Information processing apparatus

Abstract

To provide a technology effective for estimating a traffic situation for each lane on a road including a plurality of traveling lanes.SOLUTION: A control unit of an information processing device calculates a distribution of the number of probe vehicles for each traveling speed by aggregating, for each traveling speed, the number of probe vehicles traveling in a first road section provided with two or more traveling lanes during a predetermined period from a time point a predetermined time before a current time point to the current time point, according to traveling information collected from a plurality of probe vehicles. A control unit of the information processing device specifies an average traveling speed for each traveling lane in a first road section according to two or more local maximum values when the vehicle number distribution is curve-approximated and a turn signal operation history included in the traveling information, and outputs the specified average traveling speed for each traveling lane.SELECTED DRAWING: Figure 4

Description

[Technical Field]

[0001] The present disclosure relates to an information processing device. [Background technology]

[0002] A navigation program is known that sets a cost for each of multiple driving lanes included in a road section, and adjusts upward the cost of driving lanes adjacent to congested driving lanes, and prioritizes driving lanes with lower costs as recommended lanes (see, for example, Patent Document 1). [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Japanese Patent Application Laid-Open No. 2017-32438 Summary of the Invention [Problem to be solved by the invention]

[0004] An object of the present disclosure is to provide a technique that is effective in estimating traffic conditions for each lane on a road that includes multiple driving lanes. [Means for solving the problem]

[0005] One aspect of the present disclosure is an information processing device. In this case, the information processing device includes, for example, receiving driving information from each of a plurality of probe vehicles, the driving speed in each road section, the date and time when each road section was driven, and the turn signal operation history in each road section; calculating a distribution of the number of probe vehicles by travel speed by counting, according to the travel information, the number of probe vehicles that have traveled on a first road section having two or more travel lanes during a predetermined period from a point in time a predetermined time before the present time to the present time, by travel speed; Identifying an average driving speed for each of the two or more driving lanes in the first road section according to two or more maximum values ​​obtained by curve approximating the vehicle number distribution and the turn signal operation history included in the driving information; outputting the average driving speed for each of the two or more driving lanes in the first road section; The control unit may include:

[0006] The present disclosure can also be understood as an information processing method in which a computer executes the processing of an information processing device, an information processing program for causing a computer to execute the information processing method, or a non-transitory storage medium for storing the information processing program. [Effects of the Invention]

[0007] According to the present disclosure, it is possible to provide a technique that is effective in estimating traffic conditions for each lane on a road that includes multiple driving lanes. [Brief explanation of the drawings]

[0008] [Figure 1] FIG. 1 is a diagram illustrating an example of a system configuration according to an embodiment. [Figure 2] FIG. 3 is a diagram illustrating an example of data stored in a travel information DB according to the embodiment. [Figure 3] 10 is a flowchart illustrating an example of a processing routine executed by a server in the embodiment. [Figure 4] FIG. 10 is a diagram illustrating an example of the correlation between the actual average driving speed for each driving lane in the first road section and an approximation curve of the vehicle number distribution. [Figure 5] 4 is a diagram for explaining an example of a method for determining a driving lane in which a target probe vehicle is traveling in a first road section in an embodiment. FIG. DETAILED DESCRIPTION OF THE INVENTION

[0009] One method for estimating the traffic conditions of a road section including multiple travel lanes is to estimate the congestion level of each of the multiple travel lanes based on the time required for a probe vehicle to travel the road section and the position information of the probe vehicle. However, sensors such as a GPS (Global Positioning System) used to acquire the position information of the probe vehicle are often used to estimate the congestion level of each of the multiple travel lanes. It has been difficult to accurately identify the driving lane that a probe vehicle actually traveled in. The present disclosure provides a technique that is effective in solving such a problem.

[0010] As a result of repeated and diligent verification, the inventors of the present application discovered that when the average traveling speed of probe vehicles differs for each traveling lane, curve approximation of the distribution of the number of probe vehicles by traveling speed reveals a characteristic of a high correlation with the average traveling speed for each traveling lane. In other words, the inventors of the present application discovered that when the average traveling speed differs for each traveling lane in a road section including N (a natural number greater than or equal to 1) traveling lanes, N maximum values ​​appear in the curve generated by curve approximation of the distribution of the number of probe vehicles by traveling speed, and the traveling speeds corresponding to these maximum values ​​are each approximately the same as the average traveling speed for the N traveling lanes.

[0011] Therefore, in the information processing device according to the present disclosure, the control unit receives driving information from multiple probe vehicles. The driving information includes the driving speed of each probe vehicle when it traveled through each road section, the date and time when it traveled through each road section, and the blinker operation history for each road section. In one example, such driving information may be transmitted from each probe vehicle to the information processing device each time the probe vehicle travels through each road section. The "road section" in the present disclosure may be a road section divided according to road links used in map data for a car navigation system, or may be a road section divided independently by the operator of the information processing device, etc.

[0012] A control unit of an information processing device according to the present disclosure calculates a vehicle count distribution by travel speed by tallying the number of probe vehicles that traveled a first road section during a predetermined period of time by travel speed in accordance with travel information received from multiple probe vehicles. In the present disclosure, a "predetermined period" refers to a period from a predetermined time before the current time to the current time. The first road section is a road section with two or more lanes traveling in the same direction (a road section with two or more lanes in each direction). When calculating the vehicle count distribution, the control unit of the information processing device according to the present disclosure may calculate the vehicle count distribution using only travel information of probe vehicles (target probe vehicles) that did not operate their turn signals during the first road section among vehicles that traveled the first road section during the predetermined period of time. This is because a probe vehicle that operated its turn signal during the first road section is likely to have changed lanes during the first road section. Therefore, if the vehicle count distribution is calculated including the travel information of the probe vehicle, the characteristics discovered by the present inventors may not be apparent.

[0013] The control unit of the information processing device according to the present disclosure generates an approximate curve of the vehicle count distribution by performing curve approximation on the calculated vehicle count distribution. The curve approximation of the vehicle count distribution may be obtained using known methods such as interpolation or kernel density estimation. If the average driving speeds of the multiple probe vehicles in the first road section differ for each driving lane, the approximate curve obtained in this manner will have the same number of maximum values ​​as the number of driving lanes, in accordance with the inventor's findings described above. However, it is necessary to determine which driving lane each of the multiple maximum values ​​appearing on the approximate curve corresponds to.

[0014] In response to this, the control unit of the information processing device according to the present disclosure is configured to In one example, the control unit may acquire the turn signal operation history in a second road section preceding the first road section from the travel information of probe vehicles included in the number of each of the two or more local maximum values, and determine which of the two or more driving lanes in the first road section each of the two or more local maximum values ​​corresponds to based on the acquired turn signal operation history.

[0015] Here, when the first road section includes two driving lanes, if the last turn signal operation performed in the second road section by a target probe vehicle included in the number of either of the two maximum values ​​is a right (or left) turn signal operation, it can be determined that the maximum value corresponds to the right (or left) driving lane (the number indicated by the maximum value corresponds to the number of target probe vehicles that traveled in the right (left) driving lane).

[0016] Furthermore, if the first road section includes three driving lanes, and the last two turn signal operations performed in the second road section by a target probe vehicle included in one of the three local maxima are right turn signal operations, it can be determined that the local maxima corresponds to the right driving lane. Furthermore, if the last two turn signal operations performed in the second road section by a target probe vehicle included in another of the three local maxima are left turn signal operations, it can be determined that the local maxima corresponds to the left driving lane. And it can be determined that the remaining local maxima corresponds to the middle driving lane.

[0017] When the correspondence between the local maximum values ​​and the driving lanes is determined by the above-described method, the control unit of the information processing device according to the present disclosure identifies the driving speed of the target probe vehicle included in each of the two or more local maximum values ​​as the average driving speed of each of the two or more driving lanes in the first road section. Then, the control unit of the information processing device according to the present disclosure outputs the identified average driving speed for each driving lane (the average driving speed of each of the two or more driving lanes in the first road section). Outputting the average driving speed of each of the two or more driving lanes in the first road section may include providing (transmitting) the average driving speed of each of the two or more driving lanes in the first road section to an external device that provides road traffic information to a car navigation system or the like.

[0018] According to the information processing device of the present disclosure, even if a sensor such as a GPS cannot accurately identify the driving lane in which the probe vehicle is traveling, it is possible to estimate the average driving speed for each driving lane. This makes it possible to estimate the traffic conditions (e.g., the degree of congestion) for each driving lane on a road that includes multiple driving lanes.

[0019] Specific embodiments of the present disclosure will be described below with reference to the accompanying drawings. Unless otherwise specified, the hardware configurations, module configurations, functional configurations, and the like described in the following embodiments are not intended to limit the technical scope of the disclosure to those configurations alone.

[0020] <Embodiment> In this embodiment, an example will be described in which an information processing device according to the present disclosure is applied to a system for providing information about facilities to a user who drives a vehicle.

[0021] (System Overview) FIG. 1 is a diagram showing a schematic example of a system configuration according to this embodiment. In the example shown in FIG. 1, the system includes a plurality of vehicle-mounted terminals 100 and a server 200. The vehicle-mounted terminals 100 and the server 200 are connected to each other via a network. The network may be, for example, a WAN (Wide Area Network), which is a global public communication network such as the Internet. rea Network), or other communications network.

[0022] The on-board terminal 100 is a computer mounted on the probe vehicle 10. The on-board terminal 100 has a function of transmitting travel information to the server 200 each time the probe vehicle 10 travels through a road section. The travel information in this embodiment includes an identifier (vehicle ID) of the probe vehicle 10, an identifier (section ID) of the road section traveled by the probe vehicle 10, the travel speed of the probe vehicle 10 when it traveled through the road section, the date and time when the probe vehicle 10 traveled through the road section (travel date and time), and a history of turn signal operations (turn signal operation history) performed while the probe vehicle 10 was traveling through the road section. The turn signal operation history is information in which the turn signal operation direction (rightward or leftward) is arranged in chronological order. The data included in the travel information is, for example, generated according to CAN data collected by each probe vehicle 10.

[0023] The server 200 is one or more computers that calculates the average driving speed for each driving lane in a road section having multiple driving lanes in accordance with driving information received from multiple in-vehicle terminals 100 and outputs (transmits) the calculation results to an external device. In this embodiment, the server 200 corresponds to the information processing device according to the present disclosure. In one example, the external device is a device that provides congestion information for each road section to a car navigation system of a vehicle. Note that the provision of congestion information for each road section may be performed by the server 200. In this case, the server 200 may be configured to achieve the function of calculating the congestion degree for each driving lane in each road section in accordance with the average driving speed for each driving lane in each road section.

[0024] (System configuration) An example of the configuration of the in-vehicle terminal 100 and the server 200 included in the system of this embodiment will now be described with reference to FIG.

[0025] The in-vehicle terminal 100 is a computer mounted on the probe vehicle 10, and may be configured, for example, by a combination of an ECU (Electronic Control Unit) and a DCM (Data Communication Module). As illustrated in Fig. 1, the in-vehicle terminal 100 includes a control unit 101, a storage unit 102, a turn signal switch 103, a vehicle speed sensor 104, a position acquisition unit 105, and a communication I / F 106.

[0026] The control unit 101 is a computing unit that achieves each function of the in-vehicle terminal 100 by executing programs stored in the storage unit 102. The control unit 101 in this embodiment can be realized by, for example, a hardware processor such as a CPU. The storage unit 102 is configured with a storage medium such as a RAM, a magnetic disk, and / or a flash memory. The storage unit 102 stores programs executed by the control unit 101, data used by the programs, and the like. The data stored in the storage unit 102 includes data required for communication with the server 200 (e.g., the IP address of the server 200), CAN data collected while the probe vehicle 10 is running (e.g., when the ignition switch or power switch is on), data linking the location of each road section with an identifier (section ID), and an identifier (vehicle ID) of the probe vehicle 10.

[0027] The turn signal switch 103 detects a turn signal operation by the driver of the probe vehicle 10. The turn signal operation detected by the turn signal switch 103 includes the direction of the turn signal operation (rightward or leftward). The vehicle speed sensor 104 detects the traveling speed of the probe vehicle 10. The position acquisition unit 105 acquires the current position (geographical coordinates such as latitude and longitude) of the probe vehicle 10. In one example, the position acquisition unit 105 may be configured to include a GPS (Global Positioning System) receiver. In another example, the position acquisition unit 105 may be configured to acquire the current position (geographical coordinates such as latitude and longitude) of the probe vehicle 10. The communication I / F 106 is a communication interface for connecting the in-vehicle terminal 100 to the network N1. In one example, the communication I / F 106 connects to a network via a cellular communication network (for example, 3G, 4G, or 5G) and communicates with the server 200 through the network.

[0028] In the in-vehicle terminal 100 configured as described above, the control unit 101 collects CAN data while the probe vehicle 10 is running, and stores the collected CAN data in the storage unit 102. The CAN data includes various data acquired by the ECU of the probe vehicle 10 through the in-vehicle sensors. In this embodiment, the CAN data includes at least the traveling speed detected by the vehicle speed sensor 104, the position where the traveling speed was detected by the vehicle speed sensor 104 (the current position of the probe vehicle 10 acquired by the position acquisition unit 105 at the time when the traveling speed was detected by the vehicle speed sensor 104. Hereinafter, this may be referred to as the "speed detection position"), the date and time when the traveling speed was detected by the vehicle speed sensor 104 (hereinafter, this may be referred to as the "speed detection date and time"), the direction of the turn signal operation detected by the turn signal switch 103 (hereinafter, this may be referred to as the "turn signal operation direction"), the position where the turn signal operation was detected by the turn signal switch 103 (the current position of the probe vehicle 10 acquired by the position acquisition unit 105 at the time when the turn signal operation was detected by the turn signal switch 103. Hereinafter, this may be referred to as the "operation detection position"), and the date and time when the turn signal operation was detected by the turn signal switch 103 (hereinafter, this may be referred to as the "operation detection date and time").

[0029] Furthermore, in the in-vehicle terminal 100 configured as described above, the control unit 101 transmits travel information to the server 200 via the communication I / F 106 each time the probe vehicle 10 travels through a road section. As described above, the travel information in this embodiment includes the vehicle ID of the probe vehicle 10, the section ID of the road section traveled by the probe vehicle 10, the travel speed in the road section, the travel date and time in the road section, and the turn signal operation history for the road section. The travel speed in the road section may be the average travel speed during the period in which the probe vehicle 10 travels from the start point to the end point of the road section. The turn signal operation history may be a history of the turn signal operation direction detected by the turn signal switch 103 during the period in which the probe vehicle 10 travels from the start point to the end point of the road section. The travel speed and turn signal operation history may be generated according to the CAN data stored in the memory unit 102. For example, the control unit 101 may first identify data collected on the travel date and time of the road section from the CAN data stored in the storage unit 102 (for example, a travel speed whose speed detection date and time coincides with the travel date and time, and a turn signal operation direction whose operation detection date and time coincides with the travel date and time). Next, the control unit 101 may extract all travel speeds whose speed detection positions belong to the road section from the identified data, and calculate the average value of the extracted travel speeds. Furthermore, the control unit 101 may extract all turn signal operation directions whose operation detection positions belong to the road section from the identified data, and generate a turn signal operation history by arranging the extracted turn signal operation directions in chronological order.

[0030] Next, an example of the configuration of the server 200 will be described. The server 200 in this embodiment is one or more computers operated by a road administrator, a road traffic information service provider, or the like, and corresponds to an information processing device according to the present disclosure. As illustrated in FIG. 1 , the server 200 in this embodiment is configured to include a control unit 201, a storage unit 202, and a communication I / F 203. The control unit 201, the storage unit 202, and the communication I / F 203 of the server 200 are similar to the control unit 101, the storage unit 102, and the communication I / F 106 of the in-vehicle terminal 100, respectively. However, the storage unit 202 of the server 200 stores map data 220 and a driving information DB 221. The communication I / F 203 of the server 200 may be connected to a network via a LAN or Wi-Fi (registered trademark) instead of a cellular communication network.

[0031] Here, the map data 220 and the travel information DB 221 stored in the storage unit 202 of the server 200 will be described. The map data 220 is map data of roads on which a vehicle can travel, and includes link data related to road links, node data related to nodes, and information related to road links. The travel information DB 221 includes travel lane data relating to the number of travel lanes provided, etc. The travel information DB 221 is a database constructed in the storage unit 202 when the processor of the server 200 executes a DBMS (Database Management System) program.

[0032] FIG. 2 is a diagram showing an example of data stored in the travel information DB 221 in this embodiment. As illustrated in FIG. 2, the travel information DB 221 in this embodiment has multiple tables for each pre-classified road section. The road sections in this embodiment are sections corresponding to road links included in the map data 220. Note that the road sections in this embodiment may also be sections that have been independently classified by the operator of the server 200 or the like. In the example shown in FIG. 2, the travel information DB 221 stores M road section tables, from a first road section table to an M-th road section table (M is a natural number greater than or equal to 1), in a format that can be identified by section ID. In this embodiment, the larger the number assigned to a road section, the closer the road section is in the direction of travel. In other words, the M-th road section is the road section immediately before the M-1-th road section in the direction of travel.

[0033] In each of the first to Mth road section tables, a record is registered for each probe vehicle 10. Each record has fields for a vehicle ID, a driving speed, a driving date and time, a turn signal operation history, etc. The vehicle ID field registers an identifier (vehicle ID) of the probe vehicle 10 that traveled through the corresponding road section. The driving speed field registers the driving speed at which the probe vehicle 10 traveled through the corresponding road section. The driving date and time field registers the date and time at which the probe vehicle 10 traveled through the corresponding road section. The turn signal operation history field registers the turn signal operation history of the probe vehicle 10 when it traveled through the corresponding road section. Here, for a probe vehicle 10 in which multiple turn signal operations are detected in the corresponding road section, information that can identify the time series of the turn signal operation direction is registered in the turn signal operation history field. For example, of the probe vehicles 10 registered in the first road section table in FIG. 2, for the probe vehicle 10 with a vehicle ID of "V0001", information indicating "right to left" is registered in the turn signal operation history. This indicates that while traveling on the first road section, first a right turn signal was operated, and then a left turn signal was operated. Note that for a probe vehicle 10 that has operated its turn signal only once while traveling on the corresponding road section, information indicating the direction of that single turn signal operation ("right" or "left") is registered in the turn signal operation history field. Also, for a probe vehicle 10 that has not operated its turn signal even once while traveling on the corresponding road section (for example, a probe vehicle 10 for which "V0002" is registered in the vehicle ID field of the first road section table in FIG. 2), information indicating that there is no turn signal operation history ("none") is registered in the turn signal operation history field.

[0034] 2 is registered in each road section table of the travel information DB 221 by the control unit 201 of the server 200. Specifically, when the communication I / F 203 receives travel information transmitted from the in-vehicle terminal 100, the control unit 201 first identifies the road section table corresponding to the section ID included in the travel information. Next, the control unit 201 adds a new record to the identified section table. The control unit 201 then registers the vehicle ID, travel speed, travel date and time, and blinker operation history included in the received travel information in each field of the added record.

[0035] In the server 200 configured as described above, the control unit 201 periodically identifies the average driving speed for each driving lane in a road section having multiple driving lanes. The average driving speed for each driving lane in each road section is identified based on information registered in the driving information DB 221. The process of identifying the average driving speed for each driving lane in each road section will be described later. In response to identifying the average driving speed for each driving lane in each road section, the control unit 201 of the server 200 transmits the identified average driving speed for each driving lane to an external device. As described above, the external device may be a device for providing congestion information for each road section to a car navigation system or the like of a vehicle.

[0036] (Processing flow) Here, the flow of processing executed by the server 200 in this embodiment will be described with reference to Fig. 3. Fig. 3 is a flowchart showing an example of a processing routine executed by the server 200 at a predetermined cycle (for example, every few minutes to every few tens of minutes). The processing routine in Fig. 3 is executed for each of the M road sections, from the first to the Mth, shown in Fig. 2, but here, a case will be described in which the processing routine is executed for the first road section in Fig. 2. In the following description, it is assumed that the first road section has two driving lanes.

[0037] In the processing routine of FIG. 3, the control unit 201 of the server 200 sets a target probe vehicle 10 from among the probe vehicles 10 that have traveled the first road section during a predetermined period (step S101). The predetermined period is the period from a predetermined time (e.g., about 5 minutes) before the current time to the current time. The target probe vehicle 10 is a probe vehicle 10 that has not operated its turn signal even once while traveling on the first road section, among the probe vehicles 10 that have traveled on the first road section during the predetermined period (i.e., a probe vehicle 10 that is estimated not to have changed lanes while traveling on the first road section). In setting such a target probe vehicle 10, the control unit 201 first accesses the first road section table registered in the travel information DB 221 and identifies records whose travel dates and times registered in the travel date and time field belong to the predetermined period. Next, the control unit 201 extracts, from the identified records, records in which "none" is registered in the turn signal operation history field. Then, the control unit 201 sets the probe vehicle 10 corresponding to the extracted record as the target probe vehicle 10. After completing the process of step S101, the control unit 201 executes the process of step S102.

[0038] In step S102, the control unit 201 calculates the distribution of the number of target probe vehicles 10 by traveling speed by counting the number of target probe vehicles 10 that traveled the first road section during a predetermined period according to the traveling information of the target probe vehicles 10 set in step S101. After completing the processing of step S102, the control unit 201 executes the processing of step S103.

[0039] In step S103, the control unit 201 generates an approximate curve of the number distribution by performing curve approximation on the number distribution calculated in step S102. In one example, the control unit 201 may generate a histogram of the number distribution calculated in step S102, and then perform curve approximation on the generated histogram using a known interpolation method, kernel density estimation method, or the like, to generate the approximate curve of the number distribution.

[0040] Here, the correlation between the actual average traveling speed for each traveling lane in the first road section and the approximate curve of the vehicle count distribution will be described with reference to FIG. 4. In the example shown in FIG. 4, the first road section is a road section (a so-called road section with two lanes in each direction) with two traveling lanes (the first traveling lane and the second traveling lane in FIG. 4) traveling in the same direction. In the example shown in FIG. 4(A), the average traveling speed of the target probe vehicles 10 traveling in the first traveling lane is 75 km / h, and the average traveling speed of the target probe vehicles 10 traveling in the second traveling lane is 105 km / h. For the first road section in which the average traveling speed differs for each traveling lane, when the approximate curve of the vehicle count distribution is generated according to the procedure described in steps S101 to S103, an approximate curve Ac1 having two maximum values ​​Lm1 and Lm2 is generated, as shown in FIG. 4(B). In other words, when the approximate curve of the vehicle count distribution is generated for a road section in which the average traveling speed differs for each traveling lane, the same number of maximum values ​​as the number of traveling lanes appears. Furthermore, the traveling speeds of the target probe vehicle 10 included in the two maximum values ​​Lm1 and Lm2 are approximately equal to the average traveling speeds of the first and second traveling lanes, respectively. As a result of repeated and diligent investigations, the inventors have found that the correlation shown in FIG. 4 holds even when the number of travel lanes is three or more.

[0041] Returning now to the description of FIG. 3 , upon completing the process of step S103, the control unit 201 executes the process of step S104. In step S104, the control unit 201 determines whether the number of local maxima included in the approximation curve of the vehicle count distribution generated in step S103 matches the number of driving lanes in the first road section. The number of driving lanes in the first road section is obtained from the map data 220 stored in the memory unit 202. If the number of local maxima included in the approximation curve of the vehicle count distribution does not match the number of driving lanes in the first road section (a negative determination in step S104), the control unit 201 terminates the execution of the processing routine of FIG. 3 . If the number of local maxima included in the approximation curve of the vehicle count distribution does not match the number of driving lanes in the first road section, the control unit 201 may calculate the average driving speed of all driving lanes in the first road section. On the other hand, if the number of maximum values ​​included in the approximate curve of the vehicle count distribution matches the number of driving lanes in the first road section (positive judgment in step S104), it can be determined that the average driving speed in the first road section differs for each driving lane, and therefore the control unit 201 executes processing in step S105.

[0042] In step S105, the control unit 201 determines the correspondence between the maximum values ​​included in the approximate curve of the vehicle count distribution generated in step S103 and the driving lanes. Here, in the example shown in FIG. 4, the control unit 201 determines whether each of the two maximum values ​​Lm1 and Lm2 included in the approximate curve Ac1 of the vehicle count distribution corresponds to the first driving lane or the second driving lane of the first road section. Such a determination is made based on the blinker operation history when the target probe vehicle 10 included in the number of vehicles of either the maximum value Lm1 or Lm2 traveled through the second road section just before the first road section. Specifically, first, the control unit 201 accesses the first road section table of the travel information DB 221 and identifies the target probe vehicle 10 included in the number of vehicles of the maximum value Lm1. That is, the control unit 201 identifies, from among the target probe vehicles 10 registered in the first road section table, target probe vehicles 10 whose travel speed registered in the travel speed field matches or differs by within a few km / h from the travel speed corresponding to the maximum value Lm1 (75 km / h in the example shown in FIG. 4). The control unit 201 accesses the second road section table using the vehicle ID of the identified target probe vehicle 10 as an argument, and identifies records in which information matching the vehicle ID is registered in the vehicle ID field. Then, the control unit 201 extracts, from the identified records, records in which one or more turn signal operation histories are registered in the turn signal operation history field. The control unit 201 determines whether the target probe vehicle 10 traveled in the first travel lane or the second travel lane in the first road section, based on the information registered in the turn signal operation history field of the extracted record.

[0043] 5, if the last turn signal operation direction when the target probe vehicle 10 was traveling in the second road section was to the left, it can be determined that the target probe vehicle 10 was traveling in the left-hand driving lane (first driving lane) of the first road section. In response to this, the control unit 201 determines that the maximum value Lm1 corresponds to the first driving lane of the first road section (the number of maximum values ​​Lm1 corresponds to the number of target probe vehicles 10 that traveled in the first driving lane of the first road section). Then, the control unit 201 determines that the remaining maximum value Lm2 corresponds to the second driving lane of the first road section (the number of maximum values ​​Lm2 corresponds to the number of target probe vehicles 10 that traveled in the second driving lane of the first road section). If the last blinker operation direction when the target probe vehicle 10 was traveling in the second road section was to the right, it can be determined that the target probe vehicle 10 was traveling in the right-hand driving lane (second driving lane) of the first road section. In this case, the control unit 201 may determine that the maximum value Lm1 corresponds to the second driving lane of the first road section.

[0044] Furthermore, if the first road section has three driving lanes, and the target probe vehicles 10 included in one of the three local maximum values ​​travel on the second road section and the last two turn signal operations are right turn signal operations, the local maximum value can be determined to correspond to the right driving lane in the first road section. Furthermore, if the target probe vehicles 10 included in another of the three local maximum values ​​travel on the second road section and the last two turn signal operations are left turn signal operations, the local maximum value can be determined to correspond to the left driving lane in the first road section. Once the driving lanes corresponding to two of the three local maximum values ​​have been determined in this manner, the remaining local maximum value can be determined to correspond to the middle driving lane in the first road section.

[0045] Returning to the description of FIG. 3, after completing the process of step S105, the control unit 201 executes the process of step S106. In step S106, the control unit 201 identifies the average traveling speed for each traveling lane in the first road section according to the correspondence determined in step S105. Here, if it is determined that the maximum value Lm1 in the example shown in FIG. 4 corresponds to the first traveling lane in the first road section and the maximum value Lm2 corresponds to the second traveling lane in the first road section, the control unit 201 identifies the traveling speed (75 km / h) of the target probe vehicle 10 included in the number of vehicles with the maximum value Lm1 as the average traveling speed of the first traveling lane, and identifies the traveling speed (105 km / h) of the target probe vehicle 10 included in the number of vehicles with the maximum value Lm2 as the average traveling speed of the second traveling lane. After completing the process of step S106, the control unit 201 executes the process of step S107.

[0046] In step S107, the control unit 201 outputs the average driving speed for each lane in the first road section. Outputting the average driving speed for each lane in the first road section may, for example, include transmitting the average driving speed for each lane in the first road section to an external device that provides congestion information to a car navigation system of the vehicle or the like via the communication I / F 203. In another example, outputting the average driving speed for each lane in the first road section may include calculating a congestion level for each lane in accordance with the average driving speed for each lane in the first road section, and transmitting the calculated congestion level for each lane to the car navigation system of the vehicle via the communication I / F 203 and / or displaying it on a website that publishes road traffic information. After completing the process of step S107, the control unit 201 terminates the execution of the processing routine of FIG. 3.

[0047] (Actions and Effects of the Embodiments) In the above-described embodiment, the server 200 uses the travel speed and blinker operation history for each road section collected from the probe vehicle 10 to identify the average travel speed for each travel lane in each road section over a recent period (predetermined period) from the present time. This makes it possible to identify the average travel speed for each travel lane in each road section even when a sensor such as a GPS cannot accurately identify the travel lane in which the probe vehicle 10 is traveling. As a result, it becomes possible to estimate the traffic conditions (e.g., the degree of congestion) for each travel lane in each road section. Furthermore, in the above-described embodiment, the travel speed and blinker operation history used to identify the average travel speed for each travel lane in each road section can be limited to those collected from probe vehicles 10 that are estimated not to have changed lanes while traveling in each road section, thereby making it possible to more accurately identify the average travel speed for each travel lane.

[0048] <Other> The above-described embodiment is merely an example, and the present disclosure may be modified as appropriate without departing from the spirit thereof. For example, part of the processing executed by the server 200 may be executed by another computer connected to the server 200 via a network. The present disclosure can also be realized by supplying a computer program (information processing program) that implements the functions described in the above embodiments to a computer, and having one or more processors in the computer read and execute the program. [Explanation of symbols]

[0049] 10 Vehicle, 200 Server, 201 Control unit, 202 Storage unit, 203 Communication I / F, 220 Map data, 221 Travel information DB

Claims

1. receiving driving information from each of a plurality of probe vehicles, the driving speed in each road section, the date and time when each road section was driven, and the turn signal operation history in each road section; calculating a distribution of the number of probe vehicles by travel speed by counting, according to the travel information, the number of probe vehicles that have traveled on a first road section having two or more travel lanes during a predetermined period from a time point a predetermined time before the current time to the current time, by travel speed; Identifying an average driving speed for each of the two or more driving lanes in the first road section according to two or more maximum values ​​obtained by curve approximating the vehicle number distribution and the turn signal operation history included in the driving information; outputting the average driving speed for each of the two or more driving lanes in the first road section; A control unit that executes Information processing device.

2. Calculating the average driving speed of each of the two or more driving lanes in the first road section includes: acquiring the turn signal operation history in a second road section preceding the first road section from the travel information of the probe vehicle included in each of the two or more local maximum values; determining, according to the acquired turn signal operation history, which of the two or more driving lanes in the first road section each of the two or more maximum values ​​corresponds to; Including, The information processing device according to claim 1 .

3. Calculating the number distribution of the probe vehicles by traveling speed includes: setting a target probe vehicle, which is a probe vehicle in which a turn signal operation has not been performed during the first road section, from among the probe vehicles that have traveled the first road section during the predetermined period according to the turn signal operation history; Calculating the vehicle number distribution by counting the number of the set target probe vehicles by traveling speed; Including, The information processing device according to claim 1 .

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