Lane determination device and lane determination procedure

Abstract

In the present invention, a lane in which a vehicle is traveling is estimated by a lane estimation unit (14) based on map information, current position information of the vehicle, and white line information about a white line dividing a road in which the vehicle is traveling. The lane estimation unit (14) estimates the lane based on a lane probability for each lane obtained based on a line type of the white line, a lane probability for each lane obtained based on whether or not an adjacent lane is present, and a lane probability for each lane obtained based on a lane in which the vehicle was traveling when the lane was previously estimated.

Description

Technical FieldThe present invention relates to a lane determination device and a lane determination method that determines a lane as a lane on which a vehicle travels.Prior ArtTechnologies for determining a lane as a lane on which a vehicle travels are used if a current position of the vehicle in a car navigation device, a position of the unit, or the like is determined. For example, an environmental environment such as a lane of the vehicle and a curb is detected by using a sensor including a camera, a laser radar, and the like, thereby determining the current position of the vehicle.The technologies for determining the driving lane of the vehicle are described in, for example, JP 2008-276 642 A and JP 2005-4 442 A. In the technologies described in JP 2008-276 642 A and JP 2005-4 442 A, the travel lane of the vehicle is determined based on image information of an image captured by the camera and map information indicating a map.Specifically, a lane recognition apparatus described in JP 2008-276 642 A is configured to determine which is a broken line or a solid white line, the white line being detected from image information of an image captured by a rear camera, by using the map information and the image information, and thereby estimate whether the lane is on a right or a left side of a road.Moreover, a lane determination device described in JP 2005-4 442 A is configured to determine whether a white line pattern detected from an image detected by the camera coincides with a white line pattern determined in advance from the map and the image based on information on the determined white line pattern, thereby determining the lane.DE 10 2013 016 596 A1 discloses a method for operating a driver assistance device for a motor vehicle. The driver assistance device has a navigation system, having a position sensor and a digital map, and also environment sensors. The method comprises the steps of locating the motor vehicle by means of the position sensor, assigning the motor vehicle to a road by the navigation system, capturing data of the environmental sensors, evaluating the data and calculating individual probabilities for the presence of the motor vehicle in different lanes of the road on the basis of the evaluated data of the environmental sensors and available information of the navigation system, calculating a presence probability of the motor vehicle for each lane on the basis of the individual probabilities and assigning a lane to the motor vehicle and determining a degree of confidence for the assignment of the lane. In order to achieve an improved lane assignment of the host vehicle, the individual probabilities are weighted as a function of current driving-mode-relevant parameters when calculating the location probability. This has the advantage that the lane assignment is realized in a particularly flexible and reliable manner. DE 10 2013 020 334 A1 describes a method for determining a lane of a multi-lane roadway for a vehicle, in which a current lane traveled by the vehicle is assigned to the vehicle. In this case, it is provided that a value is assigned to the currently traveled lane, this value being incremented when a lane change to a lane adjacent in a first direction and / or decremented when a lane change to a lane adjacent in a second direction.DE 10 2010 007 091 A1 discloses a further method for determining the position for a motor vehicle, in which a comparison of the geoposition with the digital road map data, the driving lane and at least further driving lane information is carried out.SUMMARY OF THE INVENTIONObject of the InventionIn the technologies described in JP 2008-276 642 A and JP 2005-4 442 A, information on a white line detected from an image acquired in real time is used. There is no problem in a situation where the white line is detected with high accuracy; however, on a real road, the white line is not always detected due to an accuracy of the camera and a density of the white line. When a white line is not detected, there is a fear that the driving lane cannot be accurately determined in the technologies described in JP 2008-276 642 A and JP 2005-4 442 A.Thus, in the technologies described in JP 2008-276 642 A and JP 2005-4 442 A, there is a problem in that the travel lane of the vehicle cannot be stably determined.It is an object of the present invention to provide a lane determination apparatus and a lane determination method which can stably determine the lane of the vehicle.Means for Achieving the ObjectThe object is achieved by a device having the features specified in claim 1. Advantageous embodiments are evident from the sub-claims.The object is further achieved by a method according to claim 9.Effects of the InventionAccording to the lane determination apparatus of the present invention, the lane is estimated by the lane estimation unit based on the probability that each of the lanes is the lane, the probability is obtained based on the line type of the white line, the probability that each of the lanes is the lane, the probability is obtained based on whether or not the adjacent line exists, and the probability that each of the lanes is the lane, the probability is obtained based on the lane on which the vehicle has traveled when the lane has been estimated beforehand. In this way, the lane can be estimated with good accuracy. Moreover, when a detection accuracy for the white line is relatively low, the lane can be estimated by using one of the above-described probabilities that each of the lanes is the lane, and accordingly estimation with relatively high stability can be performed. Thus, the driving lane of the vehicle can be stably determined.According to the lane determination apparatus of the present invention, the lane is estimated based on the probability that each of the lanes is the lane, the probability is obtained based on the line type of the white line, the probability that each of the lanes is the lane, the lane is obtained based on whether or not the adjacent lane exists, and the probability that each of the lanes is the lane, the probability is obtained based on the lane on which the vehicle has traveled when the lane has been previously estimated. In this way, the lane can be estimated with good accuracy. Moreover, when a detection accuracy of the white line is relatively low, the driving lane can be estimated by using one of the above-described probabilities that each of the lanes is the driving lane, and accordingly estimation with relatively high stability can be performed. Thus, the driving lane of the vehicle can be stably determined.Objects, features, aspects and advantages of the present invention will become more apparent from the following detailed description and the accompanying drawings.Brief Description of the FiguresFIG. 1 is a block diagram showing a configuration of a lane determination device in a first embodiment of the present invention. FIG. 2 is a block diagram showing a hardware configuration of the lane determination device 1 in the first embodiment of the present invention. FIG. 3 is a view showing an example of a white line information detectability region 30 by a white line information acquisition unit 13. FIG. 4 is a view showing an example of a relationship between positions of vehicles and white lines. FIG. 5 is a view showing another example of the relationship between the positions of the vehicles and the white lines. FIG. 6 is a view showing an example of a relationship between the positions of the vehicles and the white lines when a lane change occurs. FIG. 7 is a view showing an example of detection positions of the white lines. FIG. 8 is a view showing an example of the detection positions of the white lines changed by the lane change. FIG. 9 is a graph showing temporal changes in the detection positions of the white lines. FIG. 10 is a table showing an example of a lane probability list on a two-line road. FIG. 11 is a table showing an example of a lane probability list on a three-lane road. FIG. 12 is a table showing an example of a lane probability list on a four-lane road. FIG. 13 is a table showing another example of the lane probability list for use in a lane estimating unit 14. FIG. 14 is a flowchart showing a processing method related to lane determination processing in the lane determination device 1 of the first embodiment of the present invention. FIG. 15 is a flowchart showing a processing method related to lane estimation processing in the lane determination device 1 of the first embodiment of the present invention. FIG. 16 is a flowchart showing the processing method related to the lane estimation processing in the lane determination device 1 of the first embodiment of the present invention. FIG. 17 is a flowchart showing a processing method related to an irregular white line information identification processing in the lane determination device 1 of the first embodiment of the present invention. FIG. 18 is a block diagram showing a configuration of a lane determination device 2 in a second embodiment of the present invention. FIG. 19 is a flowchart showing a processing method related to position determination processing in the lane determination device 2 of the second embodiment of the present invention. FIG. 20 is a block diagram showing a configuration of a lane determination device 3 in a third embodiment of the present invention. FIG. 21 is a flowchart showing a processing method related to error correction processing in the lane determination device 3 of the third embodiment of the present invention.DESCRIPTION OF EMBODIMENTS< Embodiment>FIG. 1 is a block diagram showing a configuration of a lane determination device 1 in a first embodiment of the present invention. The lane determination device 1 of this embodiment is configured to be attachable to a vehicle such as an automobile. In this embodiment, the lane determination device 1 is realized by a navigation device having a navigation function for route guidance. A lane determination method of another embodiment of the present invention is executed by the lane determination device 1 of this embodiment.The lane determination device 1 is configured by including a map database 11, a current position acquisition unit 12, a white line information acquisition unit 13, a lane estimation unit 14, a lane monitoring unit 15, a white line information storage unit 16, and a lane determination unit 17.The map database 11 is realized by a storage device such as a hard disk (abbreviation: HDD) device and a semiconductor memory, for example. The map database 11 stores map information on a map. The map database 11 belongs to a map information storage unit.The map information is configured by hierarchally arranging a plurality of maps belonging to predetermined scales. The map information includes: road information as information on roads; lane information as information on lanes constituting roads; and configuration line information as information on configuration lines constituting the lanes.The road information includes, for example, information on shapes of roads, widths and longitudes of roads, bends of roads, slopes / slopes of roads, identifiers of roads, number of lanes of roads, types of lines of roads, and additionally road attributes such as general roads, express freeways, and priority roads.The lane information includes, for example, information about identifiers of lanes constituting the roads, lengths and latitudes of the lanes, and additionally center lines.The configuration line information includes information on identifiers of respective lines constituting the lane shapes, lengths and latitudes of the respective lines constituting the lane shapes, and additionally line types and bends of the respective lines constituting the lane shapes. The road information is managed for each of the roads. The lane information and the configuration line information are managed for each of the lanes.The map information is used for navigation, driving support, automatic driving, and the like. The map information may be updated through communication or may be generated from white line information acquired by the white line information acquisition unit 13.In this embodiment, the map database 11 is provided in the lane determination device 1, but it may be provided outside the lane determination device 1. For example, the map database 11 may be provided outside the vehicle to which the lane determination device 1 is attached, for example, in a server device outside the vehicle. In this case, the lane determination device 1 is configured to acquire all or part of the map information from the map database provided outside the vehicle through communication. Specifically, the lane determination device 1 is configured to acquire the map information from, for example, a map database provided in the server device outside the vehicle via a communication network such as the Internet.The current position acquisition unit 12 acquires current position information indicating a current position of the vehicle to which the lane determination device 1 is mounted. The current position information is indicated by, for example, any one or a plurality of: a road link indicating a road on which the vehicle travels; lengths and latitudes of the current position; a road identifier as identification information on a road on the map based on the map information; a lane identifier as identification information of the lane; a road attribute; additionally, a rectangular area including the current position on the map; and the like.The current position detection unit 12 is configured of, for example, a global positioning system (abbreviation: GPS) sensor, a gyroscope sensor, a vehicle speed sensor, and an acceleration sensor.The current position acquisition unit 12 performs map matching with the map based on the map information read from the map database 11 by using the information detected by the GPS sensor, the gyroscope sensor, the vehicle speed sensor, and the acceleration sensor, and thereby generates the current position information indicating the current position.The current position acquisition unit 12 may be configured to acquire the current position information from the hardware provided outside the lane determination device 1 via the communication network such as the Internet. The current position acquisition unit 12 outputs the acquired current position information to the lane estimation unit 14.The white line information acquisition unit 13 is configured of a front camera provided to be capable of acquiring an area in front of the vehicle in a traveling direction, a rear camera provided to be capable of acquiring an area behind the vehicle in the traveling direction, and sensors such as laser radars.The white line information acquisition unit 13 acquires the above-mentioned areas by using the front camera and the rear camera, thereby acquiring the white line information about white lines plotted on roads in the above-mentioned areas. Here, the white lines denote division lines that share a road, and include a road center line, a lane boundary line, and a road boundary line. Moreover, the white lines include lines having colors that are not white, such as a yellow line.The white line information includes information indicating line types of the white lines such as a solid line, a broken line, a double line, and a yellow line, and additionally information indicating shapes of the white lines. The information indicating the shapes of the white lines is, for example, information in which each of the white lines is represented by a function. The white line information may include information indicating a quality of the white lines. Moreover, the white line information may include information indicating lengths of white lines, of which white line information is usable as reliable.The white line information acquisition unit 13 acquires white line information on all white lines within a detectable range of the vehicle. Specifically, for example, as shown in FIG. 7 to be described later, the white line information acquisition unit 13 acquires white line information about a left white line (hereinafter referred to as "left white line") and a right white line (hereinafter referred to as "right white line") of the traveling lane, directed forward in the traveling direction of the vehicle, and additionally about left white lines and right white lines of lanes, hereinafter referred to as "adjacent lanes") adjacent to the traveling lane.In this embodiment, the white line information acquisition unit 13 acquires information on roads, obstacles, and road signs in the above-mentioned areas in addition to the white line information such that the front camera and the rear camera acquire the above-mentioned areas. The white line information acquisition unit 13 may be configured to acquire the white line information from the hardware provided outside the lane determination device 1 via the communication network such as the Internet. The white line information acquisition unit 13 outputs the acquired white line information to the lane estimation unit 14 and the lane monitoring unit 15.The lane estimating unit 14 estimates the lane from the map information read out from the map database 11, the current position information output from the current position acquiring unit 12, and the white line information output from the white line information acquiring unit 13.Specifically, the lane estimating unit 14 acquires the identifier of the traveling road from the current position information output from the current position acquiring unit 12. From the map information read out from the map database 11, the lane estimating unit 14 acquires number-of-lanes information indicating the number of lanes of the road on which the vehicle travels and line type information indicating line types thereof.The lane estimating unit 14 acquires information indicating the line types of the white lines and the positions of the white lines from the white line information output from the white line information acquiring unit 13. The lane estimating unit 14 calculates a wide (hereinafter referred to as "lane width" in some cases) of the lane and the adjacent lanes from the acquired information on the positions of the white lines.The lane estimating unit 14 stochastically estimates the lane on which the vehicle is currently traveling from a lane probability of each of the lanes obtained based on the line type of the white line, a lane probability of each of the lanes obtained based on whether or not such adjacent lanes exist, and a lane probability of each of the lanes obtained based on a lane on which the vehicle has traveled when the lane has been previously estimated. The lane estimating unit 14 estimates that a lane in which a lane probability is the largest is the lane from the lane probability of each of the lanes. Here, "lane probability" denotes a probability that each of the lanes is the lane in which the vehicle travels at the current time.In this embodiment, the lane estimation unit 14 estimates the lane by using the Bayesian estimation. The estimation method for the driving lane by the driving lane estimation unit 14 is not limited thereto, and in another embodiment of the present invention, the driving lane may be estimated by using another method such as maximum likelihood estimation. The lane estimating unit 14 outputs estimated lane information indicating the estimated lane as an estimation result to the lane monitoring unit 15.The lane monitoring unit 15 stores the white line information output from the white line information acquisition unit 13 in the white line information storage unit 16. Upon determining that the lane has been changed, the lane monitoring unit 15 updates the number of lanes stored in the white line information storage unit 16Specifically, the lane monitoring unit 15 continuously monitors the white line information output from the white line information acquisition unit 13, and determines whether or not the lane change has been performed based on the white line information output from the white line information acquisition unit 13 and the white line information stored in the white line information storage unit 16.More specifically, the lane monitoring unit 15 determines whether a detection position of the left white line and a detection position of the right white line have changed, thereby detecting whether or not the vehicle has changed lanes. The lane monitoring unit 5 determines whether or not the lane change has been performed based on a detection result whether or not the vehicle has changed the lane. The lane transmission unit 15 outputs a determination result of whether or not the lane has been changed and the updated number of the lane to the lane determination unit 17.White line information storage unit 16 stores the white line information acquired by white line information acquisition unit 13. The white line information storage unit 16 stores white line information acquired in the past. That is, the white line information storage unit 16 is realized by a storage device such as a semiconductor memory. The guidance line information storage unit 16 stores history information as white line information acquired by the white line information acquisition unit 13 within a predetermined time (hereinafter, this may be referred to as "predetermined time" in some cases).The white line information storage unit 16 stores the white line information including the information indicating the shapes of the white lines, the line types of the white lines, and the quality of the white lines, and information indicating a time when the white line information has been acquired. In addition, the white line information storage unit may store information obtained by processing the left white line and the right white line, and the like.Upon the estimated lane information being output from the lane estimating unit 14, the lane determining unit determines 7 that the lane estimated as the lane by the lane estimating unit 14 is the lane based on the output estimated lane information.Upon determining the driving lane based on the estimated lane information output from the driving lane estimation unit 14, the driving lane determination unit 17 determines the driving lane based on the determination result output from the driving lane monitoring unit 15. When the determination result output from the lane monitoring unit 15 indicates that the lanes have been changed, then based on the updated number of the lane output from the lane monitoring unit 15, the lane determining unit 17 determines that the lane having the corresponding number is the lane.When the estimation result by the lane estimation unit 14 and the determination result by the lane monitoring unit 15 are different from each other, the lane determination unit 17 preferably uses the estimation result of the lane estimation unit 14 when the lane probability obtained by the lane estimation unit 14 exceeds a predetermined threshold value. When the lane probability obtained by the lane estimating unit 14 is less than the predetermined threshold value, the lane determining unit 7 preferably uses the determination result of the lane monitoring unit 15.FIG. 2 is a block diagram showing a hardware configuration of the lane determination device 1 in the first embodiment of the present invention. As shown in FIG. 2, the lane determination device 1 is configured by including at least a processing circuit 21, a memory 22, and an input / output interface 23.The map database 11, the current position acquisition unit 12, the white line information acquisition unit 13, and the line information storage unit 16 shown in FIG. 1 described above are connected to the input / output interface 23. In FIG. 1, such a configuration is adopted in which the map database 11, the current position acquisition unit 12, the device line information acquisition unit 13, and the white line information storage unit 16 are arranged in the lane determination device 1; however, such a configuration may be adopted in which these pieces of hardware are externally attached to the lane determination device 1.Respective functions of the lane estimating unit 14, the lane monitoring unit 15, and the lane determining unit 17 in the lane determining device 1 are realized by the processing circuit 21. That is, the lane irradiation device 1 includes the processing circuit 21 for estimating the lane by the lane estimation unit 14, monitoring the lane by the lane monitoring unit 15, and determining the lane by the lane determination unit 17. the processing circuit 21 is a CPU (Central Processing Unit: also as a central processing device, processing devices, operation device, microprocessor, microcomputer, processor, DSP (Digital Signal Processor)) that executes a program stored in the memory 22.The functions of the lane estimation unit 14, the lane monitoring unit 15, and the lane determination unit 7 are realized by software, firmware, or a combination of the software and the firmware. The software and the firmware are described as programs and are stored in the memory 22.The processing circuit 21 reads out and executes the programs stored in the memory 22, thereby realizing the functions of the respective sections of the lane estimating unit 14, the lane monitoring unit 15, and the lane determining unit 17. That is, the lane determination device 1 includes the memory 22 for storing such programs in which, at a time point when they are executed by the processing circuit 21, a step of estimating the lane by the lane estimation unit 14, a step of monitoring the lane by the lane monitoring unit 15, and a step of determining the lane by the lane determination unit 14 are thus executed.Moreover, these programs may be assumed to be those that cause a computer to execute a method and procedure for processing that are executed by the lane estimating unit 14, the lane monitoring unit 15, and the lane determining unit 7.Here, as the memory 22, for example, nonvolatile or volatile semiconductor memory such as a RAM (random access memory), a ROM (read only memory), a flash memory, an EPROM (erasable programmable read only memory), and an EEPROM (electrically erasable programmable read only memory), and additionally, a magnetic disk, a flexible disk, an optical disk, a compact disk, a mini disk, a DVD (digital versatile disk), and the like can be adopted.By using FIGS. 3 to 9, a description will be given of a mood operation for the driving lane by the driving lane determination device 1 of this embodiment. FIG. 3 is a view showing an example of a white line information detectability region 30 by the white line information acquisition unit 13. In FIG. 3, the white line information detectability region 30 on the front side in the traveling direction of the vehicle 31 is represented by a viewing angle θ of the front camera constituting the white line information acquisition unit 13. The front camera is configured to be suitable for adjusting the viewing angle θ arbitrarily in response to a lane width of the road and the like.The white line information acquisition unit 13 may acquire white line information about white lines present within such a detectability region 30. Specifically, as shown in FIG. 3, the white line information acquisition unit 13 may acquire white line information about a solid white line 32 on a left side in a forward direction in the traveling direction of the vehicle 31 and a broken line 34 adjacent to a right side thereof and a solid white line 33 on a right side in a direction in the traveling direction of the vehicle 31 and a broken white line 35 adjacent to a left side thereof.The detectability range 30 of the white line information is not limited to the viewing angle θ of the front camera and can be represented by other parameters. For example, the detectability region 30 may represent white line information by a viewing angle of the rear camera constituting the white line information acquisition unit 13, or may be represented by the detectable region of a sensor constituting the white line information acquisition unit 13, or may be represented by a region obtained by adding these to each other.FIG. 4 is a view showing an example of a relationship between positions of vehicles and white lines. FIG. 4 shows a case where vehicles 41 to 43 travel respective lanes on a three-lane road. Here, a traveling direction of the vehicles 41 to 43 is determined as an upward direction on a paper surface of FIG. 4, and FIG. 3 lanes constituting the three-lane road shown in FIG. 4 are determined as a 1st lane, a 2nd lane, and a 3rd lane in an order from the left side in a direction in the traveling direction of the vehicles 41 to 43. moreover, 4 white lines separating the respective lanes are determined as a 1st white line 32, a 2nd white line 34, a 3rd white line 35, and a 4th white line 33 in an order from the left side in the direction of the traveling directions of the vehicles 41 to 43. At this time, the 1st white line 32 and the 4th white line 33 are road boundary lines, as solid white lines. The 2nd white line 34 and the 3rd white line 35, which are lane edge lines, are formed as broken white lines.In the case of the vehicle 41 indicated with a symbol "A" and traveling on the 1st lane, a left white line thereof is the solid 1st white line 32 and a right white line thereof is the broken 2nd white line 34. In the case of the vehicle 42 indicated with a symbol "B" and traveling on the 2nd lane, a left white line thereof is the broken 2nd white line 34 and a right white line thereof is the broken 3rd white line 35.As described above, when the white lines 34 and 35 serving as the lane boundary lines are formed of such broken lines, the line types of the left white line and the right white line change corresponding to the lanes on which the vehicles 41 to 43 travel. Thus, the lane determination unit 17 can determine the lane by using the relationship between the lane and the line types of the left white line and the right white line.FIG. 5 is a view showing another example of the relationship between the positions of the vehicles and the white lines. FIG. 5 shows a case where the white lines 36 and 37 serving as lane boundary lines are formed of solid lines. Also in FIG. 5, it is assumed that the road is a three-lane road around which vehicles 44 to 46 travel on respective lanes.Moreover, a traveling direction of the vehicles 44 to 46 is determined as an upward direction on a paper surface of FIG. 5, and 3 lanes constituting the three-lane road shown in FIG. 5 are determined as a 1st lane, a 2nd lane, and a 3rd lane, in an order from the left side toward the traveling directions of the vehicles 44 to 46. moreover, 4 white lines sharing the respective lanes are determined as the 1st white line 32, a 2nd white line 36, a 3rd white line 37, and the 4th white line 33, in an order from the left side toward the traveling directions of the vehicles 44 to 46.In the example shown in FIG. 5, the 1st white line 32 and the 4th white line 33, which are roads outside lines, are formed of solid white lines in a similar manner to the above-described case shown in FIG. 4. In the example shown in FIG. 5, the 2nd white line 36 and the 3rd white line 37, which are lane boundary lines, are formed of broken white lines.In the example shown in FIG. 5, in the case of the vehicle 44 which is denoted by a symbol "D" and travels on the 1st lane, a left white line thereof and a right white line thereof are the white lines 32 and 36 which are solid lines, respectively. Also in the case of the vehicle 45 indicated with a symbol "E" and traveling on the 2nd lane, similarly, a left white line thereof and a right white line thereof are the white lines 36 and 37 which are solid lines, respectively. Also in the case of the vehicle 46 which is indicated with a symbol "F" and travels on the 3rd lane, similarly, a left white line thereof and a right white line thereof are the white lines 37 and 33, which are solid lines, respectively.As described above, when the white lines 3 36 7 serving as the lane boundary lines are formed by such solid lines, the line types of the left white line and the right white line are identical for all the lanes. Thus, the lane determination unit 17 cannot determine the lane even when the relationship between the lane and the line types of the left white line and the right white line is used. In this case, the lane may be determined by using another method described later in combination.FIG. 6 is a view showing an example of a relationship between the positions of the vehicles and the white lines when a lane change occurs. FIG. 6 shows an example of crossing of the vehicles occurring when a road similar to the three-lane road shown in FIG. 4 is branched from the center.Here, a case is assumed in which a vehicle 31 a, which is denoted by the symbol "A" and travels on the 1st lane, changes the lane from the 1st lane to a lane branching to the left side in the traveling direction. At a position of the vehicle 31 aacsigned with the symbol "A", a left white line thereof is the solid 1st white line 32 and a right white line thereof is the broken 2nd white line 34. Moreover, at the position of the vehicle 31 bsignified with the symbol "B" above, there occurs a state in which the vehicle 31 bcrosses a broken white line 52 extending from the 1st white line 13 2 and sharing the 1st lane and a line branching from the 1st lane, and then the vehicle 31 bis positioned on the subject white line 52.At a position of a vehicle 31 c, denoted by the symbol "C", which is a position at a phase where the vehicle continues whiter and the lane change is completed, both a left white line thereof and a right white line thereof are the solid white lines 51 that share the lane branching from the 1st lane.As described above, when the lane is changed from the 1st lane to the left side in the turn-direction branching lanes, the crossing of the left white line occurs and the detection positions of the left white line and the right white line change. Thus, the lane monitoring unit 14 can determine whether or not the lane change has been performed by monitoring changes of the left white line and the right white line.Moreover, a case is considered in which a vehicle 31 d, which is denoted by the symbol "D" and travels on the 2nd lane, changes the lane to the 3rd lane as a right lane thereof. At a position of the vehicle 31 dsignified with the symbol "D", a left white line thereof and a right white line thereof become the white lines 34 and 35 which are broken lines, respectively. At the position of a vehicle 31 enoted with the symbol "E", which is a position at the center of lane change, a right white line thereof is the solid white line 33 that divides the 3rd lane as a right lane thereof. Moreover, at the position of the vehicle 31 esignified with the symbol "E", a state occurs in which the vehicle 31 eis crossed over the broken white line 35 sharing the 2nd lane and the 3rd lane, and then the vehicle 31 eis positioned on the white line 35 concerned.At a position of a vehicle 31 fnot denoted by the symbol "F", which is a position of a phase at which the vehicle continues to travel and the lane change is completed, a left white line thereof is the broken white line 35 that divides the 3rd lane, and a right white line thereof is the solid white line 33 that divides the 3rd lane.As described above, when the lane is changed from the 2nd lane to the 3rd lane as the right lane, the crossing of the right white line occurs and the line types of the left white line and the right white line change. Thus, the lane monitoring unit 15 can determine whether or not the lane change has been performed by monitoring changes of the left white line and the right white line.FIG. 7 is a view showing an example of such white line detection positions. The white line information acquired by the white line information acquisition unit 13 is represented such that a center position of the vehicle 31 is taken as an origin, that is taken forward in the traveling direction as positive in a Y axis direction, and that is taken rightward in the traveling direction as positive in an X axis direction.As shown in FIG. 7, when the vehicle 31 is traveling on the 2nd lane in the center of the road formed of 3 lanes, the 2nd white line 34, which is the left white line on the left side in the direction of the traveling direction, between the 2nd white lines 34 and 35 sharing the 2nd lane is detected as the traveling lane at a position p 11. The 3rd white line 35 which is the right white line on the right side in the direction of the traveling direction is detected at a position pR.The 1st white line 32 sharing the 1st lane adjacent to the left side of the 2nd lane is further detected at a position pLL on the left side of the detection position pL of the 2nd white line 34. The 4th lane 33 sharing the 3rd lane adjacent to the right side of the 2nd lane is further detected at a position pRR on the right side of the detection position pR of the 3rd white line 35.FIG. 8 is a view showing an example of the detection positions of the white lines changed by the lane crossing. In a similar manner to the vehicle 31 shown in FIG. 7, a case is considered in which the vehicle 31 dreferenced with the symbol "D" performs the lane change to the 3rd lane as the right lane from the traveling state on the 2nd lane and moves to the position of the vehicle 31 freferenced with the symbol "F". In this case, the left white line detection position pL of the vehicle 31, the right white line detection position pR thereof, the left white line detection position pLL on the left adjacent lane, and the right white line detection position pRR of the right adjacent lane change.Thus, the lane monitoring unit 15 monitors the detection positions pL and pR of the left white line and the right white line sharing the lane, and changes over time of the detection positions pLL and pRR of the left white line and the right white line sharing the adjacent lanes can thereby detect the change of the lanes.FIG. 9 is a graph showing the time variation of the detection positions of the white lines. In FIG. 9, an axis of abscess indicates a time T [×0.1 seconds] and an axis of ordinate indicates a position variation Δ(t) [m], which is a difference obtained by subtracting a detection position of the white line at a time t- 1 from a detection position of the white line at a time t. In FIG. 9, such a position variation Δ(t) of the left white line on the left side in the direction of the traveling direction of the vehicle is represented by a line denoted by reference numeral "61", and such a position variation Δ(t) of the right white line on the right side in the direction of the traveling direction of the vehicle is represented by a line denoted by reference numeral "62".As shown in FIG. 9, in the positions denoted by reference numerals "63" and "64", both the left white line variation position 61 and the right white line variation position 62 assume negative values. As shown in FIG. 7, with respect to each of the left white line position pL and the right white line position pR, the right side in the direction of the traveling direction Y is taken as the positive direction of the X axis, and accordingly, the position variation Δ(t) is negative, meaning that the left white line position pL and the right white line position pR have changed in the left direction. Thus, it is seen that the lane change to the left lane was carried out at the positions indicated by reference numerals "63" and "64".Moreover, in the positions denoted by reference numerals "65" and "Sek 6", both the left white line variation position 61 and the right white line variation position 62 take positive values. As shown in FIG. 7, with respect to the left white line position pL and the right white line position pR, the right side in the direction of the traveling direction Y is taken as the positive direction of the X axis, and accordingly, it means that the position variation Δ(t) is positive, that the left white line position pL and the right white line position pR have changed in the right direction. Thus, it is seen that the lane change to the right lane is carried out at the positions denoted by reference numerals "65" and "66".FIGS. 10 to 12 are tables showing an example of lane probability lists for use in the lane estimation unit 14. FIG. 10 is a table showing an example of a lane probability 10 list on a road having 2 lanes. FIG. 11 is a table showing an example of a lane probability list on a 3-lane road. FIG. 12 is a table showing an example of a lane probability list on a 4-lane road. The lane probability lists are tables for estimating the lane in which lane probabilities of the respective lanes belonging to the left white line line types and the right white line line types are obtained for each number of lanes. In FIGS. 10 to 12, for each of the line types of the left white lines and the right white lines, the lane probabilities of the respective lanes constituting the road are shown.In FIG. 10, 2 lanes are taken as the 1st lane and the 2nd lane in order from the left side toward the traveling direction of the vehicle. In each column in FIG. 10, the lane probability Pω1of the 1st lane and the lane probability Pω2of the 2nd lane are represented as "(Pω1, Pω2)".In FIG. 11, 3 lanes are taken as the 1st lane, the 2nd lane, and the 3rd lane in order from the left side toward the traveling direction of the vehicle. In each column in FIG. 11, the lane probability Pω1of the 1st lane, the lane probability Pω2of the 2nd lane, and the lane probability Pω3of the 3rd lane are represented as "(Pω1, Pω2, Pω3)".In FIG. 12, 4 lanes are taken as the 1st lane, the 2nd lane, the 3rd lane, and a 4th lane in order from the left side toward the traveling direction of the vehicle. In each column in FIG. 12, the lane probability Pω1of the 1st lane, the lane probability Pω2of the 2nd lane, the lane probability Pω3of the 3rd lane, and a lane probability Pω4of the 4th lane are represented as "(Pω1, Pω2, Pω3, Pω4)".The lane estimation unit 14 may estimate the lane by using the lane probability lists shown in FIGS. 10 to 12, for example. The lane probability list is stored in the map database 11. In this embodiment, the lane probabilities are determined in advance, but this is not limited thereto. For example, the lane estimation unit 14 may update each of the lane probabilities stored in the map database 11 by learning, or an external device may update the lane probabilities stored in the map database 11 via communication.FIG. 13 is a table showing another example of the lane probability list for use in the lane estimating unit 14. FIG. 13 shows an example of the lane probabilities of the respective lanes which are obtained based on whether or not there is an adjacent lane. FIG. 13 shows the lane probabilities in the cases of 2 lanes, 3 lanes and 4 lanes. In FIG. 13, a track width of the left track is indicated by a symbol "WL", a track width of the right track is indicated by a symbol "WR", and a prescribed width is indicated as a predetermined track width by a symbol "W 0".For example, a case is considered in which the track width WL of the left track is substantially smaller than the prescribed width W 0 (WL<W 0), and the track width WR of the right track is substantially equal to the prescribed width W 0 (WR≈W 0). In this case, when the number of lanes is 3, that is, when the road 3 has lanes, it is assumed that no lane is on the left side of the lane and that a lane is on the right side of the lane. Thus, the lane probabilities of the respective lanes are set to a probability Pb=(0.5, 0.3, 0.2), for example, as shown in FIG. 13. That is, the lane probability Pb 1 of the 1st lane is set to 0.5, the lane probability Pb 2 of the 2nd lane is set to 0.3, and the lane probability Pb 3 of the 3rd lane is set to 0.2.When the track width WL of the left track is substantially smaller than the prescribed width W 0 (WL<<W 0) and the track width WR of the right track is substantially smaller than the prescribed width W 0 (WR<<W 0) when the track width WL of the left track is substantially equal to the prescribed width W 0 (WL≈W 0) and the track width WR of the right track is substantially smaller than the prescribed width W 0 (WR<W 0), and, When the lane width WL of the left lane is substantially equal to the prescribed width W 0 (WL≈W 0) and the lane width WR of the right lane is substantially equal to the prescribed width W 0 (WR≈W 0), the lane probabilities of the respective lanes are set as shown in FIG. 13, respectively.The lane estimating unit 14 may estimate the lane by using the lane probability list shown in FIG. 13, for example. The lane probability list is stored in the map database 11. The lane probabilities are those determined in advance in this embodiment, but they may be updated by learning or may be updated via communication.FIG. 14 is a flowchart showing a processing method related to lane change determination processing in the lane determination device 1 of the first embodiment of the present invention. Respective processes of the flowchart shown in FIG. 14 are executed by the white line information acquisition unit 13 and the lane monitoring unit 15. The flowchart shown in FIG. 14 is started when a power supply of the lane determination device 1 is turned on or is started every predetermined cycle, and the processing proceeds to step a 1.In step a 1, the white line information acquisition unit 13 acquires the white line information. When the process of step a 1 is finished, the processing proceeds to step a 2.In step a 2, the lane monitoring unit 15 calculates the lane width from the white line information acquired in step a 1. When the process of step a 2 is finished, the processing proceeds to step a 3.In step a 3, the lane monitoring unit 15 stores the white line information acquired in step a 1 and the lane width information indicating the lane width calculated in step a 2 in the white line information storage unit 16.In step a 4, the lane monitoring unit 15 identifies irregular white line information. Details of the process of step a 4 will be described later. When the process of step a 4 is finished, the processing proceeds to step a 5.In step a 5, the lane monitoring unit 15 determines whether or not the vehicle has crossed the left white line. When it is determined that the vehicle has crossed the left white line, the processing proceeds to step a 6, and when it is determined that the vehicle has not crossed the left white line, the processing proceeds to step a 7.In step a 6, the lane monitoring unit 15 determines that the vehicle has moved to the left lane. When the process in step a 6 is finished, the processing proceeds to step a 10.In step a 7, the lane monitoring unit 15 determines whether the vehicle has crossed the right white line. When it is determined that the vehicle has crossed the right white line, the processing proceeds to step a 8, and when it is determined that the vehicle has not crossed the right white line, the processing proceeds to step a 9.In step a 8, the lane monitoring unit 15 determines that the vehicle has moved to the right lane. When the processing in step a 8 is finished, the processing proceeds to step a 10.In step a 9, the lane monitoring unit 15 determines that the vehicle has not changed the lane. When the process in step a 9 is finished, the processing proceeds to step a 10.In step a 10, the lane monitoring unit 15 notifies the lane determination unit 17 of a determination result in step a 6, step a 8, or step a 9. When the process in step a 10 is finished, the entire processing method of FIG. 14 is finished.Specifically, the determinations in step a6 to step a9 as to whether or not the vehicle has crossed the white lines and whether or not the vehicle has changed the lane are carried out as follows.In step a6, it is determined from time series data of the left white line whether or not the vehicle has crossed the left white line. The position pL of the left white line is detected to be shifted by about one half of the lane width W 0 during normal travel. The center of the vehicle is a zero point, and accordingly, when the center portion of the vehicle crosses the white line, the position of the detected white line changes.When the vehicle moves to the right lane, the white line seen on the right side is seen on the left side, and the white line seen on the right side of the right adjacent lane is seen on the right side of the vehicle. When the vehicle moves to the left lane, the white line seen on the right side is seen on the right adjacent lane, and the white line seen on the left side is seen on the right side. In this way, it can be determined whether or not the track is changed, and the direction of the track change can be determined.The position variation Δ(t), which is a difference between the left white line detection position X=pL (t-1) at a time t-1 and the left white line detection position X=pL (t) at a time t, can be represented as in Equation (1) below. [Equation 1]If the position variation Δ(t) is within a range of the prescribed width W 0±a permissible error α, the prescribed width W 0 being a predetermined track width, then it is determined that the track is changed, and if the position variation Δ(t) is outside the range, then it is determined that the position variation Δ(t) is within a range of a sampling error, and is not treated as the track change. Moreover, for the α of the prescribed width, W0±α, 2α, 3α, and the like can be set, and the position variation Δ(t) can be calculated as the intersection probabilities P_links as in Equations (2) to (5) below. [Equation 2] [Equation 3] [Equation 4] [Equation 5]These do not necessarily occur simultaneously on the left and right white lines, and accordingly, these are determined within a predetermined time. Weights are assigned to the calculated probabilities based on quality information of the white lines, thereby estimating the driving lane. If it can be determined that both the left and the bright lines are crossed, in step a5 and in step a6, it is determined that the track is changed. The position variation calculated by the probabilities is determined that the track is changed when a product of P_links and P_rechts exceeds a predetermined threshold.FIGS. 15 and 16 are flowcharts showing a processing method related to lane estimation processing in the lane determination device 1 of the first embodiment of the present invention. Respective processes of the flowchart shown in FIGS. 15 and 16 are executed by the current position acquisition unit 12, the white line information acquisition unit 13, and the lane estimation unit 14. The flowchart shown in FIGS. 15 and 16 is started when a power supply of the lane determination device 1 is turned on, or is started every predetermined cycle, and the processing proceeds to step b 1.In step b 1, the current position acquisition unit 12 acquires the current position information. When the process in step b 1 is finished, the processing proceeds to step b 2.In step b 2, the lane estimation unit 14 determines whether or not the road link has changed. When it is determined that the road link has changed, the processing proceeds to step b 3, and when it is determined that the road link has not changed, the processing proceeds to step b 5.In step b 3, the lane estimation unit 14 performs a number-of-lane information acquisition operation of the changed road link. When the process in step b 3 is finished, the processing proceeds to step b 4.In step b 4, the lane estimating unit 14 determines whether the number-of-lanes information could be acquired. When it is determined that the number-of-lanes information could be acquired, the processing proceeds to step b 5, and when it is determined that the number-of-lanes information could not be acquired, the processing proceeds to step b 7.In step b 5, the white line information acquisition unit 13 acquires the white line information. When the process in step b 5 is finished, the processing proceeds to step b 6.In step b 6, the lane estimation unit 14 calculates the lane width from the white litial information acquired in step b 5. When the process in step b 6 is finished, the processing proceeds to step b 10 of FIG. 16.In step b 7, the white line information acquisition unit 13 acquires white line information. When the process in step b 7 is finished, the processing proceeds to step b 8.In step b 8, the lane estimation unit 14 calculates the lane width from the white line information acquired in step b 7. When the process in step b 8 is finished, the processing proceeds to step b 9.In step b 9, the lane estimation unit 14 estimates the number of lanes of the changed road link. When the process in step b 9 is finished, the processing proceeds to step b 10 of FIG. 16.In step b 10 of FIG. 16, the lane estimation unit 14 obtains the lane probability of each lane from the line types of the left white line and the right white line. When the process in step b 10 is finished, the processing proceeds to step b 11.In step b 11, the lane estimation unit 14 obtains a lane probability of each lane from the lane width of the adjacent lane. When the process in step b 11 is finished, the processing proceeds to step b 12.In step b 12, the lane estimation unit 14 estimates the lane from the lane probability of each lane. When the process in step b 12 is finished, the processing proceeds to step b 13.In step b 13, the lane estimation unit 14 notifies the lane determination unit of a 7 estimation result. When the process in step b 13 is finished, all the processing methods of FIGS. 15 and 16 are finished.Specifically, the estimation of the driving lane in step b 12 is performed as follows. By using the lane probabilities calculated in step b10 and step b11, probability weighting is applied to the lane in which the vehicle has traveled until immediately before, and estimation of the lane is thus performed. In this embodiment, the lane is stochastically determined by the Bayesian estimation.A probability P(XIHk) is calculated from the following equation (6) by synthesizing with each other a line type probability P1(X) of the left white line and the right white line, a number-of-lanes probability P2(X) corresponding to whether or not the left and right lanes are present, and a lane probability P3(X) predicted from the predetermined lane and a lane change. [Equation 6]In Equation (6), α is a parameter dynamically changed based on reliability of camera scan data, whether or not an irregular value is present and whether or not an accurate map is present, and β is a weighting parameter to a history.For a previous probability P(HK), a standard value thereof is set to a uniform distribution between the respective tracks, and values thereof are set at a 2nd time and thereafter to P(HkIX) calculated from previous probabilities. The standard value is set to the uniform distribution with respect to the number of lanes, and accordingly, if the road has 3 lanes, the previous probability is shown in the following equation (7). [Equation 7]With respect to the later probability P(Hk|X) of the driving lane (event Hk, k=1, 2,3,..., n (n is the number of lanes)), if a lane predicted from a current camera occurs (event X), the later probability P(Hk|X) is calculated from the probability P(XIHk) of the event X and the previous probability P(Hk) by using the Bayesian estimation equation shown in the following equation (8). [Equation 8]It is determined that k is such a lane Ln(t) at a maximum later probability P(Hk|X), and at a time when the probability exceeds a threshold, it is determined that the vehicle is traveling on the lane, and the processing of the lane monitoring unit 15 is started.If it is determined that the lane change has occurred, the lane monitoring 101 5 resets the later probability P(HkIX) and the probability P(XIHk), that is, a variable i in the equation (8) is set to 0 (i=0), thereby recalculating a later probability P(Hk|X) of the lane based on a currently observed value.Moreover, the lane monitoring unit 15 resets the later probability P(HkIX) and the probability P(XIHk) also in the cases (1) to (7) below.(1) Lane change(2) Turn right and left(3) Time of branching / merging and entering a connection(4) Timing when Number of Tracks Increases / Decreases(5) when a number of tracks become known from unknown(6) when a number of tracks become known(7) a timing when a change is made between a road and outside a roadWhen the number of lanes on such a travel road is changed, an assignment of the lane number is changed, and accordingly, the lane number of the lane on which the vehicle travels is also updated. For example, as the number of lanes increases by one lane on the left, then the lane number is increased by 1, and as the number of lanes increases by one lane on the right, then the lane is left as it is.FIG. 17 is a flowchart showing a processing method related to identification processing for the irregular white line information in the lane determination device 1 of the first embodiment of the present invention. Respective processes of the flowchart shown in FIG. 17 are executed by the lane monitoring unit 15. The flowchart shown in FIG. 17 is started when the power supply of the lane determination device 1 is turned on, or is started every predetermined cycle, and the processing proceeds to step c 1.In step c 1, the lane monitoring unit 15 determines whether a difference between the lane width and the predetermined width exceeds an allowable range. When it is determined that the difference between the track width and the prescribed width exceeds the allowable range, the processing proceeds to step c 6, and when it is determined that the difference between the track width and the prescribed width does not exceed the allowable range, the processing proceeds to step c 2.In step c 2, the lane monitoring unit 15 calculates an average value within a predetermined time for each piece of information obtained from the white line information. When the process in step c 2 is finished, the processing proceeds to step c 2.In step c 3, the lane monitoring unit 15 determines whether the difference between the average value and a detected value exceeds the allowable range in any piece of information. When it is determined that the difference between the average value and the detected value of the allowable range in one piece of information exceeds, the processing proceeds to step c 6, and when it is determined that the difference between the average value and the detected value does not exceed the allowable range in any piece of information, the processing proceeds to step c 4.In step c 4, the lane monitoring unit 15 determines whether a difference between the currently detected value and the previously detected value exceeds an allowable range. When it is determined that the difference between the currently detected value and the previously detected value exceeds the allowable range, then the processing proceeds to step c 6, and when it is determined that the difference between the currently detected value and the previously detected value does not exceed the allowable ranges, then the processing proceeds to step c 5.In step c 5, the lane monitoring unit 15 determines whether the currently detected value is the same as an initial setting value. When it is determined that the currently detected value is the same as the initial set value, the processing proceeds to step c 6, and when it is determined that the currently detected value is not the same as the initial set value, the entire processing procedure in FIG. 17 is ended.In step c 6, the lane monitoring unit 15 determines that the white line information is irregular. When the process in step c 6 is finished, the processing proceeds to step c 7.In step c 7, the lane monitoring unit 15 performs setting so that the white line information irregularly determined in step c 6 is unable to be used. When the process in step c 7 is finished, the entire processing procedure of FIG. 17 is finished.As described above, according to this embodiment, by the lane estimating unit 14, the lane is estimated based on the lane probability of each of the lanes obtained based on the line type of the white line, the lane probability of each of the lanes obtained based on whether or not the adjacent lane exists, and the lane probability of each of the lanes obtained based on the lane on which the vehicle has traveled when the lane has been previously estimated. In this way, the lane can be estimated with good accuracy. Moreover, when the detection accuracy for the white line is relatively low, the driving lane can be estimated by using any driving lane probability from the above-mentioned driving lane probabilities, and accordingly estimation with relatively high stability can be performed. Thus, the driving lane of the vehicle can be stably determined.Moreover, in this embodiment, when the number of lanes information cannot be acquired from the map information, the lane estimating unit 14 estimates the number of lanes based on the lane probability of each of the lanes obtained based on whether or not the adjacent lane exists and based on the number of times the vehicle changes the lane, and estimates the lane based on the estimated number of lanes. In this way, even if the number-of-lanes information cannot be acquired from the map information, the lane can be estimated.Moreover, in this embodiment, when the same white line information is continuously acquired by the white line information acquisition unit 13, the lane estimation unit 14 estimates the lane based on the lane probability of each of the lanes obtained based on whether or not the adjacent lane exists and based on the lane probability of each of the lanes obtained based on the lane the vehicle has traveled when the lane has been previously estimated. That is, when the same white line information is continuously acquired by the white line information acquisition unit 13, the lane estimation unit 14 predicts that the state is temporarily irregular, and estimates the lane without using the lane probability based on the white line information acquired by the white line information acquisition unit 13. In this way, the lane can be estimated with higher accuracy.Moreover, in this embodiment, when the lane probability of another lane exceeds the predetermined threshold after the lane is estimated, the lane estimating unit 14 updates the lane to the above-mentioned other lane. In this way, the lane can be estimated with higher accuracy.Moreover, in this embodiment, when it is determined that the white line has been crossed from the time change of the white line information acquired by the white line information acquisition unit 13, the lane estimation unit 14 estimates the lane again. In this way, such estimation accuracy for the driving lane can be improved. Moreover, the estimation accuracy of the traveling lane can be maintained.Moreover, in this embodiment, based on the lane width of each of the lanes predicted from the white line information, the line type of the white line thereof, and the surrounding vehicle information, the lane estimating unit 14 predicts whether or not the adjacent lane exists, and based on a result of the prediction, obtains the lane probability of each of the lanes obtained based on whether or not the adjacent lane exists. In this way, such estimation accuracy for the driving lane can be improved.Moreover, in this embodiment, when the number of times the lane that is changed acquired from the white line information is larger than the number of lanes that is obtained from the map information, the lane estimating unit 14 determines that the map information is wrong, and estimates the lane. In this way, even if the map information is wrong, the lane can be estimated with high accuracy.< Embodiment>FIG. 18 is a block diagram showing a configuration of a lane determination device 2 in a second embodiment of the present invention. The lane determination device 2 of this embodiment includes the same elements as those of the lane determination device 1 of the first embodiment, and accordingly, the same reference numerals are assigned to the same elements, and a common description is omitted.In a similar manner to the first embodiment, the lane determination device 2 of this embodiment is configured to be mounted on a vehicle such as an automobile. Moreover, in this embodiment, the lane determination device 2 is realized by a navigation device having a navigation function for route guidance. A lane determination method of another embodiment of the present invention is executed by the lane determination device 2 of this embodiment.The lane determination device 2 is further configured to include a shift amount determination unit 71 and a map matching unit 72 in addition to the configuration of the lane determination device 1 of the first embodiment. That is, the lane determination device 2 is still configured including the map database 11, the current position acquisition unit 12, the white line information acquisition unit 13, the lane estimation unit 14, the lane monitoring unit 15, the white line information storage unit 16, the lane determination unit 17, the shift amount determination unit 71, and the map matching unit 72.The displacement amount determination unit 71 is constituted of, for example, a gyroscope sensor, a vehicle speed sensor, an acceleration sensor, and a magnetic sensor. The displacement amount determination unit 71 calculates a displacement amount of the vehicle based on information detected by the gyroscope sensor, the vehicle speed sensor, the acceleration sensor, and the magnetic sensor by using a method called self / independent navigation or healing (dead reckoning) method. Specifically, the displacement amount determination unit 71 calculates a distance and a direction in which the vehicle has moved as a displacement amount of the vehicle.The displacement amount determination unit 71 gives displacement amount information indicating the calculated displacement amount of the vehicle, for example, the distance and the direction in which the vehicle has moved, to the map matching unit 72. The displacement amount determination unit 71 may calculate the displacement amount of the vehicle as, for example, the distance and the direction in which the vehicle has moved from the camera, the laser radar, or the like.The map matching unit 72 determines the position of the vehicle on the map based on the map information, based on the lane information indicating the lane and output from the lane determination unit 17, and based on the shift amount information output from the shift amount determination unit 71. Specifically, the map matching unit 72 determines which lane of a real road on the map included in the map information read from the map database 11 the vehicle is straight.A hardware configuration of the lane determination device 2 in this embodiment is similar to the hardware configuration of the lane determination device 1 shown in FIG. 2, and accordingly, illustration and common description are omitted. In a similar manner to the lane determination apparatus 1 shown in FIG. 2, the lane determination apparatus 2 is still configured to include at least a processing circuit, a memory, and an input / output interface.Respective functions of the displacement amount determination unit 71 and the map matching unit 72 in the lane determination device 2 are realized by the processing circuitry. That is, the lane determination device 2 includes the processing circuit for determining the displacement amount of the vehicle by the displacement amount determination unit 71 and determining the position of the vehicle on the map based on the map information based on the lane information and the displacement amount information by the map matching unit 72.The functions of the displacement amount determination unit 72 and the map matching unit 72 in the lane determination device 2 are realized by software, firmware, or a combination of the software and firmware. The software, the firmware, is described as programs and stored in the memory.The processing circuit reads out and executes the programs stored in the memory, thereby realizing the functions of the respective sections of the displacement amount determination unit 71 and the map matching unit 72. That is, the lane determination device 2 includes the memory for storing such a program at which, at a time point when executed by the processing circuit, in the step of determining the displacement amount of the vehicle by the displacement amount determination unit 71 and a step of determining the position of the vehicle on the map based on the map information based on the lane information and the displacement amount information by the map matching unit 72 are thus executed.Moreover, this program may also be the one that causes a computer to execute a method and procedure of processing executed by the shift amount determination unit 71 and the map matching unit 72 in the lane determination device 2.FIG. 19 is a flowchart showing a processing method related to such positioning processing in the lane determination device 2 of the second embodiment of the present invention. Respective processes of the flowchart shown in FIG. 19 are executed by the map matching unit 72. The flowchart shown in FIG. 19 is started when the power supply of the lane determination device 2 is turned on, or is started every predetermined cycle, and the processing proceeds to step d 1.In step d 1, the map matching unit 72 acquires the lane information from the lane determination unit 17.In step d 2, the map matching unit 72 acquires the shift amount information from the shift amount determination unit 71.In step d 3, the map matching unit 72 acquires the map information from the map database 11.In step d 4, the map matching unit 72 determines the moving position of the vehicle from the lane information acquired in step d 1, the displacement amount information acquired in step d 2, and the map information acquired in step d 3. When the process in step d 4 is finished, the entire processing method of FIG. 19 is finished.As described above, according to this embodiment, after the travel lane is determined by the travel lane determination unit 17, the vehicle is mapped on the map by the map matching unit 72 while considering the shift amount of the vehicle. In this way, the current position of the vehicle can be determined with relatively high accuracy.< Embodiment>FIG. 20 is a block diagram showing a configuration of a lane determination device 3 in a third embodiment of the present invention. The lane determination device 3 of this embodiment includes the same elements as those of the lane determination device 1 of the first embodiment and the lane determination device 2 of the second embodiment, and accordingly, the same reference numerals are assigned to the same elements, and a common description is omitted.In a similar manner to the first embodiment and the second embodiment, the lane determination device 3 of this embodiment is configured to be mounted on a vehicle such as an automobile. Moreover, in this embodiment, the lane determination device 3 is realized by a navigation device having a navigation function for route guidance. A lane determination method of another embodiment of the present invention is executed by the lane determination device 3 of this embodiment.The lane determination device 3 is further configured by including a feature information acquisition unit 81, a road shape information acquisition unit 82, and a road reference information storage unit 83 in addition to the configuration of the lane determination device 2 of the second embodiment. That is, the lane determination device 3 is configured to include the map database 11, the current position acquisition unit 12, the white line information acquisition unit 13, the lane estimation unit 14, the lane monitoring unit 15, the white line information storage unit 16, the lane determination unit 17, the shift amount determination unit 71, the map matching unit 72, the feature information acquisition unit 81, the road shape information acquisition unit 82, and the road reference information storage unit 83.The feature information acquisition unit 81 is formed of a front camera provided to be capable of detecting a front of the vehicle in the traveling direction, a rear camera provided to be capable of detecting a rear of the vehicle in the traveling direction, and sensors such as reader radars. The feature information acquisition unit 81 acquires feature information on a feature installed on a road such as a sign, a temporary stop line, a pedestrian crossing, and a guardrail on the road on which the vehicle travels. The feature information acquisition unit 81 stores the acquired feature information on the road reference information storage unit 83.The road shape information acquisition unit 82 is configured of sensors such as a gyroscope sensor, an inclination sensor, a laser radar, and a camera. The road shape information acquisition unit 82 acquires road shape information including information indicating a longitudinal gradient (hereinafter referred to as "inclination" in some cases) of the road on which the vehicle is traveling, information indicating a bank (hereinafter referred to as "inclination bank" in some cases) of the road on which the vehicle is traveling, and information indicating a curvature of the curve of the road on which the vehicle is traveling. The road shape information acquisition unit 82 acquires the road shape information in consideration of the inclination and orientation of the vehicle. The road shape information acquisition unit 82 stores the acquired road shape information in the road reference information storage unit 83.The road reference information storage unit 83 is realized by a storage device such as a semiconductor memory. The road reference information storage unit 83 stores the feature information output from the feature information acquisition unit 81 and the road shape information output from the road shape information acquisition unit 82. The road reference information storage unit 83 stores the feature information acquired by the feature information acquisition unit 81 within a predetermined time (hereinafter referred to as a "prescribed time" in some cases) and the road shape information acquired by the road shape information acquisition unit 82 within the predetermined time.A hardware configuration of the lane determination device 3 in this embodiment is similar to the hardware configuration of the lane determination device 1 shown in FIG. 2, and accordingly, illustration and common description are omitted. In a similar manner to the lane determination device 1 shown in FIG. 2, the lane determination device 3 is configured to include at least a processing circuit, a memory, and an input / output interface.Respective functions of the feature information acquisition unit 81 and the road shape information acquisition unit 82 in the lane determination device 3 are realized by the processing circuitry. That is, the lane determination device 3 includes the processing circuit for acquiring the feature information by the feature information acquisition unit 81 and acquiring the road shape information by the road shape information acquisition unit 82.The functions of the information acquisition unit 81 and the road shape information acquisition unit 82 in the lane determination device 3 are realized by software, firmware, or a combination of the software and firmware. The software and company are described as programs and stored in the memory.The processing circuit reads out and executes the programs stored in the memory, thereby realizing the functions of the respective sections of the feature information acquisition unit 81 and the road shape information acquisition unit 82. That is, the lane determination unit 3 includes the memory for storing such a program at a time. In which this is executed by the processing circuit, a step of acquiring the feature information by the feature information acquisition unit 81 and a step of acquiring the road shape information by the road shape information acquisition unit 82 are thus executed.Moreover, this program may also be the one that causes a computer to execute a method and procedure of processing executed by the information acquisition unit 81 and the road shape information acquisition unit 82 in the lane determination device 3.FIG. 21 is a flowchart showing a processing method related to error correction processing in the lane determination device 3 of the third embodiment of the present invention. Respective processes of the flowchart shown in FIG. 21 are executed by the map matching unit 72. The flowchart shown in FIG. 21 is started when the power supply of the lane determination device 3 is turned on, or is started every predetermined cycle, and the processing proceeds to step e 1.In step e 1, the map matching unit 72 acquires the road information from the road reference information storage unit 83.In step e 2, the map matching unit 72 acquires the feature information from the road reference information storage unit 83. when the process in step e 2 is finished, the processing proceeds to step e 3.In step e 3, the map matching unit 72 acquires the map information from the map database 11.In step e 4, from the road shape information acquired in step e 1, the feature information acquired in step e 2, and the map information acquired in step e 3, the map matching unit 72 obtains a positional relationship and a correlation between the detected road shape and a feature and the road shape and the feature based on the map information. When the process in step e 4 is finished, the processing proceeds to step e 5.In step e 5, from the positional relationship and the correlation between the detected road shape and a feature and the road shape and the feature based on the map information, the positional relationship and the correlation obtained in step e 4, the map matching unit 72 calculates an error of a position detected as the current position of the vehicle. When the process in step e 5 is finished, the processing proceeds to step e 6.In step e 6, the map matching unit 72 corrects the current position of the vehicle based on the error calculated in step e 5. When the process in step e6 is finished, the entire processing procedure of Fig. 21 is finished.As described above, according to this embodiment, the error of the position of the vehicle with respect to the traveling direction of the vehicle is determined by the map matching unit 72 based on the correlation between the road shape such as a gradient and a curvature detected by the road shape information detecting unit 82 formed of the sensor and the like and the road shape such as a gradient and a curvature of the road based on the map information and based on the relationship between the position of the feature detected by the feature information detecting unit 81 formed of the sensor and the like and the position of the feature based on the map information. In this way, the current position of the vehicle can be determined with relatively high accuracy.The lane determination devices 1 to 3 of the respective embodiments as described above can be applied not only to the vehicle mountable navigation device but also to a system in which a communication terminal, a server device, and the like are appropriately combined with each other. The communication terminal is, for example, a PND (Portable Navigation Device) or a portable communication device having a function of communicating with the server device. The portable communication device is, for example, a mobile phone, a smartphone, and a tablet-type terminal.When the system is formed by appropriately combining the navigation device, the congregation terminal, and the server device with each other as described above, the elements of each of the lane determination devices 1 to 3 according to the respective embodiments may be dispersedly arranged in the respective devices constituting the system, or may be concentratedly arranged in one of the devices.Regardless of whether the respective elements of each of the lane determination devices 1 to 3 of the embodiments are dispersedly arranged as described above in the respective devices constituting the above-described system or concentratedly arranged as described above in one of the devices, effects similar to those in the above-described respective embodiments can be obtained.The above-described respective embodiments and modification examples thereof are merely illustrations of the present invention, and respective embodiments and modification examples thereof can be freely combined with each other within the scope of the present invention. Moreover, any elements of the respective embodiments and the modification examples may be changed or omitted as appropriate.Although the present invention has been described in detail, the above description is in all aspects illustrative and the present invention is not limited thereto. This is to be understood that numerous modification examples, which are not illustrated, are conceivable without departing from the scope of the present invention.List of reference characters1,2,3 Lane determination device 11 Map database 12 Current position acquisition unit 13 White line information acquisition unit 14 Lane estimation unit 15 Lane monitoring unit 16 White line information storage unit 17 Lane determination unit 21 Processing circuit 22 Memory 23 Input / output interface 31, 31 a, 31 b, 31 c, 31 b, 31 e, 31 f, 41, 42, 43, 44, 45, 46 Vehicle 71 Displacement amount determination unit 72 Map matching unit 81 Feature information acquisition unit 82 Road shape information acquisition unit 83 Road reference information storage unit

Claims

A lane determination device (1, 2, 3) that determines a lane as a lane on which a vehicle travels, from lanes constituting a road, the lane determination device comprising: a map information storage unit (11) for storing map information about a map including the road; a current position acquisition unit (12) for acquiring current position information about a current position of the vehicle; a white line information acquisition unit (13) for acquiring white line information about a white line sharing the road; a white line information storage unit (16) for storing the white line information; a lane estimating unit (14) for estimating the lane on which the vehicle travels based on the map information, the current position information, and the white line information; a lane monitoring unit (15) for monitoring the lane estimated by the lane estimating unit (14); and a lane determining unit (17) for determining the lane based on a result of the estimation by the lane estimating unit (14) and a result of the monitoring by the lane monitoring unit (15); wherein the lane estimating unit (14) calculates a total probability that the vehicle travels on each of the lanes based on a probability that each of the lanes constituting the road is the lane, the probability being obtained based on a line type of the white line, a probability, wherein each of the lanes is the driving lane, the probability is obtained based on whether or not there is a lane adjacent to the current position of the vehicle and a probability that each of the lanes is the driving lane, the probability is obtained based on a lane on which the vehicle has traveled when the driving lane has been previously estimated, and estimates that one of the lanes whose total probability is the largest is the driving lane, and wherein when the number of times the vehicle has changed the lane on which the vehicle has traveled, the number is obtained from the white line information is larger than the number of the lanes, the number is obtained from the map information, the driving lane estimating unit (14) determines that the map information is wrong, and estimating the driving lane.The lane determination device (1 / 2 / 3) according to claim 1, wherein when number-of-lanes information indicating the number of lanes cannot be acquired from the map information, the lane estimation unit (14) estimates the number of lanes based on the probability that each of the lanes is the lane, the probability being obtained based on whether or not the lane adjacent to the lane exists, and the number of times the vehicle has changed the lane on which the vehicle has traveled, which is determined based on the number of times the vehicle has crossed the white line, and estimates the lane based on the estimated number of lanes.The lane determination device (1, 2, 3) according to claim 1, wherein, when the white line information that is identical is continuously acquired by the white line information acquisition unit (13), the lane estimation unit (14) estimates the lane based on the probability that each of the lanes is the lane, the probability being obtained based on whether or not the lane adjacent to the lane is present, and the probability that each of the lanes is the lane, the probability being obtained based on the lane on which the vehicle has traveled when the lane has been previously estimated.The lane determination device (1, 2, 3) according to claim 1, wherein when a probability that a lane other than the lane estimated as the lane is the lane exceeds a predetermined threshold after the lane is estimated, the lane estimation unit (14) updates the lane to this other lane.The lane determination device (1, 2, 3) according to claim 1, wherein when it is determined that the white line is crossed from a temporal change of the white line information acquired by the white line information acquisition unit (13), the lane estimation unit (14) re-estimates the lane.The lane determination device (1, 2, 3) according to claim 1, wherein based on a lane width of each of the lanes predicted from the white line information, the line type of the white line of the lane, and information about vehicles surrounding the vehicle, the lane estimation unit (14) predicts whether or not the adjacent lane exists, and obtains, based on a result of the prediction, a probability that each of the lanes is the lane, the probability being obtained based on whether or not the lane adjacent to the lane exists.The lane determination device (1, 2, 3) according to claim 1, further comprising: a displacement amount determination unit (71) for determining a displacement amount of the vehicle; and a map matching unit (72) for determining, based on lane information indicating the lane determined by the lane determination unit (17) and based on displacement amount information indicating the displacement amount determined by the displacement amount determination unit (71), a position of the vehicle on the map based on the map information.The lane determination apparatus (1, 2, 3) according to claim 7, further comprising: a road shape information acquisition unit (82) for acquiring road shape information on a shape of the road; A feature information acquisition unit (81) for acquiring feature information about a feature installed on the road, wherein the map matching unit (72) corrects an error of a position of the vehicle with respect to a traveling direction of the vehicle, based on a correlation between the shape of the road, the shape being based on the road shape information acquired by the road shape information acquisition unit (82), and a shape of the road, the shape being based on the map information, and based on a relationship between a position of the feature, the position being based on the feature information and acquired by the feature information acquisition unit (81), and a position of the feature, the position being based on the map information.A lane determination method for the lane determination device (1, 2, 3) that determines a lane as a lane on which a vehicle travels from lanes that form a road, the lane determination method comprising: acquiring current position information about a current position of the vehicle by the current position acquisition unit (12) of the lane determination device (1, 2, 3); acquiring white line information about a white line that divides the road by the white line information acquisition unit (13) of the lane determination device (1, 2, 3); estimating the driving lane on which the vehicle is traveling based on map information about a map including the road, the current position information, and the white line information by the driving lane estimating unit (14) of the driving lane determining device (1 / 2 / 3); monitoring the estimated driving lane by the driving lane monitoring unit (15) of the driving lane determining device (1 / 2 / 3); and determining the driving lane based on a result of the estimation and a result of the monitoring by the driving lane determining unit (17) of the driving lane determining device (1 / 2 / 3), wherein at a time of estimating the driving lane, the driving lane estimating unit (14) calculates a total probability that the vehicle is traveling on each of the lanes based on a probability that each of the lanes constituting the road is the driving lane, wherein the probability is obtained based on a line type of the white line, a probability that each of the lanes is the lane, the probability is obtained based on whether or not there is a lane adjacent to the current position of the vehicle, and a probability that each of the lanes is the lane, the probability is obtained based on a lane on which the vehicle has traveled when the lane has been previously estimated, and estimates that one of the lanes whose total probability is the largest is the lane, and wherein when the number of times the vehicle has changed the lane on which the vehicle has traveled, the number is obtained from the white line information is greater than the number of the lanes, the number is obtained from the map information, wherein, the lane estimating unit (14) determines that the map information is wrong and estimates the lane.

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