Data collection system and onboard data recording device

Abstract

A data recording device according to the present invention refers to an area map that indicates the correspondence between location information and area attributes to acquire area attributes that correspond to the current location of a vehicle, refers to a collection trigger list that indicates the correspondence between area attributes, trigger occurrence conditions, and information related to the recording of target data to be collected to identify occurrence conditions that correspond to the area attributes of the current location of the vehicle, determines the occurrence of a trigger on the basis of the trigger occurrence conditions and the output of an onboard sensor, determines an encoder parameter for adjusting data size when data is recorded in accordance with a correction value calculated on the basis of a cumulative collection count for vehicle data accumulated at a data collection server, records vehicle data generated by encoding target data in accordance with the encoder parameter at a memory resource, and transmits the recorded vehicle data to the data collection server.

Description

Data collection system and in-vehicle data recording device

[0001] The present invention relates to a data collection system and an in-vehicle data recording device.

[0002] A data recording device is installed in an automobile (hereinafter referred to as a vehicle) that travels on a road, and when an abnormality such as an accident or breakdown occurs, the data recording device records the vehicle's control data, operation data, video data, etc. before and after the occurrence. Hereinafter, the vehicle's control data, operation data, video data, etc. will be collectively referred to as vehicle data.

[0003] In recent years, vehicle data has been collected and recorded not only when an abnormality such as an accident or breakdown occurs, but also when various other situations are triggered, and the collected vehicle data is used to improve the performance of systems such as autonomous driving (AD) and advanced driver-assistance systems (ADAS).

[0004] However, the size of vehicle data collected from vehicles continues to increase with the advancement of systems and the increase in the number of on-board sensors. In particular, with regard to cameras as on-board sensors, the size of the video data obtained as a result of capturing images is significantly increasing due to the increase in the number of cameras installed in vehicles, as well as the increase in the number of pixels and frame rates. However, since the capacity of the storage installed in vehicles for storing this video data is limited, it is necessary to reduce the size of the video data.

[0005] Regarding technology for reducing the size of video data captured in a vehicle, for example, Patent Document 1 describes "an in-vehicle device that includes an acquisition unit, a detection unit, and a generation unit, in which the acquisition unit acquires video data captured in the vehicle, the detection unit detects the driving conditions at the time the video data was acquired, and the generation unit compresses the video data using a compression method according to the driving conditions detected by the detection unit to generate compressed data."

[0006] Japanese Patent Application Laid-Open No. 2020-107291

[0007] The technology described in Patent Document 1 allows for the selection of an appropriate data compression rate depending on the vehicle's driving conditions. However, this technology does not take into consideration the possibility that, for example, when recording video data in response to the occurrence of a specific condition in the vehicle as a trigger, similar scenes may be recorded in response to the same trigger, resulting in redundant video data information.

[0008] The present invention has been made in view of the above-mentioned points, and has an object to make it possible to reduce the data size of vehicle data while maintaining its usefulness.

[0009] The present application includes a number of means for solving at least some of the above-mentioned problems, examples of which are as follows.

[0010] A representative example of the invention disclosed in the present application is as follows: That is, a data collection system including a data collection server and a data recording device mounted on a vehicle, wherein the data recording device acquires area attributes corresponding to the current location of the vehicle by referring to an area map showing correspondence between location information and area attributes, identifies the occurrence condition corresponding to the area attribute of the current location of the vehicle by referring to a collection trigger list showing correspondence between the area attributes, trigger occurrence conditions, and information related to the recording of target data to be collected, determines the occurrence of the trigger based on the output of an on-board sensor and the trigger occurrence condition, determines encoding parameters for adjusting the data size when recording data according to a correction value calculated based on the cumulative number of collected vehicle data stored in the data collection server, records vehicle data generated by encoding the target data according to the encoding parameters in a memory resource, and transmits the recorded vehicle data to the data collection server.

[0011] According to the present invention, the data size can be reduced while maintaining the usefulness of vehicle data.

[0012] Problems, configurations, and effects other than those described above will become apparent from the following description of the embodiments.

[0013] FIG. 1 is a diagram showing an example of the configuration of a data collection system according to a first embodiment of the present invention. FIG. 2 is a diagram showing an example of the configuration of a data collection device. FIG. 3 is a logical block diagram showing an example of the flow of various data in the data collection system according to the first embodiment of the present invention. FIG. 4 is a diagram showing an example of an area map. FIG. 5 is a diagram showing an example of a collection trigger list. FIG. 6 is a diagram showing an example of a collection trigger list (on-board). FIG. 7 is a diagram showing an example of a data quality table. FIG. 8 is a flowchart showing an example of a trigger identification process. FIG. 9 is a flowchart showing an example of a process when a trigger occurs. FIG. 10 is a diagram showing another example of an area map. FIG. 11 is a logical block diagram showing an example of the flow of data in a data collection system according to a second embodiment of the present invention.

[0014] Hereinafter, several embodiments of the present invention will be described with reference to the drawings. In all drawings used to describe each embodiment, the same components are generally designated by the same reference numerals, and repeated description thereof will be omitted. Furthermore, in the following embodiments, the components (including element steps, etc.) are not necessarily essential unless otherwise specified, or unless they are clearly considered essential in principle. Furthermore, when the terms "consisting of A," "composed of A," "having A," or "including A" are used, other elements are not excluded unless otherwise specified, or unless it is clearly considered that only that element is included. Similarly, in the following embodiments, when referring to the shape, positional relationship, etc. of components, etc., these terms include those that are substantially similar or similar to the shape, etc., unless otherwise specified, or unless it is clearly considered otherwise in principle.

[0015] <Configuration Example of Data Collection System 1 According to First Embodiment of the Present Invention> FIG. 1 shows a configuration example of a data collection system 1 according to a first embodiment of the present invention.

[0016] The data collection system 1 includes a data collection center 10, data recording devices 100-1, 100-2, 100-3, . . . mounted on vehicles V-1, V-2, V-3, .

[0017] Hereinafter, when there is no need to distinguish between the vehicles V-1, V-2, V-3, etc., they will be referred to as vehicle V. The same applies to the data recording devices 100-1, 100-2, 100-3, etc.

[0018] The data collection system 1 collects vehicle data D (vehicle control data, operation data, video data, etc.) from a data recording device 100 mounted on a vehicle V via a network N and supplies the data to a user terminal 200 of a user. The user may be, for example, a developer of an autonomous driving system, an advanced driving assistance system, etc., and utilizes the vehicle data in the development of such systems.

[0019] The data collection center 10 is provided on a so-called cloud-based data collection server, and collects vehicle data D transmitted from each vehicle V via a network N such as the Internet or a mobile phone communication network, and provides the vehicle data D to users. The data collection center 10 manages an area map 11, a collection trigger list 12, a data quality table 13, and a collected data DB (database) 14 (all shown in FIG. 3). These are edited, updated, read, and other operations are performed from a user terminal 200.

[0020] The user terminal 200 is a terminal device used by a user, and is configured as a general computer such as a PC (personal computer), a tablet terminal, a smartphone, etc. The user connects to the data collection center 10 using the user terminal 200 and updates trigger conditions for specifying scenes from which the user wishes to collect vehicle data D, the quality of the vehicle data D to be collected, an area map, etc. The user connects to the data collection center 10 using the user terminal 200 and obtains collected vehicle data from the collected data DB 14.

[0021] The data recording device 100 mounted on the vehicle V connects to the data collection center 10 via the network N, stores the area map 11, collection trigger list 12, and data quality table 13 acquired from the data collection center 10 in its own non-volatile memory 4 (FIG. 2), and then records the vehicle data D acquired by the on-board sensors mounted on the vehicle V in accordance with the stored data, and uploads the recorded vehicle data D to the data collection center 10 at a predetermined time (for example, when the vehicle is parked in a predetermined place).

[0022] 2 shows an example of the configuration of the data recording device 100. The data recording device 100 includes a processor 2, a memory 3, a non-volatile memory 4, and an I / O (Input / Output) device 5. The processor 2, the memory 3, the non-volatile memory 4, and the I / O device 5 are interconnected via an interconnect 6, and input and output various data via the interconnect 6. The I / O device 5 transmits and receives vehicle data to and from the on-board sensor 120, etc., via a network link 7.

[0023] The on-board sensor 120 is, for example, a camera, radar, LiDAR (Light Detection and Ranging), a vehicle speed sensor, a positioning sensor, a steering operation amount sensor, an accelerator operation amount sensor, a brake operation amount sensor, and the like.

[0024] The network link 7 may be, for example, a Controller Area Network (CAN), Ethernet, or Camera Serial Interface (CSI)-2. A plurality of network links 7 may be provided as necessary. In this case, each network link 7 may use a different protocol.

[0025] An OS (Operating System) 8, as well as programs for realizing a communication unit 101, a self-location identification unit 103, an area attribute acquisition unit 104, a data quality determination unit 106, a trigger determination unit 108, and a recording unit 109 are loaded into the memory 3. The processor 2 executes the OS 8 loaded into the memory 3, and executes programs for realizing the communication unit 101, etc. on the OS 8, thereby realizing the communication unit 101, the self-location identification unit 103, the area attribute acquisition unit 104, the data quality determination unit 106, the trigger determination unit 108, and the recording unit 109, which are the main entities for performing the processes described below. However, as described above, the communication unit 101, etc. are realized by the processor 2, and therefore the actual entity that executes each process is the processor 2.

[0026] The OS 8 and programs executed by the processor may be stored in advance in the memory 3, or may be downloaded from a predetermined server or the like via a removable medium (CD-ROM, flash memory, etc.) or a network such as the Internet, stored in storage, which is a non-transitory storage medium, and read from the storage when needed. For this reason, the data recording device 100 should preferably have an interface for reading data from removable media.

[0027] The communication unit 101, the self-location identification unit 103, the area attribute acquisition unit 104, the data quality determination unit 106, the trigger determination unit 108, and the recording unit 109 will be described later with reference to FIG.

[0028] The nonvolatile memory 4 stores an area map (on-board) 102, a data quality table 105, and a collection trigger list (on-board) 107, which correspond to the area map 11, the data quality table 13, and the collection trigger list 12 read from the data collection center 10. The nonvolatile memory 4 also includes a data recording storage 110 for recording vehicle data D acquired by the on-board sensor 120. However, the data recording storage 110 has a limited capacity.

[0029] The area map (on-board) 102 is information for identifying the area attributes of the current location of the vehicle V.

[0030] The data quality table 105 contains information for determining the quality of the vehicle data D acquired by the on-board sensor 120 when it is recorded.

[0031] The collection trigger list (on-board) 107 is information for determining a trigger for recording the vehicle data D for the on-board sensor 120 .

[0032] The data recording device 100 may be configured as a dedicated device, or a part of a vehicle control device may have the function of the data recording device 100 .

[0033] <Flow of Various Data in Data Collection System 1> FIG. 3 shows an example of the flow of various data in the data collection system 1. As shown in FIG.

[0034] A user can connect to the data collection center 10 using a user terminal 200 and edit or update the area map 11, collection trigger list 12, and data quality table 13 managed by the data collection center 10. In addition, a user can obtain a collected data DB 14 managed by the data collection center 10 using the user terminal 200.

[0035] In the data recording device 100, the communication unit 101 connects to the data collection center 10 via the network N, acquires the area map 11, collection trigger list 12, and data quality table 13 managed by the data collection center 10, and stores them in the non-volatile memory 4 as the area map (on-board) 102, collection trigger list (on-board) 107, and data quality table 105, respectively. The communication unit 101 also connects to the data collection center 10 via the network N at a predetermined timing, and uploads the vehicle data D recorded in the data recording storage 110 to the data collection center 10. The uploaded vehicle data D is accumulated in the collected data DB 14.

[0036] The self-location determining unit 103 determines coordinate information (latitude, longitude, altitude) representing the current location of the vehicle V based on the output of the on-board positioning sensor.

[0037] The area attribute acquisition unit 104 acquires area attributes corresponding to the current location of the vehicle V based on the coordinate information of the vehicle V and the area map (on-board) 102.

[0038] The data quality determination unit 106 determines the data quality when recording the vehicle data D acquired by the on-board sensor 120 in the data recording storage 110, based on the area attribute corresponding to the current location of the vehicle V, the data quality table 105, and the image quality correction value of the collection trigger list (on-board) 107. For example, the data quality determination unit 106 determines a parameter capable of adjusting the data size of the video data as the vehicle data D.

[0039] The trigger determination unit 108 identifies one or more triggers that are valid at the current location of the vehicle V, based on the area attributes corresponding to the current location of the vehicle V and the valid areas recorded in the collection trigger list (on-board) 107. Furthermore, the trigger determination unit 108 monitors the recognition results from the on-board sensor 120 based on the occurrence conditions corresponding to the identified triggers, and determines whether or not a trigger has occurred. If it determines that a trigger has occurred, it notifies the recording unit 109 of this fact, along with the target data, target time, and image quality correction value recorded in the collection trigger list (on-board) 107.

[0040] In response to notification of the occurrence of a trigger from the trigger determination unit 108, the recording unit 109 acquires the data designated as target data from the output of the on-board sensor 120 as vehicle data D, adjusts the quality of the vehicle data D, i.e., adjusts the data size, in accordance with the data quality determined by the data quality determination unit 106, and records the vehicle data D in the data recording storage 110.

[0041] 4 shows an example of the area map 11 managed by the data collection center 10. As described above, the area map 11 uniquely identifies the area attribute to which the current location of the vehicle V belongs based on the coordinate information of the current location of the vehicle V.

[0042] In the example shown in the figure, all areas on the map are classified into three road types: "expressway," "main road," and "residential road," plus "other." In this embodiment, the current location of the vehicle V is classified into one of these four area attributes: "expressway," "main road," "residential road," and "other." However, the number of area attributes is not limited to four, and the number of types may be increased or decreased.

[0043] For example, area attributes may be classified based on the degree of influence of a predetermined area, an accident-prone area, a congested area, lane type (driving lane, passing lane, etc.), climate, weather, day / night, etc. Furthermore, multiple area attributes may be set for the same location, or the area attribute may be changed depending on the time of day.

[0044] The area map 11 managed by the data collection center 10 is a wide-ranging map (for example, the entire territory of Japan), but the area map (on-board) 102 that the data recording device 100 reads from the data collection center 10 and stores in the non-volatile memory 4 may be the same wide-ranging map as the area map 11, or may be a narrower map based on the current location of the vehicle V (for example, the prefecture where the vehicle V is currently located). In this case, the area map (on-board) 102 may be updated as appropriate according to the current location of the vehicle V so that the current location of the vehicle V does not deviate from the area map (on-board) 102.

[0045] <Collection Trigger List 12 Managed by Data Collection Center 10> FIG. 5 shows an example of the collection trigger list 12 managed by the data collection center 10. As shown in FIG.

[0046] The collection trigger list 12 associates data collection triggers with trigger IDs that can uniquely identify them, and records the effective area representing the area attributes that are the target of each trigger, the conditions under which each trigger occurs, the target data to be collected when each trigger occurs, the target time representing the time period before and after the trigger occurs during which the target data is recorded, the target number of collections and cumulative number of collections of target data for each trigger, and the image quality correction value.

[0047] In the example of Figure 5, the conditions for generating each trigger are expressed as names indicating the state of vehicle V (collision detection, override (driver intervening to drive during automatic driving), poor signal recognition, etc.), but this is not limited to this and may also be the output value of a sensor that identifies the state of vehicle V.

[0048] Although all examples of target data are video data, the target data may also include various sensor outputs such as radar images, LiDAR images, vehicle speed, steering operation amount, accelerator and brake operation amount, etc.

[0049] For example, a target time of (-20, 10) means that target data is recorded from 20 seconds before to 10 seconds after the trigger occurrence timing.

[0050] The target number of collections is a value that is specified and updated by the user of the vehicle data D. Note that there may be a trigger for which the target number of collections is not specified. In this case, target data is recorded without an upper limit in response to the occurrence of the trigger, so that important target data is not missed and can be recorded in a high-quality state.

[0051] The cumulative number of collected data is the number of vehicle data D uploaded from each vehicle V and accumulated in the collected data DB 14.

[0052] The image quality correction value is a value that influences the final determination of data quality in the data quality determination unit 106, and is calculated in the data collection center 10. The image quality correction value is a function of a value X based on the target number of collections and the cumulative number of collections, and the function f(X) as the image quality correction value is defined, for example, as in the following equation (1).

[0053]

[0054] In equation (1), X is the quotient obtained by dividing the cumulative number of collected images by the target number of collected images. The image quality correction value f(X) is expressed as a step function.

[0055] However, the image quality correction value f(X) is not limited to equation (1), and any calculation formula may be used. For example, a step function with three or more steps may be used, or a function that varies linearly depending on X may be used.

[0056] For example, a fixed value may be specified as the image quality correction value for a trigger for which the target number of images to be collected is not defined, such as trigger ID 000 whose occurrence condition is "collision detection," or for a trigger that corresponds to an important scene regardless of the cumulative number of images to be collected. Also, for trigger ID 0001 whose occurrence condition is "override," the target number of images to be collected does not need to be defined.

[0057] <Regarding the collection trigger list (on-board) 107 stored in the non-volatile memory 4 of the data recording device 100> FIG. 6 shows an example of the collection trigger list (on-board) 107 stored in the non-volatile memory 4 of the data recording device 100.

[0058] The collection trigger list (on-board) 107 is obtained by extracting only necessary information from the collection trigger list 12 managed by the data collection center 10 and storing it in the non-volatile memory 4 of the data recording device 100 .

[0059] 6, the effective area, occurrence condition, target data, target time, and image quality correction value are recorded in association with the trigger ID from the collection trigger list 12 (FIG. 5), but the target number of collections and the cumulative number of collections are not recorded. However, instead of the target number of collections and the cumulative number of collections, an image quality correction value calculated based on the target number of collections and the cumulative number of collections is recorded.

[0060] <Data Quality Tables 13 and 105> FIG. 7 shows an example of the data quality tables 13 and 105. As shown in FIG.

[0061] In the figure, three types of parameters, namely, the frame rate of the video data, the pixel magnification, and the image quality, are specified in association with each area attribute. These are parameters that are referenced when a trigger occurs in the case of each area attribute of the current location of the vehicle V.

[0062] The frame rate is a value that indicates how many images the video data consists of per second. For example, the frame rate is increased when driving at high speeds (when the area attribute is a highway), and decreased when driving at low speeds (when the area attribute is a residential road).

[0063] The pixel number magnification is a value by which the number of pixels of the image constituting the original video data is multiplied when the video data is recorded. The image quality is a parameter used when encoding the video data in the recording unit 109, and in this embodiment, the larger the value, the better the image quality (however, the larger the data size).

[0064] For example, in a residential area (when the area attribute is a residential road), the number of pixels and image quality can be increased to make the image more detailed. Conversely, in a place where there is little change in the surroundings, such as a highway (when the area attribute is a highway), the number of pixels and image quality can be decreased.

[0065] Note that the parameters that can adjust the data size of the video data associated with each area attribute are not limited to those described above, and may include, for example, the bit rate of the entire video data and the number of vertical and horizontal pixels. In this specification, these parameters are collectively referred to as encoding parameters.

[0066] <Regarding Trigger Identification Processing> FIG. 8 is a flowchart showing an example of trigger identification processing by the data recording device 100. As shown in FIG.

[0067] The trigger identification process is initiated, for example, in response to an operation by the driver to put the vehicle V into a state in which it can be driven (for example, turning on the ignition button).

[0068] First, the communication unit 101 reads the area map 11, collection trigger list 12, and data quality table 13 managed by the data collection center 10, and stores them in the non-volatile memory 4 as the area map (on-board) 102, the collection trigger list (on-board) 107, and the data quality table 13 (step S301).

[0069] Next, the self-position identifying unit 103 identifies coordinate information representing the current location of the vehicle V based on the output of the on-board positioning sensor (step S302).

[0070] Next, the area attribute acquisition unit 104 acquires area attributes corresponding to the current location of the vehicle V based on the coordinate information representing the current location of the vehicle V and the area map (on-board) 102 (step S303).

[0071] Next, the trigger determination unit 108 identifies one or more triggers that are valid at the current location of the vehicle V based on the area attributes corresponding to the current location of the vehicle V and the valid areas recorded in the collection trigger list (on-board) 107 (step S304). After this, the process returns to step S301, and the subsequent steps are repeated until the driver performs an operation to end the driving of the vehicle V (for example, an operation to turn off the ignition button).

[0072] <Processing When a Trigger Occurs> FIG. 9 is a flowchart showing an example of processing by the data recording device 100 when a trigger occurs.

[0073] The processing when a trigger occurs is initiated, similar to the trigger identification processing described above, in response to, for example, an operation by the driver of the vehicle V to put the vehicle V into a state where it can be driven (for example, an operation of turning on the ignition button), and is executed in parallel with the trigger identification processing.

[0074] First, the trigger determination unit 108 monitors the recognition result output by the on-board sensor 120 (step S401), and determines whether the trigger occurrence condition determined in the trigger identification process described above is satisfied (step S402). If it is determined that the trigger occurrence condition is not satisfied (NO in step S402), the trigger determination unit 108 returns the process to step S401 and repeats steps S401 and S402.

[0075] If it is determined that the trigger occurrence conditions are met (YES in step S402), the trigger determination unit 108 then notifies the data quality determination unit 106 of the trigger ID corresponding to the trigger that has occurred, and refers to the collection trigger list (on-board) 107 to obtain the target data and target time corresponding to the trigger that has occurred, and notifies the recording unit 109 (step S403).

[0076] Next, the data quality determination unit 106 refers to the area attributes of the current location, the data quality table 105, and the image quality correction values ​​in the collection trigger list (on-board) 107, determines encoding parameters, and notifies the recording unit 109 (step S404).

[0077] For example, assume that the area attribute of the current location is "residential road" and a trigger with trigger ID 002 has occurred. In this case, the trigger determination unit 108 references the collection trigger list (on-board) 107 to obtain the target data "front camera video" and "side camera video" and the target time (-10, 0) corresponding to trigger ID 002. The data quality determination unit 106 also references the collection trigger list (on-board) 107 to obtain the image quality correction value 0.8 corresponding to trigger ID 002. The data quality determination unit 106 then references the data quality table 105 to obtain the encoding parameters of the video data: a frame rate of 10, a pixel count magnification of 0.5, and an image quality of 70, and multiplies the image quality by the image quality correction value 0.8 to determine the image quality as 56.

[0078] Next, the recording unit 109 acquires the target data for the target time (step S405) and encodes the acquired target data in accordance with the determined encoding parameters (step S406). Next, the recording unit 109 records the encoded target data in the data recording storage 110 (step S407). After this, the process returns to step S401, and the subsequent steps are repeated until the driver performs an operation to end the running of the vehicle V (for example, by turning off the ignition button).

[0079] As described above, according to the first embodiment, it is possible to collect vehicle data D required by users of the vehicle data D according to the cumulative number of collections per trigger, while achieving both the usefulness of the vehicle data (target data) D and the utilization efficiency of the data recording storage 110. Specifically, vehicle data D for which the cumulative number of collections is equal to or less than the target number of collections can be collected with high quality in the collected data DB 14. Conversely, vehicle data D for which the number of vehicle data D is saturated, i.e., the cumulative number of collections is greater than the cumulative number of collections, can be collected in a small size in the collected data DB 14. This makes it possible to save the capacity of the collected data DB 14.

[0080] <Example of Area Map 11> Fig. 10 shows another example of the area map 11. In the example of the area map 11 shown in Fig. 4, area attributes are set according to road type, but as shown in Fig. 10, the area map 11 may set area attributes in a format similar to a heat map, regardless of road type. In the case of the area map 11 of Fig. 10, the area attributes can also be identified from the coordinate information of the current location of the vehicle V.

[0081] 11 shows the flow of data in a data collection system 1 according to a second embodiment of the present invention. The second embodiment is based on the premise that a vehicle V is connectable to the network N at all times or almost all times during operation, and omits the process in the first embodiment ( FIG. 3 ) in which the data recording device 100 reads the area map 11, collection trigger list 12, and data quality table 13 from the data collection center 10 and stores them in the non-volatile memory 4 as an area map (on-board) 102, a collection trigger list (on-board) 107, and a data quality table 105.

[0082] Whenever it becomes necessary to refer to these, the data collection center 10 can be accessed and referenced. Specifically, the area attribute acquisition unit 104 references the area map 11 of the data collection center 10 via the communication unit 101 at specified intervals and acquires the area attributes using the self-location estimation result. Furthermore, when the recording unit 109 notifies the occurrence of a trigger and the trigger ID, the data quality determination unit 106 references the data quality table 13 of the data collection center 10 via the communication unit 101 and acquires the corresponding parameters.

[0083] According to the second embodiment, the storage capacity of the nonvolatile memory 4 installed in the vehicle can be saved compared to the first embodiment, and therefore it is possible to increase the capacity allocated to the data recording storage 110.

[0084] In the above-described embodiment, the video data is recorded as vehicle data in the data recording storage 110 and uploaded to the data collection center 10, but sensor outputs other than the video data may be recorded as vehicle data in the data recording storage 110 and uploaded to the data collection center 10.

[0085] The present invention is not limited to the above-described embodiments, and various modifications are possible. For example, the above-described embodiments have been described in detail to clearly explain the present invention, and the present invention is not necessarily limited to those including all of the described configurations. Furthermore, it is possible to replace part of the configuration of one embodiment with or add to the configuration of another embodiment.

[0086] Furthermore, some or all of the aforementioned configurations, functions, processing units, processing means, etc. may be implemented in hardware, for example, by designing them as integrated circuits. Furthermore, the aforementioned configurations, functions, etc. may be implemented in software by a processor interpreting and executing programs that implement the respective functions. Information such as programs, tables, and files that implement the respective functions may be stored in memory, a recording device such as a hard disk or SSD, or a recording medium such as an IC card, SD card, or DVD. Furthermore, the control lines and information lines shown are those considered necessary for explanation, and do not necessarily represent all control lines and information lines in the product. In reality, it can be assumed that almost all components are interconnected.

Claims

1. A data collection system comprising a data collection server and a data recording device mounted on a vehicle, wherein the data recording device: - refers to an area map representing the correspondence between position information and area attributes to obtain the area attribute corresponding to the current location of the vehicle; - refers to a collection trigger list representing the correspondence between the area attribute, the generation condition of a trigger, and information regarding recording of target data to be collected to specify the generation condition corresponding to the area attribute of the current location of the vehicle; - determines the occurrence of the trigger based on the output of an in-vehicle sensor and the generation condition of the trigger; - determines encoding parameters for adjusting the data size when recording data according to a correction value calculated based on the cumulative number of collected vehicle data stored in the data collection server; - records vehicle data generated by encoding the target data according to the encoding parameters in a memory resource; - and transmits the recorded vehicle data to the data collection server.

2. The data collection system according to claim 1, wherein the determined encoding parameters include at least one of the frame rate, pixel number magnification, image quality, bit rate, and vertical and horizontal pixel numbers when encoding video data which is the target data.

3. The data collection system according to claim 2, wherein the data recording device changes the image quality of video data according to the determined encoding parameters.

4. The data collection system according to claim 1, wherein the types of the area attributes include at least one of road type, a predetermined area, an accident-prone area, a congested area, lane type, and the degree of influence of climate, weather, and day and night.

5. The data collection system according to claim 1, wherein the generation conditions of the trigger include at least one of collision detection, override, and signal recognition failure.

6. The data collection system according to claim 1, wherein the data collection server calculates the correction value based on the cumulative number of collected vehicle data and the target number of collected target data set in the collection trigger list, and notifies the calculated correction value to the data recording device. A data collection system characterized by the above.

7. The data collection system according to claim 6, wherein the data collection server records a fixed value as the correction value in the collection trigger list for at least one of the collision detection and override of the generation conditions of the trigger for which the target collection number is not set, and notifies the correction value recorded in the collection trigger list to the data recording device. A data collection system characterized by the above.

8. The data collection system according to claim 1, wherein the data recording device acquires the area map from the data collection server and stores it in the memory resource, and acquires the area attribute of the current location of the vehicle based on the output of the positioning sensor mounted on the vehicle with reference to the stored area map. A data collection system characterized by the above.

9. A data recording device for vehicle use, which is composed of one or more arithmetic units and computer resources including one or more memory resources, wherein the arithmetic unit is an area attribute acquisition unit that acquires an area attribute corresponding to the current location of the vehicle by referring to an area map representing the correspondence between location information and area attributes; the arithmetic unit is a trigger determination unit that refers to a collection trigger list representing the correspondence between the area attribute, the generation condition of the trigger, and information related to the recording of target data to be collected, specifies the generation condition corresponding to the area attribute of the current location of the vehicle, and determines the generation of the trigger based on the output of the in-vehicle sensor and the generation condition of the trigger; the arithmetic unit is a data quality determination unit that determines an encoding parameter for adjusting the data size when recording data according to a correction value calculated based on the cumulative number of vehicle data accumulated in the data collection server; the arithmetic unit is a recording unit that records the vehicle data generated by encoding the target data according to the encoding parameter in the memory resource; and the arithmetic unit is a communication unit that transmits the vehicle data recorded in the memory resource to the data collection server. The data recording device is characterized by the above components.

10. The data recording device according to claim 9, wherein the communication unit acquires the area map from the data collection server and stores it in the memory resource, and the area attribute acquisition unit acquires the area attribute of the current location of the vehicle based on the output of the positioning sensor mounted on the vehicle by referring to the stored area map. The data recording device is characterized by the above components.

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