Driving history analysis system

Abstract

To provide a driving history analysis system that increases a possibility of identifying parking information such as parking of a vehicle in a parking lot even if data for the parking lot is insufficient.SOLUTION: A driving history analysis system comprises: a driving history acquisition unit that acquires a driving history of a vehicle parked in a polygon area of a parking lot associated with an attribute of the parking lot; an analysis target history acquisition unit that acquires an analysis target history which is a driving history of a vehicle parked in a polygon area of a non-parking lot to which no parking lot attribute is associated; and an attribute determination unit that determines the attribute of non-parking lot polygon. The attribute determination unit records the non-parking lot polygon as the parking lot polygon in a recording unit when a distance between the parking lot polygon indicated by the driving history and the non-parking lot polygon indicated by the analysis target history is less than a predetermined threshold.SELECTED DRAWING: Figure 1

Description

[Technical Field]

[0001] The present invention relates to a driving history analysis system. [Background technology]

[0002] Patent Document 1 describes a system that verifies whether a polygon belonging to a probe car's parking location is a site related to the destination, and if it is confirmed that there is a relationship between the two, registers the deviation position from the final driving link and identifies the entrance to the parking lot based on this registered deviation position. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Patent No. 5437674 Summary of the Invention [Problem to be solved by the invention]

[0004] Although the system described in Patent Document 1 can identify the entrance to a parking lot, the polygon of the parking lot may differ from the shape of the actual parking lot, and in such cases, the polygon of the parking spot may not be linked to the parking lot. For example, if a parking lot is divided into sections, polygon data may not be linked to a specific parking lot, and even if the vehicle is actually parked in the linked parking lot, it may not be recognized as having been parked in the linked parking lot, which could result in the inability to obtain information about parking or driving history.

[0005] The present invention has been made in consideration of the above-mentioned problems, and aims to provide a driving history analysis system that increases the possibility of identifying information regarding parking, such as parking in a parking lot, even when data on the parking lot is insufficient. [Means for solving the problem]

[0006] In order to achieve the above object, the present invention comprises a driving history acquisition unit that acquires the driving history of vehicles parked in an area of ​​a parking lot polygon that is associated with a parking lot attribute, an analysis target history acquisition unit that acquires an analysis target history that is the driving history of vehicles parked in an area of ​​a non-parking lot polygon that is not associated with the parking lot attribute, and an attribute determination unit that determines the attributes of the non-parking lot polygon, and when the distance between the parking lot polygon indicated by the driving history and the non-parking lot polygon indicated by the analysis target history is less than a predetermined threshold, the attribute determination unit records the non-parking lot polygon in a recording unit as the parking lot polygon.

[0007] That is, in the driving history analysis system, if the distance between a parking lot polygon associated with a parking lot attribute and a non-parking lot polygon not associated with a parking lot attribute is less than a predetermined threshold, the non-parking lot polygon is recorded as a parking lot polygon. This makes it possible to identify polygons not associated with a parking lot attribute that are likely to represent a parking lot as parking lots. As a result, even if data on parking lots is insufficient, it is possible to increase the possibility of identifying information related to parking, such as parking in a parking lot.

[0008] In order to achieve the above object, the present invention comprises a driving history acquisition unit that acquires the driving history of vehicles parked in an area of ​​a parking lot polygon associated with a parking lot attribute, an analysis target history acquisition unit that acquires an analysis target history that is the driving history of vehicles parked in an area of ​​a non-parking lot polygon that is not associated with the parking lot attribute, and an attribute determination unit that determines the attributes of the non-parking lot polygon, and when a first parking locus that is the locus of a vehicle parked in the area of ​​the non-parking lot polygon indicated by the analysis target history and a second parking locus that is the locus of a vehicle parked in the area of ​​the parking lot polygon indicated by the driving history satisfy a predetermined condition, the attribute determination unit records the non-parking lot polygon as the parking lot polygon in a recording unit.

[0009] That is, in the driving history analysis system, if the parking locus (first parking locus) of a non-parking lot polygon that is not associated with a parking lot attribute and the parking locus (second parking locus) of a parking lot polygon that is associated with a parking lot attribute satisfy a predetermined condition (for example, the parking locus is similar), the non-parking lot polygon is recorded as a parking lot polygon. This makes it possible to identify polygons that are not associated with a parking lot attribute and that are likely to represent a parking lot as parking lots. As a result, even if data on parking lots is not sufficiently available, it is possible to increase the possibility of identifying information related to parking, such as parking in a parking lot. [Brief explanation of the drawings]

[0010] [Figure 1] 1 is a block diagram showing the configuration of a driving history analysis system according to an embodiment of the present invention; [Figure 2] FIG. 10 is a diagram illustrating a configuration for determining the attributes of non-parking lot polygons based on the distance between polygons. [Figure 3] FIG. 10 is another diagram illustrating a configuration for determining the attributes of non-parking lot polygons based on the distance between polygons. [Figure 4] FIG. 10 is yet another diagram illustrating a configuration for determining the attributes of non-parking lot polygons based on the distance between polygons. [Figure 5] 10 is a diagram illustrating a configuration for determining attributes of a non-parking lot polygon based on a parking lot locus. FIG. [Figure 6] 4 is a flowchart illustrating an example of processing of the system according to the present embodiment. [Figure 7] 10 is a subroutine in the processing of the system in this embodiment. [Figure 8] 10 is another subroutine in the processing of the system in this embodiment. DETAILED DESCRIPTION OF THE INVENTION

[0011] Here, the embodiments of the present invention will be described in the following order. (1) Configuration of the driving history analysis system: (2) Flowchart: (3) Other embodiments:

[0012] (1) Configuration of the driving history analysis system: The driving history analysis system in this embodiment is a system that acquires and analyzes driving history information about which parking lots a vehicle has been parked in. FIG. 1 is a block diagram showing the configuration of a driving history analysis system 10 according to the present invention. The driving history analysis system 10 is a server that can communicate with a vehicle 100. Although not shown, the driving history analysis system 10 can communicate with multiple vehicles.

[0013] Vehicle 100 is a so-called probe car, and includes a communication unit 110 and a positioning unit 120. Vehicle 100 also includes a recording medium (not shown) that records map information 130 and driving history 140. Communication unit 110 is a wireless communication circuit for wirelessly communicating with driving history analysis system 10. Positioning unit 120 includes positioning sensors such as a GNSS (Global Navigation Satellite System) receiver, a vehicle speed sensor, and a gyro sensor (none of which are shown).

[0014] The map information 130 includes node data indicating the positions of nodes set on the roads on which the vehicle travels, shape interpolation point data indicating the positions of shape interpolation points for identifying the shape of the roads between nodes, link data indicating the connections between nodes, and facility data indicating the positions of facilities on the roads and in their surrounding areas.

[0015] The facility data may include various types of information. The various types of information include, for example, polygon data that indicates the two-dimensional shape of the facility. Specifically, for example, a polygon that indicates the shape of the perimeter of the facility is divided into triangles, and information that indicates each triangle (for example, information that indicates vertices) is associated with the facility data as polygon data. Note that the polygon data may not be divided into triangles, and information that indicates each vertex of the polygon may be associated with the facility data. Note that the facility data is associated with the name of the facility.

[0016] The facility data may also include information indicating the attributes of the facility. In this embodiment, if the attribute of the facility is a parking lot, information indicating that the attribute of the facility is a parking lot is associated with the facility data. If an attribute indicating that the facility is a parking lot is associated with the facility data, the polygon is said to be associated with an attribute indicating that the parking lot is associated, and such a polygon is defined as a parking lot polygon. On the other hand, if the attribute of the facility is not associated with information indicating that the facility is a parking lot, the polygon associated with the facility data is defined as a non-parking lot polygon. Note that if the attribute of the facility is a parking lot, a name such as "XX Parking Lot" or "XX Park" is associated as the name of the facility.

[0017] The driving history 140 includes, as probe information, at least information relating to the parking of the vehicle 100. Specifically, the driving history 140 is associated with identification information of the vehicle 100, and includes information indicating the vehicle's positions over time (at regular intervals or at regular times), which is the vehicle's trajectory. In this embodiment, the driving history is a single history from the start to the end of the vehicle 100's driving, and the end point of the driving is the parking position. Each vehicle position is associated with information indicating whether map matching has been performed. If map matching has been performed, the vehicle's position is on a road, and if map matching has not been performed, the vehicle is off the road (for example, in a facility such as a parking lot).

[0018] The vehicle 100 then transmits the probe information including the driving history 140 to the driving history analysis system 10 via the communication unit 110 at regular time intervals.

[0019] Next, the driving history analysis system 10 will be described. The driving history analysis system 10 includes a control unit 20 equipped with a CPU, RAM, ROM, etc., a recording unit 30, and a communication unit 40. The recording unit 30 records various programs and various data. The communication unit 40 is a wireless communication circuit for wireless communication with the vehicle 100. The control unit 20 executes various programs stored in the recording unit 30 and ROM. The control unit 20 can execute a driving history analysis program 21 as an example of this program, and in this embodiment, can modify information associated with polygons of map information based on the driving history.

[0020] The recording unit 30 records map information 30a and driving history 30b. The map information 30a includes node data, shape interpolation point data, link data, facility data, etc. The map information 30a in the driving history analysis system 10 is updated based on probe information from each probe car, including the vehicle 100. That is, the accuracy of the map information 30a is improved by updating the map information based on the probe information. The driving history 30b, like the driving history 140 of the vehicle 100, includes at least information about parking, such as the vehicle's trajectory. The driving history 30b also includes probe information from each probe car, including the vehicle 100. That is, the driving history 30b records a large number of driving histories corresponding to the identification information of a large number of vehicles.

[0021] The relationship between facility data and polygon data will now be described. As described above, facility data may include polygon data that represents the two-dimensional shape of a facility. The polygon data associated with the facility data may not have facility attributes associated with it. This is because it is difficult to accurately define polygons and attributes for all facilities on a map, and some facility data may be inaccurate or insufficient. That is, even if polygon data exists, facility data may exist, but attributes may not be associated with the facility data. Furthermore, a parking lot may be represented by multiple polygons (in other words, multiple facility data). In this case, parking lot attributes may be associated with some polygons, while parking lot attributes may not be associated with the remaining polygons. This embodiment is configured to determine the attributes of polygons that do not have parking lot attributes associated with them, i.e., non-parking lot polygons.

[0022] The control unit 20 can execute various programs stored in the recording unit 30 or ROM. The control unit 20 of this embodiment can execute a driving history analysis program 21 as an example of this program. The driving history analysis program 21 is a program that causes the control unit 20 to function as a driving history acquisition unit 21a, an analysis target history acquisition unit 21b, and an attribute determination unit 21c. Note that, hereinafter, the processes described as being performed by the driving history acquisition unit 21a, the analysis target history acquisition unit 21b, and the attribute determination unit 21c are processes that are realized by the control unit 20.

[0023] The driving history acquisition unit 21a acquires the driving history of vehicles parked in the area of ​​a parking lot polygon associated with parking lot attributes. Specifically, the driving history acquisition unit 21a acquires the driving history recorded in the recording unit 30. At this time, the driving history acquisition unit 21a identifies the parking spot of the vehicle and, with reference to the map information 30a, determines whether the parking spot is included in the polygon based on the parking spot. If the parking spot is included in the polygon, the driving history acquisition unit 21a identifies the attribute of the facility corresponding to the polygon with reference to the map information 30a. Then, the driving history acquisition unit 21a acquires the driving history of vehicles for which the facility attribute is identified as a parking lot.

[0024] The analysis target history acquisition unit 21b acquires the analysis target history, which is the driving history of vehicles parked in areas of non-parking lot polygons that are not associated with parking lot attributes. Specifically, the analysis target history acquisition unit 21b acquires the driving history recorded in the recording unit 30. At this time, the analysis target history acquisition unit 21b identifies the parking spot of the vehicle and, with reference to the map information 30a, determines whether the parking spot is included in a polygon based on the parking spot. If the parking spot is included in a polygon, the analysis target history acquisition unit 21b refers to the map information 30a and acquires one driving history in which the attribute of the facility corresponding to the polygon is not a parking lot attribute, and sets that driving history as the analysis target.

[0025] The attribute determining unit 21c determines the attributes of the non-parking lot polygons. Specifically, it determines the attributes of the non-parking lot polygons acquired by the analysis target history acquiring unit 21b. Hereinafter, the determination of the attributes of the non-parking lot polygons will be specifically described.

[0026] The control unit 20 first determines whether a parking lot polygon exists among polygons adjacent to a non-parking lot polygon. That is, the control unit 20 determines whether a polygon associated with a parking lot attribute exists around a non-parking lot polygon to which a parking lot attribute is not associated. If the control unit 20 determines that a parking lot polygon exists around a non-parking lot polygon, it determines whether the distance between the non-parking lot polygon and the parking lot polygon is less than a predetermined threshold. If the control unit 20 determines that the distance between the non-parking lot polygon and the parking lot polygon is less than the threshold, it further determines whether a vehicle parked in the area of ​​the non-parking lot polygon passed through the parking lot polygon. Specifically, the control unit 20 references the analysis target history and determines whether the vehicle passed through other polygons before entering the polygon containing the parking spot based on the driving position and map information 30a. If a vehicle parked in a non-parking lot polygon passed through other polygons before entering the polygon containing the parking spot, the control unit 20 identifies the polygon through which the vehicle passed immediately before entering the polygon containing the parking spot. When the control unit 20 identifies the polygon through which the vehicle traveled immediately before entering the polygon containing the parking spot and determines that the polygon through which the vehicle traveled immediately before entering is a parking lot polygon, it assigns a parking lot attribute to the non-parking lot polygon. Additionally, the control unit 20 associates the non-parking lot polygon with the same name as the name associated with the parking lot polygon. In other words, the control unit 20 regards the non-parking lot polygon as an adjacent parking lot polygon. The control unit 20 then records the non-parking lot polygon as a parking lot polygon in the recording unit 30.

[0027] With reference to Figure 2, the determination of the attributes of non-parking lot polygons will be specifically described. In the example shown in Figure 2, there is a parking lot that includes three polygons P1, P2, and P3 as a whole, and these three polygons P1, P2, and P3 include parking lot polygons and non-parking lot polygons. In Figure 2, the symbol E indicates the entrance / exit to the parking lot, the symbol O indicates a point on the road where map matching failed, and the symbol P indicates the parking point of the vehicle. Roads R and the like exist around polygons P1, P2, and P3. Road R is a road with intersections I1 and I2 as its endpoints (nodes). In Figure 2, the dashed lines indicate an example of a vehicle's parking trajectory, and the dashed-dotted lines indicate links connecting the nodes.

[0028] In the example of FIG. 2, of polygons P1, P2, and P3, only polygon P2 is a parking lot polygon. In other words, only polygon P2 is associated with a parking lot attribute. In the example shown in FIG. 2, a "☆" is added to the area of ​​polygon P2 to indicate that polygon P2 is associated with a parking lot attribute and is a parking lot polygon. On the other hand, polygons P1 and P3 are non-parking lot polygons, that is, polygons P1 and P3 are not associated with a parking lot attribute.

[0029] Since the parking spot is within polygon P1 and polygon P1 is a non-parking lot polygon, the control unit 20 determines whether polygon P2, which is an adjacent polygon, is a parking lot polygon. As described above, polygon P2 is a parking lot polygon, so it determines whether the distance L between polygon P1 and polygon P2 is less than a threshold. Note that the distance L between polygon P1 and polygon P2 is the length of a perpendicular line connecting the points where the perimeter of one polygon (polygon P1) and the perimeter of the other polygon (polygon P2) are closest to each other. In the example shown in FIG. 2, one side of polygon P1 and polygon P2 overlap, and the length of the perpendicular line (i.e., the distance L between the polygons) is "0." Therefore, it can be said that the distance L is less than the threshold.

[0030] The control unit 20 further determines whether the vehicle parked in the area of ​​polygon P1 passed through polygon P2. Specifically, the control unit 20 refers to the analysis target history and determines whether the vehicle passed through other polygons (e.g., polygons P2 and P3) before entering polygon P1 that includes the parking spot. If the vehicle parked in polygon P1 passed through other polygons P2 and P3 before entering polygon P1, the control unit 20 identifies the polygon through which the vehicle traveled immediately before entering polygon P1, and determines whether the identified polygon is associated with a parking lot attribute. In the example shown in FIG. 2, the polygon through which the vehicle traveled immediately before entering polygon P1 that includes the parking spot is polygon P2, and polygon P2 is a parking lot polygon.

[0031] If the polygon through which the vehicle traveled immediately before entering the polygon containing the parking spot is a parking lot polygon, the control unit 20 assigns a parking lot attribute to the non-parking lot polygon. Therefore, in the example shown in FIG. 2, the control unit 20 assigns a parking lot attribute to polygon P1. Furthermore, in this embodiment, when the control unit 20 assigns a parking lot attribute to a non-parking lot polygon, it assigns a name associated with the adjacent parking lot polygon. In other words, the control unit 20 regards the non-parking lot polygon as a parking lot polygon and associates the name associated with polygon P2 with polygon P1.

[0032] On the other hand, as shown in Figure 3, if the distance between polygon P1 and polygon P2 is large, that is, if the distance L between polygon P1 and polygon P2 is equal to or greater than a threshold, the control unit 20 considers it difficult to conclude whether the vehicle parking point P is a parking lot or not, and does not associate a parking lot attribute with the facility data of polygon P1.

[0033] Next, as shown in FIG. 4, an example will be described in which, of polygons P1, P2, and P3, polygon P3 is a parking lot polygon and polygons P1 and P2 are non-parking lot polygons. In the example shown in FIG. 4, the vehicle's parking spot P is within polygon P1. When parking within polygon P1, the vehicle passes through polygon P3, which is a parking lot polygon, but polygon P2, through which the vehicle traveled just before entering polygon P1, is a non-parking lot polygon and is not associated with a parking lot attribute. Therefore, the control unit 20 deems it difficult to conclude whether the vehicle's parking spot P is a parking lot or not, and does not associate a parking lot attribute with the facility data of polygon P1.

[0034] In this manner, in this embodiment, when the distance between a parking lot polygon associated with a parking lot attribute and a non-parking lot polygon not associated with a parking lot attribute is less than a predetermined threshold, the non-parking lot polygon is assigned a parking lot attribute and recorded as a parking lot polygon. This makes it possible to identify polygons not associated with a parking lot attribute but that are likely to represent a parking lot as parking lots. As a result, even if data on parking lots is insufficient, it is possible to increase the likelihood of identifying information related to parking, such as parking in a parking lot.

[0035] Next, an example of a case where a vehicle does not pass through a parking lot polygon before entering a polygon including a parking spot will be described. As described above, if a vehicle passes through a parking lot polygon before entering a polygon including a parking spot, the control unit 20 assigns a parking lot attribute to the non-parking lot polygon. On the other hand, if a vehicle does not pass through a parking lot polygon before entering a polygon including a parking spot, the control unit 20 determines the attribute of the polygon including the parking spot by comparing a parking trajectory based on the driving history, which is the history to be analyzed, with a parking trajectory based on the driving history of parking in the area of ​​the parking lot polygon, in addition to making a determination based on the distance between adjacent polygons. Note that in this embodiment, if the distance between the non-parking lot polygon and the parking lot polygon is equal to or greater than a threshold, it is considered difficult to consider the parking spot as a parking lot, as described above, and the parking lot attribute is not assigned to the non-parking lot polygon (i.e., the process of considering the non-parking lot polygon as a parking lot polygon is not performed). Therefore, an example of a case where a vehicle does not pass through a parking lot polygon before entering a polygon including a parking spot will be described assuming that the distance between the polygon including the parking spot and the parking lot polygon is less than a threshold.

[0036] If a vehicle does not pass through a parking lot polygon before entering a polygon containing a parking spot, assuming that the distance between the parking spot polygon and the parking lot polygon is less than a threshold (i.e., they are adjacent), the polygon containing the parking spot is assumed to be located in front of the parking lot polygon. However, even if the polygon containing the parking spot is located in front of the parking lot polygon, the parking spot is not necessarily a parking lot. As in the above example, once a parking lot polygon has been passed, there is little error in treating a non-parking lot polygon as a parking lot polygon. However, if the vehicle has not yet passed through or entered the parking lot polygon, there may be an error in treating the polygon containing the parking spot as a parking lot polygon. Therefore, in this embodiment, if a vehicle has not passed through a parking lot polygon before entering the polygon containing the parking spot, the attributes of the polygon containing the parking spot are determined based on the parking trajectory.

[0037] Here, the parking trajectory of the vehicle will be described. The parking trajectory is information indicating the time-series transition of the vehicle's position, and is calculated by vehicle 100, which is a probe car. Specifically, as described above, vehicle 100 is equipped with a GNSS receiver, a vehicle speed sensor, and a gyro sensor as positioning sensors. The GNSS receiver receives radio waves from navigation satellites and outputs a signal for calculating the current location of the vehicle via an interface (not shown). The vehicle speed sensor outputs a signal corresponding to the rotational speed of the wheels of the vehicle. The gyro sensor detects the angular acceleration of the vehicle turning in a horizontal plane, and outputs a signal corresponding to the orientation of the vehicle.

[0038] The vehicle 100 acquires the current location of the vehicle by a control unit (not shown) within a facility such as a parking lot (i.e., outside a road) based on a self-contained navigation trajectory, which is a trajectory of a position estimated based on signals output from a vehicle speed sensor and a gyro sensor, and on map information 130. If the target for acquiring the current location is a road, multiple possible comparison roads are set, and the comparison roads are narrowed down based on the error circle of the GNSS signal acquired by the GNSS receiver. The vehicle 100 then performs a map matching process with reference to the map information 130 to estimate that the road on which the vehicle is traveling is the road whose shape most closely matches the self-contained navigation trajectory among the narrowed down comparison roads, and acquires the current location of the vehicle on the road estimated by the map matching process. During the traveling process, the vehicle 100 executes a process for acquiring the current location of the vehicle based on output signals from the GNSS receiver, the vehicle speed sensor, and the gyro sensor at predetermined distance intervals or predetermined time intervals. Then, the vehicle 100 acquires information indicating the history of the current location at predetermined intervals, that is, information indicating the transition of the current location, as a parking trace, and records the acquired parking trace in the travel history 140.

[0039] The parking trajectory calculated in this manner is transmitted from the vehicle 100 to the driving history analysis system 10 and recorded in the recording unit 30 in the driving history analysis system 10. Therefore, the control unit 20, using the function of the analysis target history acquisition unit 21b, refers to the recording unit 30 to acquire parking trajectories in which parking points are included in non-parking lot polygons.

[0040] In this embodiment, a driving history 30b is recorded in the recording unit 30, and the driving history 30b includes information related to the parking trajectory of the vehicle. The control unit 20 calculates a parking trajectory S to a parking spot P, using a point on the road that is out of map matching as the origin O (i.e., the start point of the parking trajectory). Specifically, the control unit 20 acquires one analysis target history in which the attribute of the facility corresponding to the polygon that includes the parking spot is not a parking lot attribute, and acquires the parking trajectory S of that analysis target history. The control unit 20 acquires the parking trajectory S by referring to the driving history 30b recorded in the recording unit 30.

[0041] More specifically, the control unit 20 extracts coordinates for every certain distance a [m] from the origin O to the parking point P, which are points outside the map matching, to obtain the parking trajectory S. For example, if the distance from the origin O of the parking trajectory to the parking point P is b [m], the number of extracted points d is d=b / a[pieces] This becomes:

[0042] The control unit 20 calculates the coordinates for the number of extraction points d. If the coordinates of the starting point of the parking trajectory are S0(X0, Y0), the parking trajectory S from the starting point to the parking point (i.e., parking completion) can be expressed as follows: S=(S0(X0,Y0),S1(X1,Y1),S2(X2,Y2),…S d (X d ,Y d ))

[0043] The control unit 20 performs the same process on the parking lot polygon, which is the comparison target history. As described above, the recording unit 30 includes the driving history 30b, which includes the parking locus. Therefore, the control unit 20, by using the function of the driving history acquisition unit 21a, selects, from the recorded parking history, the parking locus S, which has a parking point included in the parking lot polygon and has the same length as the parking locus S, which is the analysis target history. αSpecifically, the control unit 20 refers to the parking locus whose parking point is included in the parking lot polygon, and extracts the parking locus S whose distance from the origin O is the same as that of the parking locus S. α The acquired parking trajectory S α can be shown as follows: S α =(S α0 (X α0 ,Y α0 ),S α1 (X α1 ,Y α1 ),…S αd (X αd ,Y αd )) In addition, the parking trajectory S α The calculation method of is the same as the calculation method of the parking locus S, which is the history to be analyzed, and therefore will be omitted.

[0044] Next, the control unit 20 calculates the parking trajectory S and the parking trajectory S α Specifically, the control unit 20 compares the parking trajectory S with the parking trajectory S α Calculate the distance between the corresponding points of the parking trajectory S and the parking trajectory S α That is, the control unit 20 calculates the deviation of the parking locus S from the parking locus S. α and the corresponding coordinates (e.g., S0 and S α0 The control unit 20 then determines whether the sum of the calculated distances is the difference between the two trajectories and whether it is less than a predetermined value. α If it is determined that the sum of the distances of the points on the parking trajectory S and the parking trajectory S is less than a predetermined value, α are considered to be similar or the same. In other words, the control unit 20 determines that the vehicle parked in the non-parking lot polygon along a trajectory similar to the trajectory taken when the vehicle was parked inside the parking lot polygon, and since the two polygons are close, the attribute of the facility associated with the non-parking lot polygon can be considered to be a parking lot. In other words, the control unit 20 considers the non-parking lot polygon to be a parking lot polygon.

[0045] In addition, parking trajectory S and parking trajectory Sα If the sum of the distances between the parking locus S and the parking data is equal to or greater than a predetermined value, the control unit 20 β and parking trajectory S and parking trajectory S β This process of comparing the parking loci is repeated at least until it is determined that the distance of the parking loci is less than a predetermined value. In this embodiment, the parking locus S corresponds to the "first parking locus" and the parking locus S α corresponds to the "second parking trajectory", and the fact that the parking trajectories are similar or the same corresponds to the "predetermined condition".

[0046] With reference to Figure 5, a specific example will be described in which a vehicle does not pass through a parking lot polygon before entering a polygon containing a parking spot. In the example shown in Figure 5, the same reference numerals are used to indicate the same information as in Figure 2. In the example shown in Figure 5, the vehicle's parking spot P is within polygon P1. Of polygons P1, P2, and P3, polygon P2 is a parking lot polygon, and polygons P1 and P3 are non-parking lot polygons. In the example shown in Figure 5, the polygon containing the parking spot is located in front of parking lot polygon P3, and therefore polygon P3 is the polygon to be analyzed.

[0047] The control unit 20 calculates the parking trajectory S from the origin O, which is a point outside the map matching, to the parking point P. In addition, the control unit 20 extracts a parking history to be compared recorded in the driving history 30b, and extracts and calculates a parking trajectory having the same length as the parking trajectory S in the comparison history. In the example shown in FIG. 5, the control unit 20 extracts comparison data α and comparison data β as comparison histories, and calculates the parking trajectory S in the comparison data α. α and the parking trajectory in the comparison data β is expressed as the parking trajectory S β In addition, in FIG. 5, the parking trajectory S α is shown by a dashed line, and the parking trajectory S β is indicated by a two-dot chain line.

[0048] The control unit 20 compares the parking locus S with the parking locus S. Specifically, the control unit 20 compares the parking locus S with the parking locus S. α Comparison with parking trajectory S and parking trajectory S β As shown in Figure 5, the parking trajectory S and the parking trajectory S α The parking trajectories S and S are almost overlapping and the difference is small. α It can be said that the parking trajectory S and the parking trajectory S are similar. α The difference between the parking trajectory S and the parking trajectory S is less than a predetermined value. β That is, even if the trajectories are the same length, the end point of the parking trajectory S is within the polygon P3, while the end point of the parking trajectory S β The end points of the parking trajectories S and S are within the polygon P2, and the parking trajectories are not similar to each other. β The difference between them is equal to or greater than a predetermined value.

[0049] In this way, in the example shown in Figure 5, parking trajectory S and parking trajectory S α That is, the parking trajectory S of a vehicle parked in polygon P1, which is a non-parking lot polygon, and the parking trajectory S of a vehicle parked in polygon P2, which is a parking lot polygon, are similar. α It can be said that the parking locus S is a locus obtained by vehicle drivers driving with the same intention. In other words, the parking locus S can be considered to be a locus resulting from driving a vehicle to park it in a parking lot. Therefore, in the example shown in FIG. 5, the attribute of the facility associated with polygon P3 can be considered to be a parking lot. In other words, a vehicle parked in polygon P3 can be considered to have parked in the same parking lot as polygon P2.

[0050] In the example shown in Figure 5, the control unit 20 extracts and compares comparison data α and comparison data β as comparison data, but if at least one similar parking trajectory can be extracted, the non-parking lot polygon can be considered as a parking lot polygon.

[0051] The driving history analysis system 10 configured in this manner determines the attributes of non-parking lot polygons based on the distance from the parking lot polygons and the parking trajectory, as described above. The processing executed by the driving history analysis system 10 of this embodiment will be described below with reference to a flowchart.

[0052] (2) Flowchart: 6 is a flowchart showing an example of parking lot attribute determination processing executed by the control unit 20. In this embodiment, the parking lot attribute determination processing is repeatedly executed at predetermined fixed intervals (for example, once a week). Specific control contents will be described below.

[0053] First, the control unit 20 reads the driving history acquired after the previous execution of the parking attribute determination process (step S1). That is, the control unit 20 refers to the driving history 30b and acquires all of the driving history acquired after the previous execution of the parking attribute determination process.

[0054] Next, the control unit 20 starts the following loop processing (processing of steps S2 to S5) for the driving histories read in step S1. That is, the control unit 20 extracts one of the driving histories acquired in step S1 as the processing target and performs the loop processing, sequentially performing the loop processing for all of the driving histories acquired in step S1 until the loop processing is completed. Specifically, the control unit 20 determines whether a polygon exists in the parking spot (step S2). That is, the control unit 20 determines whether a polygon exists in the parking spot, in other words, whether the parking spot is within the area of ​​the polygon (step S3). Note that steps S2 and S3 may be executed simultaneously, or the order of steps S2 and S3 may be reversed. Furthermore, since steps S2 and S3 are substantially the same, one of the steps may be omitted.

[0055] For example, if the parking spot is not inside a facility, such as on a road, or if the parking spot is inside a facility to which no polygon is associated, the control unit 20 determines that no polygon exists at the parking spot and makes a negative determination in step S3. If a negative determination is made in step S3, that is, if it is determined that no polygon exists at the parking spot, the control unit 20 ends the loop processing for the driving history to be processed and starts the loop processing for the next driving history.

[0056] On the other hand, if the determination in step S3 is affirmative, i.e., if it is determined that a polygon exists within the parking spot, the control unit 20 determines whether a parking lot attribute is associated with the polygon containing the parking spot (step S4). That is, the control unit 20 determines whether the polygon at the parking spot is a parking lot polygon. In other words, the control unit 20 determines whether the attribute of the facility to which the polygon containing the parking spot is associated is a parking lot attribute. If the determination in step S4 is affirmative, i.e., if it is determined that the polygon at the parking spot is associated with a parking lot attribute, the control unit 20 ends the loop processing for the driving history to be processed without performing any particular processing, because the polygon at the parking spot is already associated with the parking lot attribute and the facility name, and starts the loop processing for the next driving history.

[0057] On the other hand, if the determination in step S4 is negative, that is, if it is determined that the parking lot attribute is not associated with the parking spot polygon, the control unit 20 performs adjacent polygon-based parking lot attribute determination processing to determine the parking lot attribute based on the polygon adjacent to the parking spot (step S5). In this case, since the driving history shows a trajectory of parking in a non-parking spot polygon, the driving history is the analysis target history, and step S5 is executed for the analysis target history.

[0058] FIG. 7 shows a subroutine for the parking lot attribute determination process based on adjacent polygons in step S5. When this process is performed, the polygon containing the parking spot is a non-parking lot polygon to which no parking lot attribute is associated due to a negative determination in step S4 described above. The control unit 20 first determines whether or not there is a polygon to which a parking lot attribute is associated among the adjacent polygons (step S50). That is, the control unit 20 determines whether or not there is a parking lot polygon within a predetermined distance around the polygon containing the parking spot. If the determination in step S50 is negative, that is, if it is determined that there is no polygon to which a parking lot attribute is associated among the adjacent polygons, the control unit 20 considers it difficult to conclude whether the polygon containing the parking spot is a parking lot or not, and does not associate a parking lot attribute with the facility data of the parking spot (step S51).

[0059] On the other hand, if the answer to step S50 is affirmative, that is, if it is determined that a polygon having a parking lot attribute associated with it exists among the adjacent polygons, the control unit 20 starts the following loop process (the process of steps S52 to S55) for the number of polygons having a parking lot attribute associated with it. That is, the control unit 20 performs the loop process for all of the parking lot polygons among the adjacent polygons.

[0060] Specifically, the control unit 20 determines whether the distance between the polygon including the parking spot and the parking lot polygon is less than a predetermined threshold (step S52). As explained above with reference to FIG. 2, the control unit 20 determines that the distance between the polygons is less than the threshold when, for example, part of the periphery of the polygon including the parking spot overlaps with part of the periphery of the parking lot polygon. On the other hand, as explained above with reference to FIGS. 3 and 4, the control unit 20 determines that the distance between the polygons is greater than or equal to the threshold when the shortest distance between the periphery of the polygon including the parking spot and the periphery of the parking lot polygon is greater than or equal to the threshold. Of course, the method for determining the distance is just an example, and the determination may also be made based on the distance between the centers of gravity of the polygons, etc.

[0061] If the answer to this step S52 is negative, i.e., if it is determined that the distance between the polygon containing the parking spot and the parking lot polygon is greater than or equal to a threshold, the control unit 20 starts loop processing regarding the relationship with the next polygon to which the parking lot attribute is associated.

[0062] On the other hand, if the determination in step S52 is affirmative, i.e., if it is determined that the distance between the polygon including the parking spot and the parking lot polygon is less than the threshold, the control unit 20 determines whether or not the vehicle passed through the parking lot polygon immediately before entering the polygon including the parking spot (step S53). That is, the control unit 20 determines whether or not the polygon including the parking spot is located on the forward direction side of the parking lot polygon and the parking lot polygon is the polygon immediately before (in the backward direction) the polygon of the parking spot.

[0063] If the answer to this step S53 is affirmative, that is, if it is determined that the vehicle passed through the parking lot polygon immediately before entering the polygon containing the parking spot, the control unit 20 assigns a parking lot attribute to the non-parking lot polygon (step S54). That is, the attribute of the polygon containing the parking spot is set to "parking lot." In addition, the control unit 20 associates the polygon containing the parking spot with the same name as the name associated with the parking lot polygon.

[0064] On the other hand, if the answer to step S53 is negative, that is, if it is determined that the vehicle did not pass through the parking lot polygon immediately before entering the polygon containing the parking spot, the control unit 20 performs parking lot attribute determination processing based on the parking locus (step S55). Note that this parking lot attribute determination processing based on the parking locus will be described later.

[0065] The control unit 20 ends the loop process when it has completed the process of step S54 or the process of step S55 for the number of polygons to which parking lot attributes have been associated. Then, the control unit 20 determines whether parking lot attributes have been associated with the driving history (analysis target history) (step S56). That is, the control unit 20 determines whether parking lot attributes have been associated with each polygon including a parking spot through the above-mentioned loop process. If parking lot attributes have not been associated through the loop process, a negative determination is made in step S56, and in this case, the control unit 20 proceeds with the process to step S51. That is, the control unit 20 considers it difficult to conclude whether each polygon including a parking spot is a parking lot or not, and does not associate parking lot attributes with the facility data of the parking spot.

[0066] On the other hand, if the answer to this step S56 is affirmative, that is, if it is determined in the loop processing that parking lot attributes are associated with the driving history, the control unit 20 ends the subroutine shown in FIG. 7.

[0067] Here, the parking lot attribute determination process based on the parking trajectory in step S55 will be described. FIG. 8 shows a subroutine of the parking lot attribute determination process based on the parking trajectory in step S55. The control unit 20 performs the following loop process (processing of steps S550 to S554) for all driving histories in which the vehicle parked in adjacent parking lot polygons. That is, the analysis target driving history, which is the driving history to be processed, indicates a trajectory in which the vehicle parked in a non-parking lot polygon, and the loop process of steps S52 to S55 in FIG. 7 is performed in a specific parking lot polygon adjacent to the non-parking lot polygon. Because step S55 is performed during this process, the process shown in FIG. 8 is performed in a state in which the specific parking lot polygon is adjacent to the non-parking lot polygon. Therefore, the control unit 20 references the driving history 30b, extracts driving histories in which the vehicle parked in the parking lot polygon adjacent to the non-parking lot polygon, and performs the loop process of steps S550 to S554 for each of the driving histories to be processed. The parking lot attribute determination process based on the parking trajectory shown in FIG. 8 is a process that is executed when the vehicle does not pass through the parking lot polygon before entering the polygon including the parking spot.

[0068] Specifically, the control unit 20 calculates the parking trajectory S from the point where the road has deviated from map matching to the parking spot (step S550). As described above with reference to FIG. 5, the control unit 20 refers to the driving history 30b, and based on the analysis target history of parking in a non-parking lot polygon, extracts coordinates for each fixed driving distance from the point where the road has deviated from map matching to the parking spot to acquire the parking trajectory S. Note that step S550 may be executed before the loop process. In other words, after step S550 is executed, steps S551 to S554 may be repeated as the target of the loop process.

[0069] In addition, the control unit 20 compares the parking locus S with the parking locus S in the comparison data α. αSpecifically, the control unit 20 refers to the driving history 30b, and extracts coordinates for every certain driving distance from the point where the map matching is missed to the parking point, based on the driving history that is the processing target of the loop process of steps S550 to S554. Then, the control unit 20 extracts a parking locus S having the same length as the parking locus S based on the extracted coordinates. α Extract.

[0070] Next, the control unit 20 calculates the parking locus S and the parking locus S from the parking locus obtained in step S550 and step S551. α The control unit 20 calculates the sum of the distances of the points (coordinates) on the parking locus S and the parking locus S by calculating the distances of the corresponding points on the parking locus S and obtaining the sum of the distances (step S552). α Then, the control unit 20 calculates the difference between the parking locus S and the parking locus S α In other words, the control unit 20 determines whether the total sum of the differences between the parking locus S and the parking locus S is less than a predetermined value (step S553). α Determine whether it is similar to

[0071] If the determination in step S553 is negative, that is, if the parking trajectory S and the parking trajectory S α If the difference between the parking trajectory S and the parking trajectory S is equal to or greater than a predetermined value, the control unit 20 α is not similar to the next data to be compared, parking trajectory S β On the other hand, if the determination in step S553 is affirmative, that is, if the parking trajectory S and the parking trajectory S α If the difference between the parking locus S and the parking locus S is less than the predetermined value, the control unit 20 sets the attribute of the polygon including the parking spot to "parking lot" (step S554). α The control unit 20 determines that the non-parking lot polygons are similar to the parking lot polygons, and regards the non-parking lot polygons as parking lot polygons. The control unit 20 also associates the polygons including the parking spots with the names associated with the facility data of the comparison target data α.

[0072] In addition, parking trajectory S and parking trajectory Sα If the difference between the two is equal to or greater than a predetermined value and therefore the answer to step S553 is negative, the control unit 20 sequentially extracts comparison data (comparison data β, comparison data γ...) from the adjacent polygons and performs the loop process in Fig. 8 until at least a parking locus similar to the parking locus S is found. If the control unit 20 does not find a parking locus similar to the parking locus S as a result of extracting and comparing all the target data, it ends the loop process and proceeds to step S56 in Fig. 7. Note that when step S554 is executed, the loop process of steps S550 to S554 may be exited and the subroutine may be ended.

[0073] As described above, in this embodiment, if the distance between a parking lot polygon associated with a parking lot attribute and a non-parking lot polygon not associated with a parking lot attribute is less than a predetermined threshold, the non-parking lot polygon is assigned a parking lot attribute and recorded as a parking lot polygon. Furthermore, in this embodiment, the attributes of the non-parking lot polygon are determined by comparing the parking trajectory of the non-parking lot polygon with the parking trajectory of the polygon associated with a parking lot attribute. This makes it possible to grasp the attributes of the non-parking lot polygon. As a result, even if parking lot data is insufficient, the possibility of identifying parking information, such as parking in a parking lot, can be increased. In other words, parking history can be acquired even if the polygon is not organized according to the actual shape of the parking lot. Furthermore, by acquiring the attributes of such non-parking lot polygons, information such as "which vehicle types can park in which parking lots" can be accumulated as parking history.

[0074] (3) Other embodiments: The above embodiment is an example for implementing the present invention, and various other embodiments can be adopted. For example, at least some of the components constituting the driving history analysis system 10 may be separated into multiple devices or systems. That is, at least some of the driving history acquisition unit 21a, analysis target history acquisition unit 21b, and attribute determination unit 21c constituting the driving history analysis system 10 may be separated into multiple devices. Furthermore, some of the components of the above embodiment may be omitted, and the order of processing may be changed or omitted.

[0075] Furthermore, in the above-described embodiment, the control unit 20 was configured to assign parking lot attributes to non-parking lot polygons when predetermined conditions are met based on the distance between polygons and the parking trajectory. However, the control unit 20 may also assign parking lot attributes or the name of the facility as a parking lot to the parking history (i.e., parking data). Furthermore, in the above-described embodiment, an attribute indicating that the non-parking lot polygon is a parking lot and the name of the adjacent parking lot are associated with the facility data associated with the non-parking lot polygon. However, a configuration in which only one of them is associated may also be configured. If an attribute indicating that the non-parking lot polygon is a parking lot is associated with facility data, it is possible to identify that the polygon is a parking lot. If the name of the adjacent parking lot is associated with facility data, it is possible to identify that the polygon is the same parking lot as the adjacent polygon.

[0076] In addition, in the above-described embodiment, when determining the attributes of a polygon containing a parking spot to be analyzed, the attributes are determined based on the distance between the polygons or the parking trajectory, depending on the positional relationship between the parking spot and the polygon to which the parking spot attribute is associated. That is, if the point where the vehicle is parked passes through the parking spot polygon, the attributes of the polygon containing the parking spot are determined based on the distance between the polygons. If the point where the vehicle is parked is located in front of the parking spot polygon but not through it, the attributes of the polygon containing the parking spot are determined based on the parking trajectory. However, in this embodiment, it is sufficient to determine the attributes of the polygon containing the parking spot to be analyzed. Therefore, regardless of the positional relationship between the polygon containing the parking spot and the polygon to which the parking spot attribute is associated (i.e., whether the polygon containing the parking spot is in front of or behind the parking spot polygon in the direction of travel of the vehicle), the attributes may be determined based on the distance between the polygons or the parking trajectory of each polygon.

[0077] That is, even if the polygon including the parking spot is located in the backward direction (near side) of the parking lot polygon, the attribute of the polygon including the parking spot may be determined based on the distance between the polygons. Similarly, even if the polygon including the parking spot is located in the forward direction (far side) of the parking lot polygon, the attribute of the polygon including the parking spot may be determined based on the parking trajectory.

[0078] Furthermore, it is sufficient that the attributes of a polygon containing a parking spot can be determined by at least one of the distance between polygons and the parking trajectory, and therefore the attributes of a polygon containing a parking spot can be determined by both the distance between polygons and the parking trajectory.

[0079] Furthermore, the present invention can also be applied as a program or method. The above-described systems, programs, and methods may be realized as standalone devices or may be realized using shared components, and include various other aspects. For example, it is possible to provide a method or program realized by the above-described system. Furthermore, it is possible to modify the invention as appropriate, for example, by making some parts software and some parts hardware. Furthermore, the invention can also be realized as a recording medium for a program that controls the device. Of course, the recording medium for the software may be a magnetic recording medium or a semiconductor memory, and any recording medium developed in the future can be considered in the same way. [Explanation of symbols]

[0080] 10...driving history analysis system, 20...control unit, 21...driving history analysis program, 21a...driving history acquisition unit, 21b...analysis target history acquisition unit, 21c...attribute determination unit, 30...recording unit, 30a...map information, 30b...parking history, 40...communication unit, 100...vehicle (probe car), 110...communication unit, 120...positioning unit, 130...map information, 140...parking history.

Claims

1. a driving history acquisition unit that acquires driving histories of vehicles parked in areas of parking lot polygons associated with parking lot attributes; an analysis target history acquisition unit that acquires an analysis target history, which is the travel history of a vehicle parked in an area of ​​a non-parking lot polygon to which the parking lot attribute is not associated; an attribute determination unit that determines the attributes of the non-parking lot polygons; The attribute determination unit If the distance between the parking lot polygon indicated by the driving history and the non-parking lot polygon indicated by the analysis target history is less than a predetermined threshold, the non-parking lot polygon is recorded as the parking lot polygon in a recording unit. Driving history analysis system.

2. The attribute determination unit When the vehicle passes through the parking lot polygon in the travel history of the vehicle parked in the area of ​​the non-parking lot polygon and the distance is less than the threshold, the non-parking lot polygon is recorded as the parking lot polygon in the recording unit. The driving history analysis system according to claim 1 .

3. a driving history acquisition unit that acquires driving histories of vehicles parked in areas of parking lot polygons associated with parking lot attributes; an analysis target history acquisition unit that acquires an analysis target history, which is the travel history of a vehicle parked in an area of ​​a non-parking lot polygon to which the parking lot attribute is not associated; an attribute determination unit that determines the attributes of the non-parking lot polygons; The attribute determination unit When a first parking locus, which is a locus of a vehicle parked in the area of ​​the non-parking lot polygon indicated by the analysis target history, and a second parking locus, which is a locus of a vehicle parked in the area of ​​the parking lot polygon indicated by the driving history, satisfy a predetermined condition, the non-parking lot polygon is recorded as the parking lot polygon in a recording unit; Extracting a trajectory having the same length as the first parking trajectory from the second parking trajectory; determining that the predetermined condition is satisfied when a difference between the first parking locus and the extracted second parking locus is less than a predetermined value; Driving history analysis system.

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