JP2011027594A - Map data verification system - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To provide a technique for enabling detection of a difference of the natural features of the landscape between those in map data and those in the real world in a short time. <P>SOLUTION: This map data verification system includes a position detecting means which detects the position of a driver's own vehicle (100), the map data wherein the data on a road and the natural features of the landscape (301, 302 and 303) are stored, a distance measuring means such as a laser scanner or a stereo camera which measures a distance (101) to the natural feature of the landscape existing by the side of the road, an error part detecting means and a transmission means. The error part detecting means finds an estimate of the distance measured by the distance measuring means, from the position of the driver's own vehicle and the map data, and determines the part showing a difference from an actual measured distance, as the error part. The transmission means notifies a map control server (200) of the error part detected in the driver's own vehicle. <P>COPYRIGHT: (C)2011,JPO&INPIT

Description

  The present invention relates to a technique for verifying whether map data matches reality.

  In order to improve the freshness of the map data in the car navigation device, a map distribution mechanism and the like have been prepared (Patent Documents 1 and 2, etc.). By the way, in order to increase the freshness of the map data, the frequency of field surveys must be increased, but the update frequency is limited and it is difficult to always distribute the latest map data.

  In Patent Document 3, a landmark is recognized from an in-vehicle camera image and used for correction in order to improve the measurement accuracy of the vehicle position, and when the recognized landmark is different from the built-in map data, It is described that update information of map data is sent to the distribution center and that the latest map data is acquired from the map distribution center. In Patent Document 3, the map distribution center reports that the built-in map data is different from the actual one in consideration of the probability of the recognition result and the image capturing condition.

JP 2007-121528 A JP 2007-64951 A JP 2008-51612 A

  When the map data possessed by the car navigation device is old and different from the actual data, it is preferable that the location can be detected as early as possible. An object of the present invention is to detect a difference between map data and real-world features in a short time.

  In order to achieve the above object, in the present invention, the difference between the map data and the real world features is detected by the following means or processing.

  The map data verification system according to the present invention includes a vehicle and a server device that can communicate with each other by wireless communication means. The vehicle includes position detecting means for detecting the position of the host vehicle, map data storing road and feature data, distance measuring means for measuring a distance to the feature existing on the side of the road, and distance measuring means. An error detection means for detecting a location (error location) where the distance measured by the vehicle is different from a value predicted from the vehicle position and the map data, and a transmission means for transmitting information on the error location of the map data to the server device as error information And have. The server device includes a receiving unit that receives error information transmitted from the vehicle, and an error information storage unit that stores the received error information.

As the distance measuring means, a laser scanner or a stereo camera can be used. The laser scanner measures the distance to the measurement object by measuring the time for the laser pulse to reciprocate between the measurement object and the sensor. For example, if the laser scanner is fixed obliquely forward (left front and right front) of the vehicle, the distance to an object existing on the roadside can be measured as the vehicle moves. The laser scanner preferably scans at a predetermined frequency (for example, several tens to several hundreds hertz) in the vertical direction, but may not scan in the vertical direction. The stereo camera measures the distance to the measurement object based on the parallax of images taken from the two cameras. In the case of a stereo camera, it is possible to measure the distance for all of the objects to be photographed by one photographing.

  The map data is preferably three-dimensional map data. That is, it is preferable to store a three-dimensional shape of a road or a feature. However, even two-dimensional map data can be used in the present invention as long as the plane shape of the feature and the distance between the feature and the road are included in addition to the road information. That is, it is only necessary to include data capable of calculating the distance between an arbitrary point on the road and the feature. The feature means a non-moving body whose position is fixed on the ground surface except for a moving body among objects existing on the ground. The feature may be an artifact or a natural object, and the artifact includes, for example, a building, various facilities, a bridge, and a railway, and the natural object includes, for example, a mountain, a sea, a river, and the like. .

  The position of the host vehicle can be detected by position detection means. The position detection means is typically a GPS device, but the position information of the host vehicle may be obtained complementarily using an acceleration sensor or a gyro sensor. For position detection, wireless communication other than GPS, markers embedded in roads (magnetic markers, image markers, etc.) may be used. The traveling direction can also be detected from the history of the position of the host vehicle.

  If the position and traveling direction of the host vehicle are known, the distance to the feature located in the measurement direction by the distance measuring means can be calculated from the map data. When the distance to the feature calculated from the map data and the distance to the feature actually measured by the distance measuring means are different, it is understood that the map data is different from the actual. Specifically, according to the map data, if there is a feature near the side of the road, but the measured distance by the distance measuring means is larger than the predicted value, the feature that is supposed to exist in the map data Can be determined to have disappeared. On the other hand, if there is no feature near the side of the road in the map data, and the distance to the farther feature is determined to be measured, but the distance measured by the distance measuring means is short, , It can be determined that a new feature has been generated at that position. As described above, the error detection means can detect a location where the map data has an error (referred to as an error location).

  Note that the measurement of the distance to the feature by the distance measuring means may employ an average measurement distance during a certain measurement period (for example, the time during which the vehicle travels several meters). This is because the measurement using only one point may be affected by an error or may measure the distance to an obstacle. Further, when scanning in the vertical direction using a laser scanner as a distance measuring means, if the vehicle speed is slower than the scanning frequency, the three-dimensional shape of the feature can be measured. If the map data is also three-dimensional, compare the shape of the features in the map data with the measurement results to determine whether they are the same feature, and determine if there is an error in the map data Also good.

  Information on the error location detected by the error detection means is transmitted as error information to the server device by the transmission means. Such communication means (road-to-vehicle communication means) includes wireless communication such as mobile WiMAX, portable communication network, wireless LAN, DSRC (dedicated narrow area communication), and optical communication such as visible light communication and infrared light communication. Can be adopted. As described above, since the information on the error location is transmitted to the server device by road-to-vehicle communication, error information detected by a plurality of vehicles is collected in the server device. That is, the server device can collect many error locations in a short time. Thereby, the location where map data differs from reality can be detected in a short time.

A laser scanner or a stereo camera can be used as the distance measuring means. Laser scanners are not significantly affected by illumination, but at the time of rainfall, they are affected by raindrops and the measurement performance is degraded. Therefore, it is preferable not to perform the measurement by the laser scanner at the time of rain, or to add to the error information that the measurement is at the time of rain. Whether or not it is raining may be determined by, for example, whether or not the wiper is operating, or may be determined by acquiring information related to the weather by wireless communication or the like. Further, when a stereo camera is used as the distance measuring means, the measurement performance during the day is good, but the measurement performance is degraded in other cases (such as at night). Therefore, it is preferable not to perform the measurement by the stereo camera except during the daytime or to add to the error information that the measurement is other than during the daytime. Here, the daytime can be defined as, for example, between 1 hour after sunrise and 1 hour before sunset with reference to sunrise and sunset times.

  In the present invention, the server device preferably stores the error information in the error information storage means together with the reliability of the error determination. Here, the reliability of the error determination refers to the reliability with which the determination that the information of the map data is different from the actual measurement is reliable. For example, the measurement accuracy by the distance measuring means can be used as the reliability. As described above, when the distance measuring means is a laser scanner, the error determination based on the measurement in the fine weather has higher reliability than the error determination based on the measurement in the rain. When the distance measuring means is a stereo camera, the error determination based on the daytime measurement has higher reliability than the error determination based on the nighttime (other than daytime) measurement.

  In addition, it can be determined that the error determination reliability is high at a location where an error is determined by many vehicles. Therefore, the server device can determine that the reliability of the error determination for the error portion transmitted as error information from many vehicles is high.

  In addition, it is possible to determine that a part determined to be an error from a vehicle traveling in a different direction with respect to the same part has a high reliability of the error determination. Therefore, when transmitting error information to the server device, it is preferable to transmit the traveling direction of the host vehicle when the distance measurement of the error location is performed.

  Further, it can be determined that the shorter the distance between the error location and the host vehicle when the error location is measured, the higher the accuracy of the distance measurement, and thus the higher the reliability of the error determination. Therefore, when transmitting error information to the server device, it is preferable to transmit the distance between the error location and the own vehicle when the distance measurement of the error location is performed.

  The present invention can be understood as a map data verification system having at least a part of the above means. Moreover, this invention can also be grasped | ascertained as the map data verification method containing at least one part of the said process, or the program for implement | achieving this method. Each of the above means and processes can be combined with each other as much as possible to constitute the present invention.

  According to the present invention, a difference between map data and real world features can be detected in a short time.

FIG. 1 is a diagram for explaining the outline of the map data verification system according to the present embodiment. FIG. 2 is a diagram illustrating a functional configuration of the in-vehicle device according to the present embodiment. FIG. 3 is a diagram for explaining error detection of map data. FIG. 4 is a diagram showing a format of error information. FIG. 5 is a flowchart of an error location detection process for map data.

Exemplary embodiments of the present invention will be described in detail below with reference to the drawings. In the following description, an example in which a feature is a building will be described, but the feature may be other than a building.

(Overview)
FIG. 1 is a diagram for explaining the outline of a map data verification system according to this embodiment. A vehicle 100 traveling in the right direction in the figure travels while measuring a distance with a laser scanner in the directions indicated by reference numerals 101 and 102. The direction in which the distance is measured is diagonally forward of the vehicle, and the distance to the building existing on the side of the road can be measured. The vehicle 100 has map data for navigation. This map data includes building data in addition to road data. Therefore, if the position of the host vehicle is known, the distance to the building existing in the measurement directions 101 and 102 can be predicted from the map data. If the distance predicted from the map data is different from the actual measurement distance measured by the laser scanner, it can be seen that the map data is different from the actual. For example, consider a situation where buildings 301, 302, and 303 exist in the map data, but the building 302 is actually demolished. As shown in the figure, when the measurement direction 101 of the vehicle 100 coincides with the direction of the building 302, the actual measurement distance in the measurement direction 101 is the distance to the building 303, which is longer than the distance predicted from the map data. Therefore, it can be seen that the building 302 has disappeared. That is, it can be seen that the vehicle 100 includes the building 302 included in the map data. Conversely, even if a new building is created in a place where no building exists in the map data, the measurement distance by the laser scanner is different from the distance predicted from the map data, so the generation of the building can be grasped. . When the vehicle 100 detects a location where the map data does not reflect reality (error location) in this way, the vehicle 100 notifies the map management server 200 of information on the error location through road-to-vehicle communication. Error information is transmitted from a plurality of vehicles, and the map management server 200 accumulates the received error information. Then, based on the accumulated error information, it is determined that the map data is incorrect, it is determined that the field measurement should be performed for updating the map data, or the map data is updated based on the error information. can do.

(Functional configuration)
FIG. 2 is a diagram illustrating a functional configuration of the in-vehicle device and the map management server in the present embodiment. The laser scanner 1 measures the distance to the measurement object by irradiating the laser pulse and measuring the time until the reflected pulse returns. In the present embodiment, the laser scanner 1 is used to measure the distance between the vehicle and a building that is located on the side of the road. Two laser scanners 1 are mounted on the vehicle and are directed diagonally left frontward and diagonally forward right. Although the horizontal direction in the measurement direction is fixed, scanning is performed in a predetermined angular range in the vertical direction. For example, a range from 0 degrees (horizontal) to 70 degrees is scanned at a scanning frequency of 100 Hz. Of course, the range of scanning angles and the scanning frequency can be set as appropriate. As the range of the scanning angle is increased, the distance to the building existing at a higher position can be measured. In addition, the higher the scanning frequency, the higher the resolution can be measured, and the more detailed three-dimensional shape of the building can be acquired. Although it varies depending on the distance of the measurement object and the moving speed of the vehicle, if the distance is 10 m, the speed is 50 km, and the scanning frequency is 100 Hz, the measurement can be performed at intervals of about 10 to 20 cm.

  The installation conditions of the laser scanner 1 are not limited to the above. For example, the measurement direction of the laser scanner is not limited to diagonally forward, and may be laterally or diagonally backward. The number of laser scanners does not have to be two, and three or more laser scanners may be used, and by increasing the scanning angle range (for example, 180 degrees or more) with only one laser scanner, The distance to the buildings on both sides can be measured. Further, if the distance between the vehicle and the building is measured without measuring the three-dimensional shape of the building, a distance measuring sensor that does not perform scanning may be used. A distance measuring sensor other than the laser type may be used.

A stereo camera may be used as the distance measuring means. The stereo camera captures a pair of images with two cameras, and calculates the distance to the object to be imaged based on the parallax. Stereo cameras acquire images at a frame rate of about 30 frames per second. In the case of using a stereo camera, it is preferable to use two sets of stereo cameras facing left diagonally forward and right diagonally forward as in the case of the laser scanner, but the present invention is not limited to this. In addition, as an imaging device (CCD, CMOS, etc.) of the stereo camera, an imaging device that can detect not only the visible light region but also the near infrared region may be used so that it can be photographed at night.

  The own vehicle position detection unit 2 detects the position and traveling direction of the own vehicle using the GPS device 3, the gyro sensor 4, the acceleration sensor 5, and the like. The absolute coordinate of the host vehicle is acquired based on the GPS satellite signal received by the GPS device 3, and correction is performed based on the traveling direction obtained from the gyro sensor 4 and the moving distance obtained from the acceleration sensor 5. The position can be detected with high accuracy. In addition, position correction may be performed by matching with map data (map matching). In addition, the position detection of the own vehicle is not limited to the above-described configuration, and the vehicle's position can be detected by using a method such as acquisition of position information by wireless communication, detection of a magnetic marker embedded in a road, image recognition of a camera image, etc. The position may be detected.

  The three-dimensional map data 6 stores the three-dimensional shape of roads and surrounding structures. The error location detector 7 detects a location where the 3D map data 6 is different from the actual location. The distance from the current vehicle position to the building in the measurement direction of the laser scanner can be calculated from the position and traveling direction of the host vehicle obtained from the host vehicle position detection unit 2 and the three-dimensional map data 6. That is, the predicted value of measurement by the laser scanner when the map data is correct can be calculated. Therefore, the error location detection unit 7 compares the actual measurement value obtained by the laser scanner 1 with the predicted value calculated from the own vehicle position and the map data, and determines whether or not they match, thereby determining the map data. Determine whether is correct.

A process for determining the correctness of the map data based on the result of the distance measurement will be described in more detail with reference to FIG. FIG. 3 shows an example of a map included in the three-dimensional map data 6. For example, as shown in FIG. 3A, a case is considered in which buildings 51, 52, and 53 exist near intersections on the three-dimensional map data 6. The error point detection unit 7 of the vehicle A in the figure can determine (predict) that the measurement result of the laser scanner 1 facing left front is the distance 61 based on the position / traveling direction of the host vehicle and map data. . Similarly, it can be determined that the measurement result by the laser scanner 1 facing left front is the distance 62 for the vehicle B as well. When the map data matches the actual situation, the actual measurement result by the laser scanner is equal to the distances 61 and 62 predicted from the map data.
However, as shown in FIG. 3B, when the building 51 has disappeared, the distances 63 and 64 between the buildings 53 and 52 that should not be seen from the vehicles A and B are measured. The Thus, when the actual measurement result is larger than the measurement value predicted based on the three-dimensional map data 6, it can be determined that the building has disappeared.
Conversely, if it is recorded in the 3D map data 6 that the building 51 does not exist, the vehicles A and B are predicted to measure the distances 63 and 64 in FIG. As actual measurement results, distances 61 and 62 are obtained. Thus, when the actual measurement result is smaller than the measurement value predicted based on the three-dimensional map data 6, it can be determined that the building has been generated.
As described above, the error location detector 7 detects a location (error location) where the data recorded in the map data is different from the actual one.

Note that when there is an object that temporarily appears in the measurement direction of the laser scanner 1 such as another vehicle or person and is not included in the map data, the distance to this object is measured. Verification of map data based on this measurement distance leads to false detection. If the measurement result by the laser scanner is smaller than the distance between the vehicle and the side of the road (including the sidewalk), the measurement result is displayed on the map. It is preferable not to use for verification. That is, the shortest distance to the area where the building can exist in the measurement direction of the laser scanner 1 is calculated from the map data, and if the actual measurement result is shorter than the calculated shortest distance, the measurement is invalidated (error (It is not used for determination). In this way, it is possible to verify the map data without being affected by the temporarily existing object.

  When determining the error location, information other than the distance between the vehicle and the object may be used. For example, it may be used for determination whether or not the heights of buildings match. When scanning vertically with a laser scanner, the height of the building can be determined. When the height of the building recorded in the map data is different from the actual height, it can be determined that another building has been built at that position. When the laser scanner 1 can measure with high resolution, the map data is correct depending on whether or not the three-dimensional shape of the building obtained as a measurement result matches the three-dimensional shape of the building included in the map data. Can be judged.

  Here, it is assumed that the 3D map data 6 is used as the map data. However, when the map data is not verified by matching the 3D shape of the building, the 2D map data is used. It doesn't matter. In this case, if the two-dimensional map data includes the planar shape of the building or the distance from the roadside, the distance from the arbitrary point on the road to the building can be calculated. It is feasible. Further, if the height is included as the attribute data of the building, it is possible to execute the determination using the height.

  Information (error information) related to the location determined to be different from the actual by the error location detection unit 7 is transmitted to the map management server by the road-to-vehicle communication unit 9. The road-vehicle communication units 9 and 10 can use any communication medium such as wireless communication or optical communication (visible light communication or infrared light communication), and the communication method is not particularly limited. The error information transmitted from the vehicle to the map management server is stored in the error information storage unit 11 of the map management server. The error location information detected by the error location detection unit 7 does not need to be immediately transmitted to the map management server. First, the error information is accumulated in the vehicle. Alternatively, the information may be transmitted to the map management server at a time when the operation is stopped.

FIG. 4 shows attribute information included in error information transmitted to and accumulated in the map management server 200. The determination result 31 stores information indicating what kind of error has occurred, that is, whether the target object has disappeared, the object has been generated, or the target object has changed. Further, information representing the position of the error location is stored in the position coordinates 32 of the target object. The position of the error location may be stored as position coordinates, or when an identifier is assigned to the building in the map data, the identifier may be used. Also included is a version 33 of the map on which error detection has been performed. Whether an error occurs or not depends largely on the version of the map data that the vehicle has, so it is important which version of the map data is the error information. The error information further includes a measurement condition 34 when error detection is performed.
The measurement condition 34 may include, for example, the measurement means 35, the measurement date and time 36, the position 37 of the host vehicle at the time of measurement, the traveling direction 38 at the time of measurement, the weather 39 at the time of measurement, and the like. Since it is conceivable that the means for measuring the distance differs depending on the vehicle, what type of measuring device (for example, a laser scanner, an infrared distance measuring sensor, a stereo camera, etc.) is used, and the measuring performance is measured by the measuring means 35. To store. The measurement date and time 36 is used for grasping at which point it is determined that an error has occurred. The measurement date and time 36 relates to the reliability of error determination when the measurement accuracy of the measurement means varies depending on the time zone. The position 37 of the own vehicle at the time of measurement is used to determine from which point the measurement is made or the distance from the object. It can be determined that the measurement from a position closer to the object has better measurement accuracy, and thus the reliability of error determination is higher. The travel direction 38 at the time of measurement is used not only when traveling in a specific direction but also when traveling in different directions, if the same error can be detected, it can be determined that the reliability of error detection is high. Because. The reason for using the weather 39 at the time of measurement is that when the measurement accuracy changes depending on the weather, the reliability of error determination is affected. For example, since the measurement accuracy of a laser scanner is lowered when it rains, it is preferable to include at least whether or not it was raining as the weather 39.

  Thus, the certainty of error detection (reliability) can be determined from information such as measurement conditions included in the error information. Therefore, not only attribute information such as measurement conditions but also reliability may be given to error information transmitted from the vehicle. In addition, the map management server may assign the reliability based on information included in the error information. Regarding individual error detection, it can be determined that the higher the distance measurement accuracy, the higher the reliability of error detection. In this way, the map management server can grasp the reliability of error detection based on information such as the measurement date and time, the weather at the time of measurement, the distance to the measurement object, and the like.

(Processing flow)
Next, error detection processing of map data performed by the vehicle will be described with reference to FIG. First, it is determined whether or not the vehicle is traveling (S102). If the vehicle is stopped (S102-NO), no processing is performed and the process ends. When the vehicle is traveling (S102-YES), the position of the host vehicle is estimated by the host vehicle position detection unit 2 (S104). Further, distance measurement by the laser scanner 1 is performed (S106). The error location detection unit 7 determines the distance from the position of the host vehicle and surrounding information included in the three-dimensional map data 6 to the feature existing in the measurement direction by the laser scanner 1, that is, the measurement result by the laser scanner 1. The predicted value is calculated (S108). Then, it is determined whether the difference between the measurement result by the laser scanner and the predicted value from the map data is equal to or greater than a threshold value (S110). The threshold value is a value larger than the measurement error of the laser scanner 1.

  If the difference between the measurement result and the predicted value is larger than the threshold value (S110-YES), the map data is incorrect, so the error information is temporarily stored. Of the error information attributes, the determination result 31 can be determined based on the magnitude of the measurement result and the predicted value. When the measurement result is smaller than the predicted value, it can be determined that the building is generated, and the measurement result is higher than the predicted value. If it is too large, it can be judged that the building has disappeared. As the position coordinates 32 of the target object, when the building is extinguished, it is easy to use the identifier of the building. Of course, absolute coordinates may be used as the position coordinates 32. The date and time 36, the vehicle position 37, and the traveling direction 38 at the time of measurement are obtained from the built-in clock and the vehicle position detection unit 2. The weather 39 at the time of measurement may be acquired from the outside by wireless communication. However, if it is only necessary to record whether or not it is raining, it is easy to determine whether or not the wiper is operating.

  While the vehicle is traveling, the above error detection is repeated, and the detected error information is temporarily stored. When the vehicle stops (S114-YES), error information is transmitted to the map management server 200. In addition, the timing which transmits error information to the map management server 200 is not restricted when stopping driving | running | working, It may be arbitrary timings. For example, it may be transmitted at the same time that an error is detected, or may be communicated at regular intervals. Here, it is assumed that the vehicle and the map management server 200 are basically communicable at all times. However, when the location where the vehicle can communicate with the map management server 200 is limited, the vehicle is not connected to the map management server 200. The error information may be transmitted every time communication is possible.

(Map management server processing)
Next, the operation of the map management server 200 that has received error information from surrounding vehicles will be described. The map management server 200 accumulates error information transmitted from various vehicles, and determines the generation / disappearance of features for each location where an error report is made based on the accumulated error information. Since the error report includes attribute data as shown in FIG. 4, the following determination is made based on these.

  The first consideration is the map version included in the error information. That is, it is determined based on the map version 33 which version of the map data the error information reports. The map management server may use only error information related to the latest version of map data for determination. If only the latest version of error information is used, the error information related to the old version of map data can be ignored. In addition, even if the error information is related to the old version of the map data, if the feature data at the location where the error occurred is the same in the error report target version and the latest version, the error information is updated to the latest version of the map data. Can be treated as being for data. That is, the map management server has the latest version of map data and one or more versions of map data older than that, and when error information based on the old version of map data is received, If the feature data is the same between the old version and the latest version, this error information is handled as error information for the latest version of map data. In this way, error reports from vehicles using old versions of map data can be used effectively.

  The reliability of error information can be determined based on the number of error reports for the same location. That is, there is a high possibility that an error has actually occurred at a location where an error is detected by many vehicles. Since how many error reports are reliable depends on the number of vehicles passing through the place, the traffic volume at each place may be referred to. In addition, it is possible to determine that a place where the number of error reports is clearly smaller than the surrounding places is an error report due to erroneous detection.

  In addition, for each error determination, the reliability can be determined by the relationship between the measurement means and the measurement conditions. If the measuring means is a laser scanner, there may be a case where the measurement error during the rain becomes large. Therefore, it can be judged that the error judgment during the rain is low in reliability. Further, when the measuring means is a stereo camera or the like, the measurement accuracy is affected by illumination, so that it is possible to determine that the error determination at night or during the rain is low in reliability. Further, since the measurement accuracy is higher as the distance between the vehicle and the measurement object is shorter, the reliability of the error determination may be determined based on the position of the target object and the position at the time of measurement.

  When error information transmitted from many vehicles is accumulated, a plurality of error information for the same point is accumulated. Therefore, not only the error determination reliability is calculated by focusing on individual error information, but also the error determination reliability may be calculated based on a plurality of accumulated error information. Most simply, as described above, it can be determined that there is a high possibility that an error has actually occurred at a location where a lot of error information having the same content is accumulated. In addition, it is highly likely that an error has actually occurred at a location where a vehicle traveling in a different direction is determined to be in error. In addition, there is a high possibility that an error has actually occurred at a location where both vehicles having different measuring means have determined that there is an error. Thus, by accumulating a plurality of error information, the reliability of the reported error can be evaluated.

Since errors in map data are determined based on error information reported by many vehicles in this way, the effects of false detection by individual vehicles can be statistically eliminated, and reliable error information can be obtained. It can be automatically aggregated. In the map management server, if the location where it can be determined that an error has actually occurred is displayed on the display (display means) in such a way that it can be grasped visually, how much error is included in the map data by the administrator (map data) How old it is). That is, it is possible to grasp the gap between the map data and the real world, and to determine which region should be re-investigated at which timing. Of course, the map management server itself may display a message that prompts a resurvey when the number of error locations in the area (for example, the number per unit area) exceeds a threshold value.

(Operation and effect of this embodiment)
Since map data error information is stored in the map management server based on measurements from multiple vehicles, it is possible to statistically eliminate false detections and false detections that are unavoidable in measurement from moving vehicles and are reliable. Error information can be stored automatically. By using the error information accumulated in this manner, the frequency and timing of the re-survey can be reasonably determined locally. As a result, the number of re-surveys can be optimized, and a reduction in map production cost and a high freshness of map data can be rationally achieved.

DESCRIPTION OF SYMBOLS 1 Laser scanner 2 Own vehicle position detection part 7 Error location detection part 9, 10 Road-to-vehicle communication part 11 Error information storage part

Claims (7)

A map data verification system comprising a vehicle and a server device capable of communicating with each other,
The vehicle is
Position detecting means for detecting the position of the host vehicle;
Map data storing road and feature data,
A distance measuring means for measuring the distance to the feature on the side of the road;
An error detecting means for detecting an error location where the distance measured by the distance measuring means is different from a value predicted from the vehicle position and map data;
Transmitting means for transmitting the error location information of the map data to the server device as error information;
Have
The server device is
Receiving means for receiving error information transmitted from the vehicle;
Error information storage means for storing received error information;
A map data verification system comprising:   The map data verification system according to claim 1, wherein the distance measuring means is a laser scanner.   The map data verification system according to claim 1, wherein the distance measuring unit is a stereo camera. The map data verification system according to any one of claims 1 to 3, wherein the server device stores error information together with reliability of error determination in the error information storage unit.   5. The map data verification system according to claim 4, wherein the reliability is increased as an error location is transmitted from many vehicles. When the vehicle transmits the error information to the server device, the vehicle transmits the traveling direction of the host vehicle when measuring the distance of the error location,
The server device increases the reliability of the error location when it is determined that the map data and the actual measurement are different due to distance measurement while traveling in different directions for one error location. The map data verification system according to claim 4 or 5. When the vehicle transmits the error information to the server device, it transmits the distance between the error location and the host vehicle,
The map data verification system according to any one of claims 4 to 6, wherein the server device increases the reliability of the error location as the distance from the error location is shorter.

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