Patent Publication Number: US-2021180963-A1

Title: Onboard device

Description:
CROSS-REFERENCE TO RELATED APPLICATIONS 
     The present application is a continuation application of International Application No. PCT/JP2019/033512, filed on Aug. 27, 2019, which claims priority to Japanese Patent Application No. 2018-163078 filed on Aug. 31, 2018. The contents of these applications are incorporated herein by reference in their entirety. 
    
    
     BACKGROUND 
     1. Technical Field 
     The present disclosure relates to an onboard device. 
     2. Related Art 
     There is an onboard device that is mounted on a vehicle, acquires information necessary for travel based on information on a vehicle and its surroundings and map data, and provides information for use in vehicle control. For example, in car navigation and autonomous driving, information necessary for travel is provided based on such information. 
     SUMMARY 
     The present disclosure provides an onboard device. According to one aspect of the present disclosure, an onboard device includes a map data provision unit, a computation unit and a determination unit. The map data provision unit is configured to provide map data pertaining to a road on which a vehicle travels. The computation unit is configured to, when vehicle probe data indicating the positions and shapes of a road and a feature in the vicinity of the vehicle is given, compare the vehicle probe data with the map data provided from the map data provision unit to calculate a difference. The determination unit is configured to, when the difference exceeds a threshold value beyond which control of the vehicle based on the map data and the probe data will be impaired, determine the detected vehicle probe data as vehicle probe data to be transmitted. 
    
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
       In the accompanying drawings: 
         FIG. 1  is an electrical configuration diagram showing an embodiment; 
         FIG. 2  is a schematic configuration diagram of a system; 
         FIG. 3  is a diagram showing the flow of determination processing; 
         FIG. 4  is a diagram showing the flow of deterioration determination; 
         FIG. 5  is a diagram illustrating the calculation of a difference degree; 
         FIG. 6  is a diagram showing a specific example of the difference degree; 
         FIG. 7  is a diagram illustrating the calculation of a control margin; 
         FIG. 8  is a first diagram showing a specific example of the control margin; 
         FIG. 9  is a second diagram showing a specific example of the control margin; 
         FIG. 10  is a diagram illustrating the calculation of a landmark margin; 
         FIG. 11  is a first diagram showing a specific example of the landmark margin; and 
         FIG. 12  is a second diagram showing a specific example of the landmark margin. 
     
    
    
     DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS 
     An onboard device is mounted on a vehicle, acquires information necessary for travel based on information on a vehicle and its surroundings and map data, and provides information for use in vehicle control. 
     In this case, regarding the map data, in order to capture the actual situation, that actually changes from moment to moment, there has been considered a system designed to transmit the information recognized, for example, by a sensor provided in the vehicle to a center that manages map information in a centralized manner (hereinafter referred to as center) for updating purposes. 
     However, if all the information detected during travel of the vehicle is sent as probe data to the center, the amount of information increases. Therefore, the amount of communication increases, and a heavy burden of information analysis processing is imposed on the center side. 
     Therefore, there is a method of transmitting only necessary information as probe data, for example, as presented in JP 2007-264731 A. In this method, the vehicle needs to know the information which is not analyzed by the center. For this purpose, the latest map information is always transmitted to the onboard device from the center, and the onboard device finds differences between the latest map information and the information detected by the onboard device, and transmits the differences to the center. 
     By adopting this method, it is possible to reduce the amount of information as compared with the technique of transmitting all the information detected, during travel, by the vehicle as probe data to the center. However, assuming that the amount of information detected as probe data is further increased in order to improve the accuracy, there arises a problem of an increase in burden of information analysis processing on the center side. 
     An object of the present disclosure is to provide an onboard device capable of minimizing the amount of data, detected by a vehicle during travel, to be transmitted to a center, during travel, by a vehicle to a center to the minimum necessary to reduce the burden of information analysis processing at the center. 
     The inventor has considered the following points for the above purpose. First, conventionally, probe data is collected for the purpose of keeping map information updated, as described above. However, when the significance of this is further investigated, the final purpose is not to keep the map information updated, but is actually to realize the function using the map information. So, even if there is a difference in map information, whether the difference is information necessary for using the map information can be adopted as a new criterion to decide whether to upload the difference information as probe data. 
     In other words, even if there is a difference between the information held by the center that manages the map data and the situation in the real world, no practical problem will arise if functionality can be realized in the vehicle that uses the map data. Therefore, based on such a way of thinking, the difference information at a level that is unnecessary to realize the function is not uploaded to the center, so that the amount of information/communication of the data to be uploaded from the vehicle to the center can be further reduced. 
     In the above case, for example, when the vehicle is equipped with a robust control system, even if there is a slight difference between the map data and the actual situation, it is possible to handle the difference and perform proper control. In other words, even if there is a difference between the real world and the map information due to a certain change in the real world, it is possible to perform control correctly by virtue of the robustness of the control system. 
     Therefore, it can be decided that this difference between the real world and the map information does not affect the control, and the difference does not have to be transmitted to the center, and can be regarded as a difference that does not change the map information. 
     However, even if the difference between the real world and the map information does not affect the control as described above, if another difference at such a level occurs in another place close to the place, the control system may not work properly due to these two differences between the real world and the map information. In this case, only when control is not performed correctly, these differences are transmitted from the onboard device of the vehicle to the center so that the map information is changed. 
     That is, at the timing when the information for updating the map is transmitted from the onboard device to the center, a situation necessarily occurs in which control is not performed correctly, and the end user is disadvantaged. 
     In light of the above circumstances, an onboard device according to an aspect of the present disclosure includes: 
     a map data provision unit configured to provide map data pertaining to a road on which a vehicle travels; 
     a computation unit configured to, when vehicle probe data indicating the positions and shapes of a road and a feature in the vicinity of the vehicle is given, compare the vehicle probe data with the map data provided from the map data provision unit to calculate a difference; and 
     a determination unit configured to, when the difference exceeds a threshold value beyond which control of the vehicle based on the map data and the probe data will be impaired, determine the detected vehicle probe data as vehicle probe data to be transmitted. 
     The above configuration is adopted so that, even if there is a difference between the map data and the vehicle probe data regarding the recognized features, it is determined by the determination unit that the vehicle probe data does not have to be transmitted to update the map data when it falls within a controllable value range in which the travel of the vehicle can be controlled based on the map data and the vehicle probe data. Therefore, it is possible to reduce the amount of the vehicle probe data to be transmitted. 
     The above object and other objects, features and advantages of the present disclosure will be further clarified by the following detailed description with reference to the accompanying drawings. 
     Hereinafter, an embodiment of the present disclosure will be described with reference to  FIGS. 1 to 12 . 
     In  FIG. 2  showing the overall configuration of this system, vehicles  1  to  3  travel on a road while collecting vehicle probe data as will be described below. The vehicles  1  to  3  are each provided with an autonomous driving system or driving support system, and perform driving control using the vehicle probe data and the map data. 
     The vehicles  1  to  3  each have a communication function, and transmit only vehicle probe data determined as vehicle probe data in which the map data needs to be updated in a manner as will be described below, among the detected vehicle probe data, to a server  4   a  of a map data collection center  4 . The map data collection center  4  transmits the received vehicle probe data to a server  5   a  of a map data update center  5 . 
     The map data update center  5  executes processing of updating the map data to map data corresponding to a latest situation based on the thus-transmitted vehicle probe data. The vehicles  1  to  3  acquire the latest map data updated and created at the map data update center  5  from a medium such as a DVD or by use of the communication function, and thus can obtain the latest map data. 
     Next, an onboard device  10  included in each of the vehicles  1  to  3  and the related configurations will be described with reference to  FIG. 1 . The onboard device  10  includes a computation unit  11  and a determination unit  12  as functional blocks. The computation unit  11  includes an outside situation recognition section  11   a , an own vehicle position identification section/landmark margin calculation section  11   b , a map data acquisition/storage section  11   c , and a data difference detection section/difference degree calculation section  11   d . The determination unit  12  includes a difference upload determination section  12   a  and a control⋅function realization section/control margin calculation section  12   b . The onboard device  10  actually has a configuration mainly composed of a CPU, and achieves the functions of the computation unit  11  and the determination unit  12  based on programs stored therein. 
     Sensors  20  are connected to the onboard device  10 . As the sensors  20 , a camera  20   a  that captures the outside of the vehicle, a radar  20   b , a LiDAR (Light Detection and Ranging/Laser Imaging Detection and Ranging)  20   c , an ultrasonic sensor  20   c , and the like are provided. When the sensor data detected by the sensors  20  are inputted to the onboard device  10 , the computation unit  11  is used to analyze the data and calculate it as the vehicle probe data indicating the outside situation. 
     The camera  20   a  captures the front and surrounding situations outside the vehicle, and outputs the video information as sensor data. The radar  20   b  and LiDAR  20   c  detect the front and surrounding situations of the vehicle and distances from features, and output the information as the sensor data. The ultrasonic sensor  20   d  outputs ultrasonic waves to detect whether an object exists in vehicle surroundings, and outputs the information as the sensor data. 
     A communication unit  30  handles external communication for the onboard device  10 , and communicates with the map data collection center  4  described above to transmit the vehicle probe data to be transmitted, which has been determined, in a manner as will be described later, by the onboard device  10 . In addition, the communication unit  30  communicates with the map data update center  5  described above to download the updated latest map data or receive necessary map data each time. 
     A recognized feature data storage unit  40  stores the data on features recognized by the onboard device  10 , which is read and used by the onboard device  10  as needed. A map data storage unit  50  stores and holds the latest map data downloaded from the server  5   a  of the map data update center  5  by the communication unit  30 . With regard to the map data, map data stored in a medium such as a DVD may also be utilized, or the map data updated by the map data update center  5  may be sequentially downloaded and thus stored and held as the latest map data. 
     A control output device  60  is a control device for controlling travel of the vehicles  1  to  3 , and controls the travel of the own vehicle in response to a travel control command created by the onboard device  10 . In an autonomous driving/driving support mode, the onboard device  10  creates a travel control command based on the information captured by the sensor  20 , and, in this case, refers to the map data as needed to realize highly accurate travel control. 
     &lt;Outline of Autonomous Driving/Driving Support System&gt; 
     Next, the outline of autonomous driving/driving support system in the vehicles  1  to  3  will be described. In this embodiment, the vehicles  1  to  3  are each equipped with an autonomous driving/driving support system. The role of the map data is an important element in the autonomous driving/driving support system. First, the autonomous driving/driving support system using the map data identifies the position of the own vehicle on the map data. 
     In this case, it is difficult to identify the position of a moving body on the earth, which is the absolute position thereof. GNSS (Global Navigation Satellite System) is generally used to identify the absolute position of a moving body, but, in that case, an error of about 10 m occurs. Therefore, there exists a technique of identifying the absolute position with higher accuracy, but which requires a large-scale device for measurement, so it is not realistic in terms of cost to install it in mass-produced vehicles. 
     Therefore, the onboard device  10  can adopt a technique of identifying the position including the above-described error, which has been captured from the communication unit  30  by GNSS, and then identifying where the own vehicle is located on the map data by using the map data with higher accuracy. Specifically, the position is identified by comparing the features on the map data with the surrounding information obtained from the sensor  20  and various other onboard sensors. 
     For example, the case is assumed where a state where a speed limit sign exists 10 m ahead of the own vehicle and that the own vehicle is traveling northward at a position 1.5 m away from the left outer line of the left lane is detected from the data obtained from onboard sensors. The own vehicle can acquire the map data on the surroundings of the own vehicle position estimated from the GNSS information, and calculate and identify where the own vehicle exists on the map data, from the shape of the road, i.e., lane and the positions of signs in the map data. 
     Next, control when the control⋅function of the own vehicle is realized in the autonomous driving/driving support system using the map data will be described. In some cases, it may not be possible to realize the control⋅function using only the surrounding information obtained from various onboard sensors, and the map data is used to deal with such cases. 
     For example, with regard to the function of traveling while keeping to the center of the lane, it is necessary to detect the front lane shape in advance for steering control, but, since there may be a blind corner in front, the front lane shape may not be recognized by the onboard sensors. In addition, it may be difficult for the onboard sensors to recognize the front lane shape due to weather conditions such as rain, snow or the like that make visibility poor. In such a case, the map data can be used to complement the recognition results of the onboard sensors, and the function of traveling while keeping to the center of the lane can be continued without interruption. 
     Next, the means of supplying the map data when the map data is utilized in the manner as described above will be described. 
     Any means of supplying the map data from the map data update center  5  to the onboard device  10  may be used, as described above, and such means can be classified as follows. 
     (1) The map data is captured and stored in the storage section  10   c  or the map data storage unit  50  of the onboard device  10  via a medium such as a CD or DVD flash memory. Alternatively, the map data in the medium may be read the onboard device  10 , as needed, in a state where the medium is attached to the device. 
     (2) The map data is captured and stored in the storage section  10   c  within the onboard device  10  or the map data storage unit  50  via a cellular communication network, Wi-Fi, Bluetooth (registered trademark) and the like, using the communication unit  30 . 
     In this case, either the map data on the whole country or only the map data on the surroundings of the location where the onboard devices  10  of the vehicles  1  to  3  exist may be stored as the map data held in the onboard device  10  or the map data storage unit  50 . 
     Further, the storage section  10   c  and the map data storage unit  50  may store the map data semi-permanently to reuse it, or may adopt a method of making a request to the map data update center  5  each time of use to obtain and use it. 
     In this embodiment, it is assumed that the amount of communication between the onboard device  10  and the map data collection center  4  is reduced to the minimum necessary, and thus the map data used, as data for comparison, by the onboard device  10  is desirably as fresh as possible. Therefore, it is preferable that the latest map data should always be acquired by the communication unit  30  using a wide area communication network or the like and used as data for comparison. This is because the permanent use of old map data as data for comparison tends to increase the gap between the map data and the outside situation as the real world, and does not match the purpose of suppressing the amount of communication of the vehicle probe data to be uploaded. 
     &lt;Description of Operation of Onboard Device  10 &gt; 
     Next, the operation of the onboard device  10  will be described. 
     The target to be recognized by the onboard device  10  as the situation in the real world, i.e., the outside situation, based on the sensor data detected by the sensor  20  is as follows. This is vehicle probe data required for vehicle control, and it is determined whether to transmit it to the map data collection center  4  as needed. 
     The target to be recognized includes road lane markings, pedestrian crossings, stop lines, channelizing strips, regulation arrows, and other markings drawn on the road surface such as information for use in traffic control and traffic regulation drawn on the road. In addition, targets provided as objects are, for example, signs for regulation, warning, guidance and assistance, traffic lights, and other objects which can serve as landmarks used by the onboard device to identify its own position. 
     Further the computation unit  11  of the onboard device  20  calculates the positions, forms, meanings, and the like of the targets described above, including, in the case of road lane markings, the three-dimensional positions of the markings and their colors such as white or yellow; and, in the case of signs, the three-dimensional positions of the signs themselves, the heights/widths of the signs, the three-dimensional positions of the support columns of the signs, the types of the signs, and the meanings of the signs. 
     As the sensors  20  that recognize the outside information, the camera  20   a , the radar  20   b , the LiDAR  20   c , the ultrasonic sensor  20   d , and the like are provided. It is not necessary to provide all of these sensors, and they can also be selectively provided. By combining the sensor data detected by these sensors  20 , GNSS information, and other vehicle information such as speed, the outside situation can be recognized. 
     &lt;Map Data Processing&gt; 
     Next, the contents of the map data processing by the onboard device  10  will be described with reference to  FIGS. 3 and 4 . In the following description, the contents of the map data processing will be described, as a whole, as being executed by the onboard device  10 , but, in terms of function, are operations shared by the computation unit  11  and the determination unit  12 . Furthermore, it is assumed that the onboard device  10  is controlling autonomous driving of the vehicle  1 . 
     First, the onboard device  10  identifies the current position in step A 1 . The onboard device  10  computes and identifies the current position by the own vehicle position identification section/landmark margin calculation section  11   b  based on the GNSS information received via the communication unit  30 . In this step, the approximate position of the own vehicle on the map is acquired. Next, the onboard device  10  reads the map data from the map data storage unit  50  in step A 2 . In this step, the onboard device  10  reads the map data on a region around the current position identified in step A 1  from the map data storage unit  50  by the map data acquisition/storage section  11   c.    
     Subsequently, the onboard device  10  performs outside situation recognition processing in step A 3 . In this step, the onboard device  10  first captures data regarding the outside situation, for example, from the camera  20   a , radar  20   b , LiDAR  20   c  and ultrasonic sensor  20   d  constituting the sensors  20 , sensors mounted in other vehicles, and the like by the outside situation recognition section  11   a.    
     After that, the onboard device  10  recognizes lane markings, pedestrian crossings, stop lines, channelizing strips and regulation arrows drawn with as markings on the road surface, other information for use in traffic control and traffic regulation drawn on the road, and the like, in the outside situation recognition section  11   a , and also recognizes signs and traffic lights provided as objects and other landmarks used by the onboard device to identify its own position. After that, the onboard device  10  saves the recognized feature data recognized by the outside situation recognition section  11   a  in the recognized feature data storage unit  40 , in step A 4 . 
     Next, the onboard device  10  performs deterioration determination processing in step A 5 . In this case, the deterioration information obtained by this processing is determined so that the data detected as the difference between the recognized feature data and the map data is intentionally not uploaded to the map data collection center  4 , or is transmitted in a state in which a “deterioration flag” is added thereto when it is uploaded. 
     For example, when it is decided, through recognition by the onboard device  10 , that a change is not a change intended by a road manager, like a change when a marking on the road, such as a painted lane marking, has been rubbed off and has disappeared due to deterioration or when a sign has been bent and changed in position, the change is determined as such deterioration information. 
     In this case, faintness or disappearance, due to deterioration, of the marking drawn on the road is determined by comparison in terms of the value of recognition confidence degree when the onboard device  10  recognizes the lane marking on the road and the lane marking position on the map data. 
     When the lane marking exists on the map data, and the recognition result by the onboard device  10  leads to a reduction in lane marking recognition confidence degree below the threshold value, so that the onboard device  10  determines that the lane cannot be detected, and, as a result, concludes that a difference between the map data and the outside situation has occurred, the onboard device  10  decides that the difference is due to “paint deterioration”, and adds a “deterioration flag” when the difference is recorded as the difference information. 
     The map data update center  5  sets the threshold value at the time of changing the data on the difference information added with the “deterioration flag” to be higher than those for other changes. This is because, even if the lane marking has become faint and has disappeared and thus cannot be seen in reality, the onboard device  10  determines that the lane marking should originally have existed there, and leaves the data on the map data, so that it may be able to be utilized in the control by the onboard device  10 . 
     The specific contents of the deterioration determination processing are performed by the outside situation recognition section  11   a  through the procedures shown in  FIG. 4 . In step B 1 , the onboard device  10  compares the recognized feature data with the map data. Based on this comparison result, the onboard device  10  decides, in step B 2 , whether any recognized feature has been changed, and, in the case of “NO”, terminates the processing with no change determination. 
     In the case of “YES” in step B 2 , the onboard device  10  decides, in the next step B 3 , whether the change state is due to shape deterioration such as when a sign has been bent and changed in position. In the case of “YES”, it sets the “deterioration flag” for shape deterioration. In the case of “NO” in step B 3 , the onboard device  10  proceeds to step B 4 . In step B 4 , the onboard device  10  decides whether the change state is due to paint deterioration such as when the marking on the road has been rubbed off or has disappeared due to deterioration, and, in the case of “YES”, sets the “deterioration flag” for paint deterioration. 
     When deciding, in step B 2 , that a change has occurred, which is not due to shape deterioration or paint deterioration, the onboard device  10  determines, in step B 7 , whether the change is due to any other deterioration. In the case of “YES”, the onboard device  10  proceeds to step B 8 , and sets “deterioration flag” corresponding to the determined deterioration. In the case of “NO” in step B 7 , the onboard device  10  decides that the change is intentional and not due to deterioration. As a result, the onboard device  10  terminates the deterioration determination processing and proceeds to the next step A 6 , determining that step A 5  in  FIG. 3  is completed. 
     In step A 6 , the onboard device  10  executes the function of controlling the autonomous driving by the control⋅function realization section/control margin calculation section  12   b  of the determination unit  12 , in consideration of the map data and the recognized feature data obtained in the manner described above, and outputs the control to the control output device  60 . 
     At this time, in step A 7 , first, the onboard device  10  compares the recognized outside situation with the map data to calculate a difference degree Vd, in the data difference detection section/difference degree calculation section  11   d  of the computation unit  11 . 
     Here, the data difference detection section/difference degree calculation section  11   d  of the onboard device  10  calculates, as the difference degree Vd, information obtained by quantizing a degree of difference between the real-world situation recognized in the manner described above and the stored map data. 
     In this case, the data difference detection section/difference degree calculation section  11   d  specifically calculates the difference degree Vd for each type of outside situation detected in a range in which the vehicle travels a certain distance, i.e., a determination range. The determination level for the difference degree Vd is set to differ depending on type. For example, the determination level for the sign position is set to less than 75%, and, specifically, when a positional discrepancy is found in one of four signs, the difference degree Vd is acceptable. The determination level for the stop line is set to 100%, and if a positional discrepancy is found even in one stop line, the difference information is uploaded. The determination level for the difference degree Vd is determined based on how the map data is used in the onboard device  10 . 
     The reason why the determination level for the sign position is low is as follows. Specifically, the sign position is utilized for identifying the position of the own vehicle in the map data, and the processing is not performed based on one sign, but comprehensive processing/determination is performed based on a plurality of sign positions. 
     On the other hand, when the stop line position is utilized to identify the position of the own vehicle, the front/rear position determination can be processed very clearly. Therefore, the positional difference of one stop line may greatly affect the position identification of the onboard device  10 . Also, in vehicle control, when stopping the vehicle at a stop line, positional deviation of the stop line may cause problems when there is uncertainty in processing performed by the onboard device  10 , for example, when the onboard device  10  has difficulty in recognizing the outside due to bad weather or when the outside situation cannot be seen due to the preceding vehicle or the like. 
     Next, the onboard device  10  decides, in step A 8 , whether the calculated value of the difference degree Vd can be regarded as substantially zero in consideration of error. In the case of “NO”, i.e., when the difference degree Vd cannot be regarded as zero, the onboard device  10  proceeds to step A 9  and calculates a control margin Vmc and a landmark margin Vml. 
     The control margin, as used herein, is an index indicating the margin when the onboard device  10  performs vehicle control. The onboard device  10  feeds back the results of vehicle control using the outside situation and the map data, for the purpose of quantification as to whether the vehicle was controlled with a sufficient margin, or in other words, whether control was impaired. 
     The onboard device  10  compares the result of control performed in consideration of the outside situation with the result of vehicle control assumed based on the information read from the map data in advance, when performing the vehicle control. Actually, the outside situation will be used preferentially. For example, in the case of the function of traveling while keeping to the center of the lane, possible contents to be compared are the amount of deviation of the vehicle from the center of the lane, the lateral acceleration of the vehicle, and the like. The onboard device  10  compares these numerical values, and decides that the control margin is large when each difference is small. 
     In the case of “YES” in step A 8 , the onboard device  10  performs step A 13  and terminates the processing. In step A 13 , the onboard device  10  decides not to upload the information to the map data collection center  4  because the difference degree Vd as the target for determination can be regarded as substantially zero. 
     Next, when proceeding to step A 10 , the onboard device  10  determines whether the control margin Vmc is larger than a predetermined threshold Nmc and the landmark margin Vml is larger than a predetermined threshold Nml. The onboard device  10  proceeds to step A 11  in the case of “NO” in step A 10 , that is, when both the control margin Vmc and the landmark margin Vml are equal to or less than the threshold values. 
     In the above case, the onboard device  10  determines both the control margin Vmc and the landmark margin Vml during vehicle control. Further, when not performing vehicle control, it determines only the landmark margin Vml. As a result, it can perform a determination including the conditions for the contents of the actually-performed control, and, even when not performing vehicle control, can perform a determination intended for this. 
     In step A 11 , the onboard device  10  performs processing of uploading the difference information calculated based on the sensor data as the vehicle probe data including the deterioration flag described above. As a result, the onboard device  10  transmits the vehicle probe data to the server  4   a  of the map data collection center  4  via the communication unit  30 . 
     On the other hand, in the case of “YES” in step A 10  described above, i.e., when both the control margin Vmc and the landmark margin Vml are sufficiently larger than the threshold values, the onboard device  10  proceeds to step A 12  in which it decides whether the difference degree Vd exceeds a predetermined threshold value Nd. When the difference Vd exceeds a certain amount though the control margin is sufficient, the onboard device  10  determines “YES”, proceeds to step A 11 , and performs processing of uploading the information as vehicle probe data. In the case of “NO” in step A 12 , the onboard device  10  performs step A 13  and terminates the processing. 
     By virtue of execution of the map data processing described above, the amount of communication can be reduced by omitting uploading of the vehicle probe data to the data collection center  4  if the vehicle control by the onboard device  10  can be performed without any trouble, even if the detected vehicle probe data has some difference from the map data. 
     &lt;Calculation of Difference Degree&gt; 
     Next, calculation examples of the difference degree Vd described above will be described with reference to  FIGS. 5 and 6 . The difference degree Vd is set for each type. For example, the difference degree regarding landmarks, i.e., features is Vdl, and the difference degree regarding markings is Vdp. Now, calculation examples of these difference degrees will be described. 
     The landmark difference Vdl is calculated as shown by equation (1) in  FIG. 5 . For the quantification processing, the number of features, i.e., landmarks, existing in both the recognized feature data and the map data is defined as Pcf, and the number of features existing in only one of these data is defined as Psf. Further, the phrase “features existing in both of these data” means that the features exist in both of these data at the same position and with the same attribute. 
     Next, the marking difference degree Vdp is calculated as shown by equation (2) in  FIG. 5 . For the quantification processing, the distance (length) of a marking existing in both the recognized feature data and the map data is defined as Lcp, and the distance (length) of a marking existing in only one of them is defined as Lsp. Further, the phrase “existing in both of these data” means that the marking exists in both of these data at the same position and with the same color. 
       FIG. 6  shows a specific example.  FIG. 6( a )  shows map data acquired, for example, by downloading on the vehicle side. Markings P 1  to P 5  that separate the lanes and four signs L 1  to L 4  are shown. 
     On the other hand,  FIG. 6( b )  shows feature data recognized by the onboard device  10 , for example, by means of the sensor  20 . The own vehicle travels on a track indicated by a broken line with an arrow, and there are markings P 1  and P 2  and three signs L 2  to L 4  as features existing around the trajectory. Among these, the marking P 2  is a lane marking of the lane adjacent to the lane on the own vehicle travels, which is shown as a marking P 2   a  in which an undetected portion exists in front. 
       FIG. 6( c )  shows the result of extracting the data on the surroundings of the trajectory of the own vehicle shown in  FIG. 6 ( b )  from the map data. In this figure, the markings P 1  and P 2  and four signs L 1  to L 4  are extracted. 
     When the difference Vd is calculated by executing the processing shown in step A 7  of the processing shown in  FIG. 3  described above, the result as shown in  FIG. 6( d )  is obtained. Difference data is shown in the left column. In this figure, the sign L 1  existing only in the map data is shown, and the other signs L 2  to L 4  exist in both of the map data and the recognized feature data, and thus are not displayed as differences. With regard to the markings, there is a difference in the marking P 2 , and an undetected portion in the recognized feature data is displayed as a difference. 
     From this result, the landmark difference degree Vdl can be calculated according to equation (1) as follows: 
     
       
         
           
             
               Vdl 
               = 
               
                 
                   Pcf 
                   / 
                   
                     ( 
                     
                       Pcf 
                       + 
                       Psf 
                     
                     ) 
                   
                 
                 = 
                 
                   
                     3 
                     / 
                     4 
                   
                   = 
                   
                     0.7 
                      
                     5 
                   
                 
               
             
             , 
           
         
       
     
     since the number of features Pcf existing in both of these data is 3, and the number of features Psf existing only in one of these data is 1. 
     Further, the marking difference degree Vdp can be calculated according to equation (2) as follows: 
     
       
         
           
             
               Vdp 
               = 
               
                 
                   Lcp 
                   / 
                   
                     ( 
                     
                       Lcp 
                       + 
                       Lsp 
                     
                     ) 
                   
                 
                 = 
                 
                   
                     17 
                      
                     
                       0 
                       / 
                       2 
                     
                      
                     00 
                   
                   = 
                   
                     0.8 
                      
                     5 
                   
                 
               
             
             , 
           
         
       
     
     since the distance Lcp of the marking existing in both of these data is 170 m, and the distance Lsp of the marking existing only in one of these data is 30 m. 
     &lt;Calculation of Control Margin&gt; 
     Next, a calculation example of the control margin Vcm described above will be described with reference to  FIGS. 7 and 9 . The control margin Vcm is obtained by quantifying the difference between the trajectory estimated from the map data and the locus of travel according to the actual vehicle control. The control margin Vcm is calculated as shown by equation (3) in  FIG. 7 . 
     For the quantification processing, here, the track difference permissible amount in a certain section is defined as D; the deviation amount of the travel track in the certain section from the estimated track is defined as AD; and the maximum value in the section is defined as ΔD max. Further, an operator MIN (A, B) shall take a smaller value of the numbers A and B in parentheses. 
     When the actual travel control is performed, the control margin in the traveled section is calculated according to the above definition. As a result, as shown by equation (3), when the maximum value ΔD max of the deviation amount exceeds the track difference permissible amount D, the margin Vcm becomes zero, and when the maximum value ΔD max is equal to or less than the track difference permissible amount D, the margin Vcm is obtained as a value larger than zero. 
     That is, when the onboard device  10  performs vehicle control based on the map data and the recognized feature data, the margin Vcm may be obtained as a value larger than zero even if there is a difference between these data. In this case, the onboard device  10  is able to perform vehicle control with a margin even if there is no updated map data corresponding to the difference degree, and it can be understood to be unnecessary to transmit the vehicle probe data having such a difference degree to the map data collection center  4 . 
       FIGS. 8 and 9  show specific examples 1 and 2. In  FIG. 8  showing specific example 1, the map data regarding the road acquired by downloading or the like on the vehicle side is shown at the upper left, and the trajectory Sc of the own vehicle estimated from the map data is shown by the dotted line in the figure. On the other hand,  FIG. 8  shows, at the upper right, the feature data regarding the road recognized by the onboard device  10 , for example, via the sensor  20 . The curve shape of the recognized road is gentler than the curve shape in the map data. The actual trajectory Sa of the own vehicle traveling according to the lane keeping control from the lane marking indicating the travel lane is shown in the figure. 
     On the lower side of  FIG. 8 , the map data and the recognized feature data are shown in a superimposed state, in order to compare the trajectory Sc estimated from the map data in a certain section with the actual trajectory Sa of the own vehicle. In the figure, a plurality of the deviation amounts ΔD between the estimated trajectory Sc and the actual trajectory Sa of the own vehicle (ΔD 1  to ΔDn) within the section are calculated, and the largest deviation amount, among these, is shown as ΔD max. Based on the thus-obtained results, the control margin Vcm 1  can be calculated according to the above equation (3). 
     In this case, the control margin Vcm 1  is calculated as follows. For example, when the maximum value ΔD max of the detected deviation amount ΔD is 0.3 m and the track difference permissible value D here is 0.1 m, the control margin Vcm in the section is calculated from equation (3) as follows. 
     
       
         
           
             
               Vmc 
                
               
                   
               
                
               1 
             
             = 
             
               
                 
                   ( 
                   
                     0.1 
                     - 
                     
                       MIN 
                        
                       
                         ( 
                         
                           0.3 
                           , 
                           
                             0 
                             . 
                             1 
                           
                         
                         ) 
                       
                     
                   
                   ) 
                 
                 / 
                 0.1 
               
               = 
               0 
             
           
         
       
     
     In  FIG. 9  showing specific example 2, the same map data as that shown in  FIG. 8  is shown at the upper left, and the trajectory Sc of the own vehicle estimated from the map data is shown by the dotted line in the figure. On the other hand,  FIG. 9  shows, at the upper right, the feature data regarding the road recognized by the onboard device  10 , for example, via the sensor  20 . The recognized road is provided with an evacuation region X on the outer side of the curve. The actual trajectory Sa of the own vehicle traveling according to the lane keeping control from the lane marking indicating the travel lane is shown in the figure. 
     On the lower side of  FIG. 9 , the map data and the recognized feature data are shown in a superimposed state, in order to compare the trajectory Sc estimated from the map data in a certain section with the actual trajectory Sa of the own vehicle. In the figure, a plurality of the deviation amounts ΔD between the estimated trajectory Sc and the actual trajectory Sa of the own vehicle (ΔD 1  to ΔDn) within the section are similarly calculated, and the largest deviation amount, among these, is shown as ΔD max. 
     In this case, the control margin Vcm 2  is calculated as follows. For example, when the maximum value ΔD max of the detected deviation amount ΔD is 0.02 m and the track difference permissible value D here is 0.1 m, the control margin Vcm 2  in the section is calculated from equation (3) as follows. 
     
       
         
           
             
               Vcm 
                
               
                   
               
                
               2 
             
             = 
             
               
                 
                   ( 
                   
                     0.1 
                     - 
                     
                       MIN 
                        
                       
                         ( 
                         
                           0.02 
                           , 
                           
                             0 
                             . 
                             1 
                           
                         
                         ) 
                       
                     
                   
                   ) 
                 
                 / 
                 0.1 
               
               = 
               0.8 
             
           
         
       
     
     &lt;Calculation of Landmark Margin&gt; 
     Next, a calculation example of the landmark margin Vml will be described with reference to  FIGS. 10 and 12 . The difference between the feature data read from the map data by the onboard device  10  and the actual recognized feature data can be detected regardless of whether during the travel control by the onboard device  10  or not. 
     In this case, when identifying the vehicle position on the map, the onboard device  10  recognizes a plurality of landmarks, i.e., signs to match the recognition result to the map data, and thus is usually designed to have robustness as the control function so as to be able to identify the own vehicle position even if there is some deviation. However, it is intended, on purpose, to virtually confirm and evaluate whether the position of the own vehicle could be identified properly when the landmarks recognized by the onboard device  10  could be used or recognized. 
     On the assumption of a state in which the number of landmarks are virtually decreased, it is estimated whether the onboard device  10  can identify its own position to determine a required number of landmarks LLM for identifying its own position. As shown by equation (4) in  FIG. 10 , the difference between the number of landmarks RLM properly recognized at present and the required number of landmarks LLM is the landmark margin Vml. 
     Since different map data are referred to and recognized for the control margin Vmc and the landmark margin Vml, the amount of communication can be suppressed by uploading only the relevant difference information when the vehicle probe data is uploaded as difference information to the map data collection center  4  through the margin determination. Therefore, for example, when the control margin Vmc is larger than the threshold value but the landmark margin Vml is smaller than or equal to the threshold value, only the vehicle probe data indicating the difference information relevant to landmarks is uploaded to the map data collection center  4 . 
     Examples of calculating the landmark margin Vml will be described with reference to  FIGS. 11 and 12 . On the left side of  FIG. 11 , signs L 0  to L 4  are shown on a four-lane road as landmarks indicated in the map data. On the other hand, on the right side of  FIG. 11 , a travel lane and signs L 1  to L 4  are shown as landmarks indicated in the data regarding the features recognized in a section. 
     In this case, the data regarding the features recognized in the section are the four signs L 1  to L 4 , which match the signs L 1  to L 4  in the map data, and the position can be identified by the onboard device  10 . The landmark margin Vml is calculated in this situation. 
     It is assumed that there is little recognized feature data as to whether the position can be identified by the onboard device  10 . As described above, the number of recognized landmarks RLM is 4. As shown in  FIG. 12 , assuming that one feature data cannot be recognized, there are four cases as shown in the figure, and the onboard device  10  can identify the position in all of these cases. Similarly, assuming that two feature data cannot be recognized, two cases are shown  FIG. 12 , but there are six cases. The onboard device  10  can also identify the position in all of these cases. 
     In contrast, two cases in which three feature data cannot be recognized are shown  FIG. 12 , but there are four cases, and the onboard device  10  cannot identify the position in these cases. Thus, in these cases, the required number of landmarks LLM for identifying its own position of the onboard device  10  in the section is 2. 
     As a result, the landmark margin Vml can be obtained according to equation (4) shown in  FIG. 10  as follows. 
     
       
         
           
             Vml 
             = 
             
               
                 4 
                 - 
                 2 
               
               = 
               2 
             
           
         
       
     
     According to this embodiment as described above, the computation unit  11  and the determination unit  12  are provided in the onboard device  10 , and, even if there is a difference between the map data and the vehicle probe data regarding the recognized features, it is determined by the determination unit  12  that the vehicle probe data does not have to be transmitted to update the map data when it falls within a controllable value range in which the travel of the vehicle can be controlled based on the map data and the vehicle probe data. Therefore, it is possible to reduce the amount of the vehicle probe data to be transmitted. 
     Other Embodiments 
     It should be noted that the present disclosure is not limited to the above embodiment, and can be applied to various embodiments without departing from the gist thereof. For example, the present disclosure can be modified or extended as follows. 
     While the present disclosure has been described with reference to an embodiment, it is to be understood that the disclosure is not limited to the embodiment and structure. The present disclosure covers various modification and equivalent arrangements. In addition, while the various combinations and configurations, other combinations and configurations, including more, less or only a single element, are also within the spirit and scope of the present disclosure.