JP2021060245A - Traveling direction estimation device and object tracking device - Google Patents

Abstract

To provide a traveling direction estimation device and a tracking device capable of accurately estimating a traveling direction of an object.SOLUTION: A traveling direction estimation device includes an object detection unit, a position calculation unit, a shape estimation unit, a tangential direction calculation unit, and a traveling direction estimation unit. The object detection unit detects an object using a sensor mounted on a moving body. The position calculation unit calculates a position of the object. The shape estimation unit estimates a shape of a track on which the object is present. The tangential direction calculation unit calculates the tangential direction of the track at the position of the object on the basis of the shape of the track and the position of the object. The traveling direction estimation unit estimates the traveling direction of the object on the basis of the tangential direction.SELECTED DRAWING: Figure 1

Description

The present disclosure relates to a traveling direction estimation device and an object tracking device.

Patent Document 1 discloses an object tracking device. The object tracking device is mounted on the vehicle. The object tracking device repeats a processing cycle of detecting an object using an in-vehicle radar. The object tracking device predicts the position of the same object (hereinafter referred to as the predicted position) detected in the (N + 1) th processing cycle from the position and speed of the object detected in the Nth processing cycle. N is a natural number. The object tracking device sets a connection range centered on the predicted position. When the object detected in the (N + 1) th processing cycle is within the connection range, the object tracking device determines that the object detected in the (N + 1) th processing cycle is the object detected in the Nth processing cycle. to decide.

Japanese Unexamined Patent Publication No. 2018-25492

In order to predict the predicted position, it is necessary to estimate the velocity of the object detected in the Nth processing cycle. In order to estimate the velocity of an object, it is necessary to estimate the traveling direction of the object. Conventionally, it has been assumed that the traveling direction of an object is the same as the traveling direction of the own vehicle.

However, for example, when the object is a preceding vehicle and the preceding vehicle is traveling on a curved road, the traveling direction of the preceding vehicle is significantly different from the traveling direction of the own vehicle. Therefore, assuming that the traveling direction of the preceding vehicle is the same as the traveling direction of the own vehicle, the traveling direction of the preceding vehicle cannot be accurately estimated. Further, if the traveling direction of the preceding vehicle cannot be estimated accurately, it becomes difficult to track the preceding vehicle.

One aspect of the present disclosure is to provide a traveling direction estimation device and a tracking device capable of accurately estimating the traveling direction of an object.

One aspect of the present disclosure is an object detection unit configured to detect an object existing around the moving body using a sensor mounted on the moving body, and the object detection unit detected by the object detection unit. A position calculation unit configured to calculate the position of an object, a shape estimation unit configured to estimate the shape of a traveling path on which the object exists detected by the object detection unit, and the shape estimation unit. A tangential direction calculation unit configured to calculate the tangential direction of the travel path at the position of the object based on the shape of the travel path estimated by the above and the position of the object calculated by the position calculation unit. It is a traveling direction estimation device including a traveling direction estimation unit configured to estimate the traveling direction of the object detected by the object detecting unit based on the tangential direction calculated by the tangent direction calculating unit.

The traveling direction estimation device, which is one aspect of the present disclosure, estimates the traveling direction of an object based on the tangential direction of the traveling path at the position of the object. The tangential direction of the travel path at the position of the object is likely to be close to the traveling direction of the object. Therefore, the traveling direction estimation device, which is one aspect of the present disclosure, can accurately estimate the traveling direction of the object.

It is a block diagram which shows the structure of the object tracking apparatus 1. It is a block diagram which shows the functional structure of the object tracking apparatus 1. It is explanatory drawing which shows one millimeter wave radar apparatus 31 and its object detection area 39. It is explanatory drawing which shows 5 millimeter wave radar apparatus 31 and each object detection area 39. It is a flowchart which shows the whole process which the object tracking apparatus 1 executes. It is a flowchart which shows the traveling direction calculation process which the object tracking apparatus 1 executes. It is a flowchart which shows the shape estimation process of the traveling path executed by the object tracking apparatus 1. It is explanatory drawing which shows the method of estimating the shape of the traveling path 45 in which an object 43 exists by using the curvature of the traveling locus 41 of a vehicle 3. It is explanatory drawing which shows the traveling direction D1 of the object 43 when the reliability is low. It is explanatory drawing which shows the traveling direction D1 of the object 43 when the reliability is high.

An exemplary embodiment of the present disclosure will be described with reference to the drawings.
<First Embodiment>
1. 1. Configuration of Object Tracking Device 1 The configuration of the object tracking device 1 will be described with reference to FIGS. 1 to 4. As shown in FIG. 1, the object tracking device 1 is mounted on the vehicle 3. The vehicle 3 corresponds to a moving body. The object tracking device 1 includes a microcomputer having a CPU 5 and, for example, a semiconductor memory such as a RAM or a ROM (hereinafter referred to as a memory 7).

Each function of the object tracking device 1 is realized by the CPU 5 executing a program stored in a non-transitional substantive recording medium. In this example, the memory 7 corresponds to a non-transitional substantive recording medium in which a program is stored. Moreover, when this program is executed, the method corresponding to the program is executed. The object tracking device 1 may include one microcomputer or a plurality of microcomputers.

As shown in FIG. 2, the object tracking device 1 includes an object detection unit 9, a position calculation unit 11, a shape estimation unit 13, a tangential direction calculation unit 15, a traveling direction estimation unit 17, and a moving body traveling direction calculation. It includes a unit 19, a reliability calculation unit 21, a yaw rate calculation unit 23, a ground speed estimation unit 25, and a tracking unit 27. The portion of the object tracking device 1 excluding the tracking unit 27 is the traveling direction estimation device 29.

As shown in FIG. 1, the object tracking device 1 is connected to a millimeter-wave radar device 31, a camera 33, an information storage unit 35, and a sensor group 37.
The millimeter wave radar device 31 detects an object existing around the vehicle 3. The millimeter wave radar device 31 sends the detection result to the object tracking device 1. For example, as shown in FIG. 3, one millimeter-wave radar device 31 is attached to the center at the front end of the vehicle 3. The millimeter wave radar device 31 has an object detection region 39 in front of the vehicle 3. The object detection area 39 is an area in which an object can be detected.

Further, for example, as shown in FIG. 4, millimeter-wave radar devices 31 are attached to the four corners of the vehicle 3 and the center at the front end, respectively. Each of the five millimeter-wave radar devices 31 has an object detection area 39. The millimeter wave radar device 31 corresponds to a sensor mounted on a moving body.

The camera 33 photographs the periphery of the vehicle 3 and generates an image. The camera 33 sends the generated image to the object tracking device 1. The information storage unit 35 stores map information. The map information is information including the position, shape, and the like of the traveling path. The sensor group 37 includes a sensor that detects information about the vehicle 3. The sensor group 37 includes, for example, a vehicle speed sensor, a steering angle sensor, and the like.

2. Processing executed by the object tracking device 1 The processing executed by the object tracking device 1 will be described with reference to FIGS. 5 to 10. The object tracking device 1 repeatedly executes the process shown in FIG. 5 at predetermined time intervals. Executing the process shown in FIG. 5 once is one process cycle.

In step 1 of FIG. 5, the object detection unit 9 uses the millimeter-wave radar device 31 to perform a process of detecting an object existing in the vicinity of the vehicle 3. As a result, the object detection unit 9 acquires the observation information. The observation information is information representing the position of the object, the velocity of the object, and the like. There is one observation information for each detected object.

The object tracking device 1 registers the object information related to the object tracked up to the previous processing cycle in the memory 7. The object information is information indicating the position of the tracked object, the velocity of the object, the traveling direction of the object, the yaw rate of the object, and the like. There is one object information for each object. The object tracking device 1 performs the processes of steps 2 to 6 described later for each of the object information registered in the previous processing cycle.

In step 2, among the object information registered in the previous processing cycle, is there any object information (hereinafter referred to as unprocessed object information) that has not yet been processed in steps 3 to 6 in this processing cycle? The tracking unit 27 determines whether or not it is. If there is unprocessed object information, this process proceeds to step 3. If there is no unprocessed object information, this process proceeds to step 7.

In step 3, the tracking unit 27 selects one object information from the unprocessed object information. The selected object information will be referred to as the object information being processed below. The tracking unit 27 calculates current prediction information for the object information being processed. The prediction information is information including a predicted value of the position of the object at the present time, a predicted value of the velocity of the object at the present time, and the like.

The tracking unit 27 estimates the predicted value of the position of the object at the present time as follows. The object information being processed represents the position of the object, the velocity of the object, and the traveling direction of the object. The tracking unit 27 calculates the velocity in the traveling direction of the object (hereinafter referred to as the traveling direction velocity) based on the object information being processed. The tracking unit 27 sets the position advanced from the position of the object in the object information being processed in the traveling direction of the object at the traveling direction velocity by the time of the cycle cycle as the predicted value of the position of the object at the present time. The cycle cycle is the cycle of the processing cycle. Further, the tracking unit 27 estimates the predicted value of the velocity of the object at the present time based on the object information being processed.

In step 4, the tracking unit 27 compares the prediction information calculated in step 3 with the observation information acquired in step 1. The tracking unit 27 associates the observation information within the connection range centered on the prediction information with the object information being processed. The connection range may be, for example, a range relating to the position of the object or a range relating to the position and speed of the object. The associated observation information will be referred to as related observation information below.

In step 5, the position calculation unit 11 performs the filtering process as follows. The position calculation unit 11 synthesizes the predicted value of the position of the object included in the related observation information and the predicted value of the position of the object included in the predicted information after giving a predetermined weight to each of them, and synthesizes the filtered object. Calculate the position. Further, the position calculation unit 11 synthesizes the velocity of the object included in the related observation information and the predicted value of the velocity of the object included in the prediction information after giving a predetermined weight to each of them, and after filtering. Calculate the velocity of the object.

The position calculation unit 11 newly registers the object information for the object represented by the object information during processing. The newly registered object information (hereinafter referred to as the latest processing object information) includes the position of the object after filtering and the velocity of the object after filtering. By associating the object information being processed with the observation information in step 4 and newly registering the latest object information being processed in step 5, the object represented by the object information being processed is tracked. Correspond.

Step 6 is a traveling direction calculation process. This process will be described with reference to FIG. In step 11 of FIG. 6, the tracking unit 27 determines whether or not the elapsed cycle is equal to or less than a predetermined value. The elapsed cycle is the number of processing cycles in which the object represented by the processing object information is tracked up to the present time.

If the elapsed cycle is less than or equal to a predetermined value, this process proceeds to step 12. If the elapsed cycle exceeds a predetermined value, the process proceeds to step 19.
In step 12, the moving body traveling direction calculation unit 19 calculates the traveling direction of the vehicle 3 by using the sensor group 37.

In step 13, the ground speed estimation unit 25 calculates the ground speed of the object represented by the object information being processed. The ground speed is the speed with respect to the ground. The ground speed estimation unit 25 uses the millimeter-wave radar device 31 to calculate the relative speed of an object with reference to the vehicle 3. Further, the ground speed estimation unit 25 calculates the speed of the vehicle 3 with respect to the ground by using the sensor group 37. The ground speed estimation unit 25 calculates the ground speed of an object based on the relative speed of the object with respect to the vehicle 3 and the speed of the vehicle 3 with respect to the ground. When the ground speed of the object is equal to or higher than a predetermined value, this process proceeds to step 14. If the ground speed of the object is less than a predetermined value, this process proceeds to step 18.

Step 14 is a process of estimating the shape of the traveling path. This process will be described with reference to FIG. In step 21 of FIG. 7, the shape estimation unit 13 estimates the shape of the traveling path on which the object exists by using the curvature of the traveling locus of the vehicle 3. For example, the shape estimation unit 13 continuously measures the steering angle of the vehicle 3 to calculate the curvature of the traveling locus 41 of the vehicle 3 as shown in FIG. The shape estimation unit 13 assumes that the object 43 and the vehicle 3 are traveling on the same travel path 45, and that the curvature of the travel path 45 of the object 43 is equal to the curvature of the travel locus 41 of the vehicle 3. presume. In the example shown in FIG. 8, the object 43 is a preceding vehicle.

In step 22, the shape estimation unit 13 estimates the shape of the traveling path by using an array of roadside objects arranged along the traveling path where the object exists. For example, the shape estimation unit 13 recognizes roadside objects lined up along the traveling path by using the millimeter wave radar device 31 or the camera 33. Examples of roadside objects include guardrails and curbs. The shape estimation unit 13 recognizes the shape of the array of roadside objects. The shape of the arrangement of roadside objects generally matches the shape of the road. The shape estimation unit 13 uses the shape of the array of roadside objects as the shape of the traveling path.

In step 23, the shape estimation unit 13 estimates the shape of the traveling path on which the object exists by using the map information. For example, the shape estimation unit 13 uses a millimeter-wave radar device 31 or a camera 33 to acquire a relative position of an object with respect to the vehicle 3. Further, the shape estimation unit 13 acquires the absolute position of the vehicle 3. The shape estimation unit 13 acquires the absolute position of the object by using the relative position of the object with respect to the vehicle 3 and the absolute position of the vehicle 3. The shape estimation unit 13 collates the absolute position of the object with the map information to estimate the shape of the traveling path on which the object exists.

In step 24, the shape estimation unit 13 estimates the shape of the traveling path by using the shape of the traveling lane marking in the traveling path where the object exists. For example, the shape estimation unit 13 uses the camera 33 to recognize the travel lane markings on the travel path. Examples of the traveling division line include a white line and the like. The shape of the lane marking generally matches the shape of the track. The shape estimation unit 13 uses the shape of the traveling lane marking as the shape of the traveling path.

In step 25, the shape estimation unit 13 integrates the shapes of the travel paths estimated in steps 21 to 24, and finally estimates the shape of the travel path. For example, the shape estimation unit 13 averages the shapes of the travel paths estimated in steps 21 to 24 to obtain the final shape of the travel path.

In step 26, the reliability calculation unit 21 calculates the reliability of the shape of the traveling path estimated in step 25. As a method for the reliability calculation unit 21 to calculate the reliability, for example, there are the following methods (a) to (c).

(A) The reliability calculation unit 21 continuously acquires an index representing the shape of the traveling path. Examples of the index include curvature, radius of curvature, and the like. The reliability calculation unit 21 calculates the reliability higher as the elapsed time from when the index is out of the predetermined range is longer. For example, when the index is curvature, the predetermined range is a range equal to or more than a preset lower limit value and less than or equal to a preset upper limit value.

(B) The reliability calculation unit 21 continuously acquires an index representing the shape of the traveling path, as in the case of (a) above. The reliability calculation unit 21 calculates the reliability lower as the amount of change in the index with the passage of time increases.

(C) The shape estimation unit 13 estimates the shape of the traveling path by a plurality of methods. As a plurality of methods, for example, there are the methods of steps 21 to 24. The reliability calculation unit 21 calculates the reliability higher as the degree of matching of the shapes of the traveling paths estimated by the plurality of methods is higher. For example, the shape of the traveling path estimated by the first method is defined as the first estimated shape. Further, the shape of the same traveling path estimated by the second method is used as the second estimated shape. The higher the degree of coincidence between the first estimated shape and the second estimated shape, the higher the reliability of the reliability calculation unit 21.

Returning to FIG. 6, in step 15, the tangential direction calculation unit 15 calculates the tangential direction of the traveling path at the position of the object. The position of the object is the position of the object represented by the latest processing object information. The travel path is a travel path whose shape is estimated in step 14. The tangential direction is the traveling direction of the traveling path at the position of the object.

In step 16, the traveling direction estimation unit 17 estimates the traveling direction of the object based on the tangential direction calculated in step 15. The traveling direction estimation unit 17 combines, for example, the tangential direction calculated in step 15 and the traveling direction of the vehicle 3 calculated in step 12 with predetermined weights, thereby synthesizing the traveling direction of the object. To estimate.

The higher the reliability estimated in step 26, the larger the weight given in the tangential direction and the smaller the weight given in the traveling direction of the vehicle 3. For example, when the reliability is low, as shown in FIG. 9, the traveling direction D1 of the object 43 is closer to the traveling direction D3 of the vehicle 3 than the tangential direction D2.

When the reliability is high, as shown in FIG. 10, the traveling direction D1 of the object 43 is closer to the tangential direction D2 than the traveling direction D3 of the vehicle 3.
The traveling direction estimation unit 17 adds the estimated traveling direction of the object to the latest processing object information. Therefore, the latest processing object information includes the traveling direction of the object.

In step 27, the yaw rate calculation unit 23 calculates the yaw rate of the object. An object is an object represented by the latest processing object information. The yaw rate calculation unit 23 is based on the shape of the traveling path estimated in step 14, the traveling direction of the object estimated in step 16, and the position and speed of the object included in the latest processing object information. Calculate the yaw rate.

The yaw rate calculation unit 23 adds the calculated yaw rate of the object to the latest processing object information. Therefore, the latest processing object information includes the yaw rate of the object.
In step 18, the traveling direction estimation unit 17 estimates that the traveling direction of the vehicle 3 calculated in step 12 is the traveling direction of the object. The traveling direction estimation unit 17 adds the estimated traveling direction of the object to the latest processing object information. Therefore, the latest processing object information includes the traveling direction of the object.

In step 19, the traveling direction estimation unit 17 estimates the traveling direction of the object by using the result of the filtering process. The traveling direction estimation unit 17 adds the estimated traveling direction of the object to the latest processing object information. Therefore, the latest processing object information includes the traveling direction of the object.

Returning to FIG. 5, in step 7, the tracking unit 27 determines whether or not there is unused observation information. Unused observation information is observation information that is not associated with any object information. If there is unused observation information, this process proceeds to step 8. If there is no unused observation information, the current processing cycle is terminated.

The process of step 8 is a process of calculating the traveling direction of an object represented by unused observation information. This process is the same as the process of step 6.
In step 9, the tracking unit 27 registers new object information. The new object information is information obtained by adding the traveling direction of the object estimated in step 8 to the unused observation information.

3. 3. Effects of the Travel Direction Estimator 29 and the Object Tracking Device 1 (1A) The Travel Direction Estimator 29 estimates the traveling direction of an object based on the tangential direction of the traveling path at the position of the object. The tangential direction of the travel path at the position of the object is likely to be close to the traveling direction of the object. Therefore, the traveling direction estimation device 29 can accurately estimate the traveling direction of the object.

(1B) The traveling direction estimation device 29 uses the curvature of the traveling locus of the vehicle 3, the arrangement of roadside objects lined up along the traveling path, the map information, and the shape of the traveling lane marking on the traveling path to form the shape of the traveling path. To estimate. Therefore, the traveling direction estimation device 29 can estimate the traveling direction of the object more accurately.

(1C) The traveling direction estimation device 29 can calculate the traveling direction of the vehicle 3. The traveling direction estimation device 29 estimates the traveling direction of the object by synthesizing the tangential direction of the traveling path and the traveling direction of the vehicle 3 with predetermined weights.

Therefore, even if the estimation result of the tangential direction of the traveling path is inaccurate, the traveling direction estimation device 29 accurately estimates the traveling direction of the object as compared with the case where only the tangential direction of the traveling path is used. Can be done.
(1D) The traveling direction estimation device 29 calculates the reliability of the shape of the traveling path. The higher the reliability of the traveling direction estimation device 29, the greater the weight given to the tangential direction of the traveling path. Therefore, the traveling direction estimation device 29 can estimate the traveling direction of the object more accurately.

(1E) The traveling direction estimation device 29 includes (a) the elapsed time since the index representing the shape of the traveling path is out of the predetermined range, (b) the amount of change in the index with the passage of time, and (c). The reliability is calculated using one or more selected from the group consisting of the matching degree of the shape of the traveling path estimated by each of a plurality of methods. Therefore, the traveling direction estimation device 29 can calculate the reliability more accurately.

(1F) The traveling direction estimation device 29 can calculate the yaw rate of an object based on the traveling direction of the object and the shape of the traveling path.
(1G) The traveling direction estimation device 29 estimates the ground speed of the object. The traveling direction estimation device 29 estimates the traveling direction of the object by the processing of steps 14 to 16 on the condition that the ground speed is equal to or higher than a preset threshold value.

The traveling direction estimation device 29 estimates the traveling direction of the object in the process of step 18 for the object having a low ground speed. Therefore, the traveling direction estimation device 29 can reduce the processing load. For an object with a low ground speed, it is less necessary to accurately estimate the traveling direction. As an object having a low ground speed, for example, there is an object other than a vehicle.

(1H) The object tracking device 1 tracks an object using the traveling direction of the object estimated in the processes of steps 12 to 16 only for the object whose elapsed cycle is equal to or less than a predetermined value. Therefore, the processing load of the object tracking device 1 can be reduced as compared with the case where the object is always tracked using the traveling direction of the object estimated in the processes of steps 12 to 16.

In the case of an object whose elapsed cycle exceeds a predetermined value, the traveling direction of the object can be estimated by the process of step 19, so that the processes of steps 12 to 16 need not be performed.
The fact that the elapsed cycle is less than or equal to a predetermined value corresponds to the fact that the elapsed time from the time when the object is first detected is less than or equal to the predetermined value.

The object tracking device 1 may track an object using the traveling direction of the object estimated in the processes of steps 12 to 16 only for the object detected for the first time.
<Other Embodiments>
Although the embodiments of the present disclosure have been described above, the present disclosure is not limited to the above-described embodiments, and can be implemented in various modifications.

(1) An object may be detected by using another sensor instead of the millimeter wave radar device 31.
(2) Another moving body may be used instead of the vehicle 3. Examples of other moving bodies include ships, aircraft, railroad vehicles, and the like.

(3) Of steps 21 to 24, steps 1 to 3 arbitrarily selected may be executed, and the remaining steps may not be executed. For example, step 21 may be performed and steps 22-24 may not be performed. In this case, the shape of the travel path obtained in step 25 is the shape of the travel path estimated in step 21.

Further, for example, step 22 may be executed and steps 21, 23 to 24 may not be executed. In this case, the shape of the travel path obtained in step 25 is the shape of the travel path estimated in step 22.
Further, for example, steps 23 may be executed and steps 21 to 22 and 24 may not be executed. In this case, the shape of the travel path obtained in step 25 is the shape of the travel path estimated in step 23.

Further, for example, steps 24 may be executed and steps 21 to 23 may not be executed. In this case, the shape of the travel path obtained in step 25 is the shape of the travel path estimated in step 24.
(4) In step 16, the tangential direction calculated in step 15 may be used as the traveling direction of the object.

(5) In step 16, the weights given to the tangential direction and the traveling direction of the vehicle 3 may be set based on a reference other than the reliability. Further, the weights given to the tangential direction and the traveling direction of the vehicle 3 may be fixed values.

(6) The object tracking device 1 and its method described in the present disclosure are provided by configuring a processor and memory programmed to perform one or more functions embodied by a computer program. It may be realized by a dedicated computer. Alternatively, the object tracking device 1 and its method described in the present disclosure may be realized by a dedicated computer provided by configuring a processor with one or more dedicated hardware logic circuits. Alternatively, the object tracking device 1 and its method described in the present disclosure comprises a processor and memory programmed to perform one or more functions and a processor composed of one or more hardware logic circuits. It may be realized by one or more dedicated computers configured by a combination. The computer program may also be stored on a computer-readable non-transitional tangible recording medium as an instruction executed by the computer. The method for realizing the functions of each part included in the object tracking device 1 does not necessarily include software, and all the functions may be realized by using one or a plurality of hardware.
(7) A plurality of functions possessed by one component in the above embodiment may be realized by a plurality of components, or one function possessed by one component may be realized by a plurality of components. .. Further, a plurality of functions possessed by the plurality of components may be realized by one component, or one function realized by the plurality of components may be realized by one component. Further, a part of the configuration of the above embodiment may be omitted. In addition, at least a part of the configuration of the above embodiment may be added or replaced with the configuration of the other above embodiment.

(8) In addition to the above-mentioned object tracking device 1, a system having the object tracking device 1 as a component, a program for operating a computer as the object tracking device 1, a non-transitional non-transitional memory such as a semiconductor memory in which this program is recorded. The present disclosure can also be realized in various forms such as an actual recording medium and an object tracking method.

1 ... Object tracking device, 3 ... Vehicle, 5 ... CPU, 7 ... Memory, 9 ... Object detection unit, 11 ... Position calculation unit, 13 ... Shape estimation unit, 15 ... Tangent direction calculation unit, 17 ... Travel direction estimation unit, 19 ... Moving object traveling direction calculation unit, 21 ... Reliability calculation unit, 23 ... Yaw rate calculation unit, 25 ... Ground speed estimation unit, 27 ... Tracking unit, 29 ... Travel direction estimation device, 31 ... Millimeter wave radar device, 33 ... Camera, 35 ... Information storage unit, 37 ... Sensor group, 39 ... Object detection area, 41 ... Travel locus, 43 ... Object, 45 ... Travel path

Claims (9)

An object detection unit configured to detect an object existing around the moving body using a sensor mounted on the moving body, and an object detection unit.
A position calculation unit configured to calculate the position of the object detected by the object detection unit, and a position calculation unit.
A shape estimation unit configured to estimate the shape of the traveling path on which the object exists, which is detected by the object detection unit, and a shape estimation unit.
The tangential direction configured to calculate the tangential direction of the travel path at the position of the object based on the shape of the travel path estimated by the shape estimation unit and the position of the object calculated by the position calculation unit. Calculation unit and
A traveling direction estimation unit configured to estimate the traveling direction of the object detected by the object detection unit based on the tangential direction calculated by the tangential direction calculating unit.
A traveling direction estimator comprising. The traveling direction estimation device according to claim 1.
The shape estimation unit is one or more selected from a group consisting of the curvature of the traveling locus of the moving body, the arrangement of roadside objects lined up along the traveling path, map information, and the shape of the traveling marking line on the traveling path. A traveling direction estimation device configured to estimate the shape of the traveling path using the above. The traveling direction estimation device according to claim 1 or 2.
A mobile body traveling direction calculation unit configured to calculate the traveling direction of the moving body is further provided.
The traveling direction estimation unit is configured to estimate the traveling direction of the object by synthesizing the tangential direction and the traveling direction of the moving body with predetermined weights. apparatus. The traveling direction estimation device according to claim 3.
A reliability calculation unit configured to calculate the reliability of the shape of the traveling path is further provided.
The traveling direction estimation unit is a traveling direction estimation device configured so that the higher the reliability, the greater the weight attached to the tangential direction. The traveling direction estimation device according to claim 4.
The reliability calculation unit includes (a) the elapsed time since the index representing the shape of the traveling path estimated by the shape estimation unit is out of the predetermined range, and (b) the change of the index with the passage of time. The traveling direction estimation configured to calculate the reliability using one or more selected from the group consisting of the quantity and (c) the degree of coincidence of the shape of the traveling path estimated by each of a plurality of methods. apparatus. The traveling direction estimation device according to any one of claims 1 to 5.
A progress further comprising a yaw rate calculation unit configured to calculate the yaw rate of the object based on the traveling direction of the object estimated by the traveling direction estimation unit and the shape of the traveling path estimated by the shape estimating unit. Direction estimator. The traveling direction estimation device according to any one of claims 1 to 6.
Further comprising a ground speed estimation unit configured to estimate the ground speed of the object detected by the object detection unit.
The traveling direction estimation unit is a traveling direction estimation device configured to estimate the traveling direction of the object on the condition that the ground speed estimated by the ground speed estimation unit is equal to or higher than a preset threshold value. .. An object tracking device
The traveling direction estimation device according to any one of claims 1 to 7,
A tracking unit configured to track the object detected by the object detection unit, and
With
The tracking unit is limited to the object whose elapsed time from the time when it is first detected by the object detection unit is equal to or less than a predetermined value, and uses the traveling direction of the object estimated by the traveling direction estimation device to obtain the object. An object tracking device configured to perform tracking. The object tracking device according to claim 8.
The tracking unit is an object tracking device configured to track the object using the traveling direction of the object estimated by the traveling direction estimation device only for the object detected for the first time by the object detecting unit. ..

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