Data collection instruction device

Abstract

To provide a data collection instruction device that can select the type of vehicle to instruct to collect probe data depending on whether or not there is snow coverage in a predetermined area.SOLUTION: A data collection instruction device includes a determination unit 61 that determines whether there is snow coverage in a predetermined area, and a notification processing unit 62 that, if there is snow coverage, sends a collection instruction to a snow removal vehicle via a communication device to instruct the snow removal vehicle to collect probe data representing a predetermined type of feature in the predetermined area, and on the other hand, if there is no snow coverage, sends the collection instruction to a vehicle other than the snow removal vehicle via the communication device.SELECTED DRAWING: Figure 8

Description

Technical Field

[0001] The present invention relates to a data collection instruction device for instructing collection of data used for generating or updating a map.

Background Art

[0002] In a high-precision map that a vehicle's automatic driving system refers to for automatically driving and controlling the vehicle, it is required to accurately represent information about roads. Therefore, data representing roads or features around the roads within a predetermined area, obtained by sensors mounted on the vehicle, is collected from vehicles that have actually traveled in the predetermined area. However, depending on the weather around the vehicle, it becomes difficult to detect such features from sensor signals. Therefore, a technique of referring to weather information when collecting data has been proposed (see Patent Document 1).

[0003] In the technique disclosed in Patent Document 1, a vehicle-side device for a road map update system sequentially determines whether a road on which the vehicle is traveling is a new road not included in the road map data. Then, when it is determined that the road on which the vehicle is traveling is a new road, the vehicle-side device transmits an image of the periphery of the vehicle captured by an in-vehicle camera to a map management device based on the determination that the image captured by the in-vehicle camera can be used for updating the center-side road map data based on the weather information.

Prior Art Documents

Patent Documents

[0004]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0005] In some regions, the state of snow accumulation on the road may continue for a long period. In such cases, with the above-described technology, no images are collected and the map information is not updated while the snow remains. Therefore, it is desirable to be able to collect data representing ground features that can be used for generating or updating map information even when there is snow on the road.

[0006] Therefore, an object of the present invention is to provide a data collection instruction device that can select the type of vehicle for instructing the collection of probe data according to the presence or absence of snow accumulation in a predetermined area.

Means for Solving the Problem

[0007] According to one embodiment, a data collection instruction device is provided. This data collection instruction device includes a determination unit that determines whether there is snow accumulation in a predetermined area, and when there is snow accumulation, a collection instruction for instructing the collection of probe data representing a predetermined type of ground feature for the predetermined area is notified to a snow removal vehicle via a communication device. On the other hand, when there is no snow accumulation, a notification processing unit that notifies a collection instruction to a vehicle other than the snow removal vehicle via the communication device.

Effect of the Invention

[0008] The data collection device according to the present disclosure has an effect that it can select the type of vehicle for instructing the collection of probe data according to the presence or absence of snow accumulation in a predetermined area.

Brief Description of the Drawings

[0009]

Figure 1

Figure 2

Figure 3

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Figure 8

Figure 9

Embodiments for Carrying out the Invention

[0010] Hereinafter, with reference to the drawings, a data collection device, a data collection method and a data collection computer program executed by the data collection device, and a data collection instruction device will be described. This data collection device is mounted on a vehicle. This data collection device generates data (hereinafter referred to as probe data) representing predetermined features on or around a road, which is used for generating or updating a map, based on an image representing the surroundings of the vehicle. At that time, this data collection device determines whether there is snow accumulation around the vehicle, and sets the type of feature to be detected according to the determination result. In particular, when there is snow accumulation, this data collection device sets features of a type that can be detected even with snow accumulation as the features to be detected.

[0011] FIG. 1 is a schematic configuration diagram of a data collection system in which a data collection device is implemented. In the present embodiment, the data collection system 1 includes a data collection device 3 mounted on at least one vehicle 2 and a server 4. The at least one vehicle 2 may be a snow removal vehicle, or may be a vehicle other than a snow removal vehicle such as a passenger car, a bus, or a truck. The data collection device 3 is connected to the server 4 via the radio base station 6 and the communication network 5, for example, by accessing a radio base station 6 connected via a communication network 5 to which the server 4 is connected and a gateway (not shown). In FIG. 1, as the at least one vehicle 2, one snow removal vehicle 2a and one passenger car 2b are shown, respectively. However, the data collection system 1 may have a plurality of snow removal vehicles equipped with the data collection device 3. Similarly, the data collection system 1 may have a plurality of vehicles other than snow removal vehicles equipped with the data collection device 3. Further, as in the modification example described later, when the server 4 notifies a collection instruction uniformly to each vehicle 2 regardless of the presence or absence of snow accumulation, the data collection system 1 may have only either a snow removal vehicle or a vehicle other than a snow removal vehicle. Furthermore, a plurality of radio base stations 6 may be connected to the communication network 5.

[0012] First, the vehicle 2 and the data collection device 3 will be described. As described above, the data collection system 1 may include a plurality of vehicles 2 equipped with the data collection device 3, and the vehicle 2 may be either a snow removal vehicle 2a or a vehicle 2b other than a snow removal vehicle. However, since each vehicle 2 and each data collection device 3 may have the same configuration and execute the same process with respect to the data collection process, hereinafter, one vehicle 2 and one data collection device 3 will be described.

[0013] Figure 2 is a schematic configuration diagram of the vehicle 2. The vehicle 2 includes a camera 21 for photographing the surroundings of the vehicle 2, a GPS receiver 22, a wireless communication terminal 23, and a data collection device 3. The camera 21, the GPS receiver 22, the wireless communication terminal 23, and the data collection device 3 are communicably connected via an in-vehicle network compliant with a standard such as a controller area network. Further, the vehicle 2 may further include a distance measuring sensor (not shown) such as a LiDAR sensor for measuring the distance to an object around the vehicle 2.

[0014] The camera 21 is an example of an imaging unit, and includes a two-dimensional detector composed of an array of photoelectric conversion elements sensitive to visible light, such as a CCD or a C-MOS, and an imaging optical system for forming an image of an area to be photographed on the two-dimensional detector. The camera 21 is mounted, for example, in the passenger compartment of the vehicle 2 so as to face the front of the vehicle 2. The camera 21 photographs the front area of the vehicle 2 at a predetermined photographing cycle (for example, 1 / 30 second to 1 / 10 second), and generates an image in which the front area is shown. The image obtained by the camera 21 may be a color image or a gray image. Note that the photographing direction of the camera 21 is not limited to the front direction of the vehicle 2. In particular, the camera 21 mounted on the snowplow vehicle 2a may be mounted so as to photograph the rear area of the snowplow vehicle 2a. Thereby, an image showing the road surface after snow removal is generated. Further, the vehicle 2 may be provided with a plurality of cameras 21 having different photographing directions or focal lengths.

[0015] Each time the camera 21 generates an image, the generated image is output to the data collection device 3 via the in-vehicle network.

[0016] The GPS receiver 22 receives GPS signals from GPS satellites at a predetermined period, and determines the self-position of the vehicle 2 based on the received GPS signals. Then, the GPS receiver 22 outputs, at a predetermined period, positioning information representing the result of determining the self-position of the vehicle 2 based on the GPS signals to the data collection device 3 via the in-vehicle network. Note that the vehicle 2 may have a receiver compliant with a satellite positioning system other than the GPS receiver 22. In this case, the receiver may determine the self-position of the vehicle 2.

[0017] The wireless communication terminal 23 is an example of a communication device, and is a device that executes wireless communication processing compliant with a predetermined wireless communication standard. For example, by accessing the wireless base station 6, the wireless communication terminal 23 is connected to the server 4 via the wireless base station 6 and the communication network 5. That is, a communication line is established between the wireless communication terminal 23 and the server 4 via the wireless base station 6 and the communication network 5. Then, the wireless communication terminal 23 receives a downlink wireless signal including a collection instruction signal or a signal representing a collection target area received from the server 4, and outputs the received signals to the data collection device 3. Further, the wireless communication terminal 23 generates an uplink wireless signal including specified type of collection target data (for example, probe data or an image) received from the data collection device 3. Then, the wireless communication terminal 23 transmits the uplink wireless signal to the wireless base station 6 to transmit the collection target data to the server 4.

[0018] FIG. 3 is a hardware configuration diagram of the data collection device 3. The data collection device 3 temporarily stores the image received from the camera 21. Further, the data collection device 3 generates probe data based on the image or the like, and temporarily stores the generated probe data. Then, the data collection device 3 transmits the probe data and the image to the server 4 via the wireless communication terminal 23. For this purpose, the data collection device 3 includes a communication interface 31, a memory 32, and a processor 33.

[0019] The communication interface 31 is an example of an in-vehicle communication unit and has an interface circuit for connecting the data collection device 3 to the in-vehicle network. That is, the communication interface 31 is connected to the camera 21, the GPS receiver 22, and the wireless communication terminal 23 via the in-vehicle network. And each time the communication interface 31 receives an image from the camera 21, it passes the received image to the processor 33. Also, each time the communication interface 31 receives positioning information from the GPS receiver 22, it passes the received positioning information to the processor 33. Furthermore, each time the communication interface 31 receives information from the server 4, such as a collection instruction signal, from the wireless communication terminal 23, it passes that information to the processor 33. Additionally, the communication interface 31 outputs the data to be collected and the like received from the processor 33 to the wireless communication terminal 23 via the in-vehicle network.

[0020] The memory 32 is an example of a storage unit and has, for example, a volatile semiconductor memory and a non-volatile semiconductor memory. The memory 32 may further have another storage device such as a hard disk drive. And the memory 32 stores various data used in the processes related to data collection executed by the processor 33 of the data collection device 3. For example, the memory 32 stores the identification information of the vehicle 2, and the parameters of the camera 21 such as the focal length, the shooting direction, and the installation position of the camera 21. Furthermore, the memory 32 stores various parameters for identifying a determiner for determining the presence or absence of snow accumulation, and various parameters for identifying an identifier for detecting a ground object from the image received from the camera 21. Also, the memory 32 stores the positioning information received from the GPS receiver 22. Additionally, the memory 32 stores the information representing the collection target area received from the server 4. Moreover, the memory 32 may store a computer program or the like for realizing each process executed by the processor 33.

[0021] Further, the memory 32 is provided with a storage area for storing images (hereinafter referred to as an image storage area) and a storage area for storing probe data (hereinafter referred to as a probe storage area). The images received by the data collection device 3 from the camera 21 are temporarily stored in the image storage area. Also, the probe data generated by the processor 33 is temporarily stored in the probe storage area.

[0022] The processor 33 includes one or more CPUs (Central Processing Units) and their peripheral circuits. The processor 33 may further include other arithmetic circuits such as a logical arithmetic unit, a numerical arithmetic unit, or a graphic processing unit. And the processor 33 executes data collection processing while the vehicle 2 is running.

[0023] FIG. 4 is a functional block diagram of the processor 33 of the data collection device 3. The processor 33 includes an image storage unit 41, a determination unit 42, a setting unit 43, a detection unit 44, and a communication processing unit 45. Each of these units included in the processor 33 is, for example, a functional module realized by a computer program operating on the processor 33. Alternatively, each of these units included in the processor 33 may be a dedicated arithmetic circuit provided in the processor 33.

[0024] Each time the data collection device 3 receives an image from the camera 21, the image storage unit 41 writes the image into the image storage area of the memory 32. At this time, each time the image storage unit 41 receives an image from the camera 21, it associates the position of the vehicle 2 represented by the latest positioning information and the orientation of the vehicle 2 indicated by an orientation sensor (not shown) with the image. Further, the image storage unit 41 may also associate parameters of the camera 21 such as the focal length, installation position, and shooting direction of the camera 21 with the image. The information associated with these images is uploaded to the server 4 together with the images themselves when the images are uploaded to the server 4.

[0025] The determination unit 42 determines whether there is snow accumulation around the vehicle 2. In the present embodiment, the determination unit 42 inputs the latest image received from the camera 21 into a discriminator pre-trained to be able to distinguish between a region covered with snow and other regions. Then, when the size of the region covered with snow indicated by the output result of the discriminator is equal to or greater than a predetermined snow accumulation determination threshold, the determination unit 42 determines that there is snow accumulation around the vehicle 2. As such a discriminator, the determination unit 42 can use a deep neural network (DNN) for semantic segmentation, such as a Fully Convolutional Network or a U-Net.

[0026] Alternatively, the determination unit 42 may determine whether there is snow accumulation around the vehicle 2 based on the weather information received from a server (not shown) for distributing weather information via the wireless communication terminal 23. In this case, the determination unit 42 determines whether the current position of the vehicle 2 indicated by the latest positioning information received from the GPS receiver 22 is included in the region with snow accumulation indicated by the weather information. Then, when the current position of the vehicle 2 is included in the region with snow accumulation, the determination unit 42 may determine that there is snow accumulation around the vehicle 2.

[0027] Note that hereinafter, the state in which it is determined that there is snow accumulation around the vehicle 2 may be simply referred to as having snow accumulation or snow accumulation time, and the state in which it is determined that there is no snow accumulation around the vehicle 2 may be simply referred to as having no snow accumulation or non-snow accumulation time. The determination unit 42 notifies the setting unit 43 of the determination result of the presence or absence of snow accumulation.

[0028] The setting unit 43 sets the type of the object to be detected based on the determination result of the presence or absence of snow accumulation notified from the determination unit 42. In the present embodiment, when it is determined that there is snow accumulation around the vehicle 2, the setting unit 43 sets, as the type of the object to be detected, a road or a three-dimensional structure located around the road. Such three-dimensional structures include, for example, poles or arrow signs indicating the position of the road shoulder, road signs, billboards, and traffic lights. This is because such three-dimensional structures are likely to be visible without being covered by snow even when the road surface around the vehicle 2 is covered with snow. Note that since the surface of the road sign may be covered with snow, the setting unit 43 preferably does not set the display content of the road sign as the detection target, but only the road sign itself. Similarly, the setting unit 43 preferably detects the billboard itself rather than the display content of the billboard. The positions of the road signs, billboards, and traffic lights are represented in, for example, a so-called high-precision map or a dynamic map so that they can be used for the localization process of detecting the position of the host vehicle. Furthermore, the three-dimensional structure to be detected may include a snow wall formed as a result of snow removal. However, since the position of the snow wall can change, although the position of the snow wall is used for updating the dynamic map, it is preferably not used for updating the high-precision map. The high-precision map is a map including information used to specify the position of the vehicle at the lane level, such as lane dividing lines. The dynamic map is a map including dynamic information such as quasi-dynamic or quasi-static information such as traffic information and information about surrounding vehicles in addition to such information.

[0029] On the other hand, when it is determined that there is no snow accumulation around the vehicle 2, the setting unit 43 sets, as the type of the object to be detected, a predetermined object including a road surface structure formed along the road surface of the road or the ground around the road. Such road surface structures include road markings such as lane dividing lines, stop lines, or crosswalks, and curbstones. Note that the predetermined objects to be detected when it is determined that there is no snow accumulation around the vehicle 2 may include three-dimensional structures such as poles and road signs that are detection targets during snow accumulation.

[0030] FIG. 5(a) and FIG. 5(b) are diagrams each showing an example of a ground object of a type to be detected during snow accumulation and during non-snow accumulation. In the example shown in FIG. 5(a), in an image 500 representing the surroundings of the vehicle 2, it is detected that there is snow accumulation. Due to the snow accumulation, the ground objects on the road surface are not visible. Therefore, as the ground objects to be detected, three-dimensional structures such as a pole 501 and a traffic signal 502 are set.

[0031] On the other hand, in the example shown in FIG. 5(b), in an image 510 representing the surroundings of the vehicle 2, no snow accumulation is detected, and the ground objects on the road surface are also visible. Therefore, as the ground objects to be detected, road markings such as lane dividing lines 511 are set.

[0032] The setting unit 43 notifies the detection unit 44 of the type of the set ground object to be detected.

[0033] During the running of the vehicle 2, the detection unit 44 detects, at predetermined intervals or each time the vehicle 2 travels a predetermined distance, the ground object of the type set by the setting unit 43 from the latest image generated by the camera 21. Then, the detection unit 44 generates probe data representing the type of the ground object detected on the image and the position of the ground object.

[0034] For example, the detection unit 44 detects a feature of a type to be detected represented in the input image by inputting the image to an identifier. As such an identifier, the detection unit 44 can use a DNN having a convolutional neural network (CNN) type architecture such as Single Shot MultiBox Detector or Faster R-CNN. Alternatively, the detection unit 44 may use a DNN having a self attention network (SAN) type architecture such as Vision Transformer as such an identifier. Or, the detection unit 44 may use an identifier based on another machine learning method such as an AdaBoost identifier as such an identifier. Such an identifier is pre-trained according to a predetermined learning method such as the error backpropagation method using a large number of teacher images in which the feature is represented, so as to detect a feature of a type to be detected from the image. Then, the identifier outputs information representing a region (for example, a circumscribed rectangle of the feature to be detected, hereinafter referred to as an object region) including the feature of the type to be detected on the input image, and information representing the type of the feature represented in the object region.

[0035] In this embodiment, a first discriminator used when it is determined that there is snow accumulation around the vehicle 2 and a second discriminator used when it is determined that there is no snow accumulation around the vehicle 2 are prepared separately. That is, the first discriminator is pre-trained to detect features of the type to be detected during snow accumulation from an image. In contrast, the second discriminator is pre-trained to detect features of the type to be detected during non-snow accumulation from an image. The first discriminator and the second discriminator may be based on different architectures or the same architecture. When the setting unit 43 notifies the type of feature when it is determined that there is snow accumulation around the vehicle 2, the detection unit 44 inputs the image to the first discriminator. As a result, features of the type to be detected during snow accumulation are detected from the image. On the other hand, when the setting unit 43 notifies the type of feature when it is determined that there is no snow accumulation around the vehicle 2, the detection unit 44 inputs the image to the second discriminator. As a result, features of the type to be detected during non-snow accumulation are detected from the image. In this way, by preparing discriminators separately for snow accumulation and non-snow accumulation, the types of features to be detected for each discriminator can be limited, so that the detection unit 44 can accurately detect the types of features to be detected.

[0036] Alternatively, a common discriminator may be used when it is determined that there is snow accumulation around the vehicle 2 and when it is determined that there is no snow accumulation around the vehicle 2. In this case, the discriminator is pre-trained to detect not only features of the type to be detected during snow accumulation but also features of the type to be detected during non-snow accumulation from an image. Then, the detection unit 44 inputs the image to the discriminator regardless of whether it is during snow accumulation or non-snow accumulation. However, during snow accumulation, the detection unit 44 may ignore detection results other than those of features of the type to be detected during snow accumulation among the detection results output from the discriminator. Conversely, during non-snow accumulation, the detection unit 44 may ignore detection results other than those of features of the type to be detected during non-snow accumulation among the detection results output from the discriminator. In this way, by using a common discriminator for snow accumulation and non-snow accumulation, the necessary hardware resources can be reduced.

[0037] The detection unit 44 estimates the position of the ground object represented in the object area based on parameters such as the orientation from the camera 21, the position of the vehicle 2 at the time of image generation, the traveling direction, the shooting direction of the camera 21, the focal length, and the installation position, corresponding to the center of gravity of the object area detected from the image. At this time, the detection unit 44 may estimate the position of the ground object by so-called Structure from Motion (SfM). In this case, the detection unit 44 associates the object areas representing the same ground object with each other using optical flow between two images obtained at different timings. Then, the detection unit 44 may estimate the position of the ground object by triangulation based on the position and traveling direction of the vehicle 2 when each of the two images was obtained, the parameters of the camera 21, and the position of the object area in each image. Then, the detection unit 44 generates probe data including information representing the type of the detected ground object and the estimated position. The detection unit 44 may further include information representing the position and traveling direction of the vehicle 2 at the time of image generation in the probe data. The detection unit 44 may further include information representing the size and position on the image of the object area in the probe data. Note that the detection unit 44 generates one probe data for each detected ground object. Therefore, when a plurality of ground objects are detected from one image, a plurality of probe data are generated from one image.

[0038] Each time the detection unit 44 generates probe data, it writes the generated probe data into the probe storage area of the memory 32.

[0039] The communication processing unit 45 transmits the data to be collected stored in the memory 32 to the server 4 via the wireless communication terminal 23.

[0040] The communication processing unit 45 refers to the information representing the area to be collected and the latest positioning information, and determines whether the vehicle 2 has entered the area to be collected. When the vehicle 2 enters the area to be collected, the communication processing unit 45 transmits the data to be collected for the area to be collected specified by the collection instruction signal to the server 4 via the wireless communication terminal 23.

[0041] Note that the collection target area is specified, for example, for each of one or more consecutive road sections or for each area having a predetermined shape. When the collection target area is specified as a road section, the information representing the collection target area includes identification information for identifying the road section and information representing the positions of the ends where entry or exit to / from the road section is possible. Further, when the collection target area is an area having a predetermined shape, the information representing the collection target area includes information representing the position of the outer edge of the area. And when the position of the vehicle 2 represented by the latest positioning information is included in the area or road section indicated by the information representing the collection target area, the communication processing unit 45 determines that the vehicle 2 has entered the collection target area.

[0042] When probe data is specified as collection target data, the communication processing unit 45 transmits the probe data stored in the probe storage area of the memory 32 to the server 4 via the wireless communication terminal 23 in order from the oldest.

[0043] Also, when probe data and images are specified as collection target data, the communication processing unit 45 transmits the probe data stored in the probe storage area of the memory 32 and the images stored in the image storage area to the server 4 via the wireless communication terminal 23 in order from the oldest, respectively.

[0044] Furthermore, the image specified as the collection target data may be a partial image. In this case, the communication processing unit 45 generates a partial image by cutting out the range estimated to represent the road surface from each of the individual images stored in the image storage area. Then, the communication processing unit 45 transmits the generated partial images to the server 4 via the wireless communication terminal 23 in order from the oldest, together with the probe data stored in the probe storage area of the memory 32.

[0045] Also, the communication processing unit 45 deletes the collection target data transmitted to the server 4 via the wireless communication terminal 23 from the memory 32.

[0046] When the vehicle 2 exits the collection target area, the communication processing unit 45 refers to the memory 32 to identify the collection target data that has not been transmitted at the time of exit. Then, when the transmission of the identified collection target data to the server 4 is completed, the communication processing unit 45 ends the transmission of the collection target data. Note that the communication processing unit 45 may determine whether the vehicle 2 has exited the collection target area by referring to the information representing the collection target area and the latest positioning information, in the same manner as determining whether the vehicle 2 has entered the collection target area.

[0047] FIG. 6 is an operation flowchart of data collection processing, particularly processing related to the generation of probe data. The processor 33 executes data collection processing according to the following operation flowchart at a predetermined cycle or each time the vehicle 2 travels a predetermined distance.

[0048] The image storage unit 41 of the processor 33 writes the image received by the data collection device 3 from the camera 21 into the image storage area of the memory 32 (step S101). Also, the determination unit 42 of the processor 33 determines whether there is snow accumulation around the vehicle 2 (step S102).

[0049] When there is snow accumulation around the vehicle 2 (step S102 - Yes), the setting unit 43 of the processor 33 sets a three-dimensional structure located on or around the road as the type of ground object to be detected (step S103). On the other hand, when there is no snow accumulation around the vehicle 2 (step S102 - No), the setting unit 43 sets a predetermined ground object including a road surface structure formed along the road surface or the ground around the road as the type of ground object to be detected (step S104).

[0050] After step S103 or S104, the detection unit 44 of the processor 33 detects the ground object of the set type from the image generated by the camera 21 and generates probe data representing the detected ground object (step S105). Then, the detection unit 44 writes the generated probe data into the probe storage area of the memory 32 (step S106). Then, the processor 33 ends the processing related to the generation of the probe data.

[0051] Since it is assumed that the presence or absence of snow accumulation does not change locally very much, the processor 33 may execute the processes of steps S102 to S104 only once before and after the vehicle 2 enters the collection target area.

[0052] As described above, this data collection device sets the type of ground object to be detected according to the presence or absence of snow accumulation around the vehicle. In particular, this data collection device, when there is snow accumulation, can detect even if the road surface is covered with snow, and sets the types of ground objects used for map generation or update as the types of ground objects to be detected. Therefore, this data collection device can collect probe data even when there is snow accumulation. Therefore, this data collection device can prevent the probe data from not being collected for a long period of time.

[0053] According to a modification, the setting unit 43 may set the type of ground object to be detected for each area on the image. That is, for the area determined to have snow accumulation, which is represented by the output result of the determination device of the determination unit 42, the setting unit 43 sets a three-dimensional structure as the type of ground object to be detected as in the above embodiment. On the other hand, for the area determined to have no snow accumulation, which is represented by the output result of the determination device, a predetermined ground object including a structure on the road surface is set as the type of ground object to be detected. Then, the detection unit 44 may detect the ground object of the type set for that area for each area. That is, the detection unit 44 may generate probe data only for the ground objects included in the area determined to have snow accumulation among the ground objects detected by inputting the image to the first discriminator. Similarly, the detection unit 44 may generate probe data only for the ground objects included in the area determined to have no snow accumulation among the ground objects detected by inputting the image to the second discriminator.

[0054] According to this modification, even when there is a mixture of areas where snow has been removed and areas where snow has not been removed around the vehicle, the data collection device can appropriately detect ground objects.

[0055] Next, the server 4 will be described. The server 4 is an example of a data collection instruction device, and selects the type of vehicle that instructs the collection of data to be collected according to the presence or absence of snow accumulation. Further, the server 4 designates the type of data to be collected for the collection target area. Then, the server 4 represents the specified type of data as data to be collected for the selected type of vehicle, and notifies a collection instruction signal that instructs the collection of the data to be collected. Further, the server 4 stores the probe data or image transmitted from the data collection device 3 mounted on each vehicle 2 to which the collection instruction signal has been notified. Then, the server 4 generates or updates a map of the collection target area based on those probe data or images. Further, the server 4 notifies each vehicle 2 of the collection target area.

[0056] FIG. 7 is a hardware configuration diagram of the server 4. The server 4 includes a communication interface 51, a storage device 52, a memory 53, and a processor 54. The communication interface 51, the storage device 52, and the memory 53 are connected to the processor 54 via signal lines. The server 4 may further include an input device such as a keyboard and a mouse, and a display device such as a liquid crystal display.

[0057] The communication interface 51 is an example of a communication unit, and has an interface circuit for connecting the server 4 to the communication network 5. And the communication interface 51 is configured to be able to communicate with the data collection device 3 mounted on each vehicle 2 via the communication network 5 and the radio base station 6. That is, the communication interface 51 passes the data to be collected received from the data collection device 3 of each vehicle 2 via the radio base station 6 and the communication network 5 to the processor 54. Also, the communication interface 51 transmits the collection instruction signal received from the processor 54 to the data collection device 3 of each vehicle 2 via the communication network 5 and the radio base station 6.

[0058] The storage device 52 is an example of a storage unit, and has, for example, a hard disk device or an optical recording medium and its access device. The storage device 52 stores type designation information, and for each of a plurality of road sections, the data to be collected collected for that road section, and the like. Further, the storage device 52 stores vehicle type information and identification information representing the type of each vehicle 2 (snow removal vehicle or other vehicle). Further, the storage device 52 may store a computer program for executing data collection processing on the server 4 side, which is executed on the processor 54. Furthermore, the storage device 52 may store a map generated or updated based on the data to be collected.

[0059] The memory 53 is another example of a storage unit, and has, for example, a non-volatile semiconductor memory and a volatile semiconductor memory. The memory 53 temporarily stores various data generated during the execution of the data collection process, and various data obtained by communication with each vehicle 2 such as probe data and images.

[0060] The processor 54 is an example of a control unit, and has one or a plurality of CPUs (Central Processing Units) and its peripheral circuits. The processor 54 may further have other arithmetic circuits such as a logical arithmetic unit or a numerical arithmetic unit. And the processor 54 executes data collection processing on the server 4 side.

[0061] FIG. 8 is a functional block diagram of the processor 54 of the server 4. The processor 54 has a determination unit 61 and a notification processing unit 62. Each of these units included in the processor 54 is a functional module realized by, for example, a computer program operating on the processor 54. Alternatively, each of these units included in the processor 54 may be a dedicated arithmetic circuit provided in the processor 54.

[0062] The determination unit 61 determines whether there is snow accumulation in the collection target area. For example, the determination unit 61 determines whether there is snow accumulation in the collection target area based on the weather information received from a server (not shown) for weather information distribution via the communication interface 51. To do so, the determination unit 61 compares the collection target area with the area with snow accumulation indicated by the weather information. And when a region of a predetermined ratio or more of the collection target area is included in the area with snow accumulation indicated by the weather information, the determination unit 61 may determine that there is snow accumulation in the collection target area. Alternatively, when a reference point (for example, the center or centroid of the collection target area) set within the collection target area is included in the area with snow accumulation indicated by the weather information, the determination unit 61 may also determine that there is snow accumulation in the collection target area.

[0063] Also, when the server 4 receives an image generated within the collection target area from any one of the vehicles 2 within a recent predetermined period (for example, several hours to 1 day), the determination unit 61 may determine the presence or absence of snow accumulation based on the image. In this case, the determination unit 61 may determine the presence or absence of snow accumulation based on the determination result obtained by inputting the image to a determiner for determining the presence or absence of snow accumulation, similar to the determination unit 42 of the data collection device 3. And when the determination unit 61 determines that there is snow accumulation based on the image, it determines that there is snow accumulation in the collection target area.

[0064] The determination unit 61 notifies the notification processing unit 62 of the determination result of the presence or absence of snow accumulation in the collection target area.

[0065] The notification processing unit 62 selects the type of vehicle to which the collection instruction is to be notified based on the determination result of the presence or absence of snow accumulation in the collection target area. Specifically, when there is snow accumulation in the collection target area, the notification processing unit 62 selects a snow removal vehicle as the type of vehicle to which the collection instruction is to be notified. On the other hand, when there is no snow accumulation in the collection target area, the notification processing unit 62 selects a vehicle other than the snow removal vehicle as the type of vehicle to which the collection instruction is to be notified. And the notification processing unit 62 specifies the vehicle of the selected type among each of the vehicles 2 by referring to the vehicle type information and the identification information.

[0066] The notification processing unit 62 refers to the type designation information corresponding to the collection target area. Then, based on the type designation information, the notification processing unit 62 identifies the type of collection target data designated for the collection target area. The types of collection target data include an image representing the environment around the vehicle 2 generated by the camera 21 mounted on the vehicle 2, a partial image representing the road surface cut out from the image, or probe data representing a ground object detected from the image. Therefore, in the type designation information, for each collection target area, one of the types of collection target data, namely image, partial image, and probe data, is indicated.

[0067] The notification processing unit 62 includes information for designating the identified type of collection target data in the collection instruction signal. When probe data is indicated in the type designation information, the notification processing unit 62 designates only the probe data as the collection target data. Also, when an image is indicated in the type designation information, the notification processing unit 62 designates the probe data and the image as the collection target data. Furthermore, when a partial image is indicated in the type designation information, the processor 54 designates the probe data and the partial image as the collection target data.

[0068] The notification processing unit 62 transmits the generated collection instruction signal to each individual vehicle 2 of the selected type via the communication interface 51, the communication network 5, and the radio base station 6.

[0069] If a plurality of collection target areas are set, the processor 54 may execute the processing of the determination unit 61 and the processing of the notification processing unit 62 for each collection target area.

[0070] Note that the processor 54 may set a collection target area based on the number of probe data collected for each road section stored in the storage device 52. For example, a road section where the number of probe data collected in the most recent predetermined period (e.g., several weeks to several months) is less than a predetermined collection threshold is set as the collection target area. Alternatively, the processor 54 may set, as the collection target area, a road section among the individual road sections represented in the map to be updated, for which the elapsed time since the previous update is equal to or more than a predetermined elapsed time threshold. Then, the processor 54 may notify the data collection device 3 of each vehicle 2 of the set collection target area via the communication interface 51.

[0071] Furthermore, the processor 54 may generate or update a map using the collected probe data and images. The map to be generated or updated is a map used for automatic driving control of the vehicle, and may be either a high-precision map or a dynamic map. The processor 54 aligns the features represented by the respective probe data collected for a continuous section from one vehicle 2 with the corresponding features represented by other probe data collected in the past or represented in the map to be updated. Then, the processor 54 identifies, as newly installed features, those among the features represented by the respective probe data collected for the continuous section for which there are no corresponding features in other probe data or in the map to be updated. Then, the processor 54 adds information (position and type) regarding the identified features to the map to be generated or updated. Also, the processor 54 may identify, as removed, a feature among the features represented in the map to be updated for which there is no corresponding feature in the features represented by the respective probe data collected for the continuous section. Then, the processor 54 may delete the information regarding the feature identified as removed from the map to be updated.

[0072] FIG. 9 is an operation flowchart of a process related to a data collection instruction. When the timing (for example, a predetermined date and time) comes, the processor 54 of the server 4 executes a process related to a data collection instruction according to the following operation flowchart.

[0073] The determination unit 61 of the processor 54 determines whether there is snow accumulation in the collection target area (step S201). When there is snow accumulation in the collection target area (step S201-Yes), the notification processing unit 62 of the processor 54 selects a snow removal vehicle as the type of vehicle to which the collection instruction is notified (step S202). On the other hand, when there is no snow accumulation in the collection target area (step S201-No), the notification processing unit 62 selects a vehicle other than the snow removal vehicle as the type of vehicle to which the collection instruction is notified (step S203).

[0074] After step S202 or S203, the notification processing unit 62 notifies the selected vehicle of a collection instruction signal via the communication interface 51, the communication network 5, and the radio base station 6 (step S204). Then, the processor 54 executes a process related to the data collection instruction.

[0075] As described above, this data collection instruction device selects the type of vehicle that instructs the collection of collection target data including probe data according to the presence or absence of snow accumulation in the collection target area. In particular, when there is snow accumulation in the collection target area, this data collection instruction device selects a snow removal vehicle as the vehicle that instructs the collection of collection target data. Therefore, this data collection instruction device can enable the generation and collection of probe data with the road surface visible to a certain extent even during snow accumulation. Therefore, this data collection instruction device can suppress a decrease in the accuracy of the ground objects represented in the probe data even during snow accumulation, and can also cause the data collection device to collect probe data about the ground objects represented on the road surface such as road markings. Also, when there is no snow accumulation, since the generation and collection of probe data are performed on vehicles other than snow removal vehicles that do not run much except during snow removal, this data collection instruction device can appropriately collect probe data even when there is no snow accumulation.

[0076] According to a modified example, the server 4 may notify a collection instruction uniformly to each vehicle 2 regardless of the presence or absence of snow accumulation in the collection target area. Further, as described above, when the server 4 designates a vehicle for which data collection is instructed, in the data collection device mounted on each vehicle, the processes of the determination unit 42 and the setting unit 43 may be omitted on the assumption that probe data representing a type of ground object to be collected when there is no snow accumulation is collected.

[0077] As described above, those skilled in the art can make various changes according to the implemented form within the scope of the present invention.

Explanation of Signs

[0078] 1 Data collection system 2 Vehicle 2a Snow removal vehicle 2b Ordinary passenger car 21 Camera 22 GPS receiver 23 Wireless communication terminal 3 Data collection device 31 Communication interface 32 Memory 33 Processor 41 Image storage unit 42 Determination unit 43 Setting unit 44 Detection unit 45 Communication processing unit 4 Server 51 Communication interface 52 Storage device 53 Memory 54 Processor 61 Determination unit 62 Notification processing unit 5 Communication network 6 Wireless base station

Claims

【Claim 1】 A determination unit that determines whether there is snow accumulation in a predetermined area, When there is snow accumulation, a collection instruction for instructing the collection of probe data representing a predetermined type of ground object for the predetermined area is notified to a snow removal vehicle via a communication device. On the other hand, when there is no snow accumulation, the collection instruction is notified to a vehicle other than the snow removal vehicle via the communication device. A notification processing unit, A data collection instruction device having the above.

Images