Processing device and processing method

Abstract

In order to solve the problem of how to accurately calculate the distance between a sensor and a target device, this processing device comprises: an acquisition unit for repeatedly performing data acquisition processing in which distance data pertaining to the distance between a sensor 11 that is installed in a vehicle 1 and transmits electromagnetic waves and a target device (portable terminal 2) is acquired using the sensor 11; and a processing unit that excludes outlier data from among a data set including a plurality of pieces of distance data acquired in the past and calculates a representative value for the distance between the sensor 11 and the target device on the basis of the data set after exclusion of the outlier data.

Description

Processing device and processing method

[0001] The present invention relates to a processing device and a processing method.

[0002] In recent years, technologies have been used that perform various processes depending on the positional relationship between a target device, such as a user's mobile terminal, and a vehicle. For example, Patent Document 1 discloses a technology that automatically unlocks a vehicle door when it is detected that a user's mobile terminal is approaching the vehicle.

[0003] Japanese Patent Application Laid-Open No. 2020-204149

[0004] In a technology for performing various processes according to the positional relationship between a target device and a vehicle, for example, a data acquisition process is repeatedly performed to acquire distance data relating to the distance between the sensor and the target device using a sensor installed in the vehicle that emits electromagnetic waves, and the distance between the sensor and the target device is calculated using multiple distance data acquired in the past. Various processes are then performed using the calculated distance. Therefore, it is desirable to accurately calculate the distance between the sensor and the target device.

[0005] In view of the above, an object of the present invention is to provide a processing device and a processing method that can accurately calculate the distance between a sensor and a target device.

[0006] In order to solve the above problem, the processing device is a processing device for a vehicle and includes an acquisition unit that repeatedly performs a data acquisition process to acquire distance data regarding the distance between the sensor and the target device using a sensor installed in the vehicle that emits electromagnetic waves, and a processing unit that excludes outlier data from a dataset including multiple distance data acquired in the past, and calculates a representative value of the distance between the sensor and the target device based on the dataset after the outlier data has been excluded.

[0007] In order to solve the above problem, the processing method is a vehicle processing method, in which an acquisition unit of the processing device repeatedly performs a data acquisition process to acquire distance data regarding the distance between the sensor and a target device using a sensor installed in the vehicle that emits electromagnetic waves, and a processing unit of the processing device excludes outlier data from a dataset including multiple distance data acquired in the past, and calculates a representative value of the distance between the sensor and the target device based on the dataset after the outlier data has been excluded.

[0008] According to the present invention, it is possible to accurately calculate the distance between the sensor and the target device.

[0009] FIG. 1 is a schematic diagram showing a general configuration of a vehicle according to an embodiment of the present invention. FIG. 2 is a block diagram showing an example of a functional configuration of a processing device according to an embodiment of the present invention. FIG. 3 is a diagram for explaining automatic control of door unlocking and locking performed by a processing device according to an embodiment of the present invention. FIG. 4 is a flowchart showing an example of an overall flow of processing performed by a processing device according to an embodiment of the present invention. FIG. 5 is a flowchart showing an example of a flow of processing for calculating a representative value of the distance between a sensor and a mobile terminal performed by a processing device according to an embodiment of the present invention. FIG. 6 is a diagram showing an example of a data set used in the processing for calculating a representative value of the distance between a sensor and a mobile terminal according to an embodiment of the present invention.

[0010] Preferred embodiments of the present invention will be described in detail below with reference to the accompanying drawings. Dimensions, materials, and other specific values ​​shown in the embodiments are merely examples for facilitating understanding of the invention and, unless otherwise specified, do not limit the present invention. In this specification and drawings, elements having substantially the same functions and configurations are designated by the same reference numerals to avoid redundant explanation, and elements not directly related to the present invention are not shown.

[0011] <Configuration of Vehicle> The configuration of a vehicle 1 according to an embodiment of the present invention will be described with reference to FIGS. 1 to 3. FIG.

[0012] 1 is a schematic diagram showing a general configuration of a vehicle 1. As shown in FIG. 1, the vehicle 1 includes a plurality of sensors 11 and a processing device 12.

[0013] There is no particular limitation on the drive source of the vehicle 1. For example, the vehicle 1 may be equipped with only a motor as a drive source, or only an engine as a drive source, or may be equipped with both a motor and an engine as drive sources.

[0014] The sensors 11 are installed on the vehicle 1 to identify the position of a target device (e.g., a mobile terminal 2 described later) outside the vehicle 1. In the example of FIG. 1 , four sensors 11, namely, sensors 11a, 11b, 11c, and 11d, are installed on the vehicle 1. The sensor 11a is installed on the right front of the vehicle 1. The sensor 11b is installed on the left front of the vehicle 1. The sensor 11c is installed on the left rear of the vehicle 1. The sensor 11d is installed on the right rear of the vehicle 1. However, the number and arrangement of the sensors 11 installed on the vehicle 1 are not limited to the example of FIG. 1 . As described later, the sensors 11 can emit electromagnetic waves. This allows distance data regarding the distance between the sensors 11 and the target device to be obtained. The operation of the sensors 11 will be described in detail later.

[0015] The processing device 12 includes a CPU (Central Processing Unit), which is an arithmetic processing device; a ROM (Read Only Memory), which is a storage element that stores programs used by the CPU, calculation parameters, etc.; and a RAM (Random Access Memory), which is a storage element that temporarily stores parameters that change as the CPU executes. The processing device 12 may be, for example, a single device or may be divided into multiple devices. When the processing device 12 is divided into multiple devices, the various functions described below are shared among the multiple devices. For example, some functions of the processing unit 12b described below and other functions may be shared by different devices.

[0016] Fig. 2 is a block diagram showing an example of the functional configuration of the processing device 12. As shown in Fig. 2, the processing device 12 includes, for example, an acquisition unit 12a, a processing unit 12b, and a storage unit 12c.

[0017] The acquisition unit 12a acquires information from each device in the vehicle 1. For example, the acquisition unit 12a acquires information from each sensor 11. Specifically, the acquisition unit 12a outputs an operation command to each sensor 11 and acquires information detected by each sensor 11. Note that in this specification, acquisition of information may include extraction or generation (e.g., calculation) of information, etc.

[0018] The processing unit 12b performs various processes. In particular, the processing unit 12b performs a process related to identifying the position of a target device (e.g., a mobile terminal 2 described later) outside the vehicle 1. Details of the processes performed by the processing unit 12b will be described later.

[0019] The storage unit 12c stores various types of information, which are used in the processing performed by the processing unit 12b.

[0020] Here, the processing device 12 can perform various processes depending on the positional relationship between the vehicle 1 and a target device outside the vehicle 1. For example, the processing device 12 automatically controls unlocking and locking of the doors of the vehicle 1 depending on the positional relationship between the vehicle 1 and a mobile terminal 2 (for example, a terminal such as a smartphone owned by the user of the vehicle 1). Hereinafter, such control performed by the processing device 12 is also referred to as automatic control of unlocking and locking of the doors.

[0021] 3 is a diagram illustrating the automatic control of door locking and unlocking performed by the processing device 12. As described below, the processing device 12 can identify the relative position of the mobile terminal 2 with respect to the vehicle 1 using each sensor 11. For example, the sensor 11 transmits a first electromagnetic wave W1 to the mobile terminal 2, and the mobile terminal 2 transmits a second electromagnetic wave W2 to the sensor 11 upon receiving the first electromagnetic wave W1. The processing device 12 can determine the distance between the sensor 11 and the mobile terminal 2 based on the flight time of the electromagnetic waves. The processing device 12 can then identify the relative position of the mobile terminal 2 with respect to the vehicle 1 based on the distance between each sensor 11 and the mobile terminal 2. Details of the process related to obtaining distance data using the sensors 11 will be described later.

[0022] For example, as shown by the solid arrow in Figure 3, when the mobile terminal 2 enters area A1 within a predetermined distance from the outer periphery of the vehicle 1, the processing device 12 automatically unlocks the doors of the vehicle 1 or outputs unlock permission to a device responsible for the locking and unlocking functions. On the other hand, when the mobile terminal 2 exits area A1, the processing device 12 automatically locks the doors of the vehicle 1 or outputs lock permission to a device responsible for the locking and unlocking functions. With this automatic control of door unlocking and locking, for example, even if the user of the vehicle 1 has their hands full with luggage, the user can unlock the doors simply by approaching the vehicle 1. This improves convenience.

[0023] The processing device 12 can authenticate whether or not the mobile device 2 is a terminal that is linked to the user of the vehicle 1 and registered in advance, for example, by using information obtained through communication between the mobile device 2 and the sensor 11. Only when the mobile device 2 is a terminal that is linked to the user of the vehicle 1 and registered in advance, the processing device 12 automatically controls the unlocking and locking of the doors as described above.

[0024] The following mainly describes an example in which the target device whose location is to be identified is the mobile terminal 2. However, as will be described later, the mobile terminal 2 is merely one example of the target device. Furthermore, automatic control of door unlocking and locking is merely one example of processing that is performed in accordance with the positional relationship between the vehicle 1 and the target device.

[0025] <Operation of Processing Apparatus> The operation of the processing apparatus 12 according to the embodiment of the present invention will be described with reference to FIGS.

[0026] As described above, the processing device 12 can perform various processes (e.g., automatic control of door unlocking and locking) according to the positional relationship between the vehicle 1 and the mobile terminal 2. When performing such processes, the processing device 12 performs a process for identifying the relative position of the mobile terminal 2 with respect to the vehicle 1. The process for identifying the relative position performed by the processing device 12 will be described below.

[0027] Fig. 4 is a flowchart showing an example of the overall flow of processing performed by the processing device 12. Step S101 in Fig. 4 corresponds to the start of the processing flow shown in Fig. 4. The processing flow shown in Fig. 4 starts, for example, while the vehicle 1 is stopped.

[0028] When the processing flow shown in FIG. 4 starts, in step S102, the acquisition unit 12a performs a data acquisition process to acquire distance data relating to the distance between the sensor 11 and the portable terminal 2.

[0029] Specifically, in step S102, the acquisition unit 12a performs a data acquisition process for each sensor 11. That is, in the data acquisition process, the acquisition unit 12a acquires distance data relating to the distance between each sensor 11 and the portable terminal 2. The following mainly describes an example in which the distance data is data that directly indicates the distance between the sensor 11 and the portable terminal 2. However, as will be described later, the distance data may be data that can be substantially converted into the distance between the sensor 11 and the portable terminal 2.

[0030] In the data acquisition process, the acquisition unit 12a acquires distance data using the sensor 11. For example, the acquisition unit 12a causes the sensor 11 to emit a first electromagnetic wave W1. The sensor 11, for example, emits the first electromagnetic wave W1 radially in each direction around it. The first electromagnetic wave W1 emitted from the sensor 11 is then received by the mobile terminal 2. Here, when the mobile terminal 2 receives the first electromagnetic wave W1, the mobile terminal 2 that has received the first electromagnetic wave W1 emits a second electromagnetic wave W2 to the sensor 11. The second electromagnetic wave W2 emitted from the mobile terminal 2 is then received by the sensor 11.

[0031] The acquiring unit 12a acquires distance data based on a first time period from the time when the first electromagnetic wave W1 is emitted from the sensor 11 to the time when the first electromagnetic wave W1 is received by the portable terminal 2, and a second time period from the time when the second electromagnetic wave W2 is emitted from the portable terminal 2 in response to the reception of the first electromagnetic wave W1 to the time when the second electromagnetic wave W2 is received by the sensor 11. Here, the sum of the first time and the second time period corresponds to the time it takes for the electromagnetic wave to travel back and forth between the sensor 11 and the portable terminal 2. Therefore, the acquiring unit 12a acquires, for example, half the value obtained by multiplying the sum of the first time and the second time period by the speed of the electromagnetic wave (i.e., the speed of light), as distance data indicating the distance between the sensor 11 and the portable terminal 2.

[0032] When the portable terminal 2 receives the first electromagnetic wave W1, it determines whether the sender of the first electromagnetic wave W1 is a pre-registered vehicle 1, and transmits the second electromagnetic wave W2 if it determines that the sender of the first electromagnetic wave W1 is a pre-registered vehicle 1. Therefore, there is actually a time difference between the time when the first electromagnetic wave W1 is received by the portable terminal 2 and the time when the second electromagnetic wave W2 is transmitted from the portable terminal 2. Therefore, the acquisition unit 12a takes such a time difference into consideration and calculates the sum of the first time and the second time to acquire distance data.

[0033] The acquisition unit 12a also stores the distance data obtained by the data acquisition process in the storage unit 12c. As will be described later, the data acquisition process of step S102 is repeatedly performed. Therefore, the acquisition unit 12a stores the obtained distance data in the storage unit 12c as needed each time the data acquisition process is repeated. As a result, the distance data obtained at each point in time is accumulated in the storage unit 12c.

[0034] As will be described later, the method of acquiring distance data in the data acquisition process is not limited to the above example.

[0035] After step S102, in step S103, the processing unit 12b performs a calculation process to calculate a representative value of the distance between the sensor 11 and the portable terminal 2.

[0036] As will be described later, the processing unit 12b can identify the relative position of the mobile terminal 2 with respect to the vehicle 1 based on the distance between each sensor 11 and the mobile terminal 2. Here, the distance data acquired in the data acquisition process of step S102 may vary due to various factors, as will be described later. Therefore, the processing unit 12b does not use only one piece of distance data as information indicating the distance between the sensor 11 and the mobile terminal 2, but calculates a representative value of the distance between the sensor 11 and the mobile terminal 2 using multiple pieces of distance data acquired in the past. This makes it possible to more accurately determine the distance between each sensor 11 and the mobile terminal 2 by taking into account the variation in the distance data. Note that the calculation process of the representative value of the distance in step S103 will be described in detail later.

[0037] After step S103, in step S104, the processing unit 12b performs a determination process to determine the relative position of the mobile terminal 2 with respect to the vehicle 1, and then the process returns to step S102.

[0038] In step S104, the processing unit 12b identifies the relative position of the portable terminal 2 with respect to the vehicle 1 based on the distance between each sensor 11 and the portable terminal 2. Specifically, the processing unit 12b identifies the relative position of the portable terminal 2 with respect to the vehicle 1 by using a representative value of the distance as information indicating the distance between each sensor 11 and the portable terminal 2.

[0039] For example, in the horizontal plane, the portable device 2 exists on a circle whose center is the sensor 11a and whose radius is the distance between the sensor 11a and the portable device 2. Similarly, the portable device 2 exists on a circle whose center is the sensor 11b and whose radius is the distance between the sensor 11b and the portable device 2. Similarly, the portable device 2 exists on a circle whose center is the sensor 11c and whose radius is the distance between the sensor 11c and the portable device 2. Similarly, the portable device 2 exists on a circle whose center is the sensor 11d and whose radius is the distance between the sensor 11d and the portable device 2. Therefore, the processing unit 12b can determine that the portable device 2 is located at the intersection of these circles. In this way, the processing unit 12b can identify the relative position of the portable device 2 with respect to the vehicle 1.

[0040] As described above, in the processing device 12, the acquisition unit 12a repeatedly performs a data acquisition process to acquire distance data related to the distance between the sensor 11 and the portable terminal 2. Here, the distance data acquired in the data acquisition process may vary due to various factors. For example, the distance indicated by the distance data may be longer due to electromagnetic waves emitted from the sensor 11 or the portable terminal 2 being reflected off the ground or passing through an object (e.g., a bag containing the portable terminal 2). Furthermore, the distance indicated by the distance data may vary due to, for example, a calculation error in the processing device 12.

[0041] Therefore, the processing unit 12b calculates a representative value of the distance between the sensor 11 and the portable terminal 2 using multiple distance data acquired in the past. In this embodiment, by implementing some improvements in the process of calculating the representative value of the distance between the sensor 11 and the portable terminal 2, it becomes possible to calculate the distance between the sensor 11 and the portable terminal 2 with high accuracy, as will be described later. Below, the process of calculating the representative value of the distance between the sensor 11 and the portable terminal 2 performed by the processing unit 12 will be described.

[0042] Fig. 5 is a flowchart showing an example of the flow of a process performed by the processing device 12 to calculate a representative value of the distance between the sensor 11 and the mobile terminal 2. Step S201 in Fig. 5 corresponds to the start of the process flow shown in Fig. 5. Step S205 in Fig. 5 corresponds to the end of the process flow shown in Fig. 5. The process flow shown in Fig. 5 is executed, for example, in step S103 of the process flow shown in Fig. 4.

[0043] As will be described later, processing unit 12b calculates a representative value of the distance between sensor 11 and portable device 2 using a data set including a plurality of distance data acquired in the past. Fig. 6 is a diagram showing an example of a data set used in the calculation process of the representative value of the distance between sensor 11 and portable device 2. In Fig. 6, nine distance data D1, D2, D3, D4, D5, D6, D7, D8, and D9 are shown, with the horizontal axis representing the time when each distance data was acquired and the vertical axis representing the distance value indicated by each distance data.

[0044] In the following, an example will be described in which a data set including the most recent nine distance data items acquired in the past is used to calculate a representative value of the distance between the sensor 11 and the mobile terminal 2. However, as will be described later, the number of distance data items included in the data set is not limited to this example.

[0045] When the processing flow shown in FIG. 5 starts, in step S202, the processing unit 12b determines a reference range according to the distribution of distance data in the data set.

[0046] As described below, the reference range is a range for determining outlier data to be excluded from the dataset. Specifically, the reference range is a range in which distance data is mainly distributed in the dataset before the outlier data is excluded. The processing unit 12b determines, for example, a range corresponding to the interquartile range (IQR) in the dataset before the outlier data is excluded as the reference range. For example, the processing unit 12b may calculate a range from the 25th percentile (first quartile) to the 75th percentile (third quartile) as such a range. In the example of FIG. 6, a range R1 corresponding to the interquartile range is determined as the reference range.

[0047] However, the processing unit 12b may determine a range other than the above as the reference range. For example, the processing unit 12b may use a value smaller than the 25th percentile as the lower limit of the reference range, or a value larger than the 25th percentile. Also, for example, the processing unit 12b may use a value smaller than the 75th percentile as the upper limit of the reference range, or a value larger than the 75th percentile. Also, for example, the width of the reference range (i.e., the difference between the lower limit and the upper limit) may be expanded or reduced by multiplying it by a predetermined coefficient.

[0048] After step S202, in step S203, the processing unit 12b removes outlier data from the data set.

[0049] Specifically, the processing unit 12b determines, as outlier data, distance data that indicates a value outside the reference range determined in step S202. For example, in the example of FIG. 6, seven pieces of distance data, D2, D3, D4, D5, D6, D8, and D9, indicate values ​​within range R1, which is the reference range. On the other hand, two pieces of distance data, D1 and D7, indicate values ​​outside range R1, which is the reference range. Therefore, the processing unit 12b determines, among the distance data D1, D2, D3, D4, D5, D6, D7, D8, and D9, the distance data D1 and D7 as outlier data and excludes them from the dataset.

[0050] After step S203, in step S204, the processing unit 12b calculates a representative value of the distance between the sensor 11 and the mobile terminal 2 based on the data set after excluding the outlier data, and the processing flow shown in Figure 5 ends.

[0051] For example, processing unit 12b calculates the average value of distance data included in the dataset after excluding the outlier data as the representative value of the distance between sensor 11 and mobile device 2. For example, in the example of Fig. 6, processing unit 12b calculates the average value of distance data D2, D3, D4, D5, D6, D8, and D9 included in the dataset after excluding the outlier data as the representative value of the distance between sensor 11 and mobile device 2.

[0052] In addition, the processing unit 12b may calculate a value other than the average value of the distance data included in the dataset after excluding outlier data (for example, the median value of the distance data included in the dataset after excluding outlier data) as a representative value of the distance between the sensor 11 and the mobile terminal 2.

[0053] As described above, in this embodiment, the processing unit 12b of the processing device 12 removes outlier data from a data set including multiple pieces of distance data acquired in the past, and calculates a representative value of the distance between the sensor 11 and the portable device 2 based on the data set after the removal of the outlier data. This allows for calculation of the representative value of the distance between the sensor 11 and the portable device 2 after removing outlier data that indicates values ​​that are considered to be abnormal values ​​from the multiple pieces of distance data acquired in the past, taking into consideration that the distance data acquired in the data acquisition process may vary due to various factors. Therefore, the distance between the sensor 11 and the portable device 2 can be calculated with high accuracy.

[0054] 4 to 6, examples of the processing performed by the processing device 12 have been described above. However, the processing performed by the processing device 12 may be a processing in which the processing examples described above have been modified.

[0055] For example, in the above example, a data set including the most recent nine pieces of distance data acquired in the past is used to calculate a representative value of the distance between the sensor 11 and the portable terminal 2. However, the number of pieces of distance data included in the data set is not limited to this example. For example, the number of pieces of distance data included in the data set may be less than nine or more than nine.

[0056] Here, in certain cases, the processing unit 12b may change the number of pieces of distance data included in the data set before excluding the outlier data.

[0057] For example, the processing unit 12b may change the number of pieces of data in response to an input operation by the user. In this case, the user can change the number of pieces of data by performing a predetermined input operation using an input device or the like of the vehicle 1. For example, the fewer the number of pieces of data, the shorter the total time required for the process to calculate the representative value of the distance between the sensor 11 and the portable device 2. On the other hand, the greater the number of pieces of data, the more accurate the calculation of the distance between the sensor 11 and the portable device 2 can be.

[0058] Furthermore, for example, processing unit 12b may change the number of pieces of data based on the distance between sensor 11 and the portable terminal 2. For example, when the representative value of the distance between sensor 11 and the portable terminal 2 is small, there is a greater need to quickly grasp changes in the position of the portable terminal 2 than when the representative value is large. Therefore, processing unit 12b may reduce the number of pieces of data and shorten the total time required for processing to calculate the representative value of the distance between sensor 11 and the portable terminal 2. On the other hand, when the representative value of the distance between sensor 11 and the portable terminal 2 is large, there is a lesser need to quickly grasp changes in the position of the portable terminal 2 than when the representative value is small. Therefore, processing unit 12b may increase the number of pieces of data and improve the accuracy of calculation of the distance between sensor 11 and the portable terminal 2.

[0059] The above mainly describes an example in which the distance data is data that directly indicates the distance between the sensor 11 and the portable terminal 2. However, the distance data may be data that can be substantially converted into the distance between the sensor 11 and the portable terminal 2. For example, the distance data may be data that indicates the total value of the flight time (i.e., the second time) of the first electromagnetic wave W1 transmitted from the sensor 11 to the portable terminal 2 and the flight time (i.e., the second time) of the second electromagnetic wave W2 transmitted from the portable terminal 2 to the sensor 11.

[0060] The above description also illustrates an example in which distance data is acquired based on the time of flight (i.e., the second time) of the first electromagnetic wave W1 transmitted from the sensor 11 to the portable terminal 2 and the time of flight (i.e., the second time) of the second electromagnetic wave W2 transmitted from the portable terminal 2 to the sensor 11 during the data acquisition process. However, the method for acquiring distance data during the data acquisition process is not limited to the above example. For example, during the data acquisition process, the acquisition unit 12a may acquire distance data based on the received signal strength when the electromagnetic wave transmitted from the sensor 11 is received by the portable terminal 2. In this case, for example, when the portable terminal 2 receives the electromagnetic wave transmitted from the sensor 11, the acquisition unit 12a measures the received signal strength and transmits a signal indicating the measurement result of the received signal strength to the sensor 11. Then, the acquisition unit 12a can determine that the greater the received signal strength, the closer the distance between the sensor 11 and the portable terminal 2 is. In this case, data directly indicating the received signal strength may itself be used as distance data.

[0061] In addition, the above description mainly describes an example in which the target device whose position is to be identified is the mobile terminal 2. However, the target device whose position is to be identified may be a device other than the mobile terminal 2. For example, the target device whose position is to be identified may be another vehicle, a charger for the battery of the vehicle 1, a garage gate, a drone, a robot, etc.

[0062] In the above description, automatic control of door unlocking and locking has been described as an example of processing performed in accordance with the positional relationship between the vehicle 1 and the target device. However, the processing performed in accordance with the positional relationship between the vehicle 1 and the target device may be processing other than automatic control of door unlocking and locking. For example, the processing performed in accordance with the positional relationship between the vehicle 1 and the target device may be processing that permits activation of a drive source such as an engine of the vehicle 1 when it is detected that the mobile terminal 2 of the user of the vehicle 1 is approaching the vehicle 1.

[0063] <Effects of the Processing Apparatus> The effects of the processing apparatus 12 according to the embodiment of the present invention will be described.

[0064] The processing device 12 includes an acquisition unit 12a that repeatedly performs a data acquisition process to acquire distance data related to the distance between the sensor 11 and a target device (in the above example, the mobile terminal 2) using a sensor 11 installed in the vehicle 1 that emits electromagnetic waves, and a processing unit 12b that removes outlier data from a dataset including multiple distance data previously acquired and calculates a representative value of the distance between the sensor 11 and the target device based on the dataset after the removal of the outlier data. This allows the processing device 12 to calculate a representative value of the distance between the sensor 11 and the target device after removing outlier data that indicates values ​​that are considered to be abnormal from multiple distance data previously acquired, taking into account that the distance data acquired in the data acquisition process may vary due to various factors. Therefore, the distance between the sensor 11 and the target device can be calculated with high accuracy.

[0065] Preferably, in the processing device 12, the processing unit 12b determines, as outlier data, distance data that indicates a value outside a reference range (e.g., range R1 in the example of FIG. 6 ) corresponding to the distribution of distance data in the dataset before the elimination of the outlier data. This makes it possible to appropriately exclude, as outlier data, data that indicates a value that is considered to be an abnormal value from among multiple distance data acquired in the past. Therefore, it is possible to appropriately realize the calculation of the distance between the sensor 11 and the target device with high accuracy.

[0066] The method for determining outlier data is not limited to the above example. For example, the processing unit 12b may determine, as outlier data, distance data that indicates a value outside a reference range (e.g., a preset range) that is determined without taking into account the distribution of distance data in the data set before the outlier data is excluded.

[0067] Preferably, in the processing device 12, the processing unit 12b changes the number of pieces of distance data included in the data set before excluding outlier data, thereby changing, for example, the total time required for processing to calculate a representative value of the distance between the sensor 11 and the target device and the calculation accuracy of the distance between the sensor 11 and the target device.

[0068] Preferably, in the processing device 12, the processing unit 12b changes the number of pieces of data based on the distance between the sensor 11 and the target device (in the above example, the mobile terminal 2). This makes it possible to appropriately change, for example, the total time required for processing to calculate a representative value of the distance between the sensor 11 and the target device and the calculation accuracy of the distance between the sensor 11 and the target device according to the distance between the sensor 11 and the target device.

[0069] Preferably, in the processing device 12, the acquiring unit 12a acquires distance data in the data acquisition process based on a first time period from the time when the first electromagnetic wave W1 is emitted from the sensor 11 to the time when the first electromagnetic wave W1 is received by the target device (in the above example, the mobile terminal 2), and a second time period from the time when the second electromagnetic wave W2 is emitted from the target device in response to reception of the first electromagnetic wave W1 to the time when the second electromagnetic wave W2 is received by the sensor 11. This appropriately realizes acquisition of distance data regarding the distance between the sensor 11 and the target device in the data acquisition process.

[0070] Preferably, in the processing device 12, the target device is the mobile terminal 2. This allows the distance between the sensor 11 and the mobile terminal 2 to be calculated with high accuracy when performing processing (e.g., automatic control of door unlocking and locking) that is performed depending on the positional relationship between the vehicle 1 and the mobile terminal 2.

[0071] The above describes a preferred embodiment of the present invention with reference to the accompanying drawings. However, it goes without saying that the present invention is not limited to the above-described embodiment, and various modified or altered examples within the scope of the claims also fall within the technical scope of the present invention.

[0072] For example, the processes described herein using flowcharts do not necessarily have to be performed in the order shown in the flowcharts, some process steps may be performed in parallel, additional process steps may be employed, and some process steps may be omitted.

[0073] Furthermore, for example, the series of processes performed by the processing device 12 described above may be realized using software, hardware, or a combination of software and hardware. The programs constituting the software are stored in advance in a storage medium provided inside or outside the information processing device, for example.

[0074] REFERENCE SIGNS LIST 1 vehicle 2 portable terminal (target device) 11 sensor 11a sensor 11b sensor 11c sensor 11d sensor 12 processing device 12a acquisition unit 12b processing unit 12c storage unit A1 area D1 distance data D2 distance data D3 distance data D4 distance data D5 distance data D6 distance data D7 distance data D8 distance data D9 distance data R1 range (reference range) W1 first electromagnetic wave W2 second electromagnetic wave

Claims

1. A processing device (12) for a vehicle (1), comprising: an acquisition unit (12a) that repeatedly performs a data acquisition process to acquire distance data relating to the distance between a sensor (11) installed on the vehicle (1) that emits electromagnetic waves and a target device (2) using the sensor (11); and a processing unit (12b) that excludes outlier data from a data set including a plurality of previously acquired distance data, and calculates a representative value of the distance between the sensor (11) and the target device (2) based on the data set after the exclusion of the outlier data.

2. The processing device according to claim 1, wherein the processing unit (12b) determines, as the outlier data, the distance data that indicates a value outside a reference range (R1) according to the distribution of the distance data in the data set before the outlier data is excluded.

3. The processing device according to claim 1, wherein the processing unit (12b) changes the number of pieces of distance data included in the data set before the outlier data is removed.

4. The processing device according to claim 3, wherein the processing unit (12b) changes the number of pieces of data based on the distance between the sensor (11) and the target device (2).

5. A processing device as described in any one of claims 1 to 4, wherein the acquisition unit (12a) acquires the distance data in the data acquisition process based on a first time from the time a first electromagnetic wave (W1) is emitted from the sensor (11) to the time the first electromagnetic wave (W1) is received by the target device (2), and a second time from the time a second electromagnetic wave (W2) is emitted from the target device (2) in response to receiving the first electromagnetic wave (W1) to the time the second electromagnetic wave (W2) is received by the sensor (11).

6. The processing device according to any one of claims 1 to 4, wherein the target device is a mobile terminal (2).

7. A processing method for a vehicle (1), comprising: an acquisition unit (12a) of a processing device (12) repeatedly performs a data acquisition process to acquire distance data relating to the distance between a sensor (11) installed on the vehicle (1) that emits electromagnetic waves and a target device (2), using the sensor (11); and a processing unit (12b) of the processing device (12) excludes outlier data from a data set including a plurality of previously acquired distance data, and calculates a representative value of the distance between the sensor (11) and the target device (2) based on the data set after the outlier data has been excluded.

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