Road information correction device

Abstract

To provide a road information correction device capable of correcting road information acquired using one's own vehicle position information and map information with high accuracy, regardless of influence on a road shape, afternoon sun, or the like.SOLUTION: In the device that calculates a correction amount of road information with respect to one's own vehicle position based on first road information and comparative road information, the comparative road information is acquired based on a vehicle state amount including right / left partition line position information near the one's own vehicle acquired with time, and information about a vehicle speed and a yaw rate of the one's own vehicle.SELECTED DRAWING: Figure 1

Description

[Technical Field]

[0001] The present disclosure relates to a road information correction device that further corrects road information acquired relative to a vehicle's position based on vehicle position measurement information and map information. [Background technology]

[0002] 2. Description of the Related Art Conventionally, there has been progress in the development of technology for obtaining road information for a vehicle's current position based on vehicle position measurement information and map information obtained from satellites, and providing driving assistance using this road information.

[0003] To provide advanced driving assistance, it is necessary to acquire highly accurate road information relative to the vehicle's position. To achieve this, it is necessary not only to improve the accuracy of map information, but also to improve the accuracy of the correlation between the vehicle's position and the map information, in other words, the accuracy of matching the vehicle's position accurately on the map. However, the vehicle positioning information obtained from satellites may occasionally contain errors, which may cause errors in the relative relationship between the vehicle position and the map information, which may also result in a deterioration in the accuracy of road information obtained from the map information for the vehicle position.

[0004] As a countermeasure, a means is being considered for correcting the relative relationship between the vehicle's position and road information using a monitoring device or the like mounted on the vehicle. For example, Patent No. 3692910 uses information obtained from a camera mounted on the vehicle that captures the view ahead in the direction of travel. It discloses a means for comparing road information, particularly road curvature information, obtained from the forward image information captured by this camera with road information obtained from a map, and correcting the vehicle's position based on the comparison results and the road information obtained from the map. [Prior art documents] [Patent documents]

[0005] [Patent Document 1] Patent No. 3692910 Summary of the Invention [Problem to be solved by the invention]

[0006] When a camera capturing an image of the area ahead in the direction of travel is used, as in Patent No. 3692910, such a camera captures an image over a wide range, even at a relatively long distance. Therefore, due to factors such as large changes in road shape, it may not be possible to obtain highly accurate road information, particularly on roads with a large curvature or gradient. Furthermore, since such a camera capturing an image of the area ahead in the direction of travel is positioned with its optical axis at an angle relatively close to horizontal, factors such as halation or reduced contrast due to the influence of direct light, such as the setting sun, may reduce the accuracy of detecting road information. As the accuracy of the road information obtained from the camera decreases in this way, the accuracy of the comparison results with road information obtained from a map also decreases, making it difficult to improve the accuracy of correcting the vehicle's position relative to the road information obtained from a map.

[0007] The present disclosure has been made to solve the above-mentioned problems, and aims to provide a road information correction device that can correct road information obtained using vehicle positioning information and map information with higher accuracy regardless of the influence of road shape or the setting sun, etc. [Means for solving the problem]

[0008] The road information correction device according to the present disclosure includes: a first road information acquisition unit that acquires first road information for the vehicle position based on the vehicle position measurement information and map information; Position information of the left and right lane markings of the lane in which the vehicle is traveling, acquired from a surroundings monitoring device; Vehicle state quantities including information on the speed and yaw rate of the host vehicle acquired from a vehicle state quantity monitoring device; a second road information acquisition unit that generates second road information for a host vehicle position based on the plurality of pieces of left and right lane line position information acquired over time and the vehicle state quantity; a correction amount calculation unit that uses the second road information as comparative road information and calculates a correction amount for the first road information based on the first road information and the comparative road information; The road information correction unit corrects either or both of the vehicle position and the first road information based on the correction amount calculated by the correction amount calculation unit. [Effects of the Invention]

[0009] According to the road information correction device of the present disclosure, the relative relationship between the vehicle position and road information can be corrected using left and right lane marking position information obtained from a surrounding monitoring device, thereby making it possible to correct road information with higher accuracy regardless of the influence of road shape or the setting sun, etc. [Brief explanation of the drawings]

[0010] [Figure 1] 1 is a block diagram showing the overall configuration of a road information correction device according to a first embodiment, including peripheral devices. [Figure 2] 1 is a schematic hardware configuration diagram of a road information correction device according to a first embodiment. [Figure 3] FIG. 4 is a schematic hardware configuration diagram of another example of the road information correction device according to the first embodiment. [Figure 4] FIG. 3 is a schematic diagram for explaining first road information according to the first embodiment. [Figure 5] FIG. 4 is a schematic diagram for explaining second road information according to the first embodiment. [Figure 6] 6 is a flowchart showing the processing of a second road information acquisition unit according to the first embodiment. [Figure 7] 4 is a schematic diagram for explaining the coordinate conversion process of the second road information acquisition unit according to the first embodiment. FIG. [Figure 8] 2 is a schematic diagram for explaining the position of a lane marking detected by the periphery monitoring device according to the first embodiment. FIG. [Figure 9] 5 is a flowchart showing the process of a correction amount calculation unit according to the first embodiment. [Figure 10]5 is a schematic diagram for explaining a point cloud position change process of a correction amount calculation unit according to the first embodiment. FIG. [Figure 11] 5 is a schematic diagram for explaining a comparable area calculation process by the correction amount calculation unit according to the first embodiment. FIG. [Figure 12] 4 is a schematic diagram for explaining a correction amount calculation process of a correction amount calculation unit according to the first embodiment. FIG. [Figure 13] FIG. 10 is a block diagram showing a schematic configuration of a road information correction device according to a second embodiment. [Figure 14] 10 is a flowchart showing the process of a correction amount calculation unit according to the second embodiment. [Figure 15] FIG. 10 is a block diagram showing a schematic configuration of a road information correction device according to a third embodiment. [Figure 16] 11 is a flowchart showing the process of a correction amount calculation unit according to the third embodiment. DETAILED DESCRIPTION OF THE INVENTION

[0011] Embodiment 1 A road information correction device according to a first embodiment will be described with reference to the drawings. This type of road information correction device is often incorporated into various driving assistance devices that use road information. Examples of driving assistance devices include lane keeping assistance devices, traffic jam driving assistance devices, adaptive cruise control assistance devices, and automatic driving devices.

[0012] <Overall structure> FIG. 1 shows the overall configuration of a road information correction device 10 including peripheral devices. The map information 21 contains desired information required for driving assistance, etc., for the entire target area, and includes at least road lane marking position information. The vehicle position measurement information 22 is position measurement information of the vehicle's position obtained from a satellite. The vehicle state quantity monitoring device 23 acquires vehicle state quantities including information on the vehicle's speed and yaw rate. The periphery monitoring device 24 is a side camera mounted on the underside of the left and right door mirrors, and acquires left and right lane marking position information in the vicinity of the vehicle. Note that the periphery monitoring device 24 is not limited to a side camera, and may be, for example, a LiDAR (Lidar) or the like, as long as it can acquire lane marking position information in the vicinity of the vehicle.

[0013] The drive control device 31, the electric steering device 32, the output control device 33, and the electric brake device 34 constitute part of the driving assistance device. The control information 40 is various information required for the desired driving assistance, such as a target vehicle speed and a target steering angle. The electric steering device 32 controls the steering angle of the host vehicle. The output control device 33 controls the output of the drive source of the host vehicle. The electric brake device 34 controls the braking force of the host vehicle. The drive control device 31 controls the electric steering device 32, the output control device 33, and the electric brake device 34 based on the road information output from the road information correction device 10 and the control information 40. For example, in a lane keeping assist device, the shape of the lane ahead of the vehicle (curvature, gradient, etc.) is determined from road information as a more advanced driving assistance, and at least one of the electric steering device 32, the output control device 33, and the electric brake device 34 is controlled to perform steering angle control and acceleration / deceleration control appropriate for the determined shape. Note that the drive control device 31, the electric steering device 32, the output control device 33, and the electric brake device 34 are not limited to the configuration shown in FIG. 1 as long as they can control the steering angle, vehicle speed, or acceleration / deceleration of the vehicle.

[0014] <Road information correction device> The road information correction device 10 has, as functional blocks, a first road information acquisition unit 11, a second road information acquisition unit 12, a correction amount calculation unit 13, and a road information correction unit 14.

[0015] The first road information acquisition unit 11 acquires first road information including road dividing line position information relative to the host vehicle position, based on the host vehicle position measurement information 22 and map information 21. The second road information acquisition unit 12 generates second road information including road dividing line position information relative to the host vehicle position, based on the vehicle state quantity monitoring device 23 and the periphery monitoring device 24. Here, the road dividing line position information for the host vehicle position included in the first road information and the road dividing line position information for the host vehicle position included in the second road information are acquired or generated based on different information.

[0016] The correction amount calculation unit 13 uses the second road information as comparative road information for the first road information. The correction amount calculation unit 13 calculates a correction amount for the first road information based on the first road information and the comparative road information. The road information correction unit 14 corrects either or both of the vehicle position and the first road information based on this correction amount.

[0017] As shown in FIG. 2, the road information correction device 10 includes a processing unit 90 such as a CPU (Central Processing Unit), a storage device 91, and an input / output device 92 for inputting and outputting external signals to the processing unit 90, thereby realizing the functions of each of the functional blocks 11 to 14.

[0018] The arithmetic processing device 90 may be an ASIC (Application Specific Integrated Circuit), an IC (Integrated Circuit), a DSP (Digital Signal Processor), an FPGA (Field Programmable Gate Array), a GPU (Graphics Processing Unit), an AI (Artificial Intelligence) chip, various logic circuits, various signal processing circuits, etc. Furthermore, the arithmetic processing device 90 may be a plurality of the same or different types, and each process may be shared and executed. The storage device 91 may be a variety of storage devices, such as a RAM (Random Access Memory), a ROM (Read Only Memory), a flash memory, an EEPROM (Electrically Erasable Programmable Read Only Memory), a hard disk, etc.

[0019] The input / output device 92 is equipped with an input / output port, a drive circuit, a communication device, an A / D converter, etc. The input / output device 92 is connected to the map information 21, the vehicle position measurement information 22, the vehicle state quantity monitoring device 23, the surroundings monitoring device 24, the drive control device 31, etc., and communicates with these devices.

[0020] The functions of the functional blocks 11 to 14 provided in the road information correction device 10 are realized by the arithmetic processing device 90 executing software (programs) stored in the storage device 91 and cooperating with other hardware of the road information correction device 10, such as the storage device 91 and the input / output device 92. Note that setting data used by the functional blocks 11 to 14, etc., is stored in the storage device 91, such as an EEPROM.

[0021] Alternatively, the road information correction device 10 may be provided with dedicated hardware 93 as a processing circuit, as shown in FIG. 3, such as a single circuit, a composite circuit, a programmed processor, a parallel programmed processor, an ASIC, an FPGA, a GPU, an AI chip, or a circuit that combines these.

[0022] The operation of each of the functional blocks 11 to 14 of the road information correction device 10 will be described in detail below. <1st Road Information Acquisition Department> The first road information acquisition unit 11 acquires first road information including road dividing line position information relative to the vehicle position, based on the vehicle position measurement information 22 and map information 21. An example of the first road information is shown in Fig. 4. The first road information includes point cloud information that expresses at least the positions of road dividing lines as a point cloud, and the point cloud information is expressed in two-dimensional coordinates with host vehicle A as the origin, the traveling direction of host vehicle A as the x-axis, and the left and right directions relative to the traveling direction as the y-axis. In addition to the point cloud information, the first road information may also include desired information required for driving assistance, for example.

[0023] <Second road information acquisition section> The second road information acquisition unit 12 generates second road information including lane dividing line position information relative to the vehicle position based on the vehicle state quantity monitoring device 23 and the surroundings monitoring device 24. An example of the second road information is shown in Figure 5. The second road information includes point cloud information that represents the positions of multiple left and right lane markings acquired over time as a point cloud. If the current time is t2, the previous time is t1, and the time before that is t0, then one lane marking has been detected on each side of the host vehicle's positions A0, A1, and A2 at each time, and Figure 5 includes points indicating a total of six lane marking detection positions.

[0024] Here, the second road information is the lane marking detection position acquired at the current time t2 using the periphery monitoring device 24, and the lane marking detection positions acquired and stored at the previous time t1 and the time t0 before that using the periphery monitoring device 24. Note that the lane marking detection positions acquired at the previous time t1 and the time t0 before that have been converted into position information in a coordinate system with the current host vehicle position as the origin, based on information from the vehicle state quantity monitoring device 23.

[0025] The side cameras, which are the periphery monitoring device 24, capture images of a relatively narrow range around the vehicle. Therefore, deterioration of detection accuracy due to factors such as large changes in road shape is unlikely to occur. In addition, because the optical axis of the side cameras is directed relatively downward, deterioration of detection accuracy due to halation or reduced contrast caused by direct light such as the setting sun is unlikely to occur.

[0026] On the other hand, the side camera serving as the perimeter monitoring device 24 has a narrow imaging range, so the detection range that can be obtained each time is limited. For example, in FIG. 5, only one lane line detection position is obtained on each side at each time. However, in the present disclosure, multiple lane line position information obtained over time is used in combination, so that detection accuracy does not deteriorate even on roads with large curvatures or gradients, and road information can be obtained over a wide detection range. For example, in FIG. 5, a total of six lane line detection positions can be obtained, three on each side.

[0027] The processing of the second road information acquisition unit 12 is shown in the flowchart of FIG. In step S101, the vehicle speed and yaw rate of the host vehicle are obtained from the vehicle state quantity monitoring device 23.

[0028] In step S102, the lane marking position information is acquired from the periphery monitoring device 24. In step S102, if it is determined that the detection reliability of the lane marking obtained from the periphery monitoring device 24 is low or that the lane marking position information obtained from the periphery monitoring device 24 is an erroneous detection, the lane marking position information obtained from the periphery monitoring device 24 is replaced with a value indicating invalidity (hereinafter referred to as an invalid value). One method for determining whether lane marking position information has been detected as incorrect is to store lane marking positions that have previously been determined not to be abnormal, compare the stored lane marking positions with lane marking positions acquired from the periphery monitoring device 24, and determine an incorrect detection if the lane marking position acquired from the periphery monitoring device 24 is a value that deviates from the stored past lane marking positions. Note that if past lane marking position information is not stored, such as when the road information correction device is started, the determination of incorrect detection of lane marking position information is skipped, and only the detection reliability of the periphery monitoring device 24 is determined.

[0029] Furthermore, when detecting lane markings using the perimeter monitoring device 24, in locations where road markings other than lane markings, such as deceleration road markings, are painted on the road, depending on the device used, the other road markings may be detected as lane markings. Therefore, it is determined whether other road markings have been detected instead of lane markings, and if a road marking has been detected, the value acquired from the perimeter monitoring device 24 is corrected in step S102 from the road marking position to the lane marking position.

[0030] Whether other road markings have been detected can be determined by using the lane width calculated based on the left and right lane marking position information acquired by the periphery monitoring device 24. When a road marking is detected, the lane width changes by a certain amount compared to when lane marks have been detected. Therefore, when the lane width calculated from the left and right lane marking positions changes by a certain amount, the periphery monitoring device 24 determines that it has detected a road marking rather than a lane marking. In addition, correction from the road marking position to the lane marking position is possible by correcting the value detected by the periphery monitoring device 24 by the amount of the change in lane width.

[0031] In step S103, coordinate conversion of the second road information is performed. An example of coordinate conversion of the second road information is shown in FIG. Each point in the second road information is expressed in two-dimensional coordinates with host vehicle A as the origin, the direction of travel of host vehicle A as the x-axis, and the left and right directions relative to the direction of travel as the y-axis. If the current time is T1 and the previous time is T0, then LP1-LP3 and RP1-RP3 in the second road information represent the lane marking positions as seen from host vehicle A at time T0. Therefore, when time T1 arrives and host vehicle A has moved, LP1-LP3 and RP1-RP3 must be converted to lane marking positions LP1'-LP3' and RP1'-RP3' as seen from the position of host vehicle A at time T1. Therefore, in step S103, the amount of movement of the host vehicle since the previous time is calculated from the vehicle speed and yaw rate acquired from the vehicle state quantity monitoring device 23, and the second road information is coordinate-converted based on the amount of movement of the host vehicle so that the coordinates of the second road information are converted from those relative to the previous host vehicle position to those relative to the current host vehicle position.

[0032] In step S104, points that have been stored for a predetermined time or longer are deleted from the point cloud of the second road information. The second road information stores previously detected lane marking positions while performing coordinate transformation based on vehicle state quantities. However, it is conceivable that vehicle speed and yaw rate information may contain slight errors due to noise from the device, etc. Therefore, the more repeatedly coordinate transformations using vehicle speed and yaw rate information are performed, the more errors accumulate, raising concerns that the accuracy of the stored lane marking position information may deteriorate. Therefore, in step S104, points that have been stored for a predetermined time or longer are deleted from the point cloud of the second road information. Note that instead of a predetermined time, it is also possible to count the number of coordinate transformations and delete points that have undergone a predetermined number of coordinate transformations or more.

[0033] In step S105, it is determined whether the lane marking position information acquired in step S102 is an invalid value. If it is not an invalid value, the process proceeds to step S106, and if it is an invalid value, the process proceeds to step S107.

[0034] In step S106, the lane marking position information acquired in step S102 is added to the second road information. If the storage area of ​​the second road information is insufficient, the lane marking position information that has been stored for the longest time among the lane marking position information stored in the second road information is deleted, and the lane marking position information acquired in step S102 is newly added.

[0035] In step S107, it is determined whether the second road information needs to be reset. The reset determination is made when the erroneous detection determination of the lane marking position information performed in step S102 is determined to be an erroneous detection a predetermined number of times or more in succession.

[0036] In the false detection determination performed in step S102, there are two possible cases in which a false detection is determined to have occurred a predetermined number of times in succession: a case in which there is an error in the lane marking position information stored in the second road information, and a case in which the lane marking position detected by the perimeter monitoring device 24 changes.

[0037] A case in which the lane marking position information stored in the first second road information is erroneous occurs when the periphery monitoring device 24 detects erroneous lane marking position information when no lane marking position information is stored in the second road information, such as when the road information correction device system is started. When no lane marking position information is stored in the second road information, no erroneous detection determination of the lane marking position information is performed in step S102, so lane marking position information is stored in the second road information even if there is an error in the lane marking position information. After that, even if the periphery monitoring device 24 detects correct lane marking position information, it is compared with the stored erroneous lane marking position information in the erroneous detection determination of the lane marking position information, so even if correct lane marking position information is detected, it continues to be determined to be an erroneous detection.

[0038] A second case in which the position of the lane marking detected by the periphery monitoring device 24 changes is, for example, when the road on which the vehicle is traveling changes from a section without white lines to a section with white lines, as shown in FIG. 8. When there are no white lines, the periphery monitoring device 24 detects the position of L1, which is the boundary between the shoulder and the roadway, as a lane marking. Therefore, the lane marking position information for L1 is stored in the second road information. After that, when a white line appears, the periphery monitoring device 24 detects the position of L2 as a lane marking. However, because the lane marking position information for L1 is stored in the second road information, the lane marking position information for L2 is determined to be an erroneous detection in the erroneous detection determination in step S102, and therefore cannot be stored in the second road information.

[0039] In such a case, the number of times that erroneous detection is determined in the erroneous detection determination of the lane marking position information performed in step S102 must be counted, and if erroneous detection is determined to occur a predetermined number of times or more consecutively, a reset process is required. In both cases, where there is an error in the lane marking position information stored in the second road information, and where the lane marking position changes, erroneous detection determinations will be repeated unless the second road information is reset. On the other hand, if the perimeter monitoring device 24 erroneously detects a lane marking, the erroneous detection is unlikely to continue for a long period of time, and in most cases, the lane marking will be detected correctly within a short period of time. In such cases where the perimeter monitoring device 24 temporarily detects a lane marking, it is not desirable to reset the second road information. Therefore, when determining whether to reset, it is important to consider whether erroneous detection has been determined to occur a predetermined number of times or more consecutively in the erroneous detection determination process.

[0040] If it is determined in step S107 that a reset is necessary, the process proceeds to step S108, whereas if it is determined that a reset is not necessary, the process of the second road information acquisition unit 12 ends.

[0041] In step S108, all the lane marking position information stored as the second road information is deleted, and then the processing of the second road information acquisition unit 12 is terminated.

[0042] <Correction amount calculation section> The processing of the correction amount calculation unit 13 is shown in the flowchart of Fig. 9. The correction amount calculation unit 13 compares the road dividing line position information for the host vehicle position included in the first road information with the road dividing line position information for the host vehicle position included in the second road information, which is the comparison road information, and calculates the correction amount by which to correct the first road information.

[0043] In step S201, the correction amount is initialized to 0. The correction amount includes at least a rotation angle for rotating the entire first road information and a translation amount for translating the entire first road information.

[0044] In step S202, the point cloud positions of the second road information are changed. The first road information and the second road information are point cloud information expressed in two-dimensional coordinates with host vehicle A as the origin, the traveling direction of host vehicle A as the x-axis, and the left and right directions relative to the traveling direction as the y-axis. However, as shown on the left side of Fig. 10, the x-positions of each point in the first road information and the second road information do not match. Therefore, in step S202, the x-positions of each point in the second road information are changed so that they match the x-positions of each point in the first road information.

[0045] To change the x-position, first, the point cloud of the second road information is converted into approximate curve information by polynomial approximation. Then, by substituting each x-position of the first road information into the approximate curve information, it is possible to obtain a point cloud with the same x-position as the first road information, as shown on the right side of Figure 10.

[0046] The second road information stores the lane marking positions detected by the perimeter monitoring device 24 as a point cloud, but points that have been stored for a long period of time may have deteriorated accuracy. Therefore, when performing polynomial approximation, a process may be added to remove points that have been acquired for a period of time greater than or equal to a threshold from the approximation. This prevents the approximation accuracy from deteriorating because the approximation does not include points that are likely to have deteriorated accuracy. The period of time greater than or equal to the threshold may be determined by time or the number of times the point has been used in processing.

[0047] In step S203, a comparable area between the first road information and the second road information is calculated. The comparable area represents the location where the x-positions of each point in the first road information and the second road information overlap. An example of calculating the comparable area is shown in FIG. 11. In FIG. 11, three points, -10m, 0m, and 10m in the x-position, overlap between the first road information and the second road information. Therefore, the comparable area is -10m to 10m, and the comparable distance between the first road information and the second road information is 20m.

[0048] When calculating the comparable area, even if the x-positions of the first road information and the second road information overlap, processing may be added to exclude areas that are more than a certain distance away from the vehicle as non-comparable areas. The second road information stores multiple lane marking positions detected over time by the perimeter monitoring device 24 as a point cloud, so the accuracy is generally higher the closer to the vehicle and worsens the further away. If areas where accuracy is likely to be poor are included in the comparable area, there is a possibility that the correct correction amount will not be calculated. Therefore, by defining areas that are more than a certain distance away from the vehicle as non-comparable areas and excluding them from the comparable area, the possibility of calculating an incorrect correction amount can be reduced.

[0049] In step S204, it is determined whether the comparable distance between the first road information and the second road information is equal to or greater than a threshold. If the comparable distance is less than the threshold, the process of the correction amount calculation unit 13 ends. If the comparable distance is equal to or greater than the threshold, the process proceeds to step S205.

[0050] If the comparable distance is less than the threshold, there are few comparison points between the first road information and the second road information, so there is a possibility that a highly accurate correction amount cannot be calculated. If the first road information is corrected using a low-accuracy correction amount, there is a concern that the accuracy of the first road information will also deteriorate. Therefore, if the comparable distance between the first road information and the second road information is less than the threshold, the correction amount is not calculated and the processing of the correction amount calculation unit 13 is terminated. This makes it possible to prevent the first road information from being corrected using a low-accuracy correction amount.

[0051] In step S205, the amount of correction for correcting the first road information is calculated. First, as shown in FIG. 12, each point of the first road information and the second road information existing in the comparable area is compared, and the deviation (E1, E2, E3) of each point is calculated. Then, the entire first road information is translated and rotated to search for the position where the sum of the deviations (E1, E2, E3) of each point is minimum. The position where the sum of the deviations is minimum is then found, and the rotation angle and translation amount for moving the first road information to that position are calculated as the amount of correction.

[0052] In step S206, it is determined whether the first road information and the second road information deviate by more than a threshold value. If the first road information and the second road information do not deviate by more than a threshold value, the process of the correction amount calculation unit 13 ends. If the deviation is more than the threshold value, the process proceeds to step S207. In step S207, the correction amount is set to 0. Thereafter, the process of the correction amount calculation unit 13 ends.

[0053] To determine whether the first road information and the second road information deviate by more than a threshold value, for example, if the correction amount calculated in step S205 is greater than or equal to a threshold value, it is determined that the first road information and the second road information used in the calculation deviate by more than the threshold value. If the shapes of the first road information and the second road information differ significantly, correcting the first road information with a correction amount calculated from the two significantly different pieces of road information may actually worsen the accuracy of the first road information. Therefore, the system determines whether the first road information and the second road information differ by more than a threshold, and if they do, sets the correction amount to 0 so that the first road information is not corrected.

[0054] As a method for determining whether the first road information and the second road information deviate by more than a threshold value, a method may be used in which the deviation of each point between the first road information and the second road information is calculated as shown in FIG. 12, and if any one of the deviations of each point exceeds the threshold value, it is determined that the first road information and the second road information deviate.

[0055] <Road Information Correction Unit> The road information correction unit 14 relatively corrects the first road information with respect to the vehicle position, using the rotation angle and translational movement amount, which are the correction amounts calculated by the correction amount calculation unit 13. The corrected road information is sent to a driving assistance device (not shown), etc. This makes it possible to obtain road information corrected with higher accuracy, which in turn makes it possible to implement more advanced driving assistance, etc.

[0056] Embodiment 2 A road information correction device according to the second embodiment will be described with reference to the drawings. <Road information correction device> The schematic configuration of the road information correction device is shown in Fig. 13. In addition to the configuration of the first embodiment, it has a forward monitoring device 25 and a third road information acquisition unit 15. Accordingly, the processing of the correction amount calculation unit 13 also differs partly from that of the first embodiment.

[0057] The forward monitoring device 25 is a front camera provided in front of the vehicle, and acquires position information of left and right lane lines ahead of the vehicle. Note that the forward monitoring device 25 is not limited to a front camera, and may be, for example, a radar, LiDAR (lidar), or the like, as long as it can acquire position information of lane lines ahead of the vehicle.

[0058] <Third Road Information Acquisition Department> The third road information acquisition unit 15 acquires third road information including lane marking position information relative to the vehicle position based on the forward monitoring device 25. Here, the forward camera serving as the forward monitoring device 25 captures images over a wide range up to a relatively long distance, and therefore does not need to acquire lane marking position information over time as the second road information acquisition unit 12 does. When the left and right lane marking information is obtained as approximate curve information from the forward monitoring device 25, the obtained approximate curve information is set as the third road information. When the left and right lane marking information is obtained as point cloud information from the forward monitoring device 25, the point cloud is polynomial-approximated to obtain approximate curve information, and the obtained approximate curve information is set as the third road information.

[0059] <Correction amount calculation section> The processing of the correction amount calculation unit 13 is shown in the flowchart of Fig. 14. In addition to the processing of the first embodiment, steps S208 and S209 are included. Functionally speaking, in the first embodiment, the second road information is always used as the comparison road information. In contrast, in the second embodiment, either the second road information or the third road information is selectively used as the comparison road information.

[0060] In step S208, based on the third road information acquired by the third road information acquisition unit 15, point cloud information expressed in two-dimensional coordinates with the x-axis representing the direction of travel of the vehicle A and the y-axis representing the left and right directions relative to the direction of travel is acquired.

[0061] As a method for acquiring point cloud information, since the third road information is represented by an approximate curve, the x-position of each point of the first road information is substituted into the approximate curve of the third road information to generate point cloud information. This makes it possible to acquire a point cloud of the third road information that has the same x-position as the first road information.

[0062] In step S209, comparative road information to be compared with the first road information in order to calculate the correction amount is selected, either the second road information or the third road information.

[0063] The method of selecting the comparison road information is as follows: if the reliability of the third road information is equal to or greater than a threshold, i.e., if the reliability is high, the third road information is selected as the comparison road information; and if the reliability of the third road information is less than the threshold, i.e., if the reliability is low, the second road information is selected as the comparison road information.

[0064] As a method for determining the reliability of the third road information, for example, there is a method of obtaining the detection reliability of the lane markings from the forward monitoring device 25 and using that reliability as the reliability of the third road information. Another method is to obtain curvature or gradient information of the road on which the vehicle is traveling, and if the curvature or gradient information is equal to or greater than a predetermined value, determine that the reliability of the third road information is below a threshold, i.e., low.

[0065] In the third road information obtained using the forward camera, the detection accuracy of road information may be reduced due to factors such as large changes in road shape, halation caused by direct light such as the setting sun, or reduced contrast, etc. However, in other circumstances, it is a great advantage to be able to easily obtain road information over a wide range ahead of the vehicle in the traveling direction.

[0066] Therefore, by selectively using either the second road information or the third road information as comparison road information based on the reliability of the third road information, it is possible to combine the advantages of each road information and calculate a more accurate correction amount.

[0067] In step S203, a comparable area of ​​road information is calculated based on the first road information and the comparison road information, and in step S204, the calculated comparable distance is determined. Then, in step S205, the first road information and the comparison road information are compared to calculate a correction amount. In step S206, it is determined whether the first road information and the comparison road information deviate from each other. In step S207, if there is a deviation between the first road information and the comparison road information, the correction amount is changed to an invalid value. Note that the processes from step S203 to step S207 have been explained in embodiment 1, so detailed explanation will be omitted.

[0068] In the second embodiment, third road information is added, and the first road information is corrected with either the second road information or the third road information. The third road information is based on sensing information from the forward monitoring device 25 that acquires road information ahead of the host vehicle, and therefore is road information ahead of the host vehicle. On the other hand, the second road information is stored sensing information from the periphery monitoring device 24 that acquires road information around the host vehicle, and therefore is road information from the vicinity of the host vehicle to the rear of the host vehicle. Furthermore, while the second road information includes road information that has been stored in the past, the third road information is information sensed in real time. Therefore, in order to provide driving assistance, correcting the first road information using the third road information, which is real-time road information in the traveling direction of the vehicle, is likely to improve the accuracy of the first road information. However, the accuracy of the third road information decreases depending on the road environment, such as roads with a large curvature or gradient. Therefore, in the second embodiment, when the reliability of the third road information is high, the first road information is corrected using the third road information, and when the reliability of the third road information is low, the first road information is corrected using the second road information. This makes it possible to improve the accuracy of the first road information according to various road environments.

[0069] Embodiment 3 A road information correction device according to the third embodiment will be described with reference to the drawings. <Road information correction device> The schematic configuration of the road information correction device is shown in Fig. 15. In addition to the configuration of the second embodiment, it has a correction amount estimating unit 16. Accordingly, the processing of the correction amount calculating unit 13 also differs in part from that of the second embodiment.

[0070] <Correction amount estimator> The correction amount estimation unit 16 calculates the current estimated correction amount based on the previous correction amounts calculated by the correction amount calculation unit 13 based on the first road information and the comparative road information. As a means for estimating the correction amount, for example, a method using a Kalman filter is available. As another means, a method may be used in which a neural network, such as an RNN (Recurrent Neural Network) or an LSTM (Long Short Term Memory), is used to learn the correction amount and calculate the estimated correction amount.

[0071] <Correction amount calculation section> The processing of the correction amount calculation unit 13 is shown in the flowchart of Figure 16. Compared to the processing of the first embodiment, steps S210, S211, S212, and S213 are added, and step S207 is deleted. Functionally speaking, when the reliability of the comparison road information is below a threshold, i.e., when the reliability is low, an estimated correction amount is used as the correction amount.

[0072] In step S210, it is determined whether the reliability of the comparison road information is high. Since the comparison road information is either the second road information or the third road information, the reliability of the comparison road information will be the reliability of the second road information if the second road information is selected, or the reliability of the third road information if the third road information is selected. If the reliability of the comparison road information is high, proceed to step S203; if the reliability of the comparison road information is low, proceed to step S211.

[0073] Here, one method for determining the reliability of the second road information is to determine the reliability as high if there are many points in the point cloud of the second road information that have been stored for a period less than a threshold, and to determine the reliability as low if there are few points that have been stored for a period less than the threshold. The shorter the period for which stored points have been stored, the less the influence of errors due to coordinate transformation and the higher the accuracy. On the other hand, if lane marking position information is no longer available from the perimeter monitoring device 24, new road information will not be added to the second road information, and the second road information will contain a lot of road information that has been stored a long time ago and has reduced accuracy. Therefore, the reliability of the second road information can be determined by using the period since storage.

[0074] As another method, the reliability of the second road information may be determined by acquiring the detection reliability of the lane markings from the periphery monitoring device 24. For example, the detection reliability acquired from the periphery monitoring device 24 is stored in the second road information. The detection reliability can be acquired in six levels from 0 to 5, with the closer to 5 the reliability is, the higher the reliability is. In step S102 shown in FIG. 6, if the detection reliability acquired from the periphery monitoring device 24 is low, the detected road information is not added to the second road information. If the threshold for determining that the detection reliability is low is set to 1 or less, the second road information stores road information with detection reliability levels of 2 to 5. If the road information stored in the second road information contains a large amount of road information with detection reliability levels of 2 and 3, the reliability of the second road information is determined to be low, and if the road information contains a large amount of road information with detection reliability levels of 4 and 5, the reliability of the second road information is determined to be high.

[0075] It should be noted that if the comparable distance is not equal to or greater than the threshold in step S204, or if there is a discrepancy between the first road information and the comparative road information in step S206, the process also proceeds to step S211.

[0076] In step S211, the estimated correction amount is used as the correction amount used to correct the first road information.

[0077] In step S212, the time during which the estimated correction amount is used as the correction amount for the first road information is measured, and it is determined whether the measured time is equal to or longer than a predetermined time. If the measured time is not equal to or longer than the predetermined time, the processing of the correction amount calculation unit 13 is terminated. If the measured time is equal to or longer than the predetermined time, the processing proceeds to step S213. Note that step S212 may be any step as long as it determines whether the period during which the estimated correction amount is used is equal to or longer than a threshold, and may, for example, determine whether the number of times the estimated correction amount is continuously used is equal to or longer than a threshold.

[0078] In step S213, the correction amount is changed to 0, and the processing of the correction amount calculation unit 13 ends.

[0079] The estimated correction amount is estimated based on the correction amount calculated previously based on the first road information and the comparative road information. When the estimated correction amount is used as the correction amount for the first road information, the second road information and the third road information are unavailable, so the correction amount based on the first road information and the comparative road information is not calculated. However, if the second road information and the third road information are unavailable for a long period of time, the correction amount used as the basis for the estimation also becomes outdated, and the accuracy of the correction amount estimation deteriorates. Therefore, when an estimated correction amount is used as the correction amount for the first road information, an upper limit is set on the period, and if the estimated correction amount is used as the correction amount for a period equal to or longer than the threshold, the correction of the first road information is terminated.

[0080] In the third embodiment, an estimated correction amount is added, and the first road information is corrected with either the second road information, the third road information, or the estimated correction amount.

[0081] As explained in the second embodiment, it is desirable to correct the first road information using the third road information when the reliability of the third road information is high, and to correct the first road information using the second road information when the reliability of the third road information is low. However, there may be cases where both the second road information and the third road information cannot be used, such as when the vehicle passes through road conditions where there are temporarily no lane markings or lane markings are difficult to detect. Even in such cases, the accuracy of the first road information can be improved by using the estimated correction amount. The third road information uses real-time sensing information, and the second road information uses stored sensing information. In contrast, the estimated correction amount predicts the current correction amount based on the correction amount previously calculated using the second road information or the third road information. Therefore, the highest accuracy in correcting the first road information is achieved when the third road information is used, the second road information is used, or the estimated correction amount is used, in that order of accuracy. Therefore, the estimated correction amount is used when neither the second road information nor the third road information is available.

[0082] Although exemplary embodiments and examples are described in this disclosure, the features, aspects, and functions described in one or more embodiments are not limited to the application of a particular embodiment, but may be applied to the embodiments alone or in various combinations. Therefore, countless variations not illustrated are contemplated within the scope of the technology disclosed in this disclosure specification. For example, this includes cases where at least one component is modified, added, or omitted, and even cases where at least one component is extracted and combined with components of other embodiments. [Explanation of symbols]

[0083] 10: Road information correction device, 11: First road information acquisition unit, 12: Second road information acquisition unit, 13: Correction amount calculation unit, 14: Road information correction unit, 15: Third road information acquisition unit, 16: Correction amount estimation unit, 21: Map information, 22: Vehicle position measurement information, 23: Vehicle state quantity monitoring device, 24: Surroundings monitoring device, 25: Forward monitoring device

Claims

1. a first road information acquisition unit that acquires first road information relative to the vehicle position based on the vehicle position measurement information and map information; Position information of the left and right lane markings of the lane in which the vehicle is traveling, acquired from a surroundings monitoring device; Vehicle state quantities including information on the speed and yaw rate of the host vehicle acquired from a vehicle state quantity monitoring device; a second road information acquisition unit that generates second road information relative to a host vehicle position based on the plurality of pieces of left and right lane line position information acquired over time and the vehicle state quantity; a correction amount calculation unit that uses the second road information as comparative road information and calculates a correction amount for the first road information based on the first road information and the comparative road information; A road information correction device including a road information correction unit that corrects either or both of the vehicle position and the first road information based on the correction amount calculated by the correction amount calculation unit.

2. a forward monitoring device that monitors the front of the vehicle; a third road information acquisition unit that acquires third road information for a vehicle position from the forward monitoring device; The road information correction device according to claim 1, characterized in that the correction amount calculation unit uses the second road information as the comparison road information when it determines that the reliability of the third road information is less than a threshold, and uses the third road information as the comparison road information when it determines that the reliability of the third road information is equal to or greater than a threshold.

3. a correction amount estimation unit that estimates a current correction amount based on the correction amount calculated previously by the correction amount calculation unit; The road information correction device according to claim 2, characterized in that, when the correction amount calculation unit determines that the reliability of the comparison road information is less than a threshold, it calculates the correction amount based on the estimated value of the correction amount estimation unit.

4. 4. The road information correction device according to claim 1, wherein the surroundings monitoring device is a side camera provided on the left and right sides of the vehicle.

5. the second road information acquisition unit acquires the current left and right lane marking line position information from the surroundings monitoring device in a coordinate system with the current host vehicle position as the origin; A road information correction device as described in any one of claims 1 to 3, characterized in that the left and right lane line position information of the second road information generated last time is converted into the left and right lane line position information in a coordinate system with the current vehicle position as the origin based on the vehicle state quantity acquired this time, and the left and right lane line position information detected this time by the surroundings monitoring device is added to this converted left and right lane line position information of the previous time to generate the left and right lane line position information as the current second road information.

6. the correction amount calculation unit converts the plurality of pieces of left and right lane line position information acquired over time and included in the second road information into approximate curve information by polynomial approximation; 4. The road information correction device according to claim 1, wherein the left and right lane marking position information is excluded from the polynomial approximation if a period of time equal to or greater than a threshold has elapsed since acquisition.

7. 4. The road information correction device according to claim 3, wherein the correction amount calculation unit invalidates the correction amount when a period of time during which the correction amount based on the estimated value has been in use becomes equal to or greater than a threshold value.

8. The road information correction device according to claim 2 or 3, characterized in that the correction amount calculation unit determines that the reliability of the third road information is less than a threshold value when the curvature of the road or the gradient of the road indicated by the third road information is equal to or greater than a threshold value.

9. The road information correction device according to claim 1 or 2, characterized in that the correction amount calculation unit invalidates the correction amount when it determines that the first road information and the comparison road information deviate by more than a threshold value.

10. The road information correction device according to any one of claims 1 to 3, characterized in that the correction amount calculation unit defines an overlapping area between the first road information and the comparison road information as a comparable area, and calculates a correction amount based on the first road information and the comparison road information included in the comparable area.

11. The road information correction device according to claim 10, characterized in that the correction amount calculation unit excludes from the comparable area any area that is more than a predetermined distance away from the vehicle, even if the area is an overlapping area between the first road information and the comparison road information.

12. The road information correction device according to claim 10, characterized in that the correction amount calculation unit does not calculate a correction amount based on the first road information and the comparison road information when the comparable distance, which is the length of the comparable area, is less than a threshold value.

13. the second road information acquisition unit determines, based on the lane width of the acquired left and right lane marking position information, whether the currently acquired left and right lane marking position information is actually position information relating to lane markings or position information relating to other road markings; 4. The road information correction device according to claim 1, wherein, when it is determined that the position information is related to the other road markings, the currently acquired position information related to the other road markings is corrected to the currently assumed position information of the lane markings based on the amount of change between the previous value and the current value of the lane width.

14. the second road information acquisition unit determines whether the left and right lane marking position information acquired from the surroundings monitoring device is an erroneous detection, 4. The road information correction device according to claim 1, wherein the second road information is reset when the number of consecutive erroneous detections exceeds a threshold value.

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