Information processing device, information processing system, and information processing method

Abstract

To provide a technique for estimating an advance direction of a lane with the use of accuracy of external information.SOLUTION: An information processing device comprises: at least one memory (102, 103) including a program code; and at least one processor (101) for executing the program code. The processor acquires external information including at least information related to the peripheral area of a vehicle, and determines an advance direction of at least one lane with the use of first accuracy (A1) expressing the height of accuracy of the external information.SELECTED DRAWING: Figure 6

Description

[Technical Field]

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

[0002] Conventionally, when there are multiple lanes, an automatic driving device or a driving assistance device for a vehicle estimates the traveling direction of the lane based on external information and determines the lane in which the vehicle can travel (see, for example, Patent Document 1). Here, the "traveling direction of the lane" refers to the traveling direction of the vehicle that is predetermined for that lane. In other words, the "traveling direction of the lane" refers to the direction in which a vehicle traveling on that lane should travel. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Patent No. 6583697 Summary of the Invention [Problem to be solved by the invention]

[0004] The external world information includes, for example, information about objects (e.g., other vehicles) and information about a plurality of lane markings that define the lane. Such external world information is acquired by sensors (e.g., radar sensors, camera sensors, etc.) mounted on the vehicle. However, the accuracy (precision) of the external world information may be low. The device described in Patent Document 1 estimates the lane traveling direction without considering the accuracy of the external world information. Therefore, there is a possibility that the lane traveling direction may be estimated incorrectly.

[0005] Therefore, the present disclosure provides a technique for estimating the traveling direction of a lane using the accuracy of external environment information. [Means for solving the problem]

[0006] In one or more embodiments, an information processing device is provided, the information processing device comprising at least one memory containing program code and at least one processor configured to execute the program code, the processor configured to receive information about a surrounding area of ​​a vehicle, the information being stored in the memory, and the program code. and information including the direction of movement of an object traveling on the lane. Acquire external information including at least With respect to the direction of movement of the object Indicates the accuracy of the external information determining a first accuracy of the direction of movement of the object and the Using first accuracy, at least one The aforementioned The vehicle is configured to determine a lane direction of travel, the lane direction being a predetermined direction of travel of the vehicle relative to the lane.

[0007] In one or more embodiments, an information processing system is provided, comprising the information processing device described above and at least one vehicle, wherein the information processing device is configured to receive the external world information from the at least one vehicle.

[0008] In one or more embodiments, a method for processing information is provided, the method comprising: and information including the direction of movement of an object traveling on the lane. acquiring external world information including at least With respect to the direction of movement of the object Indicates the accuracy of the external information determining a first accuracy of the direction of movement of the object and the Using first accuracy, at least one The aforementioned and determining a lane direction, the lane direction being a predetermined direction of travel of the vehicle relative to the lane. [Effects of the Invention]

[0009] According to the above configuration, by using the accuracy of the external environment information, it is possible to reduce the possibility of erroneously estimating the traveling direction of the lane. Other problems, configurations, and effects will become clear from the description of the following embodiments. [Brief explanation of the drawings]

[0010] [Figure 1] 1 is a diagram illustrating a configuration of an information processing system according to a first embodiment. [Figure 2]1 is a functional block diagram of an information processing apparatus according to a first embodiment. [Figure 3] FIG. 1 is a plan view showing a situation in which a plurality of vehicles are traveling on a road. [Figure 4] FIG. 3 is a diagram showing the configuration of a first table in the first embodiment. [Figure 5] FIG. 4 is a diagram showing the configuration of a second table in the first embodiment. [Figure 6] 1 is a flowchart executed by the information processing device in the first embodiment. [Figure 7] FIG. 10 is a diagram showing the configuration of a first table in the second embodiment. [Figure 8] 10 is a flowchart executed by an information processing device in the second embodiment. [Figure 9] 11 is a flowchart executed by an information processing device in the third embodiment. [Figure 10] FIG. 10 is a diagram illustrating a configuration of an information processing system according to a fourth embodiment. [Figure 11] 10 is a flowchart executed by an information processing device (server) in the fourth embodiment. DETAILED DESCRIPTION OF THE INVENTION

[0011] Hereinafter, several embodiments will be described with reference to the accompanying drawings. The accompanying drawings illustrate specific configurations, but are not to be used to limit the technical scope of the present disclosure.

[0012] In the following explanation, roads follow Japanese traffic laws and vehicles drive on the left side of the road. Roads include multiple dividing lines. The multiple dividing lines define one or more lanes.

[0013] The dividing lines that define lanes include outer lines, center lines, and lane boundary lines. The outer lines are the lines at both ends of the road width (the outermost lines in the road width direction) and indicate the boundary with the shoulder or sidewalk. The center line is a line that separates the travel direction of lanes, that is, the line that indicates the boundary with the oncoming lane. Therefore, the travel direction of the lane on the left side of the center line is opposite to the travel direction of the lane on the right side. The lane boundary lines are lines that indicate the boundary between multiple lanes when the travel direction of the lanes is the same.

[0014] Furthermore, the types (line types) of the lane markings include, for example, solid lines and dashed lines. The colors (line colors) of the lane markings include white and yellow. The outer lines, center lines, and lane boundary lines can each be expressed as follows: For example, the outer lines are solid white lines. The center lines are solid white lines, solid yellow lines, or dashed white lines. The lane boundary lines are dashed white lines. Note that the outer lines, center lines, and lane boundary lines may also be expressed with combinations of line types and colors other than those described above.

[0015] Example 1 (Configuration of information processing system) 1 is a diagram showing the configuration of an information processing system according to Example 1. The information processing system includes an information processing device 100 and an input / output device 120.

[0016] The information processing device 100 is mounted on a vehicle VA. In this example, the information processing device 100 is an ECU. ECU is an abbreviation for electronic control unit, and is an electronic control circuit having a microcomputer as a component. The information processing device 100 includes a CPU 101, a memory 102, a non-volatile memory 103, an interface 104, etc.

[0017] The CPU 101 includes at least one processor and / or circuit. The memory 102 includes, for example, a RAM. The non-volatile memory 103 includes, for example, a flash memory and a ROM. The CPU 101 uses the memory 102 as a work memory to execute program code (instructions) stored in the non-volatile memory 103. This enables the CPU 101 to execute the processes described below.

[0018] The input / output device 120 is a PC (Personal Computer), a tablet terminal, a smartphone, or the like. The input / output device 120 can be connected to the information processing device 100 via the interface 104. The input / output device 120 can read information stored in the nonvolatile memory 103, write information to the nonvolatile memory 103, and update the information stored in the nonvolatile memory 103.

[0019] The vehicle VA includes an external environment information acquisition device 110. The external environment information acquisition device 110 is a device that acquires external environment information. The information processing device 100 acquires the external environment information from the external environment information acquisition device 110.

[0020] The external environment information includes at least information about the surrounding area of ​​the vehicle VA. The external environment information includes, for example, object information about objects present in the surrounding area of ​​the vehicle VA and lane marking information about lane markings present in the surrounding area of ​​the vehicle VA. Note that "objects" include moving objects such as pedestrians, four-wheeled vehicles, and two-wheeled vehicles, as well as stationary objects such as guardrails and fences.

[0021] The object information includes, for example, the distance between the vehicle VA and the object, the direction of movement of the object relative to the vehicle VA, the orientation of the object relative to the vehicle VA, the relative speed between the vehicle VA and the object, and the type of object (for example, information on whether the object is moving or stationary). The lane marking information includes the positions of multiple lane markings that define the lane, the type (line type) of the lane markings, and the color (line color) of the lane markings. Note that the external environment information is not limited to the above examples and may include other information as long as it is used to estimate the lane travel direction.

[0022] For example, the external environment information acquisition device 110 includes at least one of a radar sensor, a camera sensor, and a communication device. Note that the external environment information acquisition device 110 is not limited to the above examples and may include other devices.

[0023] The radar sensor emits a beam into the area surrounding the vehicle VA and can obtain object information based on information about the reflected wave of the beam.

[0024] The camera sensor captures an image of the area surrounding the vehicle VA and acquires image data. The camera sensor can perform image recognition processing on the image data to acquire object information and lane marking information.

[0025] The communication device includes a transmitter and a receiver. The communication device can communicate with devices outside the vehicle VA using V2X (Vehicle to X) technology. V2X includes V2V (Vehicle to Vehicle), V2I (Vehicle to Infrastructure), V2P (Vehicle to People), and V2N (Vehicle to Network). Therefore, the communication device can obtain external world information via wireless communication from at least one of other vehicles, infrastructure equipment, terminals carried by people, and networks.

[0026] (Configuration of information processing device) 2 is a functional block diagram of the information processing device 100. The information processing device 100 includes a control unit 200 and a storage unit 210 as functional components.

[0027] The control unit 200 includes a first module 201, a second module 202, a third module 203, and a fourth module 204. These modules 201 to 204 are realized by the CPU 101 executing program codes stored in the nonvolatile memory 103.

[0028] The storage unit 210 includes a first storage area 211, a second storage area 212, and a third storage area 213. These storage areas 211 to 213 are realized by one or both of the memory 102 and the nonvolatile memory 103.

[0029] The first module 201 determines the accuracy of the external world information. Hereinafter, the "accuracy of the external world information" will be referred to as the "first accuracy A1." The first accuracy A1 represents the degree of precision (likelihood) of the external world information. In other words, the first accuracy A1 represents the degree of reliability of the external world information. Therefore, the larger the first accuracy A1, the higher the accuracy of the external world information corresponding to that first accuracy A1. In this example, the first accuracy A1 is determined as a value in the range of 0 to 100.

[0030] FIG. 3 shows a situation in which multiple vehicles are traveling on a road 300. The road 300 includes five lanes Ln1 to Ln5. The five lanes Ln1 to Ln5 are defined by six dividing lines (white lines) WL1 to WL6. Dividing line WL4 is the center line. As indicated by the arrows, the direction of travel in the lanes Ln1 to Ln3 on the left side of dividing line WL4 is "upward" on the drawing, and the direction of travel in the lanes Ln4 to Ln5 on the right side of dividing line WL4 is "downward" on the drawing.

[0031] A vehicle VA equipped with an information processing device 100 is traveling in lane Ln3. A first other vehicle V1 is traveling in lane Ln1, a second other vehicle V2 is traveling in lane Ln2, and a third other vehicle V3 is traveling in lane Ln4.

[0032] 3, the first module 201 acquires external world information from the external world information acquisition device 110. The first module 201 creates a first table from the external world information. The first table includes various information used to estimate the traveling direction of each of the lanes Ln1 to Ln5. The first module 201 stores the created first table in the first storage area 211.

[0033] FIG. 4 is an example of the first table 400. The first table 400 includes, as its constituent items, a lane 401, an object movement direction 402, a distance (D) 403, and a first accuracy (A1) 404. The lane 401 is an identifier for uniquely identifying each lane included in the road 300. The first module 201 detects lane lines WL1 to WL6 based on external information (specifically, lane line information). The first module 201 defines multiple lanes, assuming that one lane exists between adjacent lane lines. For example, the first module 201 defines lane Ln1 between lane line WL1 and lane line WL2. Through this process, the first module 201 defines lanes Ln1 to Ln5 based on the lane lines WL1 to WL6. The first module 201 assigns an identifier to each of the lanes Ln1 to Ln5. In this example, the lanes 401 are designated by the symbols Ln1 to Ln5 given to the lanes in FIG.

[0034] The object movement direction 402 indicates the movement direction of an object moving on each of the lanes Ln1 to Ln5. In this example, the object movement direction 402 is used to estimate the traveling direction of each of the lanes Ln1 to Ln5. The first module 201 detects other vehicles V1 to V3 as objects from external world information (specifically, object information) and detects the movement direction of each of the other vehicles V1 to V3. The first module 201 then associates the positions of each of the vehicles (VA and V1 to V3) with the lanes Ln1 to Ln5. For example, the first module 201 associates the position of the first other vehicle V1 with the lane Ln1 and determines that the first other vehicle V1 is traveling on the lane Ln1.

[0035] The object's movement direction 402 is expressed as either a "forward direction" or a "reverse direction" based on the movement direction of the vehicle VA. The forward direction indicates the same direction as the current movement direction of the vehicle VA. The reverse direction indicates the opposite direction to the current movement direction of the vehicle VA.

[0036] Note that the object movement direction 402 is not limited to this example. The object movement direction 402 may be expressed by an azimuth angle θ. With respect to the azimuth angle θ, the north direction of the azimuth is defined as 0°. The azimuth angle θ increases clockwise. The east direction of the azimuth is 90°, the south direction of the azimuth is 180°, and the west direction of the azimuth is 270°.

[0037] The distance D is the distance between the vehicle VA and the object. The first module 201 can acquire the distance D from external world information (specifically, object information). The distance D is used to calculate the first accuracy A1.

[0038] The first module 201 calculates a first accuracy A1 of the object's moving direction 402 based on the distance D. This is because it is considered that the accuracy of the external world information (recognition accuracy of radar sensors, camera sensors, etc.) is lower as the distance D is larger. Taking this into consideration, the first module 201 reduces the first accuracy A1 as the distance D is larger.

[0039] For example, the first accuracy A1 is defined by a function f(D)=100-10×D that depends on the distance D. The first module 201 may calculate the first accuracy A1 by substituting the distance D into the function f(D).

[0040] Since the vehicle VA is traveling in lane Ln3, the movement direction 402 of the object (i.e., the vehicle VA) corresponding to lane Ln3 is correct. Therefore, the first module 201 sets the first accuracy A1 of the movement direction 402 of the object corresponding to lane Ln3 to "100." Furthermore, there is no object in lane Ln5. In this case, the "object movement direction 402, distance (D) 403, and first accuracy (A1) 404" corresponding to lane Ln5 are set to null values.

[0041] The method of calculating the first accuracy A1 is not limited to the above example. The first module 201 may calculate the first accuracy A1 based on the characteristics of the external world information acquisition device 110. As an element for determining the characteristics of the external world information acquisition device 110, for example, a variable determined by the internal processing logic of the external world information acquisition device 110 may be used. An example of such a variable is the existence probability of an object output by AI (Artificial Intelligence) that recognizes an object from an image of a camera sensor.

[0042] The second module 202 obtains the first table 400 from the first storage area 211. The second module 202 creates a second table from the first table 400. The second table includes information about the traveling direction of each of the lanes Ln1 to Ln5. The second module 202 stores the second table in the second storage area 212.

[0043] FIG. 5 is an example of the second table 500. The second table 500 includes, as its constituent items, a lane 501, a lane traveling direction 502, and a second accuracy (A2) 503. The lane 501 is the same as the lane 401 in the first table 400. In this example, the lane traveling direction 502 is expressed as either a "forward direction" or a "reverse direction," as described above. Note that the lane traveling direction 502 is not limited to this example. The lane traveling direction 502 may be expressed by an azimuth angle θ. The second accuracy A2 represents the degree of accuracy (likelihood) of the lane traveling direction 502. In other words, the second accuracy A2 represents the degree of reliability of the lane traveling direction 502. Therefore, the larger the second accuracy A2, the higher the accuracy of the lane traveling direction corresponding to the second accuracy A2. In this example, the second accuracy A2 is determined as a value ranging from 0 to 100.

[0044] The second module 202 determines (estimates) the traveling direction 502 of each of the lanes Ln1 to Ln5 based on the first table 400.

[0045] First, the second module 202 determines the traveling direction 502 of the lane using the object movement direction 402 corresponding to the highest first accuracy A1 in the first table 400. In the first table 400, the first accuracy A1 of the object movement direction 402 corresponding to the lane Ln3 is "100 (i.e., the maximum value)." In such a case, the second module 202 directly adopts the object movement direction 402 as the traveling direction 502 of the lane Ln3. In other words, the second module 202 determines the "forward direction" as the traveling direction 502 of the lane Ln3. In this way, the second module 202 determines the traveling direction 502 of the lane Ln3, which has the highest first accuracy A1.

[0046] Next, the second module 202 determines whether the travel direction 502 of lanes other than lane Ln3 is consistent with the travel direction 502 of lane Ln3 as a reference. For example, in the first table 400, the travel direction 402 of the object corresponding to lane Ln1 is the "reverse direction." Lane Ln1 is located to the left of lane Ln3. Considering that road 300 is a left-hand traffic road, the travel direction 402 of the object corresponding to lane Ln1 is inconsistent. In such a case, the second module 202 determines the travel direction 502 of lane Ln1 to be the "forward direction" instead of the "reverse direction."

[0047] On the other hand, the movement direction 402 of the object corresponding to lane Ln2 and the movement direction 402 of the object corresponding to lane Ln4 are not contradictory with respect to the traveling direction 502 of lane Ln3. Therefore, the second module 202 determines the traveling direction 502 of lane Ln2 to be the "forward direction" and the traveling direction 502 of lane Ln4 to be the "reverse direction."

[0048] Furthermore, the second module 202 may determine the traveling direction 502 of lane Ln5 as follows. In the first table 400, the object movement direction 402 corresponding to lane Ln5 is null. In such a case, the second module 202 adopts the traveling direction 502 of lane Ln4, which is closest to lane Ln5, as the traveling direction 502 of lane Ln5. In other words, the second module 202 determines the traveling direction 502 of lane Ln5 to be "reverse direction."

[0049] Next, the second module 202 calculates a second accuracy A2 for each of the lanes Ln1 to Ln5. The second module 202 calculates the second accuracy A2 based on the first accuracy A1. For lane Ln1, since the object movement direction 402 has been corrected as described above, the accuracy of the lane's traveling direction 502 is considered to be low. Therefore, the second accuracy A2 corresponding to lane Ln1 may be calculated using the following formula (A2=100-A1). Therefore, the second module 202 sets the second accuracy A2 corresponding to lane Ln1 to "60".

[0050] For lanes Ln2, Ln3, and Ln4, the object movement direction 402 is adopted as the lane travel direction 502 without any correction. In this case, the second module 202 sets the first accuracy A1 as the second accuracy A2 as is. The second module 202 sets the second accuracy A2 corresponding to lane Ln2 to "80", the second accuracy A2 corresponding to lane Ln3 to "100", and the second accuracy A2 corresponding to lane Ln4 to "70".

[0051] In the first table 400, the first accuracy A1 corresponding to lane Ln5 is null. In this case, the second module 202 adopts the first accuracy A1 of lane Ln4, which is closest to lane Ln5, as the second accuracy A2 of lane Ln5. That is, the second module 202 sets the second accuracy A2 of lane Ln5 to "70."

[0052] The third module 203 determines (estimates) the drivable area based on the travel direction 502 of the lane in the second table 500. The drivable area means an area in which the vehicle VA can travel (enter). The third module 203 stores information about the drivable area in the third memory area 213.

[0053] The drivable area may be expressed by lane position information and the direction of travel of the lane. The lane position information may be expressed as a sequence of points representing lane center positions. The sequence of points is expressed as a combination of latitude, longitude, and altitude.

[0054] The third module 203 determines, as the drivable area, lanes having the same traveling direction 502 as the traveling direction 502 of the lane Ln3 in which the vehicle VA is traveling, based on the second table 500. The third module 203 determines the lanes Ln1, Ln2, and Ln3 as the drivable area.

[0055] The third module 203 may determine the drivable area based on the second accuracy A2. For example, the third module 203 may determine lanes whose second accuracy A2 is equal to or greater than a predetermined value (e.g., 70) as the drivable area. In this configuration, the third module 203 determines lanes Ln2 and Ln3 as the drivable area. Because lanes whose second accuracy A2 is low are not treated as drivable areas, it is possible to prevent the vehicle VA from entering risky lanes.

[0056] The fourth module 204 compares information regarding the currently determined drivable area with information regarding (past) drivable areas stored in the third memory area 213, and updates the information regarding the drivable area stored in the third memory area 213.

[0057] 6 is a flowchart showing a routine executed by the information processing device 100 in the embodiment 1. The information processing device 100 repeatedly executes the routine of FIG. 6 at predetermined intervals.

[0058] In the following description, the modules 201 to 204 of the control unit 200 are described as the subject, but since the CPU 101 is the entity that executes these modules, the subject may be replaced with the CPU 101.

[0059] The first module 201 acquires outside world information from the outside world information acquisition device 110 (S601). Then, the first module 201 creates the first table 400 as described above based on the outside world information (S602). The first module 201 stores the first table 400 in the first storage area 211.

[0060] Next, the second module 202 obtains the first table 400 from the first storage area 211. Then, the second module 202 creates the second table 500 as described above based on the first table 400 (S603). The second module 202 stores the second table 500 in the second storage area 212.

[0061] Next, the third module 203 obtains the second table 500 from the second storage area 212. Then, the third module 203 determines the drivable area as described above based on the second table 500 (S604). The third module 203 stores information about the drivable area in the third storage area 213. Note that if information about the drivable area already exists in the third storage area 213, the fourth module 204 compares the information about the currently determined drivable area with the (past) information about the drivable area stored in the third storage area 213, and updates the information about the drivable area stored in the third storage area 213.

[0062] (effect) According to the above configuration, the information processing device 100 acquires external environment information from the external environment information acquisition device 110 and determines the traveling direction of at least one lane present in the surrounding area of ​​the vehicle VA using a first accuracy A1 that indicates the accuracy of the external environment information. The information processing device 100 can prevent external environment information with a low first accuracy A1 from being reflected in the determination of the traveling direction of the lane. Therefore, the possibility of erroneously estimating the traveling direction of the lane can be reduced.

[0063] Furthermore, the information processing device 100 determines a first accuracy A1 for the object's movement direction 402, and determines the lane's traveling direction using the object's movement direction 402 and the first accuracy A1. There is a high possibility that the movement direction of an object traveling on the lane matches the lane's traveling direction. The information processing device 100 can accurately determine the lane's traveling direction using the object's movement direction.

[0064] Furthermore, the information processing device 100 uses the first accuracy A1 to calculate a second accuracy A2, which indicates the accuracy of the lane's direction of travel, and determines the drivable area using the second accuracy A2. Since lanes with a low second accuracy A2 are not treated as drivable areas, the vehicle VA can be prevented from entering lanes that pose a risk. This ensures high safety.

[0065] (Variation) The second module 202 may determine the travel direction of the lane as follows. If the first accuracy A1 of the object's movement direction 402 is equal to or less than a predetermined threshold Ath, the second module 202 determines the "opposite direction" as the travel direction of the lane. This prevents lanes with a low first accuracy A1 from being treated as drivable areas. This prevents the vehicle VA from entering a risky lane. Note that if the first accuracy A1 of the object's movement direction 402 is greater than a predetermined threshold Ath, the second module 202 may simply determine the object's movement direction 402 as the travel direction of the lane.

[0066] 1 shows only a logical configuration, and there are no restrictions on the physical configuration. For example, the information processing device 100 may be implemented in the external environment information acquisition device 110. That is, the information processing device 100 may be implemented in an on-board sensor (for example, a radar sensor or a camera sensor).

[0067] The travel direction 502 of the lane may include "bidirectional." An example of a lane determined to be "bidirectional" is a lane (road) in which multiple vehicles pass each other. Note that even if the first module 201 can detect only one lane based on external information, it may set multiple virtual lanes within that single lane depending on the lane width.

[0068] A lane is not limited to the area between two dividing lines, but may also be the area between a dividing line and a solid object (such as a curb, a guardrail, or a fence).

[0069] The second accuracy (A2) 503 may be omitted from the second table 500. In this case, the third module 203 determines, as the drivable area, a lane having the same traveling direction 502 as the traveling direction 502 of the lane Ln3 in which the vehicle VA is traveling.

[0070] The control unit 200 may further include a module that executes driving assistance control (or automatic driving control) that assists in part or all of the driving operation of the vehicle VA. The control unit 200 may acquire the drivable area from the third storage area 213 and execute driving assistance control based on the drivable area.

[0071] <Example 2> The configuration of the second embodiment will be described using the situation in Fig. 3. The first module 201 acquires outside world information from the outside world information acquisition device 110. Then, the first module 201 creates a first table 700 shown in Fig. 7 from the outside world information and stores the first table 700 in the first storage area 211.

[0072] The first table 700 includes, as its constituent items, a lane marking 701, a line type 702, a line color 703, and a first accuracy (A1) 704. The lane marking 701 is an identifier for uniquely identifying a lane marking included on the road 300 on which the vehicle VA is traveling. The first module 201 detects the lane markings WL1 to WL6 based on external information (specifically, lane marking information). The first module 201 assigns an identifier to each of the lane markings WL1 to WL6. In this example, the symbols WL1 to WL6 assigned to each lane marking in FIG. 3 are used as the lane markings 701.

[0073] The line type 702 is information indicating the type of the lane marking, and in this example, is either a solid line or a dashed line. The line color 703 is information indicating the color of the lane marking, and in this example, is either white or yellow. The first accuracy A1 indicates the degree of accuracy (likelihood) of the "combination of the line type 702 and the line color 703." In other words, the first accuracy A1 indicates the degree of reliability of the "combination of the line type 702 and the line color 703." As described above, the first accuracy A1 is determined as a value in the range of 0 to 100. The first accuracy A1 may be an evaluation value of the image recognition processing output by the AI.

[0074] Fig. 8 is a flowchart showing a routine executed by the information processing device 100 in the embodiment 2. The information processing device 100 repeatedly executes the routine of Fig. 8 at predetermined intervals.

[0075] The first module 201 acquires outside world information from the outside world information acquisition device 110 (S801). Then, the first module 201 creates a first table 700 based on the outside world information (S802). The first module 201 stores the first table 700 in the first storage area 211.

[0076] Next, the second module 202 obtains the first table 700 from the first storage area 211. Then, the second module 202 creates the second table 500 based on the first table 700 (S803). The second module 202 stores the second table 500 in the second storage area 212.

[0077] Specifically, the second module 202 defines lanes Ln1 to Ln5 based on the first table 700. As described above, the second module 202 defines lanes Ln1 to Ln5 by assuming that one lane exists between adjacent dividing lines. Through this process, the second module 202 can also obtain the lane number LN. The second module 202 switches the process for determining the lane direction depending on the lane number LN. In this example, the lane number LN is divided into the following cases (a) to (c). (a) Number of lanes LN ≧ 3 (b) Number of lanes LN = 2 (c) Number of lanes LN = 1

[0078] In the example of FIG. 3, the number of lanes LN is "5." Therefore, this corresponds to (a) above. In this case, the second module 202 determines the direction of travel for each of the lanes Ln1 to Ln5 as follows: The second module 202 extracts lane markings whose line type 702 is "solid" other than the lane markings WL1 and WL6, which correspond to the outside lines. In the first table 700, the line type 702 of the lane marking WL4 is "solid." Under Japanese traffic regulations, a solid white line is likely to be a center line. Taking this into consideration, the second module 202 determines that the lane marking WL4 is the center line. The second module 202 determines the direction of travel for each of the lanes Ln1 to Ln5 based on the relationship between the lane in which the vehicle VA is traveling and the center line. The vehicle VA is traveling in lane Ln3, and the lane marking WL4 is the center line. Therefore, the second module 202 determines the direction of travel for each of the lanes Ln1 to Ln3, which are to the left of the lane marking WL4, to be "forward." On the other hand, the second module 202 determines the "opposite direction" as the travel direction for each of the lanes Ln4 to Ln5 located to the right of the dividing line WL4.

[0079] In addition, when the number of lanes LN is "2" as in (b) above, the second module 202 determines the "forward direction" as the direction of travel for the lane in which the vehicle VA is traveling, and determines the "reverse direction" as the direction of travel for the lane in which the vehicle VA is not traveling.

[0080] When the lane number LN is "1" as in (c) above, the second module 202 determines the "forward direction" as the travel direction of the lane.

[0081] Next, the third module 203 obtains the second table 500 from the second storage area 212. Then, the third module 203 determines the drivable area as described above based on the second table 500 (S804). The third module 203 stores information about the drivable area in the third storage area 213.

[0082] (effect) According to the above configuration, the information processing device 100 determines the lane traveling direction using the lane marking information. Specifically, the information processing device 100 determines the lane traveling direction using the line type 702, the line color 703, and the number of lanes. The information processing device 100 can determine the lane traveling direction even when there is no object (other vehicle) on the lane. Furthermore, the information processing device 100 can determine the lane traveling direction in accordance with traffic regulations.

[0083] (Variation) The second module 202 may determine the direction of travel of the lanes using at least one of the line type 702, the line color 703, and the number of lanes.

[0084] The second module 202 may determine the center line based on the line color 703. Under Japanese traffic regulations, a yellow dividing line is likely to be a center line. Taking this into consideration, if there is only one dividing line whose line color 703 is "yellow," the second module 202 may determine that this dividing line is the center line. Then, the second module 202 determines the traveling direction of each lane based on the relationship between the lane in which the vehicle VA is traveling and the center line.

[0085] If the center line cannot be determined using the line type 702 and / or the line color 703, the information processing device 100 may determine the travel direction of the lane in accordance with traffic regulations. The information processing device 100 may determine the travel direction of the lane on the left side of the vehicle VA as the "forward direction," and the travel direction of the lane on the right side of the vehicle VA as the "reverse direction."

[0086] In the first table 700, a first accuracy A1 may be determined for each of the line type 702 and the line color 703. Furthermore, in the first table 700, the first accuracy (A1) 704 may be omitted.

[0087] Example 3 In the third embodiment, the external environment information further includes at least one of information about the time when the external environment information was acquired (hereinafter referred to as "time information") and information about the weather (hereinafter referred to as "weather information"). The time information may be, for example, headlight ON / OFF information. The weather information may be, for example, wiper ON / OFF information.

[0088] 9 is a flowchart showing a routine executed by the information processing device 100 in the third embodiment. The information processing device 100 repeatedly executes the routine of FIG. 9 at predetermined intervals.

[0089] The first module 201 acquires outside world information from the outside world information acquisition device 110 (S901). As described above, the outside world information includes time information and weather information. Then, the first module 201 creates a first table 400 based on the outside world information (S902). The first module 201 stores the first table 400 in the first storage area 211.

[0090] Specifically, the accuracy of on-board sensors such as radar sensors and camera sensors is likely to decrease at night. Therefore, when the headlights are on, the first module 201 reduces the value of the first accuracy (A1) 404 in the first table 400 by a predetermined first value. Similarly, the accuracy of on-board sensors is likely to decrease in rainy weather. Therefore, when the wipers are on, the first module 201 reduces the value of the first accuracy (A1) 404 in the first table 400 by a predetermined second value.

[0091] Next, the second module 202 obtains the first table 400 from the first storage area 211. Then, the second module 202 creates the second table 500 as described above based on the first table 400 (S903). The second module 202 stores the second table 500 in the second storage area 212.

[0092] Next, the third module 203 obtains the second table 500 from the second storage area 212. Then, the third module 203 determines the travelable area as described above based on the second table 500 (S904). The third module 203 stores information about the travelable area in the third storage area 213.

[0093] (effect) According to the above configuration, the information processing device 100 determines the first accuracy A1 using at least one of time information and weather information. The information processing device 100 can reflect conditions such as nighttime and rainy weather in the first accuracy A1. This can increase the accuracy of the finally determined lane traveling direction.

[0094] (Variation) The configuration of the second embodiment may be applied to this embodiment. That is, the information processing device 100 may determine the lane traveling direction using at least one of the line type 702, the line color 703, and the number of lanes. The information processing device 100 may change the first accuracy A1 (704) of the first table 700 using at least one of time information and weather information.

[0095] Example 4 10 is a diagram showing the entire information processing system according to Example 4. In this example, an information processing device 100 is realized as a server in a data center.

[0096] The information processing device 100 is connected to a plurality of vehicles VB and VC via a communication network 1001. The communication network 1001 is, for example, one of a mobile phone network, an Internet network, and a short-range wireless communication network, or a combination of two or more of them.

[0097] Each of the multiple vehicles VB and VC is equipped with an external environment information acquisition device 110. The external environment information acquisition device 110 includes a communication device as described above, and transmits external environment information to the information processing device 100 via the communication device. The information processing device 100 receives external environment information from the multiple vehicles VB and VC. The information processing device 100 determines the traveling direction of the lane as described above, and also determines the drivable area. The information processing device 100 transmits information regarding the drivable area to each of the multiple vehicles VB and VC. Each of the multiple vehicles VB and VC receives information regarding the drivable area. Each of the multiple vehicles VB and VC may perform driving assistance control based on the drivable area.

[0098] Fig. 11 is a flowchart showing a routine executed by the information processing device 100 in the fourth embodiment. The information processing device 100 repeatedly executes the routine of Fig. 11 at predetermined intervals.

[0099] Each of the plurality of vehicles VB and VC acquires external environment information from the external environment information acquisition device 110. Each of the plurality of vehicles VB and VC transmits the external environment information to the information processing device 100 via the communication network 1001. The first module 201 receives the external environment information (S1101).

[0100] The external environment information may include information acquired by different sensors of the same vehicle and / or information acquired by the same sensor at different times.

[0101] The first module 201 creates the first table 400 based on the external world information (S1102). The first module 201 stores the first table 400 in the first storage area 211.

[0102] Next, the second module 202 obtains the first table 400 from the first storage area 211. Then, the second module 202 creates the second table 500 as described above based on the first table 400 (S1103). The second module 202 stores the second table 500 in the second storage area 212.

[0103] When the second module 202 receives external environment information from each of the multiple vehicles VB and VC, the second module 202 may calculate the first accuracy A1 based on the mounting position, mounting angle, performance, etc. of the on-board sensor. For example, when the second module 202 receives external environment information from a vehicle having an on-board sensor with low performance, the second module 202 may lower the first accuracy A1 of the external environment information acquired from that vehicle.

[0104] Next, the third module 203 obtains the second table 500 from the second storage area 212. Then, the third module 203 determines the drivable area as described above based on the second table 500 (S1104). The third module 203 stores information about the drivable area in the third storage area 213.

[0105] Next, the third module 203 acquires information about the drivable area from the third storage area 213. Then, the third module 203 transmits the information about the drivable area to each of the multiple vehicles VB and VC (S1105). The information about the drivable area may be transmitted in a map format, such as a map of a navigation system or a high-precision map. Note that each of the multiple vehicles VB and VC may integrate (fuse) the received information about the drivable area with external environment information acquired by the vehicle itself.

[0106] (effect) According to the above configuration, the information processing device 100 acquires external environment information from multiple vehicles VB and VC. Since the information processing device 100 can acquire a wide range of external environment information from many vehicles, it can accurately determine the traveling direction of the lane and the drivable area.

[0107] For example, a situation may arise in which vehicle VB can acquire external environment information but vehicle VC cannot. Even in such a situation, information processing device 100 can determine a drivable area based on the external environment information acquired from vehicle VB and transmit information about the drivable area to vehicle VC. Information processing device 100 can provide information about the drivable area even to vehicle VC that cannot acquire external environment information.

[0108] (Variation) The information processing device 100 implemented as a server may be realized by one of the above-mentioned "Example 1, Example 2, and Example 3" or a combination of these. For example, the information processing device 100 may create the first table 700 based on external world information. The information processing device 100 may determine the first accuracy A1 using at least one of time information and weather information.

[0109] It should be noted that the above-described embodiment is merely an example, and the scope of the technical idea of ​​the present disclosure is not limited to the above-described configuration. Other embodiments conceivable within the scope of the technical idea of ​​the present disclosure are also included in the scope of the present disclosure.

[0110] The above-described first to fourth embodiments and their modifications can also be applied to roads that comply with traffic laws in countries or regions other than Japan. For example, the above-described first to fourth embodiments and their modifications can also be applied to countries or regions that drive on the right side of the road.

[0111] The above-described configuration may be realized by a non-transitory computer readable medium on which program code is recorded. The information processing device 100 (or the CPU 101) may be configured to read the program code stored in the non-transitory computer readable medium and execute the program code. Examples of the non-transitory computer readable medium include a flexible disk, a CD-ROM, a DVD-ROM, a hard disk, an optical disk, a magneto-optical disk, a CD-R, a magnetic tape, a non-volatile memory card, and a ROM.

[0112] The program code may also be supplied to the information processing device 100 via a wired communication path such as an electric wire or an optical fiber, or via a wireless communication path.

[0113] Although the embodiments of the present invention have been described in detail above, the present invention is not limited to the above-described embodiments, and various design modifications can be made without departing from the spirit of the present invention as defined in the claims. For example, the above-described embodiments have been described in detail to clearly explain the present invention, and the present invention is not necessarily limited to those including all of the described configurations. Furthermore, it is possible to replace part of the configuration of one embodiment with the configuration of another embodiment, or to add the configuration of another embodiment to the configuration of one embodiment. Furthermore, it is possible to add, delete, or replace part of the configuration of each embodiment with other configurations. [Explanation of symbols]

[0114] 100...information processing device, 110...external world information acquisition device, 120...input / output device, 200...control unit, 210...storage unit.

Claims

1. at least one memory containing program code; at least one processor configured to execute the program code; Equipped with The processor: acquiring external environment information relating to the area surrounding the vehicle, the external environment information including at least information relating to the direction of movement of an object traveling on the lane; determining a first accuracy indicating a degree of accuracy of the external world information with respect to the movement direction of the object; a configuration in which the travel direction of the lane is determined to be either a forward direction or a reverse direction using the movement direction of the object and the first accuracy; the forward direction is the same as the direction of movement of the vehicle, the reverse direction is a direction opposite to the direction of movement of the vehicle; When the first accuracy of the external environment information is equal to or less than a predetermined threshold, the reverse direction is determined as the traveling direction of the lane. Information processing device.

2. 2. The information processing device according to claim 1, the external environment information includes lane marking information regarding lane markings that define the lane; the processor is configured to determine the direction of travel of the lane using the lane marking information; The lane marking information includes at least one of the type of the lane marking, the color of the lane marking, and the number of lanes defined by the lane marking. Information processing device.

3. 2. The information processing device according to claim 1, the external environment information includes at least one of time information relating to a time when the external environment information was acquired and weather information; the processor is configured to determine the first accuracy using at least one of the time information and the weather information. Information processing device.

4. 2. The information processing device according to claim 1, The processor is configured to determine a drivable area, which is an area in which the vehicle can travel, using the traveling direction of the lane. Information processing device.

5. 5. The information processing device according to claim 4, The processor: Using the first accuracy, a second accuracy is calculated that indicates a degree of accuracy of the traveling direction of the lane; The second accuracy is used to determine the drivable area. It was configured as follows: Information processing device.

6. 5. The information processing device according to claim 4, The processor is configured to store information about the drivable area in the memory; The processor: comparing the currently determined drivable area with the drivable area stored in the memory; The travelable area stored in the memory is updated. It was configured as follows: Information processing device.

7. An information processing device according to claim 1; at least one vehicle; Equipped with The information processing device includes: configured to receive the external environment information from the at least one vehicle; Information processing system.

8. 8. The information processing system according to claim 7, The processor: determining a drivable area in which the vehicle can travel using the travel direction of the lane; Transmitting information about the drivable area to the vehicle It was configured as follows: Information processing system.

9. 8. The information processing system according to claim 7, the external environment information includes a moving direction of an object traveling on the lane, The processor: determining the first likelihood for the direction of movement of the object; determining the direction of travel of the lane using the direction of movement of the object and the first accuracy; It was configured as follows: Information processing system.

10. 8. The information processing system according to claim 7, the external environment information includes lane marking information regarding lane markings that define the lane; the processor is configured to determine the direction of travel of the lane using the lane marking information; The lane marking information includes at least one of the type of the lane marking, the color of the lane marking, and the number of lanes defined by the lane marking. Information processing system.

11. acquiring external environment information relating to a surrounding area of ​​the vehicle, the external environment information including at least information relating to a direction of movement of an object traveling on a lane; determining a first accuracy indicating a degree of accuracy of the external world information with respect to the movement direction of the object; determining, as a traveling direction of the lane, one of a forward direction that is the same direction as the traveling direction of the vehicle and a reverse direction that is the opposite direction to the traveling direction of the vehicle, using the traveling direction of the object and the first accuracy; determining the reverse direction as the traveling direction of the lane when the first accuracy of the external environment information is equal to or less than a predetermined threshold; Including, Information processing methods.

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