RU2776105C1 - Method for movement assistance and apparatus for movement assistance - Google Patents

Abstract

FIELD: controlling.

SUBSTANCE: invention relates to a method for movement assistance and an apparatus for movement assistance. Method for movement assistance initiates the sensor to detect the boundary of the lane near the vehicle, calculates the own positions of the vehicle, converts the coordinate system of the detected lane boundary into the coordinate system equivalent to the cartographic data stored in the memory apparatus, in accordance with the own positions. Configuration information of the lane boundary, included in the cartographic data, is then integrated with the lane boundary, the coordinate system whereof was converted, in order to generate integrated data. The integrated range is herein determined when the configuration information is integrated with the lane boundary, the coordinate system whereof was converted, so that the lane boundary includes at least either multiple parts of different curvatures, or multiple differently directed straight parts, and the configuration information correlates with the lane boundary, the coordinate system whereof was converted, in order to generate integrated data, including at least the determined integrated range.

EFFECT: provided movement assistance by comparing the configuration information on the road in the cartographic data with the configuration information on the road detected by a sensor.

21 cl, 14 dwg

Description

FIELD OF TECHNOLOGY

[0001] The present invention relates to a motion assistance method and a motion assistance device.

BACKGROUND OF THE INVENTION

[0002] Patent Document 1 discloses a technique according to which the presence or absence of discrepancy between the measurement information in the real world obtained by the sensor and the map as reference information regarding the environment is determined.

LIST OF CITATIONS

PATENT LITERATURE

[0003] Patent Document 1: Japanese Pending Patent Application Publication No. 2017-181870

SUMMARY OF THE INVENTION

TECHNICAL PROBLEM

[0004] The technique disclosed in Patent Document 1 does not take into account the road configuration in the range in which the measurement information and the map are to be compared. If there are no specific characteristics regarding the road configuration, for example, when the road configuration in the range to be compared includes only a straight shape or a curved shape having a constant curvature, a comparison difference may occur.

[0005] The present invention provides a traffic assistance method and a traffic assistance apparatus capable of properly performing a comparison between the road configuration information in the map data and the road configuration information detected by the sensor.

TECHNICAL SOLUTION

[0006] An aspect of the present invention is a traffic assistance method including detecting a lane boundary in the vicinity of a vehicle, calculating the vehicle's own positions, converting a coordinate system of the detected lane boundary to a coordinate system equivalent to map data stored in a storage device , according to one's own positions, and integrating the lane boundary configuration information included in the map data with the lane boundary whose coordinate system is transformed to generate integrated data, wherein the integrated range is determined when the configuration information is integrated with the lane boundary , whose coordinate system has been transformed such that the lane boundary includes at least either a plurality of parts having different curvatures or a plurality of straight parts directed in different directions, and The configuration information is associated with a lane boundary whose coordinate system has been transformed to generate integrated data while including at least a certain integrated range.

[0008] the Purpose and advantages of the present invention will be realized and achieved using the elements and combinations, in particular set forth in the attached claims. It is to be understood that both the foregoing general description and the following detailed description are illustrative and explanatory and do not limit the present invention as claimed.

BRIEF DESCRIPTION OF THE DRAWINGS

[0009]

[FIG. 1] FIG. 1 is a diagram illustrating an example of a schematic configuration of a driving assistance device according to an embodiment of the present invention.

[FIG. 2] FIG. 2 is an explanatory diagram of an example of matching processing.

[FIG. 3] FIG. 3 is an explanatory diagram of an example of a matching result.

[FIG. 4] FIG. 4 is an explanatory diagram illustrating an example of integrated range determination processing.

[FIG. 5] FIG. 5 is an explanatory diagram illustrating an example of lane forward angle calculation processing.

[FIG. 6] FIG. 6 is an explanatory diagram illustrating an example of lane forward angle calculation processing.

[FIG. 7] FIG. 7 is a graph illustrating the distribution of angles in the forward direction of a lane.

[FIG. 8] FIG. 8 is an explanatory diagram illustrating an example of integrated range determination processing.

[FIG. 9] FIG. 9 is a graph illustrating the distribution of angles in the forward direction of a lane.

[FIG. 10] FIG. 10 is a flowchart illustrating an example of a driving assistance method according to an embodiment of the present invention.

[FIG. 11] FIG. 11 is a flowchart illustrating an example of integrated range determination processing.

[FIG. 12] FIG. 12 is an explanatory diagram illustrating an example of integrated range determination processing.

[FIG. 13] FIG. 13 is an explanatory diagram illustrating an example of integrated range determination processing.

[FIG. 14] FIG. 14 is an explanatory diagram illustrating an example of integrated range determination processing.

DESCRIPTION OF EMBODIMENTS

[0010] An embodiment of the present invention will be described below with reference to the drawings. The same or similar elements mentioned in the following description of the drawings are denoted by the same or similar reference numerals.

[0011] (Drive assist device)

The driving assistance device according to the embodiment of the present invention can be installed on a vehicle (hereinafter, the vehicle on which the driving assistance device according to the embodiment of the present invention is installed is referred to as the “host vehicle”). As shown in FIG. 1, the driving assistance device 1 according to an embodiment of the present invention includes a storage device 2, a global positioning system (GPS) receiver 3 (GPS sensor), a vehicle sensor 4, a peripheral sensor 5, a processing circuit 6, a display 7, a device 8 the vehicle control and the actuator 9. The processing circuit 6 can communicate with the storage device 2, the GPS receiver 3, the vehicle sensor 4, the peripheral sensor 5, the display 7 and the vehicle control device 8 to transmit and receive data and signals via the bus. controller network (CAN), for example, wired or wirelessly.

[0012] The storage device 2 may be, for example, a semiconductor memory, a magnetic memory, or an optical memory. The storage device 2 may be installed in the processing circuit 6 . The storage device 2 includes a map storage unit 10 for storing map data. The driving assistance device 1 according to an embodiment of the present invention integrates map data stored in the map storage unit 10 with point data acquired by the peripheral sensor 5. The map data stored in the map storage unit 10 may be high-resolution map data (hereinafter, simply referred to as "high-resolution map").

[0013] The high resolution map is suitable for autonomous driving. A high-resolution map is map data having a higher resolution than navigation map data (simply referred to as a "navigation map") and includes per-lane information that is more accurate than per-road information. For example, the high-resolution map includes, as information on each lane, lane node information indicating anchor points on a lane reference line (e.g., a center line in a lane) and lane connection information indicating sectional aspects of the lane. traffic between the respective lane nodes. The lane node information includes a corresponding identification number, positional coordinates, a number of lane connections to be connected to, and an identification number of the respective lane connections to be connected to. The lane connection information includes the corresponding identification number, lane type, lane width, lane shape, lane boundary type, lane boundary shape, and lane reference line shape.

[0014] The high-resolution map further includes information about objects on the ground, such as the type and positional coordinates of each object on the ground, including a traffic light, a stop line, a sign, a building, a telegraph pole, a curb, and a pedestrian crossing available in lane or near it, as well as the identification number of each node of the lane and the identification number of each connection of the lane corresponding to the positional coordinates of each object on the ground. Because the high-resolution map includes node and link information for each traffic lane, the traffic lane on the traffic route that the main vehicle is currently traveling on can be accurately determined. The high resolution map includes coordinates indicating the position of each lane in the continuation direction and the width direction. The high-resolution map also includes coordinates indicating the position of an object in 3D space (eg, longitude, latitude, and altitude), and each traffic lane and each object on the ground described above can be indicated by corresponding 3D images.

[0015] The high-resolution map may include point group data about multiple points (boundary points) constituting, for example, a lane boundary. The map data integrated by the driving assistance device 1 with the lane boundary data obtained by the periphery sensor 5 is not necessarily a high-resolution map, and the map data is only required to include point group data of the multiple points constituting the lane boundary.

[0016] The database for the map data can be managed on the server, from outside the driving assistance device 1, and updated delta data for the map data can be obtained via telematics, for example, to update the map data stored in the map storage unit 10. Alternatively, map information may be obtained via telematics, such as vehicle-to-vehicle communication or vehicle-to-road infrastructure communication, depending on the position at which the main vehicle is moving. The use of telematics eliminates the need to store data-intensive mapping data in the main vehicle to save storage capacity. The use of telematics also makes it possible to update the received map data to accurately recognize actual traffic situations, such as changes in road structure, and the presence or absence of roadworks or construction. The use of telematics also makes it possible to recognize accurate information because map data generated from data received from a variety of other vehicles other than the main vehicle can be used.

[0017] The GPS receiver 3 receives radio waves from a plurality of navigation satellites to obtain the current position (own position) of the main vehicle, and outputs the obtained current position of the main vehicle to the processing circuit 6. A global navigation satellite system (GNSS) receiver may be included in place of the GPS receiver 3.

[0018] The vehicle sensor 4 is a sensor for detecting the current position and motion state (behavior) of the main vehicle. The vehicle sensor 4 may include a speed sensor, an acceleration sensor, a gyro sensor, and a yaw rate sensor, but the type and number of vehicle sensors are not limited to the above case. The speed sensor may determine the speed according to the wheel speed of the main vehicle to output the determined speed to the processing circuit 6 . The acceleration sensor can detect acceleration in the longitudinal direction and the vehicle width direction of the main vehicle itself, for example, to output the determined acceleration to the processing circuit 6 . The gyro sensor may determine the angular velocity of the main vehicle to output the determined angular velocity to the processing circuit 6 . The yaw rate sensor, for example, can detect an angular rotation rate (yaw rate) about a vertical axis passing through the center of gravity point of the main vehicle to output the determined yaw rate to the processing circuit 6 .

[0019] The peripheral sensor 5 is a sensor for detecting the environment (environment) of the main vehicle. The peripheral sensor 5 may include a camera, a radar, and a communication device, but the type and number of the peripheral sensors 5 are not limited to the above case. The camera used as the peripheral sensor 5 may be a CCD camera, for example. The camera may be a monocular camera or a stereo camera. The camera captures the environment of the main vehicle, detects, as the environment data of the main vehicle based on the captured images, the relative position between the main vehicle and an object such as another vehicle, a pedestrian or a bicycle, the distance between each object and the main vehicle, as well as a road structure such as lane boundaries (white lines) or curbs on the road, and outputs the detected environment data to the processing circuit 6 .

[0020] The radar used as the peripheral sensor 5 may be, for example, a millimeter wave radar, an ultrasonic radar, or a laser rangefinder (LRF). The radar detects, as the main vehicle environment data, the relative position of the object relative to the main vehicle, the distance between the object and the main vehicle, and the relative speed between the object and the main vehicle, and outputs the detected environment data to the processing circuit 6.

[0021] The communication device used as the peripheral sensor 5 can receive data about the environment of the main vehicle, including the own position of the main vehicle, through, for example, communication between vehicles with other vehicles, communication between road infrastructure and vehicle means with a device on the side of the road, or communication with the traffic information center, and output the detected environment data to the processing circuit 6 . Each of the GPS receiver 3, the vehicle sensor 4 and the peripheral sensor 5 used herein can be used as a sensor capable of detecting an actual road structure and the like in the vicinity of the main vehicle.

[0022] The processing circuit 6 is a controller, such as an electronic control unit (ECU), for performing arithmetic-logical operations necessary for processing driving assistance for the main vehicle. The processing circuit 6 may include a processor, a storage device, and an input/output interface. The processor may be a central processing unit (CPU) including an arithmetic logic unit (ALU), a control circuit (control unit), and various types of registers, or a microprocessor equivalent to a CPU. The storage device installed in the processing circuit 6 or externally connected thereto may be, for example, a semiconductor memory or a disk medium, and may also include a register, a cache memory, and a storage medium such as ROM or RAM used as the main memory. storage device. The processor included in the processing circuit 6 executes a program previously stored in the storage device to cause the movement assistance device 1 to execute the information processing described below.

[0023] For example, the processing circuit 6 may output guide information based on the map data stored in the map storage unit 10 from the display 7 or any other information presentation device such as a speaker to present information to the inside person. The processing circuit 6 may, for example, perform driving assistance for the main vehicle. The term "driving assistance" can refer either to fully automated driving, in which the main vehicle moves autonomously without the participation of an occupant person (such as a driver), or to driving assistance to control at least one of propulsion, braking and steering. The term "driving assistance" as used herein covers the case of controlling all of the propulsion, braking and steering of the main vehicle without the participation of an occupant, as well as the case of controlling at least one of the propulsion, braking and steering main vehicle.

[0024] The driving assistance execution processing circuit 6 generates a driving route to be followed by the main vehicle according to the map data stored in the map storage unit 10 . The driving route includes the driving route for each lane in addition to the driving route for each road from the current position of the primary vehicle to the destination. The motion path may include a motion control profile, such as a speed profile. For example, the processing circuit 6 accurately determines the position of the main vehicle in the map data, and generates a driving route (travelling course) so that it can be navigated along the lane based on the position of the main vehicle. The driving route (traffic course) can be generated, for example, along the center of the traffic lane.

[0025] The route generation processing circuit 6 refers to the map data stored in the map storage unit 10, and can also acquire high-precision positional information about the surroundings from the peripheral sensor 5. Thus, the processing circuit 6 preferably prepares, in addition to the map data, integrated data in which the map data is integrated with the environment data received from the peripheral sensor 5 to generate a driving route using the integrated data. The processing circuit 6 outputs the generated driving route to the vehicle control device 8 .

[0026] The vehicle control device 8 is an ECU for performing traffic control for the main vehicle. The vehicle control device 8 includes a processor and peripheral components such as a memory. The processor may be, for example, a CPU or an equivalent microprocessor. The storage device may include semiconductor memory, magnetic memory, and optical memory. The storage device may include a register, a cache memory, and a memory such as ROM or RAM used as the main storage device. The vehicle control device 8 may be implemented by a functional logic circuit installed in a general purpose semiconductor integrated circuit. For example, the vehicle control device 8 may include a programmable logic device (PLD) such as a programmable gate array (FPGA).

[0027] The vehicle control device 8 calculates the control amount of the actuator 9 so that the main vehicle moves along the driving path generated by the processing circuit 6. The vehicle control device 8 sends the calculated control amount to the actuator 9. The actuator 9 controls the movement of the main vehicle in accordance with the control signal received from the vehicle control device 8. The actuator 9 may be a driving actuator, a brake actuator, and a steering actuator. The driving actuator may be an electronically controlled throttle, for example, to control the opening degree of the accelerator of the main vehicle in accordance with the control signal received from the vehicle control device 8 . The brake actuator may be a hydraulic circuit, for example, to control the brake operation of the brake of the main vehicle in accordance with the control signal received from the vehicle control device 8 . The steering actuator controls the steering of the main vehicle in accordance with the control signal received from the vehicle control device 8 .

[0028] Traffic situations in which the driving assistance device 1 according to the embodiment of the present invention operates are described below with reference to FIG. 2 and FIG. 3. As shown in FIG. 2, the map data stores positional coordinates of a plurality of compound points P1 constituting a lane boundary L1 on one side defining a lane L0 on which the main vehicle 100 is traveling, and positional coordinates of a plurality of compound points P2 constituting a lane boundary L2 on the other side. , which determines the lane L0 of motion. The periphery sensor 5 detects the real world lane boundaries corresponding to the lane boundaries L1 and L2 when the main vehicle 100 is moving to detect the positional coordinates of a plurality of detection points p1 upon detecting the real world lane boundary corresponding to the lane boundary L1, and positional coordinates of the plurality of detection points p2 when detecting a lane boundary in the real world corresponding to the lane boundary L2. FIG. 2 indicates the forward driving direction D0 of the main vehicle 100 and the forward direction D1 of the driving lane L0 with respective arrows.

[0029] The following is a case where it is intended to perform correlation between the component points P1 and P2 as the configuration information of the lane boundaries L1 and L2 in the map data and the detection points p1 and p2 detected by the periphery sensor 5 through the matching (comparison) processing, to generate integrated data in a predefined integrated range (matching range) A1. The traffic lane L0 in the integrated range A1 in this case has a road configuration that has a simple straight line without any specific characteristics, which may lead to a difference in said comparison in the forward direction D1 of the lane L0, since the data in the forward direction D1 of the lane L0 movements are optional (binding). It is then assumed that the composite points P1 and P2 in the map data are adjusted to reduce the error, for example, with respect to the detection points p1 and p2. This case can lead to a gap between lane boundaries L3 and L4, consisting of composite points P3 and P4 obtained after correction, and lane boundaries L5 and L6 in the real world in the A2 range after changing the road configuration from straight to curved, as shown in FIG. 3.

[0030] As with the straight line road configuration, a curved road having a predetermined curvature has no particular characteristics and results in a difference when compared in the forward lane direction. The driving assistance device 1 according to the embodiment of the present invention can determine an appropriate integrated range when generating integrated data, including performing matching processing in consideration of road configuration characteristics while avoiding matching difference so as to properly generate integrated data.

[0031] As shown in FIG. 1, the processing circuit 6 in the driving assistance device 1 according to an embodiment of the present invention includes a logic block, as functional or physical hardware resources, including a self-position calculation block 11, a boundary recognition block 12, an integrated range determination block 13, a matching block 14, an integration block 15, and a route calculation block 16 . Own position calculation unit 11, boundary recognition unit 12, integrated range determination unit 13, matching unit 14, integration unit 15 and movement route calculation unit 16 11 may implement a physical logic circuit, which may be a PLD such as, for example, an FPGA, or a functional a logic circuit equivalently installed in a general purpose semiconductor integrated circuit by software processing.

[0032] The own position calculation unit 11, the border recognition unit 12, the integrated range determination unit 13, the matching unit 14, the integration unit 15, and the movement route calculation unit 16 may be implemented by a single hardware component, or each of them may be implemented with using separate hardware. For example, the own position calculation unit 11, the boundary recognition unit 12, the integrated range determination unit 13, the matching unit 14, the integration unit 15, and the driving route calculation unit 16 may be implemented in an automobile navigation system such as an in-vehicle infotainment (IVI) system. , and the vehicle control device 8 may be implemented by a driving assistance system such as an advanced driver assistance system (ADAS).

[0033] The own position calculation unit 11 acquires the history (sequence of points) of the main vehicle's own positions from the GPS receiver 3 or through the vehicle-to-vehicle communication or the road infrastructure-to-vehicle communication. The own position calculation unit 11 can convert the main vehicle own position coordinate system in the real world to the same coordinate system as the map data to calculate the main vehicle own position in the map data. For example, the positional coordinates of the main vehicle's own positions in the real world received from the GPS receiver 3 are converted into positional coordinates in the map coordinate system. The own position calculation unit 11 can calculate the amount of movement and the direction of movement of the main vehicle based on the vehicle information (odometry information) such as the wheel speed and the yaw rate of the main vehicle detected by the vehicle sensor 4, namely, to calculate the history of own positions by odometry. The own position calculation unit 11 may subject the points constituting the own position history to curve fitting to calculate the heading of the main vehicle.

[0034] The boundary recognition unit 12 recognizes lane boundaries according to the environment data detected by the peripheral sensor 5. The boundary recognition unit 12 recognizes lane marks, such as white lines, as lane boundaries, for example. Recognized lane boundaries can be of any type and are only required to be targets included as lane boundaries in the map data. For example, the boundary recognition unit 12 may recognize structures such as side ditches, curbs, fences, and posts as a lane boundary.

[0035] The boundary recognition unit 12 also converts the coordinate system of the detected lane boundaries to the same coordinate system as the map data according to the own positions calculated by the own position calculation unit 11 . For example, the boundary recognition unit 12 converts the lane boundary detection point coordinate system, which is a local coordinate system using own positions as the origin, into a map coordinate system to which the map data refers, in accordance with the main vehicle's own positions, received by the block 11 for calculating your own position from the receiver 3 GPS. The converted target is not limited to the map coordinate system, and the coordinate system, for example, may be a relative coordinate system that uses a positioning-enabled format.

[0036] For example, as illustrated in FIG. 4, the map data stores the positional coordinates of a plurality of compound points P11, P12, P13, P14, and P15 constituting a lane boundary L7 on one side defining a lane L9 along which the main vehicle 100 travels, and the positional coordinates of a plurality of compound points P31, P32, P33, P34 and P35 constituting the lane boundary L8 on the other side. It is assumed that the dotted lines indicating the respective lane boundaries L7 and L8 are obtained by interpolating the respective composite points P11-P15 and P31-P35 from the curves. FIG. 4 determines the X direction in which the east direction in the east-west direction in the map coordinate system is a positive direction, and determines the Y direction in which the north direction in the north-south direction in the map coordinate system is a positive direction.

[0037] The lane boundary L7 has a portion (straight portion) L71 extending in the forward direction D2 of lane L9, a portion (curved portion) L72 connected to the straight portion L71 and curved to the left, and a portion (straight portion) L73 connected to curved portion L72 and extending in the forward direction D3 of the lane L9 orthogonal to the forward direction D2. The lane boundary L8 has a portion (straight portion) L81 extending in the forward direction D2, a portion (curved portion) L82 connected to the straight portion L81 and curved to the left, and a portion (straight portion) L83 connected to the curved portion L82 and extending into forward direction D3 orthogonal to the forward direction D2.

[0038] The peripheral sensor 5 detects lane boundaries in the real world corresponding to lane boundaries L7 and L8 when the main vehicle 100 is moving. The boundary recognition unit 12 recognizes the lane boundaries in the real world corresponding to the lane boundaries L7 and L8 according to the detection result obtained by the peripheral sensor 5, and calculates the positional coordinates of a plurality of detection points p11 to p19 when detecting the lane boundary in the real world corresponding to the boundary L7 of the lane, and the positional coordinates of the plurality of detection points p21-p29 when detecting a lane boundary in the real world corresponding to the lane boundary L8. Although FIG. 4 illustrates a case of real world lane boundary recognition corresponding to a pair of lane boundaries L7 and L8, only a real world lane boundary corresponding to either lane boundary L7 or lane boundary L8 can be recognized. Although FIG. 4 illustrates detection points p11-p19 and p21-p29 behind the main vehicle 100, lane boundaries L7 and L8 can be detected from the front and sides of the main vehicle 100 while driving to obtain detection points.

[0039] The integrated range determining unit 13 determines the integrated range (matching range) when the lane boundary configuration information included in the map data is integrated with the lane boundary information detected by the periphery sensor 5. For example, the integrated range determination unit 13 determines the integrated range so that the respective lane boundaries include a plurality of portions having different curvature values or curvature radii. For example, each radius of curvature may be obtained such that the curved portion of each lane boundary is approximated by an arc of a circle, and each curvature may be obtained as the reciprocal of the radius of curvature. Each of the plurality of parts may be either a straight part or a curved part. Namely, the plurality of parts may be a combination of two or more curved parts having different curvature, or a combination of a straight part and a curved part.

[0040] For example, as shown in FIG. 4, the curvature of the respective straight portions L71 and L73 is zero, which is different from the curvature of the curved portion L72. The integrated range determining unit 13 may determine the integrated range to include the two parts L71 and L72 of the lane boundary L7, or determine the integrated range to include the two parts L72 and L73. Alternatively, the integrated range determination unit 13 may determine the integrated range to include the three portions L71, L72, and L73 of the lane boundary L7.

[0041] The integrated range determination unit 13 may determine the integrated range such that the lane boundary includes a plurality of straight portions pointing in different directions. Alternatively, the integrated range determination unit 13 may determine the integrated range such that the lane boundary includes a plurality of straight portions forming an angle with each other that is greater than or equal to a predetermined threshold value (e.g., 30 degrees) and less than or equal to a predetermined threshold value (for example, 90 degrees). In other words, the integrated range determination unit 13 may determine the integrated range such that the lane boundary includes a plurality of straight portions forming different angles with a predetermined direction (for example, direction X in FIG. 4). For example, as shown in FIG. 4, the integrated range determination unit 13 may determine the integrated range such that the lane boundary L7 includes two straight portions L71 and L73 directed in directions orthogonal to each other.

[0042] For example, the integrated range determination unit 13 accurately determines the respective composite points corresponding to the respective detection points obtained when the periphery sensor 5 detects the lane boundaries according to the point group data of the composite points constituting the respective lane boundaries in the map data. The composite points may be composite points stored in the map data or virtual composite points plotted on a curve by which the corresponding composite points stored in the map data are interpolated. The integrated range determination unit 13 evaluates each angle formed between the predetermined direction and the forward direction of the lane at the respective precisely determined composite points. The forward direction of the lane can be obtained, for example, based on the position in space of the main vehicle or connection information included in the map data. The integrated range determination unit 13 determines the integrated range such that the variation of the angles estimated at the respective composite points is greater than or equal to a predetermined threshold value. The change in angles can be obtained such that a difference is obtained between the respective angle data estimated at the respective composite points and the mean value, and the respective differences are squared to calculate the mean value to obtain a discrepancy.

[0043] Alternatively, the integrated range determination unit 13 may accurately determine the composite points corresponding to the respective detection points obtained when the sensor 5 detects the periphery of the lane boundaries, and then interpolate the corresponding composite points along the curve to calculate the nearest points on this curve with respect to corresponding detection points. Then, the integrated range determination unit 13 may evaluate each angle formed between the predetermined direction and the forward direction of the lane at the respective nearest points, and determine the integrated range such that the change in the angles estimated at the respective nearest points is greater than or equal to a predetermined threshold value.

[0044] For example, as shown in FIG. 4, the integrated range determination unit 13 searches for multiple points in the map data corresponding to the corresponding detection point p11 to p19 and p21 to p29 when the lane boundaries are detected by the peripheral sensor 5 within a predetermined distance from the respective points p11 to p19. and p21 to p29 detection. Then, the integrated range determination unit 13 accurately determines the composite points P11, P15, P31, and P35 corresponding to the detection points p13, p17, p23, and p27.

[0045] The integrated range determination unit 13 also interpolates the component points P11-P15, including the component points P11 and P15, along the curve L7, and interpolates the component points P31-P35, including the well-defined component points P31 and P35, along the curve L8. The integrated range determining unit 13 further calculates the nearest points P21 to P27 as virtual compound points on the curve L7 corresponding to other detection points p11, p12, p14, p15, p16, p18 and p19 in which the corresponding compound points are not precisely determined, and calculates nearest points P41-P47 as virtual composite points on curve L8 corresponding to other detection points p21, p22, p24, p25, p26, p28 and p29.

[0046] The respective positional coordinates of the detection points p11-p19 and p21-p29, the composite points P11-P15 and P31-P35, and the nearest point P21-P27 and P41-P47, as well as the correlation information between the points p11-p19 and p21- The detection p29 and each of the composite points P11-P15 and P31-P35 and the nearest points P21-P27 and P41-P47 are stored in the map storage unit 10 in the storage device 2, for example, and can be used as needed when expanding the integrated range.

[0047] The integrated range determination unit 13 further evaluates each angle formed between the predetermined direction and the forward direction of the lane at the respective composite points P11-P15 and nearest points P21-P27. For example, as shown in FIG. 5, when the direction X at the composite point P11 is set to zero degrees, the angle θ1 of the forward driving direction D2 of the main vehicle with respect to the direction X, measured counterclockwise, is 180 degrees. Similarly, as shown in FIG. 6, the angle θ2 of the forward driving direction D3 of the main vehicle with respect to the X direction at the compound point P15, measured counterclockwise, is 90 degrees. The corresponding angles at the compound points P12-P14 and nearest points P21-P27 are calculated in a similar way. The corresponding angles at the compound points P31-P35 and nearest points P41-P47 are also calculated in the same way.

[0048] The integrated range determination unit 13 sets the initial value of the integrated range and determines whether the change (variance) of the angles estimated at the respective composite points and the corresponding nearest points in the integrated range is equal to or greater than a predetermined threshold value. When the change (divergence) of angles is less than a predetermined threshold value, the integrated range determining unit 13 expands the integrated range to a predetermined threshold value or more to determine the integrated range. For example, when the integrated range A1 shown in FIG. 4 is defined such that the lane boundary L7 includes only the straight portion L71, and the lane boundary L8 includes only the straight portion L81, the change d1 of the angles at the composite points P11 and P12 and the nearest points P21-P24 in the integrated range A1 is quite small as shown in FIG. 7. Then, the integrated range determination unit 13 determines that the angle change d1 is less than a predetermined threshold value.

[0049] Thus, the integrated range determining unit 13 expands the integrated range A1 as shown in FIG. 8 so that the lane boundary L7 includes three portions L71, L72, and L73, and the lane boundary L8 includes three portions L81, L82, and L83. Thus, the change d2 of the angles at the respective composite points P11-P15 and nearest points P21-P27 in the integrated range A1 is increased, as shown in FIG. 9. The integrated range determination unit 13 determines that the angle change is equal to or greater than a predetermined threshold to determine the integrated range A1 shown in FIG. 8. Although FIG. 8 illustrates a case of determining the integrated range A1 behind the main vehicle 100, the integrated range may be determined to include the front region in front of the main vehicle 100.

[0050] For example, when the detection points can be sequentially detected by the peripheral sensor 5, the integrated range determination unit 13 can evaluate each angle formed between the predetermined direction and the forward direction of the lane at the respective detection points. Then, the integrated range determination unit 13 may determine the integrated range such that the change (divergence) of the angles estimated at the respective detection points is greater than or equal to a predetermined threshold value.

[0051] The mapping unit 14 performs a comparison (comparison) between the lane boundary configuration information included in the map data and the lane boundary information detected by the periphery sensor 5, while at the same time including at least an integrated range determined by the determining unit 13 integrated range. The matching can be done in a traditional way, such as iterative closest point (ICP). The term “matching” as used herein refers to the process of performing matching between the multiple points in the lane boundary configuration information included in the map data and the detection points when the lane boundaries are detected by the periphery sensor 5 (in other words, determining the combination of detection points and composite points corresponding to said detection points). The matching unit 14 outputs matching information (matching result) in which detection points and composite points are correlated with each other.

[0052] For example, as shown in FIG. 8, the matching unit 14 performs matching between the compound points P11 and P15 and the nearest points P21 to P27 on the lane boundary L7 included in the map data and the detection point p11 to p17 detected by the peripheral sensor 5. The matching unit 14 also performs matching between the compound points P31 and P35 and the nearest points P41 to P47 on the lane boundary L8 included in the map data and the detection point p21 to p27 detected by the peripheral sensor 5.

[0053] The integration unit 15 integrates the lane boundary information detected by the periphery sensor 5 and converted to the same coordinate system as the map data with the lane boundary configuration information included in the map data according to the matching result. obtained by the mapping unit 14 to generate the integrated data. As used herein, the term "integration" refers to the processing of integrating the detection point data detected by the periphery sensor 5 with the composite point data in the map data in a state in which the detection points detected by the periphery sensor 5 and the composite points in the map data, united by juxtaposition are related to each other. The integrated data can be used, for example, when generating a traffic plan. The generated integrated data is stored in the card storage unit 10 in the storage device 2 or any other storage device.

[0054] The integration unit 15 can directly integrate the lane boundary information detected by the periphery sensor 5 with the lane boundary configuration information included in the map data to generate integrated data including the positional coordinates of the detection points detected by the periphery sensor 5 , and positional coordinates of composite points included in the cartographic data and correlated with the corresponding detection points. Alternatively, the integration unit 15 may correct the lane boundary configuration information included in the map data according to the matching result obtained by the collator 14 to generate, as integrated data, the corrected lane boundary configuration information and the lane boundary information. detected by the peripheral sensor 5.

[0055] The integration unit 15 can optimize the positional coordinates of the composite points on the lane boundaries included in the map data to minimize the positional error between the composite points on the lane boundaries included in the map data and the detection points detected by the periphery sensor 5. For example, the integration unit 15 may calculate the sum of the squared differences (errors) between the composite points on the lane boundaries included in the map data and the detection points detected by the periphery sensor 5 to minimize the calculated sum. The integration unit 15 can integrate the data detected by the periphery sensor 5 with the mapping data to minimize the error between the whole point group data for detection points detected by the periphery sensor 5 within the integrated range and the whole point group data for multiple points at lane boundaries, included in the map data in the integrated range.

[0056] The integration unit 15 shifts the positional coordinates of the composite points P11 and P15 and the nearest points P21-P27 on the border L7 of the lane included in the map data, as shown in FIG. 8 by the same distance in the same direction to calculate the amount of offset so that the sum of the positional errors is the smallest, in order to align the component points P11 and P15 and the nearest points P21-P27 at the boundary L7 of the lane included in the mapping data, with detection points p11-p17 detected by the peripheral sensor 5. Then, the integration unit 15 corrects (updates) the positional coordinates of the composite points included in the map data stored in the map storage unit 10 so that they are shifted by the offset amount M. The integration unit 15 may correct all of the multiple points included in the map data or correct only the multiple points within a predetermined range near the main vehicle.

[0057] The integrated range determination unit 13 may determine the integrated range repeatedly (multiple times) at predetermined intervals each time the main vehicle moves. The matching unit 14 may re-execute matching processing between detection points and multiple points in the integrated range determined by the integrated range determination unit 13 at predetermined intervals each time the main vehicle moves. The integration unit 15 may perform integration processing by recorrecting the map data, for example, using the matching results obtained by the matching unit 14 .

[0058] The driving route calculation unit 16 generates a driving route along which the main vehicle is to move according to the integrated data generated by the integration unit 15 . The route calculation unit 16 outputs the generated route to the vehicle control device 8 .

[0059] (Movement assistance method)

An operation example (driving assistance method) of the driving assistance device 1 according to the embodiment of the present invention will be described below with reference to the flowchart shown in FIG. ten.

[0060] In step S1, the own position calculation unit 11 calculates the main vehicle's own positions obtained from the GPS receiver 3 and the like. In step S2, the boundary recognition unit 12 detects lane boundaries present in the vicinity of the main vehicle according to the environment data detected by the peripheral sensor 5 . In step S3, the integrated range determination unit 13 converts the coordinate system of the lane boundaries detected by the boundary recognition unit 12 into the same coordinate system as the map data.

[0061] In step S4, the integrated range determining unit 13 determines an integrated range used in integrating the lane boundary configuration information included in the map data stored in the map storage unit 10 in the storage device 2 with the lane boundary information detected by the sensor 5 peripherals. For example, the integrated range determination unit 13 determines the integrated range such that the lane boundaries include at least a plurality of portions having different curvature values or a plurality of straight portions pointing in different directions.

[0062] An example of integrated range determination processing in step S4 is described in detail below with reference to the flowchart shown in FIG. 11. In step S41, the integrated range determination unit 13 calculates the closest points on the lane boundaries in the map data with respect to the corresponding detection points obtained after the lane boundaries were detected. In step S42, the integrated range determination unit 13 calculates the angle formed between the predetermined direction and the forward direction of the lane at the respective nearest points. In step S43, the integrated range determination unit 13 determines whether the change (divergence) of the angles at the respective closest points in the integrated range is equal to or greater than a predetermined threshold value. When it is determined that the change (divergence) of the angles is less than a predetermined threshold, the process proceeds to step S44. Then, the integrated range determination unit 13 executes the integrated range extension processing in the direction opposite to the forward driving direction of the vehicle, and the process returns to step S43. When the change (divergence) of the angles is determined at step S43 to be equal to or greater than a predetermined threshold value, the integrated range determining unit 13 finalizes the integrated range to complete the integrated range determination processing at step S4.

[0063] Returning to FIG. 10. In step S5, the matching unit 14 performs matching processing between the road configuration information included in the map data and the road configuration information detected by the peripheral sensor 5 and converted to the same coordinate system as the map data, while including at least the integrated range determined by the block 13 for determining the integrated range. In step S6, in accordance with the matching result obtained by the matching unit 14, the integration unit 15 integrates the road configuration information included in the map data with the road configuration information detected by the peripheral sensor 5 and converted to the same coordinate system as the map data to generate integrated data. The integration unit 15 stores the generated integrated data in the card storage unit 10 .

[0064] In step S7, the driving route calculation unit 16 generates a driving route on which the main vehicle is to travel according to the integrated data generated by the integration unit 15 . In step S8, the vehicle control device 8 drives the actuator 9 to perform vehicle control on the main vehicle to cause the main vehicle to follow the driving route generated by the driving route calculation unit 16 .

[0065] In step S9, the processing circuit 6 determines whether the ignition switch (IGN) of the host vehicle is turned off. The process ends when it is determined that the ignition switch is off. The process returns to step S1 when it is determined that the ignition switch has not yet been turned off.

[0066] (Effects of the Embodiment)

According to an embodiment of the present invention, the integrated range determination unit 13 determines the integrated range so that the lane boundaries have portions having different curvature or directed in different directions by integrating the lane boundary configuration information included in the map data with the lane boundary information. movements detected by the peripheral sensor 5 to generate integrated data. The integrated range determining unit 13 correlates and integrates the lane boundary configuration information included in the map data with the lane boundary information detected by the periphery sensor 5 to generate integrated data while including at least a certain integrated range.

[0067] In this way, the integrated range determining unit 13 can determine the integrated range appropriately so that the lane road configuration in the integrated range has certain characteristics. Thus, the accuracy of matching processing between the lane boundary configuration information included in the map data and the lane boundary information detected by the periphery sensor 5 can be improved, resulting in proper matching. This enables a suitable correlation between the lane boundary configuration information included in the map data and the lane boundary information detected by the periphery sensor 5 while performing fine alignment as necessary to properly generate integrated data.

[0068] The integrated range determining unit 13 also determines the integrated range so that the respective lane boundaries include a plurality of straight portions forming different angles with a predetermined direction. This can minimize the difference when matching in the forward direction of the lane when matching in a simple straight lane, so as to improve the matching accuracy accordingly.

[0069] The integrated range determining unit 13 also calculates the composite points corresponding to the respective detection points, and evaluates the respective angles formed between the predetermined direction and the forward direction of the lane at the respective composite points to determine the integrated range so that the change (divergence) the estimated angles were greater than or equal to a predetermined threshold. This can minimize the difference when matching in the forward direction of the lane when matching in a simple straight lane, so as to improve the matching accuracy accordingly.

[0070] The integrated range determination unit 13 also calculates the composite points corresponding to the respective detection points, and interpolates the corresponding composite points along the curve to calculate the nearest points on said curve relative to the detection points. Then, the integrated range determining unit 13 evaluates the respective angles formed between the predetermined direction and the forward direction of the lane at the respective nearest points to determine the integrated range such that the angle change is greater than or equal to the predetermined threshold. This makes it possible to accurately calculate the forward direction of the lane at the respective nearest points.

[0071] The integrated range determining unit 13 also evaluates the respective angles formed between the predetermined direction and the forward direction of the lane at the respective detection points to determine the integrated range such that the change (discrepancy) in the estimated angles is greater than or equal to a predetermined threshold. Evaluation of the change (divergence) of angles in the forward direction of the lane at the detection points, when it is possible to sequentially detect the detection points, for example, can minimize the difference when matching in the forward direction of the lane after matching on a simple straight road, to correspondingly improve the matching accuracy.

[0072] The integrated range determining unit 13 re-determines the integrated range, the matching unit 14 re-matches between the detection points and the composite points in the integrated range determined by the integrated range determining unit 13, and the integration unit 15 re-corrects the map data using the matching result each time when the main vehicle is moving. Because the mapping data is corrected beforehand using the previous matching result when matching is performed, the composite points corresponding to the corresponding detection points can be detected accurately when the integrated range is determined.

[0073] The integration unit 15 generates integrated data to include the front area in front of the main vehicle in the forward direction outside the integrated range. This allows integrated data to be pre-generated in an area before it is reached by the main vehicle, in addition to the integrated range in which the matching unit 14 performs the matching.

[0074] The driving assistance device 1 according to an embodiment of the present invention can be used for various types of road configurations. The following is a case in which it is assumed that the lane L9 is curved at a right angle, as shown in FIG. 12. The lane boundary L7 has a straight portion L71 extending in the forward direction D2 and a straight portion L72 connected to the straight portion L71 and extending in the forward direction D3 orthogonal to the forward direction D2. The lane boundary L8 has a straight portion L81 extending in the forward direction D2 and a straight portion L82 connected to the straight portion L81 and extending in the forward direction D3 orthogonal to the forward direction D2.

[0075] Each of the straight portions L71 and L72 at the lane boundary L7 has zero curvature, but they are directed in different directions. Each of the straight portions L81 and L82 at the lane boundary L8 has zero curvature, but they are directed in different directions. Then, the integrated range determination unit 13 determines the integrated range A1 to include two straight portions L71 and L72 of the lane boundary L7 and two straight portions L81 and L82 of the lane boundary L8. The integrated range determination unit 13 may determine the integrated range A1 according to either the lane boundary L7 or the lane boundary L8 information only.

[0076] (First modified example)

The first modified example of the embodiment of the present invention is illustrated below with a case of determining the integrated range according to the change in forward driving directions of the main vehicle when the integrated range determination unit 13 determines the integrated range.

[0077] The own position calculation unit 11 sequentially executes processing on sampling own positions along the main vehicle's driving course, and calculates a sequence of points P51 to P56 when the periphery sensor 5 can detect lane boundaries, as illustrated, for example, in FIG. 13.

[0078] The integrated range determination unit 13 evaluates the forward direction of the main vehicle 100 at the respective own positions P51 to P56 calculated by the own position calculation unit 11 . For example, the integrated range determining unit 13 may use the position in space of the main vehicle 100 obtained by the GPS receiver 3 as the forward direction of the main vehicle. Alternatively, the integrated range determination unit 13 may interpolate the history (sequence of points) of the eigenpositions P51-P56 along the curve L10 and obtain the tangents to the curve L10 at the respective eigenpositions P51-P56 to calculate the forward driving directions of the main vehicle 100. As alternatively, the integrated range determination unit 13 may calculate the forward driving directions of the main vehicle 100 using the lane information to which the main vehicle 100 belongs when the connection information and the like in the map data includes lane information, for example, the shape and type of lane to which the main vehicle 100 belongs.

[0079] The integrated range determining unit 13 determines the integrated range such that the change (divergence) of the forward driving directions of the main vehicle 100 at the respective own position P51-P56 is greater than or equal to a predetermined threshold value.

[0080] According to the first modified example of the embodiment of the present invention, own positions are computed upon detection of lane boundaries, and the forward driving directions of the main vehicle are estimated at the respective own positions to determine the integrated range such that the forward driving direction divergence of the main vehicle is greater than or is equal to a predefined threshold value. Because the first modified example can access eigenposition information with fewer than the number of detection points obtained from lane edge detection, the matching difference can be minimized with less computational overhead.

[0081] Detection of forward directions of the main vehicle by the GPS receiver 3 can accordingly calculate forward directions.

[0082] Calculating the forward directions of the main vehicle by interpolating the own positions of the main vehicle along the curve to obtain tangents to the curve accordingly enables the forward directions to be accurately calculated.

[0083] Calculating the forward driving directions of the main vehicle using the lane information included in the map data to which the lead vehicle belongs, without using the GPS receiver 3, makes it possible to accurately calculate the forward driving directions while avoiding the effect of changing the accuracy of the receiver 3 GPS.

[0084] (Second modified example)

The second modified example of the embodiment of the present invention is illustrated below with a case of determining the integrated range according to the change in lane curvature values when the integrated range determining unit 13 determines the integrated range.

[0085] For example, the integrated range determination unit 13 accurately determines the composite points corresponding to the respective detection points detected by the periphery sensor 5 according to the composite points constituting the lane boundary configuration information included in the map data, and estimates the curvature or radius of curvature traffic lanes at corresponding, well-defined composite points. For example, the radius of the circumscribed circle is obtained for the positional coordinates of the target composite point and the positional coordinates of two composite points adjacent to the target composite point to calculate the radius of curvature of the lane at the target composite point. The integrated range determining unit 13 determines the integrated range such that the change in curvature values or curvature radii of the lane at the respective composite points is greater than or equal to a predetermined threshold value.

[0086] Alternatively, the integrated range determination unit 13 can accurately determine the composite points corresponding to the respective detection points detected by the periphery sensor 5 according to the composite points constituting the lane boundary configuration information included in the map data, interpolate the corresponding accurately certain composite points along the curve and calculate the nearest points on this curve relative to the detection points. The integrated range determination unit 13 estimates the curvature or radius of curvature of the lane at the respective calculated nearest points. For example, based on the positional coordinates of the target closest point and the positional coordinates of the two closest points adjacent to the target closest point, the integrated range determination unit 13 can calculate the curvature or radius of curvature of the lane at the target closest point. The integrated range determination unit 13 may determine the integrated range such that the change in curvature values or radii of curvature of the lane at respective nearest points is greater than or equal to a predetermined threshold value.

[0087] For example, as shown in FIG. 8, the integrated range determination unit 13 calculates the curvature of the straight portion L71 at the lane boundary L7 at the composite point P11 at the lane boundary L7 as the curvature of the lane L9 based on the positional coordinates of the nearest point P22, the composite point P11, as well as the nearest point P23 on the boundary. L7 lanes. The integrated range determination unit 13 also calculates the curvature of the curved portion L72 at the lane boundary L7 at the composite point P13 at the lane boundary L7 as the curvature of the lane L9 based on the positional coordinates of the composite points P12, P13 and P14 at the lane boundary L7.

[0088] According to the second modified example of the embodiment of the present invention, the curvature or radius of curvature of the lane is estimated at the respective composite points corresponding to the detection points obtained by detecting the boundaries of the lane, so that the integrated range is determined so that the change (difference) of the curvature values or lane curvature radii was greater than or equal to a predetermined threshold. Estimating the variation (divergence) of lane curvature values or curvature radii can minimize the difference in lane forward matching that can be caused by matching only along a curve having a constant curvature or curvature radius to correspondingly improve matching accuracy.

[0089] In addition, the respective composite points corresponding to the detection points obtained by detecting the lane edges are interpolated with a curve, the nearest points on this curve are calculated relative to the respective detection points, and the curvature or radius of curvature of the lane is estimated at the respective nearest points, so that the integrated range is determined such that the change (difference) in the curvature values or curvature radii of the lane is greater than or equal to a predetermined threshold value. This makes it possible to accurately calculate curvature values or radii of curvature in an appropriate manner.

[0090] (Third modified example)

The third modified example of the embodiment of the present invention is illustrated below with the case of determining the integrated range according to the change in curvature values or radii of curvature of the driving course of the main vehicle when the integrated range determination unit 13 determines the integrated range.

[0091] The own position calculation unit 11 sequentially performs processing on sampling own positions along the main vehicle's driving course, and calculates a sequence of points P51 to P56 when the periphery sensor 5 can detect lane boundaries, as illustrated, for example, in FIG. 13.

[0092] The integrated range determination unit 13 estimates the curvature or radius of curvature of the main vehicle's course at the respective calculated eigenpositions. The curvature or radius of curvature of the driving path of the main vehicle may be calculated according to the yaw rate detected by the yaw rate sensor, which is the peripheral sensor 5 mounted on the main vehicle. For example, the radius of curvature can be calculated according to the ratio R=V/Y, where V [m/s] is the speed of the main vehicle, R [m] is the radius of curvature of the heading of the main vehicle, and Y [rad/s ] - yaw rate of the main vehicle.

[0093] The integrated range determination unit 13 may interpolate the sequence of points at their own positions along the curve to calculate the curvature or radius of curvature of the main vehicle's course. When the lane information included in the connection information in the map data includes lane type or shape information, the integrated range determination unit 13 can calculate the curvature or radius of curvature of the main vehicle's driving course using the lane information, to to which the vehicle belongs.

[0094] The integrated range determining unit 13 determines the integrated range such that the change in curvature values or radii of curvature of the main vehicle's course at the respective own positions is greater than or equal to a predetermined threshold value.

[0095] According to the third modified example of the embodiment of the present invention, the eigenpositions obtained by detecting the lane edges are sequentially calculated, and the heading curvature of the main vehicle is estimated at the respective eigenpositions so as to determine the integrated range such that the change in the heading curvature values movement of the main vehicle was greater than or equal to a predetermined threshold. Because the third modified example accesses eigenposition information with fewer than the number of detection points, the matching difference can be minimized with less computational overhead.

[0096] Calculating the curvature or radius of curvature of the main vehicle's heading based on the yaw rate detected by the yaw rate sensor, which is the periphery sensor 5 installed on the main vehicle, can properly calculate the curvature or radius of curvature of the main vehicle.

[0097] Calculating the curvature or radius of curvature of the main vehicle's course by interpolating a sequence of points at respective eigenpositions with the help of a curve enables the course curvature or radius of curvature to be properly calculated.

[0098] Calculating the curvature or radius of curvature of the driving course of the main vehicle using information about the lane included in the map data to which the main vehicle belongs, without using the GPS receiver 3 or the yaw rate sensor, makes it possible to accurately calculate the curvature or radius of curvature heading of the main vehicle while avoiding the effect of changing the accuracy of the GPS receiver 3 or the yaw rate sensor.

[0099] (Fourth modified example)

A fourth modified example of an embodiment of the present invention is illustrated below with a case of thinning out detection points or own positions in the integrated range when the integrated range determination unit 13 expands the integrated range.

[0100] For example, the integrated range determining unit 13 sets the integrated range as the initial setting, and extends the integrated range in the opposite direction of the forward driving direction of the main vehicle (reverse) when the lane boundaries do not include a plurality of parts having different curvature values, or a plurality of straight parts pointing in different directions within a specified integrated range. Then, the integrated range determination unit 13 thins out the detection points or own positions in the integrated range. The decimation intervals may be appropriately defined, and may be alternating points or multiple points, or may be any predetermined distance or irregular intervals. The matching processing by the matching unit 14 is performed using the remaining detection points or own positions without using the detection points or own positions excluded by decimation in the matching processing.

[0101] The integrated range determination unit 13 may vary the decimation intervals of the detection points or own positions depending on the curvature of the lane in the map data. For example, the integrated range determination unit 13 increases the decimation intervals of the detection points or own positions to more frequently sample as the curvature of the lane increases (in other words, as the radius of curvature of the lane decreases), since the road configuration is assumed to have significant characteristics. The integrated range determination unit 13 reduces the decimation intervals of detection points or own positions to perform coarse sampling as the curvature of the lane decreases (in other words, as the radius of curvature of the lane increases).

[0102] Alternatively, the integrated range determination unit 13 may change the decimation intervals of the detection points or own positions depending on the lane length in the map data. For example, the integrated range determination unit 13 reduces the decimation intervals of detection points or own positions to perform coarse sampling as the length of the lane increases, since the road configuration is assumed to have few characteristics. The integrated range determination unit 13 increases the decimation intervals of the detection points or own positions to sample more frequently as the lane length decreases.

[0103] As shown in FIG. 4, for example, the integrated range extends in the direction opposite to the forward direction of the main vehicle 100 (backward) in the integrated range A1 after the initial setting, since the respective lane boundaries L7 and L8 include only one straight portion L71 or L81. As shown in FIG. 8, when the integrated range A1 is expanded, the detection points p12, p14, p16 and p18 are decimated from the detection points p11 to p19 at the lane boundary L7 at alternate positions. The detection points p21 to p29 at the lane boundary L8 are also subjected to thinning processing in the same manner as the detection points p11 to p19 at the lane boundary L7.

[0104] According to the fourth modified example of the embodiment of the present invention, the decimation processing of detection points or eigenpositions in the integrated range when spreading can improve the matching processing efficiency to appropriately reduce the computational load.

[0105] Changing the thinning intervals of detection points or own positions depending on the curvature of the lane in the map data, to, for example, reduce the thinning intervals for coarse sampling when the lane is long and straight and thus has a lane configuration with a small number of characteristics, can effectively reduce the computational load without reducing the matching accuracy. When a traffic lane is curved with a large curvature and thus has a traffic lane configuration with significant performance, the decimation intervals are increased to perform frequent sampling in order to improve matching accuracy.

[0106] Changing the thinning intervals of detection points or own positions depending on the length of the lane in the map data, to, for example, perform a coarser sampling when the lane is long and straight and thus has a lane configuration with few features , can effectively reduce the computational load without compromising matching accuracy.

[0107] Although the present invention has been described above with reference to a specific embodiment, it should be understood that the present invention should not be limited by the description and drawings that form part of this disclosure. Various alternative implementations, examples and technical applications will be obvious to those skilled in the art according to this disclosure.

[0108] For example, the range in which the integration unit 15 generates integrated data when integrating the lane boundary configuration information included in the map data with the lane boundary information detected by the periphery sensor 5 is not limited to the inside of the integrated range. The integration unit 15 may integrate the lane boundary configuration information included in the map data with the lane boundary information detected by the periphery sensor 5 in a range including an area outside the integrated range. For example, as shown in FIG. 14, the integration unit 15 can generate integrated data in the range A3 including, in addition to the integrated range A1, an area ahead of the integrated range A1 in the forward direction of the main vehicle 100. This allows the integration unit 15 to pre-generate integrated data in an area in which detection points have not yet been received, before it is reached by the main vehicle.

[0109] The integration unit 15 can integrate all lane boundary configuration information included in the map data in the integrated range with all lane boundary information detected by the periphery sensor 5. Alternatively, the integration unit 15 may integrate part of the lane boundary configuration information included in the map data in the integrated range with all of the lane boundary information detected by the periphery sensor 5. Alternatively, the integration unit 15 may integrate all of the lane boundary configuration information included in the map data in the integrated range with a portion of the lane boundary information detected by the periphery sensor 5.

[0110] All examples and conventions provided herein are for pedagogical purposes to help the reader understand the invention and the concepts introduced by the inventor in the development of the art, and they should not be construed as limitations to such specifically listed examples and conditions, but the organization of such examples in the description is not intended to demonstrate the superiority or inferiority of the present invention. While one or more embodiments of the present invention have been described in detail, it should be understood that various changes, substitutions, and modifications may be made to the invention without departing from the spirit and scope of the present invention.

LIST OF SYMBOLS

[0111]

1 MOVEMENT ASSIST DEVICE

2 STORAGE

3 GLOBAL POSITIONING SYSTEM RECEIVER

4 VEHICLE SENSOR

5 PERIPHERAL SENSOR

6 PROCESSING SCHEME

7 DISPLAY

8 VEHICLE CONTROL DEVICE

9 ACTUATOR

10 CARD STORAGE UNIT

11 OWN POSITION CALCULATION BLOCK

12 BORDER RECOGNITION UNIT

13 BLOCK OF DETERMINING THE INTEGRATED RANGE

14 BLOCK COMPARISON

15 INTEGRATION BLOCK

16 ROUTE CALCULATION BLOCK

100 MAIN VEHICLE

Claims (58)

1. A method of assistance in movement, comprising: detecting a lane boundary in the vicinity of the vehicle by means of the sensor; obtaining own positions of the vehicle; converting a coordinate system of a lane boundary detected by the sensor into a coordinate system equivalent to the map data stored in the storage device according to own positions; and integrating lane boundary configuration information included in the map data with a lane boundary whose coordinate system has been converted to generate integrated data, wherein the matching range is determined so that the boundary of the lane whose coordinate system is transformed includes at least either a plurality of parts having different curvature or a plurality of straight parts directed in different directions, the matching is performed between the configuration information and the boundary the lane whose coordinate system has been converted is within a range including at least said matching range, and the configuration information and the border of the lane whose coordinate system has been converted are integrated according to the matching result to generate integrated data. 2. The driving assistance method according to claim 1, wherein each of the plurality of straight portions forms a different angle from each other with a predetermined direction. 3. The method of assistance in movement according to claim 2, further comprising: accurately determining the composite points constituting the configuration information, which correspond to the detection points obtained by detecting the lane boundary; estimating the angle at respective well-defined composite points formed between the predetermined direction and the lane forward direction determined by the lane boundary; and determining a matching range such that the change in angles is greater than or equal to a predetermined threshold. 4. The method of assistance in movement according to claim 2, further comprising: setting composite points constituting the configuration information and corresponding to detection points obtained by detecting a lane boundary; interpolation of corresponding well-defined composite points along the curve; calculating the nearest points on this curve relative to the corresponding detection points; estimating the angle at the respective calculated nearest points formed between the predetermined direction and the lane forward direction determined by the lane boundary; and determining a matching range such that the change in angles is greater than or equal to a predetermined threshold. 5. The method of assistance in movement according to claim 2, further comprising: estimating the angle at the detection points obtained by detecting the lane boundary formed between the predetermined direction and the lane forward direction determined by the lane boundary; and determining a matching range such that the change in angles is greater than or equal to a predetermined threshold. 6. The method of assistance in movement according to claim 1 or 2, further comprising: calculation of a sequence of points of own positions upon detection of the border of the traffic lane; estimating the forward direction of the vehicle in the respective own positions; and determining a matching range such that the forward direction change of the vehicle is greater than or equal to a predetermined threshold. 7. The driving assistance method of claim 6, further comprising detecting the forward direction of the vehicle by means of a global positioning system receiver mounted on the vehicle. 8. The method of assistance in movement according to claim 6, further comprising: interpolation of the respective own positions along the curve; and obtaining a tangent to said curve in order to calculate the forward direction of the vehicle. 9. The driving assistance method of claim 6, further comprising calculating the forward direction of the vehicle by using information about the lane to which the vehicle belongs included in the map data. 10. The method of assistance in movement according to claim 1, further comprising: setting composite points constituting configuration information that correspond to detection points obtained by detecting a lane boundary; estimating the curvature of the lane, defined by the boundary of the lane, at the respective well-defined composite points; and determining a matching range such that the change in curvature values is greater than or equal to a predetermined threshold value. 11. The method of assistance in movement according to claim 1, further comprising: setting composite points constituting configuration information that correspond to detection points obtained by detecting a lane boundary; interpolation of corresponding well-defined composite points along the curve; calculating the nearest points on this curve relative to the corresponding detection points; estimating the lane curvature defined by the lane boundary at the respective calculated nearest points; and determining a matching range such that the change in lane curvature values is greater than or equal to a predetermined threshold value. 12. The method of assistance in movement according to claim 1, further comprising: calculation of a sequence of points of own positions upon detection of the border of the traffic lane; assessing the curvature of the course of the vehicle in the respective own positions; and determining a matching range such that the change in vehicle course curvature values is greater than or equal to a predetermined threshold value. 13. The driving assistance method of claim 12, further comprising calculating a course curvature according to a yaw rate detected by a yaw rate sensor mounted on the vehicle. 14. The driving assistance method of claim 12, further comprising interpolating a sequence of points of own positions along the curve to calculate the curvature of the course of travel. 15. The driving assistance method of claim 12, further comprising calculating the curvature of the driving course by using information about the lane to which the vehicle belongs included in the map data. 16. The method of assistance in movement according to any one of paragraphs. 1-15, additionally containing: correlating the configuration information with a boundary of a lane whose coordinate system has been converted each time the vehicle travels; and recorrecting the map data by using the result after matching. 17. The driving assistance method according to claim 1, further comprising, when expanding the matching range, thinning out the detection points obtained when a lane boundary is detected within the matching range, or own positions obtained when a lane boundary is detected. 18. The traffic assistance method of claim 17, further comprising varying the thinning interval depending on the lane curvature defined by the lane boundary, within the matching range. 19. The traffic assistance method of claim 17 or 18, further comprising varying the thinning interval depending on the lane length defined by the lane boundary within the matching range. 20. The method of assistance in movement according to any one of paragraphs. 1-19, further comprising generating integrated data to include a front region ahead of the vehicle in the forward direction of the vehicle outside of a certain matching range. 21. A motion assistance device, comprising: a sensor configured to detect a lane boundary in the vicinity of the vehicle; a storage device configured to store map data; and a controller configured to obtain the vehicle's own positions, convert the lane boundary coordinate system detected by the sensor into a map data equivalent coordinate system according to the own positions, and integrate the lane boundary configuration information included in the map data with lane boundary whose coordinate system has been transformed to generate integrated data, moreover, the controller is configured to determine the range of matching so that the border of the lane, the coordinate system of which is transformed, includes at least either a plurality of parts having different curvatures, or a plurality of straight parts directed in different directions, as well as performing matching between the configuration information and the lane boundary whose coordinate system has been converted, within a range including at least said matching range, and integrating the configuration information with the lane boundary whose coordinate system has been converted, according to the matching result, to generate integrated data.

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