Data processing device, data processing method, program, and data processing system

Abstract

Reduce the time required to process measurement data. [Solution] The data processing device according to this disclosure acquires received intensity data representing the received intensity of a signal reflected at a measurement point located at a distance from the target vehicle for each of a plurality of distances, identifies a nearby measurement point which is a measurement point located within a first predetermined distance from the target vehicle, and if the nearby measurement point satisfies predetermined data reduction conditions, identifies the data shown in the received intensity data that corresponds to a distance within a second predetermined distance from the target vehicle as the data to be analyzed.

Description

Technical Field

[0001] The present disclosure relates to a data processing apparatus, a data processing method, a program, and a data processing system.

Background Art

[0002] Techniques for processing data obtained from a distance measuring sensor provided in a vehicle have been developed. For example, the radar ECU (Electronic Control Unit) disclosed in Patent Document 1 calculates the distance to an obstacle using the data obtained from the radar, and notifies the driving support ECU of the calculation result.

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] When the amount of measurement data obtained from the distance measuring sensor is large, it takes time to process the measurement data. Patent Document 1 does not mention the time required for processing the measurement data.

Means for Solving the Problems

[0005] The data processing apparatus according to one embodiment specifies a short-distance measurement point, which is a measurement point located within a first predetermined distance from the target vehicle, based on reception intensity data representing the reception intensity of signals reflected at measurement points each separated from the target vehicle by a plurality of distances. Further, when the short-distance measurement point satisfies a predetermined condition, the data processing apparatus specifies, as data to be analyzed, data corresponding to distances within a second predetermined distance from the target vehicle among the data indicated by the reception intensity data.

Effects of the Invention

[0006] According to the above embodiment, a technique is provided for reducing the time required to process measurement data. [Brief explanation of the drawing]

[0007] [Figure 1] This diagram illustrates the general operation of a data processing device. [Figure 2] This is a block diagram illustrating the functional configuration of a data processing device. [Figure 3] This is a block diagram illustrating the hardware configuration of a computer that implements a data processing device. [Figure 4] This is a flowchart illustrating the processing flow performed by a data processing device. [Figure 5] This flowchart illustrates the flow of the process for identifying the target of analysis, which is performed repeatedly. [Figure 6] This diagram illustrates the functional configuration of a data processing device 2000 having an output unit. [Modes for carrying out the invention]

[0008] Embodiments of the present disclosure will be described in detail below with reference to the drawings. In each drawing, the same or corresponding elements are denoted by the same reference numerals, and redundant explanations are omitted as necessary for clarity. Unless otherwise specified, predetermined values ​​such as specified values ​​and thresholds are stored in advance in a storage device accessible from the device that uses those values. Furthermore, unless otherwise specified, the storage unit is composed of one or any number of storage devices.

[0009] <Overview> Figure 1 illustrates an overview of the operation of the data processing device 2000. Herein, Figure 1 is intended to facilitate understanding of the overview of the data processing device 2000, and the operation of the data processing device 2000 is not limited to what is shown in Figure 1.

[0010] The data processing device 2000 handles the received intensity data 30 obtained from the sensor 20. The sensor 20 is any sensor that uses signals to measure distance. For example, the sensor 20 may be a millimeter-wave radar or a LiDAR (Light Detection and Ranging) sensor.

[0011] The sensor 20 is installed on the target vehicle 10. The target vehicle 10 is any vehicle, such as an automobile or a motorcycle. The received intensity data 30 obtained from the sensor 20 is used, for example, to control the target vehicle 10. In this case, the target vehicle 10 may be a fully autonomous vehicle that does not require driver operation, or it may be a vehicle in which some operations are assisted by a computer (for example, ADAS (advanced driver-assistance systems)).

[0012] In Figure 1, the sensor 20 is positioned to face forward of the target vehicle 10. However, the orientation of the sensor 20 is not limited to facing forward of the target vehicle 10, but can be any direction. Furthermore, if the target vehicle 10 is equipped with multiple distance measuring sensors, the data processing device 2000 can treat each of these multiple distance measuring sensors as sensor 20.

[0013] Sensor 20 generates received intensity data 30 by transmitting a signal and receiving the reflected signal. The signal transmitted by sensor 20 is, for example, an electromagnetic wave such as a millimeter wave or a laser.

[0014] The received signal strength data 30 indicates the strength of the received signal received by the sensor 20, corresponding to multiple distances relative to the sensor 20. The strength of the received signal corresponding to a certain distance is the received signal strength reflected at a measurement point located at that distance from the sensor 20. The measurement point is a point on an object that reflects the signal transmitted from the sensor 20. Here, since the sensor 20 is installed on the target vehicle 10, the "distance relative to the sensor 20" can also be treated as the "distance relative to the target vehicle 10".

[0015] The data processing device 2000 operates as follows, for example. The data processing device 2000 acquires reception intensity data 30. Further, the data processing device 2000 identifies a measurement point 40 located within a first predetermined distance from the target vehicle 10 among the measurement points 40. The first predetermined distance is an arbitrary distance determined in advance. Hereinafter, the measurement point 40 located within the first predetermined distance from the target vehicle 10 is also expressed as a "short-distance measurement point".

[0016] The data processing device 2000 determines whether a predetermined condition (hereinafter, data reduction condition) regarding the short-distance measurement point is satisfied. The data reduction condition is, for example, a condition indicating that the number of short-distance measurement points is relatively large. The condition indicating that the number of short-distance measurement points is relatively large is, for example, a condition such as "the number of short-distance measurement points is equal to or greater than a threshold value" or "the ratio of the number of short-distance measurement points to the total number of measurement points is equal to or greater than a threshold value".

[0017] When the data reduction condition is satisfied, the data processing device 2000 identifies, as analysis target data (analysis target data 60), the data corresponding to a distance within a second predetermined distance from the target vehicle 10 among the data included in the reception intensity data 30. Note that the first predetermined distance and the second predetermined distance may be the same as each other or different from each other. When the data reduction condition is not satisfied, for example, the data processing device 2000 identifies the entire reception intensity data 30 as the analysis target data 60.

[0018] Here, the data reduction condition is set to be satisfied when information regarding a position relatively far from the target vehicle 10 (a position farther than the second predetermined distance) is unnecessary. When information regarding a position farther than the second predetermined distance from the target vehicle 10 is unnecessary, the data corresponding to a distance farther than the second predetermined distance from the target vehicle 10 among the data included in the reception intensity data 30 is unnecessary. Therefore, when the data reduction condition is satisfied, the data processing device 2000 does not treat the data corresponding to a distance farther than the predetermined distance from the target vehicle 10 as the analysis target data 60.

[0019] There are various specific situations where information regarding positions relatively far from the target vehicle 10 is unnecessary. For example, such a situation is one where traffic congestion has occurred in the front direction of the sensor 20 (e.g., the traveling direction of the target vehicle 10). When there is traffic congestion, since the target vehicle 10 travels at a low speed, the probability that an object existing at a position relatively far from the target vehicle 10 affects the target vehicle 10 is low. Therefore, information regarding positions relatively far from the target vehicle 10 becomes unnecessary.

[0020] Another situation where information regarding positions relatively far from the target vehicle 10 is unnecessary is a situation where there is a wall in the front direction of the sensor 20. In this case, the probability that an object existing at a position farther than this wall affects the target vehicle 10 is low. Therefore, information regarding positions farther than this wall becomes unnecessary.

[0021] Another situation where information regarding positions relatively far from the target vehicle 10 is unnecessary is a situation where the level crossing existing in the front direction of the sensor 20 is closed. When the level crossing is closed, the probability that an object located beyond the level crossing affects the target vehicle 10 is low. Therefore, information regarding positions farther than this level crossing becomes unnecessary.

[0022] <Examples of operational effects> According to the data processing device 2000, using the reception intensity data 30, a short-distance measurement point 40 that is a measurement point located within the first predetermined distance from the target vehicle 10 is specified. And when the data reduction condition regarding the short-distance measurement point is satisfied, data corresponding to a distance within the second predetermined distance from the target vehicle 10 is specified as the analysis target data 60.

[0023] As described above, the data reduction condition is set to be satisfied when information regarding a position farther than the second predetermined distance from the target vehicle 10 is unnecessary. By doing so, when information regarding a position farther than the second predetermined distance from the target vehicle 10 is unnecessary, data corresponding to a distance farther than the second predetermined distance from the target vehicle 10 is not treated as the analysis target data 60. Thereby, the data amount of the analysis target data 60 can be reduced.

[0024] The data to be analyzed 60 is used, for example, to control the target vehicle 10. By reducing the amount of data to be analyzed 60, the time required to control the target vehicle 10 can be shortened. Furthermore, by reducing the amount of data to be analyzed 60, the amount of computing resources required to control the target vehicle 10 can also be reduced.

[0025] The data processing device 2000 of this embodiment will be described in more detail below.

[0026] <Example of functional configuration> Figure 2 is a block diagram illustrating the functional configuration of the data processing device 2000. The data processing device 2000 includes an acquisition unit 2020, a first identification unit 2040, and a second identification unit 2060. The acquisition unit 2020 acquires received intensity data 30. The first identification unit 2040 identifies nearby measurement points. If the data reduction conditions for nearby measurement points are met, the second identification unit 2060 identifies the data included in the received intensity data 30 that corresponds to a distance within a second predetermined distance as the data to be analyzed 60.

[0027] <Example of hardware configuration> Each functional component of the data processing device 2000 may be implemented by hardware (e.g., hardwired electronic circuits) or by a combination of hardware and software (e.g., a combination of electronic circuits and programs that control them). The following will further explain the case where each functional component of the data processing device 2000 is implemented by a combination of hardware and software.

[0028] Figure 3 is a block diagram illustrating the hardware configuration of the computer 1000 that implements the data processing device 2000. The computer 1000 is any computer. For example, the computer 1000 is an ECU installed inside the target vehicle 10. This ECU is implemented using an MCU (Micro Controller Unit), such as a SoC (System on Chip). Note that the computer 1000 may be the MCU only, not the entire ECU. The computer 1000 may be a dedicated computer designed to implement the data processing device 2000, or it may be a general-purpose computer.

[0029] For example, by installing a predetermined application on computer 1000, the various functions of data processing device 2000 are realized on computer 1000. The above application consists of programs for realizing each functional component of data processing device 2000.

[0030] The method of obtaining the above program is arbitrary. For example, the program can be obtained from the storage medium on which it is stored. The storage medium on which the program is stored can be any storage medium, such as a DVD (Digital Versatile Disk) or a USB (Universal Serial Bus) memory. Alternatively, the program can be obtained by downloading it from a server device that manages the storage device on which the program is stored.

[0031] Computer 1000 includes a bus 1020, a processor 1040, memory 1060, a storage device 1080, an input / output interface (I / F) 1100, and a network interface 1120. The bus 1020 is a data transmission path for the processor 1040, memory 1060, storage device 1080, input / output interface 1100, and network interface 1120 to send and receive data from each other. However, the method of connecting the processor 1040 and other components is not limited to bus connection.

[0032] The processor 1040 is a variety of processors such as an MPU (Microprocessor Unit), CPU (Central Processing Unit), GPU (Graphics Processing Unit), or FPGA (Field-Programmable Gate Array). The memory 1060 is the main memory, implemented using RAM (Random Access Memory), etc. The storage device 1080 is the auxiliary storage, implemented using ROM (Read Only Memory), flash memory, or memory card, etc.

[0033] The input / output interface 1100 is an interface for connecting the computer 1000 with input / output devices. For example, the sensor 20 is connected to the input / output interface 1100.

[0034] The network interface 1120 is an interface for connecting computer 1000 to a network. This network could be, for example, Ethernet (registered trademark) or CAN (Controller Area Network).

[0035] The storage device 1080 stores programs that implement each functional component of the data processing unit 2000 (programs that implement the aforementioned applications). The processor 1040 reads these programs into memory 1060 and executes them to implement each functional component of the data processing unit 2000.

[0036] The data processing device 2000 may be implemented using one computer 1000 or multiple computers 1000. In the latter case, the configuration of each computer 1000 does not need to be identical and can be different.

[0037] <Processing flow> Figure 4 is a flowchart illustrating the processing flow performed by the data processing device 2000. The acquisition unit 2020 acquires the received intensity data 30 (S102). The first identification unit 2040 identifies the nearby measurement points (S104). If the data reduction condition for nearby measurement points is met (S106: YES), the second identification unit 2060 identifies the data included in the received intensity data 30 that corresponds to a distance within the second predetermined distance as the data to be analyzed 60 (S108). On the other hand, if the data reduction condition is not met (S106: NO), the second identification unit 2060 identifies all the data included in the received intensity data 30 as the data to be analyzed 60 (S110).

[0038] The data processing device 2000 can repeatedly perform the series of processes shown in Figure 4. For example, the sensor 20 repeatedly generates received intensity data 30. The data processing device 2000 sequentially acquires the received intensity data 30 that is repeatedly generated in this way and identifies the data to be analyzed 60 for each received intensity data 30.

[0039] <Acquisition of received signal strength data 30: S102> The acquisition unit 2020 acquires the received intensity data 30 (S102). There are various ways in which the acquisition unit 2020 acquires the received intensity data 30. For example, the sensor 20 is configured to output the received intensity data 30 to the data processing device 2000. In this case, the acquisition unit 2020 acquires the received intensity data 30 by receiving the received intensity data 30 output from the sensor 20.

[0040] In addition, for example, the sensor 20 is configured to store the received intensity data 30 in a storage unit accessible from the data processing unit 2000. In this case, the acquisition unit 2020 acquires the received intensity data 30 by reading it from the storage unit.

[0041] Sensor 20 repeatedly generates received intensity data 30. Specifically, sensor 20 generates received intensity data 30 at predetermined measurement intervals. For example, acquisition unit 2020 acquires the received intensity data 30 at these predetermined measurement intervals.

[0042] The sensor 20 may have multiple transmitting antennas that transmit distance measurement signals and multiple receiving antennas that receive reflected signals. In this case, the sensor 20 generates received signal strength data 30 for each of the multiple combinations of transmitting antennas and receiving antennas. Therefore, the acquisition unit 2020 acquires these multiple received signal strength data 30.

[0043] For example, suppose there are four transmitting antennas and four receiving antennas. In this case, there are 16 possible combinations of transmitting and receiving antennas. Therefore, the sensor 20 generates 16 pieces of received signal strength data 30. The acquisition unit 2020 then receives these 16 pieces of received signal strength data 30.

[0044] <Identification of nearby measurement points: S104> The first identification unit 2040 identifies nearby measurement points (S104). To this end, for example, the first identification unit 2040 generates point cloud data relating to the position of each measurement point. The point cloud data is a collection of multiple point data. One point data represents, for example, the position of one measurement point and the distance from the sensor 20 to that measurement point. The position of the measurement point may be represented in two dimensions or in three dimensions.

[0045] In this case, if the data processing device 2000 does not utilize the position of each measurement point, the point data does not need to indicate the position of the measurement point. Also, as will be described later, the second identification unit 2060 may utilize the velocity of each measurement point. In this case, it is preferable for each point data to further indicate the velocity of the corresponding measurement point.

[0046] For example, the first identification unit 2040 generates point cloud data for a given measurement time using multiple received intensity data 30 generated at that measurement time. Various existing methods can be used to generate point cloud data that shows the distance to each measurement point, the position of each measurement point, and the velocity of each measurement point, using multiple data showing the intensity of the received signal for each distance.

[0047] The first identification unit 2040 determines whether the distance from the target vehicle 10 to each of the multiple point data included in the point cloud data is less than or equal to a first predetermined distance. Point data whose distance from the target vehicle 10 is less than or equal to the first predetermined distance represents a close-range measurement point. Therefore, the first identification unit 2040 identifies the measurement points represented by point data whose distance from the target vehicle 10 is less than or equal to the first predetermined distance as close-range measurement points.

[0048] Point cloud data may be generated using a portion of the received intensity data 30. By generating point cloud data from a portion of the received intensity data 30, rather than the entire data, the time and computing resources required for generating the point cloud data can be reduced. Hereinafter, point cloud data generated using a portion of the received intensity data 30 will be referred to as second-order point cloud data. On the other hand, point cloud data generated using the entire received intensity data 30 will be referred to as first-order point cloud data.

[0049] For example, as mentioned above, the data processing device 2000 repeatedly performs a series of processes (hereinafter referred to as the analysis target identification process) to identify the data to be analyzed 60 from the received intensity data 30. In the nth analysis target identification process, the first identification unit 2040 determines whether the data reduction condition was met in the previous (i.e., the n-1th) analysis target identification process. Then, depending on the result of the determination, either the first point cloud data or the second point cloud data is generated.

[0050] More specifically, if the data reduction conditions were not met in the previous analysis target identification process, the first identification unit 2040 generates the first point cloud data using the entire received intensity data 30. On the other hand, if the data reduction conditions were met in the previous analysis target identification process, the first identification unit 2040 generates the second point cloud data using a portion of the received intensity data 30. For example, the second point cloud data is generated using data from the received intensity data 30 that corresponds to a distance within a second predetermined distance from the target vehicle 10.

[0051] Figure 5 is a flowchart illustrating the flow of the analysis target identification process, which is executed repeatedly. S202 to S206 represent the first execution of the analysis target identification process. In the first execution, the analysis target data 60 has not yet been identified. Therefore, the first point cloud data generated from the entire received intensity data 30 is used.

[0052] Specifically, the acquisition unit 2020 acquires the received intensity data 30 (S202). The first identification unit 2040 generates first point cloud data using the entire received intensity data 30 (S204). The data processing device 2000 uses the first point cloud data to identify the data to be analyzed 60 from the received intensity data 30 acquired in S202 (S206).

[0053] S208 to S220 constitute loop processing L1. Loop processing L1 represents the second and subsequent executions of the analysis target identification process.

[0054] In S208, the data processing device 2000 determines whether a predetermined termination condition is met. If the termination condition is met, the execution of loop processing L1 ends. That is, the execution of the series of processes shown in Figure 5 ends.

[0055] You can set any condition for termination. For example, the termination condition could be "an operation to restart or shut down the data processing device 2000 has been performed."

[0056] If the termination condition is not met in S208, the acquisition unit 2020 acquires the received intensity data 30 (S210). The first identification unit 2040 determines whether the data reduction condition was met in the previous analysis target identification process (S212). If the data reduction condition was not met (S212: NO), the first identification unit 2040 generates the first point cloud data using the entire received intensity data 30 (S214). If the data reduction condition was met (S212: YES), the first identification unit 2040 generates the second point cloud data using a portion of the received intensity data 30 (S216). The data processing device 2000 identifies the analysis target data 60 from the received intensity data 30 using the first point cloud data generated in S214 or the second point cloud data generated in S216 (S218). Since S220 is the end of the loop process L1, S208 is executed again.

[0057] <Determination of whether data reduction conditions are met: S106> The second identification unit 2060 determines whether the data reduction conditions for short-range measurement points are met (S106). As mentioned above, the data reduction conditions are set to be met when information about locations further than a second predetermined distance from the target vehicle 10 is unnecessary. For example, a condition indicating that "the number of short-range measurement points is relatively large" is used as a data reduction condition. As mentioned above, specific examples of conditions indicating that "the number of short-range measurement points is relatively large" include "the number of short-range measurement points is greater than or equal to a predetermined number" and "the ratio of the number of short-range measurement points to the total number of measurement points is greater than or equal to a predetermined ratio".

[0058] For example, suppose the data reduction condition is that "the number of nearby measurement points is equal to or greater than a predetermined number." In this case, the second identification unit 2060 determines whether or not the number of nearby measurement points is equal to or greater than the predetermined number. If the number of nearby measurement points is equal to or greater than the predetermined number, the second identification unit 2060 determines that the data reduction condition is met. On the other hand, if the number of nearby measurement points is not equal to or greater than the predetermined number, the second identification unit 2060 determines that the data reduction condition is not met.

[0059] For example, suppose the data reduction condition is that "the ratio of the number of nearby measurement points to the total number of measurement points is equal to or greater than a predetermined ratio." If the ratio of the number of nearby measurement points to the total number of measurement points is equal to or greater than the predetermined ratio, the second identification unit 2060 determines that the data reduction condition is met. On the other hand, if the ratio of the number of nearby measurement points to the total number of measurement points is not equal to or greater than the predetermined ratio, the second identification unit 2060 determines that the data reduction condition is not met. Here, the total number of measurement points can be represented by the total number of point data included in the point cloud data.

[0060] Data reduction conditions may include conditions related to the speed of the measurement points. For example, a data reduction condition might be that "the number of nearby measurement points with a speed below a predetermined speed is relatively large."

[0061] The condition that "there are a relatively large number of short-range measurement points moving at a speed below a predetermined speed" is met when there are many measurement points near the target vehicle 10 that are not moving or are moving at a low speed. Therefore, by including this condition regarding the speed of the measurement points in the data reduction conditions, it is possible to more accurately grasp situations such as congestion occurring in the direction in front of the sensor 20 or the presence of a wall in the direction in front of the sensor 20.

[0062] The condition "the number of short-range measurement points traveling at a speed below a predetermined speed is relatively large" can be expressed more specifically as "the number of short-range measurement points traveling at a speed below a predetermined speed is greater than or equal to a predetermined number" or "the ratio of the number of short-range measurement points traveling at a speed below a predetermined speed to the total number of measurement points is greater than or equal to a predetermined ratio." For example, suppose the data reduction condition is "the number of short-range measurement points traveling at a speed below a predetermined speed is greater than or equal to a predetermined number." In this case, the second identification unit 2060 determines whether the number of short-range measurement points traveling at a speed below a predetermined speed is greater than or equal to a predetermined number.

[0063] If the number of close-range measurement points at a speed below a predetermined speed is greater than or equal to a predetermined number, the second identification unit 2060 determines that the data reduction condition is met. On the other hand, if the number of close-range measurement points at a speed below a predetermined speed is not greater than or equal to a predetermined number, the second identification unit 2060 determines that the data reduction condition is not met.

[0064] The data reduction condition is that "the ratio of the number of short-range measurement points traveling at a speed of a predetermined speed or less to the total number of measurement points is equal to or greater than a predetermined ratio." In this case, the second identification unit 2060 determines whether the ratio of the number of short-range measurement points traveling at a speed of a predetermined speed or less to the total number of measurement points is equal to or greater than a predetermined ratio.

[0065] If the ratio of the number of close-range measurement points traveling at a speed of a predetermined speed or less to the total number of measurement points is equal to or greater than a predetermined ratio, the second identification unit 2060 determines that the data reduction condition is met. On the other hand, if the ratio of the number of close-range measurement points traveling at a speed of a predetermined speed or less to the total number of measurement points is not equal to or greater than a predetermined ratio, the second identification unit 2060 determines that the data reduction condition is not met.

[0066] In order to identify short-range measurement points that are traveling at a speed below a predetermined speed, the first identification unit 2040 determines, for each point data included in the point cloud data, whether the distance from the target vehicle 10 is below a first predetermined distance, and whether the speed is below a predetermined speed. The determination of whether the distance from the target vehicle 10 is below a first predetermined distance and the determination of whether the speed is below a predetermined speed may be performed in any order.

[0067] The data reduction conditions may also include spatial range conditions for the measurement points of interest. For example, a data reduction condition could be that "the number of measurement points located within a first predetermined distance from the target vehicle 10 and included in a predetermined spatial range is relatively large." In this way, by focusing on measurement points included in a specific spatial range, the density of measurement points can be taken into consideration.

[0068] The spatial range is defined, for example, by one or more ranges in the coordinate space of the point data, specifically the range in the X-axis direction, the Y-axis direction, and the Z-axis direction. For example, the range in the X-axis direction and the Y-axis direction can be defined by the conditions "x1 <= X <= x2 and y1 <= Y <= y2".

[0069] Thus, the spatial range condition of the measurement point of interest is included in the data reduction condition. In this case, the first identification unit 2040 identifies point data that falls within the predetermined spatial range indicated in the data reduction condition from the point cloud data generated from the received intensity data 30 or the data to be analyzed 60. The first identification unit 2040 then determines whether the identified point data corresponds to a nearby measurement point.

[0070] Both spatial range conditions and velocity conditions may be included in the data reduction conditions. For example, a data reduction condition such as "the number of short-range measurement points located within a predetermined spatial range and with a velocity below a predetermined velocity is relatively large" may be used. In this case, the first identification unit 2040 identifies short-range measurement points with a velocity below a predetermined velocity from within the predetermined spatial range.

[0071] <How to handle the 60 data points to be analyzed> There are various ways to handle the data to be analyzed 60. For example, the data processing device 2000 outputs the data to be analyzed 60. If the data reduction conditions are met, data indicating the received signal strength for each distance up to the second predetermined distance from the target vehicle 10 is output as the data to be analyzed 60. On the other hand, if the data reduction conditions are not met, the entire received signal strength data 30 is output as the data to be analyzed 60.

[0072] The functional component that outputs the data to be analyzed 60 is called the output unit. Figure 6 is a diagram illustrating the functional configuration of a data processing device 2000 having an output unit 2080. The output unit 2080 outputs the data to be analyzed 60.

[0073] The output method of the data to be analyzed 60 is arbitrary. For example, the output unit stores the data to be analyzed 60 in any storage unit. Alternatively, for example, the output unit transmits the data to be analyzed 60 to a device that will use the data to be analyzed 60.

[0074] The output unit 2080 may output point cloud data generated from the analysis target data 60, in addition to, or instead of, the analysis target data 60 identified by the second identification unit 2060. For example, the data processing device 2000 identifies the analysis target data 60 for each of the multiple received intensity data 30 obtained from multiple combinations of transmitting and receiving antennas. This results in multiple analysis target data 60. The output unit 2080 generates point cloud data using these multiple analysis target data 60. The point cloud data generated from the analysis target data 60, being generated from the analysis target data 60, does not contain point data for all measurement points, but rather point data for only some measurement points. The output unit 2080 then outputs the point cloud data generated from the analysis target data 60. The output mode of the point cloud data generated from the analysis target data 60 is arbitrary, similar to the output mode of the analysis target data 60.

[0075] If the data reduction conditions are not met, the output unit 2080 may output the first point cloud data.

[0076] Although the present invention has been specifically described above based on embodiments, it goes without saying that the present invention is not limited to the above embodiments and can be modified in various ways without departing from its essence.

[0077] Each drawing is merely illustrative to illustrate one or more embodiments. Each drawing may be associated with one or more other embodiments rather than with only one specific embodiment. As those skilled in the art will understand, various features or steps described with reference to any one drawing can be combined with features or steps shown in one or more other drawings, for example, to create embodiments not explicitly shown or described. Not all features or steps shown in any one drawing to illustrate an exemplary embodiment are necessarily required, and some features or steps may be omitted. The order of steps shown in any of the drawings may be changed as appropriate.

[0078] In this disclosure, a program includes a set of instructions (or software code) that, when loaded into a computer, cause the computer to perform one or more of the functions described in the embodiments. A program may be stored on a non-temporary computer-readable medium or a physical storage medium. Examples, but not limited to, include random-access memory (RAM), read-only memory (ROM), flash memory, solid-state drive (SSD) or other memory technologies, CD-ROM, digital versatile disc (DVD), Blu-ray® disc or other optical disc storage, magnetic cassette, magnetic tape, magnetic disk storage or other magnetic storage devices. A program may be transmitted over a temporary computer-readable medium or a communication medium. Examples, but not limited to, include temporary computer-readable medium or a communication medium that includes electrical, optical, acoustic or other forms of propagating signals.

[0079] <Note> (Note 1) For each of several distances, an acquisition unit acquires received intensity data representing the received intensity of a signal reflected from the target vehicle at a measurement point at the aforementioned distance, A first identification unit identifies a short-range measurement point, which is the measurement point located within a first predetermined distance from the target vehicle, A data processing device having a second identification unit that, when the nearby measurement point satisfies predetermined data reduction conditions, identifies data from the received intensity data that corresponds to a distance within a second predetermined distance from the target vehicle as data to be analyzed. (Note 2) The data reduction conditions include the condition that the number of nearby measurement points is equal to or greater than a predetermined number, or the condition that the ratio of the number of nearby measurement points to the total number of measurement points is equal to or greater than a predetermined ratio. The data processing device according to Appendix 1, wherein the second identifying unit determines whether the number of nearby measurement points is equal to or greater than the predetermined number, or whether the ratio of the number of nearby measurement points to the total number of measurement points is equal to or greater than the predetermined ratio. (Note 3) The aforementioned first specific part is, Using the received intensity data, point cloud data is generated in which point data indicating the distance from the measurement point to the target vehicle is included for each of the multiple measurement points. The data processing device described in Appendix 2, which identifies the nearby measurement point by identifying the point data from the point cloud data that indicates a distance of less than or equal to the first predetermined distance. (Note 4) The data reduction conditions include the condition that the number of nearby measurement points traveling at a speed of a predetermined speed or less is greater than or equal to a predetermined number, or the condition that the ratio of the number of nearby measurement points traveling at a speed of a predetermined speed or less to the total number of measurement points is greater than or equal to a predetermined ratio. The first identification unit further identifies the velocity of each of the measurement points, The data processing device according to Appendix 1, wherein the second identifying unit determines whether the number of close-range measurement points traveling at a speed of the predetermined speed or less is equal to or greater than the predetermined number, or whether the ratio of the number of close-range measurement points traveling at a speed of the predetermined speed or less to the total number of measurement points is equal to or greater than the predetermined ratio. (Note 5) The aforementioned first specific part is, Using the received intensity data, point cloud data is generated in which point data indicating the distance from the measurement point to the target vehicle and the speed at the measurement point are included for each of the multiple measurement points. The data processing device described in Appendix 4, which identifies the short-range measurement point having a speed of the predetermined speed or less by identifying the point data from the point cloud data that indicates a distance of the first predetermined distance or less and a speed of the predetermined speed or less. (Note 6) The data reduction conditions include the condition that the number of nearby measurement points included in a predetermined spatial range is greater than or equal to a predetermined number, or the condition that the ratio of the number of nearby measurement points included in the predetermined spatial range to the total number of measurement points is greater than or equal to a predetermined ratio. The data processing device according to Appendix 1, wherein the second identifying unit determines whether the number of nearby measurement points included in the predetermined spatial range is greater than or equal to a predetermined number, or whether the ratio of the number of nearby measurement points included in the predetermined spatial range to the total number of measurement points is greater than or equal to a predetermined ratio. (Note 7) The aforementioned first specific part is, Using the received intensity data, point cloud data is generated in which point data indicating the distance from the measurement point to the target vehicle and the position of the measurement point are included for each of the multiple measurement points. The data processing device according to Appendix 6, which identifies the nearby measurement point included in the predetermined spatial range by identifying the point data from the point cloud data that indicates a position within the predetermined spatial range and a distance of less than or equal to the first predetermined distance. (Note 8) The data processing device according to Appendix 1, having an output unit that outputs point cloud data indicating the positions of each measurement point located within a second predetermined distance from the target vehicle, using the data to be analyzed. (Note 9) For each of several distances, an acquisition step is to acquire received intensity data representing the received intensity of the signal reflected from the target vehicle at a measurement point located at the aforementioned distance, A first identification step involves identifying a nearby measurement point, which is the measurement point located within a first predetermined distance from the target vehicle. A data processing method performed by a computer, comprising: a second identification step of identifying data from the received intensity data that corresponds to a distance within a second predetermined distance from the target vehicle, when the nearby measurement point satisfies predetermined data reduction conditions, as data to be analyzed. (Note 10) For each of several distances, an acquisition step is to acquire received intensity data representing the received intensity of the signal reflected from the target vehicle at a measurement point located at the aforementioned distance, A first identification step involves identifying a nearby measurement point, which is the measurement point located within a first predetermined distance from the target vehicle. A program that causes a computer to perform a second identification step, in which, when the nearby measurement point satisfies predetermined data reduction conditions, the data shown in the received intensity data that corresponds to a distance within a second predetermined distance from the target vehicle is identified as data to be analyzed. (Note 11) A sensor that generates received intensity data for each of several distances, representing the received intensity of a signal reflected from the target vehicle at a measurement point at the aforementioned distance, It has a data processing device, The aforementioned data processing device is The acquisition unit acquires the aforementioned received signal strength data, A first identification unit identifies a short-range measurement point, which is the measurement point located within a first predetermined distance from the target vehicle, A data processing system comprising: a second identification unit that, when the nearby measurement point satisfies predetermined data reduction conditions, identifies data from the received intensity data that corresponds to a distance within a second predetermined distance from the target vehicle as data to be analyzed. (Note 12) One or more memory elements in which instructions are stored, It has one or more processors, The one or more processors execute the instruction, For each of the multiple distances, receive intensity data is acquired that represents the received intensity of the signal reflected from the target vehicle at a measurement point located at the aforementioned distance. A short-range measurement point, which is the measurement point located within a first predetermined distance from the target vehicle, is identified. When the aforementioned short-range measurement point satisfies predetermined data reduction conditions, the data shown in the received intensity data that corresponds to a distance within a second predetermined distance from the target vehicle is identified as the data to be analyzed. A data processing device configured as follows. (Note 13) For each of several distances, an acquisition step is to acquire received intensity data representing the received intensity of the signal reflected from the target vehicle at a measurement point located at the aforementioned distance, A first identification step involves identifying a nearby measurement point, which is the measurement point located within a first predetermined distance from the target vehicle. A non-temporary computer-readable medium containing a program that causes a computer to perform a second identification step, in which, when the nearby measurement point satisfies predetermined data reduction conditions, the data shown in the received intensity data that corresponds to a distance within a second predetermined distance from the target vehicle is identified as data to be analyzed.

[0080] Some or all of the elements (e.g., configuration and function) described in Appendices 2 to 8 that are dependent on Appendice 1 may also be dependent on Appendices 9 to 13, respectively, in the same way as the dependencies in Appendices 2 to 8. Some or all of the elements described in any appendice may be applicable to various hardware, software, recording units, systems, and methods for recording software. [Explanation of Symbols]

[0081] 10 Target Vehicles 20 sensors 30 Received signal strength data 40 measurement points 60 Data to be analyzed 1000 computers 1020 Bus 1040 processor 1060 memory 1080 Storage Devices 1100 Input / Output Interface 1120 Network Interface 2000 Data Processing Devices 2020 Acquisition Department 2040 1st Specific Department 2060 2nd Specific Section 2080 Output Section

Claims

1. For each of several distances, an acquisition unit acquires received intensity data representing the received intensity of a signal reflected from the target vehicle at a measurement point at the aforementioned distance, A first identification unit identifies a short-range measurement point, which is the measurement point located within a first predetermined distance from the target vehicle, A data processing device having a second identification unit that, when the nearby measurement point satisfies predetermined data reduction conditions, identifies data from the received intensity data that corresponds to a distance within a second predetermined distance from the target vehicle as data to be analyzed.

2. The data reduction conditions include the condition that the number of nearby measurement points is equal to or greater than a predetermined number, or the condition that the ratio of the number of nearby measurement points to the total number of measurement points is equal to or greater than a predetermined ratio. The data processing device according to claim 1, wherein the second identifying unit determines whether the number of nearby measurement points is equal to or greater than the predetermined number, or whether the ratio of the number of nearby measurement points to the total number of measurement points is equal to or greater than the predetermined ratio.

3. The first specified part is, Using the received intensity data, point cloud data is generated in which point data indicating the distance from the measurement point to the target vehicle is included for each of the multiple measurement points. The data processing device according to claim 2, which identifies the nearby measurement point by identifying the point data from the point cloud data that indicates a distance of less than or equal to the first predetermined distance.

4. The data reduction conditions include the condition that the number of nearby measurement points traveling at a speed of a predetermined speed or less is greater than or equal to a predetermined number, or the condition that the ratio of the number of nearby measurement points traveling at a speed of a predetermined speed or less to the total number of measurement points is greater than or equal to a predetermined ratio. The first identification unit further identifies the velocity of each of the measurement points, The data processing device according to claim 1, wherein the second identifying unit determines whether the number of close-range measurement points traveling at a speed of the predetermined speed or less is equal to or greater than the predetermined number, or whether the ratio of the number of close-range measurement points traveling at a speed of the predetermined speed or less to the total number of measurement points is equal to or greater than the predetermined ratio.

5. The first specified part is, Using the received intensity data, point cloud data is generated in which point data indicating the distance from the measurement point to the target vehicle and the speed at the measurement point are included for each of the multiple measurement points. The data processing device according to claim 4, which identifies the short-range measurement point having a speed of the predetermined speed or less by identifying the point data from the point cloud data that indicates a distance of the first predetermined distance or less and a speed of the predetermined speed or less.

6. The data reduction conditions include the condition that the number of nearby measurement points included in a predetermined spatial range is greater than or equal to a predetermined number, or the condition that the ratio of the number of nearby measurement points included in the predetermined spatial range to the total number of measurement points is greater than or equal to a predetermined ratio. The data processing device according to claim 1, wherein the second identifying unit determines whether the number of nearby measurement points included in the predetermined spatial range is greater than or equal to a predetermined number, or whether the ratio of the number of nearby measurement points included in the predetermined spatial range to the total number of measurement points is greater than or equal to a predetermined ratio.

7. The first specified part is, Using the received intensity data, point cloud data is generated in which point data indicating the distance from the measurement point to the target vehicle and the position of the measurement point are included for each of the multiple measurement points. The data processing device according to claim 6, which identifies the nearby measurement point included in the predetermined spatial range by identifying point data from the point cloud data that indicates a position within the predetermined spatial range and a distance of less than or equal to the first predetermined distance.

8. The data processing device according to claim 1, further comprising an output unit that outputs point cloud data indicating the positions of each measurement point located within a second predetermined distance from the target vehicle, using the data to be analyzed.

9. For each of several distances, an acquisition step is to acquire received intensity data representing the received intensity of the signal reflected from the target vehicle at a measurement point located at the aforementioned distance, A first identification step involves identifying a nearby measurement point, which is the measurement point located within a first predetermined distance from the target vehicle. A data processing method performed by a computer, comprising: a second identification step of identifying data from the received intensity data that corresponds to a distance within a second predetermined distance from the target vehicle, when the nearby measurement point satisfies predetermined data reduction conditions, as data to be analyzed.

10. For each of several distances, an acquisition step is to acquire received intensity data representing the received intensity of the signal reflected from the target vehicle at a measurement point located at the aforementioned distance, A first identification step involves identifying a nearby measurement point, which is the measurement point located within a first predetermined distance from the target vehicle. A program that causes a computer to perform a second identification step, in which, when the aforementioned close-range measurement point satisfies predetermined data reduction conditions, the data shown in the received intensity data that corresponds to a distance within a second predetermined distance from the target vehicle is identified as data to be analyzed.

11. A sensor that generates received intensity data for each of several distances, representing the received intensity of a signal reflected from the target vehicle at a measurement point at the aforementioned distance, It has a data processing device, The aforementioned data processing device is The acquisition unit acquires the aforementioned received signal strength data, A first identification unit identifies a short-range measurement point, which is the measurement point located within a first predetermined distance from the target vehicle, A data processing system comprising: a second identification unit that, when the nearby measurement point satisfies predetermined data reduction conditions, identifies data from the received intensity data that corresponds to a distance within a second predetermined distance from the target vehicle as data to be analyzed.

Images