JP5772453B2 - Moving body position detection system, moving body position detection apparatus, moving body position detection method, and computer program - Google Patents

Description

  The present invention relates to a mobile body position detection system, a mobile body position detection device, a mobile body position detection method, and a computer program that detect the position of a mobile body.

  2. Description of the Related Art In recent years, a navigation device is often mounted on a vehicle that provides vehicle travel guidance so that a driver can easily arrive at a desired destination. Here, the navigation device detects the current position of the vehicle by a GPS receiver or the like, acquires map data corresponding to the current position through a recording medium such as a DVD-ROM or HDD or a network, and displays it on a liquid crystal monitor. It is a device that can do. Further, such a navigation device has a route search function for searching for an optimum route from the departure place to the destination when a desired destination is input. The guidance route set based on the search result is displayed on the display screen, and when approaching a branch point (hereinafter referred to as a guidance branch point) for guidance such as turning left or right, a voice or display screen is displayed. By performing the guidance used, the user is surely guided to a desired destination. In recent years, some cellular phones, PDAs (Personal Digital Assistants), personal computers, and the like have functions similar to those of the navigation device. Furthermore, it is also possible to perform the above guidance for pedestrians and two-wheeled vehicles as well as vehicles.

  Here, when performing guidance such as turning left or right at the guidance branch point, it is important to perform guidance at an appropriate timing. In order to perform the guidance at an appropriate timing, it is necessary to accurately detect the current position of the vehicle or the like. Here, as one of methods for accurately detecting the position of a vehicle or the like, for example, in Japanese Patent Application Laid-Open No. 2007-147521, a white line or road surface paint taken from a camera behind the vehicle is detected by image recognition. And a technique for detecting a detailed current position of a vehicle by comparing a road surface paint with a previously stored map information DB.

JP 2007-147521 A (page 14, FIG. 16)

  However, in the technique of the above-mentioned Patent Document 1, it is possible to accurately detect the current position of the vehicle at the time when the white line or the road surface paint is imaged by the camera. There was a problem that an error occurred between the position and the actual vehicle position.

  The present invention has been made in order to solve the above-described problems, and a moving body position detection system capable of accurately estimating an error range generated with respect to a detection position of the moving body due to movement of the moving body. An object of the present invention is to provide a moving body position detecting device, a moving body position detecting method, and a computer program.

In order to achieve the above object, the mobile body position detection system (1) according to claim 1 of the present application includes a first sensor (22) mounted on the mobile body to detect the movement distance of the mobile body (81). Obtained by the sensor result obtaining means (13) for obtaining the detection result and the detection result of the second sensor (24) mounted on the moving body in order to detect the azimuth change of the moving body, and the sensor result obtaining means. Based on the detection result of the first sensor and the detection result of the second sensor, the position detection means (13) for detecting the position of the moving body and the detection error of the first sensor First influence specifying means (13) for specifying how much error amount is generated in the traveling direction, the reverse direction, or both directions of the moving body with respect to the detection result, and detection by the second sensor If the error is Respect of the detection result, the traveling direction of the movable body, a second impact specifying means for specifying whether cause errors of how much error amount in either the reverse or both directions (13), the first effect specific And the position detected by the position detecting means based on the detection error of the first sensor and the detection error of the second sensor based on the identification results of the means and the second influence specifying means can occur on the traveling direction side. And a maximum error amount that can occur on the opposite side of the traveling direction, and a range including the maximum error amount in each specified direction is detected by the position detection means. Error range estimating means (13) for estimating the range.
The “moving body” includes a pedestrian and a two-wheeled vehicle in addition to the vehicle.

A mobile body position detection system (1) according to claim 2 is the mobile body position detection system according to claim 1, wherein the mobile body (81) is a predetermined distance from the first sensor (22). A sensor for detecting a moving distance of the moving body by adding the predetermined distance each time a pulse is output , based on a pulse output each time the sensor is moved. The error is a first error caused by specifying the predetermined distance based on a past learning result, while the specified predetermined distance deviates from a distance that the moving body moves in an interval in which pulses are actually output. If a second error caused by the moving body on a road (81) with a gradient moves, the pulse is not outputted at the timing to be outputted, before the interval actually pulse output Distance the moving object moves is characterized in that it comprises a third error caused by longer than the predetermined distance.

  Further, the mobile body position detection system (1) according to claim 3 is the mobile body position detection system according to claim 2, wherein the first error corresponds to a detection result of the position detection means (13). Thus, an error is generated in both directions opposite to the moving direction of the moving body (81), and the second error is an error in the direction opposite to the moving direction of the moving body with respect to the detection result of the position detecting means. And the third error causes an error in the traveling direction of the moving body with respect to the detection result of the position detecting means.

Further, the mobile body position detection system (1) according to claim 4 is the mobile body position detection system according to claim 1, wherein the second sensor (24) is a potential difference caused by a motion generated in an element inside. A sensor for detecting an azimuth change of the moving body based on the angular velocity and a sensitivity coefficient that defines a correspondence relationship between the potential difference and the azimuth change . While the detection error of the two sensors specifies the sensitivity coefficient based on the past learning result, the fourth error generated when the specified sensitivity coefficient deviates from the correspondence between the actual potential difference and the azimuth change ; It includes a fifth error caused by a temperature change around the second sensor and a sixth error caused by the moving body moving on a road with a gradient.

  Further, the mobile body position detection system (1) according to claim 5 is the mobile body position detection system according to claim 4, wherein the fourth error corresponds to a detection result of the position detection means (13). Thus, an error is generated in both directions opposite to the moving direction of the moving body (81), and the fifth error is detected in both directions opposite to the moving direction of the moving body with respect to the detection result of the position detecting means. The sixth error causes an error in the direction opposite to the traveling direction of the moving body with respect to the detection result of the position detecting means.

According to a sixth aspect of the present invention, there is provided a moving body position detecting device comprising: a detection result of the first sensor (22) mounted on the moving body and an orientation change of the moving body in order to detect a moving distance of the moving body (81); Sensor result acquisition means (13) for acquiring the detection result of the second sensor (24) mounted on the moving body to detect the detection result, and the detection result of the first sensor acquired by the sensor result acquisition means Based on the detection result of the second sensor, the position detection means (13) for detecting the position of the moving body, and the detection error of the first sensor is compared with the detection result of the position detection means. The first influence specifying means (13) for specifying how much error amount is caused in the traveling direction, the reverse direction, or both directions, and the detection error of the second sensor are detected by the position detecting means. For the result, the moving body Traveling direction, a second impact specifying means for specifying whether cause errors of how much error amount in either the reverse or both directions (13), a specific result of the first impact specifying means and the second impact specifying means The position detected by the position detection means based on the detection error of the first sensor and the detection error of the second sensor is based on the maximum error amount that can occur on the traveling direction side and on the opposite side of the traveling direction. An error range estimation unit (13) that identifies the maximum error amount that can be generated and estimates a range including the maximum error amount in each specified direction as the error range of the position of the moving body detected by the position detection unit. It is characterized by having.

According to a seventh aspect of the present invention, there is provided a moving body position detecting method in which the sensor result acquisition means includes a detection result of the first sensor (22) mounted on the moving body in order to detect a moving distance of the moving body (81). wherein the Luz step to acquire a detection result of the second sensor (24) mounted on the movable body to detect a heading change of said moving body, the position detecting means, acquired by the sensor result obtaining means based on a detection result of the the detection results of the first sensor the second sensor, and Luz step to detect the position of the movable body, the first impact specifying means, the detection error of the first sensor, the position detection the detection result of means, the traveling direction of the moving body, and Luz step to identify whether cause errors of how much error amount in either backward or bidirectional, the second impact specifying means, said first detection error of 2 sensors, the position detection hand Respect of the detection result, the traveling direction of the moving body, and Luz step to identify whether cause errors of how much error amount in either backward or bidirectional, the error range estimating means, said first impact A position detected by the position detection unit based on the detection error of the first sensor and the detection error of the second sensor may occur on the traveling direction side based on the identification results of the identification unit and the second influence identification unit. A maximum error amount and a maximum error amount that can occur on the opposite side of the traveling direction are specified, and a range including the maximum error amount in each specified direction is detected by the position detection unit. and having a Luz step to estimate the error range, the.

Furthermore, the computer program according to claim 8 is a computer program for detecting a moving distance of the moving body (81) and a detection result of the first sensor (22) mounted on the moving body and a change in orientation of the moving body. second sensor mounted on the moving body for detecting (24) of the detection result and a sensor result obtaining means for obtaining, said sensor result acquisition means of the first sensor obtained by the detection result and the second Based on the detection result of the sensor, the position detection means for detecting the position of the moving body, and the detection error of the first sensor is the direction in which the moving body travels in the opposite direction relative to the detection result of the position detection means. Alternatively, a first influence specifying unit that specifies how much error amount is caused in which direction in both directions, and a detection error of the second sensor is determined based on a detection result of the position detecting unit . Progress Direction, based on the identification result of the second impact specifying means, the first impact specifying means and the second impact specifying means for specifying whether cause errors of how much error amount in either backward or bidirectional, The position detected by the position detecting means based on the detection error of the first sensor and the detection error of the second sensor is the maximum amount of error that can occur on the traveling direction side and the maximum amount that can occur on the opposite side of the traveling direction. An error amount is specified , and functions as an error range estimation unit that estimates a range including the maximum error amount in each specified direction as an error range of the position of the moving object detected by the position detection unit .

According to the moving body position detection system having the above-described configuration, the detection error of the first sensor for detecting the moving distance of the moving body causes an error with respect to the detection position of the moving body. with specifying the amount and the detection error of the second sensor for detecting a heading change of the moving body, identifies the direction and amount that causes an error with respect to the detected position of the moving object, specified direction and amount Since the error range of the detection position of the moving object is estimated based on the above, even if a detection error occurs in the sensor, the influence of the detection error that has occurred on the detection position of the moving object should be specified appropriately Therefore, it is possible to accurately estimate the error range that occurs with respect to the detection position of the moving object. As a result, by considering the estimated error range, it becomes possible to execute guidance and control for the moving body at an appropriate timing.

  According to the moving body position detection system according to claim 2, the detection error of the first sensor for detecting the moving distance of the moving body is such that the correspondence between the number of output pulses and the moving distance of the moving body is the same. Since it includes a first error that occurs due to deviation from the predicted value, a second error that occurs when the moving body moves on a road with a gradient, and a third error that occurs when a pulse is not output at the timing at which it should be output. The error range can be estimated in consideration of the detection error of the first sensor that may cause an error in the detection position of the moving body.

  In addition, according to the moving body position detection system according to the third aspect, the direction in which the first to third errors generated in the first sensor cause the error relative to the detection position of the moving body is specified. Therefore, it is possible to more accurately estimate the error range generated with respect to the detection position of the moving body.

  According to the moving body position detection system of the fourth aspect, the detection error of the second sensor for detecting the azimuth change of the moving body is that the correspondence between the potential difference and the azimuth change of the moving body is based on the predicted value. Since the fourth error caused by the deviation, the fifth error caused by the temperature change around the second sensor, and the sixth error caused by the moving body moving on the road with the gradient, the detection position of the moving body is included. It is possible to estimate the error range in consideration of the detection error of the second sensor that may cause an error.

  In addition, according to the moving body position detection system according to claim 5, the direction in which the fourth to sixth errors generated in the second sensor cause an error with respect to the detection position of the moving body is specified. Therefore, it is possible to more accurately estimate the error range generated with respect to the detection position of the moving body.

Further, according to the moving body position detecting device of the sixth aspect, the direction and amount in which the detection error of the first sensor for detecting the moving distance of the moving body causes an error with respect to the detection position of the moving body. And the direction and amount of detection error of the second sensor for detecting the azimuth change of the moving body causes an error with respect to the detection position of the moving body, and based on the specified direction and amount . Therefore, even if a detection error occurs in the sensor, it is possible to appropriately identify the effect of the detection error that has occurred on the detection position of the moving object. Thus, it is possible to accurately estimate the error range that occurs with respect to the detection position of the moving object. As a result, by considering the estimated error range, it becomes possible to execute guidance and control for the moving body at an appropriate timing.

According to the moving body position detection method of claim 7, the direction and amount in which the detection error of the first sensor for detecting the moving distance of the moving body causes an error with respect to the detection position of the moving body. And the direction and amount of detection error of the second sensor for detecting the azimuth change of the moving body causes an error with respect to the detection position of the moving body, and based on the specified direction and amount . Therefore, even if a detection error occurs in the sensor, it is possible to appropriately identify the effect of the detection error that has occurred on the detection position of the moving object. Thus, it is possible to accurately estimate the error range that occurs with respect to the detection position of the moving object. As a result, by considering the estimated error range, it becomes possible to execute guidance and control for the moving body at an appropriate timing.

Furthermore, according to the computer program of the eighth aspect, the detection error of the first sensor for detecting the moving distance of the moving body specifies the direction and amount that cause the error with respect to the detection position of the moving body. In addition, the detection error of the second sensor for detecting the azimuth change of the moving body specifies the direction and amount that cause an error with respect to the detection position of the moving body, and the moving body is based on the specified direction and amount. Since the error range of the detection position of the sensor is estimated, even if a detection error occurs in the sensor, it is possible to appropriately identify the influence of the detection error that has occurred on the detection position of the moving object. It is possible to accurately estimate an error range generated with respect to the detection position of the body. As a result, by considering the estimated error range, it becomes possible to execute guidance and control for the moving body at an appropriate timing.

It is the block diagram which showed the navigation apparatus which concerns on this embodiment. It is the figure which showed an example of the traffic signal and stop line which are arrange | positioned at a branch point. It is the figure which showed an example of the guidance phrase condition table. It is a figure explaining the guidance start point prescribed | regulated by the guidance phrase condition table. It is a flowchart of a branch point guidance processing program according to the present embodiment. It is the figure which showed an example of the feature table. It is the figure shown about the arrival determination method to the guidance start point at the time of estimating an error range with respect to the detection position of a vehicle. It is a flowchart of the sub process program of the error range estimation process which concerns on this embodiment. It is a flowchart of the sub process program of the estimation process of the error range based on the road shape which concerns on this embodiment. It is a figure explaining the error of the detection position of the vehicle which arises when a vehicle drive | works a curved road. It is the figure which showed the maximum front deviation lane number in the case of driving | running | working the curved road bent to the left direction. It is the figure which showed the maximum rear shift | offset | difference lane number in case a vehicle drive | works the curved road bent in the left direction. It is the figure which showed the maximum number of front misalignment lanes when a vehicle drive | works the curved road bent rightward. It is a figure showing the maximum number of rear shift lanes when the vehicle travels on a curved road bent in the right direction. It is a figure explaining the error of the detection position of the vehicle which arises when a vehicle drive | works a curve road. It is a figure explaining the calculation method of the difference of the length of the curve (arc) which a curve road draws, and the length of the line segment (string) which connected the shape complement point with the straight line. It is a flowchart of the sub process program of the estimation process of the error range based on the sensor error which concerns on this embodiment. It is a figure explaining the detection error of the vehicle speed sensor produced when a vehicle drive | works the road with a gradient. It is a flowchart of the sub process program of the estimation process of the error range based on the lane change which concerns on this embodiment. It is a figure explaining the error of the detection position of the vehicle which arises when a vehicle changes lanes.

  Hereinafter, a mobile body position detection system and a mobile body position detection apparatus according to the present invention will be described in detail with reference to the drawings based on an embodiment in which the navigation apparatus is embodied. First, a schematic configuration of the navigation device 1 according to the present embodiment will be described with reference to FIG. FIG. 1 is a block diagram showing a navigation device 1 according to this embodiment.

  As shown in FIG. 1, the navigation device 1 according to the present embodiment includes a current position detection unit 11 that detects a current position of a vehicle on which the navigation device 1 is mounted, a data recording unit 12 that records various data, A navigation ECU 13 that performs various arithmetic processes based on the input information, an operation unit 14 that receives operations from the user, and a liquid crystal display 15 that displays a map around the vehicle and facility information related to the facility to the user. Communicating between a speaker 16 that outputs voice guidance regarding route guidance, a DVD drive 17 that reads a DVD as a storage medium, and an information center such as a probe center or a VICS (registered trademark: Vehicle Information and Communication System) center And a communication module 18 for performing. The navigation device 1 is connected to a back camera 19 for detecting a road marking described later.

Below, each component which comprises the navigation apparatus 1 is demonstrated in order.
The current position detection unit 11 includes a GPS 21, a vehicle speed sensor (first sensor) 22, a steering sensor 23, a gyro sensor (second sensor) 24, and the like. The current vehicle position, direction, vehicle travel speed, current time, and the like. Can be detected. Here, in particular, the vehicle speed sensor 22 is a sensor for detecting a moving distance and a vehicle speed of the vehicle, generates a pulse according to the rotation of the driving wheel of the vehicle, and outputs a pulse signal to the navigation ECU 13. And navigation ECU13 calculates the rotational speed and moving distance of a driving wheel by counting the generated pulse. Note that the navigation device 1 does not have to include all of the above five types of sensors, and the navigation device 1 may include only one or more of these types of sensors.

  Further, the data recording unit 12 reads an external storage device and a hard disk (not shown) as a recording medium, a map information DB 31 recorded on the hard disk, a guidance phrase condition table 32, a feature table 33, a predetermined program, and the like. A recording head (not shown) as a driver for writing predetermined data to the hard disk is also provided. The data recording unit 12 may be configured by a memory card, an optical disk such as a CD or a DVD, instead of the hard disk.

  Here, the map information DB 31 is, for example, link data 34 relating to roads (links), node data 35 relating to node points, branch point data 36 relating to each branch point, and features relating to road markings among features formed on the road. The storage means stores feature data 37, facility data relating to facilities, map display data for displaying a map, search data for searching for a route, search data for searching for a point, and the like.

  Here, as the link data 34, for example, a link ID for identifying the link, end node information for specifying a node located at the end of the link, road type of the road constituting the link, the number of lanes, opposite Presence / absence of lanes, link coordinates between nodes (for example, the shape of a curve on a curved road), position coordinates of shape complementing points, etc. are stored. As the node data 35, a node ID for identifying the node, position coordinates of the node, connection destination node information for specifying a connection destination node to which the node is connected via a link, and the like are stored. Further, as the branch point data 36, relevant node information for specifying a node forming the branch point (intersection), connection link information for specifying a link connected to the branch point (hereinafter referred to as a connection link), a branch point The traffic signal information 38 and the like related to traffic signals installed in the vicinity of is stored.

  In addition, the traffic signal information 38 is the direction in which the traffic light is installed (that is, the direction in which the traffic light is facing) of the traffic signal installed around each branch point (intersection) in the whole country. ), The number of lamps (3-lamp type, 2-lamp type, 1-lamp type, etc.), the position coordinates where the traffic light is installed (hereinafter referred to as installation coordinates), and the like are stored. Furthermore, when a plurality of traffic lights are installed at one branch point, the installation direction, installation coordinates, etc. are stored for each of the traffic lights. For example, as shown in FIG. 2, eight traffic lights 52 to 59 are installed at a branching point 51 where two one-lane roads intersect. Accordingly, as the traffic signal information 38 of the branch point 51, the installation direction, installation coordinates, and the like of the traffic signals 52 to 59 are stored.

The traffic signal information 38 is the traffic signal on the most exit side for each exit direction from the branch point (that is, the traffic signal that can be visually recognized at the end of the branch point when the vehicle passes through the branch point). It is good also as a structure which memorize | stores only the information regarding a side signal apparatus. For example, at the branch point 51 shown in FIG. 2, information on the traffic signal 53 that is the exit side traffic signal is stored for the exit direction from the bottom to the top of the diagram, and the exit side is displayed for the exit direction from the top to the bottom of the diagram. Stores information on the traffic light 55 that is a traffic light, stores information on the traffic light 57 that is a traffic light on the exit side with respect to the exit direction from the left to the right in the figure, and exits on the exit direction from the right to the left in the figure. Information on the traffic signal 59 that is a traffic signal is stored. That is, it is good also as a structure which memorize | stores only the installation direction and installation coordinate of the traffic lights 53, 55, 57, 59 among the 8 traffic lights 52-59. In addition, for each approach direction from a branch point, as a configuration for storing only information related to a traffic light that is closest to the entry side (that is, the departure side) (that is, a traffic light that can be visually recognized by the vehicle first, hereinafter referred to as an entry side traffic signal) Also good.
And navigation ECU13 is based on each data memorize | stored in map information DB31 as mentioned later, and the branch existing in the departure place side of a guidance route from this guidance branch point ahead of the advancing direction of a vehicle. A point (hereinafter referred to as a front branch point) is specified. Moreover, the traffic signal information 38 of the traffic lights around the guidance branch point and the front branch point and the feature data 37 of the stop line are acquired. Then, a feature table 33 (see FIG. 6), which will be described later, is created based on the information on the specified guidance branch point and near branch point, the acquired traffic signal information 38, and the feature data 37. The guidance branch point is a branch point to which guidance such as a right / left turn instruction is given when the navigation device 1 performs traveling guidance according to the guidance route set in the navigation device 1.

On the other hand, the feature data 37 stores information related to the road marking of the stop line, among the features formed on the road. Specifically, the identification ID, the coordinate data for specifying the position of the stop line on the map, and the branch point ID for identifying the branch point where the stop line is installed are stored. For example, as shown in FIG. 2, stop lines 60 to 63 are installed at four points at a branch point 51 where roads of two lanes on one side intersect. Therefore, as the feature data 37, various information regarding the stop lines 60 to 63 is stored.
When the navigation ECU 13 recognizes the stop line formed on the road surface from the captured image captured by the back camera 19, it detects the detailed current position of the vehicle based on the coordinate data associated with the recognized stop line (or It is possible to correct a position that has already been detected. And guidance and vehicle control are performed based on the detected current position.

  In addition, the guidance phrase condition table 32 is a table that stores the guidance branch point guidance, the contents of the spoken phrase, the conditions for starting the guidance utterance, and the like. Hereinafter, the guidance phrase condition table 32 will be described in more detail with specific examples. FIG. 3 shows an example of the guidance phrase condition table 32. FIG. 4 is a diagram for explaining a guidance start point defined in the guidance phrase condition table 32 shown in FIG. In FIG. 3, the number of traffic lights located between the current position of the vehicle and the guidance branch point is shown in the case where a traffic light is installed at the guidance branch point among the guidance performed at the guidance branch point. The guidance for specifying the guidance branch point will be described. In the following description of the embodiment, the guide branch point and the front branch point are both branch points where a traffic light is installed, and the branch on the one side before the guide branch point (the departure side along the guide route). The point is referred to as the first front branch point, the branch point on the further one side of the first front branch point (the departure side along the guide route) is referred to as the second front branch point, and further to the second front branch point. A branch point on the front side (the departure side along the guide route) will be referred to as a third front branch point.

As shown in Fig. 3, the guidance for specifying the guidance branch point using the number of traffic lights located between the current position of the vehicle and the guidance branch point is “the third signal is in the left (right) direction. "And the second signal is in the left (right) direction" and "the next signal is in the left (right) direction". Furthermore, a guidance start condition, which is a condition for starting a guidance utterance, is associated with each guidance phrase.
For example, in the case of guiding “the second signal is in the left (right) direction”, the user can count two traffic lights including the guidance branch point before entering the guidance branch point. In the meantime, the guidance utterance needs to be started. Therefore, the guidance phrase “the second signal is in the left (right) direction” is guided on the condition that the vehicle has passed the guidance start point set for the exit side traffic light at the second front branch point. To start. In addition, the guidance start point set for the exit side traffic light at the second front branch point is a point (for example, 5 meters before) a predetermined distance before the exit side traffic signal at the second front branch point or a vehicle occupant (especially a driver). There is a point where the exit side traffic light at the second front branch point is switched from a state where it is visible to a state where it is not visible. For example, in the example shown in FIG. 4, a point A that is 5 meters before the exit side traffic signal 73 of the second front branch point 72 that is two ahead of the guide branch point 71 is a guidance start point, and the vehicle passes through the point A. At this point, guidance at the guidance branch point is started. As a result, the user who has received the guidance can count the branch points where two traffic lights, the first front branch point 74 and the guide branch point 71, are installed before entering the guidance branch point 71. It becomes possible to clearly specify that the “second signal” in the sentence is the approach side traffic signal 75 installed at the guidance branch point 71.
The number of traffic lights in the guidance phrase is preferably the number of traffic lights in the branch point unit. That is, when a plurality of traffic signals are provided at the same branch point on a large road or the like, it is desirable that the plurality of traffic signals be counted as one traffic signal. In that case, the number of traffic lights in the guidance phrase corresponds to the number of branch points where traffic lights are installed (that is, traffic signal intersections). However, even when counting is performed in units of branch points, it is desirable to count the number of traffic lights (for example, push button type traffic lights) installed outside the branch point. The same applies to the following description.

  Similarly, other guidance phrases are stored in the guidance phrase condition table 32. In addition to the left (right) direction, there are a right (left) diagonal direction, a right (left) front direction, and the like as the guidance direction of the guidance branch point. Each numerical value (5 m or the like) for specifying the guidance start condition can be changed as appropriate.

  The feature table 33 is created by the navigation ECU 13 when the vehicle reaches within a predetermined distance (for example, within 1.47 km) with respect to the guidance branch point as will be described later. The feature table 33 is a table that specifies the relative positional relationship between the stop line at the guide branch point and the front branch point and the exit side traffic signal with reference to the guide branch point in the forward direction of the vehicle. Yes (see FIG. 6). Details of the feature table 33 will be described later.

  On the other hand, the navigation ECU (Electronic Control Unit) 13 is an electronic control unit that controls the entire navigation device 1. The CPU 41 as an arithmetic device and a control device, and a working memory when the CPU 41 performs various arithmetic processes. In addition to a RAM 42 for storing route data when a route is searched, a control program, a branch point guidance processing program (FIGS. 5, 8, 9, 17, and 17) described later. 19) and the like, and an internal storage device such as a flash memory 44 for storing a program read from the ROM 43. The navigation ECU 13 constitutes various means as processing algorithms. For example, the sensor result acquisition means acquires the detection result of the vehicle speed sensor 22 for detecting the moving distance of the vehicle (moving body) and the detection result of the gyro sensor 24 for detecting a change in the direction of the vehicle. The position detection means detects the position of the vehicle based on the detection result of the vehicle speed sensor 22 and the detection result of the gyro sensor 24 acquired by the sensor result acquisition means. The first influence specifying unit specifies whether the detection error of the vehicle speed sensor 22 causes an error in the vehicle traveling direction, the reverse direction, or both directions with respect to the detection result of the position detecting unit. The second influence specifying unit specifies whether the detection error of the gyro sensor 24 causes an error in the traveling direction, the reverse direction, or both directions of the vehicle with respect to the detection result of the position detecting unit. The error range estimation means estimates the error range of the vehicle position detected by the position detection means based on the identification results of the first influence identification means and the second influence identification means. The feature detection result acquisition means acquires a detection result obtained by detecting a feature existing around the vehicle. The feature information acquisition means acquires feature information in which the feature whose detection result has been acquired by the feature detection result acquisition means is associated with the position information of the feature.

  The operation unit 14 is operated when inputting a departure point as a travel start point and a destination as a travel end point, and includes a plurality of operation switches (not shown) such as various keys and buttons. Then, the navigation ECU 13 performs control to execute various corresponding operations based on switch signals output by pressing the switches. The operation unit 14 can also be configured by a touch panel provided on the front surface of the liquid crystal display 15. Moreover, it can also be comprised with a microphone and a speech recognition apparatus.

  The liquid crystal display 15 includes a map image including a road, traffic information, operation guidance, operation menu, key guidance, guidance route from the departure point to the destination, guidance information along the guidance route, news, weather forecast, Time, mail, TV program, etc. are displayed. In particular, in the present embodiment, when the guidance branch point approaches within a predetermined distance (for example, 300 m) ahead of the traveling direction of the vehicle, an enlarged view near the guidance branch point and the traveling direction at the guidance branch point of the vehicle are displayed.

  The speaker 16 outputs voice guidance for guiding traveling along the guidance route based on an instruction from the navigation ECU 13 and traffic information guidance. In particular, in the present embodiment, when the guidance branch point is ahead of the traveling direction of the vehicle, a voice guidance indicating that the predetermined guidance start timing based on the guidance content (for example, “the second signal is to the left”) When outputting, the voice guidance at the guidance branch point is output at the timing of passing a predetermined distance before the exit side traffic light at the second branch point before.

  The DVD drive 17 is a drive that can read data recorded on a recording medium such as a DVD or a CD. Based on the read data, music and video are reproduced, the map information DB 31 is updated, and the like.

  The communication module 18 is a communication device for receiving traffic information composed of information such as traffic jam information, regulation information, and traffic accident information transmitted from a traffic information center, for example, a VICS center or a probe center. For example, a mobile phone or DCM is applicable.

  The back camera 19 uses a solid-state image sensor such as a CCD, for example, and is installed near the upper center of the license plate mounted on the rear side of the vehicle, and installed with the line-of-sight direction downward from the horizontal by a predetermined angle. Is done. Then, an image is taken of the rear of the vehicle that is opposite to the traveling direction of the vehicle during traveling. And the kind and position of the feature in the circumference | surroundings of a vehicle are detected by performing the image recognition process of a captured image. Based on the detected feature (in this embodiment, in particular, a road marking on the stop line), the detailed position of the vehicle is calculated.

  Next, a branch point guidance processing program executed by the navigation ECU 13 in the navigation device 1 having the above configuration will be described with reference to FIG. FIG. 5 is a flowchart of the branch point guidance processing program according to this embodiment. Here, the branch point guidance processing program is a program that is repeatedly executed at a predetermined interval (for example, every detection cycle of the current position of the vehicle) after the vehicle ACC is turned on, and guides the guidance branch point on the guidance route. . The programs shown in the flowcharts of FIGS. 5, 8, 9, 17, and 19 below are stored in the RAM 42 and ROM 43 provided in the navigation device 1 and are executed by the CPU 41.

  First, in step (hereinafter abbreviated as S) 1 in the branch point guidance processing program, the CPU 41 determines whether route guidance based on the guidance route set in the navigation device 1 is being performed. Here, the guidance route is a recommended route from the departure point (for example, the current position of the host vehicle) to the destination selected by the user, and is set based on the result of the route search process. The route search process is performed by a known Dijkstra method or the like using link data 34, node data 35, traffic information acquired from the VICS center, and the like stored in the map information DB 31.

  And when it determines with the route guidance based on the guidance route set in the navigation apparatus 1 being performed (S1: YES), it transfers to S2. On the other hand, when it is determined that route guidance based on the guidance route set in the navigation device 1 is not performed (S1: NO), the branch point guidance processing program is terminated.

  In S <b> 2, the CPU 41 acquires the current position of the vehicle based on the detection result of the current position detection unit 11 and dead reckoning navigation. A map matching process for specifying the current position of the vehicle on the map data is also performed. Further, in a state where the guide branch point is located within a predetermined distance ahead of the traveling direction of the vehicle, the current position of the vehicle is specified in detail using the high-precision location technology. Here, the high-precision location technology is a feature that detects features such as white lines and road surface paint captured from the back camera 19 behind the vehicle by image recognition, and further stores features such as white lines and road surface paint in advance. This is a technology that makes it possible to detect a traveling lane and a highly accurate vehicle position by collating with the data 37. In particular, in this embodiment, a stop line provided at a branch point as a feature is set as a detection target.

Hereinafter, a vehicle position detection method using the high-precision location technology will be briefly described.
First, the CPU 41 captures an image with the back camera 19 when the vehicle is located within a predetermined distance (for example, within 40 m) from the installation position of the road marking (particularly a stop line in the present embodiment) recorded in the feature data 37. The corresponding stop line is recognized (detected) from the captured image.
Next, position information associated with the stop line recognized from the feature data 37 is read out.
Then, a detailed position of the vehicle is detected based on the distance from the vehicle to the stop line when the stop line is recognized and the read position information.
The position of the vehicle may be specified by the distance to the guidance branch point, or may be specified by position coordinates.

In addition, the current position of the vehicle is detected at a predetermined interval by dead reckoning navigation from when the vehicle position is detected by recognizing the stop line until the next stop line is recognized. Specifically, the CPU 41 specifies the moving direction and the moving distance of the vehicle with respect to the reference position based on the detection results of the vehicle speed sensor 22 and the gyro sensor 24 with the position of the vehicle at the time of the previous stop line recognition as the reference position. . Then, based on the specified moving direction and moving distance, the current position of the vehicle is detected based on the relative position with respect to the reference position. In dead reckoning, the current position of the vehicle is detected on the assumption that the vehicle moves on the link. Also, road gradients and sensor errors are not considered. Therefore, as described later, an error occurs between the position of the vehicle detected by dead reckoning and the actual position of the vehicle. Further, the error basically increases as the travel distance of the vehicle increases.
Further, the current position of the vehicle detected in S2 is stored in the RAM 42 or the like and updated whenever a new current position of the vehicle is detected.

  Next, in S <b> 3, the CPU 41 obtains a guidance route (including a guidance branch point in the guidance route) set in the navigation device 1.

  Subsequently, in S4, the CPU 41 determines a guidance branch point within a predetermined distance (for example, within 1.47 km) ahead of the traveling direction of the vehicle based on the current position of the vehicle acquired in S2 and the guidance route acquired in S3. It is determined whether or not there is. Note that the guidance branch point is a branch point to which guidance such as a right / left turn instruction is given when the navigation device 1 guides traveling according to the guidance route set in the navigation device 1 as described above.

  If it is determined that there is a guidance branch point within a predetermined distance ahead of the traveling direction of the vehicle (S4: YES), the process proceeds to S5. On the other hand, when it is determined that there is no guidance branch point within a predetermined distance ahead of the traveling direction of the vehicle (S4: NO), the branch point guidance processing program is terminated.

  In S5, the CPU 41 determines whether or not guidance for a guidance branch point in front of the vehicle traveling direction has already been performed. In S5, it is determined whether or not voice guidance for instructing a right or left turn or the like at the guidance branch point among the guidance for the guidance branch point has been performed.

  And when it determines with guidance with respect to the guidance branch point ahead of the advancing direction of a vehicle having already been performed (S5: YES), the said branch point guidance process program is complete | finished. On the other hand, when it is determined that the guidance for the guidance branch point ahead of the traveling direction of the vehicle is not performed (S5: NO), the process proceeds to S6.

  In S6, the CPU 41 determines whether or not the feature table 33 for the guidance branch point located in front of the traveling direction of the vehicle has been created. Here, the feature table 33 is created in S7, which will be described later, and is based on the guide branch point ahead of the traveling direction of the vehicle, and the relative of the stop line and the exit side signal at the guide branch point and the front branch point. It is a table that specifies a specific positional relationship.

  And when it determines with the feature table 33 having been prepared with respect to the guidance branch point located ahead of the advancing direction of a vehicle (S6: YES), it transfers to S9. On the other hand, when it determines with the feature table 33 with respect to the guidance branch point located ahead of the advancing direction of a vehicle not being created (S6: NO), it transfers to S7.

  In S <b> 7, the CPU 41 acquires position information of each branch point from the map information DB 31 for the guide branch point located in front of the traveling direction of the vehicle and the front branch point located in front of the guide branch point. Further, information (position coordinates, number of lamps, etc.) related to the exit side traffic lights installed at the guidance branch point and the front branch point is acquired from the traffic signal information 38. Further, information (position coordinates, distance to the branch point, etc.) regarding the stop line (including the virtual stop line in addition to the actual stop line) arranged at the guidance branch point and the front branch point is acquired from the feature data 37. And the feature table 33 is created based on each acquired information. The front branch points to be created in the feature table 33 may be all front branch points from the current position of the vehicle to the guide branch point, or only a predetermined front branch point (for example, the first front branch point). To the third front branch point).

Here, FIG. 6 is a diagram showing an example of the feature table 33 created in S7. In the feature table 33 shown in FIG. 6, the guide branch point 82, the first front branch point 83, the second front branch point 84, and the third front side are based on the guide branch point 82 ahead of the traveling direction of the vehicle 81. The relative positional relationship between the exit side traffic lights 86 to 89 and the stop lines 90 to 93 at the branch point 85 is recorded.
For example, it is recorded that the exit side traffic signal 86 at the guidance branch point 82 is a three-lamp type and is installed at a position 10 m away from the guidance branch point 82 in the direction opposite to the departure side. In addition, the stop line 92 at the second front branch point 84 is a virtual stop line of “ID: 345”, and it is recorded that it is installed at a position 220 m away from the guide branch point 82 on the departure side. The The relative distance of the exit side traffic lights 86 to 89 from the guidance branch point 82 is calculated based on, for example, the position coordinates of the guidance branch point 82 and the position coordinates of the exit side traffic lights 86 to 89 acquired from the traffic signal information 38. Is done. The relative distances of the stop lines 90 to 93 from the guide branch points 82 are based on, for example, the position coordinates of the branch points 82 to 85 and the position data of the stop lines 90 to 93 acquired from the feature data 37. Calculated.

  Next, in S8, based on the feature table 33 created in S7, the CPU 41 determines the contents of the guidance phrase when performing guidance for the guidance branch point and the guidance start point for starting guidance for the guidance branch point. Set. For example, if the guidance route is a route that turns left at a guidance branch point ahead of the direction of travel of the vehicle, the guidance phrases are “3rd traffic light left”, “2nd traffic light left And “Next signal is to the left” are set. Further, for guidance that “the third signal is in the left direction”, a point a predetermined distance before the exit side traffic light at the third branch point before (for example, 5 m before) is set as the guidance start point. Similarly, for guidance that “the second signal is in the left direction”, a point a predetermined distance (for example, 5 m before) of the exit side traffic light of the second front branch point is set as the guidance start point. Similarly, for guidance that “the next signal is in the left direction”, a point a predetermined distance (for example, 5 m before) of the exit side traffic light at the first branch point is set as the guidance start point. In S8, the CPU 41 stores the set guidance phrase and guidance start point in the RAM 42 or the like. Thereafter, the process proceeds to S9.

  In S9, the CPU 41 executes an error range estimation process (FIG. 8) described later. The error range estimation process is a process for estimating the error range with respect to the detected position of the vehicle acquired in S2 as described later. The error range is specified by the direction in which an error occurs with respect to the detection position (the traveling direction of the vehicle, the opposite direction of the traveling direction, both directions) and the maximum possible error amount (for example, 10 m).

Next, in S10, the CPU 41 determines whether or not the vehicle has reached the guidance start point based on the detected position of the vehicle acquired in S2 and the error range estimated in S9.
Specifically, no matter where the actual vehicle is located within the error range, when the vehicle has reached the guidance start point, that is, in the direction of travel of the vehicle within the error range. When a point in the reverse direction matches the guidance start point, it is determined that the vehicle has reached the guidance start point. For example, as shown in FIG. 7, when the error range estimated in S9 is 5 m in the traveling direction of the vehicle and 10 m in the reverse direction, the error range of 10 m behind the current position 94 of the vehicle acquired in S2 It is determined that the vehicle has arrived at the guidance start point A when the point X coincides with the guidance start point A set a predetermined distance before the exit side traffic light 88 of the front branch point (for example, the second front branch point 84). Is done. As a result, even if an error occurs in the detection position of the vehicle, guidance that contradicts the sight of the occupant (for example, in a state where three traffic lights are visible up to the guidance branch point, the second signal is left (right) It is possible to prevent the guidance of “direction”.

  And when it determines with the vehicle having reached the guidance start point (S10: YES), it transfers to S11. On the other hand, when it is determined that the vehicle has not reached the guidance start point (S10: NO), the branch point guidance processing program is terminated.

In S <b> 11, the CPU 41 performs guidance related to the guidance branch point by the guidance phrase corresponding to the reached guidance start point. Specifically, guidance for identifying the guidance branch point and guidance for identifying the exit direction of the vehicle at the guidance branch point (that is, guidance for identifying the exit road from which the vehicle exits the guidance branch point) are performed. For example, in this embodiment, “3rd signal is left (right) direction”, “2nd signal is left (right) direction”, “next signal is left (right) direction” There is a guide start point corresponding to each guide phrase. For example, when the vehicle reaches the guidance start point set a predetermined distance before the exit side traffic light at the second branch point, the phrase “The second signal is in the left (right) direction” with the phrase 16 to output. Further, when the guidance branch point approaches within a predetermined distance (for example, 300 m) of the vehicle, an enlarged view near the guidance branch point and the traveling direction at the guidance branch point of the vehicle are displayed on the liquid crystal display 15.
As a result, it becomes possible for the user to accurately specify the guidance branch point and the road from which the vehicle exits from the guidance branch point.

  Next, a sub-process of the error range estimation process executed in S9 will be described with reference to FIG. FIG. 8 is a flowchart of a sub-processing program for error range estimation processing.

  First, in S21, the CPU 41 estimates an error range that occurs based on the road shape of the road on which the vehicle travels. The error range is specified by the direction in which an error occurs with respect to the detection position (the traveling direction of the vehicle, the direction opposite to the traveling direction, or both directions) and the maximum error amount (for example, 10 m). The same applies to S22 and S23 described later. Details will be described later (see FIG. 9).

  Next, in S22, the CPU 41 estimates an error range that is generated based on a detection error of a sensor mounted on the vehicle. Details will be described later (see FIG. 17).

  Subsequently, in S23, the CPU 41 estimates an error range generated based on a lane change performed by the vehicle. Details will be described later (see FIG. 19).

  Thereafter, in S24, the CPU 41 estimates an error range in consideration of all factors causing an error, based on the error ranges estimated in S21 to S23. Specifically, the maximum error amount caused by each factor is added for each direction in which an error occurs with respect to the detection position (the vehicle traveling direction or the reverse direction of the traveling direction), and all the factors are considered in the added value. The maximum amount of error that can occur.

  For example, the error range generated based on the road shape of the road on which the vehicle travels estimated in S21 is P1 [m] in the traveling direction of the vehicle and P2 [m] in the reverse direction of the traveling direction, and is estimated in S22. The error range generated based on the detection error of the sensor mounted on the vehicle is Q1 [m] in the traveling direction of the vehicle and Q2 [m] in the reverse direction of the traveling direction, and the lane that the vehicle estimated in S23 performs When the error range generated based on the change is R1 [m] in the traveling direction of the vehicle and R2 [m] in the reverse direction of the traveling direction, the error range considering all the factors estimated in S24 is (P1 + Q1 + R1) [m] in the traveling direction of the vehicle and (P2 + Q2 + R2) [m] in the opposite direction of the traveling direction. Thereafter, the process proceeds to S10, and determination of arrival of the vehicle at the guidance start point is performed based on the error range with respect to the detected position of the vehicle estimated in S24.

  Next, a sub-process of the error range estimation process based on the road shape executed in S21 will be described with reference to FIG. FIG. 9 is a flowchart of a sub-processing program of the error range estimation process based on the road shape.

  First, in S31, the CPU 41 acquires the road shape of the road on which the vehicle is traveling from the map information DB 31.

  Next, based on the road shape of the road acquired in S31, it is determined whether or not the vehicle is traveling on a curved road bent at a predetermined angle. Here, when the vehicle travels on a curved road, the position between the vehicle position detected by dead reckoning and the actual vehicle position is caused by the deviation of the link setting position on the curved road and the travel route of the vehicle. An error occurs.

  Hereinafter, the reason why an error occurs due to traveling on a curved road will be briefly described with reference to FIG. As shown in FIG. 10, if the vehicle travels on a curved road bent at a predetermined angle θ, the vehicle does not necessarily travel on the link L1 set on the curved road. Accordingly, the length of the link L1 set on the curved road is not necessarily the same as the length of the travel route L2 on which the vehicle actually travels. For example, in the example shown in FIG. 10, the link L1 is longer than the travel route L2. The distance D is increased. Here, as described above, in the dead reckoning navigation, the current position of the vehicle is detected on the assumption that the vehicle moves on the link. Therefore, the actual vehicle position is only the distance D than the vehicle position detected by the dead reckoning navigation. It will be located ahead (that is, an error will occur in the detection position of the vehicle). Further, since it is defined that the link L1 set on the curved road only needs to be set at any position on the curved road, as will be described later, the direction in which the error occurs or the error is generated depending on the position of the link L1. The amount varies.

  If it is determined that the vehicle is traveling on a curved road bent at a predetermined angle (S32: YES), the process proceeds to S33. On the other hand, when it is determined that the vehicle is not traveling on a curved road (S32: NO), the process proceeds to S36.

  In S <b> 33, the CPU 41 acquires information related to the curved road on which the vehicle travels from the map information DB 31. Specifically, the bending direction, the bending angle, the number of lanes, the lane width, the presence / absence of an oncoming lane, and the like are acquired. The lane width may be a fixed value (for example, 3.5 m). Further, the bending direction and the bending angle may be calculated from the node coordinates of each node included in the bending road.

  Next, in S34, the CPU 41 calculates the maximum front shift lane number T1 and the maximum rear shift lane number T2 based on the bending direction, the number of lanes, and the presence or absence of the opposite lane acquired in S33. Here, the maximum front misalignment lane number T1 is a case where the link set on the curved road is shorter than the travel route on which the vehicle travels, and is the maximum in the road width direction that can occur between the link and the travel route. This is the value specified by the number of lanes. Further, the maximum rear shift lane number T2 is a case where the link set on the curved road is longer than the travel route on which the vehicle travels, and is the maximum in the road width direction that can occur between the link and the travel route. This is the value specified by the number of lanes.

Hereinafter, a method of calculating the maximum front shift lane number T1 and the maximum rear shift lane number T2 will be described with reference to FIGS. Here, the maximum front deviation lane number T1 and the maximum rear deviation lane number T2 are calculated based on the bending direction of the curved road, the number of lanes, and the presence or absence of the opposite lane.
For example, FIG. 11 is a diagram illustrating a method of calculating the maximum front misalignment lane number T1 when the bending direction is the left direction with respect to the traveling direction of the vehicle. As shown in FIG. 11, when the bending direction is the left direction with respect to the traveling direction of the vehicle, the link L1 set on the bending road becomes shorter than the traveling route L2 on which the vehicle travels, and the link L1 When the maximum amount of deviation occurs in the road width direction with respect to the travel route L2, the link L1 is set along the left end of the curved road, and the vehicle travels in the rightmost lane. Therefore, the maximum front misalignment lane number T1 is a value obtained by subtracting 0.5 from the number of one-side lanes (2 in FIG. 11) regardless of the presence or absence of the oncoming lane.

  FIG. 12 is a diagram illustrating a method of calculating the maximum rearward deviation lane number T2 when the bending direction is the left direction with respect to the traveling direction of the vehicle. As shown in FIG. 12, when the bending direction is the left direction with respect to the traveling direction of the vehicle, the link L1 set on the bending road becomes longer than the travel route L2 along which the vehicle travels, and the link L1 When the maximum amount of deviation occurs in the road width direction with respect to the travel route L2, the link L1 is set along the right end of the curved road, and the vehicle travels in the leftmost lane. Therefore, the maximum rear shift lane number T2 is a value obtained by subtracting 0.5 from the number of both-side lanes (4 in FIG. 12) when there is an oncoming lane, and from the number of one side lanes when there is no oncoming lane. The value obtained by subtracting

  FIG. 13 is a diagram showing a method of calculating the maximum front misalignment lane number T1 when the bending direction is the right direction with respect to the traveling direction of the vehicle. As shown in FIG. 13, when the bending direction is rightward with respect to the traveling direction of the vehicle, the link L1 set on the bending road is shorter than the travel route L2 on which the vehicle travels, and the link L1 When the maximum amount of deviation occurs in the road width direction with respect to the travel route L2, the link L1 is set along the right end of the curved road, and the vehicle travels in the leftmost lane. Accordingly, the maximum front misalignment lane number T1 is a value obtained by subtracting 0.5 from the number of both-side lanes (4 in FIG. 13) when there is an oncoming lane, and 0.5 from the number of one-side lanes when there is no oncoming lane. The value obtained by subtracting

Next, FIG. 14 is a diagram illustrating a method of calculating the maximum rearward deviation lane number T2 when the bending direction is the right direction with respect to the traveling direction of the vehicle. As shown in FIG. 14, when the bending direction is the right direction with respect to the traveling direction of the vehicle, the link L1 set on the bending road becomes longer than the travel route L2 on which the vehicle travels, and the link L1 When the maximum amount of deviation occurs in the road width direction with respect to the travel route L2, the link L1 is set along the left end of the curved road, and the vehicle travels in the rightmost lane. Therefore, the maximum rear shift lane number T2 is a value obtained by subtracting 0.5 from the number of one-side lanes (2 in FIG. 14) regardless of the presence or absence of the oncoming lane.
In addition, although the case of left-hand traffic was demonstrated in FIGS. 11-14, in the case of right-hand traffic, the value of T1 and T2 will be interchanged.

Subsequently, in S35, the CPU 41 is caused by traveling on a curved road based on the maximum front shift lane number T1 and the maximum rear shift lane number T2 calculated in S34, and the bending angle and lane width acquired in S33. The error range of the detected position of the vehicle is estimated. Specifically, the maximum error amount D1 generated on the traveling direction side with respect to the detection position is calculated by the following equation (1), and the maximum amount generated on the opposite side of the traveling direction with respect to the detection position is calculated by equation (2). The error amount D2 is calculated. As a result, the estimated error range is “range from the front D1 of the vehicle detection position to the rear D2 of the vehicle detection position”.
D1 [m] = 2 × T2 × P ÷ tan (((180−θ) / 2) π ÷ 180) (1)
D2 [m] = 2 × T1 × P ÷ tan (((180−θ) / 2) π ÷ 180) (2)
P: Lane width [m], θ: Bending angle [°]
Thereafter, the process proceeds to S22.

  On the other hand, in S36, the CPU 41 determines whether or not the vehicle is traveling on a curved road that curves with a predetermined curvature, based on the road shape of the road acquired in S31. Here, when the vehicle travels on a curved road, the shape of the link on the curved road is specified by connecting the shape interpolation points for specifying the shape of the link with a straight line instead of a curve. An error occurs between the position of the vehicle detected by dead reckoning and the actual position of the vehicle.

  Hereinafter, the reason why an error occurs due to traveling on a curved road will be briefly described with reference to FIG. As shown in FIG. 15, when a vehicle travels on a curved road curved with a predetermined curvature, a link L3 connecting the shape complement points C1 to C5 with a straight line and a travel route L4 of the vehicle traveling in a curved line Does not match. Accordingly, the length of the link L3 set on the curve road and the length of the route L4 on which the vehicle actually travels are not the same length, and the link L3 is slightly shorter than the travel route L4. Here, as described above, in dead reckoning, the current position of the vehicle is detected on the assumption that the vehicle moves on the link. Therefore, the actual vehicle position is slightly behind the vehicle position detected by dead reckoning. (That is, an error occurs in the detection position of the vehicle). Further, as described later, the error amount changes depending on the shape of the curved road (specifically, the radius of curvature and the intersection angle).

  And when it determines with the vehicle driving | running | working the curve road which curves with a predetermined curvature (S36: YES), it transfers to S37. On the other hand, if it is determined that the vehicle is not traveling on a curved road (S36: NO), it is estimated that there is no error in the detected position of the vehicle based on the road shape of the road on which the vehicle travels, and S22 Migrate to

  In S <b> 37, the CPU 41 acquires information related to the curved road on which the vehicle travels from the map information DB 31. Specifically, the length of each line segment (C1-C2, C2-C3, C3-C4, C4-C5 in the example shown in FIG. 15) connecting adjacent shape complement points included in the curve road with a straight line and each line segment. Are obtained. The length of each line segment and the connection angle of each line segment may be calculated from the position coordinates of each shape complement point included in the curve road.

  Next, in S38, the CPU 41 divides the curved road on which the vehicle travels with the shape complementing point as a boundary based on the shape complementing point acquired in S37. For example, in the example shown in FIG. 15, it is divided into four sections C1-C2, C2-C3, C3-C4, and C4-C5. Then, the curve radius R and the intersection angle φ of the curved road on which the vehicle travels are calculated for each divided section.

In the following, a method for calculating the curve radius R and the intersection angle φ will be described with reference to FIG. 16, taking the section C1-C2 shown in FIG. 15 as an example. As shown in FIG. 16, the length of the line segment (string) connecting the shape complement points C1 and C2 with a straight line is a [m], and the line segment (string) connecting the shape complement points C2 and C3 with a straight line is shown. When the length is b [m] and the connection angle of each line segment is α [°], the curve radius R is calculated by the following equation (3).
R [m] = √ (a ² + b ² −2abcos (απ / 180)) ÷ 2 sin (α × π / 180) (3)
Further, the intersection angle φ is calculated by the following equation (4).
φ [°] = αsin ((a / 2) / 2R) × 2 × 180 / π (4)
Similarly, the curve radius R and the intersection angle φ are calculated for the other sections (C2-C3, C3-C4, C4-C5).

  Subsequently, in S39, the CPU 41 connects the length of the curve (arc) drawn by the curve road for each divided section (that is, the length of the travel route on which the vehicle actually travels) and the shape complement point by a straight line. The difference from the length of the (string) (that is, the length of the link specified by the shape interpolation point) is calculated.

In the following, taking the section C1-C2 shown in FIG. 15 as an example, the difference between the length of the curve (arc) drawn by the curve road and the length of the line segment (string) connecting the shape interpolation points with a straight line is shown below. A calculation method will be described with reference to FIG. As shown in FIG. 16, when the curve radius of the C1-C2 curve section is R [m] and the intersection angle is φ [°], the curve (arc) of the C1-C2 curve section is expressed by the following equation (5). Is calculated.
a ′ [m] = 2πR × (φ / 360) (5)
Then, the difference D _c1-c2 between the length a ′ of the curve (arc) in the curve section C1-C2 and the length a of the line segment (chord) connecting the shape complementary points with a straight line by the following equation (6). Is calculated.
D _c1-c2 [m] = a′−a (6)
Similarly, with respect to the other sections (C2-C3, C3-C4, C4-C5), the difference between the length of the curve (arc) in the curve section and the length of the line segment (string) connecting the shape complementary points with a straight line. D _c2-c3 , D _c3-c4 , D _c4-c5 are calculated.

Thereafter, in S40, the CPU 41 calculates the curve road based on the total value of the difference between the length of the curve (arc) of each section calculated in S40 and the length of the line segment (string) connecting the shape complement points with a straight line. The error range of the detected position of the vehicle caused by traveling is estimated. Specifically, a value obtained by adding up the differences between the length of the curve (arc) of each section calculated in S40 and the length of the line segment (string) obtained by connecting the shape complement points with a straight line (that is, the curve road) The difference between the length of the curve drawn by and the total length of each line segment connecting multiple shape interpolation points arranged on the curve road on the reverse side of the traveling direction with respect to the detection position D3. As a result, the estimated error range is “range from the vehicle detection position to the rear of D3 of the vehicle detection position”.
When traveling on a curved road, the length of the link specified by the shape complement point is always shorter than the length of the travel path on which the vehicle actually travels. Therefore, the error range of the detected position of the vehicle caused by traveling on the curved road occurs only on the opposite side of the traveling direction with respect to the detected position, and does not occur on the traveling direction side. Thereafter, the process proceeds to S22.

  Next, a sub-process of the error range estimation process based on the sensor error executed in S22 will be described with reference to FIG. FIG. 17 is a flowchart of a sub-processing program for error range estimation processing based on sensor error.

  In S41 to S43 below, the CPU 41 calculates a detection error (that is, a detection error of the travel distance) of the vehicle speed sensor (first sensor) 22 for detecting the travel distance of the vehicle. In S44 to S46, the CPU 41 The detection error of the gyro sensor (second sensor) 24 for detecting the azimuth of the vehicle (that is, the detection error of the azimuth of the vehicle) is calculated.

Specifically, first, in S41, the CPU 41 calculates a travel distance detection error (hereinafter referred to as a first error) due to the pulse distance of the vehicle speed sensor 22 deviating from the predicted value (learned value). Here, the vehicle speed sensor 22 is a sensor that detects the travel distance of the vehicle based on a pulse that is output every time the axle of the vehicle rotates once (that is, travels around the outer circumference of the tire). The pulse distance defines the distance traveled by the vehicle when the axle rotates once, and its value is determined (predicted) by learning up to the present time. That is, every time a pulse is output, a value obtained by adding the pulse distance is detected as the travel distance of the vehicle. However, depending on the learning state, the pulse distance may deviate from an accurate value. The first error is a detection error of the vehicle speed sensor 22 that occurs when the pulse distance deviates from an accurate value.
Since the pulse distance may be longer or shorter than an accurate value, the first error causes an error in both the traveling direction and the reverse direction with respect to the detected position of the vehicle.

Next, in S <b> 42, the CPU 41 calculates a travel distance detection error (hereinafter referred to as a second error) due to the vehicle traveling on a sloped road. As described above, each time a pulse is output, the vehicle speed sensor 22 detects a value obtained by adding the pulse distance as the travel distance of the vehicle. However, when the road is inclined at a predetermined angle β, an error occurs as follows. For example, as shown in FIG. 18, when the vehicle position at the time when the vehicle speed sensor 22 outputs a vehicle speed pulse last time is S and the pulse distance is h, the actual vehicle position at the next time the pulse distance is detected is S1. It becomes. However, dead reckoning does not consider the road gradient, so the detected vehicle position (that is, the new vehicle position detected by adding the pulse distance from the point where the vehicle speed sensor 22 previously output the vehicle speed pulse) is S2. Therefore, every time a pulse is detected, (h-hcosβ) is generated as the second error.
Regardless of the gradient angle β, S1 is always located behind S2, so that the second error causes an error only in the reverse direction of the traveling direction with respect to the detected position of the vehicle.

Subsequently, in S43, the CPU 41 calculates a travel distance detection error (hereinafter referred to as a third error) due to the fact that no pulse is output due to an error or the like even though the pulse should be output from the vehicle speed sensor 22. . As described above, each time a pulse is output, the vehicle speed sensor 22 detects a value obtained by adding the pulse distance as the travel distance of the vehicle. However, when the pulse is not output despite the timing at which the pulse should be output due to an error or the like, the detected travel distance is shorter than the actual travel distance. The third error is a detection error of the vehicle speed sensor 22 corresponding to the pulse distance caused by the fact that no pulse is output.
Note that when the pulse is not output, the detected travel distance is necessarily shorter than the actual travel distance. Therefore, the third error causes an error only in the traveling direction with respect to the detected position of the vehicle.

On the other hand, in S44, the CPU 41 calculates a vehicle direction detection error (hereinafter referred to as a fourth error) due to the sensitivity coefficient of the gyro sensor 24 deviating from the predicted value (learned value). Here, the gyro sensor 24 has an element that vibrates inside, and detects and outputs the angular velocity of the vehicle from a potential difference generated based on a motion newly generated in the device when a rotational motion is applied to the vibrating device. . Further, the CPU 41 detects a change in the direction of the vehicle by calculating the output angular velocity. The sensitivity coefficient defines the correspondence between the potential difference and the azimuth change of the vehicle together with the resolution and the like, and its value is determined (predicted) by learning up to the present time. However, depending on the learning state, the sensitivity coefficient may deviate from an accurate value. The fourth error is a detection error of the gyro sensor 24 caused by the sensitivity coefficient deviating from an accurate value.
Since the sensitivity coefficient may be larger or smaller than an accurate value, the fourth error causes an error in both the traveling direction and the reverse direction with respect to the detected position of the vehicle.

Next, in S45, the CPU 41 calculates a vehicle direction detection error (hereinafter referred to as a fifth error) due to a change in ambient temperature. As described above, the gyro sensor 24 includes an element that vibrates inside, and detects and outputs the angular velocity of the vehicle from a potential difference that is generated based on a motion that is newly generated in the device when a rotational motion is applied to the vibrating device. The potential difference is determined based on the momentum with respect to the reference position of the element, but this reference position slightly changes depending on the temperature around the sensor. As a result, an error occurs between the actual vehicle direction and the detected vehicle direction. The fifth error is a detection error of the gyro sensor 24 that occurs due to a deviation of the reference position of the element.
Since the potential difference may be larger or smaller than an accurate value, the fifth error causes an error in both the traveling direction and the reverse direction with respect to the detected position of the vehicle.

Next, in S46, the CPU 41 calculates a vehicle direction detection error (hereinafter referred to as a sixth error) due to the vehicle traveling on a road with a gradient. As described above, the gyro sensor 24 includes an element that vibrates inside, and detects and outputs the angular velocity of the vehicle from a potential difference that is generated based on a motion that is newly generated in the device when a rotational motion is applied to the vibrating device. The output value (electric signal indicating the angular velocity) output from the gyro sensor 24 is determined based on the momentum with respect to the reference position of the element. This output value is generated in the vehicle when the vehicle travels on a gradient. The weight drops below the exact value. As a result, an error occurs between the actual vehicle direction and the detected vehicle direction. The sixth error is a detection error of the gyro sensor 24 that is caused when the output value output from the gyro sensor 24 falls below an accurate value.
Since the output value output from the gyro sensor 24 is necessarily smaller than an accurate value, the sixth error causes an error only in the reverse direction of the traveling direction with respect to the detected position of the vehicle.

  Thereafter, in S47, the CPU 41, based on the detection error of the vehicle speed sensor 22 (that is, the detection error of the travel distance) calculated in S41 to S46 and the detection error of the gyro sensor 24 (that is, the detection error of the direction of the vehicle), The error range of the detected position of the vehicle caused by the sensor error is estimated.

Specifically, the maximum error amount D4 generated on the traveling direction side with respect to the detection position per pulse output is calculated by the following equation (7), and the detection position is detected per pulse output by the equation (8). Thus, the maximum error amount D5 generated on the opposite side of the traveling direction is calculated.
D4 [m] = h− (h + error 1 + error 3) × cos (error 4 + error 5) (7)
D5 [m] = h− (h + error 1 + error 2) × cos (error 4 + error 5 + error 6) (8)
h: Pulse distance [m]
Then, the detected position of the vehicle caused by the sensor error by the value D4 ′ obtained by adding D4 up to the current time after recognizing the stop line and the value D5 ′ obtained by adding D5 up to the current time after recognizing the stop line last time. The error range is estimated. That is, the estimated error range is “a range from D4 ′ front of the vehicle detection position to D5 ′ rear of the vehicle detection position”. Thereafter, the process proceeds to S23.

  Next, a sub-process of the error range estimation process based on the lane change executed in S23 will be described with reference to FIG. FIG. 19 is a flowchart of a sub-processing program for error range estimation processing based on lane change.

  First, in S51, the CPU 41 acquires the number of lanes on one side of the road on which the vehicle travels from the map information DB 31.

  Next, in S52, the CPU 41 specifies the maximum number of lane changes that can be performed on the road on which the vehicle is traveling based on the number of one-side lanes acquired in S51. Specifically, the value obtained by subtracting 1 from the number of lanes on one side of the road on which the vehicle is traveling is the maximum number of lane changes that can be made on the road on which the vehicle is traveling.

Subsequently, in S53, the CPU 41 estimates the error range of the detected position of the vehicle caused by changing the lane based on the maximum number of lane changes specified in S52.
For example, as shown in FIG. 20, when the vehicle 98 travels on a three-lane road on one side, the number of lane changes that can be performed by the vehicle 98 is a maximum of two times. Therefore, a value obtained by multiplying the maximum error distance σ (for example, 1.5 m) that can occur per lane change by 2 is the maximum error amount that may occur for the vehicle 98. Therefore, a value obtained by multiplying the maximum number of lane changes that can be performed on the road on which the vehicle is traveling by the maximum error distance σ (for example, 1.5 m) that can occur per lane change is calculated with respect to the detection position. Thus, the maximum error amount D6 generated on the opposite side of the traveling direction is obtained. As a result, the estimated error range is “a range from the vehicle detection position to the rear of D6 of the vehicle detection position”.
When a lane change is performed, the link length is always shorter than the length of the travel route on which the vehicle actually travels. Accordingly, the error range of the detected position of the vehicle caused by changing the lane occurs only on the side opposite to the traveling direction with respect to the detected position, and does not occur on the traveling direction side. In addition, the maximum error distance σ that can occur per lane change may be determined by a learned value, or a fixed value may be used. Moreover, you may determine based on a vehicle type, road width, and road classification. Thereafter, the process proceeds to S24.

As described above in detail, according to the navigation device 1 according to the present embodiment, the moving body position detection method using the navigation device 1, and the computer program executed by the navigation device 1, the stop line is recognized with high accuracy. The current position of the vehicle is detected using the location system, and after the stop line is recognized, the current position of the vehicle is detected by dead reckoning navigation (S2), and the vehicle moves on a curved road bent at a predetermined angle. Since the error range of the current position of the vehicle detected by dead reckoning navigation is estimated based on the lane width, the number of lanes, and the bending angle of the curved road (S9), even when the vehicle travels on the curved road, It is possible to accurately estimate an error range generated with respect to the detected position of the vehicle in consideration of the shape of the curved road. As a result, it is possible to execute guidance and control for the vehicle at an appropriate timing by considering the estimated error range.
In addition, since the error range is estimated based on the bending direction of the curved road, the maximum amount of deviation (maximum number of front deviation lanes T1) that can occur between the route on which the vehicle moves on the curved road and the link set on the curved road. And the maximum rear shift lane number T2) can be appropriately specified for each bending direction, and an error range generated between the vehicle detection position and the actual vehicle position can be accurately estimated based on the shift amount. Is possible.
In addition, when the vehicle travels on a curved road bent at a predetermined angle, an error range that occurs in the vehicle traveling direction and in the opposite direction with respect to the vehicle detection position is estimated, so the vehicle detection position and the actual vehicle position are estimated. It is possible to estimate the error range with respect to the direction of the error in consideration of the direction of the error that may occur between the two.
In addition, when the vehicle travels on a curved road that curves with a predetermined curved shape, the error range of the detected position of the vehicle is estimated based on the curve radius and the intersection angle of the curve drawn by the curved road. Even when traveling on a road, it is possible to accurately estimate an error range generated with respect to the detected position of the vehicle in consideration of the shape of the curved road. As a result, it is possible to execute guidance and control for the vehicle at an appropriate timing by considering the estimated error range.
In addition, since the error range is estimated based on the difference between the length of the curve drawn by the curve road and the total length of each line segment connecting a plurality of shape interpolation points arranged on the curve road, the vehicle actually traveled Based on the difference between the distance and the length of the road link specified by the shape complement point, it is possible to accurately estimate an error range that occurs between the detected position of the vehicle and the actual position of the vehicle.
In addition, when the vehicle travels on a curved road that curves with a predetermined curved shape, an error range that occurs in a direction opposite to the traveling direction of the vehicle with respect to the detected position of the vehicle is estimated, so the detected position of the vehicle and the actual vehicle It is possible to estimate the error range with respect to the direction of the error in consideration of the direction of the error that may occur with the position of the error.
Further, the detection error of the vehicle speed sensor 22 for detecting the travel distance of the vehicle specifies a direction in which an error is caused with respect to the detection position of the vehicle (S41 to S43), and for detecting a change in the direction of the vehicle. Since the direction in which the detection error of the gyro sensor 24 causes an error with respect to the detected position of the vehicle is specified (S44 to S46), the error range of the detected position of the vehicle is estimated based on the specified direction (S47). Even if a detection error occurs in the sensor, it is possible to appropriately specify the influence of the generated detection error on the detection position of the vehicle, and the error range generated for the detection position of the vehicle can be accurately determined. Can be estimated. As a result, it is possible to execute guidance and control for the vehicle at an appropriate timing by considering the estimated error range.
The detection error of the vehicle speed sensor 22 includes a first error that occurs when the correspondence between the number of pulse outputs and the travel distance of the vehicle deviates from the predicted value, and a second error that occurs when the vehicle travels on a sloped road. The error range is estimated in consideration of the detection error of the first sensor that may cause an error in the detection position of the vehicle because it includes an error and a third error that occurs due to the fact that the pulse is not output at the timing to be output. It becomes possible to do.
In addition, it is possible to specify in which direction the first to third errors generated in the vehicle speed sensor 22 cause an error with respect to the detection position of the vehicle. It becomes possible to estimate more accurately.
Further, the detection error of the gyro sensor 24 includes a fourth error caused by the correspondence between the potential difference and the azimuth change of the vehicle deviating from the predicted value, a fifth error caused by a temperature change around the second sensor, Since it includes a sixth error caused by the vehicle traveling on a certain road, it is possible to estimate the error range in consideration of the detection error of the second sensor that may cause an error in the detection position of the vehicle. .
In addition, it is possible to specify in which direction the fourth to sixth errors generated in the gyro sensor 24 cause an error with respect to the detection position of the vehicle, and an error range generated with respect to the detection position of the vehicle can be specified. It becomes possible to estimate more accurately.
Further, the maximum number of lane changes that can be performed on the road on which the vehicle is traveling is identified from the number of lanes on the road on which the vehicle is traveling (S52), and the detection position of the vehicle is determined based on the identified maximum number of lane changes. Since the error range is estimated (S53), it is possible to accurately estimate the error range in consideration of the maximum error that occurs with respect to the detected position of the vehicle when the vehicle changes lanes. As a result, it is possible to execute guidance and control for the vehicle at an appropriate timing by considering the estimated error range.
Also, since the value obtained by subtracting 1 from the number of lanes on the road on which the vehicle is traveling is specified as the maximum number of lane changes that can be performed on the road on which the vehicle is traveling, the road on which the vehicle is traveling on the basis of the road shape is specified. It is possible to accurately specify the maximum number of lane changes that can be made.
In addition, when the vehicle changes lanes, an error range that occurs in the direction opposite to the traveling direction of the vehicle with respect to the detected position of the vehicle is estimated, so that it may occur between the detected position of the vehicle and the actual position of the vehicle. It is possible to estimate an error range with respect to the error direction in consideration of a possible error direction.
Further, since the maximum error amount in the error range is estimated by multiplying the maximum number of lane changes that can be performed on the road on which the vehicle is traveling by a predetermined value, there is a possibility that the vehicle may be caused by changing the lane. It is possible to accurately estimate the error range of the detection position of a certain vehicle.
It is also possible to estimate the error range for the vehicle position detected by dead reckoning.
In addition, the high-accuracy location system detects features in the vicinity of the vehicle and detects the position of the vehicle based on the detection result, so the position of the vehicle is detected in more detail using the relative relationship with the feature. It becomes possible to do.
Furthermore, since the feature to be detected is a stop line formed on the road surface on which the vehicle moves, a large number of detection objects are installed at predetermined intervals on the road, and the position of the vehicle is detected while the vehicle is running. Can be performed at a predetermined interval and with a high frequency. Accordingly, it is possible to prevent a large difference between the estimated vehicle position and the actual vehicle position.

Note that the present invention is not limited to the above-described embodiment, and various improvements and modifications can be made without departing from the scope of the present invention.
For example, in the present embodiment, the guidance branch point guidance by the navigation device 1 is output by voice guidance from the speaker 16, but the guidance may be performed by displaying text on the liquid crystal display 15.

  In this embodiment, a stop line is used as a feature to be recognized in order to specify the current position of the vehicle. However, a road marking other than the stop line may be used. Further, obstacles other than road markings, buildings, road signs, etc. may be used. However, it is desirable that a plurality of features to be recognized be present at the departure point side from the front branch point and at a predetermined interval on the front side from the guide branch point.

  In the present embodiment, as the factors that cause an error in the detection position of the vehicle, “an error that occurs based on the road shape of the road on which the vehicle travels” and “an error that occurs based on the detection error of the sensor mounted on the vehicle”. “And an error generated based on a lane change performed by the vehicle” are considered, but other factors than the above may be considered.

  Further, in the present embodiment, the first error to the sixth error (FIG. 17) are considered as “error generated based on the detection error of the sensor mounted on the vehicle”, but other factors are also considered. It is good also as a structure.

  In the present embodiment, the curve radius and the intersection angle of the curved road are calculated by the equations (3) and (4), but may be acquired from the map information DB 31.

  In the present embodiment, a feature such as a stop line is detected by image recognition using the back camera 19, but other means (for example, a sensor) may be used as a means for detecting the stop line or the like. good. Similarly, a configuration may be employed in which the inclination angle of a stop line or the like is detected using means other than image recognition using the back camera 19.

  In the present embodiment, the signal information 38 is configured to store information related to all the traffic lights arranged around the branch point, but only information related to the signal on the most exit side is stored for each exit direction from the branch point. It is good also as composition to do. In that case, it is possible to implement the present invention by replacing the entrance side traffic signal in the present embodiment with the exit side traffic signal. Furthermore, it is good also as a structure which memorize | stores only the information regarding the traffic signal which is the most approach side for every approach direction to a branch point. Moreover, it is good also as a structure which memorize | stores the information regarding a stop line instead of a traffic light.

  In the present embodiment, as guidance for the guidance branch point, guidance is performed using the number of traffic lights (or branch points where traffic lights are installed) from the current position of the vehicle to the guidance branch point. However, other guidance may be provided. However, the effect of the present invention is remarkable particularly when performing guidance using a traffic light or a branch point.

  In addition to the navigation device, the present invention can be applied to a device having a function of detecting the current position of a moving body such as a vehicle. For example, the present invention can be applied to a portable terminal such as a cellular phone or a PDA, a personal computer, a portable music player, etc. (hereinafter referred to as a portable terminal or the like). Further, the present invention can be applied to a system including a server and a mobile terminal. In that case, each step of the above-described branch point guidance processing program (FIGS. 5, 8, 9, 17, and 19) may be configured to be implemented by either a server or a portable terminal. In addition, when the present invention is applied to a mobile terminal or the like, a mobile body other than a vehicle, for example, a user such as a mobile terminal or a vehicle position of a two-wheeled vehicle may be detected.

1 Navigation device 13 Navigation ECU
19 Back camera 31 Map information DB
33 feature table 37 feature data 41 CPU
42 RAM
43 ROM
81 Vehicle 82 Guide branch point 83-85 Near branch point 87-89 Exit side traffic light 90-93 Stop line

Claims (8)

A detection result of a first sensor mounted on the moving body for detecting a moving distance of the moving body and a detection result of a second sensor mounted on the moving body for detecting a change in direction of the moving body. A sensor result acquisition means for acquiring;
Position detection means for detecting the position of the moving body based on the detection result of the first sensor and the detection result of the second sensor acquired by the sensor result acquisition means;
A first error that specifies how much error amount the detection error of the first sensor causes in the traveling direction, the reverse direction, or both directions of the moving body with respect to the detection result of the position detection means. Impact identification means,
A second error that specifies the amount of error in which the detection error of the second sensor causes the moving body in the traveling direction, the reverse direction, or both directions with respect to the detection result of the position detecting means. Impact identification means,
Based on the identification results of the first influence identification means and the second influence identification means, the position detected by the position detection means based on the detection error of the first sensor and the detection error of the second sensor is the traveling direction The maximum error amount that can occur on the side and the maximum error amount that can occur on the side opposite to the traveling direction are specified, and the range in which the maximum error amount in each specified direction is detected by the position detection unit And an error range estimation means for estimating the error range of the body position. The first sensor detects a moving distance of the moving body by adding the predetermined distance each time a pulse is output based on a pulse output each time the moving body moves a predetermined distance. Sensor,
The detection error of the first sensor is
While specifying the predetermined distance based on the past learning result, the first error caused by the specified predetermined distance deviating from the distance traveled by the moving body in the interval at which pulses are actually output ;
A second error caused by the moving body moving on a sloped road;
A third error that is caused by a distance that the moving body has moved longer than the predetermined distance in an interval in which the pulses are not actually output at a timing at which the pulses are to be output ;
The mobile body position detection system according to claim 1, comprising: The first error causes an error in both the direction opposite to the traveling direction of the moving body with respect to the detection result of the position detection unit,
The second error causes an error in the direction opposite to the traveling direction of the moving body with respect to the detection result of the position detection unit,
The mobile body position detection system according to claim 2, wherein the third error causes an error in a traveling direction of the mobile body with respect to a detection result of the position detection unit. The second sensor detects an angular velocity of the moving body from a potential difference caused by a motion generated in an internal element, and further, based on the angular velocity and a sensitivity coefficient that defines a correspondence relationship between the potential difference and the azimuth change. A sensor for detecting a change in direction of
The detection error of the second sensor is
While identifying the sensitivity coefficient based on the past learning result, a fourth error caused by the identified sensitivity coefficient being out of the correspondence relationship between the actual potential difference and the azimuth change ,
A fifth error caused by a temperature change around the second sensor;
A sixth error caused by the moving body moving on a sloped road;
The mobile body position detection system according to claim 1, comprising: The fourth error causes an error in both the direction opposite to the moving direction of the moving body with respect to the detection result of the position detection unit,
The fifth error causes an error in both the direction opposite to the traveling direction of the moving body with respect to the detection result of the position detection unit,
The mobile body position detection system according to claim 4, wherein the sixth error causes an error in a direction opposite to a traveling direction of the mobile body with respect to a detection result of the position detection unit. A detection result of a first sensor mounted on the moving body for detecting a moving distance of the moving body and a detection result of a second sensor mounted on the moving body for detecting a change in direction of the moving body. A sensor result acquisition means for acquiring;
Position detection means for detecting the position of the moving body based on the detection result of the first sensor and the detection result of the second sensor acquired by the sensor result acquisition means;
A first error that specifies how much error amount the detection error of the first sensor causes in the traveling direction, the reverse direction, or both directions of the moving body with respect to the detection result of the position detection means. Impact identification means,
A second error that specifies the amount of error in which the detection error of the second sensor causes the moving body in the traveling direction, the reverse direction, or both directions with respect to the detection result of the position detecting means. Impact identification means,
Based on the identification results of the first influence identification means and the second influence identification means, the position detected by the position detection means based on the detection error of the first sensor and the detection error of the second sensor is the traveling direction The maximum error amount that can occur on the side and the maximum error amount that can occur on the side opposite to the traveling direction are specified, and the range in which the maximum error amount in each specified direction is detected by the position detection unit An error range estimating means for estimating as an error range of a body position. A sensor result acquisition unit detects a detection result of a first sensor mounted on the moving body to detect a moving distance of the moving body and a second mounted on the moving body to detect an azimuth change of the moving body . and Luz step to obtain a detection result of the sensor,
Position detecting means, on the basis of the sensor results were acquired by the acquiring means of the first sensor detection result and the detection result of the second sensor, and Luz step to detect the position of the movable body,
The first influence specifying means causes the detection error of the first sensor to produce an error amount in any of the moving direction, the reverse direction, or both directions of the moving body with respect to the detection result of the position detecting means. and Luz steps to identify whether to,
The second influence specifying unit causes the detection error of the second sensor to cause an error amount in any of the moving direction, the reverse direction, or both directions of the moving body with respect to the detection result of the position detecting unit. and Luz steps to identify whether to,
The error range estimation means is detected by the position detection means based on the detection error of the first sensor and the detection error of the second sensor based on the specification results of the first influence specifying means and the second influence specifying means. The maximum error amount that can be generated on the traveling direction side and the maximum error amount that can occur on the opposite side of the traveling direction are identified, and the range including the maximum error amount in each specified direction is detected. mobile location method characterized by having a Luz step to estimate an error range of the position of said mobile body detected by means. The computer,
A detection result of a first sensor mounted on the moving body for detecting a moving distance of the moving body and a detection result of a second sensor mounted on the moving body for detecting a change in direction of the moving body. A sensor result acquisition means for acquiring;
Position detection means for detecting the position of the moving body based on the detection result of the first sensor and the detection result of the second sensor acquired by the sensor result acquisition means ;
A first error that specifies how much error amount the detection error of the first sensor causes in the traveling direction, the reverse direction, or both directions of the moving body with respect to the detection result of the position detection means . Impact identification means ,
A second error that specifies the amount of error in which the detection error of the second sensor causes the moving body in the traveling direction, the reverse direction, or both directions with respect to the detection result of the position detecting means . Impact identification means ,
Based on the identification results of the first influence identification means and the second influence identification means , the position detected by the position detection means based on the detection error of the first sensor and the detection error of the second sensor is the traveling direction The maximum error amount that can occur on the side and the maximum error amount that can occur on the side opposite to the traveling direction are specified, and the range in which the maximum error amount in each specified direction is detected by the position detection unit An error range estimation means for estimating the error range of the body position;
Computer program to make it function .

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