Information processing device, information processing method, mobile body, and program

Abstract

To provide a technique for enhancing a degree of freedom in traveling of a mobile body.SOLUTION: An information processing device 100 performs the steps of: acquiring control-related information including environmental information to control a mobile body 107 (S401); and adjusting a traveling rule to be obeyed in traveling of the mobile body 107 based on the control-related information (S403). Then, the information processing device controls driving of the mobile body based on traveling control information including the adjusted traveling rule. The control-related information includes, for example, map information, operation information of the mobile body, behavior information of an obstacle, mobile body intrinsic information, road surface configuration information, and traveling history information or the like.SELECTED DRAWING: Figure 4

Description

[Technical field]

[0001] The present disclosure relates to a technique for controlling the traveling of a moving object. [Background technology]

[0002] Many technologies for autonomous driving and driving assistance for moving objects have been proposed. For example, the driving assistance device described in Patent Document 1 uses adaptive cruise control (ACC) technology that maintains the distance between the vehicle and the preceding vehicle at a target value. When a signal requesting a change in the target driving conditions (corresponding to the target distance) in the ACC is generated by the driver operating an operation button, this driving assistance device executes control to permit the change request under specific conditions.

[0003] Known examples of mobile objects that move within facilities include security robots in commercial facilities, food delivery robots in restaurants, etc. Such mobile objects, which mainly share the moving space with people, travel according to predetermined rules, such as keeping to the right or left of the road. [Prior art documents] [Patent documents]

[0004] [Patent Document 1] JP 2020-26154 A Summary of the Invention [Problem to be solved by the invention]

[0005] However, in environments such as facilities where the positions and movements of obstacles such as people are less regular, if a mobile robot tries to strictly follow the rules, the working efficiency of the mobile robot may decrease and there may be a risk of collision with obstacles. Therefore, it is desirable to be able to change the driving rules of a mobile body as needed, but the technology of changing the driving conditions by signals given from the outside (by the driver), as in Patent Document 1, reduces the degree of freedom of the mobile robot's driving.

[0006] Therefore, the present disclosure provides a technique for increasing the freedom of travel of a moving body. [Means for solving the problem]

[0007] An information processing device according to one embodiment of the present disclosure is characterized in having an acquisition means for acquiring control-related information including environmental information for controlling a moving body, an adjustment means for adjusting driving rules to be followed for driving of the moving body based on the control-related information, and a control means for controlling the driving of the moving body based on driving control information including the adjusted driving rules. Effect of the Invention

[0008] According to the present disclosure, the degree of freedom of travel of a moving body can be increased. [Brief description of the drawings]

[0009] [Figure 1] FIG. 2A is a diagram showing the configuration of a moving object according to the first embodiment, and FIG. 2B is a diagram showing the hardware configuration of an information processing device. [Diagram 2] FIG. 2 is a block diagram showing an example of a functional configuration of an information processing device. [Diagram 3] FIG. 4 is a diagram illustrating an example of a driving rule table in the first embodiment. [Figure 4] 1A is a flowchart showing a process for adjusting a driving rule, and FIG. 1B is a flowchart showing a process for determining whether or not to execute the adjustment process. [Diagram 5] FIG. 13 is a diagram for explaining the bias of a plurality of obstacles. [Figure 6] 10 is a flowchart showing a process for generating drive control information. [Figure 7] 13 is a flowchart showing a process of determining whether or not to execute an adjustment process of a travel rule using moving object specific information and road surface configuration information in the second embodiment. [Figure 8] FIG. 13 is a diagram showing an example of a driving tendency table in the third embodiment. [Figure 9] FIG. 13 is a diagram illustrating an example of a driving rule table in the fourth embodiment. [Figure 10] 13 is a flowchart illustrating a process for adjusting a driving rule in a fourth embodiment. [Figure 11] FIG. 23 is a diagram illustrating an example of an object position relationship graph in the sixth embodiment. [Figure 12] FIG. 23 is a diagram illustrating an example of an object table in the sixth embodiment. [Figure 13] FIG. 23 is a diagram illustrating an example of a positional relationship information table in the sixth embodiment. [Figure 14] 20 is a flowchart illustrating a process for adjusting a driving rule in a sixth embodiment. [Figure 15] 20 is a flowchart illustrating a process for generating drive control information in the sixth embodiment. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0010] Hereinafter, an embodiment of the present disclosure will be described with reference to the drawings. In the drawings, elements having the same configuration or function are given the same reference numerals, and repeated description thereof will be omitted. The configurations shown in the following embodiments are merely examples, and the present disclosure is not limited to the configurations shown in the drawings.

[0011] First Embodiment 1(A) is a diagram showing the configuration of a moving body according to the first embodiment. The moving body 107 is, for example, a mobile robot such as an AMR (Autonomous Mobile Robot) or an AGV (Automated Guided Vehicle). In this embodiment, it is assumed that the moving body 107 moves, for example, within a facility. "Inside a facility" means within the land on which the facility is located, regardless of whether it is indoors (inside a building) or outdoors (outside a building).

[0012] The mobile object 107 is equipped with the information processing device 100. The mobile object 107 detects obstacles present around the mobile object 107 using a sensor 105 described later, and is capable of taking evasive action when the distance between the mobile object 107 and the obstacle falls below a predetermined distance (hereinafter, referred to as the proximity limit distance).

[0013] In this embodiment, the obstacle is mainly assumed to be a moving object, particularly a person. The obstacle is not limited to a person, but may also include animals and other robots. The obstacle is not limited to a moving object, but may also include an object temporarily placed on the travel route. Although it is assumed that there is one or more obstacles, it is assumed that there are more situations where there are multiple obstacles than situations where there is only one.

[0014] 1(B) is a diagram showing a hardware configuration of the information processing device 100. The information processing device 100 has a CPU (Central Processing Unit) 101, a ROM (Read-Only Memory) 102, and a RAM (Random Access Memory) 103. The information processing device also has a storage 104 and a sensor 105. These elements are connected to each other by a system bus 106.

[0015] The CPU 101 performs calculations and logical decisions for various processes and controls each element connected to the system bus 106. Instead of the CPU 101, a PLD (Programmable Logic Device) such as an FPGA (Field Programmable Gate Array) may be used. Alternatively, an ASIC (Application Specific Integrated Circuit) may be used. Alternatively, a DSP (Digital Signal Processor) or the like may be used. A ROM (Read-Only Memory) 102 is a program memory, and stores programs for control by the CPU 101, including various processing procedures executed in the information processing device 100. A RAM (Random Access Memory) 103 is used as a temporary storage area such as a main memory or a work area for the CPU 101 . The program memory is not limited to the ROM 102, and may be an external storage device (not shown) connected by wire or wirelessly to the information processing device 100. In this case, the information processing device 100 loads the program into the RAM 103 from the external storage device.

[0016] The storage 104 is an auxiliary storage device for storing electronic data and programs. Known examples of auxiliary storage devices include a hard disk drive and a solid state drive. An external storage device that plays a similar role to the storage 104 may be used. The external storage device that replaces the storage 104 may be realized, for example, by a medium (recording medium) and an external storage drive for realizing access to the medium. Known examples of such media include a flexible disk (FD), a compact disc (CD)-ROM, and a digital versatile disc (DVD). Alternatively, it may be a magneto-optical disk (MO), a flash memory, or the like. Alternatively, the external storage device may be a storage device or a server device connected via a network.

[0017] The sensor 105 is a device that mainly acquires information on the speed and traveling direction of the moving object 107, detects obstacles existing around the moving object 107, and acquires information on their operation. The sensor 105 may be composed of multiple types of devices. The motion information of an obstacle mainly refers to the position, speed, and traveling direction of the obstacle, and typically refers to the relative position, relative speed, and relative traveling direction of the obstacle with respect to the moving body 107. The relative position of the obstacle also corresponds to the distance between the moving body 107 and the obstacle. The obstacle operation information may further include the number and density of obstacles. The obstacle density is the number of obstacles present in a certain space, as acquired by the sensor 105.

[0018] The position information of the moving object 107 can be acquired by, for example, a self-position estimation technique, as described later. Hereinafter, information on the position, speed, and traveling direction of the moving object 107 may also be referred to as operation information of the moving object 107.

[0019] An example of the sensor 105 that detects the speed and traveling direction of the moving body 107 is an IMU (Inertial Measurement Unit). The IMU can also detect the inclination and angular velocity of the moving body 107. The sensor 105 that detects the speed is not limited to an IMU, and may be an encoder that detects the number of rotations of a motor (not shown) that drives the moving body 107 to travel.

[0020] For example, examples of the sensor 105 for acquiring the motion information of an obstacle include LiDAR (Light Detection and Ranging, Laser Imaging Detection and Ranging) and a camera. A passive stereo camera may be used as the camera. The LiDAR detects the presence or absence of an obstacle from the reflected light of an irradiated laser. The camera detects the presence or absence of an obstacle from the distance value of a feature point in a stereo image.

[0021] Examples of the sensor 105 used to acquire obstacle motion information include LiDAR and Doppler radar. The LiDAR and Doppler radar acquire information on the relative position, relative speed, and relative traveling direction of the obstacle with respect to the moving body 107. The information processing device 100 may acquire motion information of the moving object, and acquire (calculate) the relative position, relative speed, and relative traveling direction of the obstacle based on obstacle information acquired by a camera or other sensors.

[0022] When the mobile object 107 is a robot that carries and carries a load, the sensor 105 may include a device that detects the weight of the load.

[0023] 2 is a block diagram showing an example of a functional configuration of the information processing device 100. The information processing device 100 includes a driving control information management unit 201, a control related information acquisition unit 202, a driving rule adjustment unit 203, a drive control information generation unit 204, and a drive control unit 205.

[0024] The driving control information management unit 201 manages driving control information. The driving control information mainly includes information on driving rules, and also includes map information. The map information includes information on the travel route of the mobile object 107 and topographical information that represents the topography around the travel route of the mobile object 107. The map information is stored in advance in the storage 104 or the above-mentioned external storage device. The information processing device 100 may generate and acquire the topographical information in real time using a technique such as SLAM (Simultaneous Localization and Mapping). A travel route is a route or course along which a mobile object travels. The terrain refers to the shape of the ground, walls, pillars, etc. that make up the route. The driving rules are rules that must be followed for driving the moving body 107. The driving rules are used by the driving control information generating unit 204 to generate driving control information (information for controlling the driving state of the moving body 107).

[0025] The control-related information acquisition unit 202 acquires control-related information for controlling the moving object 107. The control-related information acquisition unit 202 functions as an acquisition unit that acquires the control-related information in cooperation with hardware such as the CPU 101. The control-related information includes the following pieces of information. Map information Information on the movement of moving objects Obstacle movement information Mobile device specific information Road surface configuration information Driving history information

[0026] At least the map information and obstacle operation information of the above control-related information are included in the environmental information (environmental information around the mobile object 107). The moving object specific information is information specific to the moving object 107, such as the width, weight, weight of the load carried by the moving object 107, distance of the obstacle detection range, and / or remaining battery charge.

[0027] The road surface configuration information is information about the configuration of the road surface on the travel route, such as the friction coefficient of the road surface, the unevenness of the road surface, and / or the gradient of the road surface. The friction coefficient of the road surface depends on the material of the road surface as well as the dryness of the road surface (the difference between when it is dry and when it is wet).

[0028] The travel history information is information based on the movement history of the moving object 107 and obstacles present around the moving object 107.

[0029] The driving rule adjustment unit 203 acquires driving rules from the driving control information management unit 201, and adjusts the acquired driving rules based on the control related information acquired by the control related information acquisition unit 202. The driving rule adjustment unit 203 acquires driving rules in cooperation with hardware such as the CPU 101, and functions as an adjustment means for adjusting the acquired driving rules.

[0030] The drive control information generating unit 204 generates drive control information based on the drive control information including the drive rules adjusted by the drive rule adjusting unit 203 . The drive control information includes at least a correction amount (hereinafter referred to as the driving path correction amount) indicating how far to the left or right the moving body 107 will deviate from the driving path and the speed of the moving body 107, as well as a limit distance to an obstacle or an upper limit speed of the moving body 107.

[0031] Based on the drive control information, the drive control unit 205 controls the drive of the moving body 107. A control signal from the drive control unit 205 is input to a drive mechanism (not shown) such as various motors that drive the moving body 107.

[0032] The drive control information generation unit 204 and / or the drive control unit 205 function as a control means that controls the drive of the moving body based on drive control information including the adjusted driving rules, in cooperation with hardware such as the CPU 101.

[0033] 2, the information processing device 100 has a function of acquiring position information of the moving object 107. Specifically, the information processing device 100 stores a program for performing self-position estimation in the ROM 102 or the storage 104, etc., and thereby acquires the position information of the moving object 107. For example, SLAM is used as the self-position estimation. Alternatively, the information processing device 100 may have a GNSS (Global Navigation Satellite System) sensor as the sensor 105 for acquiring the position information. In this case, the map information needs to be associated with map information in the earth's coordinate system.

[0034] 3 is a diagram showing an example of a driving rule table used for managing driving rules by driving control information management unit 201. Driving rule table 300 is stored in advance in storage 104 or an external storage device.

[0035] In the driving rule ID 301, an ID for uniquely identifying a driving rule stored in the driving rule table 300 is described. The driving rules 302 describe the contents of the driving rules, that is, the contents of instructions to be sent to the drive control information generating unit 204. For example, the following five driving rules are set.

[0036] Driving rule ID "1" is "drive on the {left} side of the aisle." Driving rule ID "2" is "Keep a distance of {1.0}m between you and obstacles." Driving rule ID "3" is "drive at a speed of {4.0}km / h." Driving rule ID "4" is "If the path intersects with a movable obstacle, {slow down to 2km / h}." Driving rule ID "5" is "{slow down just before turning}."

[0037] The contents in the curly brackets {} in the driving rule 302 represent rule parameters. The rule parameters are variable values ​​that can be set by, for example, the driving rule adjustment unit 203. In the initial state, the rule parameters are set to predetermined default values.

[0038] Fig. 4(A) is a flowchart showing the process in which the driving rule adjustment unit 203 adjusts the driving rules. In this process, the CPU 101 reads a program corresponding to the process content from the ROM 102 or the storage 104, loads it into the RAM 103, and executes it (the same applies to the flowcharts shown in the other figures). The process described in this flowchart is executed repeatedly, for example, at regular time intervals. The execution interval of the process shown in Fig. 4(A) may be changed depending on the distance from the moving object 107 to an obstacle or the density of obstacles existing around the moving object 107.

[0039] In S401, the driving rule adjustment unit 203 acquires control-related information from the control-related information acquisition unit 202. In this embodiment, of the control-related information, for example, operation information of the moving object 107 and environmental information around the moving object 107 (for example, map information and operation information of an obstacle) are acquired.

[0040] In S402, the driving rule adjustment unit 203 determines whether or not to adjust the driving rules. If the driving rules are to be adjusted, the process proceeds to S403. If the driving rules are not to be adjusted, the process ends. FIG. 4B is a flowchart showing the process of determining whether or not to execute the driving rule adjustment process in S402.

[0041] In S4021, the driving rule adjustment unit 203 checks whether a predetermined time has passed since the driving rule was last adjusted. If the predetermined time has passed, the process proceeds to S4022. If the predetermined time has not passed, the driving rule adjustment unit 203 determines not to adjust the driving rule. The driving rule adjustment unit 203 may check, in addition to the elapsed time, whether the moving object 107 has moved a predetermined distance or more from the point where the driving rule was last adjusted. In this case, if the predetermined time or more has passed and the moving object 107 has moved a predetermined distance or more, the process may proceed to the next step. In other cases, the driving rule adjustment unit 203 determines not to adjust the driving rule.

[0042] In S4022, the driving rule adjustment unit 203 checks whether the moving object 107 is a predetermined distance or more away from an obstacle, a corner, a door, etc. Information on whether the moving object 107 is a predetermined distance or more away from an obstacle, a corner, a door, etc. is an example of the position of the moving object 107's operation information. If the moving object 107 is a predetermined distance or more away, the process proceeds to S4023. If the moving object 107 is not a predetermined distance away, it is determined that the driving rules are not to be adjusted.

[0043] In S4023, the driving rule adjustment unit 203 checks whether the following conditions related to the obstacle are met. If at least one of the conditions is met, it is determined that the driving rules are to be adjusted. If no condition is met, it is determined that the driving rules are not to be adjusted.

[0044] In S4023, the first condition is met when there has been a change in the behavior of an obstacle present around the moving body 107. Specifically, this condition is met when there is one or more obstacles present around the moving body 107 whose behavior has changed by a threshold or more since the previous travel rule adjustment was made. A change in the behavior of an obstacle by a threshold or more means that at least one of the position, speed, and traveling direction of the obstacle has changed by a threshold or more.

[0045] In S4023, the second condition is met when the number of obstacles existing around the moving object 107 increases or decreases.

[0046] The determination process in S402 is an example of a process for determining whether or not to adjust the driving rule based on a predetermined condition. Also, this process is not limited to the order of S4021 to S4023, and may be performed in a different order.

[0047] Returning to the description of Fig. 4(A), in S403, the driving rule adjustment unit 203 adjusts the driving rules. Specifically, the driving rule adjustment unit 203 executes a rule parameter adjustment process for each driving rule in the driving rule table 300, as exemplified below.

[0048] For a driving rule with a driving rule ID of "1", the driving rule adjustment unit 203 first acquires map information from the driving control information management unit 201. Next, the driving rule adjustment unit 203 acquires motion information of obstacles present around the moving object 107 from the control related information acquisition unit 202. Next, the driving rule adjustment unit 203 determines the positional relationship between each obstacle and the left and right side ends of the passage. The left and right side ends of the passage are typically side walls. Alternatively, if an object is placed so as to be almost in contact with the side walls, it is that object.

[0049] If there is a bias in the number of obstacles on either the left or right side of the passage, the travel rule adjustment unit 203 sets the side of the passage with the greater bias (or the greater bias; the same applies below) as the rule parameter for travel rule ID "1". The reason for setting the side with the greater bias will be described later.

[0050] Here, bias is a value derived from Dleft / W and Dright / W, where W is the width of the passage, Dleft is the distance from a certain obstacle to the left edge, and Dright is the distance from that obstacle to the right edge. If the smaller of these two values ​​is below the threshold, it is determined that the obstacle is biased to one side of the passage (there is bias). If it is determined that there is no bias (or the bias is small; the same applies below), no adjustment of the rule parameters is made.

[0051] The bias of a single obstacle has been described above. When there are multiple obstacles, the driving rule adjustment unit 203 calculates the bias of each obstacle by the above method, and calculates the bias of all the obstacles based on the calculated bias. Multiple obstacles refer to multiple obstacles that are located at a distance within the detection range of the sensor 105. For example, if the ratio of the number of obstacles 110 with bias is equal to or less than a threshold, the driving rule adjustment unit 203 determines that there is no bias, and if the ratio exceeds the threshold, the driving rule adjustment unit 203 determines that there is bias.

[0052] Fig. 5 is a diagram for explaining the imbalance of multiple obstacles (here, people and other robots). The left side of Fig. 5 shows a state where there is no imbalance among the obstacles 110 as a whole, and the right side of Fig. 5 shows a state where there is an imbalance among the obstacles 110 as a whole. The arrows indicate the traveling directions of the obstacles.

[0053] In this embodiment, one of the objectives is for the moving body 107 to adjust its own movement method in accordance with the movement of the surrounding obstacles 110 when the obstacles 110, which are mainly people, and the moving body 107 share a space. Therefore, as shown on the right side of FIG. 5, for example, when multiple obstacles 110 are biased to the left side of the passage 150 and are moving in the same traveling direction, the information processing device 100 estimates that the passage 150 currently has a rule of keeping to the left. Then, the moving body 107 also travels on the left side in the same traveling direction in accordance with that rule. Note that the traveling direction of the obstacle 110 is also one of the obstacle operation information, and the information on the traveling direction is acquired by the control related information acquisition unit 202.

[0054] As described above, in this embodiment, a case where the detected obstacle moves in the same direction as the traveling direction of the moving body 107 is assumed as a precondition for executing the determination of the bias of the obstacle. In contrast, when the traveling direction of one or more obstacles is the opposite direction to that of the moving body 107, the side opposite to the side where the bias of the obstacle exists may be set as the rule parameter of the traveling rule ID "1". In this case, the traveling rule adjustment unit 203 first acquires information that the traveling direction of one or more obstacles is the opposite direction to the own device from the control related information acquisition unit 202. Then, the traveling rule adjustment unit 203 calculates the bias of the one or more obstacles in the same manner as above, and when there is a bias, sets the side opposite to the side where the bias exists as the rule parameter.

[0055] For a driving rule with a driving rule ID of "2", the driving rule adjustment unit 203 first acquires the density of obstacles from the control related information acquisition unit 202. Next, the driving rule adjustment unit 203 determines the approach limit distance between the moving object 107 and the obstacles based on the acquired density of obstacles. Then, the driving rule adjustment unit 203 sets the approach limit distance between the moving object 107 and the obstacles as a rule parameter for the driving rule ID of "2". For example, the approach limit distance is set smaller as the density increases, so that it is possible to prevent the moving object 107 from frequently detecting obstacles and taking evasive action, etc., resulting in a decrease in work efficiency. The approach limit distance to be set may be determined using a lookup table of "density of obstacles" and "approach limit distance". Alternatively, the approach limit distance may be determined using a function of "approach limit distance between the moving object 107 and the obstacles" with the "density of obstacles" as a parameter.

[0056] For a driving rule with a driving rule ID of "3", the driving rule adjustment unit 203 first acquires the density of obstacles present around the moving body 107 from the control-related information acquisition unit 202. Next, the driving rule adjustment unit 203 determines the speed of the moving body 107 based on the acquired density of obstacles. Then, the driving rule adjustment unit 203 sets the speed of the moving body 107 as a rule parameter of the driving rule ID "3". For example, the higher the density of obstacles, the lower the speed is set, thereby reducing the risk of collision between the moving body 107 and the obstacles. The set speed of the moving body 107 may be determined using a lookup table of "density of obstacles" and "speed of moving body 107", or may be determined using a function of "speed of moving body 107" with "density of obstacles" as a parameter. Alternatively, the set speed of the moving body 107 may be determined based on the distance to the obstacle present closest to the moving body 107 instead of the density of obstacles.

[0057] Note that there may be limitations on the options or range of values ​​that can be set for each rule parameter.

[0058] 6 is a flowchart showing a process for generating drive control information by the drive control information generating unit 204. This process is executed every time the drive rule adjusting unit 203 adjusts the drive rule.

[0059] In S501, the drive control information generation unit 204 acquires driving control information (map information and driving rules) from the driving control information management unit 201.

[0060] In S502, the drive control information generating unit 204 generates drive control information based on the driving rule. Specifically, the drive control information generating unit 204 executes a process for generating drive control information for each driving rule, as exemplified below.

[0061] For a driving rule with a driving rule ID of "1", the drive control information generating unit 204 generates the following drive control information. The drive control information generating unit 204 determines a driving route correction amount at each point of the driving route based on map information, rule parameters ("left side" or "right side"), the distance between the moving object 107 and the side end of the passage, etc., and sets this as the drive control information. The distance between the moving object 107 and the side end of the passage is a constant value, or a value expressed as a function of "distance from the side end of the passage" with "each point on the driving route" as a parameter. The drive control information generating unit 204 may obtain the travel path correction amount in advance for each variation of the rule parameter ("left side" or "right side"), and acquire the travel path correction amount corresponding to the rule parameter.

[0062] For the driving rule with the driving rule ID "2", the rule parameter "proximity limit distance to an obstacle" is used as drive control information.

[0063] For the driving rule with the driving rule ID "3", the rule parameter "velocity of moving body" is used as the drive control information.

[0064] As described above, the information processing device 100 according to the present embodiment adjusts the driving rules based on the control-related information, particularly on the operation information of obstacles present around the moving object 107. That is, the information processing device 100 autonomously adjusts the driving rules according to the surrounding situation, and therefore the degree of freedom of the driving of the moving object 107 can be increased. This can improve the work efficiency or business efficiency of the moving object 107, and can also reduce the possibility of collision with obstacles and improve safety.

[0065] (Weighting process) In the first embodiment, the driving rule adjustment unit 203 may weight the input values ​​of the calculation in the adjustment process of the driving rules. For example, the closer the distance (relative position) to the moving body 107 is to an obstacle, the heavier the weight is set. This allows the contribution of an obstacle closer to the moving body 107, that is, an obstacle more likely to affect the behavior of the moving body 107, to a greater extent in the adjustment result of the driving rules. An example of weighting in the adjustment process of the rule parameters in the driving rule table 300 shown in FIG. 3 will be described below.

[0066] In the rule parameter adjustment process for a driving rule with a driving rule ID of "1", when calculating the bias of an obstacle's position in a passage, the weight of the obstacle is changed based on the distance from the moving body 107 to the obstacle. For example, the smaller the distance, the larger the weight is set. Specifically, the driving rule adjustment unit 203 calculates a weighting coefficient based on the distance to the obstacle in question, calculates the bias of the obstacle, and sets the calculated weighting coefficient to the calculated bias. When multiple obstacles are present in the vicinity, a weight may be set for each obstacle.

[0067] In the rule parameter adjustment process for a driving rule with a driving rule ID of "2" or "3", when obtaining the density of obstacles existing around the moving body 107, the weight of the obstacle is changed based on the distance between the moving body 107 and each obstacle existing around it. For example, the smaller the distance, the larger the weight is set. Specifically, the driving rule adjustment unit 203 calculates a weighting coefficient based on the distance to the obstacle in question, calculates the density of the obstacle, and sets the calculated weighting coefficient to the calculated density. When multiple obstacles exist in the vicinity, a weight may be set for each obstacle.

[0068] The values ​​to be weighted may be not only the bias or density of obstacles, but also the speed or traveling direction of the obstacles.

[0069] <Second embodiment> In the first embodiment, the driving rule adjustment unit 203 used the obstacle's motion information as the control-related information in the driving rule adjustment process shown in Fig. 4. However, in the adjustment process according to the second embodiment, in addition to or instead of using the obstacle's motion information, it is also possible to further use moving object specific information and / or road surface configuration information. Among the moving object specific information, the width, weight, and obstacle detection range of the moving object 107 are fixed values, and the detection range depends on the capabilities and software configuration of the sensor 105.

[0070] The following describes the process in which the driving rule adjustment unit 203 uses the moving object specific information and the road surface configuration information to determine whether or not to adjust the driving rules. Figure 7 is a flowchart showing this process. In this process, steps S4021 to S4023 in Figure 4(B) are the same as those in Figure 4(B), so their description will be omitted.

[0071] In this process, an additional condition is added after S4023. In S7001, the driving rule adjustment unit 203 checks whether at least one of the moving object specific information and the road surface configuration information has changed since the driving rule was last adjusted.

[0072] The above-mentioned determination process is an example of a process in which the adjustment means determines whether or not to adjust the travel rule based on at least one of the unique information of the moving object and the road surface configuration information of the travel route of the moving object. Also, this process is not limited to the order of S4021, S4022, S4023, and S7001, and may be different from this. For example, the order of S7001 and S4023 may be reversed.

[0073] An example of a process in which the driving rule adjustment unit 203 adjusts the rule parameters of the driving rules shown in Fig. 3 by further using, for example, moving object specific information and road surface configuration information will be described below. The adjustment processes for the rule parameters of the driving rules "3", "4", and "5" shown below are examples of processes for calculating the speed of a moving object based on the moving object specific information and road surface configuration information when the adjustment means determines to adjust the driving rule.

[0074] For example, a case will be described in which the rule parameters of a driving rule with a driving rule ID of "3" are adjusted when there is a change in road surface configuration information. The driving rule adjustment unit 203 first obtains the friction coefficient of the road surface from the road surface configuration information, and also obtains the distance of the obstacle detection range from the moving object specific information. The friction coefficient of the road surface in a specific road surface state is generally known.

[0075] Using the commonly known relational expression (Equation 1 below) for calculating the braking distance, the speed v at which the moving body 107 can stop after detecting an obstacle and before colliding with the detected obstacle is calculated. Then, the traveling rule adjustment unit 203 sets the speed v to the rule parameter of the traveling rule ID "3". The calculation is performed assuming that the braking distance of the moving body 107 corresponds to the distance of the detection range of the obstacle.

[0076] Braking distance (distance of obstacle detection range) = v^2 / (254 * friction coefficient of road surface) Equation 1

[0077] On the other hand, for the driving rule with the driving rule ID "3" as above, the driving rule adjustment unit 203 can first obtain the location of a charging station for charging the battery of the mobile object 107 from the driving control information management unit 201. The location of the charging station may be preset as a fixed location, for example, and may be stored, or a signal including location information of the charging station, which is transmitted from the charging station or an external server, may be received. Next, the driving rule adjustment unit 203 acquires the position information of the moving object 107, and acquires information on the remaining battery charge of the moving object 107. Next, the driving rule adjustment unit 203 calculates the distance between the position of the moving object 107 and the charging base. Next, the driving rule adjustment unit 203 calculates the speed of the moving object 107 in consideration of the remaining battery charge and the distance. For example, when the remaining battery charge is low compared to the distance, the speed at which the drive unit operates most efficiently is calculated so as not to waste the battery. Then, the driving rule adjustment unit 203 sets the calculated speed of the moving object 107 to the rule parameters of the driving rule ID "3".

[0078] For a driving rule with a driving rule ID of "4", the driving rule adjustment unit 203 first acquires the road width at the current position of the moving body 107 from map information among the environmental information around the moving body 107. Next, the driving rule adjustment unit 203 acquires the width and weight of the moving body 107 among the moving body specific information. If the moving body 107 is carrying a load, the weight of the load is also acquired. Next, the travel rule adjustment unit 203 determines the behavior of the moving body 107 when the paths of the moving body 107 and the obstacle intersect. Specifically, when the moving body 107 can only avoid a collision by changing its path, the behavior of "changing the path" is determined. When there is another behavior that can avoid a collision, the width of the road and the width of the moving body 107 are compared, and when the width of the moving body 107 is smaller than the road width, the behavior of "changing the path" is determined. When the width of the moving body 107 is larger than the road width, the behavior of "reducing the speed" is determined. In order to minimize the energy required for re-acceleration, the amount of the speed to be reduced is determined to be inversely proportional to the weight of the moving body 107 (or the total weight including the weight of the loaded object). Also, when the width of the moving body 107 is larger than the road width, the behavior of "increasing the speed" may be determined. In order to minimize the energy required for acceleration, the amount of the speed to be increased is determined to be inversely proportional to the total weight of the moving body 107. Next, the driving rule adjustment unit 203 sets the determined behavior to the rule parameters of the driving rule ID "4".

[0079] In the travel rule with the travel rule ID "5", the travel rule adjustment unit 203 acquires the weight of the mobile object 107 (and the weight of the loaded object if the mobile object 107 has a load) from the mobile object specific information. Next, the travel rule adjustment unit 203 determines the behavior of the mobile object 107 when turning a corner. Specifically, when the total weight of the mobile object 107 is equal to or greater than the threshold value t1, the behavior is determined to be such that the mobile object 107 turns the corner by expanding to the opposite side of the turning direction (with the radius of curvature equal to or greater than the threshold value) so as to minimize deceleration. This is to prevent the mobile object 107 from decelerating as much as possible, and the greater the deceleration amount, the greater the weight of the mobile object 107, the greater the energy required for re-acceleration. When the total weight of the mobile object 107 is less than the threshold value t1, the behavior is determined to be such that the mobile object 107 stops once before the corner, or decelerates to a value equal to or less than the threshold value before turning. Next, the travel rule adjustment unit 203 sets the determined behavior to the rule parameters of the travel rule ID "5".

[0080] When there are multiple adjustment processes having different rule parameters for the same driving rule ID, a priority may be set in advance for each adjustment process, and the adjustment process to be applied may be determined based on the priority. In this case, the priority may be changed based on control-related information. For example, in the above example, two adjustment processes for a driving rule with a driving rule ID of "3" are exemplified. For example, when information indicating that the road surface is wet or frozen is acquired as road surface configuration information, the priority of the former is set high and the former is applied. On the other hand, when it is detected that the remaining battery charge of the moving body 107 is lower than the threshold, the priority of the latter is set high and the latter is applied.

[0081] <Third embodiment> In the first and second embodiments, at least the motion information of the obstacle is used as the control-related information in addition to the map information. However, in addition to or instead of using the motion information of the obstacle, the travel history information of the moving object 107 can also be used. As described above, the travel history information is information based on the movement history of the moving object 107 and the obstacles present around the moving object 107. The control-related information acquisition unit 202 records, as the travel history information, information on which side of the passage the moving object 107 and the obstacles have moved to in the past, or the density of the obstacles present in the passage, in chronological order. The travel history information may be information acquired as a result of analysis of the information on the movement history of the moving object and the obstacle.

[0082] The information processing device 100 periodically analyzes the travel history of the moving object 107 and the movement history of the obstacle, such as once a day, and accumulates trends related to their movements. As an example of a trend related to the movement of the moving object 107 and the obstacle, it may be possible that the obstacle tends to walk on the left side of the aisle A from 6:30 to 8:00 on weekdays. Also, it may be possible that the moving object 107 has almost no history of approaching an obstacle in the aisle C from 12:00 to 13:00 on weekdays, and that the passage of people is sparse.

[0083] 8 is a diagram showing an example of a travel tendency table obtained by analyzing the movement history of the moving object 107 and obstacles. The travel tendency table 600 is used to manage tendencies regarding the movement of the moving object 107 and obstacles. Each row of the travel tendency table 600 shows one travel tendency.

[0084] In the driving tendency ID 601, an ID for uniquely identifying a driving tendency stored in the driving tendency table 600 is described. In the time period 602, the time period in which the driving tendency appears is described. A location where a driving tendency appears is described in the location 603. The value of the location 603 is a word capable of identifying a location in correspondence with topographical information, or a series of coordinate information indicating a specific area. The type of traveling tendency is described in the tendency type 604. Note that the "proximity frequency" is the frequency at which the distance between the moving object 107 and an obstacle becomes equal to or smaller than the proximity limit distance. The tendency 605 describes the details of the driving tendency.

[0085] The process in which the driving rule adjustment unit 203 adjusts the rule parameters of the driving rules using the driving tendency table 600 will be described below.

[0086] The driving rule adjustment unit 203 acquires information on driving tendencies having a time period including the current time from the driving tendency table 600. If the acquired time is between 6:30 and 8:00 on a weekday, the driving rule adjustment unit 203 sets the tendency value "left side" of the driving tendency ID "1" corresponding to that time to the rule parameter of the driving rule ID "1" shown in FIG. 3.

[0087] On the other hand, when the acquired time is between 12:00 and 13:00 on a weekday, the traveling rule adjustment unit 203 determines the speed of the moving body 107 to be inversely proportional to the tendency value "0.02 times / minute" of the traveling tendency ID "2" corresponding to that time. In other words, when the "proximity frequency" is a relatively low value such as "0.02 times / minute", the traveling rule adjustment unit 203 sets the relatively high speed value of the moving body 107 to the rule parameter of the traveling rule ID "3" shown in FIG. 3.

[0088] In addition, if there is no time period 602 corresponding to the current time in the driving tendency table 600, the driving rule adjustment unit 203 may execute the processing according to the first or second embodiment described above (adjustment processing of the driving rules mainly based on the operation information of the obstacle, etc.). The travel rule adjustment process may be performed based on the obstacle operation information (and map information) as the control-related information. Alternatively, if the travel tendency table 600 has a time period 602 corresponding to the current time, a determination may be made as to whether to perform either the adjustment process according to the first or second embodiment or the adjustment process based on the travel history information at the current time. In this case, the determination may be made based on the control-related information (particularly, the obstacle operation information).

[0089] <Fourth embodiment> In the first embodiment, the driving rule adjustment unit 203 may adjust the driving rule and then, when a predetermined condition is satisfied, return the driving rule to a default state. The default state is a state in which default values ​​are set for the rule parameters of the driving rule.

[0090] Fig. 9 is a diagram showing an example of a driving rule table used to manage driving rules. In this driving rule table 310, the driving rule ID 301 and the driving rule 302 are the same as those shown in Fig. 3, so the explanation will be omitted. In the default value 701, the default value of the rule parameter in the driving rule is described.

[0091] Fig. 10 is a flowchart for explaining the process of adjusting the travel rule. The process explained in this flowchart is repeatedly executed at a fixed time interval. The interval of the repeated execution may be changed according to the distance between the moving body 107 and an obstacle or the density of the obstacle. S401 to S403 are the same as S401 to S403 shown in Fig. 4, and therefore the explanation will be omitted.

[0092] In S801, the driving rule adjustment unit 203 determines whether to return the driving rules to their default states. If the driving rules are to be returned to their default states, the process proceeds to S802. If the driving rules are not to be returned to their default states, the process proceeds to S402. S801 is an example of a process in which the adjustment means sets the rule parameters of the driving rules to default values ​​based on a predetermined condition.

[0093] To determine whether or not to return the driving rules to the default state, first, it is confirmed whether a predetermined time or more has passed since the driving rules were last adjusted. If the predetermined time or more has passed, the process proceeds to the next step. If the predetermined time or more has not passed, the driving rule adjustment unit 203 determines not to return the driving rules to the default state.

[0094] The driving rule adjustment unit 203 may further check whether the moving object 107 has moved a predetermined distance or more from the point where the driving rule was last adjusted. In this case, if a predetermined time or more has passed and the moving object 107 has moved a predetermined distance or more, the process may proceed to the next step. In other cases, the driving rule adjustment unit 203 determines not to return the driving rules to the default state.

[0095] Next, the driving rule adjustment unit 203 checks whether the moving object 107 is at least a predetermined distance away from an obstacle, a corner, a door, etc. If it is away, it determines that the driving rules should be returned to the default state. If it is not away, the driving rule adjustment unit 203 determines that the driving rules should not be returned to the default state.

[0096] Specifically, in S802, the driving rule adjustment unit 203 obtains default values ​​of the rule parameters for each driving rule managed in the driving rule table 310 shown in FIG.

[0097] In addition, in S402, when determining whether to adjust the driving rules, the driving rule adjustment unit 203 checks whether a predetermined time has passed since the driving rules were last adjusted (FIG. 4(B), S4021 in FIG. 7). In checking, if the driving rules were returned to the default state in the previous process shown in FIG. 8 (S802), the driving rule adjustment unit 203 interprets this as the previous driving rule being adjusted.

[0098] As described above, in this embodiment, the period during which the travel rules are in the default state is longer than in the first to third embodiments. Therefore, it becomes easier for obstacles (people and robots) existing around the moving object 107 to predict the behavior of the moving object 107, improving safety.

[0099] In this embodiment, the elapsed time from the previous rule parameter adjustment and the motion information of the moving object 107 are taken as examples of the targets of the determination process (predetermined conditions) for adjusting the rule parameters. However, the targets of the determination process are not limited to these, and may be other control-related information such as motion information of an obstacle.

[0100] The above-described two steps in the process of determining whether to return the travel rules to the default state (checking the elapsed time and checking the operation information of the moving object 107) may be performed in the reverse order.

[0101] <Fifth embodiment> In each of the above embodiments, drive control information for the moving body 107 is generated from the adjusted travel rule, and the drive state (behavior) of the moving body 107 is changed. In the fifth embodiment, the information processing device 100 may notify a person or a robot present around the moving body 107 that the drive state of the moving body 107 will be changed. This notification process is executed after S501 and before S502 shown in FIG. 6, or is started after S502 and before the moving body 107 changes the drive state.

[0102] The information processing device 100 notifies people or robots around the moving object 107 of the change in the driving state. The information processing device 100 may continue to transmit a notification indicating that while it is changing its behavior. The driving state is changing while the moving object 107 is, for example, changing its course to the left or right of a passage, turning a corner, or changing its speed (accelerating or decelerating).

[0103] The notification method may be a method in which the moving body 107 is equipped with a notification speaker and notifies by voice, or a method in which the moving body 107 is equipped with a notification display and displays the driving status of the moving body 107 on the display, or a method in which the moving body 107 is equipped with a communication device and uses this communication device to directly transmit a signal indicating the driving status of the moving body 107 to other robots with which it can communicate. Alternatively, the information processing device 100 may present the change in the driving state to a third party before the moving object 107 changes the driving state, and change the driving state after receiving approval from the third party.

[0104] According to this embodiment, the moving body 107 can change its driving state while people or robots around the moving body 107 are paying attention to the behavior of the moving body 107 due to the notification, and the safety of the people and robots is improved. In particular, safety is increased by being notified when changing between left and right paths, when turning a corner, when increasing speed, etc.

[0105] In addition, the speaker, display, and function of generating and transmitting a signal indicating the driving state for notification in this embodiment are examples of notification means that notify that the driving state of the mobile body will be changed before the driving of the mobile body is executed under the control of the control means.

[0106] Sixth embodiment In the above embodiments, the travel rules are expressed using rule parameters, but in the sixth embodiment, the travel rules are expressed using a graph that shows the relative positions of the terrain, the moving object 107, and the obstacles. In this embodiment, the terrain, the moving object 107, and the obstacles are collectively called "objects."

[0107] Fig. 11 is a diagram illustrating a graph showing the positional relationship of objects (hereinafter, referred to as an object positional relationship graph). The positional relationship of objects may differ for each point on the driving route, and Fig. 11(A) and Fig. 11(B) illustrate the positional relationship of objects at different points.

[0108] This object position relationship graph is an example of an undirected graph with the moving object 107 and objects around the moving object 107 as nodes. Two objects 901 are related to each other by a relationship line 902 connecting them. In this embodiment, the relationship between the objects is expressed with the moving object 107 at the center. The length of the relationship line 902 represents the magnitude of the relationship between the objects. In this embodiment, the length of the relationship line 902 represents the distance between the objects 901. The shorter the relationship line 902, the closer the objects 901 connected by the relationship line 902 can approach each other.

[0109] The distance corresponding to the length of the relationship line 902 is typically the proximity limit distance. However, this distance is not limited to the proximity limit distance, and may be longer than the proximity limit distance by a predetermined distance, or may be a distance calculated based on the proximity limit distance and / or the control-related information.

[0110] 12 is a diagram showing an example of an object table used to manage the objects 901. Each row of the object table 1000 represents one object 901. An ID for uniquely identifying the object 901 stored in the object table 1000 is described in the object ID 1001 . The name of the object 901 is described in the object name 1002 .

[0111] FIG. 13 is a diagram showing an example of a positional relationship information table used to manage the positional relationship of the object 901. As shown in FIG. In the positional relationship information ID 1101, an ID for uniquely identifying the positional relationship information stored in the positional relationship information table 1100 is described. The valid range 1102 describes the location where the positional relationship information is valid. The value of the valid range 1102 is a word that can identify a location in correspondence with the topographical information, or a series of coordinate information that indicates a specific area. The valid range 1102 is used to identify the object positional relationship graph in a specific location. The object ID of one of the two related objects 901 is described in object ID (1) 1103. In the example shown in Fig. 13, object ID (1) is fixed to moving object "1". Object ID (2) 1104 describes the object ID of the object other than the object identified by object ID (1) 1103, out of the two related objects. A value expressing the magnitude of the relationship between two objects is described in the relationship value 1105. The relationship value corresponds to the length of the relationship line.

[0112] In one row of this positional relationship information table 1100, particularly, object ID (1) 1103, object ID (2) 1104, and relationship value 1105 correspond to one piece of positional relationship information.

[0113] Fig. 14 is a flowchart for explaining the process of adjusting the driving rules. This process is repeatedly executed at regular time intervals. The execution interval may be changed depending on the distance between the moving body 107 and an obstacle or the density of the obstacles. S401 and S402 are the same as those in Fig. 4(A), so the explanation will be omitted.

[0114] In S1201, the driving rule adjustment unit 203 adjusts the driving rule. In this case, the driving rule is an object position relationship graph, and the rule parameter of the driving rule is the length of the relationship line 902. Specifically, the driving rule adjustment unit 203 executes a rule parameter adjustment process as exemplified below.

[0115] As a first adjustment processing method, the driving rule adjustment unit 203 acquires topographical information (may be map information) from the driving control information management unit 201. The driving rule adjustment unit 203 also acquires position information of the moving object 107 and the obstacles from the control related information acquisition unit 202. Next, the driving rule adjustment unit 203 obtains the positional relationship between each obstacle and the left and right ends of the passage. If the obstacles are biased to either the left or right of the passage, the driving rule adjustment unit 203 adjusts the length of the relation line 902 between the object 901 representing the moving object 107 in the object position relation graph and the object 901 corresponding to both side ends of the passage. At this time, the length of the relation line 902 corresponding to the moving object 107 and the left or right of the passage on the side where the obstacles are biased is set shorter than the length of the relation line 902 corresponding to the moving object 107 and the left or right of the passage on the side where the bias is not present. This is because, as shown on the right side of Figure 5, in order to make the moving body 107 pass along the side where the obstacle is biased, the driving rule adjustment unit 203 adjusts (reduces) the distance from the side edge where the bias is located.

[0116] The length of the relation line 902 in the object position relation graph can be adjusted, for example, in the following manner. The driving rule adjustment unit 203 refers to the position relation information table 1100 and acquires the effective range corresponding to the current position of the moving body 107. There are multiple possibilities for the acquired effective range (corresponding position relation information ID). From among them, the driving rule adjustment unit 203 adjusts the relationship value of the position relation information (object ID (1) 1103, object ID (2) 1104, and relationship value 1105) that includes the relationship value that is the subject of length adjustment.

[0117] As a second adjustment processing method, the traveling rule adjustment unit 203 acquires the position of the moving object 107 and the density of obstacles existing around the moving object 107 from the control related information acquisition unit 202. Next, the traveling rule adjustment unit 203 determines a target distance between the moving object 107 and the obstacle based on the acquired density of the obstacle. The method for calculating the target distance based on the density of the obstacle is the method described in the first embodiment. Then, the traveling rule adjustment unit 203 adjusts the length of the relation line 902 between the object 901 representing the moving object 107 in the object position relation graph and the object 901 representing the obstacle so that it matches the target distance.

[0118] Specifically, the driving rule adjustment unit 203 refers to the positional relationship information table 1100 and acquires positional relationship information (object ID 1103, object ID (2) 1104, and relationship value 1105) based on the current position and effective range of the moving body 107. Then, the driving rule adjustment unit 203 sets the target distance determined above to the relationship value 1105 of the positional relationship information. Here, the target distance may be determined using a lookup table of "obstacle density" and "target distance", or may be determined using a function of "target distance" with "obstacle density" as a parameter.

[0119] 15 is a flowchart for explaining the process of generating drive control information in this embodiment. This process is executed every time the driving rule (object position relationship graph) is adjusted. S501 is the same as S501 in FIG. 6, so the description will be omitted.

[0120] In S1301 , the drive control information generating unit 204 acquires the position information of the moving object 107 from the control-related information supplied from the control-related information acquiring unit 202 .

[0121] In S1302, the drive control information generating unit 204 generates drive control information based on the driving rule. Specifically, the drive control information generating unit 204 refers to the positional relationship information table 1100 and acquires positional relationship information based on the position and effective range of the moving body 107. Then, the drive control information generating unit 204 executes a drive control information generation process as exemplified below for the object positional relationship graph represented by the positional relationship information.

[0122] The drive control information generating unit 204 executes the following process. The drive control information generating unit 204 determines a travel path correction amount at the position of the moving object 107 based on map information, relational values, and the distance between the moving object 107 and the side ends (both left and right ends) of the passage, and sets this as drive control information. The distance between the moving object 107 and the side ends of the passage may be, for example, a predetermined constant value, or may be a value expressed as a function of "distance from the side ends of the passage" with "each point on the travel path" as a parameter.

[0123] The above-mentioned relationship values ​​for calculating the travel path correction amount are relationship values ​​adjusted in S1201. That is, in order to calculate the travel path correction amount, the drive control information generating unit 204 obtains not only the relationship values ​​1105 related to both ends of the passage as the object 901, but also the relationship values ​​1105 related to other objects 901. That is, the drive control information generating unit 204 generates drive control information based on multiple pieces of positional relationship information in the positional relationship information table 1100.

[0124] As described above, in this embodiment, a graph showing the mutual positional relationships between the moving object 107, the terrain, and obstacles is introduced to express the driving rules. In other words, the driving rules can be expressed by a simple weighted undirected graph, which makes it possible to simplify the adjustment process of the driving rules.

[0125] <Other embodiments> In each of the above embodiments, it is assumed that the moving object 107 moves within a facility, for example. However, it is also possible that the moving object 107 runs on public roads as a vehicle.

[0126] Although the embodiment examples have been described in detail above, the present disclosure can be embodied, for example, as a system, an apparatus, a method, a program, or a recording medium (storage medium), etc. Specifically, the present disclosure may be applied to a system composed of multiple devices (for example, a host computer, an interface device, an imaging device, a web application, etc.), or may be applied to an apparatus composed of a single device. Needless to say, the object of the present disclosure can be achieved by the following: That is, a recording medium (or storage medium) on which is recorded a program code (computer program) of software that realizes the functions of the above-mentioned embodiments is supplied to a system or device. The storage medium is, of course, a computer-readable storage medium. Then, a computer (or a CPU or MPU) of the system or device reads and executes the program code stored in the recording medium. In this case, the program code itself read from the recording medium realizes the functions of the above-mentioned embodiments, and the recording medium on which the program code is recorded constitutes the present disclosure.

[0127] The disclosure of this embodiment includes the following configuration, method, and program. (Configuration 1) An acquisition means for acquiring control-related information including environmental information for controlling a moving object; an adjustment means for adjusting a travel rule to be followed for the travel of the moving object based on the control-related information; and a control means for controlling driving of the moving body based on driving control information including the adjusted driving rule. (Configuration 2) The information on the driving rule includes a variable rule parameter, The adjustment means adjusts the rule parameters. 2. The information processing device according to configuration 1. (Configuration 3) The adjustment means adjusts the rule parameters based on a bias of obstacles around the moving body on a path along which the moving body travels. 3. The information processing device according to configuration 2. (Configuration 4) The adjustment means adjusts the rule parameters based on a density of obstacles present around the moving object. 4. The information processing device according to configuration 2 or 3. (Configuration 5) The adjustment means determines whether or not to adjust the driving rule based on a predetermined condition. 5. The information processing device according to any one of configurations 1 to 4. (Configuration 6) The adjustment means determines whether to adjust the traveling rule based on at least one of the predetermined conditions: a time elapsed since the previous adjustment of the traveling rule, motion information of the moving object among the control-related information, and motion information of an obstacle existing around the moving object. 6. The information processing device according to configuration 5. (Configuration 7) The adjustment means determines whether to adjust the driving rule based on at least one of the predetermined conditions: a time elapsed since the previous adjustment of the driving rule, specific information of the moving object among the control-related information, and road surface configuration information of a driving route of the moving object among the control-related information. 6. The information processing device according to configuration 5. (Configuration 8) When it is determined that the travel rule is to be adjusted, the adjustment means calculates a speed of the moving body based on the unique information of the moving body and the road surface configuration information, and adjusts the travel rule based on the speed of the moving body. 8. The information processing device according to configuration 7. (Configuration 9) The adjustment means weights input values ​​for calculation in the adjustment process of the driving rules. 9. The information processing device according to any one of configurations 1 to 8. (Configuration 10) The adjustment means adjusts the driving rule based on driving history information, which is based on a movement history of the moving object and an obstacle existing around the moving object, among the control-related information. 10. The information processing device according to any one of configurations 1 to 9. Information processing device. (Configuration 11) The adjustment means sets the rule parameters of the driving rules to default values ​​based on a predetermined condition. 11. The information processing device according to any one of configurations 2 to 10. (Configuration 12) The adjustment means sets the rule parameter to the default value based on at least one of the predetermined condition, that is, the time elapsed since the previous adjustment of the rule parameter and the operation information of the moving object among the control-related information. 12. The information processing device according to configuration 11. (Configuration 13) 13. The information processing device according to any one of configurations 1 to 12, further comprising a notification means for notifying that a driving state of the moving body will be changed before driving of the moving body is executed under the control of the control means. (Configuration 14) The adjustment means acquires the travel rule as an undirected graph having the moving body and objects around the moving body as nodes. 14. The information processing device according to any one of configurations 2 to 13. (Configuration 15) the undirected graph includes relational lines connecting the nodes as the rule parameters; The length of the relation line indicates the distance between the moving object and the surrounding object. 15. The information processing device according to configuration 14. (Configuration 16) The control-related information and the driving control information each further include map information. 16. The information processing device according to any one of configurations 1 to 15. (Configuration 17) A moving body whose traveling is controlled by an information processing device, The information processing device includes: An acquisition means for acquiring control-related information including environmental information for controlling the moving object; an adjustment means for adjusting a travel rule to be followed for the travel of the moving object based on the control-related information; and a control means for controlling the driving of the moving body based on driving control information including the adjusted driving rule. (Method 1) acquiring control-related information including environmental information for controlling a moving object; adjusting a travel rule to be followed for travel of the moving object based on the control-related information; and controlling the driving of the moving body based on driving control information including the adjusted driving rule. (Program 1) A program to be executed by an information processing device that controls traveling of a moving object, acquiring control-related information including environmental information for controlling the moving object; adjusting a travel rule to be followed for travel of the moving object based on the control-related information; and controlling the driving of the moving object based on driving control information including the adjusted driving rule.

[0128] The present disclosure has been described above in detail based on preferred embodiments thereof, but the present disclosure is not limited to the above embodiments, and various modifications are possible based on the gist of the present disclosure, and these modifications are not excluded from the scope of the present disclosure. [Explanation of symbols]

[0129] 100 Information processing device 107 Mobile 110 Obstacles 201 Driving Information Management Department 202 Control-related information acquisition unit 203 Driving Rules Adjustment Department 204 Drive control information generation unit 205 Drive control unit 302 Driving Rules

Claims

1. An acquisition means for acquiring control-related information including environmental information for controlling a moving object; an adjustment means for adjusting a travel rule to be followed for the travel of the moving object based on the control-related information; and a control means for controlling driving of the moving body based on driving control information including the adjusted driving rule.

2. The information on the driving rule includes a variable rule parameter, The adjustment means adjusts the rule parameters.

2. The information processing apparatus according to claim 1,

3. The adjustment means adjusts the rule parameters based on a bias of obstacles around the moving body on a path along which the moving body travels.

3. The information processing apparatus according to claim 2.

4. The adjustment means adjusts the rule parameters based on a density of obstacles present around the moving object.

3. The information processing apparatus according to claim 2.

5. The adjustment means determines whether or not to adjust the driving rule based on a predetermined condition.

2. The information processing apparatus according to claim 1,

6. The adjustment means determines whether to adjust the traveling rule based on at least one of the predetermined conditions: a time elapsed since the previous adjustment of the traveling rule, motion information of the moving object among the control-related information, and motion information of an obstacle existing around the moving object.

6. The information processing apparatus according to claim 5,

7. The adjustment means determines whether to adjust the driving rule based on at least one of the predetermined conditions: a time elapsed since the previous adjustment of the driving rule, specific information of the moving object among the control-related information, and road surface configuration information of a driving route of the moving object among the control-related information.

6. The information processing apparatus according to claim 5,

8. When it is determined that the travel rule is to be adjusted, the adjustment means calculates a speed of the moving body based on the unique information of the moving body and the road surface configuration information, and adjusts the travel rule based on the speed of the moving body.

8. The information processing apparatus according to claim 7,

9. The adjustment means weights input values ​​for calculation in the adjustment process of the driving rules.

2. The information processing apparatus according to claim 1,

10. The adjustment means adjusts the driving rule based on driving history information, which is based on a movement history of the moving object and an obstacle existing around the moving object, among the control-related information.

2. The information processing apparatus according to claim 1,

11. The adjustment means sets the rule parameters of the driving rules to default values ​​based on a predetermined condition.

3. The information processing apparatus according to claim 2.

12. The adjustment means sets the rule parameter to the default value based on at least one of the predetermined condition, that is, the time elapsed since the previous adjustment of the rule parameter and the operation information of the moving object among the control-related information.

12. The information processing apparatus according to claim 11 .

13. 2. The information processing apparatus according to claim 1, further comprising a notification unit that notifies the user that a driving state of the moving body will be changed before the moving body is driven under the control of the control unit.

14. The adjustment means acquires the travel rule as an undirected graph having the moving body and objects around the moving body as nodes.

3. The information processing apparatus according to claim 2.

15. the undirected graph includes relational lines connecting the nodes as the rule parameters; The length of the relation line indicates the distance between the moving object and the surrounding object.

15. The information processing apparatus according to claim 14,

16. The control-related information and the driving control information each further include map information.

2. The information processing apparatus according to claim 1,

17. A moving body whose traveling is controlled by an information processing device, The information processing device includes: An acquisition means for acquiring control-related information including environmental information for controlling the moving object; an adjustment means for adjusting a travel rule to be followed for the travel of the moving object based on the control-related information; and a control means for controlling the driving of the moving body based on driving control information including the adjusted driving rule.

18. acquiring control-related information including environmental information for controlling a moving object; adjusting a travel rule to be followed for travel of the moving object based on the control-related information; and controlling driving of the moving body based on driving control information including the adjusted driving rule.

19. A program to be executed by an information processing device that controls traveling of a moving object, acquiring control-related information including environmental information for controlling the moving object; adjusting a travel rule to be followed for travel of the moving object based on the control-related information; and controlling the driving of the moving object based on driving control information including the adjusted driving rule.

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