Information processing system, information processing method, and information processing program

Abstract

To provide an information processing system capable of reducing a processing load when reproducing a traffic environment in a real world in a virtual space.SOLUTION: A communication device of an information processing system acquires mobile body information (step S10). A processing device of the information processing system calculates prediction mobile body information being the information indicating a position of a mobile body after a time when the mobile body information is acquired (step S11). The processing device calculates test prediction mobile body information being the information indicating the position of the mobile body acquired at the same time as the position of the mobile body indicated in the prediction mobile body information based on test mobile body information being the mobile body information acquired at a time different from that of the mobile body information used in calculating the prediction mobile body information (step S13). The processing device evaluates correspondence between the prediction mobile body information and the test prediction mobile body information (step S15, step S16). The processing device determines an updating period of the prediction mobile body information based on the evaluation of correspondence (step S17).SELECTED DRAWING: Figure 3

Description

[Technical Field]

[0001] The present invention relates to an information processing system, an information processing method, and an information processing program for reproducing a real-world traffic environment in a virtual space. [Background technology]

[0002] Digital twin is a technology that reproduces an environment identical to the real world in a virtual space. Patent Document 1 discloses a system that uses a transportation digital twin that reproduces a real-world traffic environment in a virtual space. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Japanese Patent Application Publication No. 2020-013557 Summary of the Invention [Problem to be solved by the invention]

[0004] In order to accurately reproduce the position of each moving object in the real world in a virtual space, it is conceivable to set the update period for the position of each moving object in the virtual world as short as possible, but this increases the processing load on the device that updates the position of the moving object. [Means for solving the problem]

[0005] An information processing system for solving the above problem includes a processing device and a communication device. The communication device sequentially acquires mobile object information, which is information indicating the position of a mobile object existing in the real world. The processing device calculates, at a default update period, predicted mobile object information, which is information indicating the position of the mobile object at a time after the time the mobile object information is acquired, based on the mobile object information sequentially acquired by the communication device. The processing device evaluates a correspondence between the position of the mobile object in the predicted mobile object information and the position of the mobile object at the same time as the predicted mobile object information, calculated from mobile object information acquired by the communication device at a time different from the time the mobile object information used to calculate the predicted mobile object information was acquired. The processing device determines the default update period based on the evaluation.

[0006] An information processing method for solving the above problem is an information processing method executed in an information processing system including a communication device that sequentially acquires mobile object information, which is information indicating the position of a mobile object existing in the real world, and a processing device that calculates, at a default update period, predictive mobile object information, which is information indicating the position of the mobile object at a time after the time the mobile object information is acquired, based on the mobile object information sequentially acquired by the communication device. This information processing method includes a step by the processing device evaluating a correspondence between the position of the mobile object in the predictive mobile object information and the position of the mobile object at the same time as the predictive mobile object information, calculated from mobile object information acquired by the communication device at a time different from the time the mobile object information used to calculate the predictive mobile object information was acquired. This information processing method also includes a step of determining the default update period based on the evaluation.

[0007] An information processing program for solving the above problem is an information processing program executed by a processing device of an information processing system including a communication device that sequentially acquires mobile object information, which is information indicating the position of a mobile object existing in the real world, and a processing device that calculates, at a default update period, predictive mobile object information, which is information indicating the position of the mobile object at a time after the time the mobile object information is acquired, based on the mobile object information sequentially acquired by the communication device. This information processing program causes the processing device to evaluate a correspondence between the position of the mobile object in the predictive mobile object information and the position of the mobile object at the same time as the predictive mobile object information, calculated from mobile object information acquired by the communication device at a time different from the time the mobile object information used to calculate the predictive mobile object information was acquired. This information processing program causes the processing device to determine the default update period based on the evaluation. [Effects of the Invention]

[0008] According to the information processing system, information processing method, and information processing program described above, it is possible to reduce the processing load for updating the predicted moving object information while calculating highly accurate predicted moving object information. [Brief explanation of the drawings]

[0009] [Figure 1] FIG. 1 is a schematic diagram illustrating an information processing system according to an embodiment. [Figure 2] FIG. 2 is a schematic diagram showing a processing device, a communication device, and a storage device that constitute the information processing system of the embodiment. [Figure 3] FIG. 3 is a flowchart showing the flow of processing executed by the information processing system of the first embodiment. [Figure 4] FIG. 4 is a schematic diagram showing a moving object in a predetermined area. [Figure 5] FIG. 5 is a schematic diagram showing the magnitude of the positional deviation between a moving body in the predicted moving body information and a moving body in the test predicted moving body information. [Figure 6]FIG. 6 is a table showing a calculation mode of the similarity, which is an index value indicating the degree of similarity. [Figure 7] FIG. 7 is a table showing the relationship between the similarity rate, which is an index value indicating the degree of similarity for each area, and the update period of the predicted moving object information for each area. [Figure 8] FIG. 8 is a flowchart showing the flow of processing executed by the information processing system of the second embodiment. DETAILED DESCRIPTION OF THE INVENTION

[0010] (First embodiment) Hereinafter, a first embodiment of an information processing system will be described with reference to FIGS. <Outline of Information Processing System 10> The information processing system 10 acquires moving object information, which is information indicating the positions of multiple moving objects 800 in the real world, at multiple times. The multiple moving objects 800 include, for example, vehicles 600, pedestrians 700, bicycles, animals, etc. The vehicles 600 include two-wheeled vehicles.

[0011] The information processing system 10 uses the acquired mobile object information to calculate, at a predetermined update period, predicted mobile object information, which is the position of the mobile object 800 after the time the mobile object information is acquired. The predicted mobile object information is a reproduction of the traffic environment in the real world in a virtual space.

[0012] As shown in FIG. 1, the information processing system 10 is capable of communicating with a plurality of information processing terminals 500, a plurality of vehicles 600, and a plurality of road sensors 900 via an external communication network 400.

[0013] The information processing terminal 500 can collect, as mobile object information, position information of the pedestrian 700 carrying the information processing terminal 500. The position information is coordinate values ​​of latitude and longitude. The information processing terminal 500 can transmit the collected position information of the pedestrian 700 to the information processing system 10 via the external communication network 400. The information processing terminal 500 is, for example, a smartphone carried by the pedestrian 700. The information processing terminal 500 also includes a wearable terminal, a tablet terminal, and the like. Examples of wearable terminals include a ring-type terminal worn on the wrist and a necklace-type terminal worn around the neck.

[0014] The vehicle 600 is equipped with an on-board sensor 610. The vehicle 600 can transmit moving body information collected by the on-board sensor 610 to the information processing system 10 via the external communication network 400. The on-board sensor 610 is, for example, a vehicle speed sensor, an accelerator sensor, a brake sensor, a steering sensor, and an acceleration sensor. The acceleration sensor is, for example, an IMU (Inertial Measurement Unit).

[0015] Furthermore, vehicle 600 is equipped with an exterior camera, sonar, and a position information acquisition system as on-board sensors 610. The exterior camera and sonar mounted on vehicle 600 collect information on the distance to other objects located around vehicle 600 and generate observation data. Vehicle 600 may also be equipped with a LiDAR (Light Detection And Ranging) sensor that performs the same function as the exterior camera and sonar. The position information acquisition system is, for example, a GNSS (Global Navigation Satellite System), RTK (Real Time Kinematic), LiDAR, etc.

[0016] The on-board sensor 610 collects, as moving body information, for example, vehicle information such as the VIN (Vehicle Identification Number) of the vehicle 600, trajectory information, which is the speed, direction of travel, and travel path of the vehicle 600, and position information.

[0017] The road sensors 900 are multiple sensors installed on a road. The road sensors 900 include multiple traffic lights 910, multiple road cameras 920, and LiDAR installed on the road. The traffic lights 910 can transmit information related to changes in the state of the traffic infrastructure, such as the timing at which the traffic light 910 changes to green and the number of seconds that the traffic light 910 remains green, to the information processing system 10 via the external communication network 400.

[0018] The road camera 920 collects observation data around the road camera 920. The observation data includes mobile object information of the mobile object 800 that exists around the road camera 920. The road camera 920 is, for example, a visible light camera or an infrared camera. The LiDAR installed on the road acquires point cloud data arranged in chronological order by continuous observation at regular time intervals. The LiDAR installed on the road also collects mobile object information of the mobile object 800 that exists around the LiDAR.

[0019] <Provision of transportation services based on predicted mobility information> The information processing system 10 can transmit the predicted moving object information to the vehicle 600. The vehicle 600 can provide transportation services to the user of the vehicle 600 based on the predicted moving object information acquired by the information processing system 10. The vehicle 600 includes, as on-board equipment, an on-board processing circuit, a brake system, a steering system, a turn signal, a speaker, and a display. The display of the vehicle 600 functions as a display unit that displays transportation services to the user of the vehicle 600. For example, the on-board processing circuit of the vehicle 600 can display a vehicle approaching notification or traffic information on the display of the vehicle 600 based on the predicted moving object information. For example, the on-board processing circuit of the vehicle 600 can issue a vehicle approaching warning to the user of the vehicle 600 from the speaker of the vehicle 600 based on the predicted moving object information. The on-board processing circuit of the vehicle 600 can control the brake system of the vehicle 600 based on the predicted moving object information, thereby slowing down or stopping the vehicle 600. For example, the on-board processing circuit of the vehicle 600 can control the steering system of the vehicle 600 based on the predicted moving object information, thereby performing steering control of the vehicle 600. The on-board processing circuit may also control the turn signals in addition to the steering control.

[0020] The information processing system 10 can transmit the predicted moving object information to the information processing terminal 500. The information processing terminal 500 can provide a transportation service to the user of the information processing terminal 500 based on the predicted moving object information acquired by the information processing system 10. For example, the information processing terminal 500 can display a vehicle approaching notification or traffic information on the display of the information processing terminal 500 based on the predicted moving object information.

[0021] The information processing system 10 can transmit the predicted moving object information to the traffic light 910. The traffic light 910 can control the function of the traffic light 910 based on the predicted moving object information acquired by the information processing system 10. For example, the traffic light 910 can control the timing at which the traffic light 910 switches to green and the number of seconds that the traffic light 910 remains green based on the predicted moving object information. This allows the information processing system 10 to contribute to smooth traffic flow.

[0022] <Configuration of Information Processing System 10> As shown in FIG. 2, the information processing system 10 includes a processing device 100, a storage device 200, and a communication device 300.

[0023] The processing device 100 includes a first processing circuit 101, a first storage circuit 102, and a first communication circuit 103. A program is stored in the first storage circuit 102. The first processing circuit 101 executes the program stored in the first storage circuit 102 to perform various processes. The first processing circuit 101 includes a processor. The processing device 100 is connected to an external communication network 400 via the first communication circuit 103.

[0024] The storage device 200 includes a second processing circuit 201, a second storage circuit 202, and a second communication circuit 203. A program is stored in the second storage circuit 202. The second processing circuit 201 executes the program stored in the second storage circuit 202 to perform various processes. The second processing circuit 201 includes a processor. The storage device 200 is connected to an external communication network 400 via the second communication circuit 203.

[0025] The communication device 300 includes a third processing circuit 301, a third storage circuit 302, and a third communication circuit 303. A program is stored in the third storage circuit 302. The third processing circuit 301 executes the program stored in the third storage circuit 302 to perform various processes. The third processing circuit 301 includes a processor. The communication device 300 is connected to an external communication network 400 via the third communication circuit 303.

[0026] The configuration of the information processing system 10 is not limited to the configuration shown in Fig. 2. For example, the processing device 100, the storage device 200, and the communication device 300 may be provided in a single server. For example, the processing device 100, the storage device 200, and the communication device 300 may be connected to each other via wired connections so that they can communicate with each other.

[0027] 2 illustrates a first vehicle 601 and a second vehicle 602 as examples of mobile objects 800 for which the information processing system 10 calculates predicted mobile object information. The first vehicle 601 includes a first on-board sensor 611 that transmits mobile object information of the first vehicle 601 to the information processing system 10 via the external communication network 400. Similarly, the second vehicle 602 includes a second on-board sensor 612 that transmits mobile object information of the second vehicle 602 to the information processing system 10 via the external communication network 400.

[0028] The communication device 300 sequentially acquires mobile object information transmitted from the sensor at a predetermined acquisition period via the third communication circuit 303. The communication device 300 stores the acquired mobile object information in the third storage circuit 302. The third processing circuit 301 of the communication device 300 transmits the mobile object information stored in the third storage circuit 302 to the processing device 100 via the third communication circuit 303.

[0029] The processing device 100 acquires moving object information from the communication device 300 via the first communication circuit 103. The processing device 100 stores the received moving object information in the first memory circuit 102. The first processing circuit 101 of the processing device 100 calculates predicted moving object information using the moving object information. The processing device 100 transmits the predicted moving object information to the memory device 200 via the first communication circuit 103.

[0030] The storage device 200 receives the predicted moving object information via the second communication circuit 203. The storage device 200 stores the acquired predicted moving object information in the second storage circuit 202. The second processing circuit 201 of the storage device 200 provides the predicted moving object information stored in the second storage circuit 202 in response to a request via the external communication network 400.

[0031] The first vehicle 601 and the second vehicle 602 are examples of moving objects 800 for which the information processing system 10 calculates predicted moving object information. For example, the information processing system 10 calculates the predicted moving object information of the first vehicle 601 based on moving object information acquired from a first in-vehicle sensor 611. For example, the information processing system 10 calculates the predicted moving object information of the second vehicle 602 based on moving object information acquired from a second in-vehicle sensor 612.

[0032] The information processing system 10 updates the predicted moving object information at a default update period. If the update period at which the information processing system 10 updates the predicted moving object information is short, the amount of predicted moving object information updated by the information processing system 10 per unit time increases. In other words, if the default update period at which the information processing system 10 updates the predicted moving object information is short, the processing load on the information processing system 10 increases. On the other hand, if the update period at which the predicted moving object information is updated is long, the discrepancy between the position of the moving object 800 in the real world and the position of the moving object 800 in the predicted moving object information may increase. Furthermore, when predicting the position of the moving object 800 beyond the current time, the accuracy of the position of the moving object 800 in the predicted moving object information may decrease. Therefore, the information processing system 10 determines an appropriate update period for the predicted moving object information by performing the process described below.

[0033] <Processing Executed by Information Processing System 10> Hereinafter, with reference to FIGS. 3 to 7, a process flow in which the information processing system 10 in the first embodiment determines the update period of the predictive moving object information will be specifically described.

[0034] 3 is a flowchart showing the flow of a series of processes executed by the information processing system 10. The information processing system 10 repeatedly executes this series of processes. As shown in Figure 3, when this series of processes begins, the information processing system 10 first acquires, in step S10, mobile object information of a mobile object 800 located within the area 20 shown in Figure 4 via the third communication circuit 303 of the communication device 300.

[0035] As shown in FIG. 4, the communication device 300 of the information processing system 10 sets a first area 21, a second area 22, a third area 23, and a fourth area 24 as areas 20 for calculating predicted mobile object information based on information indicating latitude and longitude. A first mobile object 801, a second mobile object 802, a third mobile object 803, and a fourth mobile object 804 exist in the first area 21. A fifth mobile object 805, a sixth mobile object 806, a seventh mobile object 807, and an eighth mobile object 808 exist in the second area 22. A ninth mobile object 809 and a tenth mobile object 810 exist in the third area 23. An eleventh mobile object 811, a twelfth mobile object 812, a thirteenth mobile object 813, and a fourteenth mobile object 814 exist in the fourth area 24.

[0036] In the first embodiment, the processing device 100 updates the predicted moving object information of the moving objects 800 present in each area 20 at the same update period for each area 20. For example, the processing device 100 updates the predicted moving object information of a first moving object 801, a second moving object 802, a third moving object 803, and a fourth moving object 804 present in a first area 21 at the same update period.

[0037] The communication device 300 may set any range as the area 20 based on information other than latitude and longitude. For example, the communication device 300 may set a station area with heavy traffic as the first area 21, a residential area with medium traffic as the second area 22, and a mountainous area with light traffic as the third area 23 based on the traffic volume per unit time.

[0038] The mobile object information acquired by the communication device 300 includes location information, moving speed, direction of travel, and type of each mobile object 800. After the communication device 300 acquires the mobile object information within the area 20 from the sensor, the process proceeds to step S11.

[0039] In step S11 , the processing device 100 of the information processing system 10 calculates predicted moving body information for each moving body 800 . For example, the processing device 100 estimates possible trajectories and possible positions of the vehicle 600 based on the position information, movement speed, and traveling direction of each vehicle 600, which is a moving body 800. Furthermore, the processing device 100 estimates the probability that the vehicle 600 will be present at each position within the area 20 based on road information of the area 20 acquired from a sensor. The road information of the area 20 includes the display of traffic lights installed in the lane on which the vehicle 600 is traveling, the presence or absence of road signs such as "No Entry for Vehicles," and the presence or absence of pedestrians 700 and buildings present around the vehicle 600. For example, the vehicle 600 is unlikely to enter a road beyond a point where a road sign "No Entry for Vehicles" is installed. Therefore, the processing device 100 estimates that the probability that the vehicle 600 will be present on a road beyond a point where a road sign "No Entry for Vehicles" is installed is low. The processing device 100 may be configured to use a learning model trained by machine learning to estimate the possible trajectories and possible positions of the vehicle 600 and to estimate the probability of the vehicle 600 being present at each position within the area 20.

[0040] The processing device 100 calculates, as predicted moving object information, the position where the vehicle 600 is estimated to be at a predetermined time, based on the possible trajectory and possible positions of the vehicle 600 and the probability that the vehicle 600 will be present at each position within the area 20. The method by which the processing device 100 calculates the predicted moving object information for each moving object 800 is not limited to the above method. The processing device 100 may calculate the predicted moving object information for each moving object 800 using a known prediction model.

[0041] After the processing device 100 calculates the predicted moving body information for each moving body 800, the process proceeds to step S12. In step S12, the processing device 100 acquires test moving object information that the communication device 300 acquired at a time different from the moving object information used to calculate the predicted moving object information in the area 20 and stored in the third memory circuit 302. In the first embodiment, the processing device 100 acquires, as the test moving object information, from the communication device 300, first moving object information that is moving object information that the communication device 300 acquired at a time earlier than the moving object information used to calculate the predicted moving object information. After the processing device 100 acquires the first moving object information for each moving object 800 from the third memory circuit 302 of the communication device 300, the processing proceeds to step S13.

[0042] In step S13, the processing device 100 of the information processing system 10 calculates test prediction mobile object information based on the test mobile object information. The test prediction mobile object information is information that indicates the position of the mobile object 800 at the same time as the predicted mobile object information, calculated by the processing device 100 of the information processing system 10 based on the test mobile object information. In the first embodiment, the processing device 100 calculates the first test prediction mobile object information using the first mobile object information acquired from the communication device 300. After the processing device 100 calculates the first test prediction mobile object information for each mobile object 800, the processing proceeds to step S14.

[0043] <Regarding the magnitude of the positional deviation between the predicted center CP and the test predicted center CPT> In step S14, the processing device 100 calculates the magnitude of the positional deviation between the prediction center CP, which is the position of the moving body 800 in the predicted moving body information, and the test prediction center CPT, which is the position of the moving body 800 in the first test predicted moving body information.

[0044] The first memory circuit 102 of the processing device 100 stores data on the dimensions of the moving body 800 for each type of moving body 800. The first processing circuit 101 of the processing device 100 calculates a predicted center CP based on the predicted moving body information and the data on the dimensions of the moving body 800 stored in the first memory circuit 102. The first processing circuit 101 of the processing device 100 calculates a test predicted center CPT based on the first test predicted moving body information and the data on the dimensions of the moving body 800 stored in the first memory circuit 102.

[0045] FIG. 5 is a schematic diagram showing a prediction center CP and a test prediction center CPT. A first circle 31 is a circle with a radius of 0.1 meters from the prediction center CP. A second circle 32 is a circle with a radius of 0.2 meters from the prediction center CP. A third circle 33 is a circle with a radius of 0.3 meters from the prediction center CP. The first test prediction center CPT_1 shown in FIG. 5 is a test prediction center CPT that exists within a radius of 0.1 meters from the prediction center CP. The second test prediction center CPT_2 is a test prediction center CPT that exists outside a radius of 0.1 meters but within a radius of 0.2 meters from the prediction center CP. The third test prediction center CPT_3 is a test prediction center CPT that exists outside a radius of 0.2 meters but within a radius of 0.3 meters from the prediction center CP. After the processing device 100 calculates the magnitude of the positional deviation between the prediction center CP and the test prediction center CPT for each moving object 800, the process proceeds to step S15.

[0046] <Calculation of similarity for each moving object 800> In step S15, the processing device 100 calculates the similarity between the predicted moving object information and the first test predicted moving object information based on the magnitude of the positional deviation between the prediction center CP and the test prediction center CPT. The similarity between the predicted moving object information and the first test predicted moving object information is an index value indicating the degree of similarity between the predicted moving object information and the first test predicted moving object information. The processing device 100 evaluates the correspondence between the predicted moving object information and the first test predicted moving object information by calculating the index value indicating the degree of similarity between the predicted moving object information and the first test predicted moving object information. In the information processing system 10 of the first embodiment, the index value is the above-mentioned similarity and a similarity rate, which will be described later.

[0047] As shown in FIG. 6 , when the position of the test prediction center CPT is within a radius of 0.1 meters from the position of the prediction center CP, the processing device 100 calculates the similarity between the predicted moving object information and the first test predicted moving object information to be 100. When the position of the test prediction center CPT is outside a radius of 0.1 meters but within a radius of 0.2 meters from the position of the prediction center CP, the processing device 100 calculates the similarity between the predicted moving object information and the first test predicted moving object information to be 90. When the position of the test prediction center CPT is outside a radius of 0.2 meters but within a radius of 0.3 meters from the position of the prediction center CP, the processing device 100 calculates the similarity between the predicted moving object information and the first test predicted moving object information to be 80. When the position of the test prediction center CPT is outside a radius of 0.3 meters but within a radius of 0.4 meters from the position of the prediction center CP, the processing device 100 calculates the similarity between the predicted moving object information and the first test predicted moving object information to be 70. When the position of the test prediction center CPT is outside a radius of 0.4 meters from the position of the prediction center CP, the processing device 100 calculates the similarity between the predicted moving object information and the first test predicted moving object information as 60.

[0048] As shown in FIG. 5, the first test prediction center CPT_1 is located within a radius of 0.1 meters from the prediction center CP. Therefore, as shown in FIG. 6, the similarity between the predicted moving object information and the first test predicted moving object information used to calculate the first test prediction center CPT_1 is calculated to be 100. The second test prediction center CPT_2 is located outside a radius of 0.1 meters from the prediction center CP but within a radius of 0.2 meters. Therefore, as shown in FIG. 6, the similarity between the predicted moving object information and the first test predicted moving object information used to calculate the second test prediction center CPT_2 is calculated to be 90. The third test prediction center CPT_3 is located outside a radius of 0.2 meters from the prediction center CP but within a radius of 0.3 meters. Therefore, as shown in FIG. 6, the similarity between the predicted moving object information and the first test predicted moving object information used to calculate the third test prediction center CPT_3 is calculated to be 80.

[0049] The magnitude of the deviation between the position of the moving object 800 in the predicted moving object information and the position of the moving object 800 in the test predicted moving object information is not limited to the magnitude of the deviation between the position of the prediction center CP and the test prediction center CPT. For example, the processing device 100 may calculate the magnitude of the deviation between the position of the predicted moving object information and the first test predicted moving object information for a characteristic position of each moving object 800, such as an emblem on the vehicle 600. After the processing device 100 calculates the similarity for each moving object 800 present in the area 20, the process proceeds to step S16.

[0050] <Calculation of similarity rate in Area 20> In step S16, the processing device 100 calculates a similarity rate for each area 20. The similarity rate is the proportion of moving bodies 800 that exist in the area 20, whose similarity rate is equal to or greater than a predetermined value. The similarity rate is an index value that indicates the degree of similarity. The processing device 100 can set the predetermined value to any value as long as it can appropriately determine the update period of the predicted moving body information for the moving bodies 800 for each area 20. For example, the processing device 100 may set "80" as the predetermined value. In this case, the processing device 100 determines the proportion of moving bodies 800 that exist in the area 20, whose similarity rate is equal to or greater than 80, as the similarity rate for that area 20.

[0051] In FIG. 4, moving bodies 800 with a similarity level less than 80 are represented by black circles, and moving bodies 800 with a similarity level of 80 or more are represented by white circles. A first moving body 801, a second moving body 802, a third moving body 803, and a fourth moving body 804 exist in the first area 21. The first moving body 801, the second moving body 802, the third moving body 803, and the fourth moving body 804 are moving bodies 800 with a similarity level less than 80. Therefore, the similarity rate in the first area 21 is 0%. A fifth moving body 805, a sixth moving body 806, a seventh moving body 807, and an eighth moving body 808 exist in the second area 22. The fifth moving body 805, the sixth moving body 806, and the seventh moving body 807 are moving bodies 800 with a similarity level of 80 or more. The eighth moving body 808 is a moving body 800 with a similarity level less than 80. That is, the second area 22 is an area 20 in which the similarity of three of the four moving bodies 800 is 80 or higher. Therefore, the similarity rate in the second area 22 is 75 percent. The third area 23 contains the ninth moving body 809 and the tenth moving body 810. The ninth moving body 809 and the tenth moving body 810 are moving bodies 800 with a similarity rate of 80 or higher. Therefore, the similarity rate in the third area 23 is 100 percent. The fourth area 24 contains the eleventh moving body 811, the twelfth moving body 812, the thirteenth moving body 813, and the fourteenth moving body 814. The eleventh moving body 811 and the twelfth moving body 812 are moving bodies 800 with a similarity rate of 80 or higher. The thirteenth moving body 813 and the fourteenth moving body 814 are moving bodies 800 with a similarity rate of less than 80. That is, the fourth area 24 is the area 20 where the similarity between two of the four moving bodies 800 is 80 or more. Therefore, the similarity rate of the fourth area 24 is 50%. After the processing device 100 calculates the similarity rate for each area 20, the process proceeds to step S17.

[0052] <Determining the update period for predicted moving object information> In step S17, the processing device 100 determines the update period of the predicted mobile object information for the mobile object 800 existing in each area 20 based on the similarity rate for each area 20. In the first embodiment, the information processing system 10 extends the update period of the predicted mobile object information for the mobile object 800 existing in the area 20 where the similarity rate is 80 percent or more. On the other hand, the information processing system 10 does not change the update period of the predicted mobile object information for the mobile object 800 existing in the area 20 where the similarity rate is less than 80 percent.

[0053] As shown in FIG. 7, the similarity rate in the first area 21 is 0 percent. Therefore, the processing device 100 does not change the update period of the predicted moving object information for the moving object 800 existing in the first area 21. That is, the processing device 100 does not change the update period of the predicted moving object information for the first moving object 801, the second moving object 802, the third moving object 803, and the fourth moving object 804 existing in the first area 21 shown in FIG. 6. As shown in FIG. 7, the similarity rate in the second area 22 is 75 percent. Therefore, the processing device 100 does not change the update period of the predicted moving object information for the moving object 800 in the second area 22. That is, the processing device 100 does not change the update period of the predicted moving object information for the fifth moving object 805, the sixth moving object 806, the seventh moving object 807, and the eighth moving object 808 shown in FIG. 6. The similarity rate in the third area 23 is 100 percent. Therefore, the processing device 100 extends the update period of the predicted moving object information of the moving object 800 existing in the third area 23. That is, the processing device 100 extends the update period of the predicted moving object information of the ninth moving object 809 and the tenth moving object 810. The similarity rate of the fourth area 24 is 50 percent. Therefore, the processing device 100 does not change the update period of the predicted moving object information of the moving object 800 existing in the fourth area 24. That is, the processing device 100 does not change the update period of the predicted moving object information of the eleventh moving object 811, the twelfth moving object 812, the thirteenth moving object 813, and the fourteenth moving object 814 shown in FIG. 6. After the processing device 100 executes the process of step S17, the processing device 100 ends this series of processes.

[0054] <Operation of the First Embodiment> The longer the update period for updating the predicted moving object information, the lower the processing load on the information processing system 10. On the other hand, if the update period for updating the predicted moving object information is long, there is a risk that the discrepancy between the position of the moving object 800 in the real world and the position of the moving object 800 in the predicted moving object information will increase. Furthermore, when predicting the position of the moving object 800 beyond the present, there is a risk that the accuracy of the position of the moving object 800 in the predicted moving object information will decrease. Therefore, the information processing system 10 determines the update period for updating the predicted moving object information while evaluating the correspondence with the predicted moving object information calculated using moving object information acquired at different times.

[0055] <Effects of the first embodiment> (1-1) The information processing system 10 can reduce the processing load for updating the predicted moving object information while calculating the predicted moving object information with high accuracy.

[0056] (1-2) The processing device 100 of the information processing system 10 evaluates the correspondence between the predicted moving object information and the first test predicted moving object information by calculating a similarity, which is an index value indicating the degree of similarity between the predicted moving object information and the first test predicted moving object information. This allows the information processing system 10 to calculate highly accurate predicted moving object information while reducing the processing load for updating the predicted moving object information.

[0057] (1-3) The processing device 100 of the information processing system 10 calculates the similarity between the prediction center CP and the test prediction center CPT for each moving object 800 present in the predetermined area 20. Then, based on the similarities among the multiple moving objects 800 present in the predetermined area, the processing device 100 calculates a similarity rate, which is the proportion of moving objects 800 in the predetermined area 20 whose similarity is equal to or greater than a predetermined value. The similarity rate is an index value indicating the degree of similarity. The processing device 100 determines an update period for the predicted moving object information for each predetermined area 20 based on the similarity rate. This allows the information processing system 10 to calculate highly accurate predicted moving object information for each area 20 while reducing the processing load for updating the predicted moving object information.

[0058] (1-4) The processing device 100 calculates the similarity between the predicted mobile object information and first test predicted mobile object information, which indicates information about the location of the mobile object 800 at the same time as the predicted mobile object information and is calculated from first mobile object information acquired by the communication device 300 at a time before the time when the mobile object information used to calculate the predicted mobile object information was acquired. If the similarity between the predicted mobile object information and the first test predicted mobile object information is a high numerical value, the first test predicted mobile object information can also calculate the location of the mobile object 800 with the same accuracy as the predicted mobile object information. In this case, even if the update period for updating the predicted mobile object information is extended, the processing device 100 can calculate predicted mobile object information with the same accuracy as the current one. Therefore, the processing device 100 of the above-mentioned information processing system 10 extends the update period for the predicted mobile object information for the mobile object 800 within the area 20 based on the similarity rate being equal to or greater than a predetermined numerical value. As a result, the information processing system 10 can reduce the processing load on the processing device 100 by extending the update period while maintaining the accuracy of the predicted mobile object information.

[0059] (1-5) The information processing method executed by the information processing system 10 includes steps (steps S15 and S16) in which the processing device 100 evaluates a correspondence between the position of the moving object 800 in the predicted moving object information and the moving object 800 at the same time as the predicted moving object information, calculated from moving object information acquired by the communication device 300 at a time different from the time at which the moving object information used to calculate the predicted moving object information was acquired. The information processing method executed by the information processing system 10 also includes a step (step S17) of determining a default update period based on the evaluation of the correspondence. By executing this information processing method, the information processing system 10 determines an update period for updating the predicted moving object information while evaluating the correspondence with the predicted moving object information calculated using moving object information acquired at a different time. By executing this information processing method, the information processing system 10 can calculate highly accurate predicted moving object information while reducing the processing load for updating the predicted moving object information.

[0060] (1-6) The first storage circuit 102 of the processing device 100 of the information processing system 10 stores an information processing program that causes the first processing circuit 101 of the processing device 100 to execute processing. The information processing program causes the processing device 100 to evaluate a correspondence between the position of the moving object 800 in the predicted moving object information and the position of the moving object 800 at the same time as the predicted moving object information, calculated from moving object information acquired by the communication device at a time different from the time at which the moving object information used to calculate the predicted moving object information was acquired. The information processing program causes the first processing circuit 101 of the processing device 100 to determine a default update period based on the evaluation of the correspondence. The information processing program causes the information processing system 10 to determine an update period for updating the predicted moving object information while evaluating the correspondence with the predicted moving object information calculated using moving object information acquired at a different time. This allows the information processing system 10 to calculate highly accurate predicted moving object information while reducing the processing load for updating the predicted moving object information.

[0061] <Modification of the first embodiment> The first embodiment can be modified as follows: This embodiment and the following modifications can be combined and implemented within the scope of technical compatibility.

[0062] The processing device 100 of the information processing system 10 may evaluate the correspondence without calculating an index value when determining the update period for updating the predicted moving object information. The processing device 100 then determines the update period based on the evaluation of the correspondence. For example, the processing device 100 may evaluate the correspondence between the prediction center CP, which is the position of the moving object 800 in the predicted moving object information, and the test prediction center CPT, which is the position of the moving object 800 in the test predicted moving object information. In this case, the processing device 100 evaluates the magnitude of the positional deviation between the prediction center CP and the test prediction center CPT to evaluate the correspondence. If the magnitude of the positional deviation is within a predetermined criterion, the processing device 100 evaluates that there is a correspondence between the prediction center CP and the test prediction center CPT. If the magnitude of the positional deviation is greater than the predetermined criterion, the processing device 100 evaluates that there is no correspondence between the prediction center CP and the test prediction center CPT. If the processing device 100 evaluates that there is a correspondence, the processing device 100 extends the update period for updating the predicted moving object information. On the other hand, if the processing device 100 determines that there is no correspondence, it does not change the update period for updating the predicted moving object information. If the processing device 100 determines that there is no correspondence, it may shorten the update period for the predicted moving object information. Even in the above embodiment, the information processing system 10 can reduce the processing load for updating the predicted moving object information while calculating highly accurate predicted moving object information.

[0063] The mobile object information used by the processing device 100 of the information processing system 10 to calculate the test prediction mobile object information is not limited to the first mobile object information acquired by the communication device 300 at a time before the time when the mobile object information used to calculate the prediction mobile object information was acquired. In step S12 shown in FIG. 3, the processing device 100 may acquire, as the test mobile object information, second mobile object information, which is mobile object information acquired by the communication device 300 at a time after the time when the mobile object information used to calculate the prediction mobile object information was acquired. In this case, in step S13 shown in FIG. 3, the processing device 100 calculates the test prediction mobile object information using the second mobile object information. The test prediction mobile object information calculated by the processing device 100 using the second mobile object information is defined as the second test prediction mobile object information. In step S14 shown in FIG. 3, the processing device 100 may calculate the magnitude of the positional deviation between the prediction center CP and the test prediction center CPT in the second test prediction mobile object information. Then, in step S15 shown in FIG. 3, the processing device 100 may calculate the similarity between the predicted moving object information and the second test predicted moving object information based on the magnitude of the positional deviation between the prediction center CP and the test prediction center CPT in the second test predicted moving object information. The second test predicted moving object information, which is calculated based on the second moving object information, which is newer moving object information, is estimated to be able to calculate the position of the moving object 800 with higher accuracy than the predicted moving object information. Therefore, when the similarity between the predicted moving object information and the second test predicted moving object information is high, the predicted moving object information is able to calculate the position of the moving object 800 with sufficiently high accuracy. When the predicted moving object information is able to calculate the position of the moving object 800 with sufficiently high accuracy, it is estimated that the predicted moving object information can calculate the position of the moving object 800 with the required accuracy even if the update period of the predicted moving object information is extended. 3, the processing device 100 may calculate the similarity rate for each area 20 on the condition that the similarity between the predicted moving object information and the second test predicted moving object information is equal to or greater than a predetermined value. This allows the information processing system 10 to reduce the processing load on the processing device 100 while maintaining the accuracy of the predicted moving object information.

[0064] When the predicted moving object information is information predicting the current position of the moving object 800, the latest moving object information is information that is closest to the current real-world situation that was being predicted. Therefore, the position of the moving object 800 in the latest moving object information is the most suitable comparison target for verifying the accuracy of the predicted moving object information predicting the current position of the moving object 800, among the information that the information processing system 10 is able to grasp. Therefore, in step S12 shown in FIG. 3, the processing device 100 may acquire the position of the moving object 800 in the latest moving object information as test moving object information. The processing device 100 may calculate the position of the center C of the moving object 800 in the latest moving object information based on the latest moving object information and dimensional data of the moving object 800. The processing device 100 may not calculate the test predicted moving object information in step S13 shown in FIG. 3. The processing device 100 may calculate the magnitude of the positional deviation between the predicted center CP and the position of the center C of the moving object 800 in the latest moving object information acquired by the communication device 300 in step S14 shown in FIG. 3. 3, the processing device 100 may calculate the similarity between the predicted moving object information and the latest moving object information from the magnitude of the positional deviation between the predicted center CP and the position of the center C of the moving object 800 in the latest moving object information acquired by the communication device 300. The processing device 100 determines the update period of the predicted moving object information based on the calculated similarity. This allows the information processing system 10 to calculate predicted moving object information that accurately reproduces the position of the moving object 800 in the real world, while reducing the processing load imposed by the processing device 100 for updating the predicted moving object information.

[0065] If the similarity rate in the predetermined area 20 is less than a predetermined value, the accuracy of the predicted moving object information for the moving object 800 present in the predetermined area 20 may be low. Therefore, the processing device 100 of the information processing system 10 may shorten the update cycle of the predicted moving object information when the similarity rate in the predetermined area 20 is less than the predetermined value. This allows the information processing system 10 to achieve both a reduction in processing load and maintaining the accuracy of the predicted moving object information.

[0066] The predetermined numerical value that serves as the threshold for determining whether or not to shorten the update period may be a value that is smaller than the predetermined numerical value that serves as the threshold for determining whether or not to shorten the update period.

[0067] (Second embodiment) Next, a second embodiment will be described with reference to Fig. 4, Fig. 6, and Fig. 8. The second embodiment will be described mainly focusing on differences from the first embodiment. In the second embodiment, the information processing system 10 determines an update period for the predicted moving body information for each moving body 800.

[0068] The possible moving speed of the moving body 800 varies depending on the type of the moving body 800. For example, the moving body 800 includes an object such as the vehicle 600 that has a wide range of moving speeds and can move at high speeds. For example, the moving body 800 includes an object such as the pedestrian 700 that is assumed to move at a slower speed than the vehicle 600. Therefore, the information processing system 10 sets the initial value of the update period to a different value for each type of moving body 800. For example, the information processing system 10 sets the update period of the predicted moving body information for the vehicle 600 to a shorter time than the update period of the predicted moving body information for the pedestrian 700.

[0069] <Acquisition of moving object information and calculation of predicted moving object information> 8 is a flowchart showing the flow of a series of processes executed by the information processing system 10 in the second embodiment. The information processing system 10 repeatedly executes this series of processes. As shown in FIG. 8, when this series of processes starts, the information processing system 10 first acquires, in step S20, mobile object information of the mobile object 800 whose predicted mobile object information is to be updated via the third communication circuit 303 of the communication device 300. After the communication device 300 acquires the mobile object information within the area 20 from the sensor, the process proceeds to step S21.

[0070] In step S21, the information processing system 10 calculates the predicted moving body information for each moving body 800. After the information processing system 10 calculates the predicted moving body information for each moving body 800, the process proceeds to step S22.

[0071] <Getting test mobile information> In step S22, the information processing system 10 acquires test mobile object information in the area 20. For example, the test mobile object information acquired by the information processing system 10 is first mobile object information. In another aspect, the test mobile object information acquired by the information processing system 10 may be second mobile object information. After the information processing system 10 acquires the test mobile object information for each mobile object 800, the process proceeds to step S23.

[0072] <Calculation of test predicted moving object information> In step S23, the processing device 100 of the information processing system 10 calculates test prediction mobile object information based on the test mobile object information. After the information processing system 10 calculates the test prediction mobile object information for each mobile object 800, the process proceeds to step S24.

[0073] <Calculating the magnitude of positional deviation> In step S24, the processing device 100 calculates the magnitude of the positional deviation between the prediction center CP, which is the position of the moving body 800 in the predicted moving body information, and the test prediction center CPT, which is the position of the moving body 800 in the test predicted moving body information.

[0074] After the information processing system 10 calculates the magnitude of the positional deviation between the prediction center CP and the test prediction center CPT, the process proceeds to step S25. <Calculation of similarity> In step S25, the information processing system 10 calculates the similarity between the predicted moving body information and the test predicted moving body information for each moving body 800 based on the magnitude of the positional deviation between the prediction center CP and the test prediction center CPT for each moving body 800. The method for calculating the similarity is the same as the method described with reference to Fig. 6. After the processing device 100 calculates the similarity for each moving body 800 present in the area 20, the process proceeds to step S26.

[0075] <Determining the update period for predicted moving object information> In step S26, the processing device 100 determines the update period of the predicted moving body information for each moving body 800 based on the similarity calculated for each moving body 800. The processing device 100 extends the update period of the predicted moving body information for moving bodies 800 whose similarity is 80 or more. The processing device 100 does not change the update period of the predicted moving body information for moving bodies 800 whose similarity is less than 80.

[0076] In the area 20 shown in Figure 4, the first moving body 801, the second moving body 802, the third moving body 803, the fourth moving body 804, the eighth moving body 808, the thirteenth moving body 813, and the fourteenth moving body 814 are moving bodies 800 with a similarity of less than 80. The processing device 100 does not change the update period of the predicted moving body information for the first moving body 801, the second moving body 802, the third moving body 803, the fourth moving body 804, the eighth moving body 808, the thirteenth moving body 813, and the fourteenth moving body 814. In the area 20 shown in Figure 4, the fifth moving body 805, the sixth moving body 806, the seventh moving body 807, the ninth moving body 809, the tenth moving body 810, the eleventh moving body 811, and the twelfth moving body 812 are moving bodies 800 with a similarity of 80 or more. The processing device 100 extends the update period of the predicted moving body information for the fifth moving body 805, the sixth moving body 806, the seventh moving body 807, the ninth moving body 809, the tenth moving body 810, the eleventh moving body 811 and the twelfth moving body 812.

[0077] After the processing device 100 executes the process of step S26, the processing device 100 ends this series of processes. <Operation of the Second Embodiment> The moving speed of the moving body 800 in the real world differs for each moving body 800. For example, the vehicles 600 include vehicles 600 moving at high speed and vehicles 600 that are stopped. Therefore, the processing device 100 determines an update period of the predicted moving body information for each moving body 800.

[0078] <Effects of the second embodiment> (2-1) The information processing system 10 can calculate highly accurate predicted moving body information for each moving body 800, while reducing the processing load for updating the predicted moving body information.

[0079] (2-2) The processing device 100 sets an initial value of the update period of the predicted moving body information for each type of moving body 800. This allows the information processing system 10 to determine the update period more precisely and reduce the processing load compared to when the initial value of the update period is set uniformly regardless of the type of moving body 800.

[0080] <Modification of the second embodiment> The second embodiment described above can be modified as follows: The second embodiment and the following modifications can be combined and implemented within the scope of technical compatibility.

[0081] If the similarity for a moving object 800 is less than a predetermined value, the accuracy of the predicted moving object information for that moving object 800 is low. Therefore, the processing device 100 of the information processing system 10 may shorten the update cycle of the predicted moving object information for a moving object 800 whose similarity is less than a predetermined value. This allows the information processing system 10 to achieve both a reduction in processing load and maintaining the accuracy of the predicted moving object information.

[0082] In the second embodiment, the information processing system 10 determines the update period of the predicted mobile object information for each mobile object 800 based on the similarity between the predicted mobile object information and the first test predicted mobile object information. In this case, the information processing system 10 may store a first time, which is the time when the mobile object information used to calculate the predicted mobile object information was acquired, and a second time when the first mobile object information used to calculate the first test predicted mobile object information was acquired. When the similarity is equal to or greater than a predetermined value, the information processing system 10 can accurately reproduce the mobile object information based on older mobile object information as the interval between the first time and the second time increases. When the similarity between the predicted mobile object information of a mobile object 800 and the first test predicted mobile object information is equal to or greater than a predetermined value, the information processing system may change the update period of the predicted mobile object information of the mobile object 800 to a longer update period as the interval between the first time and the second time increases. This allows the information processing system 10 to significantly reduce the processing load while suppressing a decrease in accuracy due to a change in the update period.

[0083] If the communication device 300 can continue to update the predicted moving object information at an appropriate update period, it is not necessary to acquire the type of each moving object 800 as moving object information. <Other change examples> Other elements that can be modified in common to the above embodiments include the following: The following modifications can be implemented in combination with each other to the extent that they are not technically inconsistent.

[0084] The processing device 100 of the information processing system 10 may acquire the test mobile object information from a source other than the third storage circuit 302 of the communication device 300. For example, the processing device 100 may be configured to store the test mobile object information in the first storage circuit 102 of the processing device 100. In this case, the first processing circuit 101 of the processing device 100 acquires the test mobile object information from the first storage circuit 102. [Explanation of symbols]

[0085] 10...information processing system, 20...area, 21...first area, 22...second area, 23...third area, 24...fourth area, 31...first circle, 32...second circle, 33...third circle, 100...processing device, 101...first processing circuit, 102...first memory circuit, 103...first communication circuit, 200...storage device, 201...second processing circuit, 202...second memory circuit, 203...second communication circuit, 300...communication device, 301...third processing circuit, 302...third memory circuit, 303...third communication circuit, 400...external communication line network, 500...information processing terminal, 600...vehicle, 601...first vehicle, 602...second vehicle, 610...on-vehicle sensor, 611...first on-vehicle sensor, 612...second vehicle-mounted sensor, 700...pedestrian, 800...moving object, 801...first moving object, 802...second moving object, 803...third moving object, 804...fourth moving object, 805...fifth moving object, 806...sixth moving object, 807...seventh moving object, 808...eighth moving object, 809...ninth moving object, 810...tenth moving object, 811...eleventh moving object, 812...twelfth moving object, 813...thirteenth moving object, 814...fourteenth moving object, 900...road sensor, 910...traffic light, 920...road camera, C...center, CP...prediction center, CPT...test prediction center, CPT_1...first test prediction center, CPT_2...second test prediction center, CPT_3...third test prediction center

Claims

1. a processing device and a communication device, the communication device sequentially acquires moving object information that is information indicating the position of a moving object existing in the real world; the processing device calculates, based on the moving object information successively acquired by the communication device, predicted moving object information which is information indicating a position of the moving object at a time after the time when the moving object information is acquired, at a predetermined update period; the processing device evaluates a correspondence relationship between a position of the moving object in the predicted moving object information and a position of the moving object at the same time as the predicted moving object information, the position being calculated from moving object information acquired by the communication device at a time different from the time at which the moving object information used to calculate the predicted moving object information was acquired; determining the predetermined update period based on the evaluation; Information processing system.

2. To evaluate the correspondence, calculating an index value indicating a degree of similarity between the position of the moving object in the predicted moving object information and the position of the moving object at the same time as the predicted moving object information, the index value being calculated from moving object information acquired by the communication device at a time different from the time at which the moving object information used to calculate the predicted moving object information was acquired; determining the predetermined update period based on the index value; The information processing system according to claim 1 .

3. the processing device calculates the predicted moving object information for each predetermined area at a predetermined update period; the processing device calculates the index value indicating a degree of similarity between positions of the plurality of moving objects present within the predetermined area in the predicted moving object information and positions of the plurality of moving objects present within the predetermined area at the same time as the predicted moving object information, calculated from moving object information acquired by the communication device at a time different from the time at which the moving object information used to calculate the predicted moving object information was acquired; determining the predetermined update period in the predetermined area based on the index value; The information processing system according to claim 2 .

4. the processing device calculates, for each of the moving objects, the index value indicating the degree of similarity between a position of the moving object in the predicted moving object information and a position of the moving object at the same time as the predicted moving object information, the position being calculated from moving object information acquired by the communication device at a time different from the time at which the moving object information used to calculate the predicted moving object information was acquired; The default update period is determined for each of the moving objects based on the index value. The information processing system according to claim 2 .

5. the communication device acquires a type of each of the mobile objects as the mobile object information; The processing device sets an initial value of the update period for each type of the moving body. The information processing system according to claim 4 .

6. calculate the index value indicating the degree of similarity between the predicted moving object information and first test predicted moving object information, which indicates information about the location of the moving object at the same time as the predicted moving object information, calculated from first moving object information acquired by the communication device at a time earlier than the time when the moving object information used to calculate the predicted moving object information was acquired; If the index value is equal to or greater than a predetermined value, the predetermined update period is extended. The information processing system according to claim 2 .

7. calculate the index value indicating the degree of similarity between the predicted moving object information and second test predicted moving object information, which indicates information about the location of the moving object at the same time as the predicted moving object information, calculated from second moving object information acquired by the communication device at a time later than the time when the moving object information used to calculate the predicted moving object information was acquired; If the index value is equal to or greater than a predetermined value, the predetermined update period is extended. The information processing system according to claim 2 .

8. the predicted moving object information is information predicting a current position of the moving object, calculating the index value indicating the degree of similarity between the predicted moving object information and the latest moving object information acquired by the communication device; If the index value is equal to or greater than the predetermined value, the predetermined update period is extended. The information processing system according to claim 7 .

9. The processing device shortens the default update period when the index value is less than the default value. The information processing system according to any one of claims 6 to 8.

10. a first time that is a time that the moving object information used to calculate the predicted moving object information is acquired; The default update period is changed to a longer update period as the interval between the first test predicted moving object information and the second time at which the moving object information was acquired increases. The information processing system according to claim 6.

11. An information processing method executed in an information processing system including: a communication device that sequentially acquires mobile object information, which is information indicating the position of a mobile object existing in the real world; and a processing device that calculates, at a predetermined update period, predicted mobile object information, which is information indicating the position of the mobile object at a time after the time when the mobile object information was acquired, based on the mobile object information sequentially acquired by the communication device, a step in which the processing device evaluates a correspondence relationship between a position of the moving object in the predicted moving object information and a position of the moving object at the same time as the predicted moving object information, the position being calculated from moving object information acquired by the communication device at a time different from the time at which the moving object information used to calculate the predicted moving object information was acquired; determining the predetermined update period based on the evaluation. Information processing methods.

12. An information processing program executed by a processing device of an information processing system including: a communication device that sequentially acquires mobile object information, which is information indicating the position of a mobile object existing in the real world; and a processing device that calculates, at a predetermined update period, predicted mobile object information, which is information indicating the position of the mobile object at a time after the time when the mobile object information was acquired, based on the mobile object information sequentially acquired by the communication device, Evaluating a correspondence between a position of the moving object in the predicted moving object information and a position of the moving object at the same time as the predicted moving object information, calculated from moving object information acquired by the communication device at a time different from the time at which the moving object information used to calculate the predicted moving object information was acquired; determining the predetermined update period based on the evaluation; and causing the processing device to execute Information processing program.

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