JP2011232271A - Navigation device, accuracy estimation method for on-vehicle sensor, and program - Google Patents

Abstract

PROBLEM TO BE SOLVED: To provide technology for estimating the reliability of an on-vehicle sensor by a simple means.SOLUTION: A navigation device 100 estimates the accuracy of an on-vehicle sensor. And the navigation device 100 includes: a storage means for storing map data in which the distance of a specific section is recorded; a measurement means for measuring the distance of the section using the on-vehicle sensor; and a sensor accuracy estimation means for estimating the accuracy of the on-vehicle sensor based on the difference between the distance recorded in the map data and the distance measured by the measurement means.

Description

  The present invention relates to a navigation device, an on-vehicle sensor accuracy estimation method, and a program.

  In recent years, automobiles (vehicles) have become highly functional and include various in-vehicle sensors (for example, Patent Document 1).

  The reliability of such in-vehicle sensors varies with changes in the environment (for example, weather). For example, when it rains, the reliability of cameras, laser radars, etc. may be low.

  In general, it is better not to use information obtained from such in-vehicle sensors with low reliability.

JP 2009-9209 A

  However, a technology for confirming the reliability of the in-vehicle sensor has not been established.

  An object of this invention is to provide the technique which estimates the reliability of a vehicle-mounted sensor by a simple method.

  The present invention for solving the above-mentioned problems is a navigation device for estimating the accuracy of an in-vehicle sensor, using storage means for storing map data in which the distance of a specific section is recorded, and the in-vehicle sensor. A sensor for estimating the accuracy of the in-vehicle sensor based on a deviation amount between the measuring means for measuring the distance of the section, the distance recorded in the map data, and the distance measured by the measuring means. Accuracy estimation means.

1 is a schematic configuration diagram of a navigation device to which an embodiment of the present invention is applied. It is a figure which shows the schematic data structure of map data. It is a functional block diagram of an arithmetic processing part. It is a flowchart which shows the outline | summary of the process for estimating the precision (reliability) of a vehicle-mounted sensor. It is a flowchart which shows a branch / merge presence determination process. It is a schematic diagram of the road in a junction. It is a flowchart which shows a sensor recognition result acquisition process. It is a flowchart which shows a sensor precision estimation process. It is an outline figure near the toll booth on the road.

  Hereinafter, an example of an embodiment of the present invention will be described with reference to the drawings.

  FIG. 1 is a schematic configuration diagram of a navigation device 100 to which an embodiment of the present invention is applied. As shown in the figure, the navigation device 100 includes an arithmetic processing unit 1, a display 2, a storage device 3, a voice input / output device 4 (microphone 41, speaker 42), and an input device 5 (touch panel 51, dial switch 52). The vehicle speed sensor 6, the gyro sensor 7, the GPS receiver 8, the FM multiplex broadcast receiver 9, the beacon receiver 10, and the camera 11 are provided. The navigation device 100 may be an in-vehicle navigation device mounted on a vehicle, or a mobile terminal such as a mobile phone or a PDA.

  The arithmetic processing unit 1 is a central unit that performs various processes. For example, the arithmetic processing unit 1 includes a CPU (Central Processing Unit) 21 that executes various processes such as numerical calculation and control of each device, and a RAM (Random) that stores map data, arithmetic data, and the like read from the storage device 3. (Access Memory) 22, ROM (Read Only Memory) 23 for storing programs and data, and I / F (interface) 24 for connecting various types of hardware to the arithmetic processing unit 1. The arithmetic processing unit 1 has a configuration in which devices are connected to each other via a bus 25. And each function part (101-104) mentioned later is implement | achieved when CPU21 runs the program read to memory, such as RAM22.

  For example, the arithmetic processing unit 1 calculates the current location based on information output from the vehicle speed sensor 6, the gyro sensor 7, and the GPS receiver 8. Further, map data necessary for display is read out from the storage device 3 based on the obtained current location information. Further, the read map data is developed in a graphic form, and a current location mark (or a moving body mark indicating the position of the moving body) is superimposed on the map data and displayed on the display 2. Further, using the map data stored in the storage device 3, an optimal route (hereinafter referred to as “recommended”) that connects the starting point instructed by the user or the current position calculated by the arithmetic processing unit 1 and the destination. Search for “route”. The user is guided using the speaker 42 and the display 2 of the voice input / output device 4.

  The display 2 includes a screen for displaying characters and images, and is a unit that displays graphics information generated by the arithmetic processing unit 1 and the like on the screen. The display 2 is configured by a liquid crystal display, an organic EL (Electro-Luminescence) display, or the like.

  The storage device 3 is composed of a storage medium such as a CD-ROM, DVD-ROM, HDD, or IC card. In this storage medium, for example, map data 310, audio data, moving image data, and the like are stored. The storage medium may be configured by a flash memory or the like that can hold necessary data even when power supply is stopped.

  FIG. 2 is a diagram illustrating a schematic data structure of the map data 310. As shown in the figure, the map data 310 includes link data 320 of each link constituting the road included in the mesh area for each mesh identification code (mesh ID) 311 that is a partitioned area on the map. Contains.

  For each link identification code (link ID) 321, link data 320 includes coordinate information 322 of two nodes (start node and end node) constituting the link, road type 323 indicating road type information including the link, link Link length information 324 indicating the length of the link, link travel time 325, link identification code (connection link ID) 326 connected to each of the two nodes, the position of the acceleration section at the junction of the road (for example, start point, end point) The specific section data 327 indicating the position (for example, the start point and the end point) of the section where the lane can be changed at the branch point of the road is included. Here, by distinguishing the start node and the end node for the two nodes constituting the link, the upward direction and the downward direction of the road can be managed as different links. Further, the specific section data 327 is not associated with a link (link ID 321) in which no specific section exists. The map data 310 stores drawing data for displaying roads and facilities in the map display.

  Returning to FIG. 1, the voice input / output device 4 includes a microphone 41 as a voice input device and a speaker 42 as a voice output device. The microphone 41 acquires voices and the like emitted from the driver and other passengers. The speaker 42 outputs the audio signal generated by the arithmetic processing unit 1. The microphone 41 and the speaker 42 are separately arranged at a predetermined part of the vehicle.

  The input device 5 is a unit that receives instructions from the user. The input device 5 includes a touch panel 51, a dial switch 52, and other hardware switches (not shown) such as scroll keys and scale change keys. In addition, the input device 5 includes a remote controller that can perform operation instructions to the navigation device 100 remotely. The remote controller includes a dial switch, a scroll key, a scale change key, and the like, and can send information on operation of each key or switch to the navigation device 100.

  The touch panel 51 is a transparent operation panel attached to the display surface of the display 2. The touch panel 51 specifies a touch position corresponding to the XY coordinates of the image displayed on the display 2, converts the touch position into coordinates, and outputs the coordinate. The touch panel 51 includes a pressure-sensitive or electrostatic input detection element.

  The dial switch 52 is configured to be rotatable clockwise and counterclockwise, generates a pulse signal for every rotation of a predetermined angle, and outputs the pulse signal to the arithmetic processing unit 1. The arithmetic processing unit 1 obtains the rotation angle of the dial switch 52 from the number of pulse signals.

  The vehicle speed sensor 6, the gyro sensor 7, and the GPS receiver 8 are used to calculate the current location (own vehicle position) of the moving body (navigation device 100). The vehicle speed sensor 6 is a sensor that outputs vehicle speed data used for calculating the vehicle speed. The gyro sensor 7 is composed of an optical fiber gyro, a vibration gyro, or the like, and detects an angular velocity due to the rotation of the moving body. The GPS receiver 8 receives a signal from a GPS satellite, and measures the distance between the mobile body and the GPS satellite and the rate of change of the distance with respect to three or more satellites. Measure.

  The FM multiplex broadcast receiver 9 receives an FM multiplex broadcast signal sent from an FM broadcast station. FM multiplex broadcasting includes VICS (Vehicle Infomation Communication System (registered trademark) information, general current traffic information, regulatory information, SA / PA (service area / parking area) information, FM information such as parking information, weather information, etc. As text information provided by radio stations.

  The beacon receiving device 10 receives rough current traffic information such as VICS information, regulation information, SA / PA information, parking information, weather information, emergency alerts, and the like. For example, it is a receiving device such as an optical beacon that communicates by light and a radio beacon that communicates by radio waves.

  The camera 11 images a road surface in a predetermined sensor area (for example, a range of an angle difference θ from side to side with respect to the traveling direction). Although not limited, the camera 11 is used, for example, for specifying a traveling lane or detecting an obstacle ahead of the vehicle.

  In addition, instead of the camera 11 or together with the camera 11, another vehicle-mounted sensor (a radar for detecting electromagnetic waves, a sonar for detecting sound waves, or the like) may be provided. Here, the radar and the sonar are used, for example, to detect an obstacle in front of the vehicle or to measure a distance between other vehicles.

  FIG. 3 is a functional block diagram of the arithmetic processing unit 1. As illustrated, the arithmetic processing unit 1 includes a main control unit 101, an input receiving unit 102, a display processing unit 103, and a sensor accuracy estimation unit 104.

The main control unit 101 is a central functional unit that performs various processes, and controls other functional units according to the processing content. For example, the main control unit 101 searches for a recommended route and performs route guidance using the searched recommended route. Further, when displaying a map on the display 2, the main control unit 101 extracts map data in an area requested to be displayed (for example, an area necessary for displaying the entire recommended route) from the storage device 3. Then, the display processing unit 103 is notified of an instruction to draw a road, other map structures, a starting point, a current location, a destination, a recommended route, and the like in the designated drawing method.

  The input receiving unit 102 receives a request from the user input to the input device 5, analyzes the request content, and notifies the main control unit 101 of data corresponding to the analysis result. For example, when the input receiving unit 102 receives a request for instructing power on or off, a request for triggering activation of an in-vehicle sensor (for example, the camera 11), or the like to the input device 5 of the navigation device 100, Information is received and analyzed and notified to the main control unit 101.

  The display processing unit 103 causes the display 2 to display a map, a recommended route, various messages notified to the user, and the like. Specifically, the display processing unit 103 generates graphics information to be displayed on the screen of the display 2 based on an instruction from the main control unit 101 and transmits it to the display 2. Further, the display processing unit 103 generates graphic information for displaying a vehicle mark indicating the position of the vehicle, various setting screens, and the like on the map displayed on the display 2 and transmits the graphic information to the display 2.

  The sensor accuracy estimation unit 104 estimates the accuracy (reliability) of the in-vehicle sensor (camera 11). Specifically, the sensor accuracy estimation unit 104 determines the presence / absence of a branch point or a merge point on the road (a “branch / merge determination process” described later). The sensor accuracy estimation unit 104 shoots the road surface of the sensor area using the camera 11 when there is a branching point or a merging point, and a road marking provided in a specific section of the branching point or the merging point ( For example, it recognizes a line drawn on the road surface ("sensor recognition result acquisition process" described later). Further, the sensor accuracy estimation unit 104 compares the line (specific section) recognized using the camera 11 with the specific section data 327 stored in advance in the map data 310, thereby comparing the accuracy of the in-vehicle sensor (camera 11) ( (Reliability) is estimated ("sensor accuracy estimation process" described later).

  In addition, in order to make an understanding of the structure of the navigation apparatus 100 easy, each above-mentioned component is classified according to the main processing content. The invention of the present application is not limited by the way of classifying the components or their names. The configuration of the navigation device 100 can be classified into more components depending on the processing content. Moreover, it can also classify | categorize so that one component may perform more processes.

  Moreover, each function part (101-104) may be constructed | assembled by hardware (ASIC etc.). In addition, the processing of each functional unit may be executed by one hardware, or may be executed by a plurality of hardware.

  Next, a characteristic operation of the navigation device 100 configured as described above will be described.

<Processing performed by the sensor accuracy estimation unit 104>
FIG. 4 is a flowchart illustrating an outline of processing performed by the sensor accuracy estimation unit 104 of the navigation device 100 to estimate the accuracy of the in-vehicle sensor (camera 11 in the present embodiment).

  As shown in the figure, the sensor accuracy estimation unit 104 executes the processes in the order of “branching / merging determination processing S1”, “sensor recognition result acquisition processing S2”, and “sensor accuracy estimation processing S3” described above. Estimate accuracy. Although not limited, the timing of starting the processing of S1 may be, for example, the timing at which route guidance along the recommended route is started.

  Below, each process (S1-S3) is demonstrated in detail with reference to FIG.

<Branching / Join determination processing>
FIG. 5 is a flowchart showing the “branching / merging determination process S1” performed by the sensor accuracy estimation unit 104. The main control unit 101 notifies the sensor accuracy estimation unit 104 of an instruction to start this processing (branching / merging determination processing S1) at the timing when the route guidance is started.

  When the sensor accuracy estimation unit 104 receives the notification from the main control unit 101 and starts this processing (branching / merging determination processing S1), the sensor accuracy estimation unit 104 prefetches the link data 320 (step S101). Specifically, the sensor accuracy estimation unit 104 specifies a link (link ID 321) constituting the recommended route from the map data 310 stored in the storage device 3. Then, the sensor accuracy estimation unit 104 includes links that are within a predetermined distance (for example, within 3 km) from the current location of the moving body (vehicle equipped with the navigation device 100) among the links of the specified recommended route (however, the vehicle has not traveled yet). Link).

  Next, the sensor accuracy estimation unit 104 determines whether or not a branch point or a junction point exists within a predetermined distance from the current location (step S102). Specifically, the sensor accuracy estimation unit 104 determines whether or not the specific section data 327 is associated with the link (link ID 321) read in step S101.

  Here, when the specific section data 327 is associated with the pre-read link, the sensor accuracy estimation unit 104 determines that a branch point or a merge point exists within a predetermined distance from the current location. On the other hand, when the specific section data 327 is not associated with the pre-read link, the sensor accuracy estimation unit 104 determines that there is no branching point or merging point within a predetermined distance from the current location.

  If the sensor accuracy estimation unit 104 determines that there is no branch point or junction point within a predetermined distance from the current location (step S102; No), the process returns to step S101. Therefore, the sensor accuracy estimation unit 104 repeatedly executes the processes of steps S101 and S102 while continuing to travel on a branch point or a link (road) where no junction point exists.

  On the other hand, if the sensor accuracy estimation unit 104 determines in step S102 that there is a branch point or a junction point within a predetermined distance from the current location (step S102; Yes), the process proceeds to step S103.

  When the process proceeds to step S103, the sensor accuracy estimation unit 104 stores the position of the branch point or the line (specific section) drawn to the merge point (step S103). Specifically, the sensor accuracy estimation unit 104 determines the start point and the end point of the specific section from the specific section data 327 associated with the link determined to have a branch point or a merge point in step S102. Data is extracted and stored in a memory (for example, RAM 22).

  FIG. 6 is a schematic diagram of the road at the above-described junction. Generally, when joining a main line from a branch line, a driver accelerates a moving body (vehicle) and joins the main line. Therefore, as shown in the figure, a specific section (acceleration section) for accelerating the moving body is provided at the junction. As shown in the drawing, a line for separating the main line and the branch line is drawn on the road surface in such a specific section. In the specific section data 327 of the link data 320 described above, coordinate data indicating the positions of the start point and end point of the specific section shown in the drawing is stored in advance. In step S103, the sensor accuracy estimation unit 104 reads the specific section data 327 corresponding to the junction where the moving body is approaching (stores in the memory).

  When the process of step S103 is completed, the sensor accuracy estimation unit 104 ends this process and notifies the main control unit 101 of the process.

<Sensor recognition result acquisition process>
FIG. 7 is a flowchart showing the “sensor recognition result acquisition process S <b> 2” performed by the sensor accuracy estimation unit 104. The main control unit 101 notifies the sensor accuracy estimation unit 104 of an instruction to start this processing (sensor recognition result acquisition processing S2) at the timing when the end of the branching / merging determination processing S1 is notified.

  Upon receiving the notification from the main control unit 101 and starting this processing (sensor recognition result acquisition processing S2), the sensor accuracy estimation unit 104 recognizes the line type of the line drawn on the road surface at the junction (step S201). ). Specifically, the sensor accuracy estimation unit 104 activates the camera 11 and images the road surface of the sensor area. Then, the sensor accuracy estimation unit 104 analyzes the image data obtained by photographing using the camera 11 (feature extraction or the like), and recognizes the line type of the line drawn on the road surface. In addition, the sensor area | region which is the imaging | photography range of the camera 11 is an area | region as shown, for example in FIG.

  The sensor accuracy estimation unit 104 determines whether or not the line type recognized in step S201 is an acquisition target line type (that is, a line drawn in a specific section) (step S202). Specifically, the sensor accuracy estimation unit 104 reads the feature information of the line drawn in the specific section from the storage device 3. Then, the sensor accuracy estimation unit 104 determines based on the read feature information and the feature similarity of the image data acquired in step S201. For example, when the similarity is equal to or higher than a predetermined threshold, the sensor accuracy estimation unit 104 determines that the line type recognized in step S201 is the acquisition target line type. On the other hand, if the similarity is less than the predetermined threshold, it is determined that the line type recognized in step S201 is not the acquisition target line type. Note that the feature information of the line drawn in the specific section is stored in the storage device 3 in advance.

  If the sensor accuracy estimation unit 104 determines that the line type recognized in step S201 is the acquisition target line type (step S202; Yes), the process proceeds to step S203.

  When the process proceeds to step S203, the sensor accuracy estimation unit 104 determines whether or not the line recognized in step S201 is the start point of the line drawn on the road surface of the specific section (step S203). Specifically, the sensor accuracy estimation unit 104 determines whether or not it is the first time that it is determined as the acquisition target line type in step S202. The determination method here is not limited. For example, a flag is set at the timing when the start point of the line drawn in the specific section is recognized (the process proceeds to step S204 for the first time) (“1”). The flag is lowered (set to “0”) at the timing when the end point of the line is determined (the process proceeds to step S211 described later), and the determination is made based on the flag.

  In step S203, if it is determined that the start point of the line drawn on the road surface of the specific section (step S203; Yes), the sensor accuracy estimation unit 104 proceeds to step S204. Then, the sensor accuracy estimation unit 104 stores the start point position of the line drawn in the specific section in the memory (for example, the RAM 22) (step S204). Specifically, the sensor accuracy estimation unit 104 calculates the current location using data obtained from the GPS receiver 8 or the like. Then, the sensor accuracy estimation unit 104 calculates the starting point position of the line drawn on the road surface of the specific section based on the calculated current location. The method for calculating the starting point position of the line is not limited. For example, the calculated current position itself may be calculated as the starting point position of the line, or a predetermined distance (camera 11) from the calculated current position. The estimated position between the line and the line) may be calculated as the starting point position of the line. Then, the sensor accuracy estimation unit 104 stores the calculated start position of the line in the memory.

  The sensor accuracy estimation unit 104 stores the start point position of the line, and then returns the process to step S201.

  On the other hand, if it is determined in step S203 that it is not the starting point of the line drawn on the road surface of the specific section (step S203; No), the sensor accuracy estimation unit 104 proceeds to step S205. Then, the sensor accuracy estimation unit 104 calculates the distance from the starting point position of the line (step S205). Specifically, the sensor accuracy estimation unit 104 calculates the current location using data obtained from the GPS receiver 8 or the like. Then, the sensor accuracy estimation unit 104 calculates the distance between the calculated current location and the start position stored in the memory in step S204.

  After calculating the distance from the starting point position of the line, the sensor accuracy estimation unit 104 returns the process to step S201.

  By repeating the processing from step S201 to step S205, the sensor accuracy estimation unit 104 can continuously photograph the line drawn on the road surface of the specific section from the start point to the end point, and calculates the distance from the start point to the end point. (Measurement).

  Incidentally, in step S202 described above, if the sensor accuracy estimation unit 104 determines that the line type recognized in step S201 is not the acquisition target line type (step S202; No), the process proceeds to step S206. To do.

  When the process proceeds to step S206, the sensor accuracy estimation unit 104 determines whether or not the acquisition target line type has been recognized at least once (step S206). What is necessary is just to discriminate | determine as a discrimination | determination method here, for example using the flag mentioned above.

  If it is determined that the acquisition target line type has not been recognized once (step S206; No), the sensor accuracy estimation unit 104 returns the process to step S201. Thereby, it is possible to try to recognize the line type again.

  On the other hand, if the sensor accuracy estimation unit 104 determines that the line type of the acquisition target has been recognized at least once (step S206; Yes), it reaches the end point of the line drawn on the road surface of the specific section. The process proceeds to step S207.

  When the process proceeds to step S207, the sensor accuracy estimation unit 104 determines whether the previously recognized line type is a line type that is not an acquisition target (hereinafter, referred to as “non-target line type”) (step S207). S207). Specifically, after recognizing the target line type at least once, the sensor accuracy estimation unit 104 sets a flag at the timing of recognizing the non-target line type for the first time (processing proceeds to step S207 for the first time) (“ 1 ”), the flag is lowered (set to“ 0 ”) at the timing when the end point of the line in the specific section is fixed (the process proceeds to step S211 described later), and the determination is made based on the flag. .

  If the sensor accuracy estimation unit 104 determines that the previously recognized line type is not a non-target line type (step S207; No), the process proceeds to step S209.

  Then, the sensor accuracy estimation unit 104 stores the first acquisition position of the non-target line type (that is, the position that is likely to be the end point position of the line in the specific section) in the memory (for example, the RAM 22) (step S209). . Specifically, the sensor accuracy estimation unit 104 calculates the current location using data obtained from the GPS receiver 8 or the like. Then, the sensor accuracy estimation unit 104 calculates the first acquisition position of the non-target line type based on the calculated current location. The method of calculating the first acquisition position of the non-target line type is not limited, but for example, the calculated current location itself may be calculated as the acquisition position of the non-target line type, or the calculated A position shifted from the current position by a predetermined distance (estimated distance between the camera 11 and the line) may be calculated as the acquisition position of the non-target line type. Then, the sensor accuracy estimation unit 104 stores the calculated position in the memory as a temporary end point position of the line drawn in the specific section.

  Thereafter, the sensor accuracy estimation unit 104 returns the process to step S201.

  On the other hand, if the sensor accuracy estimation unit 104 determines in step S207 that the previously recognized line type is also the non-target line type (step S207; Yes), the process proceeds to step S208, and the non-target line The distance at which the seed is continuously recognized is calculated (step S208). Specifically, the sensor accuracy estimation unit 104 calculates the distance from the temporary end position of the line to the current location. For this purpose, the sensor accuracy estimation unit 104 calculates the current location using data obtained from the GPS receiver 8 or the like. Then, the sensor accuracy estimation unit 104 calculates the distance between the calculated current location and the temporary end point position stored in the memory in step S209.

  When the sensor accuracy estimation unit 104 calculates the distance from the temporary end point position of the line, the process proceeds to step S210.

  Then, the sensor accuracy estimation unit 104 determines whether or not the distance calculated in step S208 is greater than or equal to a predetermined value A (see FIG. 6) (step S210).

  Here, if the distance calculated in step S208 is less than the predetermined value A (step S210; No), the sensor accuracy estimation unit 104 may have not yet passed the end point position of the line. Therefore, the process returns to step S201.

  On the other hand, when the distance calculated in step S109 is greater than or equal to the predetermined value A (step S210; Yes), the sensor accuracy estimation unit 104 determines that the moving body (vehicle) passes the end point position of the line. Then, the process proceeds to step S211.

  When the process proceeds to step S211, the sensor accuracy estimation unit 104 determines the end point position of the line drawn on the road surface of the specific section and the distance of the specific section (step S211). In other words, the sensor accuracy estimation unit 104 determines the temporary end point position stored in the memory in step S209 as the actual end point position when the process proceeds to step S211. Furthermore, the distance (distance from the start point) stored last in the memory in step S205 is determined as the distance of the specific section.

  When the process of step S211 is completed, the sensor accuracy estimation unit 104 ends this process and notifies the main control unit 101 of the process.

<Sensor accuracy estimation process>
FIG. 8 is a flowchart showing the “sensor accuracy estimation process S <b> 3” performed by the sensor accuracy estimation unit 104. The main control unit 101 notifies the sensor accuracy estimation unit 104 of an instruction to start this processing (sensor accuracy estimation processing S3) at the timing when the end of the sensor recognition result acquisition processing S2 is notified.

  When the sensor accuracy estimation unit 104 receives the notification from the main control unit 101 and starts this processing (sensor accuracy estimation processing S3), the distance between the specific section stored in the map data 310 and the in-vehicle sensor (camera 11). The distance of the specific section measured using is compared (step S301). Specifically, the sensor accuracy estimation unit 104 calculates the distance of the specific section from the coordinate data indicating the start point and end point of the specific section stored in the memory in step S103. Then, the calculated distance of the specific section is compared with the distance of the specific section determined in step S211.

  If the two distances compared in step S301 match (or the deviation between the two distances is within a predetermined range) (step S302; Yes), the sensor accuracy estimation unit 104 moves the process to step S303.

  When the process proceeds to step S303, the sensor accuracy estimation unit 104 starts and ends the specific section measured using the in-vehicle sensor (camera 11) and the start and end positions of the specific section stored in the map data 310. Are compared with each other (step S303). Specifically, the sensor accuracy estimation unit 104 compares the coordinate data indicating the start point of the specific section stored in the memory in step S103 with the position of the start point of the specific section determined in step S204. At the same time, the sensor accuracy estimation unit 104 compares the coordinate data indicating the end point of the specific section stored in the memory in step S103 with the position of the end point of the specific section determined in step S211.

  Here, the sensor accuracy estimation unit 104, when the positions of the start point and the end point compared in step S303 coincide (or the deviation amount of both positions is within a predetermined range) (step S303; Yes), The process directly proceeds to step S305, and it is determined that the accuracy (reliability) of the in-vehicle sensor (camera 11) is high (step S305).

  On the other hand, if both of the start point and end point positions compared in step S303 do not match (or the deviation amount between both positions exceeds a predetermined range) (step S303; No), the sensor accuracy estimation unit 104 performs processing. The process proceeds to step S304, and deviation correction is performed (step S304). The shift correction is to correct the shift between the position data obtained from the vehicle-mounted sensor (camera 11) and the actual position in order to obtain the current location used for route guidance more accurately (or simply the shift amount). Is stored in the memory).

  Then, after correcting the deviation, the sensor accuracy estimation unit 104 moves the process to step S305 and determines that the accuracy (reliability) of the in-vehicle sensor (camera 11) is high (step S305).

  After the determination in step S305, the sensor accuracy estimation unit 104 ends this process and notifies the main control unit 101.

  On the other hand, in step S302, when the two distances compared in step S301 do not match (or the deviation amount of both distances exceeds a predetermined range) (step S302; No), the sensor accuracy estimation unit 104 performs the process in step S306. Migrate to

  When the process proceeds to step S306, the sensor accuracy estimation unit 104 determines that the accuracy (reliability) of the in-vehicle sensor (camera 11) is low, terminates the process, and notifies the main control unit 101 of it. Then, the main control unit 101 receives this notification and ends the flow shown in FIG.

  When the sensor accuracy estimation unit 104 performs the above processing, the navigation device 100 of the present embodiment can estimate the accuracy (reliability) of the in-vehicle sensor. Then, by referring to the estimated result, it is possible to determine whether or not to use the data obtained from the in-vehicle sensor.

  Each processing unit of the above-described flow is divided according to main processing contents in order to facilitate understanding of the processing of the navigation device 100. The invention of the present application is not limited by the method of classification of the processing steps and the names thereof. The processing performed by the navigation device 100 can be divided into more processing steps. One processing step may execute more processes.

  Moreover, said embodiment intends to illustrate the summary of this invention, and does not limit this invention. Many alternatives, modifications, and variations will be apparent to those skilled in the art.

  Below, the modification of the said embodiment is given.

  For example, in the above flow, a process for estimating the accuracy of the in-vehicle sensor in a specific section (acceleration section) provided at a junction of roads is described. However, as described above, the present invention may estimate the accuracy of the in-vehicle sensor at a road branch point. Even in this case, the accuracy of the in-vehicle sensor can be estimated by the sensor accuracy estimation unit 104 executing the same process as in the above flow.

  Moreover, in the said embodiment, the precision of a vehicle-mounted sensor is estimated in the specific area provided in the junction of a road or a branch point. However, the present invention is not limited to this. For example, the accuracy of the in-vehicle sensor may be estimated in a specific section provided near a toll gate on a toll road.

  FIG. 9 is a schematic diagram of the vicinity of the toll gate on the toll road. As shown in the figure, a specific section similar to the above junction and branch point is provided near the toll gate. Specifically, a line is drawn on the road surface such that the point where the road starts to widen is the starting point of the specific section and the entrance of the toll gate is the end point of the specific section. The specific section data 327 stores coordinate data indicating the start point and the end point in advance. Thus, the navigation device 100 can estimate the accuracy of the in-vehicle sensor by executing the same processing as in the above flow.

  Moreover, the said embodiment demonstrated the case where it drive | works according to a recommended route. However, the present invention is not limited to this. That is, you may apply when not driving | running according to a recommended route. In this case, the sensor accuracy estimation unit 104 identifies a travel road (road planned to travel) from the current location and travel direction of the moving body (vehicle). For example, a link connected to the link at the current location and having the same road type is specified. And the sensor precision estimation part 104 can judge the presence or absence of the branch point on a driving | running | working road, and a junction point by referring the link data 320 similarly to the said embodiment. As a result, the sensor accuracy estimation unit 104 can photograph the road marking in the specific section using the in-vehicle sensor (camera 11), and estimate the accuracy of the in-vehicle sensor, as in the above embodiment.

  DESCRIPTION OF SYMBOLS 1 ... Operation processing part, 2 ... Display, 3 ... Memory | storage device, 4 ... Voice input / output device, 5 ... Input device, 6 ... Vehicle speed sensor, 7 ... Gyro sensor 8 ... GPS receiver, 9 ... FM multiplex broadcast receiver, 10 ... beacon receiver, 11 ... camera, 21 ... CPU, 22 ... RAM, 23 ... ROM 24 ... Interface (I / F), 41 ... Microphone, 42 ... Speaker, 51 ... Touch panel, 52 ... Dial switch, 100 ... Navigation device, 101 ... Main control , 102... Input reception unit, 103... Display processing unit, 104... Sensor accuracy estimation unit, 310... Map data, 311. ..Link ID 322 ... Start node / End node, 323 ... Road type, 324 ... Link length, 325 ... Link travel time, 326 ... Start connection link / End connection link, 327 ... Specific section data

Claims (9)

A navigation device that estimates the accuracy of an in-vehicle sensor,
Storage means for storing map data in which the distance of a specific section is recorded;
Measuring means for measuring the distance of the section using the in-vehicle sensor,
Sensor accuracy estimation means for estimating the accuracy of the in-vehicle sensor based on the amount of deviation between the distance recorded in the map data and the distance measured by the measurement means,
A navigation device characterized by that. The navigation device according to claim 1,
The map data includes
The start position and end position of the specific section are recorded,
The measuring means includes
Using the vehicle-mounted sensor, measure the distance from the target installed at the start point position to the target installed at the end point position,
The sensor accuracy estimation means includes
The distance between the start point position and the end point position recorded in the map data is calculated. presume,
A navigation device characterized by that. The navigation device according to claim 1 or 2,
The sensor accuracy estimation means includes
When the amount of deviation is within a predetermined value, the in-vehicle sensor is estimated to be highly accurate,
When the amount of slip exceeds a predetermined value, the in-vehicle sensor estimates low accuracy,
A navigation device characterized by that. The navigation device according to any one of claims 1 to 3,
The specific section is an acceleration section at a junction of roads.
A navigation device characterized by that. The navigation device according to any one of claims 1 to 3,
The specific section is a predetermined section in the vicinity of the toll gate on the toll road.
A navigation device characterized by that. The navigation device according to any one of claims 1 to 5,
The in-vehicle sensor is a sensor for detecting electromagnetic waves and sound waves.
A navigation device characterized by that. The navigation device according to claim 6,
The in-vehicle sensor includes a camera.
A navigation device characterized by that. A method for estimating the accuracy of an in-vehicle sensor in a navigation device that stores map data in which the distance of a specific section is recorded,
A measurement step of measuring the distance of the section using the in-vehicle sensor,
A sensor accuracy estimation step for estimating the accuracy of the in-vehicle sensor based on the amount of deviation between the distance recorded in the map data and the distance measured in the measurement step;
A navigation device characterized by that. A program for causing a computer to function as a navigation device that stores map data in which the distance of a specific section is recorded,
A measurement step of measuring the distance of the section using the in-vehicle sensor,
Causing the computer to execute a sensor accuracy estimation step of estimating the accuracy of the in-vehicle sensor based on a deviation amount between the distance recorded in the map data and the distance measured in the measurement step.
A program characterized by that.

Images