WO2023139706A1 - Processing device - Google Patents

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Publication number
WO2023139706A1
WO2023139706A1 PCT/JP2022/001838 JP2022001838W WO2023139706A1 WO 2023139706 A1 WO2023139706 A1 WO 2023139706A1 JP 2022001838 W JP2022001838 W JP 2022001838W WO 2023139706 A1 WO2023139706 A1 WO 2023139706A1
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processing
trajectory
trajectories
searching
vectorization
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PCT/JP2022/001838
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French (fr)
Japanese (ja)
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裕太 井手口
貴志 竹内
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日本電気株式会社
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Priority to PCT/JP2022/001838 priority Critical patent/WO2023139706A1/en
Publication of WO2023139706A1 publication Critical patent/WO2023139706A1/en

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    • GPHYSICS
    • G01MEASURING; TESTING
    • G01CMEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
    • G01C21/00Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00
    • G01C21/26Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 specially adapted for navigation in a road network
    • G01C21/34Route searching; Route guidance
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06FELECTRIC DIGITAL DATA PROCESSING
    • G06F17/00Digital computing or data processing equipment or methods, specially adapted for specific functions
    • G06F17/10Complex mathematical operations
    • G06F17/16Matrix or vector computation, e.g. matrix-matrix or matrix-vector multiplication, matrix factorization
    • GPHYSICS
    • G08SIGNALLING
    • G08GTRAFFIC CONTROL SYSTEMS
    • G08G1/00Traffic control systems for road vehicles

Definitions

  • the present invention relates to processing apparatuses, processing methods, and recording media.
  • the trajectories of moving objects such as cars, ships, airplanes, and unmanned guided vehicles may be determined.
  • Non-Patent Document 1 and Non-Patent Document 2 describe techniques for determining the trajectory of a moving object such as a ship's trajectory.
  • the techniques described in Non-Patent Literature 1 and Non-Patent Literature 2 after classifying the track hypotheses, global hypotheses are generated, and track hypotheses are selected based on the generated global hypotheses.
  • Non-Patent Document 3 for example, describes a method for generating global hypotheses.
  • Patent Document 1 describes an example of technology used to detect and track an object based on sensor data.
  • Non-Patent Documents 1 to 3 When generating global hypotheses as described in Non-Patent Documents 1 to 3, trajectories and trajectories that can be common to the trajectory are sometimes searched.
  • trajectories and trajectories that can be common to the trajectory are sometimes searched.
  • the number of moving bodies to be tracked increases, the number of necessary processes increases by the number of combinations. As a result, the processing time has increased.
  • the tracking of moving objects as described above may require processing in real time, so it is desirable that the processing be as fast as possible.
  • combinatorial processing such as searching for common possible trajectories, is complicated. Therefore, the efficiency of parallelization was poor and speeding up was difficult.
  • an object of the present invention is to provide a processing device, a processing method, and a recording medium that can solve the problem that it is difficult to speed up combination processing such as searching for sharable trajectories.
  • an acquisition unit that acquires information indicating a trajectory, which is a route traveled by the mobile object, that is specified based on a sensing result of the mobile object;
  • a vectorization unit that vectorizes a process of searching for a combination of trajectories acquired by the acquisition unit and causes a vector processing unit to execute the process; It has a configuration of
  • a processing method that is another aspect of the present disclosure includes: The information processing device Acquiring information indicating a trajectory, which is a route traveled by the moving body, which is specified based on the sensing result of the moving body; A configuration is adopted in which the process of searching for combinations of acquired trajectories is vectorized and executed by the vector processing unit.
  • a recording medium that is another aspect of the present disclosure includes: information processing equipment, Acquiring information indicating a trajectory, which is a route traveled by the moving body, which is specified based on the sensing result of the moving body;
  • a computer-readable recording medium recording a program for realizing a process of vectorizing a process of searching for a combination of acquired trajectories and causing a vector processing unit to execute the process.
  • each configuration as described above it is possible to provide a processing device, a processing method, and a recording medium capable of speeding up combination processing such as searching for sharable trajectories.
  • FIG. 10 is a diagram showing an example of determining a trajectory and a common possible trajectory in the first stage; It is a figure which shows an example of vectorization.
  • FIG. 10 is a diagram showing another example of vectorization;
  • FIG. 10 is a diagram showing another example of vectorization;
  • It is a figure which shows an example of a determination condition.
  • FIG. 4 is a diagram showing a detailed example of vectorization in the first method;
  • FIG. 4 is a diagram showing a detailed example of vectorization in the first method
  • FIG. 10 is a diagram showing a detailed example of vectorization in the second method
  • FIG. 10 is a diagram showing a detailed example of vectorization in the third method
  • It is a flowchart which shows the operation example of a processing apparatus.
  • FIG. 11 is a block diagram showing a configuration example of a processing device according to a second embodiment of the present disclosure
  • FIG. 1 and 2 are diagrams for explaining the outline of the present invention.
  • FIG. 3 is a block diagram showing a configuration example of the processing device 100.
  • FIG. 4 is a diagram showing an example of determination of a trajectory and a common possible trajectory in the first stage.
  • 5 to 7 are diagrams showing an example of vectorization.
  • FIG. 8 is a diagram showing an example of determination conditions.
  • 9 and 10 are diagrams showing detailed examples of vectorization in the first method.
  • FIG. 11 is a diagram showing a detailed example of vectorization in the second method.
  • FIG. 12 is a diagram showing a detailed example of vectorization in the third method.
  • FIG. 13 is a flow chart showing an operation example of the processing device 100 .
  • a processing device 100 that is an information processing device that searches for a combination of simultaneously selectable trajectories will be described.
  • FIG. 1 it is assumed that three moving objects are observed in one frame (frame 1) and three moving objects are observed in the next frame (frame 2) using sensors such as radio waves and sound waves (the number of moving objects can be arbitrary).
  • mobile 1 in frame 1 is assumed to correspond to any of mobiles 1, 2, 3 in frame 2.
  • trajectory 11 formed by moving body 1 of frame 1 to moving body 1 of frame 2 trajectory 12 formed by moving body 1 of frame 1 to moving body 2 of frame 2 is assumed to be formed.
  • trajectory 13 formed by moving body 1 of frame 1 to moving body 3 of frame 2 is assumed to be formed. The same can be said for moving bodies 2 and 3 in frame 1 .
  • the processing device 100 described in this embodiment searches for combinations of trajectories as described above without omission by the method illustrated in FIG.
  • the processing device 100 focuses on a certain trajectory and extracts common possible trajectories that are trajectories that can be shared with the focused trajectory.
  • the processing device 100 performs the above-described extraction process so as not to extract the same combination that is only different in order.
  • the processing device 100 focuses on the trajectory 22 and extracts trajectories 11 , 33 , 13 , and 31 as common possible trajectories that can be shared with the trajectory 22 .
  • the processing device 100 extracts common possible trajectories by focusing on the trajectory 11 .
  • the processing device 100 extracts common possible trajectories so as not to extract the same combination as the combination extracted by focusing on the trajectory 22 .
  • the combination of “trajectory 22, trajectory 11” has already been extracted at the stage where attention is focused on trajectory 22 . Therefore, the processing device 100 extracts the trajectory 33, the trajectory 23, and the trajectory 32 as common possible trajectories that can be shared with the trajectory 11, but does not extract the trajectory 22 that is the same combination.
  • the processing device 100 extracts common possible trajectories so as not to extract the same combination by repeating the above-described processing focusing on each trajectory as the first-stage processing.
  • “Moving objects” refer to objects that move, such as cars, ships, airplanes, and unmanned guided vehicles.
  • the moving body may be other than those exemplified above.
  • a common possible trajectory refers to, for example, a trajectory that can physically coexist (exist).
  • trajectory 11 and trajectory 22 can coexist, but trajectory 11 and trajectory 13 cannot coexist because there are two moving bodies 1 in frame 1, and are not considered common possible trajectories.
  • Common possible trajectories may be partially limited in advance in preprocessing or the like, such as trajectories whose movement distance is within a threshold value among trajectories that can physically coexist, or trajectories formed between moving bodies having a predetermined feature amount.
  • the order of trajectories that the processing device 100 pays attention to may be determined arbitrarily.
  • the processing device 100 extracts common possible trajectories that are further commonable trajectories to each trajectory indicated by the common possible trajectories extracted in the first-stage processing, so as not to extract the same combination as in the first-stage processing. Further, after the processing of searching for combinations in the second stage is completed, the processing device 100 extracts, as the processing of the third stage, common possible trajectories that are further commonable trajectories indicated by the common possible trajectories extracted in the second stage processing. After that, the processing device 100 repeats the same processing until no more combinations are extracted.
  • the processing device 100 described in the present embodiment vectorizes the second and subsequent stages of extraction processing and causes the vector processing unit 130 such as a vector engine to perform the extraction processing. That is, the processing device 100 vectorizes the processing of searching for combinations in the second and subsequent stages, and causes the vector processing unit 130 to perform the processing. Further, as described above, the processing device 100 performs extraction processing so as not to extract the same combination. Therefore, the number of possible common trajectories decreases as the stage becomes later, or even in the same stage, as the attention is focused later.
  • the processing device 100 can change the vectorization method according to the processing status of searching for a combination of the order of attention, the number of stages of processing, the number of common possible trajectories in a given trajectory, and the like. It should be noted that specific examples of the judgment when changing the vectorization method and the vectorization method will be described later.
  • FIG. 3 shows a configuration example of the processing device 100.
  • the processing device 100 has, for example, a storage unit 110, an arithmetic processing unit 120, and a vector processing unit .
  • the processing device 100 is communicably connected to an external device such as a sensor that detects a moving object using sound waves or radio waves.
  • the processing device 100 can receive the result of sensing by the sensor or the like from an external device such as a sensor.
  • the storage unit 110 is a storage device such as a hard disk or memory.
  • the storage unit 110 stores processing information and programs 112 necessary for various processes in the arithmetic processing unit 120 and the like.
  • the program 112 realizes various processing units by being read and executed by the arithmetic processing unit 120 .
  • the program 112 is preloaded from an external device or recording medium via the data input/output function of the processing device 100 and stored in the storage unit 110 .
  • Main information stored in the storage unit 110 includes sensing information 111, for example.
  • the sensing information 111 includes information indicating the position of the moving object detected by an external device such as a sensor (for example, position information such as latitude and longitude information). For example, the sensing information 111 includes information indicating the positions of multiple moving objects in multiple frames. The sensing information 111 is updated each time information indicating a sensing result is received from an external device such as a sensor.
  • the arithmetic processing unit 120 has an arithmetic device such as a processor and its peripheral circuits.
  • the arithmetic processing unit 120 reads the program 112 from the storage unit 110 and executes it, so that the hardware and the program 112 cooperate to realize various processing units.
  • Main processing units realized by the arithmetic processing unit 120 include, for example, a trajectory determination unit 121 , a vectorization method determination unit 122 , and a vectorization execution unit 123 .
  • at least the vectorization method determination unit 122 and the vectorization execution unit 123 may include, for example, a compiler realized by the arithmetic processing unit 120 reading and executing the program 112 or the like.
  • the trajectory determination unit 121 identifies, for example, a plurality of trajectories such as paths traveled by the moving body based on the position information of the moving body in multiple frames indicated by the sensing information 111 . Then, the trajectory determination unit 121 performs the above-described first-stage processing on the plurality of identified trajectories. That is, the trajectory determination unit 121 performs processing for each specified trajectory to extract a common possible trajectory in the trajectory focused on an arbitrary trajectory. At this time, the trajectory determination unit 121 extracts common possible trajectories so as not to extract the same combination that differs only in order. Further, the trajectory determination unit 121 adds each trajectory indicated by the extracted common possible trajectories to the processing targets for the next common possible trajectory search.
  • FIG. 4 shows a processing example of the trajectory determination unit 121 when three moving bodies are detected in each of frames 1 and 2 as illustrated in FIG.
  • the trajectory determination unit 121 focuses on the trajectory 22, for example.
  • the trajectory determination unit 121 extracts a common possible trajectory that is a trajectory that can be shared with the trajectory 22 .
  • the trajectory determination unit 121 extracts trajectory 11, trajectory 33, trajectory 13, and trajectory 31 as common possible trajectories.
  • the trajectory determination unit 121 focuses on the trajectory 11 .
  • the trajectory determination unit 121 extracts a common possible trajectory, which is a trajectory that can be shared with the trajectory 11, so as not to extract the same combination as an already extracted combination.
  • the trajectory determination unit 121 extracts trajectories 33, 23, and 32 as common possible trajectories, but does not extract trajectory 22 that is the same combination as the already extracted combination.
  • the trajectory determination unit 121 extracts common possible trajectories so as not to extract the same combination by repeating the same process focusing on each specified trajectory, such as trajectory 33, trajectory 21, trajectory 23, . After that, the trajectory determination unit 121 adds each trajectory indicated by the extracted common possible trajectories to the processing targets for the next common possible trajectory search.
  • the trajectory determination unit 121 does not extract the same combination as the already extracted combination. Therefore, as shown in FIG. 4, there is a possibility that the same combination of sharable trajectories has been previously extracted for trajectories that are focused on later, and the number of sharable trajectories that are actually extracted decreases. For example, in the case illustrated in FIG. 4 , the trajectory determination unit 121 does not extract a sharable trajectory when focusing on the trajectory 31 . This is because all combinations of trajectories 31 and sharable trajectories have already been extracted before focusing on trajectory 31 .
  • the trajectory determination unit 121 may be configured to perform the above-described first-stage processing on the trajectory that has undergone predetermined preprocessing by the preprocessing unit realized by, for example, the arithmetic processing unit 120 reading and executing the program 112. For example, in the pre-processing, among trajectories that can physically coexist, a process of limiting common possible trajectories that can be shared with a certain trajectory, such as a trajectory whose moving distance is within a threshold or a trajectory formed between moving bodies having a predetermined feature amount, may be performed.
  • the trajectory determination unit 121 which functions as an acquisition unit that acquires information indicating a trajectory, may acquire information indicating a trajectory based on the position information of a moving object in multiple frames indicated by the sensing information 111, or may acquire information indicating a trajectory from another processing unit such as a preprocessing unit.
  • the vectorization method determination unit 122 is a determination unit that determines a method for vectorizing the process of searching for a combination for each one or more processing targets. For example, the vectorization method determination unit 122 determines which of the predetermined methods should be used to vectorize the process of searching for a combination based on the processing status of the process of searching for a combination of trajectories, such as the order of attention, the number of stages of processing, and the number of common possible trajectories in a given trajectory. For example, the vectorization method determination unit 122 determines whether to vectorize the combination search process using any one of the first method, the second method, and the third method, based on the processing status of the process of searching for a combination of trajectories.
  • the process of searching for a common possible trajectory and adding it to the next processing target is vectorized. That is, in the first method, the process of searching for combinations of trajectories indicated by common possible trajectories corresponding to one processing target is vectorized.
  • the first stage which is the preceding stage
  • trajectories 11, 33, 13, and 31 are extracted as common possible trajectories for trajectory 22.
  • FIG. Therefore, in the first method, common possible trajectories are further searched for each of trajectory 11, trajectory 33, trajectory 13, and trajectory 31, and each trajectory indicated by the searched common possible trajectory is vectorized as the next processing target.
  • FIG. 6 shows an overview of the second method.
  • the process of searching for combinations of trajectories indicated by common possible trajectories corresponding to a plurality of processing targets is vectorized.
  • trajectories 11, 33, 13, and 31 are extracted as common possible trajectories for trajectory 22.
  • FIG. Further, in the case of FIG.
  • the trajectory 33, the trajectory 23, and the trajectory 32 are extracted as common possible trajectories of the trajectory 11 in the first stage. Therefore, in the second method, trajectories 11, 33, 13, and 31 that can be common to trajectory 22, and trajectories 33, 23, and 32 that can be common to trajectory 11 are further searched for common trajectories, and the process of adding each trajectory indicated by the searched common trajectory to the next processing target is vectorized.
  • the number of trajectories to be collectively processed in the second method may be set arbitrarily. For example, the number of trajectories to be collectively processed in the second method may be set according to the total number of common possible trajectories corresponding to the respective trajectories to be collectively processed.
  • FIG. 7 shows an overview of the third method.
  • the third method combines some of the processes of the first method. For example, in the third method, for each trajectory indicated by the common possible trajectory corresponding to one certain trajectory in the previous stage, the processing for searching for common possible trajectories is performed multiple times, and then the processing for searching for combinations is vectorized so that the processing for adding to the next processing target is performed collectively. In this way, in the third method, the process of searching for a combination is vectorized so that after performing the process of searching for a combination in the first method a plurality of times, the process of adding each trajectory indicated by the searched common possible trajectory to the next processing target is collectively performed.
  • the vectorization method determination unit 122 determines which of the above-described first method, second method, and third method should be used to vectorize the combination search process based on the processing status of the combination search process.
  • FIG. 8 shows a diagram for explaining an example of determination based on the processing status.
  • the vectorization method determination unit 122 can determine which of the first method and the second method should be used for vectorization based on the number of stages of processing.
  • the vectorization method determination unit 122 determines to vectorize by the first method when the number of processing stages is less than a predetermined value, and determines to vectorize by the second method when the number of processing stages is equal to or greater than the predetermined value. In other words, the vectorization method determination unit 122 determines to vectorize the process of searching for a combination by the first method when it is assumed that the number of trajectories to be searched (that is, the number of sharable trajectories in the previous stage) is sufficiently large based on the processing status such as the number of processing stages.
  • the vectorization method determination unit 122 determines to vectorize the processing of searching for combinations by the second method. In this way, the vectorization method determination unit 122 can determine which of the first method and the second method should be used for vectorization based on the amount of processing determined based on the processing status such as the number of stages of processing.
  • the vectorization method determination unit 122 can determine which of the first method and the third method should be used for vectorization based on the order of attention. For example, the vectorization method determination unit 122 determines to vectorize by the first method when the order of attention is less than a predetermined value, and determines to vectorize by the third method when the order of attention is equal to or greater than the predetermined value. In other words, the vectorization method determination unit 122 determines to vectorize the process of searching for combinations by the first method when it is assumed that there are sufficiently many trajectories to be searched based on the order of attention.
  • the vectorization method determination unit 122 determines to vectorize the process of searching for combinations by the third method. In this way, the vectorization method determination unit 122 can determine which of the first method and the third method should be used for vectorization based on the amount of processing determined based on the processing status such as the order of attention.
  • the vectorization method determination unit 122 can determine whether to use any of the above determination methods or a combination of the above determination methods to vectorize the process of searching for a combination using the first method, the second method, or the third method.
  • the vectorization method determination unit 122 may determine, for example, based on the number of stages of processing, which of the first method and the third method should be used for vectorization, and whether to use the first method or the second method for vectorization based on the number of sharable trajectories in the previous stage.
  • the timing at which the vectorization method determination unit 122 makes the above determination may be set arbitrarily.
  • the vectorization method determination unit 122 can determine for each stage which method should be used for vectorization. That is, the vectorization method determination unit 122 can collectively determine which method is used for vectorization for a certain stage.
  • the vectorization method determination unit 122 may determine which method should be used to vectorize the process of searching for a combination of sharable trajectories corresponding to the next one or more trajectories each time a process corresponding to the result of determining that vectorization should be performed using a certain method is completed.
  • the vectorization execution unit 123 vectorizes the process of searching for combinations according to the determination of the vectorization method determination unit 122 . Then, the vectorization execution unit 123 causes the vector processing unit 130 to execute vector processing. It should be noted that the method described in this embodiment is a process of confirming common combinations, so simple vectorization is not possible. Therefore, the vectorization execution unit 123 performs vectorization using a buffer.
  • FIG. 9 is a diagram for explaining in more detail the process of vectorization by the first method.
  • the vectorization execution unit 123 first prepares a buffer corresponding to the trajectory number in the previous stage.
  • the first stage which is the preceding stage, includes trajectories 22, 11, 33, 21, 23, 12, 32, 13, and 31. Therefore, the vectorization execution unit 123 prepares buffers corresponding to the numbers of the trajectories in the storage unit 110 or the like.
  • the vectorization execution unit 123 also performs vectorization by generating an instruction for causing the vector processing unit 130 to perform the following processing, for example.
  • • 1 is stored in the buffer corresponding to the common possible trajectory in the previous stage among the prepared buffers. ⁇ Check if there is 1 in the buffer indicated by the preceding common possible trajectory corresponding to the trajectory to be judged, and if there is 1, the buffer adds the number of 1 to the common possible trajectory frame of the trajectory to be judged. ⁇ Perform the same judgment process for each trajectory.
  • the commands are as follows.
  • 1 is stored in buffers corresponding to trajectory 11, trajectory 33, trajectory 13, and trajectory 31, so there is 1 in buffer 33.
  • indicating that there is no common possible trajectory is added to the common possible trajectory frame of trajectory 33, which is the determination target.
  • the buffer adds the number of 1 to the common possible trajectory frame of the trajectory to be determined.
  • 1 is stored in buffers corresponding to trajectory 11, trajectory 33, trajectory 13, and trajectory 31, so there is 1 in buffer 31. Therefore, 31 is added to the common possible trajectory frame of trajectory 13, which is the determination target.
  • - The preceding common possible trajectory corresponding to the trajectory 31 to be determined indicates that there is no combination of the trajectory 31 and the sharable trajectory. Therefore, no further confirmation is performed.
  • the trajectory 33 and the trajectory 31 indicated by the number added to the common possible trajectory frame are to be processed next.
  • the vectorization execution unit 123 When preparing the buffer, the vectorization execution unit 123 prepares the buffer corresponding to the trajectory number in the previous stage. At this time, the vectorization execution unit 123 can prepare a buffer corresponding to the trajectory number determined by the same processing (processing for each trajectory when multiple trajectories are collectively processed) in the previous stage.
  • FIG. 10 shows an example of a buffer prepared by the vectorization execution unit 123 in the third stage. Referring to FIG. 10 , when searching for common possible trajectories for trajectory 33 and trajectory 31 in the processing of the third stage, the trajectories determined by the same processing in the previous stage are trajectories 11, 33, 13, and 31.
  • the vectorization execution unit 123 can prepare buffers corresponding to the numbers of the trajectories in the storage unit 110 or the like. Further, when searching for a common possible trajectory for trajectory 32 in the processing of the third stage, trajectories 33, 23, and 32 are the trajectories determined by the same processing in the previous stage. Therefore, the vectorization execution unit 123 can prepare buffers corresponding to the numbers of the trajectories in the storage unit 110 or the like.
  • FIG. 11 is a diagram for explaining in more detail the process for vectorization by the second method.
  • the vectorization execution unit 123 first prepares a number of buffers corresponding to the number of the trajectory in the preceding stage and corresponding to the number of vector lengths corresponding to the number of trajectories to be processed simultaneously.
  • the first stage which is the preceding stage, includes trajectories 22, 11, 33, 21, 23, 12, 32, 13, and 31.
  • two trajectories are processed at the same time as an example. Therefore, as shown in FIG. 11, the vectorization execution unit 123 prepares a two-line buffer in the storage unit 110 or the like corresponding to each trajectory number.
  • the vectorization execution unit 123 also performs vectorization by generating an instruction for causing the vector processing unit 130 to perform the following processing, for example.
  • For each row of the buffer it is checked whether there is 1 in the buffer indicated by the preceding common possible trajectory corresponding to the trajectory to be determined, and if there is 1, the buffer adds the number of 1 to the common possible trajectory frame of the trajectory to be determined. ⁇ Similar determination processing is performed for each trajectory. ⁇ The trajectory indicated by the number added to the common possible trajectory frame is the next processing target.
  • the following instructions are used.
  • 1 is stored in the buffers corresponding to trajectories 11, 33, 13, and 31, which are sharable trajectories in the previous stage.
  • 1 is stored in the buffer corresponding to the trajectory 33, trajectory 23, and trajectory 32, which are the sharable trajectories in the previous stage.
  • ⁇ Check if there is a 1 in 33 of the first line of the buffer and 21 of the second line. (In this case, there is 1 in the buffer of 33 on the first line.
  • FIG. 12 is a diagram for explaining in more detail the process of vectorization by the third method.
  • vectorization is performed by generating an instruction indicating that the next processing target is to be added at the same time based on the results of the determination processing for the plurality of trajectories.
  • the vectorization execution unit 123 performs vectorization by generating instructions according to each method as described above according to the determination of the vectorization method determination unit 122 . Then, the vectorization execution unit 123 causes the vector processing unit 130 to execute vector processing using the generated instructions.
  • the vector processing unit 130 has a vector processor and the like, and executes vector processing according to instructions from the vectorization execution unit 123 .
  • the vector processing unit 130 may be a known vector engine or the like.
  • the above is a configuration example of the processing device 100 .
  • an operation example of the processing device 100 will be described with reference to FIG. 13 .
  • FIG. 13 is a flowchart showing an operation example of the processing device 100.
  • the trajectory determination unit 121 identifies, for example, a plurality of trajectories such as paths traveled by the moving object, based on the position information of the moving object in multiple frames indicated by the sensing information 111 . Then, the trajectory determination unit 121 performs the first-stage process on the plurality of specified trajectories. That is, the trajectory determination unit 121 extracts a common possible trajectory for the first stage (step S101).
  • the vectorization method determination unit 122 determines which of the predetermined methods should be used to vectorize the combination search process based on the processing status of the trajectory combination search process (step S102). For example, the vectorization method determination unit 122 determines whether to vectorize the combination search process using any one of the first method, the second method, and the third method, based on the processing status of the process of searching for a combination of trajectories.
  • the vectorization execution unit 123 vectorizes the process of searching for combinations according to the determination of the vectorization method determination unit 122 . Then, the vectorization execution unit 123 causes the vector processing unit 130 to execute vector processing (step S103).
  • step S104 After the vector processing in step S103, when the processing target is finished (step S104, Yes), the processing device 100 finishes the processing. On the other hand, if there is a process target (step S104, No), the vectorization method determination unit 122 returns to the determination of step S102.
  • the above is an operation example of the processing device 100 .
  • the processing device 100 has the vectorization execution unit 123 .
  • the vectorization execution unit 123 can vectorize the process of searching for a combination of trajectories and cause the vector processing unit 130 to perform the vectorization.
  • the process of searching for a combination of trajectories as described above is a memory bottleneck process. Therefore, the processing can be speeded up by causing the vector processing unit 130 with high memory access speed to perform the processing.
  • the processing device 100 also has a vectorization method determination unit 122 .
  • the vectorization execution unit 123 can execute vectorization by the method determined by the vectorization method determination unit 122 according to the processing status of the process of searching for a combination of trajectories.
  • the efficiency of vector processing can be improved by performing vectorization by a method determined according to the processing status of processing for searching for a combination of trajectories.
  • the processing device 100 described in the present embodiment searches for combinations of simultaneously selectable trajectories, as described above.
  • the result of the search performed by the processing device 100 can be used, for example, when tracking a moving object.
  • the result of the search performed by the processing device 100 may be used in situations other than tracking the moving object.
  • FIG. 14 is a diagram showing a hardware configuration example of the processing device 200.
  • FIG. 15 is a block diagram showing a configuration example of the processing device 200. As shown in FIG.
  • FIG. 14 shows a hardware configuration example of the processing device 200 .
  • the processing device 200 has the following hardware configuration as an example.
  • a processor CPU: Central Processing Unit
  • 201 that functions as a processing management unit that vectorizes processing and causes the vector processing unit to process it.
  • a vector processor 202 that functions as a vector processing unit that performs vector processing - Storage device 203 for storing program group 204
  • the processing device 200 may include a ROM (Read Only Memory), a RAM (Random Access Memory), a drive device for reading and writing to a recording medium outside the information processing device, a communication interface for connecting to a communication network outside the information processing device, an input/output interface for inputting and outputting data, a bus for connecting each component, and the like.
  • the processor 201 acquires the program group 204 and the processor 201 executes it, so that the processing device 200 can realize the functions of the acquisition unit 221 and the vectorization unit 222 shown in FIG.
  • the program group 204 is stored in advance in, for example, the storage device 203 or the ROM of the processing device 200, and is loaded into the RAM or the like by the processor 201 as necessary and executed.
  • the program group 204 may be supplied to the processor 201 via a communication network, or may be stored in a recording medium in advance, and the drive device may read the program and supply it to the processor 201 .
  • FIG. 14 shows a hardware configuration example of the processing device 200 .
  • the hardware configuration of the processing device 200 is not limited to that described above.
  • the acquisition unit 221 acquires information indicating a trajectory, which is a route traveled by the mobile body, specified based on the sensing result of the mobile body. For example, the acquisition unit 221 may acquire information indicating the trajectory based on the position information of the moving object indicated by the sensing result of the moving object.
  • the vectorization unit 222 vectorizes the process of searching for a combination of trajectories acquired by the acquisition unit 221 and causes the vector processing unit to execute it.
  • the vectorization unit 222 may vectorize the process of searching for a combination of trajectories by generating an instruction for extracting a common possible trajectory, which is a trajectory that can be shared with a trajectory, using a buffer.
  • the processing device 200 has the vectorization section 222 .
  • the vectorization unit 222 can vectorize the process of searching for a combination of trajectories and cause the vector processing unit to perform the vectorization.
  • the process of searching for a combination of trajectories as described above is a memory bottleneck process. Therefore, the processing can be speeded up by allowing the vector processing unit with high memory access speed to perform the processing.
  • a program that is another aspect of the present invention is a program that acquires information indicating a trajectory, which is a route traveled by a mobile body, specified based on the sensing result of the mobile body, vectorizes a process of searching for a combination of the acquired trajectories, and causes a vector processing unit to execute the process.
  • the processing method executed by an information processing device such as the processing device 200 described above is a method of acquiring information indicating a trajectory, which is a route traveled by a moving object, which is specified based on the sensing result of the moving object, vectorizing a process of searching for a combination of the acquired trajectories, and causing a vector processing unit to execute the processing.
  • Appendix 1 an acquisition unit that acquires information indicating a trajectory, which is a route traveled by the mobile object, that is specified based on a sensing result of the mobile object; a vectorization unit that vectorizes a process of searching for a combination of trajectories acquired by the acquisition unit and causes a vector processing unit to execute the process;
  • Appendix 3 The processing apparatus according to Appendix 1 or Appendix 2, a determination unit that determines whether to vectorize the process of searching for a combination of trajectories using a predetermined method based on the processing status of the process of searching for a combination of trajectories; The processing device, wherein the vectorization unit vectorizes a process of searching for a combination of trajectories according to the determination result of the determination unit.
  • the processing device determines which of a first method of vectorizing a process of searching for a combination of trajectories indicated by a common possible trajectory corresponding to one processing target and a second method of vectorizing a process of searching for a combination of each trajectory indicated by the common possible trajectories corresponding to a plurality of processing targets based on the processing status of the processing of searching for a combination of trajectories.
  • the processing device determines which of the first method and the second method is used for vectorization according to the amount of processing determined based on the processing status of processing for searching for a combination of trajectories. Processing device.
  • the determination unit determines which of a first method of vectorizing a process of searching for a combination of trajectories indicated by a common possible trajectory corresponding to one processing target, and a third method of vectorizing a process of performing a process of collectively adding processing targets according to the search result after performing multiple searches for combinations of each trajectory indicated by the common possible trajectory corresponding to one processing target.
  • the information processing device Acquiring information indicating a trajectory, which is a route traveled by the moving object, which is specified based on the sensing result of the moving object; A processing method in which the process of searching for combinations of acquired trajectories is vectorized and executed by the vector processing unit.
  • information processing equipment Acquiring information indicating a trajectory, which is a route traveled by the moving object, which is specified based on the sensing result of the moving object;
  • a computer-readable recording medium recording a program for vectorizing a process of searching for a combination of acquired trajectories and causing the vector processing unit to execute the process.
  • processing device 110 storage unit 111 sensing information 112 program 120 arithmetic processing unit 121 trajectory determination unit 122 vectorization method determination unit 123 vectorization execution unit 130 vector processing unit 200 processing device 201 processor 202 vector processor 203 storage device 204 program group 221 acquisition unit 222 vectorization unit

Abstract

A processing device 200 includes: an acquisition unit 221 that acquires information indicating trajectories which were identified on the basis of the results of sensing mobile bodies and which are the paths on which the mobile bodies moved; and a vectorization unit 222 that vectorizes processing for searching combinations of the trajectories acquired by the acquisition unit 221, and that causes a vectorization processing unit to execute such processing.

Description

処理装置processing equipment
 本発明は、処理装置、処理方法、記録媒体に関する。 The present invention relates to processing apparatuses, processing methods, and recording media.
 複数の観測結果に基づいて、自動車、船、飛行機、無人搬送車などの移動体が移動した経路や航路などの軌跡を判断することがある。 Based on multiple observation results, the trajectories of moving objects such as cars, ships, airplanes, and unmanned guided vehicles may be determined.
 例えば、非特許文献1や非特許文献2には、船の航跡などの移動体の軌跡を判断するための技術が記載されている。非特許文献1や非特許文献2に記載の技術の場合、航跡仮設のクラス分類を行った後、グローバル仮説を生成して、生成したグローバル仮説に基づいて航跡仮設の選定を行っている。また、グローバル仮説を生成する方法について記載された文献としては、例えば、非特許文献3がある。 For example, Non-Patent Document 1 and Non-Patent Document 2 describe techniques for determining the trajectory of a moving object such as a ship's trajectory. In the case of the techniques described in Non-Patent Literature 1 and Non-Patent Literature 2, after classifying the track hypotheses, global hypotheses are generated, and track hypotheses are selected based on the generated global hypotheses. Non-Patent Document 3, for example, describes a method for generating global hypotheses.
 また、関連する技術として、例えば、特許文献1がある。特許文献1には、センサデータに基づいて物体を検出、追跡する際に用いられる技術の一例が記載されている。 Also, as a related technology, there is Patent Document 1, for example. Patent Literature 1 describes an example of technology used to detect and track an object based on sensor data.
特開2021-089723号公報JP 2021-089723 A
 非特許文献1~3に記載されているようなグローバル仮説を生成する際などにおいては、軌跡と、当該軌跡と共通可能な軌跡と、を探索することがある。このような共通可能な軌跡を探索することなどにより移動体を追跡する場合、例えば、追跡する移動体の数が増えると、その組み合わせの数だけ必要な処理が増えることになる。その結果、処理時間が増大してしまっていた。 When generating global hypotheses as described in Non-Patent Documents 1 to 3, trajectories and trajectories that can be common to the trajectory are sometimes searched. When tracking moving bodies by searching for common trajectories, for example, as the number of moving bodies to be tracked increases, the number of necessary processes increases by the number of combinations. As a result, the processing time has increased.
 上記のような移動体の追跡は、リアルタイムで処理を行うことが必要である場合があるため、処理は出来るだけ高速にすることが望ましい。しかしながら、共通可能な軌跡の探索などの組み合わせの処理は複雑である。そのため、並列化効率が悪く高速化が困難であった。 The tracking of moving objects as described above may require processing in real time, so it is desirable that the processing be as fast as possible. However, combinatorial processing, such as searching for common possible trajectories, is complicated. Therefore, the efficiency of parallelization was poor and speeding up was difficult.
 このように、共有可能な軌跡の探索などの組み合わせの処理を高速化することが難しい、という課題が生じていた。 In this way, there was a problem that it was difficult to speed up combination processing such as searching for sharable trajectories.
 そこで、本発明の目的は、共有可能な軌跡の探索などの組み合わせの処理を高速化することが難しい、という課題を解決することが可能な処理装置、処理方法、記録媒体を提供することにある。 Therefore, an object of the present invention is to provide a processing device, a processing method, and a recording medium that can solve the problem that it is difficult to speed up combination processing such as searching for sharable trajectories.
 かかる目的を達成するため本開示の一形態である処理装置は、
 移動体のセンシング結果に基づいて特定される、前記移動体が移動した経路である軌跡を示す情報を取得する取得部と、
 前記取得部が取得した軌跡の組み合わせを探索する処理をベクトル化してベクトル処理部に実行させるベクトル化部と、
 を有する
 という構成をとる。
In order to achieve such an object, the processing device, which is one aspect of the present disclosure,
an acquisition unit that acquires information indicating a trajectory, which is a route traveled by the mobile object, that is specified based on a sensing result of the mobile object;
a vectorization unit that vectorizes a process of searching for a combination of trajectories acquired by the acquisition unit and causes a vector processing unit to execute the process;
It has a configuration of
 また、本開示の他の形態である処理方法は、
 情報処理装置が、
 移動体のセンシング結果に基づいて特定される、前記移動体が移動した経路である軌跡を示す情報を取得し、
 取得した軌跡の組み合わせを探索する処理をベクトル化してベクトル処理部に実行させる
 という構成をとる。
In addition, a processing method that is another aspect of the present disclosure includes:
The information processing device
Acquiring information indicating a trajectory, which is a route traveled by the moving body, which is specified based on the sensing result of the moving body;
A configuration is adopted in which the process of searching for combinations of acquired trajectories is vectorized and executed by the vector processing unit.
 また、本開示の他の形態である記録媒体は、
 情報処理装置に、
 移動体のセンシング結果に基づいて特定される、前記移動体が移動した経路である軌跡を示す情報を取得し、
 取得した軌跡の組み合わせを探索する処理をベクトル化してベクトル処理部に実行させる
 処理を実現するためのプログラムを記録した、コンピュータが読み取り可能な記録媒体である。
In addition, a recording medium that is another aspect of the present disclosure includes:
information processing equipment,
Acquiring information indicating a trajectory, which is a route traveled by the moving body, which is specified based on the sensing result of the moving body;
A computer-readable recording medium recording a program for realizing a process of vectorizing a process of searching for a combination of acquired trajectories and causing a vector processing unit to execute the process.
 上述したような各構成によると、共有可能な軌跡の探索などの組み合わせの処理を高速化することが可能な処理装置、処理方法、記録媒体を提供することが出来る。 According to each configuration as described above, it is possible to provide a processing device, a processing method, and a recording medium capable of speeding up combination processing such as searching for sharable trajectories.
本発明の概要を説明するための図である。BRIEF DESCRIPTION OF THE DRAWINGS It is a figure for demonstrating the outline|summary of this invention. 本発明の概要を説明するための図である。BRIEF DESCRIPTION OF THE DRAWINGS It is a figure for demonstrating the outline|summary of this invention. 処理装置の構成例を示すブロック図である。It is a block diagram which shows the structural example of a processing apparatus. 1段目における軌跡と共通可能軌跡の判断例を示す図である。FIG. 10 is a diagram showing an example of determining a trajectory and a common possible trajectory in the first stage; ベクトル化の一例を示す図である。It is a figure which shows an example of vectorization. ベクトル化の他の一例を示す図である。FIG. 10 is a diagram showing another example of vectorization; ベクトル化の他の一例を示す図である。FIG. 10 is a diagram showing another example of vectorization; 判定条件の一例を示す図である。It is a figure which shows an example of a determination condition. 第1の方法におけるベクトル化の詳細例を示す図である。FIG. 4 is a diagram showing a detailed example of vectorization in the first method; 第1の方法におけるベクトル化の詳細例を示す図である。FIG. 4 is a diagram showing a detailed example of vectorization in the first method; 第2の方法におけるベクトル化の詳細例を示す図である。FIG. 10 is a diagram showing a detailed example of vectorization in the second method; 第3の方法におけるベクトル化の詳細例を示す図である。FIG. 10 is a diagram showing a detailed example of vectorization in the third method; 処理装置の動作例を示すフローチャートである。It is a flowchart which shows the operation example of a processing apparatus. 本開示の第2の実施形態における処理装置の構成例を示すブロック図である。FIG. 11 is a block diagram showing a configuration example of a processing device according to a second embodiment of the present disclosure; FIG. 処理装置の構成例を示すブロック図である。It is a block diagram which shows the structural example of a processing apparatus.
[第1の実施形態]
 本開示の第1の実施形態について、図1から図13までを参照して説明する。図1、図2は、本発明の概要を説明するための図である。図3は、処理装置100の構成例を示すブロック図である。図4は、1段目における軌跡と共通可能軌跡の判断例を示す図である。図5から図7まではベクトル化の一例を示す図である。図8は、判定条件の一例を示す図である。図9、図10は、第1の方法におけるベクトル化の詳細例を示す図である。図11は、第2の方法におけるベクトル化の詳細例を示す図である。図12は、第3の方法におけるベクトル化の詳細例を示す図である。図13は、処理装置100の動作例を示すフローチャートである。
[First Embodiment]
A first embodiment of the present disclosure will be described with reference to FIGS. 1 to 13. FIG. 1 and 2 are diagrams for explaining the outline of the present invention. FIG. 3 is a block diagram showing a configuration example of the processing device 100. As shown in FIG. FIG. 4 is a diagram showing an example of determination of a trajectory and a common possible trajectory in the first stage. 5 to 7 are diagrams showing an example of vectorization. FIG. 8 is a diagram showing an example of determination conditions. 9 and 10 are diagrams showing detailed examples of vectorization in the first method. FIG. 11 is a diagram showing a detailed example of vectorization in the second method. FIG. 12 is a diagram showing a detailed example of vectorization in the third method. FIG. 13 is a flow chart showing an operation example of the processing device 100 .
 本開示の第1の実施形態においては、組み合わせの処理の一例として、同時に選択可能な軌跡の組み合わせを探索する情報処理装置である処理装置100について説明する。例えば、図1で示すように、電波や音波などのセンサを用いて、あるフレーム(フレーム1)で移動体が3点観測され、次のフレーム(フレーム2)で移動体が3点観測されていたとする(移動体の数は任意でよい)。このような場合、フレーム1における移動体1は、フレーム2における移動体1、2、3のいずれかに相当するものと想定される。言い換えると、フレーム1の移動体1がフレーム2の移動体1に移動することで形成される軌跡11、フレーム1の移動体1がフレーム2の移動体2に移動することで形成される軌跡12、フレーム1の移動体1がフレーム2の移動体3に移動することで形成される軌跡13、のうちのいずれかが形成されるものと想定される。同様のことは、フレーム1の移動体2、3についてもいえる。 In the first embodiment of the present disclosure, as an example of combination processing, a processing device 100 that is an information processing device that searches for a combination of simultaneously selectable trajectories will be described. For example, as shown in FIG. 1, it is assumed that three moving objects are observed in one frame (frame 1) and three moving objects are observed in the next frame (frame 2) using sensors such as radio waves and sound waves (the number of moving objects can be arbitrary). In such a case, mobile 1 in frame 1 is assumed to correspond to any of mobiles 1, 2, 3 in frame 2. In other words, one of trajectory 11 formed by moving body 1 of frame 1 to moving body 1 of frame 2, trajectory 12 formed by moving body 1 of frame 1 to moving body 2 of frame 2, and trajectory 13 formed by moving body 1 of frame 1 to moving body 3 of frame 2 is assumed to be formed. The same can be said for moving bodies 2 and 3 in frame 1 .
 本実施形態において説明する処理装置100は、例えば、図2で例示するような方法により、上述したような軌跡の組み合わせを漏れなく探索する。まず、処理装置100は、ある軌跡に着目するとともに着目した軌跡と共通可能な軌跡である共通可能軌跡を抽出する。この際、処理装置100は、順序が異なるだけの同一の組み合わせを抽出しないように、上記抽出処理を行う。例えば、図2で例示する場合、処理装置100は、軌跡22に着目するとともに、軌跡22と共通可能な軌跡である共通可能軌跡として軌跡11、軌跡33、軌跡13、軌跡31を抽出する。次に、処理装置100は、軌跡11に着目して共通可能軌跡を抽出する。この際、処理装置100は、軌跡22に着目して抽出した組み合わせと同じ組み合わせを抽出しないように、共通可能軌跡を抽出する。例えば、図2で例示する場合、“軌跡22、軌跡11”の組み合わせは、軌跡22に着目した段階で既に抽出されている。そのため、処理装置100は、軌跡11と共通可能な軌跡である共通可能軌跡として、軌跡33、軌跡23、軌跡32を抽出する一方で、同一の組み合わせになる軌跡22を抽出しない。例えば、処理装置100は、1段目の処理として、各軌跡に着目して上述したような処理を繰り返すことにより、同じ組み合わせを抽出しないように共通可能軌跡を抽出する。 The processing device 100 described in this embodiment, for example, searches for combinations of trajectories as described above without omission by the method illustrated in FIG. First, the processing device 100 focuses on a certain trajectory and extracts common possible trajectories that are trajectories that can be shared with the focused trajectory. At this time, the processing device 100 performs the above-described extraction process so as not to extract the same combination that is only different in order. For example, in the case of FIG. 2 , the processing device 100 focuses on the trajectory 22 and extracts trajectories 11 , 33 , 13 , and 31 as common possible trajectories that can be shared with the trajectory 22 . Next, the processing device 100 extracts common possible trajectories by focusing on the trajectory 11 . At this time, the processing device 100 extracts common possible trajectories so as not to extract the same combination as the combination extracted by focusing on the trajectory 22 . For example, in the example shown in FIG. 2, the combination of “trajectory 22, trajectory 11” has already been extracted at the stage where attention is focused on trajectory 22 . Therefore, the processing device 100 extracts the trajectory 33, the trajectory 23, and the trajectory 32 as common possible trajectories that can be shared with the trajectory 11, but does not extract the trajectory 22 that is the same combination. For example, the processing device 100 extracts common possible trajectories so as not to extract the same combination by repeating the above-described processing focusing on each trajectory as the first-stage processing.
 なお、移動体とは、例えば、自動車、船、飛行機、無人搬送車などの移動する物体のことをさす。移動体は、上記例示した以外であってもよい。また、共通可能軌跡とは、例えば、物理的に共存可能(存在可能)な軌跡のことを指す。例えば、軌跡11と軌跡22とは共存可能だが、軌跡11と軌跡13とはフレーム1において移動体1が2つ存在することになるため共存不可能であり、共通可能軌跡とみなされない。共通可能軌跡は、物理的に共存可能な軌跡のうち移動距離が閾値内の軌跡、所定の特徴量を有する移動体間に形成される軌跡など、前処理などにおいて予め一部に限定されていてもよい。また、処理装置100が着目する軌跡の順番などは任意に定められてよい。 "Moving objects" refer to objects that move, such as cars, ships, airplanes, and unmanned guided vehicles. The moving body may be other than those exemplified above. Also, a common possible trajectory refers to, for example, a trajectory that can physically coexist (exist). For example, trajectory 11 and trajectory 22 can coexist, but trajectory 11 and trajectory 13 cannot coexist because there are two moving bodies 1 in frame 1, and are not considered common possible trajectories. Common possible trajectories may be partially limited in advance in preprocessing or the like, such as trajectories whose movement distance is within a threshold value among trajectories that can physically coexist, or trajectories formed between moving bodies having a predetermined feature amount. In addition, the order of trajectories that the processing device 100 pays attention to may be determined arbitrarily.
 また、1段目の処理の後、処理装置100は、2段目の処理として、1段目の処理において抽出した共通可能軌跡が示す各軌跡とさらに共通可能な軌跡である共通可能軌跡を、1段目と同様に同じ組み合わせを抽出しないように、抽出する。また、2段目について組み合わせを探索する処理が終了した後、処理装置100は、3段目の処理として、2段目の処理において抽出した共通可能軌跡が示す各軌跡とさらに共通可能な軌跡である共通可能軌跡を抽出する。以降、処理装置100は、組み合わせが抽出されなくなるまで同様の処理を繰り返す。なお、後述するように、本実施形態において説明する処理装置100は、2段目以降の抽出処理を、ベクトル化した上でベクトルエンジンなどのベクトル処理部130に行わせる。つまり、処理装置100は、2段目以降における組み合わせを探索する処理をベクトル化してベクトル処理部130に行わせる。また、上述したように、処理装置100は、同じ組み合わせを抽出しないように抽出処理を行う。そのため、後の段になるほど、また、同じ段であっても後に着目するほど、共通可能軌跡の数は減る。そこで、処理装置100は、着目の順番、処理の段数、ある軌跡における共通可能軌跡の数などの組み合わせを探索する処理の処理状況に応じて、ベクトル化の方法を変えることが出来る。なお、ベクトル化の方法を変える際の判断やベクトル化の方法の具体例については、後述する。 In addition, after the first-stage processing, the processing device 100, as the second-stage processing, extracts common possible trajectories that are further commonable trajectories to each trajectory indicated by the common possible trajectories extracted in the first-stage processing, so as not to extract the same combination as in the first-stage processing. Further, after the processing of searching for combinations in the second stage is completed, the processing device 100 extracts, as the processing of the third stage, common possible trajectories that are further commonable trajectories indicated by the common possible trajectories extracted in the second stage processing. After that, the processing device 100 repeats the same processing until no more combinations are extracted. As will be described later, the processing device 100 described in the present embodiment vectorizes the second and subsequent stages of extraction processing and causes the vector processing unit 130 such as a vector engine to perform the extraction processing. That is, the processing device 100 vectorizes the processing of searching for combinations in the second and subsequent stages, and causes the vector processing unit 130 to perform the processing. Further, as described above, the processing device 100 performs extraction processing so as not to extract the same combination. Therefore, the number of possible common trajectories decreases as the stage becomes later, or even in the same stage, as the attention is focused later. Therefore, the processing device 100 can change the vectorization method according to the processing status of searching for a combination of the order of attention, the number of stages of processing, the number of common possible trajectories in a given trajectory, and the like. It should be noted that specific examples of the judgment when changing the vectorization method and the vectorization method will be described later.
 図3は、処理装置100の構成例を示している。図3を参照すると、処理装置100は、例えば、記憶部110と、演算処理部120と、ベクトル処理部130と、を有している。また、処理装置100は、移動体を音波や電波などを用いて検出するセンサなどの外部装置と通信可能に接続されている。処理装置100は、センサなどの外部装置から当該センサなどがセンシングした結果などを受信することが出来る。 3 shows a configuration example of the processing device 100. FIG. Referring to FIG. 3, the processing device 100 has, for example, a storage unit 110, an arithmetic processing unit 120, and a vector processing unit . In addition, the processing device 100 is communicably connected to an external device such as a sensor that detects a moving object using sound waves or radio waves. The processing device 100 can receive the result of sensing by the sensor or the like from an external device such as a sensor.
 記憶部110は、ハードディスクやメモリなどの記憶装置である。記憶部110は、演算処理部120などにおける各種処理に必要な処理情報やプログラム112を記憶する。プログラム112は、演算処理部120に読み込まれて実行されることにより各種処理部を実現する。プログラム112は、処理装置100が有するデータ入出力機能を介して外部装置や記録媒体から予め読み込まれ、記憶部110に保存されている。記憶部110で記憶される主な情報としては、例えば、センシング情報111などがある。 The storage unit 110 is a storage device such as a hard disk or memory. The storage unit 110 stores processing information and programs 112 necessary for various processes in the arithmetic processing unit 120 and the like. The program 112 realizes various processing units by being read and executed by the arithmetic processing unit 120 . The program 112 is preloaded from an external device or recording medium via the data input/output function of the processing device 100 and stored in the storage unit 110 . Main information stored in the storage unit 110 includes sensing information 111, for example.
 センシング情報111は、センサなどの外部装置が検出した移動体の位置を示す情報(例えば、緯度経度情報などの位置情報)などを含んでいる。例えば、センシング情報111には、複数フレームにおける複数の移動体の位置を示す情報が含まれている。センシング情報111は、センサなどの外部装置からセンシング結果を示す情報を受信するたびに更新される。 The sensing information 111 includes information indicating the position of the moving object detected by an external device such as a sensor (for example, position information such as latitude and longitude information). For example, the sensing information 111 includes information indicating the positions of multiple moving objects in multiple frames. The sensing information 111 is updated each time information indicating a sensing result is received from an external device such as a sensor.
 演算処理部120は、プロセッサなどの演算装置とその周辺回路を有する。演算処理部120は、記憶部110からプログラム112を読み込んで実行することにより、上記ハードウェアとプログラム112とを協働させて各種処理部を実現する。演算処理部120で実現される主な処理部としては、例えば、軌跡判断部121と、ベクトル化方法判定部122と、ベクトル化実行部123と、がある。なお、演算処理部120で実現される各処理部のうち、少なくともベクトル化方法判定部122と、ベクトル化実行部123とは、例えば、演算処理部120がプログラム112などを読み込んで実行することにより実現されるコンパイラなどが有してよい。 The arithmetic processing unit 120 has an arithmetic device such as a processor and its peripheral circuits. The arithmetic processing unit 120 reads the program 112 from the storage unit 110 and executes it, so that the hardware and the program 112 cooperate to realize various processing units. Main processing units realized by the arithmetic processing unit 120 include, for example, a trajectory determination unit 121 , a vectorization method determination unit 122 , and a vectorization execution unit 123 . Among the processing units realized by the arithmetic processing unit 120, at least the vectorization method determination unit 122 and the vectorization execution unit 123 may include, for example, a compiler realized by the arithmetic processing unit 120 reading and executing the program 112 or the like.
 軌跡判断部121は、センシング情報111が示す複数フレームの移動体の位置情報に基づいて、移動体が移動した経路などの軌跡を例えば複数特定する。そして、軌跡判断部121は、特定した複数の軌跡に対して、上述した1段目の処理を行う。つまり、軌跡判断部121は、任意の軌跡に着目して着目した軌跡における共通可能軌跡を抽出する処理を特定した各軌跡について行う。この際、軌跡判断部121は、順序が異なるだけの同一の組み合わせを抽出しないように、共通可能軌跡を抽出する。また、軌跡判断部121は、抽出した共通可能軌跡が示す各軌跡を次の共通可能軌跡探索を行う処理対象に追加する。 The trajectory determination unit 121 identifies, for example, a plurality of trajectories such as paths traveled by the moving body based on the position information of the moving body in multiple frames indicated by the sensing information 111 . Then, the trajectory determination unit 121 performs the above-described first-stage processing on the plurality of identified trajectories. That is, the trajectory determination unit 121 performs processing for each specified trajectory to extract a common possible trajectory in the trajectory focused on an arbitrary trajectory. At this time, the trajectory determination unit 121 extracts common possible trajectories so as not to extract the same combination that differs only in order. Further, the trajectory determination unit 121 adds each trajectory indicated by the extracted common possible trajectories to the processing targets for the next common possible trajectory search.
 図4は、図1で例示したようなフレーム1とフレーム2において3つずつの移動体が検出された場合における軌跡判断部121の処理例を示している。図4を参照すると、例えば、軌跡判断部121は、軌跡22に着目する。そして、軌跡判断部121は、軌跡22と共通可能な軌跡である共通可能軌跡を抽出する。例えば、軌跡判断部121は、共通可能軌跡として、軌跡11、軌跡33、軌跡13、軌跡31を抽出する。次に、例えば、軌跡判断部121は、軌跡11に着目する。そして、軌跡判断部121は、既に抽出した組み合わせと同じ組み合わせを抽出しないように、軌跡11と共通可能な軌跡である共通可能軌跡を抽出する。例えば、図4で例示する場合、軌跡判断部121は、共通可能軌跡として軌跡33、軌跡23、軌跡32を抽出する一方で、既に抽出した組み合わせと同一の組み合わせになる軌跡22を抽出しない。 FIG. 4 shows a processing example of the trajectory determination unit 121 when three moving bodies are detected in each of frames 1 and 2 as illustrated in FIG. Referring to FIG. 4, the trajectory determination unit 121 focuses on the trajectory 22, for example. Then, the trajectory determination unit 121 extracts a common possible trajectory that is a trajectory that can be shared with the trajectory 22 . For example, the trajectory determination unit 121 extracts trajectory 11, trajectory 33, trajectory 13, and trajectory 31 as common possible trajectories. Next, for example, the trajectory determination unit 121 focuses on the trajectory 11 . Then, the trajectory determination unit 121 extracts a common possible trajectory, which is a trajectory that can be shared with the trajectory 11, so as not to extract the same combination as an already extracted combination. For example, in the case of FIG. 4, the trajectory determination unit 121 extracts trajectories 33, 23, and 32 as common possible trajectories, but does not extract trajectory 22 that is the same combination as the already extracted combination.
 例えば、軌跡判断部121は、軌跡33、軌跡21、軌跡23、……と、軌跡22と軌跡11以降も特定した各軌跡に着目して同様の処理を繰り返すことにより、同じ組み合わせを抽出しないように共通可能軌跡を抽出する。その後、軌跡判断部121は、抽出した共通可能軌跡が示す各軌跡を次の共通可能軌跡探索を行う処理対象に追加する。 For example, the trajectory determination unit 121 extracts common possible trajectories so as not to extract the same combination by repeating the same process focusing on each specified trajectory, such as trajectory 33, trajectory 21, trajectory 23, . After that, the trajectory determination unit 121 adds each trajectory indicated by the extracted common possible trajectories to the processing targets for the next common possible trajectory search.
 なお、上述したように、軌跡判断部121は、既に抽出した組み合わせと同じ組み合わせを抽出しない。そのため、図4で示すように、後に着目する軌跡ほど、同じ組み合わせの共有可能軌跡が以前に抽出されている可能性があり、実際に抽出される共有可能軌跡の数が減る。例えば、図4で例示する場合、軌跡判断部121は、軌跡31に着目した際に共有可能軌跡を抽出しない。これは、軌跡31と共有可能な軌跡の組み合わせは、軌跡31に着目する前に既にすべて抽出されているためである。 It should be noted that, as described above, the trajectory determination unit 121 does not extract the same combination as the already extracted combination. Therefore, as shown in FIG. 4, there is a possibility that the same combination of sharable trajectories has been previously extracted for trajectories that are focused on later, and the number of sharable trajectories that are actually extracted decreases. For example, in the case illustrated in FIG. 4 , the trajectory determination unit 121 does not extract a sharable trajectory when focusing on the trajectory 31 . This is because all combinations of trajectories 31 and sharable trajectories have already been extracted before focusing on trajectory 31 .
 また、軌跡判断部121は、例えば、演算処理部120がプログラム112を読み込んで実行することにより実現される前処理部による所定の前処理が行われた軌跡に対して、上述した1段目の処理を行うよう構成してもよい。例えば、前処理では、物理的に共存可能な軌跡のうち移動距離が閾値内の軌跡、所定の特徴量を有する移動体間に形成される軌跡など、ある軌跡と共通可能な共通可能軌跡を限定する処理などを行ってよい。このように、軌跡を示す情報を取得する取得部として機能する軌跡判断部121は、センシング情報111が示す複数フレームの移動体の位置情報に基づいて軌跡を示す情報を取得してもよいし、前処理部などの他の処理部から軌跡を示す情報を取得してもよい。 Further, the trajectory determination unit 121 may be configured to perform the above-described first-stage processing on the trajectory that has undergone predetermined preprocessing by the preprocessing unit realized by, for example, the arithmetic processing unit 120 reading and executing the program 112. For example, in the pre-processing, among trajectories that can physically coexist, a process of limiting common possible trajectories that can be shared with a certain trajectory, such as a trajectory whose moving distance is within a threshold or a trajectory formed between moving bodies having a predetermined feature amount, may be performed. In this way, the trajectory determination unit 121, which functions as an acquisition unit that acquires information indicating a trajectory, may acquire information indicating a trajectory based on the position information of a moving object in multiple frames indicated by the sensing information 111, or may acquire information indicating a trajectory from another processing unit such as a preprocessing unit.
 ベクトル化方法判定部122は、1つまたは複数の処理対象ごとに、組み合わせを探索する処理をベクトル化する方法を判定する判定部である。例えば、ベクトル化方法判定部122は、着目の順番、処理の段数、ある軌跡における共通可能軌跡の数、などの軌跡の組み合わせを探索する処理の処理状況に基づいて、予め定められた方法のうちいずれの方法を用いて組み合わせを探索する処理をベクトル化するか判定する。例えば、ベクトル化方法判定部122は、軌跡の組み合わせを探索する処理の処理状況に基づいて、第1の方法、第2の方法、第3の方法のうちのいずれかの方法を用いて組み合わせを探索する処理をベクトル化するか判定する。 The vectorization method determination unit 122 is a determination unit that determines a method for vectorizing the process of searching for a combination for each one or more processing targets. For example, the vectorization method determination unit 122 determines which of the predetermined methods should be used to vectorize the process of searching for a combination based on the processing status of the process of searching for a combination of trajectories, such as the order of attention, the number of stages of processing, and the number of common possible trajectories in a given trajectory. For example, the vectorization method determination unit 122 determines whether to vectorize the combination search process using any one of the first method, the second method, and the third method, based on the processing status of the process of searching for a combination of trajectories.
 ここで、第1の方法の概要について、図5を参照して説明する。図5を参照すると、第1の方法では、探索対象の段よりも1つ前の段である前段におけるある1つの軌跡に対応する共通可能軌跡が示す各軌跡について、さらに共通可能軌跡を探索して次の処理対象に追加する処理をベクトル化する。つまり、第1の方法では、1つの処理対象に対応する共通可能軌跡が示す各軌跡について組み合わせを探索する処理をベクトル化する。例えば、図5で例示する場合、前段である1段目において、軌跡22の共通可能軌跡として、軌跡11、軌跡33、軌跡13、軌跡31を抽出している。そのため、第1の方法では、軌跡11、軌跡33、軌跡13、軌跡31のそれぞれについて、さらに共通可能軌跡を探索して、探索した共通可能軌跡が示す各軌跡を次の処理対象とする処理をベクトル化する。 Here, an overview of the first method will be described with reference to FIG. Referring to FIG. 5, in the first method, for each trajectory indicated by a common possible trajectory corresponding to a certain trajectory in the previous stage, which is one stage before the search target stage, the process of searching for a common possible trajectory and adding it to the next processing target is vectorized. That is, in the first method, the process of searching for combinations of trajectories indicated by common possible trajectories corresponding to one processing target is vectorized. For example, in the case of FIG. 5, in the first stage, which is the preceding stage, trajectories 11, 33, 13, and 31 are extracted as common possible trajectories for trajectory 22. FIG. Therefore, in the first method, common possible trajectories are further searched for each of trajectory 11, trajectory 33, trajectory 13, and trajectory 31, and each trajectory indicated by the searched common possible trajectory is vectorized as the next processing target.
 また、図6は、第2の方法の概要を示している。図6を参照すると、第2の方法では、前段における複数の軌跡に対応する共通可能軌跡が示す各軌跡についてさらに共通可能軌跡を探索して次の処理対象に追加する処理をまとめて行う処理をベクトル化する。つまり、第2の方法では、複数の処理対象に対応する共通可能軌跡が示す各軌跡についてまとめて組み合わせを探索する処理をベクトル化する。例えば、図6で例示する場合、前段である1段目において、軌跡22の共通可能軌跡として、軌跡11、軌跡33、軌跡13、軌跡31を抽出している。また、図6で例示する場合、1段目において、軌跡11の共通可能軌跡として、軌跡33、軌跡23、軌跡32を抽出している。そのため、第2の方法では、軌跡22と共通可能な軌跡11、軌跡33、軌跡13、軌跡31のそれぞれと、軌跡11と共通可能な軌跡33、軌跡23、軌跡32それぞれについてさらに共通可能軌跡を探索して、探索した共通可能軌跡が示す各軌跡を次の処理対象に追加する処理をベクトル化する。なお、第2の方法においてまとめて処理する軌跡の数は任意に設定してよい。例えば、第2の方法においてまとめて処理する軌跡の数は、まとめて処理する軌跡それぞれに対応する共通可能軌跡の数の合計値などに応じて設定されてもよい。 Also, FIG. 6 shows an overview of the second method. Referring to FIG. 6, in the second method, for each trajectory indicated by the common possible trajectories corresponding to the plurality of trajectories in the previous stage, further search for common possible trajectories and adding them to the next processing target are performed collectively. That is, in the second method, the process of searching for combinations of trajectories indicated by common possible trajectories corresponding to a plurality of processing targets is vectorized. For example, in the case of FIG. 6, in the first stage, which is the preceding stage, trajectories 11, 33, 13, and 31 are extracted as common possible trajectories for trajectory 22. FIG. Further, in the case of FIG. 6, the trajectory 33, the trajectory 23, and the trajectory 32 are extracted as common possible trajectories of the trajectory 11 in the first stage. Therefore, in the second method, trajectories 11, 33, 13, and 31 that can be common to trajectory 22, and trajectories 33, 23, and 32 that can be common to trajectory 11 are further searched for common trajectories, and the process of adding each trajectory indicated by the searched common trajectory to the next processing target is vectorized. Note that the number of trajectories to be collectively processed in the second method may be set arbitrarily. For example, the number of trajectories to be collectively processed in the second method may be set according to the total number of common possible trajectories corresponding to the respective trajectories to be collectively processed.
 また、図7は、第3の方法の概要を示している。図7を参照すると、第3の方法では、第1の方法のうちの一部の処理をまとめて行う。例えば、第3の方法では、前段におけるある1つの軌跡に対応する共通可能軌跡が示す各軌跡についてさらに共通可能軌跡を探索する処理を複数回行った後、次の処理対象に追加する処理をまとめて行うように、組み合わせを探索する処理をベクトル化する。このように、第3の方法では、第1の方法のうち組み合わせを探索する処理を複数回行った後、探索した共通可能軌跡が示す各軌跡を次の処理対象に追加する処理をまとめて行うように、組み合わせを探索する処理をベクトル化する。 Also, FIG. 7 shows an overview of the third method. Referring to FIG. 7, the third method combines some of the processes of the first method. For example, in the third method, for each trajectory indicated by the common possible trajectory corresponding to one certain trajectory in the previous stage, the processing for searching for common possible trajectories is performed multiple times, and then the processing for searching for combinations is vectorized so that the processing for adding to the next processing target is performed collectively. In this way, in the third method, the process of searching for a combination is vectorized so that after performing the process of searching for a combination in the first method a plurality of times, the process of adding each trajectory indicated by the searched common possible trajectory to the next processing target is collectively performed.
 例えば、以上のように、ベクトル化方法判定部122は、組み合わせを探索する処理の処理状況に基づいて、上述したような第1の方法、第2の方法、第3の方法のうちのいずれの方法を用いて組み合わせを探索する処理をベクトル化するか判定する。ここで、図8は、処理状況に基づく判定の一例を説明するための図を示している。例えば、図8で示すように、処理の段数が後になるほど、前段において軌跡に対応する共有可能軌跡の数は少なくなる。そこで、例えば、ベクトル化方法判定部122は、処理の段数などに基づいて、第1の方法と第2の方法のうちのいずれの方法を用いてベクトル化するか判定することが出来る。例えば、ベクトル化方法判定部122は、処理の段数が所定値未満の場合に第1の方法でベクトル化すると判定する一方、処理の段数が所定値以上の場合に第2の方法でベクトル化すると判定する。換言すると、ベクトル化方法判定部122は、処理の段数などの処理状況に基づいて探索の対象となる軌跡(つまり、前段の共有可能軌跡の数)が十分多いと想定される場合に第1の方法で組み合わせを探索する処理をベクトル化すると判定する。一方、処理の段数などに基づいて探索の対象となる軌跡が少ないと想定される場合、ベクトル化方法判定部122は、第2の方法で組み合わせを探索する処理をベクトル化すると判定する。このように、ベクトル化方法判定部122は、処理の段数などの処理状況に基づいて判断される処理の量に基づいて、第1の方法と第2の方法のうちのいずれを用いてベクトル化を行うか判定することが出来る。 For example, as described above, the vectorization method determination unit 122 determines which of the above-described first method, second method, and third method should be used to vectorize the combination search process based on the processing status of the combination search process. Here, FIG. 8 shows a diagram for explaining an example of determination based on the processing status. For example, as shown in FIG. 8, the number of sharable trajectories corresponding to trajectories in the previous stage decreases as the number of processing stages becomes later. Therefore, for example, the vectorization method determination unit 122 can determine which of the first method and the second method should be used for vectorization based on the number of stages of processing. For example, the vectorization method determination unit 122 determines to vectorize by the first method when the number of processing stages is less than a predetermined value, and determines to vectorize by the second method when the number of processing stages is equal to or greater than the predetermined value. In other words, the vectorization method determination unit 122 determines to vectorize the process of searching for a combination by the first method when it is assumed that the number of trajectories to be searched (that is, the number of sharable trajectories in the previous stage) is sufficiently large based on the processing status such as the number of processing stages. On the other hand, when it is assumed that there are few trajectories to be searched based on the number of stages of processing, the vectorization method determination unit 122 determines to vectorize the processing of searching for combinations by the second method. In this way, the vectorization method determination unit 122 can determine which of the first method and the second method should be used for vectorization based on the amount of processing determined based on the processing status such as the number of stages of processing.
 また、例えば、図8で示すように、同じ段においても着目が遅くなるほど、軌跡に対応する共有可能軌跡の数は少なくなる。そこで、例えば、ベクトル化方法判定部122は、着目の順番などに基づいて、第1の方法と第3の方法のうちのいずれの方法を用いてベクトル化するか判定することが出来る。例えば、ベクトル化方法判定部122は、着目の順番が所定値未満の場合に第1の方法でベクトル化すると判定する一方、着目の順番が所定値以上の場合に第3の方法でベクトル化すると判定する。換言すると、ベクトル化方法判定部122は、着目の順番などに基づいて探索の対象となる軌跡が十分多いと想定される場合に第1の方法で組み合わせを探索する処理をベクトル化すると判定する。一方、着目の順番などに基づいて探索の対象となる軌跡が少ないと想定される場合、ベクトル化方法判定部122は、第3の方法で組み合わせを探索する処理をベクトル化すると判定する。このように、ベクトル化方法判定部122は、着目の順番などの処理状況に基づいて判断される処理の量に基づいて、第1の方法と第3の方法のうちのいずれを用いてベクトル化を行うか判定することが出来る。 Also, for example, as shown in FIG. 8, the number of sharable trajectories corresponding to the trajectory decreases as the focus is later, even in the same stage. Therefore, for example, the vectorization method determination unit 122 can determine which of the first method and the third method should be used for vectorization based on the order of attention. For example, the vectorization method determination unit 122 determines to vectorize by the first method when the order of attention is less than a predetermined value, and determines to vectorize by the third method when the order of attention is equal to or greater than the predetermined value. In other words, the vectorization method determination unit 122 determines to vectorize the process of searching for combinations by the first method when it is assumed that there are sufficiently many trajectories to be searched based on the order of attention. On the other hand, when it is assumed that there are few trajectories to be searched based on the order of attention, the vectorization method determination unit 122 determines to vectorize the process of searching for combinations by the third method. In this way, the vectorization method determination unit 122 can determine which of the first method and the third method should be used for vectorization based on the amount of processing determined based on the processing status such as the order of attention.
 例えば、ベクトル化方法判定部122は、上記判定方法のいずれか、または、上記判定方法を組み合わせて、第1の方法、第2の方法、第3の方法のうちのいずれの方法を用いて組み合わせを探索する処理をベクトル化するか判定することが出来る。ベクトル化方法判定部122は、例えば、処理の段数に基づいて第1の方法と第3の方法のうちのいずれの方法を用いてベクトル化するか判定する、前段における共有可能軌跡の数に基づいて第1の方法と第2の方法のいずれの方法を用いてベクトル化するか判定するなど、上記例示した方法の変形例などで判定を行ってもよい。 For example, the vectorization method determination unit 122 can determine whether to use any of the above determination methods or a combination of the above determination methods to vectorize the process of searching for a combination using the first method, the second method, or the third method. The vectorization method determination unit 122 may determine, for example, based on the number of stages of processing, which of the first method and the third method should be used for vectorization, and whether to use the first method or the second method for vectorization based on the number of sharable trajectories in the previous stage.
 なお、ベクトル化方法判定部122が上記判定を行うタイミングは任意に設定してよい。例えば、ベクトル化方法判定部122は、いずれの方法を用いてベクトル化を行うか段ごとに判断することが出来る。つまり、ベクトル化方法判定部122は、ある段についていずれの方法を用いてベクトル化を行うかまとめて判断することが出来る。ベクトル化方法判定部122は、ある方法を用いてベクトル化を行うと判定した結果に応じた処理が終わるごとに、次の1つまたは複数の軌跡に対応する共有可能軌跡について組み合わせを探索する処理をいずれの方法を用いてベクトル化するか判定してもよい。 The timing at which the vectorization method determination unit 122 makes the above determination may be set arbitrarily. For example, the vectorization method determination unit 122 can determine for each stage which method should be used for vectorization. That is, the vectorization method determination unit 122 can collectively determine which method is used for vectorization for a certain stage. The vectorization method determination unit 122 may determine which method should be used to vectorize the process of searching for a combination of sharable trajectories corresponding to the next one or more trajectories each time a process corresponding to the result of determining that vectorization should be performed using a certain method is completed.
 ベクトル化実行部123(ベクトル化部)は、ベクトル化方法判定部122の判定に応じて、組み合わせを探索する処理をベクトル化する。そして、ベクトル化実行部123は、ベクトル処理部130に対してベクトル処理を実行させる。なお、本実施形態で説明する方法は共通する組み合わせを確認する処理であるため、単純にはベクトル化することは出来ない。そこで、ベクトル化実行部123は、バッファを利用してベクトル化を行う。 The vectorization execution unit 123 (vectorization unit) vectorizes the process of searching for combinations according to the determination of the vectorization method determination unit 122 . Then, the vectorization execution unit 123 causes the vector processing unit 130 to execute vector processing. It should be noted that the method described in this embodiment is a process of confirming common combinations, so simple vectorization is not possible. Therefore, the vectorization execution unit 123 performs vectorization using a buffer.
 例えば、図9は、第1の方法でベクトル化する際の処理をより詳細に説明するための図である。図9を参照すると、ベクトル化実行部123は、まず、前段における軌跡の番号に対応するバッファを用意する。例えば、図5で例示するような2段目の処理の場合、前段である1段目には軌跡22、軌跡11、軌跡33、軌跡21、軌跡23、軌跡12、軌跡32、軌跡13、軌跡31が存在する。そこで、ベクトル化実行部123は、上記各軌跡の番号に対応するバッファを記憶部110などに用意する。 For example, FIG. 9 is a diagram for explaining in more detail the process of vectorization by the first method. Referring to FIG. 9, the vectorization execution unit 123 first prepares a buffer corresponding to the trajectory number in the previous stage. For example, in the case of the second stage of processing as illustrated in FIG. 5, the first stage, which is the preceding stage, includes trajectories 22, 11, 33, 21, 23, 12, 32, 13, and 31. Therefore, the vectorization execution unit 123 prepares buffers corresponding to the numbers of the trajectories in the storage unit 110 or the like.
 また、ベクトル化実行部123は、例えば、下記のような処理をベクトル処理部130に行わせるための命令を生成することでベクトル化を行う。
・用意されたバッファのうち前段の共通可能軌跡に対応するバッファに1を格納する。
・判定対象とする軌跡に対応する、前段の共通可能軌跡が示すバッファに1があるか確認して、1がある場合、判定対象とする軌跡の共通可能軌跡枠にバッファが1の番号を追加する
・各軌跡について同様の判定処理を行う
・共通可能軌跡枠に追加した番号が示す軌跡を次の処理対象とする
The vectorization execution unit 123 also performs vectorization by generating an instruction for causing the vector processing unit 130 to perform the following processing, for example.
• 1 is stored in the buffer corresponding to the common possible trajectory in the previous stage among the prepared buffers.
・Check if there is 1 in the buffer indicated by the preceding common possible trajectory corresponding to the trajectory to be judged, and if there is 1, the buffer adds the number of 1 to the common possible trajectory frame of the trajectory to be judged. ・Perform the same judgment process for each trajectory.
 一例として、図9で示すように、図5で例示するような2段目の処理の場合は下記のような命令となる。
・前段の共有可能軌跡である軌跡11、軌跡33、軌跡13、軌跡31に対応するバッファに1を格納する。
・判定対象とする軌跡11に対応する、前段の共通可能軌跡が示すバッファ(33、23、32)に1があるか確認して、1がある場合、判定対象とする軌跡の共通可能軌跡枠にバッファが1の番号を追加する。
(今回の場合、軌跡11、軌跡33、軌跡13、軌跡31に対応するバッファに1を格納するため、33のバッファに1がある。そのため、判定対象である軌跡11の共通可能軌跡枠に33が追加される)
・判定対象とする軌跡33に対応する、前段の共通可能軌跡が示すバッファ(21、12)に1があるか確認して、1がある場合、判定対象とする軌跡の共通可能軌跡枠にバッファが1の番号を追加する。
(今回の場合、軌跡11、軌跡33、軌跡13、軌跡31に対応するバッファに1を格納するため、21、12のバッファに1はない。そのため、判定対象である軌跡33の共通可能軌跡枠には共通可能軌跡がない旨を示すΦなどが追加される)
・判定対象とする軌跡13に対応する、前段の共通可能軌跡が示すバッファ(31)に1があるか確認して、1がある場合、判定対象とする軌跡の共通可能軌跡枠にバッファが1の番号を追加する。
(今回の場合、軌跡11、軌跡33、軌跡13、軌跡31に対応するバッファに1を格納するため、31のバッファに1がある。そのため、判定対象である軌跡13の共通可能軌跡枠に31が追加される)
・判定対象とする軌跡31に対応する、前段の共通可能軌跡は軌跡31と共有可能な軌跡の組み合わせがない旨を示している。そのため、以降の確認は行わない。
・共通可能軌跡枠に追加した番号が示す軌跡33、軌跡31を次の処理対象とする。
As an example, as shown in FIG. 9, in the case of the second-stage processing as illustrated in FIG. 5, the commands are as follows.
Store 1 in buffers corresponding to trajectory 11, trajectory 33, trajectory 13, and trajectory 31, which are sharable trajectories in the previous stage.
Check if there is 1 in the buffers (33, 23, 32) indicated by the previous common possible trajectory corresponding to the trajectory 11 to be determined, and if there is 1, the buffer adds the number of 1 to the common possible trajectory frame of the trajectory to be determined.
(In this case, 1 is stored in buffers corresponding to trajectory 11, trajectory 33, trajectory 13, and trajectory 31, so there is 1 in buffer 33. Therefore, 33 is added to the common possible trajectory frame of trajectory 11, which is the determination target.)
Check if there is a 1 in the buffers (21, 12) indicated by the preceding common possible trajectory corresponding to the trajectory 33 to be determined, and if there is 1, add the number of 1 to the common possible trajectory frame of the trajectory to be determined.
(In this case, 1 is stored in the buffers corresponding to trajectory 11, trajectory 33, trajectory 13, and trajectory 31, so there is no 1 in buffers 21 and 12. Therefore, Φ indicating that there is no common possible trajectory is added to the common possible trajectory frame of trajectory 33, which is the determination target.)
Check if there is 1 in the buffer (31) indicated by the previous common possible trajectory corresponding to the trajectory 13 to be determined, and if there is 1, the buffer adds the number of 1 to the common possible trajectory frame of the trajectory to be determined.
(In this case, 1 is stored in buffers corresponding to trajectory 11, trajectory 33, trajectory 13, and trajectory 31, so there is 1 in buffer 31. Therefore, 31 is added to the common possible trajectory frame of trajectory 13, which is the determination target.)
- The preceding common possible trajectory corresponding to the trajectory 31 to be determined indicates that there is no combination of the trajectory 31 and the sharable trajectory. Therefore, no further confirmation is performed.
- The trajectory 33 and the trajectory 31 indicated by the number added to the common possible trajectory frame are to be processed next.
 なお、ベクトル化実行部123は、バッファを用意する際、前段における軌跡の番号に対応するバッファを用意する。この際、ベクトル化実行部123は、前段において同一処理(複数の軌跡をまとめて処理した場合は、軌跡ごとの処理)により判定対象となった軌跡の番号に対応するバッファを用意することが出来る。例えば、図10は、3段目においてベクトル化実行部123が用意するバッファの一例を示している。図10を参照すると、3段目の処理において軌跡33や軌跡31についてさらに共通可能軌跡を探索する場合、前段において同一処理により判定対象となった軌跡は軌跡11、軌跡33、軌跡13、軌跡31である。そのため、ベクトル化実行部123は、上記各軌跡の番号に対応するバッファを記憶部110などに用意することが出来る。また、3段目の処理において軌跡32についてさらに共通可能軌跡を探索する場合、前段において同一処理により判定対象となった軌跡は軌跡33、軌跡23、軌跡32である。そのため、ベクトル化実行部123は、上記各軌跡の番号に対応するバッファを記憶部110などに用意することが出来る。 When preparing the buffer, the vectorization execution unit 123 prepares the buffer corresponding to the trajectory number in the previous stage. At this time, the vectorization execution unit 123 can prepare a buffer corresponding to the trajectory number determined by the same processing (processing for each trajectory when multiple trajectories are collectively processed) in the previous stage. For example, FIG. 10 shows an example of a buffer prepared by the vectorization execution unit 123 in the third stage. Referring to FIG. 10 , when searching for common possible trajectories for trajectory 33 and trajectory 31 in the processing of the third stage, the trajectories determined by the same processing in the previous stage are trajectories 11, 33, 13, and 31. Therefore, the vectorization execution unit 123 can prepare buffers corresponding to the numbers of the trajectories in the storage unit 110 or the like. Further, when searching for a common possible trajectory for trajectory 32 in the processing of the third stage, trajectories 33, 23, and 32 are the trajectories determined by the same processing in the previous stage. Therefore, the vectorization execution unit 123 can prepare buffers corresponding to the numbers of the trajectories in the storage unit 110 or the like.
 また、図11は、第2の方法でベクトル化する際の処理をより詳細に説明するための図である。図11を参照すると、ベクトル化実行部123は、まず、前段における軌跡の番号に対応する、同時に処理する軌跡の数に応じたベクトル長の数のバッファを用意する。例えば、図6で例示するような2段目の処理の場合、前段である1段目には軌跡22、軌跡11、軌跡33、軌跡21、軌跡23、軌跡12、軌跡32、軌跡13、軌跡31が存在する。また、図6で例示する場合、一例として同時に2つの軌跡を処理する。そこで、ベクトル化実行部123は、図11で示すように、上記各軌跡の番号に対応する、2行のバッファを記憶部110などに用意する。 Also, FIG. 11 is a diagram for explaining in more detail the process for vectorization by the second method. Referring to FIG. 11, the vectorization execution unit 123 first prepares a number of buffers corresponding to the number of the trajectory in the preceding stage and corresponding to the number of vector lengths corresponding to the number of trajectories to be processed simultaneously. For example, in the case of the second-stage processing illustrated in FIG. 6, the first stage, which is the preceding stage, includes trajectories 22, 11, 33, 21, 23, 12, 32, 13, and 31. Also, in the case illustrated in FIG. 6, two trajectories are processed at the same time as an example. Therefore, as shown in FIG. 11, the vectorization execution unit 123 prepares a two-line buffer in the storage unit 110 or the like corresponding to each trajectory number.
 また、ベクトル化実行部123は、例えば、下記のような処理をベクトル処理部130に行わせるための命令を生成することでベクトル化を行う。
・処理する軌跡に対応する行について、前段の共通可能軌跡に対応するバッファに1を格納する。
・バッファの各行について、判定対象とする軌跡に対応する、前段の共通可能軌跡が示すバッファに1があるか確認して、1がある場合、判定対象とする軌跡の共通可能軌跡枠にバッファが1の番号を追加する。
・各軌跡について同様の判定処理を行う
・共通可能軌跡枠に追加した番号が示す軌跡を次の処理対象とする
The vectorization execution unit 123 also performs vectorization by generating an instruction for causing the vector processing unit 130 to perform the following processing, for example.
Store 1 in the buffer corresponding to the previous common possible trajectory for the row corresponding to the trajectory to be processed.
For each row of the buffer, it is checked whether there is 1 in the buffer indicated by the preceding common possible trajectory corresponding to the trajectory to be determined, and if there is 1, the buffer adds the number of 1 to the common possible trajectory frame of the trajectory to be determined.
・Similar determination processing is performed for each trajectory. ・The trajectory indicated by the number added to the common possible trajectory frame is the next processing target.
 一例として、図11で示すように、図6で例示するような2段目の処理の場合は下記のような命令となる。
・バッファの1行目について、前段の共有可能軌跡である軌跡11、軌跡33、軌跡13、軌跡31に対応するバッファに1を格納する。また、バッファの2行目について、前段の共有可能軌跡である軌跡33、軌跡23、軌跡32に対応するバッファに1を格納する。
・バッファ1行目の33、2行目の21に1があるか確認して、1がある場合、判定対象とする軌跡の共通可能軌跡枠にバッファが1の番号を追加する。
(今回の場合、1行目33のバッファに1がある。そのため、判定対象である軌跡11の共通可能軌跡枠に33を追加する)
・バッファ1行目の23、2行目の12に1があるか確認して、1がある場合、判定対象とする軌跡の共通可能軌跡枠にバッファが1の番号を追加する。
(今回の場合、各バッファに1はない)
・バッファ1行目の32に1があるか確認して、1がある場合、判定対象とする軌跡の共通可能軌跡枠にバッファが1の番号を追加する。
(今回の場合、各バッファに1はない)
・判定対象の軌跡を軌跡33と軌跡23にして、同様の処理を行う。以下、各軌跡について同様の判定処理を行う
・共通可能軌跡枠に追加した番号が示す軌跡を次の処理対象とする
As an example, as shown in FIG. 11, in the case of the second stage processing as illustrated in FIG. 6, the following instructions are used.
For the first row of the buffer, 1 is stored in the buffers corresponding to trajectories 11, 33, 13, and 31, which are sharable trajectories in the previous stage. Also, for the second row of the buffer, 1 is stored in the buffer corresponding to the trajectory 33, trajectory 23, and trajectory 32, which are the sharable trajectories in the previous stage.
・Check if there is a 1 in 33 of the first line of the buffer and 21 of the second line.
(In this case, there is 1 in the buffer of 33 on the first line. Therefore, 33 is added to the common possible trajectory frame of trajectory 11 to be determined.)
・Check if there is a 1 in 23 on the first line of the buffer and 12 on the second line.
(In this case there is no 1 in each buffer)
・Check if there is a 1 in 32 of the first row of the buffer, and if there is a 1, the buffer adds the number of 1 to the common possible trajectory frame of the trajectory to be determined.
(In this case there is no 1 in each buffer)
The same process is performed with the trajectory 33 and the trajectory 23 as the trajectories to be determined. After that, the same judgment process is performed for each trajectory ・The trajectory indicated by the number added to the common possible trajectory frame is the next processing target
 また、図12は、第3の方法でベクトル化する際の処理をより詳細に説明するための図である。図12を参照すると、第3の方法では、第1の方法のうち判定処理までを複数の軌跡について行った後、上記複数の軌跡に対する判定処理の結果に基づいて同時に次の処理対象を追加する処理を行う旨を示す命令を生成することで、ベクトル化を行う。 Also, FIG. 12 is a diagram for explaining in more detail the process of vectorization by the third method. Referring to FIG. 12, in the third method, after performing the determination processing for a plurality of trajectories in the first method, vectorization is performed by generating an instruction indicating that the next processing target is to be added at the same time based on the results of the determination processing for the plurality of trajectories.
 例えば、上述したように、ベクトル化実行部123は、ベクトル化方法判定部122の判定に応じて、上述したような各方法に応じた命令を生成することで、ベクトル化を行う。そして、ベクトル化実行部123は、生成した命令を用いて、ベクトル処理部130に対してベクトル処理を実行させる。 For example, as described above, the vectorization execution unit 123 performs vectorization by generating instructions according to each method as described above according to the determination of the vectorization method determination unit 122 . Then, the vectorization execution unit 123 causes the vector processing unit 130 to execute vector processing using the generated instructions.
 ベクトル処理部130は、ベクトルプロセッサなどを有しており、ベクトル化実行部123からの命令に応じてベクトル処理を実行する。ベクトル処理部130は、既知のベクトルエンジンなどであってよい。 The vector processing unit 130 has a vector processor and the like, and executes vector processing according to instructions from the vectorization execution unit 123 . The vector processing unit 130 may be a known vector engine or the like.
 以上が、処理装置100の構成例である。続いて、図13を参照して、処理装置100の動作例について説明する。 The above is a configuration example of the processing device 100 . Next, an operation example of the processing device 100 will be described with reference to FIG. 13 .
 図13は、処理装置100の動作例を示すフローチャートである。図13を参照すると、軌跡判断部121は、センシング情報111が示す複数フレームの移動体の位置情報に基づいて、移動体が移動した経路などの軌跡を例えば複数特定する。そして、軌跡判断部121は、特定した複数の軌跡に対して、1段目の処理を行う。つまり、軌跡判断部121は、1段目について共通可能軌跡を抽出する(ステップS101)。 FIG. 13 is a flowchart showing an operation example of the processing device 100. FIG. Referring to FIG. 13 , the trajectory determination unit 121 identifies, for example, a plurality of trajectories such as paths traveled by the moving object, based on the position information of the moving object in multiple frames indicated by the sensing information 111 . Then, the trajectory determination unit 121 performs the first-stage process on the plurality of specified trajectories. That is, the trajectory determination unit 121 extracts a common possible trajectory for the first stage (step S101).
 ベクトル化方法判定部122は、軌跡の組み合わせを探索する処理の処理状況に基づいて、予め定められた方法のうちいずれの方法を用いて組み合わせを探索する処理をベクトル化するか判定する(ステップS102)。例えば、ベクトル化方法判定部122は、軌跡の組み合わせを探索する処理の処理状況に基づいて、第1の方法、第2の方法、第3の方法のうちのいずれかの方法を用いて組み合わせを探索する処理をベクトル化するか判定する。 The vectorization method determination unit 122 determines which of the predetermined methods should be used to vectorize the combination search process based on the processing status of the trajectory combination search process (step S102). For example, the vectorization method determination unit 122 determines whether to vectorize the combination search process using any one of the first method, the second method, and the third method, based on the processing status of the process of searching for a combination of trajectories.
 ベクトル化実行部123は、ベクトル化方法判定部122の判定に応じて、組み合わせを探索する処理をベクトル化する。そして、ベクトル化実行部123は、ベクトル処理部130に対してベクトル処理を実行させる(ステップS103)。 The vectorization execution unit 123 vectorizes the process of searching for combinations according to the determination of the vectorization method determination unit 122 . Then, the vectorization execution unit 123 causes the vector processing unit 130 to execute vector processing (step S103).
 ステップS103のベクトル処理の後、処理対象が終了した場合(ステップS104、Yes)、処理装置100は処理を終了する。一方、処理対象が存在する場合(ステップS104、No)、ベクトル化方法判定部122よるステップS102の判定に戻る。 After the vector processing in step S103, when the processing target is finished (step S104, Yes), the processing device 100 finishes the processing. On the other hand, if there is a process target (step S104, No), the vectorization method determination unit 122 returns to the determination of step S102.
 以上が、処理装置100の動作例である。 The above is an operation example of the processing device 100 .
 このように、処理装置100は、ベクトル化実行部123を有している。このような構成によると、ベクトル化実行部123は、軌跡の組み合わせを探索する処理をベクトル化してベクトル処理部130に行わせることが出来る。一般に、上記のような軌跡の組み合わせを探索する処理はメモリネックな処理である。そのため、メモリアクセスが高速なベクトル処理部130に処理を行わせることで、処理を高速化させることが出来る。換言すると、例えば、本実施形態で説明した方法によると、非特許文献3に記載されているようなグローバル仮説を生成する処理を並列化することが出来る。その結果、処理の高速化を実現することが出来る。 Thus, the processing device 100 has the vectorization execution unit 123 . With such a configuration, the vectorization execution unit 123 can vectorize the process of searching for a combination of trajectories and cause the vector processing unit 130 to perform the vectorization. In general, the process of searching for a combination of trajectories as described above is a memory bottleneck process. Therefore, the processing can be speeded up by causing the vector processing unit 130 with high memory access speed to perform the processing. In other words, for example, according to the method described in this embodiment, it is possible to parallelize the process of generating global hypotheses as described in Non-Patent Document 3. As a result, high speed processing can be realized.
 また、処理装置100は、ベクトル化方法判定部122を有している。このような構成によると、ベクトル化実行部123は、軌跡の組み合わせを探索する処理の処理状況に応じてベクトル化方法判定部122が判定した方法でベクトル化を実行することが出来る。軌跡の組み合わせを探索する処理では、同じ組み合わせを抽出しないように探索処理を行うため、後の段になるほど、また、同じ段であっても後に着目するほど、共通可能軌跡の数が減る。そのため、軌跡の組み合わせを探索する処理の処理状況に応じて判定される方法によりベクトル化を行うことで、ベクトル処理の効率を向上させることが出来る。 The processing device 100 also has a vectorization method determination unit 122 . With such a configuration, the vectorization execution unit 123 can execute vectorization by the method determined by the vectorization method determination unit 122 according to the processing status of the process of searching for a combination of trajectories. In the process of searching for a combination of trajectories, since the search process is performed so as not to extract the same combination, the number of possible common trajectories decreases as the stage becomes later, or even in the same stage, the later the attention is paid. Therefore, the efficiency of vector processing can be improved by performing vectorization by a method determined according to the processing status of processing for searching for a combination of trajectories.
 なお、本実施形態で説明した処理装置100は、上述したように、同時に選択可能な軌跡の組み合わせを探索する。処理装置100が行う探索の結果は、例えば、移動体の追跡を行う際などに活用することが出来る。処理装置100が行う探索の結果は、移動体の追跡以外の場面で活用されてもよい。 It should be noted that the processing device 100 described in the present embodiment searches for combinations of simultaneously selectable trajectories, as described above. The result of the search performed by the processing device 100 can be used, for example, when tracking a moving object. The result of the search performed by the processing device 100 may be used in situations other than tracking the moving object.
[第2の実施形態]
 次に、本開示の第2の実施形態について、図14、図15を参照して説明する。図14は、処理装置200のハードウェア構成例を示す図である。図15は、処理装置200の構成例を示すブロック図である。
[Second embodiment]
Next, a second embodiment of the present disclosure will be described with reference to FIGS. 14 and 15. FIG. FIG. 14 is a diagram showing a hardware configuration example of the processing device 200. As shown in FIG. FIG. 15 is a block diagram showing a configuration example of the processing device 200. As shown in FIG.
 本開示の第2の実施形態においては、軌跡などの組み合わせを探索する情報処理装置である処理装置200について説明する。図14は、処理装置200のハードウェア構成例を示している。図14を参照すると、処理装置200は、一例として、以下のようなハードウェア構成を有している。
・処理をベクトル化してベクトル処理部に処理させる処理管理部として機能するプロセッサ(CPU:Central Processing Unit)201
・ベクトル処理を行うベクトル処理部として機能するベクトルプロセッサ202
・プログラム群204を格納する記憶装置203
 なお、処理装置200は、ROM(Read Only Memory)、RAM(Random Access Memory)、情報処理装置外部の記録媒体の読み書きを行うドライブ装置、情報処理装置外部の通信ネットワークと接続する通信インタフェース、データの入出力を行う入出力インタフェース、各構成要素を接続するバスなどを有してもよい。
In the second embodiment of the present disclosure, a processing device 200, which is an information processing device that searches for combinations of trajectories and the like, will be described. FIG. 14 shows a hardware configuration example of the processing device 200 . Referring to FIG. 14, the processing device 200 has the following hardware configuration as an example.
A processor (CPU: Central Processing Unit) 201 that functions as a processing management unit that vectorizes processing and causes the vector processing unit to process it.
A vector processor 202 that functions as a vector processing unit that performs vector processing
- Storage device 203 for storing program group 204
The processing device 200 may include a ROM (Read Only Memory), a RAM (Random Access Memory), a drive device for reading and writing to a recording medium outside the information processing device, a communication interface for connecting to a communication network outside the information processing device, an input/output interface for inputting and outputting data, a bus for connecting each component, and the like.
 また、処理装置200は、プログラム群204をプロセッサ201が取得して当該プロセッサ201が実行することで、図15に示す取得部221、ベクトル化部222としての機能を実現することが出来る。なお、プログラム群204は、例えば、予め記憶装置203や処理装置200が有するROMなどに格納されており、必要に応じてプロセッサ201がRAMなどにロードして実行する。また、プログラム群204は、通信ネットワークを介してプロセッサ201に供給されてもよいし、予め記録媒体に格納されており、ドライブ装置が該プログラムを読み出してプロセッサ201に供給してもよい。 Also, the processor 201 acquires the program group 204 and the processor 201 executes it, so that the processing device 200 can realize the functions of the acquisition unit 221 and the vectorization unit 222 shown in FIG. The program group 204 is stored in advance in, for example, the storage device 203 or the ROM of the processing device 200, and is loaded into the RAM or the like by the processor 201 as necessary and executed. Also, the program group 204 may be supplied to the processor 201 via a communication network, or may be stored in a recording medium in advance, and the drive device may read the program and supply it to the processor 201 .
 なお、図14は、処理装置200のハードウェア構成例を示している。処理装置200のハードウェア構成は上述した場合に限定されない。 Note that FIG. 14 shows a hardware configuration example of the processing device 200 . The hardware configuration of the processing device 200 is not limited to that described above.
 取得部221は、移動体のセンシング結果に基づいて特定される、移動体が移動した経路である軌跡を示す情報を取得する。例えば、取得部221は、移動体のセンシング結果が示す移動体の位置情報などに基づいて軌跡を示す情報を取得してもよい。 The acquisition unit 221 acquires information indicating a trajectory, which is a route traveled by the mobile body, specified based on the sensing result of the mobile body. For example, the acquisition unit 221 may acquire information indicating the trajectory based on the position information of the moving object indicated by the sensing result of the moving object.
 ベクトル化部222は、取得部221が取得した軌跡の組み合わせを探索する処理をベクトル化してベクトル処理部に実行させる。例えば、ベクトル化部222は、バッファを利用して軌跡と共通可能な軌跡である共通可能軌跡を抽出する命令を生成することで、軌跡の組み合わせを探索する処理をベクトル化してもよい。 The vectorization unit 222 vectorizes the process of searching for a combination of trajectories acquired by the acquisition unit 221 and causes the vector processing unit to execute it. For example, the vectorization unit 222 may vectorize the process of searching for a combination of trajectories by generating an instruction for extracting a common possible trajectory, which is a trajectory that can be shared with a trajectory, using a buffer.
 このように、処理装置200は、ベクトル化部222を有している。このような構成によると、ベクトル化部222は、軌跡の組み合わせを探索する処理をベクトル化してベクトル処理部に行わせることが出来る。一般に、上記のような軌跡の組み合わせを探索する処理はメモリネックな処理である。そのため、メモリアクセスが高速なベクトル処理部に処理を行わせることで、処理を高速化させることが出来る。 Thus, the processing device 200 has the vectorization section 222 . With such a configuration, the vectorization unit 222 can vectorize the process of searching for a combination of trajectories and cause the vector processing unit to perform the vectorization. In general, the process of searching for a combination of trajectories as described above is a memory bottleneck process. Therefore, the processing can be speeded up by allowing the vector processing unit with high memory access speed to perform the processing.
 なお、上述した処理装置200は、当該処理装置200などの情報処理装置に所定のプログラムが組み込まれることで実現できる。具体的に、本発明の他の形態であるプログラムは、移動体のセンシング結果に基づいて特定される、移動体が移動した経路である軌跡を示す情報を取得し、取得した軌跡の組み合わせを探索する処理をベクトル化してベクトル処理部に実行させる、処理を実現させるためのプログラムである。 Note that the processing device 200 described above can be realized by installing a predetermined program in an information processing device such as the processing device 200 . Specifically, a program that is another aspect of the present invention is a program that acquires information indicating a trajectory, which is a route traveled by a mobile body, specified based on the sensing result of the mobile body, vectorizes a process of searching for a combination of the acquired trajectories, and causes a vector processing unit to execute the process.
 また、上述した処理装置200などの情報処理装置により実行される処理方法は、移動体のセンシング結果に基づいて特定される、移動体が移動した経路である軌跡を示す情報を取得し、取得した軌跡の組み合わせを探索する処理をベクトル化してベクトル処理部に実行させる、という方法である。 In addition, the processing method executed by an information processing device such as the processing device 200 described above is a method of acquiring information indicating a trajectory, which is a route traveled by a moving object, which is specified based on the sensing result of the moving object, vectorizing a process of searching for a combination of the acquired trajectories, and causing a vector processing unit to execute the processing.
 上述した構成を有する、プログラム、又は、プログラムを記録したコンピュータが読み取り可能な記録媒体、又は、処理方法、の発明であっても、上述した処理装置200と同様の作用・効果を有するために、上述した本発明の目的を達成することが出来る。 Even the invention of the program, the computer-readable recording medium recording the program, or the processing method having the above-described configuration can achieve the above-described object of the present invention because it has the same actions and effects as the above-described processing apparatus 200.
 <付記>
 上記実施形態の一部又は全部は、以下の付記のようにも記載されうる。以下、本発明における処理装置などの概略を説明する。但し、本発明は、以下の構成に限定されない。
<Appendix>
Some or all of the above embodiments may also be described as the following appendices. The outline of the processing apparatus and the like in the present invention will be described below. However, the present invention is not limited to the following configurations.
(付記1)
 移動体のセンシング結果に基づいて特定される、前記移動体が移動した経路である軌跡を示す情報を取得する取得部と、
 前記取得部が取得した軌跡の組み合わせを探索する処理をベクトル化してベクトル処理部に実行させるベクトル化部と、
 を有する処理装置。
(付記2)
 付記1に記載の処理装置であって、
 前記ベクトル化部は、バッファを利用して軌跡と共通可能な軌跡である共通可能軌跡を抽出する命令を生成することで、軌跡の組み合わせを探索する処理をベクトル化する
 処理装置。
(付記3)
 付記1または付記2に記載の処理装置であって、
 軌跡の組み合わせを探索する処理の処理状況に基づいて、予め定められた方法のうちいずれの方法を用いて軌跡の組み合わせを探索する処理をベクトル化するか判定する判定部を有し、
 前記ベクトル化部は、前記判定部による判定の結果に応じて軌跡の組み合わせを探索する処理をベクトル化する
 処理装置。
(付記4)
 付記3に記載の処理装置であって、
 前記判定部は、軌跡の組み合わせを探索する処理の処理状況に基づいて、1つの処理対象に対応する共通可能軌跡が示す各軌跡について組み合わせを探索する処理をベクトル化する第1の方法と、複数の処理対象に対応する共通可能軌跡が示す各軌跡について組み合わせを探索する処理をベクトル化する第2の方法と、のうちのいずれの方法を用いてベクトル化を行うか判定する
 処理装置。
(付記5)
 付記4に記載の処理装置であって、
 前記判定部は、軌跡の組み合わせを探索する処理の処理状況に基づいて判断される処理の量に応じて、前記第1の方法と前記第2の方法のうちのいずれの方法を用いてベクトル化を行うか判定する
 処理装置。
(付記6)
 付記3から付記5までのうちのいずれか1項に記載の処理装置であって、
 前記判定部は、前記軌跡の組み合わせを探索する処理の処理状況に基づいて、1つの処理対象に対応する共通可能軌跡が示す各軌跡について組み合わせを探索する処理をベクトル化する第1の方法と、1つの処理対象に対応する共通可能軌跡が示す各軌跡について行う組み合わせの探索を複数回行った後に探索した結果に応じて処理対象をまとめて追加する処理を行う処理をベクトル化する第3の方法と、のうちのいずれの方法を用いてベクトル化を行うか判定する
 処理装置。
(付記7)
 付記6に記載の処理装置であって、
 前記判定部は、軌跡の組み合わせを探索する処理の処理状況に基づいて判断される処理の量に応じて、前記第1の方法と前記第3の方法のうちのいずれの方法を用いてベクトル化を行うか判定する
 処理装置。
(付記8)
 付記1から付記7までのうちのいずれか1項に記載の処理装置であって、
 前記取得部が取得した各軌跡について、軌跡と共通可能な共通可能軌跡を抽出する判断部を有し、
 前記ベクトル化部は、前記共通可能軌跡が示す軌跡についてさらに共通可能軌跡を探索する処理をベクトル化する
 処理装置。
(付記9)
 情報処理装置が、
 移動体のセンシング結果に基づいて特定される、前記移動体が移動した経路である軌跡を示す情報を取得し、
 取得した軌跡の組み合わせを探索する処理をベクトル化してベクトル処理部に実行させる
 処理方法。
(付記10)
 情報処理装置に、
 移動体のセンシング結果に基づいて特定される、前記移動体が移動した経路である軌跡を示す情報を取得し、
 取得した軌跡の組み合わせを探索する処理をベクトル化してベクトル処理部に実行させる
 処理を実現するためのプログラムを記録した、コンピュータが読み取り可能な記録媒体。
(Appendix 1)
an acquisition unit that acquires information indicating a trajectory, which is a route traveled by the mobile object, that is specified based on a sensing result of the mobile object;
a vectorization unit that vectorizes a process of searching for a combination of trajectories acquired by the acquisition unit and causes a vector processing unit to execute the process;
A processing device having
(Appendix 2)
The processing apparatus according to Appendix 1,
The vectorization unit vectorizes a process of searching for a combination of trajectories by generating an instruction for extracting a common possible trajectory, which is a trajectory that can be shared with a trajectory, using a buffer.
(Appendix 3)
The processing apparatus according to Appendix 1 or Appendix 2,
a determination unit that determines whether to vectorize the process of searching for a combination of trajectories using a predetermined method based on the processing status of the process of searching for a combination of trajectories;
The processing device, wherein the vectorization unit vectorizes a process of searching for a combination of trajectories according to the determination result of the determination unit.
(Appendix 4)
The processing device according to Appendix 3,
The determining unit determines which of a first method of vectorizing a process of searching for a combination of trajectories indicated by a common possible trajectory corresponding to one processing target and a second method of vectorizing a process of searching for a combination of each trajectory indicated by the common possible trajectories corresponding to a plurality of processing targets based on the processing status of the processing of searching for a combination of trajectories.
(Appendix 5)
The processing device according to Appendix 4,
The determination unit determines which of the first method and the second method is used for vectorization according to the amount of processing determined based on the processing status of processing for searching for a combination of trajectories. Processing device.
(Appendix 6)
The processing apparatus according to any one of appendices 3 to 5,
Based on the processing status of the process of searching for a combination of trajectories, the determination unit determines which of a first method of vectorizing a process of searching for a combination of trajectories indicated by a common possible trajectory corresponding to one processing target, and a third method of vectorizing a process of performing a process of collectively adding processing targets according to the search result after performing multiple searches for combinations of each trajectory indicated by the common possible trajectory corresponding to one processing target.
(Appendix 7)
The processing device according to Appendix 6,
The determination unit determines which of the first method and the third method is used for vectorization according to the amount of processing determined based on the processing status of processing for searching for a combination of trajectories. Processing device.
(Appendix 8)
The processing apparatus according to any one of Supplements 1 to 7,
a determination unit that extracts a common possible trajectory that can be shared with each trajectory acquired by the acquisition unit;
The vectorization unit vectorizes a process of further searching for a common possible trajectory for the trajectory indicated by the common possible trajectory.
(Appendix 9)
The information processing device
Acquiring information indicating a trajectory, which is a route traveled by the moving object, which is specified based on the sensing result of the moving object;
A processing method in which the process of searching for combinations of acquired trajectories is vectorized and executed by the vector processing unit.
(Appendix 10)
information processing equipment,
Acquiring information indicating a trajectory, which is a route traveled by the moving object, which is specified based on the sensing result of the moving object;
A computer-readable recording medium recording a program for vectorizing a process of searching for a combination of acquired trajectories and causing the vector processing unit to execute the process.
 以上、上記各実施形態を参照して本願発明を説明したが、本願発明は、上述した実施形態に限定されるものではない。本願発明の構成や詳細には、本願発明の範囲内で当業者が理解しうる様々な変更をすることが出来る。 Although the present invention has been described with reference to the above-described embodiments, the present invention is not limited to the above-described embodiments. Various changes that can be understood by those skilled in the art can be made to the configuration and details of the present invention within the scope of the present invention.
100 処理装置
110 記憶部
111 センシング情報
112 プログラム
120 演算処理部
121 軌跡判断部
122 ベクトル化方法判定部
123 ベクトル化実行部
130 ベクトル処理部
200 処理装置
201 プロセッサ
202 ベクトルプロセッサ
203 記憶装置
204 プログラム群
221 取得部
222 ベクトル化部
100 processing device 110 storage unit 111 sensing information 112 program 120 arithmetic processing unit 121 trajectory determination unit 122 vectorization method determination unit 123 vectorization execution unit 130 vector processing unit 200 processing device 201 processor 202 vector processor 203 storage device 204 program group 221 acquisition unit 222 vectorization unit

Claims (10)

  1.  移動体のセンシング結果に基づいて特定される、前記移動体が移動した経路である軌跡を示す情報を取得する取得部と、
     前記取得部が取得した軌跡の組み合わせを探索する処理をベクトル化してベクトル処理部に実行させるベクトル化部と、
     を有する処理装置。
    an acquisition unit that acquires information indicating a trajectory, which is a route traveled by the mobile object, that is specified based on a sensing result of the mobile object;
    a vectorization unit that vectorizes a process of searching for a combination of trajectories acquired by the acquisition unit and causes a vector processing unit to execute the process;
    A processing device having
  2.  請求項1に記載の処理装置であって、
     前記ベクトル化部は、バッファを利用して軌跡と共通可能な軌跡である共通可能軌跡を抽出する命令を生成することで、軌跡の組み合わせを探索する処理をベクトル化する
     処理装置。
    The processing apparatus according to claim 1,
    The vectorization unit vectorizes a process of searching for a combination of trajectories by generating an instruction for extracting a common possible trajectory, which is a trajectory that can be shared with a trajectory, using a buffer.
  3.  請求項1または請求項2に記載の処理装置であって、
     軌跡の組み合わせを探索する処理の処理状況に基づいて、予め定められた方法のうちいずれの方法を用いて軌跡の組み合わせを探索する処理をベクトル化するか判定する判定部を有し、
     前記ベクトル化部は、前記判定部による判定の結果に応じて軌跡の組み合わせを探索する処理をベクトル化する
     処理装置。
    The processing apparatus according to claim 1 or claim 2,
    a determination unit that determines whether to vectorize the process of searching for a combination of trajectories using a predetermined method based on the processing status of the process of searching for a combination of trajectories;
    The processing device, wherein the vectorization unit vectorizes a process of searching for a combination of trajectories according to the determination result of the determination unit.
  4.  請求項3に記載の処理装置であって、
     前記判定部は、軌跡の組み合わせを探索する処理の処理状況に基づいて、1つの処理対象に対応する共通可能軌跡が示す各軌跡について組み合わせを探索する処理をベクトル化する第1の方法と、複数の処理対象に対応する共通可能軌跡が示す各軌跡について組み合わせを探索する処理をベクトル化する第2の方法と、のうちのいずれの方法を用いてベクトル化を行うか判定する
     処理装置。
    A processing apparatus according to claim 3,
    The determining unit determines which of a first method of vectorizing a process of searching for a combination of trajectories indicated by a common possible trajectory corresponding to one processing target and a second method of vectorizing a process of searching for a combination of each trajectory indicated by the common possible trajectories corresponding to a plurality of processing targets based on the processing status of the processing of searching for a combination of trajectories.
  5.  請求項4に記載の処理装置であって、
     前記判定部は、軌跡の組み合わせを探索する処理の処理状況に基づいて判断される処理の量に応じて、前記第1の方法と前記第2の方法のうちのいずれの方法を用いてベクトル化を行うか判定する
     処理装置。
    A processing apparatus according to claim 4,
    The determination unit determines which of the first method and the second method is used for vectorization according to the amount of processing determined based on the processing status of processing for searching for a combination of trajectories. Processing device.
  6.  請求項3から請求項5までのうちのいずれか1項に記載の処理装置であって、
     前記判定部は、前記軌跡の組み合わせを探索する処理の処理状況に基づいて、1つの処理対象に対応する共通可能軌跡が示す各軌跡について組み合わせを探索する処理をベクトル化する第1の方法と、1つの処理対象に対応する共通可能軌跡が示す各軌跡について行う組み合わせの探索を複数回行った後に探索した結果に応じて処理対象をまとめて追加する処理を行う処理をベクトル化する第3の方法と、のうちのいずれの方法を用いてベクトル化を行うか判定する
     処理装置。
    A processing apparatus according to any one of claims 3 to 5,
    Based on the processing status of the process of searching for combinations of trajectories, the determining unit determines which of the first method of vectorizing the process of searching for a combination of trajectories indicated by the common possible trajectories corresponding to one processing target, and the third method of vectorizing the processing of performing a process of collectively adding processing targets according to the search results after performing multiple searches for combinations of each trajectory indicated by the common possible trajectories corresponding to one processing target.
  7.  請求項6に記載の処理装置であって、
     前記判定部は、軌跡の組み合わせを探索する処理の処理状況に基づいて判断される処理の量に応じて、前記第1の方法と前記第3の方法のうちのいずれの方法を用いてベクトル化を行うか判定する
     処理装置。
    A processing apparatus according to claim 6,
    The determination unit determines which of the first method and the third method is used for vectorization according to the amount of processing determined based on the processing status of processing for searching for a combination of trajectories. Processing device.
  8.  請求項1から請求項7までのうちのいずれか1項に記載の処理装置であって、
     前記取得部が取得した各軌跡について、軌跡と共通可能な共通可能軌跡を抽出する判断部を有し、
     前記ベクトル化部は、前記共通可能軌跡が示す軌跡についてさらに共通可能軌跡を探索する処理をベクトル化する
     処理装置。
    A processing apparatus according to any one of claims 1 to 7,
    a determination unit that extracts a common possible trajectory that can be shared with each trajectory acquired by the acquisition unit;
    The vectorization unit vectorizes a process of further searching for a common possible trajectory for the trajectory indicated by the common possible trajectory.
  9.  情報処理装置が、
     移動体のセンシング結果に基づいて特定される、前記移動体が移動した経路である軌跡を示す情報を取得し、
     取得した軌跡の組み合わせを探索する処理をベクトル化してベクトル処理部に実行させる
     処理方法。
    The information processing device
    Acquiring information indicating a trajectory, which is a route traveled by the moving body, which is specified based on the sensing result of the moving body;
    A processing method in which the process of searching for combinations of acquired trajectories is vectorized and executed by the vector processing unit.
  10.  情報処理装置に、
     移動体のセンシング結果に基づいて特定される、前記移動体が移動した経路である軌跡を示す情報を取得し、
     取得した軌跡の組み合わせを探索する処理をベクトル化してベクトル処理部に実行させる
     処理を実現するためのプログラムを記録した、コンピュータが読み取り可能な記録媒体。
    information processing equipment,
    Acquiring information indicating a trajectory, which is a route traveled by the moving body, which is specified based on the sensing result of the moving body;
    A computer-readable recording medium recording a program for vectorizing a process of searching for a combination of acquired trajectories and causing the vector processing unit to execute the process.
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Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JPH11120166A (en) * 1997-10-20 1999-04-30 Fujitsu Ltd Vectorization device and storage medium
JP2019530608A (en) * 2016-09-29 2019-10-24 ザ・チャールズ・スターク・ドレイパー・ラボラトリー・インコーポレイテッド Autonomous vehicle with object level fusion
JP2020015493A (en) * 2018-07-17 2020-01-30 バイドゥ ユーエスエイ エルエルシーBaidu USA LLC Methods and systems to predict object movement for autonomous driving vehicles

Patent Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JPH11120166A (en) * 1997-10-20 1999-04-30 Fujitsu Ltd Vectorization device and storage medium
JP2019530608A (en) * 2016-09-29 2019-10-24 ザ・チャールズ・スターク・ドレイパー・ラボラトリー・インコーポレイテッド Autonomous vehicle with object level fusion
JP2020015493A (en) * 2018-07-17 2020-01-30 バイドゥ ユーエスエイ エルエルシーBaidu USA LLC Methods and systems to predict object movement for autonomous driving vehicles

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