Targeting device, driving control system and method for calculating a correction value for sensor data

Abstract

A target device that calculates a correction parameter for correcting a detection result of a target sensor, the target device comprising: an estimated trajectory generation unit that detects a trajectory of a target for a period in which a host vehicle is moving using information of a movement of the host vehicle detected by a motion sensor, and generates a plurality of estimated trajectories having different start point positions from the detected trajectory of the target using a first variable group; a correction trajectory generation unit that generates a plurality of corrected trajectories from the trajectory of the target around the host vehicle detected by the target sensor using a second variable group; and a correction parameter calculation unit that selects a combination in which a difference between the estimated trajectory and the corrected trajectory is small, and calculates the correction parameter for correcting a displacement of the target sensor using a first variable related to the selected estimated trajectory and a second variable related to the selected corrected trajectory.

Description

Technical FieldThe present invention relates to an in-vehicle control device, and more particularly, to a target device that corrects sensor data.Background ArtA driving support system and an autonomous driving system have been developed to achieve various purposes such as reduction of traffic accidents, reduction of loads of drivers, improvement of fuel efficiency for reducing loads of the global environment, and provision of feeble-person transportation means for realizing a persistent society. In the driving support system and the autonomous driving system, a plurality of vehicle environment monitoring sensors are provided to monitor the environment of a vehicle instead of the driver. Moreover, in order to guarantee the safety of the systems, a function of performing the correction even when the mounting angle of the vehicle surroundings monitoring sensor deviates is required.The technical background of the present technical field includes the following related art. PTL 1 (JP 2015-078925) A) discloses an environment monitoring device that determines a deviation of a detection axis of a ranging sensor from a deviation between a position in a vehicle orthogonal coordinate system set by a first position setting unit and a position in the vehicle orthogonal coordinate system set by a second position setting unit for an object existing in an overlapping area between detection areas of the ranging sensor in which an azimuth in which a reference target whose relative position to the environment monitoring device is determined as a predetermined position is included in the detection area and the ranging sensor having the detection area partially overlapping with the detection area of the ranging sensor (see Summary).In addition, PTL 2 (JP 2019-91273 A) discloses an obstacle detection device that detects an obstacle by combining a plurality of pieces of sensor information. The obstacle detection device includes a front camera that detects first parameter information regarding the obstacle, a millimeter wave radar that detects second parameter information regarding the obstacle, a correction unit that calculates an axial deviation amount of an azimuth angle of the front camera or the millimeter wave radar based on the first parameter information detected by the front camera and the second parameter information detected by the millimeter wave radar and corrects the axial deviation of the front camera or the millimeter wave radar based on the calculated axial deviation amount, and a storage unit that stores the axial deviation amount.Keep ListPatent LiteraturePTL 1: JP 2015-078925 APTL 2: JP 2010-249613 ASUMMARY OF THE INVENTIONTechnical ProblemIn PTL 1, the deviation of the detection axis of the sensor is determined based on the detection position of an object existing in the region where the detection regions of the plurality of sensors overlap each other. However, PTL 1 has a problem that it is not possible to determine the axial deviation when the detection ranges of the plurality of sensors do not overlap each other. Further, in PTL 2, the deviation of the detection axis of the sensor is determined on the basis of the second parameter information regarding the obstacle existing in the region where the detection regions of the plurality of sensors overlap each other. However, PTL 2 has a problem that, when the detection ranges of the plurality of sensors do not overlap each other, it is not possible to determine whether the first parameter and the second parameter use the same target as a basis, and thus it is not possible to determine the axial deviation.Solution of the ProblemA representative example of the invention disclosed in this application is configured as follows. That is, a target device is provided that calculates a correction parameter for correcting a detection result of a target sensor. The target device includes an estimated trajectory generation unit that detects a trajectory of a target for a period in which a host vehicle is moving using information of a movement of the host vehicle detected by a motion sensor and generates a plurality of estimated trajectories having different starting point positions from the detected trajectory of the target using a first variable group, a correction trajectory generation unit that generates a plurality of corrected trajectories from the trajectory of the target around the host vehicle detected by the target sensor using a second variable group, and a correction parameter calculation unit that calculates a combination in which a difference between the estimated trajectory and the corrected trajectory is small, and calculating the correction parameter for correcting a displacement of the target sensor using a first variable related to the selected estimated trajectory and a second variable related to the selected corrected trajectory.Advantageous Effects of the InventionAccording to the present invention, it is possible to correct the axial deviation of the sensor. Objects, configurations, and effects other than those described above will be made clear by the descriptions of the following embodiments.Brief Description of the Drawings[FIG. 1 ] FIG. 1 is a functional block diagram illustrating an embodiment of a sensor fusion device having a sensor target function according to Embodiment 1 of the present invention.[FIG. 2 ] FIG. 2 is a functional block diagram illustrating a correction parameter estimation unit in Embodiment 1.[FIG. 3] FIG. 3 is a diagram illustrating a concept of a correction parameter estimation process in Embodiment 1.[FIG. 4] FIG. 4 is a diagram illustrating a concept of a process of judging a combination of an estimated trajectory and a corrected trajectory in Embodiment 1.[FIG. 5 ] FIG. 5 is a flowchart illustrating fusion processing in Embodiment 1:[FIG. 6 ] FIG. 6 is a flowchart illustrating a process in which an evaluation function in Embodiment 1 evaluates the combination of the estimated trajectory and the corrected trajectory.[FIG. 7 ] FIG. 7 is a functional block diagram illustrating a correction parameter estimation unit in Embodiment 2.[FIG. 8] FIG. 8 is a functional block diagram illustrating a correction parameter estimation unit in Embodiment 3.[FIG. 9] FIG. 9 is a functional block diagram illustrating a correction parameter estimation unit in Embodiment 4.DESCRIPTION OF THE EMBODIMENTSIn the following, best modes for carrying out the present invention will be described in detail with reference to the drawings. In all drawings for describing modes for carrying out the invention, blocks or elements having the same function are denoted by the same reference numerals and their repeated description is omitted.< 1>FIG. 1 is a functional block diagram illustrating an embodiment of a sensor fusion device 1 having a sensor target function.As illustrated in FIG. 1, the sensor fusion apparatus 1 in the present embodiment includes a sensor coordinate transformation unit 100, a sensor timing synchronization unit 110, a correction parameter estimation unit 120, a sensor data integration unit 200, and a target detection start determination unit 340. A sensor target function is configured by units other than the sensor data integration unit 200 in the sensor fusion device 1. A sensor target device is realized by the units other than the sensor data integration unit 200 a. Output signals of a first vehicle environment monitoring sensor 10 a, a second vehicle environment monitoring sensor 10 b, a host vehicle movement detection sensor 20, and a lane marker detection sensor 30 are input to the sensor fusion device 1, and transmission detection information 40 is input to the sensor fusion device 1.The first and second vehicle surroundings monitoring sensors 10 aand 10 bare sensors that detect a target in the vicinity of the host vehicle. The host vehicle motion detection sensor 20 is a sensor group that detects the speed, the yaw rate, and the steering angle of the host vehicle. The lane marking detection sensor 30 is a sensor that detects a lane marking (e.g., a lane center line, a lane boundary line, and a lane side line formed by paint, a road nail, or the like). The transmission detection information 40 indicates a movement environment (e.g., travel map data including curvature of a roadway and the like) of the host vehicle.The sensor fusion device 1 (the electronic control device) and various sensors (a first vehicle environment monitoring sensor 10 a, a second vehicle environment monitoring sensor 10 b, and the like) in the present embodiment include a computer (a microcomputer) including an arithmetic device, a working memory, and an input / output device.The arithmetic device includes a processor and executes a program stored in the work memory. A portion of the bridge. Processing performed by the arithmetic device executing the program may be executed by another arithmetic device (e.g., hardware such as a field programmable gate array (FPGA) and an application specific integrated circuit (ASIC)).The random access memory includes a ROM and a RAM which are nonvolatile memory elements. The ROM stores a fixed program (e.g., a BIOS) and the like. The RAM includes a high-speed volatile memory element such as a dynamic read / write memory (DRAM), and a nonvolatile memory element such as a static read / write memory (SRAM). The RAM stores a program executed by the arithmetic device and data used when the program is executed.The input / output device is an interface that transmits processing contents by the electronic control device and the sensors to the outside or receives data from the outside in accordance with a predetermined protocol.The program executed by the arithmetic device is stored in the nonvolatile memory, which is a non-transitory storage medium of the electronic control device and the sensors.The sensor coordinate transformation unit 100 transforms the relative coordinates of an object (a target) outside the vehicle with respect to the host vehicle into uniform relative coordinates, and outputs the uniformed relative coordinates to the sensor timing synchronization unit 110. The relative coordinates are output from the first vehicle environment monitoring sensor 10 aand the second vehicle environment monitoring sensor 10 b. Here, the object outside the vehicle is a stationary object. The sensor fusion device 1 in the present embodiment estimates a sensor coordinate transformation correction value using the stationary object. As in Embodiment 3 described later, the object outside the vehicle may include a stationary object and a moving object, and the sensor fusion device 1 may estimate a sensor coordinate transformation correction parameter using both the stationary object and the moving object. The uniform relative coordinates refer to a coordinate system in which coordinates are collected based on the data output from a plurality of vehicle environment monitoring sensors 10 aand 10 b. For example, the center of the forward end of the host vehicle is defined as an origin, the forward direction of the host vehicle is defined as x, and the direction to the left of the host vehicle is defined as y.The detection results of the speed, the yaw rate, and the steering angle of the host vehicle by the host vehicle motion detection sensor 20 are input to the sensor timing synchronization unit 110. The sensor timing synchronization unit 110 corrects the input unified relative coordinates of the target detected by the first vehicle environment monitoring sensor 10 aand the input unified relative coordinates of the target detected by the second vehicle environment monitoring sensor 10 bto the unified relative coordinates at a predetermined timing using the detection results obtained by the host vehicle motion detection sensor 20 detecting the speed, the yaw rate, and the steering angle of the host vehicle. In addition, the sensor timing synchronization unit 110 synchronizes the timings of the detection results of the sensors with each other and outputs the unified relative coordinates of the target that are time-synchronized.The sensor data integration unit 200 integrates all pieces of input information and outputs an integration result to the travel control device 2. The driving control device 2 is an autonomous driving system (ADECU) or a driving support system that controls driving of the vehicle using an output of the sensor fusion device 1.The target detection start determination unit 340 determines that the host vehicle is in a desired traveling state (e.g., the host vehicle is traveling or is traveling on a roadway having a curvature of a predetermined value or less) based on pieces of information output from the host vehicle motion detection sensor 20, the lane marking detection sensor 30, and the transmission detection information 40, and outputs a target detection start flag to the correction parameter estimation unit 120.The correction parameter estimation unit 120 selects a target to be used to calculate the sensor coordinate transformation correction value from among the input targets. The correction parameter estimation unit 120 calculates the sensor coordinate transformation correction value of the first vehicle environment monitoring sensor 10 aand the sensor coordinate transformation correction value of the second vehicle environment monitoring sensor 10 busing the coordinate values of the target, and outputs the calculated values to the sensor coordinate transformation unit 100.FIG. 2 is a functional block diagram illustrating the correction parameter estimation unit 120 in Embodiment 1. FIG. 3 is a diagram illustrating a concept of a correction parameter estimation process. FIG. 4 is a diagram illustrating a concept of a process of judging a combination of an estimated trajectory 420 and a corrected trajectory 430. FIGS. 3 and 4 are represented in a relative coordinate system based on the host vehicle, and also a stationary target is represented in a trajectory.The correction parameter estimation unit 120 compares the estimated trajectory 420, which is a trajectory of the target predicted from the host vehicle motion, with the corrected trajectory 430, which is a trajectory of the sensor data, with the axial deviation corrected. Then, the correction parameter estimation unit 120 searches a combination in which the two lanes are close to each other, and calculates a sensor coordinate transformation correction value. The correction parameter estimation unit 120 includes a host vehicle motion calculation unit 121, an estimated trajectory generation unit 122, a correction trajectory generation unit 124, an error function 126, and an evaluation function 127.The host vehicle motion calculation unit 121 calculates the motion of the host vehicle using the detection results of the speed, the yaw rate, and the steering angle of the host vehicle by the host vehicle motion detection sensor 20.The estimated trajectory generation unit 122 generates a plurality of estimated trajectories 420 having different starting point positions using a starting point position variable 123 from the trajectory of the target predicted from the movement of the host vehicle. The movement of the host vehicle is calculated by the host vehicle movement calculation unit 121. The starting point position variable 123 is a numerical character string for setting a deviation of the starting point position that causes the estimated trajectory 420 generated by the estimated trajectory generation unit 122 to vary. The number of estimated trajectories 420 generated and the range of deviation are determined by the starting point position variable 123. A function for setting the starting point position variable 123 may be determined, and the starting point position variable 123 may be generated by such a function.For example, when sensor data 400 indicated by a thick solid line is obtained from one of the vehicle surroundings monitoring sensors 10 aor 10 band the true trajectory 410 of the target is indicated by a dotted line as illustrated in FIG. 3(A), the estimated trajectory 420 indicated by a thin solid line is generated as illustrated in FIG. 3(B). For example, when the host vehicle is moving, a stationary target moves in parallel with the traveling direction of the host vehicle. Thus, an estimated trajectory parallel to the traveling direction of the host vehicle and in accordance with the speed of the host vehicle is generated with the position (the starting point) obtained by the sensor data 400 as a reference. The starting point position of the generated estimated trajectory 420 and the starting point position of the sensor data 400 are the same, but they are slightly shifted in FIG. 3(B) to facilitate understanding.The correction trajectory generation unit 124 generates a plurality of trajectories having different moving directions using an axial deviation variable 125 for each of the targets output from the first and second vehicle surroundings monitoring sensors 10 aand 10 b. The axial deviation variable 125 is a numerical character string for setting a deviation of an angular direction that causes the corrected trajectory 430 of the target generated by the correction trajectory generation unit 124 to vary. The number of corrected target tracks 430 produced and the range of deviation are determined by the axial deviation variable 125. A function for setting the axial deviation variable 125 may be determined, and by such a function, the axial deviation variable 125 may be generated.For example, as illustrated in FIG. 3(C), the corrected trajectory 430 taking into account the deviation amount of the vehicle surroundings monitoring sensor is generated with the starting point position of the sensor data 400 as a reference. Since the deviation amounts of the vehicle surroundings monitoring sensors 10 aand 10 bare unknown, a plurality of corrected trajectories 430 are generated using a plurality of deviation amounts in a range of an assumed deviation amount. The start point position of the generated corrected trajectory 430 and the start point position of the sensor data 400 are the same, but they are slightly shifted in FIG. 3(C) to facilitate understanding.As described later in Embodiment 2, the axial deviation variable 125 may indicate a deviation of the position instead of the angular direction or together with the angular direction. It is possible to cause the starting point position to vary in addition to the moving direction of the corrected path 430 of the target by the deviation of the position, and it is possible to calculate a sensor coordinate transformation correction value for correcting an error other than the axial deviation described later.The error function 126 calculates a difference between the estimated trajectory 420 generated by the estimated trajectory generation unit 122 and the corrected trajectory 430 generated by the correction trajectory generation unit 124. For example, as described later, the error function 126 compares the plurality of estimated trajectories 420 and the plurality of corrected trajectories 430 with each other in all combinations in terms of translation, rotation, and extension / contraction, and calculates a difference between the estimated trajectory 420 and the corrected trajectory 430 in each combination.The evaluation function 127 evaluates all combinations of the estimated trajectories 420 and the corrected trajectories 430 of all targets between which differences have been calculated by the error function 126, and selects a combination having a small difference (see FIG. 3(D) ).By performing such an error evaluation calculation for each of the vehicle surroundings monitoring sensors for all targets, the sensor coordinate transformation correction value of each vehicle surroundings monitoring sensor can be calculated.As illustrated in FIG. 4, the estimated trajectory generation unit 122 generates a plurality of estimated trajectories 420 having different starting point positions in left and right directions and forward and backward directions. The correction trajectory generation unit 124 generates a plurality of corrected trajectories 430 having different moving directions.The evaluation function 127 evaluates a difference between the estimated trajectory 420 and the corrected trajectory 430 calculated by the error function 126, and selects a combination in which the estimated trajectory 420 and the corrected trajectory 430 are closest to each other. In the example illustrated in FIG. 4, when the estimated trajectory 420 is displaced to the right and the corrected trajectory 430 is displaced to the left, the estimated trajectory 420 and the corrected trajectory 430 are closest to each other. The sensor coordinate transformation correction value is calculated using the displacement amount of the estimated trajectory 420 and the deviation amount of the corrected trajectory 430 in this case.FIG. 5 is a flowchart illustrating fusion processing.When the sensor coordinate transformation correction value has already been calculated, the coordinates of the target detected by the first and second vehicle surroundings monitoring sensors 10 aand 10 bare corrected using the sensor coordinate transformation correction value (S 101).Then, target fusion processing for setting the position of the target using the correction values of the coordinates of the target detected by the plurality of sensors (S 102) is performed. The target fusion processing includes a body process (S 103), a grouping error determination process (S 104), and a correction target collection process (S 105). In the body process (S 103), the correction values of the coordinates of the plurality of targets are grouped to estimate the true position of the target. For example, the most reliable correction values of the coordinates of the target may be selected, or the correction values of the plurality of coordinates may be weighted and averaged in accordance with the reliability. In the grouping error determination process. (S 104), target data whose grouping is not possible is detected.There is a possibility that the attachment positions of the vehicle surroundings monitoring sensors 10 aand 10 bthat have detected the target whose grouping is not possible differ. Thus, in the correction target collection process (S 105), collection is performed using the vehicle environment monitoring sensors 10 aand 10 bthat have detected the target whose grouping is impossible as correction targets.Then, another fusion processing is performed (S 106). In the further fusion processing, correct information of lane markings and signals are determined from information acquired by a plurality of sensors, such as lane marking fusion and signal information fusion.Then, a target processing (S 107) is executed. The target processing (S 107) includes a correction parameter estimation process (S 108) and a parameter update determination process (S 109). In the correction parameter estimation process (S 108), the correction parameter estimation unit 120 compares the estimated trajectory 420, which is a trajectory of the target predicted from the host vehicle motion, with the corrected trajectory 430, which is a trajectory of the sensor data, with the axial deviation corrected. Then, the correction parameter estimation unit 120 selects a combination in which the two lanes are close to each other, and calculates a sensor coordinate transformation correction value.In the parameter update determination process (S 109), it is determined whether to update the sensor coordinate transformation correction value. For example, as described in Embodiment 4 described later, when an impact sensor or a temperature sensor detects an abnormal acceleration or an abnormal temperature, there is a possibility that an abnormality of the first and second vehicle surroundings monitoring sensors 10 aand 10 bhas occurred. Thus, the sensor coordinate transformation correction value is updated. On the other hand, when the impact sensor or the temperature sensor does not detect the abnormal acceleration or the abnormal temperature, the sensor coordinate transformation correction value does not need to be updated.FIG. 6 is a flowchart illustrating a process in which the evaluation function 127 evaluates a combination of the estimated trajectory 420 and the corrected trajectory 430 in the correction parameter estimation process (S 108).The evaluation function 127 evaluates a combination of the estimated trajectory 420 and the corrected trajectory 430 from the standpoint of translation, rotation, and extension / contraction. The translation means a difference between the centroid position of the estimated trajectory 420 and the centroid position of the corrected trajectory 430. The rotation means a difference between the direction of the estimated trajectory 420 and the direction of the corrected trajectory 430. The extension / decrease means a difference between the length of the estimated path 420 and the length of the corrected path 430.First, the evaluation function 127 executes a translation optimization process (S 111) for setting a predetermined number (e.g., 50%) of combinations in ascending order of the difference of the center-of-gravity position among a plurality of combinations of the estimated trajectory 420 and the corrected trajectory 430. Then, the evaluation function 127 executes a rotation optimization process (S 112) for setting a predetermined number (e.g., 50%) of combinations in ascending order of the difference in direction among a plurality of combinations of the estimated trajectory 420 and the corrected trajectory 430 set from the viewpoint of translation. Then, the evaluation function 127 executes an extension / contraction optimization process (S 113) for setting a predetermined number (e.g., 50%) of combinations in ascending order of the difference in length among a plurality of combinations of the estimated track 420 and the corrected track 430 set from the viewpoint of rotation. When each of the translation optimization process (S 111), the rotation optimization process (S 112), and the extension / contraction optimization process (S 113) is executed once, a combination of 12.5% remains.Then, a process of executing each of the translation optimization process (S 111), the rotation optimization process (S 112), and the extension / contraction optimization process (S 113) is repeated once to select a combination for calculating the sensor coordinate transformation correction value.The evaluation function 127 may calculate an evaluation value obtained by evaluating the translation (the difference of the center-of-gravity position), the rotation (the difference of the direction), and the extension / contraction (the difference of the length) with a predetermined weight, and select the combination having the smallest evaluation value as a combination for calculating the sensor coordinate transformation correction value instead of the process illustrated in FIG. 6.As described above, according to Embodiment 1, it is possible to calculate the sensor coordinate transformation correction value for correcting the axial deviation between the first and second vehicle surroundings monitoring sensors 10 aand 10 band automatically correct the axial deviation of the sensors.<Ausführungsform 2>FIG. 7 is a functional block diagram illustrating a correction parameter estimation unit 120 in Embodiment 2.The correction parameter estimation unit 120 in Embodiment 1 calculates the sensor coordinate transformation correction value for correcting the axial deviation in a left / right direction between the first and second vehicle surroundings monitoring sensors 10 aand 10 b, but the correction parameter estimation unit 120 in Embodiment 2 calculates a sensor coordinate transformation correction value for correcting a general deviation that is not limited to the axial deviation in the left / right direction between the first and second vehicle surroundings monitoring sensors 10 aand 10 b. Description of components having the same functions as Embodiment 1 is omitted, and various components will be mainly described.The correction parameter estimation unit 120 in Embodiment 2 includes a host vehicle motion calculation unit 121, an estimated trajectory generation unit 122, a correction trajectory generation unit 124, an error function 126, and an evaluation function 127. The operations of the host vehicle motion calculation unit 121, the estimated trajectory generation unit 122, the error function 126, and the evaluation function 127 are the same as in Embodiment 1 described above.The correction trajectory generation unit 124 generates a plurality of trajectories having different moving directions and different starting point positions using an axial deviation variable 125 for each of the targets output from the first and second vehicle surroundings monitoring sensors 10 aand 10 b. The axial deviation variable 125 is a numerical character string for setting a deviation of the angular direction and a deviation of the position that cause the corrected trajectory 430 of the target generated by the correction trajectory generation unit 124 to vary. The number of corrected target tracks 430 produced and the range of deviation are determined by the axial deviation variable 125. A function for setting the axial deviation variable 125 may be determined, and by such a function, the axial deviation variable 125 may be generated.In Embodiment 2, the axial deviation between the first and second vehicular environment monitoring sensors 10 aand 10 bis corrected by the deviation of the angular direction, and the front / rear deviation and the right / left deviation between the installation positions of the first and second vehicular environment monitoring sensors 10 aand 10 bare corrected by the deviation of the position. Therefore, it is possible to correct an error caused by a deviation other than the axial deviation between the first and second vehicle surroundings monitoring sensors 10 aand 10 b.<Ausführungsform 3>FIG. 8 is a functional block diagram illustrating a correction parameter estimation unit 120 in Embodiment 3.The correction parameter estimation unit 120 in Embodiment 1 corrects the deviation between the sensors using the stationary objects detected by the first and second vehicle surroundings monitoring sensors 10 aand 10 b, but the correction parameter estimation unit 120 in Embodiment 3 may correct the deviation between the sensors using moving objects detected by the first and second vehicle surroundings monitoring sensors 10 aand 10 b. Description of components having the same functions as Embodiment 2 is omitted, and various components will be mainly described.The correction parameter estimation unit 120 in Embodiment 3 includes a host vehicle motion calculation unit 121, an estimated trajectory generation unit 122, a correction trajectory generation unit 124, an error function 126, and an evaluation function 127. The operations of the host vehicle motion calculation unit 121, the correction trajectory generation unit 124, the error function 126, and the evaluation function 127 are the same as in Embodiment 1 described above.The estimated trajectory generation unit 122 generates a plurality of estimated trajectories 420 having different starting point positions using a motion parameter variable 128 and a target motion pattern 129 from the trajectory of the target predicted from the motion of the host vehicle. The movement of the host vehicle is calculated by the host vehicle movement calculation unit 121. The motion parameter variable 128 is a numerical character string for setting a deviation of the motion of the target that causes the estimated trajectory 420 generated by the estimated trajectory generation unit 122 to vary. The number of estimated trajectories 420 generated and the range of deviation are determined by the motion parameter variable 128. A function for presetting the motion parameter variable 128 may be determined, and the motion parameter variable 128 may be generated by such a function. The target motion pattern 129 includes a plurality of known motion patterns of a moving target. A pattern that matches the motion of the moving target that generates the estimated trajectory 420 is output. The estimated trajectory generation unit 122 generates the estimated trajectory 420 as the relative coordinate system target based on the host vehicle using the calculated motion of the host vehicle and the calculated target motion pattern 129. The estimated trajectory 420 is given a deviation as a reference using the motion parameter variable 128 to generate multiple estimated trajectories 420.In Embodiment 3, the axial deviation between the first and second vehicle surroundings monitoring sensors 10 aand 10 bis corrected using the moving target. Therefore, even in an environment in which it is not possible to view a stationary target, it is possible to correct an error caused by the deviation between the first and second vehicle environment monitoring sensors 10 aand 10 busing the moving target.<Ausführungsform 4>FIG. 9 is a functional block diagram illustrating a correction parameter estimation unit 120 in Embodiment 4.The correction parameter estimation unit 120 in Embodiment 4 determines whether or not it is necessary to correct the deviation of the sensor using the impacts applied to the first and second vehicle surroundings monitoring sensors 10 aand 10 band the temperatures of the first and second vehicle surroundings monitoring sensors 10 aand 10 b. Description of components having the same functions as Embodiment 2 is omitted, and various components will be mainly described.The correction parameter estimation unit 120 in Embodiment 4 includes a host vehicle motion calculation unit 121, an estimated trajectory generation unit 122, a correction trajectory generation unit 124, an error function 126, and an evaluation function 127. The operations of the host vehicle motion calculation unit 121, the estimated trajectory generation unit 122, the correction trajectory generation unit 124, and the error function 126 are the same as in Embodiment 1 described above.A state detection sensor (not illustrated) is provided in the vicinity of the first vehicle surroundings monitoring sensor 10 aand the second vehicle surroundings monitoring sensor 10 b. The state detection sensor includes an impact sensor and a temperature sensor, and detects an impact and a temperature change of a portion in which each of the first and second vehicle surroundings monitoring sensors 10 aand 10 bis mounted. The state detection sensor (the impact sensor and the temperature sensor) may be mounted at a location where an impact applied to the entire vehicle such as a chassis of the host vehicle is easily detected, and an impact applied to an arbitrary location and a temperature change are detected.When the state detection sensor detects an impact equal to or greater than a threshold value stored in advance, it is estimated that an abnormality of the attachment state of the vehicle surroundings monitoring sensor 10 aor 10 bhas occurred in the vicinity thereof, and abnormal impact data 130 is output to activate the evaluation function 127. In addition, when the state detection sensor detects a temperature exceeding an operation range stored in advance, it is estimated that the vehicle surroundings monitoring sensor 10 aor 10 bin its vicinity reaches a high temperature or a low temperature and an abnormality of the attachment state occurs, and abnormal temperature data 130 is output to activate the evaluation function 127.The correction parameter estimation unit 120 determines whether an abnormality of the attachment states of the first and second vehicle surroundings monitoring sensors 10 aand 10 bhas occurred, based on the impact data and the temperature data 130 output from the state detection sensor. Then, the correction parameter estimation unit 120 sends the determination result to the evaluation function 127.When it is determined that an abnormality of the first and second vehicle surroundings monitoring sensors 10 aand 10 bhas occurred, the evaluation function 127 starts the operation of selecting a combination for calculating the sensor coordinate transformation correction value and calculates the sensor coordinate transformation correction value.In Embodiment 4, when the state detection sensor detects an abnormal impact and / or temperature, the sensor coordinate transformation correction value is calculated. Thus, when no abnormality occurs, the sensor coordinate transformation correction value is not calculated, and thus it is possible to reduce the processing load.The components, processing procedures, and operations of the function blocks described in each embodiment may be combined randomly.Further, in the description given above, the in-vehicle device (the ECU) calculates the sensor coordinate transformation correction value, but a computer communicatively connected to the vehicle may calculate the sensor coordinate transformation correction value.As described above, the target device calculates a correction parameter for correcting a detection result of a target sensor (the vehicle surroundings monitoring sensors 10 aand 10 b). The target device includes the estimated trajectory generation unit 122 that detects a trajectory of a target for a period in which the host vehicle is moving using information of a movement of the host vehicle detected by a motion sensor and generates a plurality of estimated trajectories 420 having different starting points from the detected trajectory of the target using a first variable group (a starting point position variable 123 and a movement parameter variable 128), the correction trajectory generation unit 124 that generates a plurality of corrected trajectories 430 using a second variable group (the axial deviation variable 125) from the trajectory of the target around the host vehicle detected by the vehicle environment monitoring sensors 10 aand 10 b, and the correction parameter calculation unit (the error function 126 and the evaluation function 127) that selects a combination, wherein the difference between the estimated trajectory 420 and the corrected trajectory 430 is small, and calculates the correction parameter for correcting the displacement of the vehicle environment monitoring sensors 10 aand 10 busing a first variable related to the selected estimated trajectory 420 and a second variable related to the selected corrected trajectory 430. Thus, it is possible to automatically correct the axial deviation between the vehicle surroundings monitoring sensors 10 aand 10 b. In addition, it is possible to correct not only the axial deviation but also various displacements. That is, since the relative direction of the target is influenced by a plurality of pieces of information when deviations other than the left / right axial deviation are included, the value of the axial deviation may be erroneously estimated in a known method for expressly obtaining the axial deviation. In the method in the present embodiment, it is not possible to expressly calculate the axial deviation, but it is possible to approximately obtain the value of the axial deviation to be calculated.In addition, the correction parameter calculation unit may execute the first procedure (the translation optimization procedure S 111) for indicating a combination in which the center of gravity of the estimated trajectory 420 and the center of gravity of the corrected trajectory 430 are close to each other, the second procedure (the rotation optimization procedure S 112) for indicating a combination in which the angle between the estimated trajectory 420 and the corrected trajectory 430 is small, and the third procedure (the extension / shortening optimization procedure S 113) for indicating a combination in which the length of the estimated trajectory 420 and the length of the corrected trajectory 430 are close to each other, and selects a combination in which the difference between the estimated trajectory 420 and the corrected trajectory 430 is small by sequentially executing the first procedure (S 111) repeatedly, the second procedure (S 112) and the third procedure (S 113). Therefore, it is possible to accurately select a combination of an estimated trajectory 420 and the corrected trajectory 430.In addition, the estimated trajectory generation unit 122 detects a trajectory of a target having a known motion pattern using the information of the motion of the host vehicle, and generates a plurality of estimated trajectories 420 having different starting points using the first variable group and the motion pattern. Thus, it is possible to calculate the correction parameter for correcting the displacement of the vehicle surroundings monitoring sensors 10 aand 10 busing a moving target.In addition, when an impact applied to the host vehicle and / or a temperature of the host vehicle detected by the state detection sensor are input and the impact and / or the temperature satisfy a predetermined condition, the correction parameter is output. Thus, when no abnormality occurs, the sensor coordinate transformation correction value is not calculated, and thus it is possible to reduce the processing load.In addition, the first variable group includes the (starting point position variable 123 and the motion parameter variable 128) a plurality of variables that change the starting point of the estimated trajectory 420 to at least one of the forward, the backward, the left, and the right direction, and the estimated trajectory generation unit 122 generates a plurality of estimated trajectories 420 having different starting points in the forward, the backward, the left, and the right direction using the first variable group. Thus, it is possible to accurately correct the axial deviation between the vehicle surroundings monitoring sensors 10 aand 10 b.In addition, the second variable group (the axial deviation variable 125) includes a plurality of variables that change the direction of the corrected trajectory 430, and the corrected trajectory generation unit 124 generates a plurality of corrected trajectories 430 having different directions using the second variable group from the trajectories of the target detected by the vehicle surroundings monitoring sensors 10 aand 10 b. Thus, it is possible to accurately correct the axial deviation between the vehicle surroundings monitoring sensors 10 aand 10 b.In addition, since the vehicle environment monitoring sensors 10 aand 10 bare millimeter wave radars or cameras, it is possible to calculate correction amounts of various types of vehicle environment monitoring sensors 10 aand 10 b.The present invention is not limited to the above-described embodiments, and includes various modifications and corresponding configurations within the spirit of the appended claims. For example, the above-described embodiments are described in detail in order to explain the present invention in an easily comprehensible manner, and the present invention is not necessarily limited to a case including all the described configurations. In addition, a portion of the configuration of the one embodiment may be replaced with the configuration of another embodiment. Further, the configuration of the one embodiment may be added to the configuration of another embodiment. Regarding some components in the embodiments, other components may be added, deleted, and replaced.In addition, some or all of the above-described configurations, functions, processing units, processing means, and the like may be realized by hardware, for example, by designing with an integrated circuit, or may be realized by software by a processor interpreting and executing a program for realizing each function.Information such as a program, a table, and a file that realize each function may be stored in a work memory, a storage device such as a hard disk and a solid state drive (SSD), or a recording medium such as an IC card, an SD card, a DVD, and a BD.Control lines and data lines considered necessary for the descriptions are illustrated, and not all of the control lines and data lines in the mounting are necessarily shown. In practice, almost all components can be considered to be connected to each other.List of reference characters1 Sensor fusion device 2 Traveling control device 10 a, 10 b Fahrzeug environment monitoring sensor 20 Host vehicle motion detection sensor 30 Lane marker detection sensor 40 Transmission detection information 100 Sensor coordinate transformation unit 110 Sensor timing synchronization unit 120 Correction parameter estimation unit 121 Host vehicle motion calculation unit 122 Estimated trajectory generation unit 123 Starting point position variable 124 Correction trajectory generation unit 125 Axial deviation variable 126 Error function 127 Evaluation function 128 Motion parameter variable 129 Target motion pattern 130 Impact data, temperature data 200 Sensor data integration unit 340 Target detection start determination unit 400 Sensor data 410 True trajectory 420 Estimated trajectory 430 Corrected trajectory

Claims

A target device that calculates a correction parameter for correcting a detection result of a target sensor, the target device comprising: an estimated trajectory generation unit that detects a trajectory of a target for a period in which a host vehicle is moving using information of a movement of the host vehicle detected by a motion sensor, and generates a plurality of estimated trajectories having different start point positions from the detected trajectory of the target using a first variable group; a correction trajectory generation unit that generates a plurality of corrected trajectories from the trajectory of the target around the host vehicle detected by the target sensor using a second variable group; and a correction parameter calculation unit that selects a combination in which a difference between the estimated trajectory and the corrected trajectory is small, and calculates the correction parameter for correcting a displacement of the target sensor using a first variable related to the selected estimated trajectory and a second variable related to the selected corrected trajectory.The target device according to claim 1, wherein the correction parameter calculation unit is capable of performing: a first procedure for indicating a combination in which a center of gravity of the estimated trajectory and a center of gravity of the corrected trajectory are close to each other; a second procedure for indicating a combination in which an angle between the estimated trajectory and the corrected trajectory is small; and a third procedure for indicating a combination in which a length of the estimated trajectory and a length of the corrected trajectory are close to each other; and the correction parameter calculation unit selects the combination in which the difference between the estimated trajectory and the corrected trajectory is small by sequentially repeating the first procedure, the second procedure, and the third procedure.The target device according to claim 1, wherein the estimated trajectory generation unit detects a trajectory of a target having a known motion pattern using the information of the motion of the host vehicle, and generates the plurality of estimated trajectories having different starting point positions using the first variable group and the motion pattern.The target device according to claim 1, wherein an impact applied to the host vehicle and / or a temperature of the host vehicle are input, the impact and the temperature are detected by a state detection sensor, and when the impact and / or the temperature satisfy a predetermined condition, the correction parameter is output.The target device according to claim 1, wherein the first variable group includes a plurality of variables that change the starting point position of the estimated trajectory to at least one of forward and backward directions and left and right directions, and the estimated trajectory generation unit generates the plurality of estimated trajectories having the different starting point positions in the forward, backward, left and right directions using the first variable group.The target device according to claim 1, wherein the second variable group includes a plurality of variables that change a direction of the corrected trajectory, and the correction trajectory generation unit generates a plurality of corrected trajectories having different directions from the trajectory of the target detected by the target sensor using the second variable group.The target device according to claim 1, wherein the target sensor is a millimeter wave radar or a camera.A driving control system that controls driving of a vehicle, the driving control system comprising: a sensor fusion device that integrates and outputs detection results of two or more target sensors; and a driving control device that controls driving of the vehicle using an output of the sensor fusion device, the sensor fusion device including: an estimated trajectory generation unit that detects a trajectory of a target for a period in which a host vehicle is moving using information of a movement of the host vehicle detected by a motion sensor, and generates a plurality of estimated trajectories having different starting point positions from the detected trajectory of the target using a first variable group, a correction trajectory generation unit that generates a plurality of corrected trajectories from the trajectory of the target around the host vehicle detected by the target sensor, generating, using a second variable group, a correction parameter calculation unit that selects a combination in which a difference between the estimated trajectory and the corrected trajectory is small and calculates the correction parameter for correcting displacement of the target sensor using a first variable with respect to the selected estimated trajectory and a second variable with respect to the selected corrected trajectory, a sensor coordinate transformation unit that transforms information on the target into a predetermined unified coordinate system from a coordinate system unique to the target sensor using the calculated correction parameter, and a sensor data integration unit that integrates the detection results of the target sensors and outputs an integration result.A method for calculating a correction parameter of sensor data, the method being performed by a target device that uses detection results of two or more sensors to calculate a correction parameter of the detection result of the sensor, and the method comprising: detecting a trajectory of a target for a period in which a host vehicle is moving using information of a movement of the host vehicle detected by a motion sensor, and generating a plurality of estimated trajectories having different starting point positions from the detected trajectory of the target using a first variable group; generating a plurality of corrected trajectories from the trajectory of the target around the host vehicle detected by the target sensor using a second variable group; selecting a combination in which a difference between the estimated trajectory and the corrected trajectory is small, and calculating the correction parameter for correcting a displacement of the target sensor using a first variable with respect to the selected estimated trajectory and a second variable with respect to the selected corrected trajectory.

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