vehicle traffic conditions to be smooth driving when the first driving speed identified by the second identification unit is equal to or greater than a threshold, and estimates the vehicle traffic conditions to be congested when the first driving speed identified by the second identification unit is less than the threshold. This allows the information processing device to estimate the degree of vehicle congestion in the road section. That is, the information processing device can estimate that the road section is "running smoothly" if vehicles are traveling smoothly in part of the road section to be estimated, and can estimate that the road section is "congested" or "traffic jammed" if all of the vehicles traveling in the road section (and all of the vehicles in the road section) are traveling at a low speed. The information processing device can obtain the traveling speed based on all of the vehicle traveling information in the road section, and estimate the degree of congestion in the road section based on the traveling speed (first traveling speed) of vehicles in the top vehicle speed quantile.

[0078] That is, as a specific example, the information processing device (first specifying unit) deletes records of 0 km / h due to traffic lights being stopped or waiting to turn right or left from all vehicle travel information related to the road section, and sorts the information by travel speed for each vehicle. Next, the information processing device (first identification unit) identifies, for each vehicle, as an example, a driving speed (first driving speed) of the top vehicle speed quantile 0.2 (20th percentile). That is, the information processing device (first identification unit) adopts a driving speed in the top 20% instead of a temporary maximum speed. Next, the information processing device (second identification unit) identifies a vehicle driving speed (vehicle) (first driving speed) of 0.5, as an example, a selection quantile (general road selection quantile), from among all vehicle driving information (all vehicles) within the road section. Next, the information processing device (estimation unit) estimates the congestion degree in the road section based on the identified vehicle travel speed. This enables the information processing device to reduce the possibility that it will be necessary to change conditions according to the driving environment, such as traffic volume and time of day within a road section.

[0079] (Aspect 4) In the information processing device of one aspect, the acquisition unit may acquire vehicle travel information transmitted from the vehicle at predetermined intervals in real time, and the estimation unit may estimate a traffic condition of the vehicle in real time. This allows the information processing device to estimate the current traffic conditions in the road section, i.e., the information processing device can achieve both freshness and accuracy of the vehicular traffic conditions (live traffic information) in the road section.

[0080] (Aspect 5) In one aspect of the information processing method, a computer executes the following steps: an acquisition step of acquiring multiple pieces of vehicle driving information of vehicles that have traveled through a road section; a first identification step of acquiring the driving speed of each vehicle based on each of the multiple pieces of vehicle driving information acquired by the acquisition step and identifying a first driving speed that is a predetermined upper vehicle speed quantile from the maximum speed among the driving speeds of each vehicle within the road section; a second identification step of identifying a first driving speed that is a predetermined selection quantile among the first driving speeds of each of the multiple vehicles identified by the first identification step; and an estimation step of estimating vehicle traffic conditions in the road section based on the first driving speed identified by the second identification step. As a result, the information processing method can achieve the same effects as the information processing device according to the above-described aspect.

[0081] (Aspect 6) An information processing program of one embodiment causes a computer to realize an acquisition function that acquires multiple pieces of vehicle driving information of vehicles that have traveled through a road section, a first identification function that acquires the driving speed of each vehicle based on each of the multiple pieces of vehicle driving information acquired by the acquisition function and identifies a first driving speed that is a predetermined upper vehicle speed quantile from the maximum speed among the driving speeds of each vehicle within the road section, a second identification function that identifies a first driving speed that is a predetermined selected quantile among the first driving speeds of each of the multiple vehicles identified by the first identification function, and an estimation function that estimates vehicle traffic conditions in the road section based on the first driving speed identified by the second identification function. As a result, the information processing program can achieve the same effects as the information processing device according to the above-described aspect. [Explanation of symbols]

[0082] 100 Information processing device 110 Control section 111 Acquisition Department 112 1st Specific Part 113 Second Specific Part 114 Adjustment section 115 Estimation Department 116 Output control section 117 Information Department 121 Communications Department 122 Storage section 123 Display section 200 Servers 300 (300A, 300B, 300C) Vehicle 310 (310A, 310B, 310C) Changes in vehicle speed Maximum speed during the transition of vehicle speeds for M1, M2, and M3 V1, V2, V3 The first travel speed determined by the upper speed quantile within the travel speed transition of the vehicle 400 (400A, 400B, 400C) Vehicle driving information

Claims

1. An acquisition unit that acquires a plurality of pieces of vehicle travel information of vehicles that have traveled along a road section; a first determination unit that obtains a travel speed for each vehicle based on each of the plurality of pieces of vehicle travel information obtained by the acquisition unit, and determines a first travel speed that is a predetermined upper vehicle speed quantile from a maximum speed among the travel speeds of the vehicle in the road section; A second identification unit that identifies a first travel speed that is a predetermined selection quantile among the first travel speeds of the plurality of vehicles identified by the first identification unit; an estimation unit that estimates a traffic condition of vehicles in the road section based on the first traveling speed identified by the second identification unit; An information processing device comprising:

2. an adjustment unit that adjusts at least one of a predetermined upper vehicle speed quantile used by the first determination unit and a predetermined selected quantile used by the second determination unit; The information processing device according to claim 1 .

3. The first identification unit identifies a first traveling speed by using 0.2 as a predetermined upper vehicle speed quantile, The second identification unit identifies the first traveling speed using 0.5 as a predetermined selection quantile; The estimation unit estimates that the traffic conditions of the vehicle are smooth when the first traveling speed identified by the second identification unit is equal to or greater than a threshold, and estimates that the traffic conditions of the vehicle are congested when the first traveling speed identified by the second identification unit is less than the threshold.

3. The information processing device according to claim 1 or 2.

4. The acquisition unit acquires vehicle driving information transmitted from the vehicle at predetermined intervals in real time, The estimation unit estimates a traffic situation of a vehicle in real time. The information processing device according to claim 1 .

5. The computer An acquisition step of acquiring a plurality of pieces of vehicle travel information of vehicles that have traveled along a road section; a first specifying step of acquiring a travel speed for each vehicle based on each of the plurality of pieces of vehicle travel information acquired by the acquiring step, and specifying a first travel speed that is a predetermined upper vehicle speed quantile from a maximum speed among the travel speeds of the vehicle in the road section; a second specifying step of specifying a first travel speed that is a predetermined selection quantile among the first travel speeds of the plurality of vehicles specified by the first specifying step; an estimation step of estimating a traffic condition of vehicles in the road section based on the first traveling speed identified in the second identification step; An information processing method for performing the above.

6. On the computer, An acquisition function for acquiring a plurality of pieces of vehicle travel information of vehicles that have traveled along a road section; a first determination function for obtaining a travel speed for each vehicle based on each of the plurality of vehicle travel information obtained by the obtaining function, and determining a first travel speed that is a predetermined upper vehicle speed quantile from a maximum speed among the travel speeds of the vehicle in the road section; A second identification function that identifies a first travel speed that is a predetermined selection quantile among the first travel speeds of each of the plurality of vehicles identified by the first identification function; an estimation function of estimating a traffic condition of vehicles in the road section based on the first traveling speed identified by the second identification function; An information processing program that realizes this.

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