Steering control device and vehicle

Abstract

A steering control device according to an embodiment of the present disclosure comprises a control circuit capable of calculating a target steering angle of a host vehicle on the basis of travel data including point sequence data indicating the center position of the road on which the host vehicle is traveling and data on a plurality of travel parameters including the travel speed of the host vehicle. The control circuit can calculate a plurality of time intervals by dividing the distance between adjacent points among a plurality of points included in the point sequence data by the travel speed, predict future travel data when the plurality of time intervals sequentially elapse by using model prediction control on the basis of the travel data, and calculate a target steering angle on the basis of the point sequence data and the predicted future travel data.

Description

Steering control device and vehicle

[0001] The present disclosure relates to a steering control device that controls the steering of a vehicle, and a vehicle equipped with such a steering control device.

[0002] In a lane keeping support system of a vehicle, a control algorithm called Model Predictive Control is often used. In such a vehicle, the future driving state of the vehicle is predicted in units of sampling time, and the driving control of the vehicle is performed based on the prediction result. For example, Patent Document 1 discloses a technique for shortening the sampling time in model predictive control when a predetermined condition is satisfied in the driving control of a vehicle.

[0003] Japanese Patent Application Laid-Open No. 2022-168407

[0004] The steering control device according to an embodiment of the present disclosure includes a control circuit. The control circuit can calculate the target steering angle of the host vehicle based on driving data including point sequence data indicating the position at the center of the road on which the host vehicle is traveling and data on a plurality of driving parameters including the driving speed of the host vehicle. The control circuit can calculate a plurality of time intervals by dividing the distance between adjacent points among the plurality of points included in the point sequence data by the driving speed, predict the future driving data when a plurality of time intervals elapse sequentially using model predictive control based on the driving data, and calculate the target steering angle based on the point sequence data and the predicted future driving data.

[0005] A vehicle according to one embodiment of the present disclosure comprises an imaging device, an image processing circuit, a steering device, and a control circuit. The imaging device is capable of generating an image by imaging the area in front of the vehicle. The image processing circuit is capable of generating point sequence data indicating the position of the center of the road on which the vehicle is traveling, based on the image. The steering device is capable of steering the vehicle. The control circuit is capable of calculating a target steering angle of the vehicle based on the point sequence data and driving data including data on multiple driving parameters, including the vehicle's driving speed, and can control the operation of the steering device based on the target steering angle. The control circuit is capable of calculating multiple time intervals by dividing the distance between adjacent points among the multiple points included in the point sequence data by the driving speed, predicting future driving data as the multiple time intervals have sequentially elapsed based on the driving data using model predictive control, and calculating a target steering angle based on the point sequence data and the predicted future driving data.

[0006] The accompanying drawings are provided for further understanding of this disclosure and are incorporated herein and constitute part of this specification. The drawings illustrate one embodiment and, together with the specification, serve to illustrate the principles of this disclosure.

[0007] Figure 1 is an explanatory diagram showing an example configuration of a steering system according to one embodiment of the present disclosure. Figure 2 is an explanatory diagram showing an example of the point sequence data shown in Figure 1. Figure 3 is a flowchart showing an example of operation of the control device shown in Figure 1. Figure 4 is an explanatory diagram showing an example of operation of the MPC calculation unit shown in Figure 1. Figure 5 is an explanatory diagram showing an example of operation of the MPC calculation unit according to a reference example.

[0008] In model-based predictive control, it is desirable to improve the accuracy of calculations while reducing the amount of computation.

[0009] It is desirable to provide a steering control device and a vehicle that can improve the accuracy of calculations while reducing the amount of calculation required.

[0010] Hereinafter, several exemplary embodiments of the present disclosure will be described in detail with reference to the accompanying drawings. The following description is intended to illustrate specific examples of the present disclosure and should not be construed as limiting the disclosure. For example, elements such as numerical values, shapes, materials, parts, the location of each part, and the method of connecting each part are merely examples and should not be construed as limiting the disclosure. Furthermore, in the following exemplary embodiments, components not described in separate sections based on the highest-level concepts of the present disclosure are optional and may be provided as needed. The drawings are schematic and are not intended to be to scale. Throughout this specification and the drawings, components having substantially the same function and substantially the same configuration are denoted by the same reference numerals, and redundant descriptions are omitted. Furthermore, components not directly related to an embodiment of the present disclosure are not shown in the drawings.

[0011] <Embodiment> [Configuration Example] Figure 1 shows an example configuration of a steering system 10 equipped with a steering control device according to one embodiment. This steering system 10 is installed in a vehicle 1. The steering system 10 is configured to control the steering of the vehicle 1 so that the vehicle 1 continues to travel near the center of the road. The steering system 10 may be a system that assists the driver's steering operation, or it may be a steering system for autonomous driving. The steering system 10 includes an imaging device 11, an image processing device 12, a vehicle sensor 13, a control device 20, and a steering device 14.

[0012] The imaging device 11 is configured to image the area in front of the vehicle 1. In this example, the imaging device 11 is a stereo camera and includes a left camera and a right camera. Each of the left and right cameras includes a lens and an image sensor. In this example, the imaging device 11 is positioned inside the vehicle 1, above the windshield of the vehicle 1. The left and right cameras are positioned at a predetermined distance apart in the width direction of the vehicle 1. The left camera generates a left image, and the right camera generates a right image. The left and right images constitute a stereo image. The imaging device 11 is configured to generate a series of stereo images by performing imaging operations at a predetermined frame rate (e.g., 30 fps).

[0013] The image processing device 12 is configured to generate data about the road on which the vehicle 1 is traveling, and driving data of the vehicle 1, based on the stereo image supplied from the imaging device 11. Specifically, the image processing device 12 generates a distance image by performing pattern matching processing based on the left and right images included in the stereo image. Then, based on the stereo image and the distance image, the image processing device 12 generates point sequence data DP indicating the position of the center of the road in real space by identifying the center in the width direction of the road for the vehicle 1. The image processing device 12 also generates data about the curvature of the road. This data is data about the road for the vehicle 1. The image processing device 12 also generates data about the position (offset amount) of the vehicle 1 relative to the center of the road in the width direction, and data about the direction of travel of the vehicle 1 relative to the extension direction of the road (yaw angle relative to the lane). This data is driving data of the vehicle 1. The image processing device 12 supplies this data as data DD to the MPC calculation unit 22 (described later) of the control device 20. Furthermore, the image processing device 12 supplies the point sequence data DP from the data DD to the sample time setting unit 21 (described later) of the control device 20.

[0014] Figure 2 shows an example of point sequence data DP. The image processing device 12 identifies the vehicle's travel path 100 based on the stereo image supplied from the imaging device 11. The image processing device 12 then identifies the center of the vehicle's travel path 100 in the width direction and generates point sequence data DP indicating the position of the center of the travel path. Figure 2 illustrates six points P1 to P6 that are close to the vehicle 1 from among the multiple points included in this point sequence data DP. Point P1 is a point located at a distance ΔL1 from the imaging device 11 of the vehicle 1. Point P2 is a point located at a distance ΔL2 from point P1. Point P3 is a point located at a distance ΔL3 from point P2. Point P4 is a point located at a distance ΔL4 from point P3. Point P5 is a point located at a distance ΔL5 from point P4. Point P6 is a point located at a distance ΔL6 from point P5. Distances ΔL1 to ΔL6 may be the same or different from each other. In this example, distance ΔL1 is 7m, and distances ΔL2 to L6 are 5m. The image processing device 12 generates point sequence data DP containing data about the positions of these multiple points. The image processing device 12 then supplies this point sequence data DP to the control device 20.

[0015] The vehicle sensor 13 (Figure 1) is configured to detect the state of the vehicle 1 and includes various sensors. Specifically, the vehicle sensor 13 includes a steering angle sensor, a vehicle speed sensor, and an acceleration sensor. The steering angle sensor is configured to detect the steering angle of the vehicle 1. In this example, the vehicle speed sensor is configured to detect the vehicle's speed based on the rotational speed of the vehicle's wheels. The acceleration sensor is configured to detect the longitudinal and lateral acceleration of the vehicle 1. These detection results constitute the vehicle's driving data. The vehicle sensor 13 supplies the detection results from these sensors as data DS to the MPC calculation unit 22 (described later) of the control device 20. The vehicle sensor 13 also supplies the vehicle speed data DVS, which is the vehicle's speed from this data DS, to the sample time setting unit 21 (described later) of the control device 20.

[0016] The control device 20 is configured to control the operation of the steering device 14 based on data DD, point sequence data DP supplied from the image processing device 12, data DS supplied from the vehicle sensor 13, and vehicle speed data DVS. The control device 20 predicts future driving data of the vehicle 1 in units of sample time using model predictive control. Then, the control device 20 determines a target steering angle of the vehicle 1 based on the predicted future driving data, and controls the operation of the steering device 14 based on this target steering angle. The control device 20 is configured to include one or more processors and one or more memories. The control device 20 has a sample time setting unit 21, a model predictive control (MPC) calculation unit 22, and a steering control unit 23.

[0017] The sample time setting unit 21 is configured to set the sample time Δt used in model predictive control based on the point sequence data DP and the vehicle speed data DVS.

[0018] The MPC calculation unit 22 is configured to predict future driving data of vehicle 1 based on the vehicle 1's driving data included in data DD and DS. In this case, the MPC calculation unit 22 predicts the future driving data of vehicle 1 in units of the sample time Δt set by the sample time setting unit. Then, based on the predicted future driving data, the point sequence data DP included in data DD, and data on the curvature of the road, the MPC calculation unit 22 determines the target steering angle of vehicle 1 so that vehicle 1 continues to travel near the center of the road.

[0019] The steering control unit 23 is configured to control the operation of the steering device 14 based on the target steering angle determined by the MPC calculation unit 22.

[0020] The steering device 14 is configured to steer the vehicle 1 by changing the direction of the vehicle's wheels based on instructions from the steering control unit 23 of the control device 20, and includes a steering mechanism and an electric motor for power steering.

[0021] Here, the control device 20 corresponds to a specific example of the "control circuit" in one embodiment of the present disclosure. The point sequence data DP corresponds to a specific example of the "point sequence data" in one embodiment of the present disclosure. The offset amount, lane-to-lane yaw angle, steering angle, driving speed, and acceleration correspond to a specific example of the "multiple driving parameters" in one embodiment of the present disclosure. The sample time Δt corresponds to a specific example of the "time interval" in one embodiment of the present disclosure. The imaging device 11 corresponds to a specific example of the "imaging device" in one embodiment of the present disclosure. The image processing device 12 corresponds to a specific example of the "image processing circuit" in one embodiment of the present disclosure. The steering device 14 corresponds to a specific example of the "steering device" in one embodiment of the present disclosure.

[0022] [Operation and Function] Next, the operation and function of the steering system 10 of this embodiment will be described.

[0023] (Overall Operation Overview) First, the operation of the steering system 10 will be explained with reference to Figure 1. The imaging device 11 captures an image of the area in front of the vehicle 1. The image processing device 12 generates data about the vehicle 1's travel path and the vehicle 1's travel data based on the stereo image supplied from the imaging device 11. The data about the travel path includes point sequence data DP indicating the position of the center of the travel path, and data about the curvature of the travel path. The vehicle 1's travel data includes data about the offset amount and the lane-to-lane yaw angle. The image processing device 12 supplies this data as data DD to the MPC calculation unit 22 of the control device 20. The image processing device 12 also supplies the point sequence data DP from this data DD to the sample time setting unit 21 of the control device 20. The vehicle sensor 13 detects the vehicle 1's steering angle, travel speed, and acceleration. The vehicle sensor 13 then supplies data about these as data DS to the MPC calculation unit 22 of the control device 20. Furthermore, the vehicle sensor 13 supplies the vehicle speed data DVS, which is the driving speed of the vehicle 1 from the data DS, to the sample time setting unit 21 of the control device 20.

[0024] The sample time setting unit 21 of the control device 20 sets the sample time Δt used in model predictive control based on the point sequence data DP and the vehicle speed data DVS. The MPC calculation unit 22 predicts the future driving data of vehicle 1 based on the driving data of vehicle 1 included in the data DD and DS. At that time, the MPC calculation unit 22 predicts the future driving data of vehicle 1 in units of the sample time Δt set by the sample time setting unit. Then, based on the predicted future driving data and the point sequence data DP and data on the curvature of the road included in the data DD, the MPC calculation unit 22 determines the target steering angle of vehicle 1 so that vehicle 1 continues to travel near the center of the road. The steering control unit 23 controls the operation of the steering device 14 based on the determined target steering angle.

[0025] (Detailed Operation) Figure 3 shows an example of the operation of the control device 20. The control device 20 performs the following processing each time data DD, point sequence data DP, data DS, and vehicle speed data DVS are supplied.

[0026] First, the sample time setting unit 21 of the control device 20 sets the sample time Δt based on the point sequence data DP and the vehicle speed data DVS (step S101). Specifically, the sample time setting unit 21 calculates the sample time Δt (sample time Δt1) by dividing the distance ΔL1 by the driving speed of the vehicle 1 indicated by the vehicle speed data DVS, based on the point sequence data DP shown in Figure 2. Similarly, the sample time setting unit 21 calculates the sample time Δt (sample time Δt2) by dividing the distance ΔL2 by the vehicle speed 1, the sample time Δt (sample time Δt3) by dividing the distance ΔL3 by the vehicle speed 1, the sample time Δt (sample time Δt4) by dividing the distance ΔL4 by the vehicle speed 1, the sample time Δt (sample time Δt5) by dividing the distance ΔL5 by the vehicle speed 1, and the sample time Δt (sample time Δt6) by dividing the distance ΔL6 by the vehicle speed 1. The same applies to subsequent sequences of points.

[0027] Next, the MPC calculation unit 22 of the control device 20 predicts future driving data of vehicle 1 based on the driving data of vehicle 1 included in data DD and DS, using the sample time Δt calculated in step S101 as the unit (step S102). Specifically, the MPC calculation unit 22 predicts the driving data after a sample time Δt1 has elapsed, then predicts the driving data after a sample time Δt2 has elapsed, then predicts the driving data after a sample time Δt3 has elapsed, then predicts the driving data after a sample time Δt4 has elapsed, then predicts the driving data after a sample time Δt5 has elapsed, and then predicts the driving data after a sample time Δt6 has elapsed. The same applies thereafter.

[0028] Figure 4 shows an example of predicted driving data. In this prediction, vehicle 1 will travel to position A1 after a sample time Δt1 has elapsed, then to position A2 after a further sample time Δt2 has elapsed, then to position A3 after a further sample time Δt3 has elapsed, then to position A4 after a further sample time Δt4 has elapsed, then to position A5 after a further sample time Δt5 has elapsed, and then to position A6 after a further sample time Δt6 has elapsed. The same applies thereafter. The MPC calculation unit 22 predicts the offset amount, lane-to-lane yaw angle, steering angle, driving speed, acceleration, etc., of vehicle 1 at each of these timings.

[0029] Next, the MPC calculation unit 22 of the control device 20 determines a target steering angle for the vehicle 1 so that the vehicle 1 continues to travel near the center of the road, based on the predicted future driving data, the point sequence data DP, and the data on the curvature of the road (step S103).

[0030] Then, the steering control unit 23 controls the operation of the steering device 14 based on the determined target steering angle (step S104).

[0031] This concludes this flow.

[0032] Thus, in the steering system 10, the sample time setting unit 21 sets the sample time Δt based on the point sequence data DP and the vehicle speed data DVS, and the MPC calculation unit 22 predicts the future driving data of the vehicle 1 based on the driving data of the vehicle 1 included in the data DD and DS, using this sample time Δt as the unit. As a result, the steering system 10 can reduce the amount of calculation while increasing the accuracy of the calculation.

[0033] In other words, in typical model predictive control, the sample time Δt is set to a predetermined fixed value. When using such model predictive control, the MPC calculation unit 22 predicts the future driving data of vehicle 1 using this predetermined fixed value, the sample time Δt, as a unit, for example, as shown in Figure 5. In Figure 5, positions A11 to A19 are the future driving positions of vehicle 1. In this case, since the point sequence data DP and the predicted driving data are different time-series data, the calculation accuracy when calculating the steering angle based on the point sequence data DP and the predicted future driving data decreases. Furthermore, in order to improve the calculation accuracy, it is necessary to shorten this sample time Δt. However, in this case, the calculation load increases.

[0034] On the other hand, in this embodiment, the sample time Δt is calculated based on the point sequence data DP, in accordance with the interval included in the point sequence data DP. This allows the time series of the predicted driving data to be aligned with the time series of the point sequence data DP, thus preventing a decrease in calculation accuracy. Furthermore, since it is only necessary to align the time series of the predicted driving data with the time series of the point sequence data DP, it is not necessary to further reduce the sample time Δt, thus reducing the computational load.

[0035] Thus, the steering system 10 is equipped with a control circuit (control device 20) capable of calculating the target steering angle of the vehicle based on point sequence data DP indicating the center position of the road on which the vehicle (vehicle 1) is traveling, and driving data including data on multiple driving parameters, including the driving speed of the vehicle (vehicle 1). The control circuit (control device 20) is capable of calculating multiple time intervals (multiple sample times Δt) by dividing the distance between adjacent points among the multiple points included in the point sequence data DP by the driving speed, predicting future driving data for each of the multiple time intervals (multiple sample times Δt) as they sequentially elapse based on the driving data using model predictive control, and calculating the target steering angle based on the point sequence data DP and the predicted future driving data. As a result, the steering system 10 can match the time series of the predicted driving data with the time series of the point sequence data DP. Consequently, the steering system 10 can improve the accuracy of calculations while reducing the amount of computation.

[0036] [Effects] As described above, this embodiment includes a control circuit capable of calculating the target steering angle of the vehicle based on point sequence data indicating the center position of the road on which the vehicle is traveling, and driving data including data on multiple driving parameters, including the vehicle's speed. The control circuit is capable of calculating multiple time intervals by dividing the distance between adjacent points among the multiple points included in the point sequence data by the driving speed, predicting future driving data for each of the multiple time intervals as they sequentially elapse based on the driving data using model predictive control, and calculating the target steering angle based on the point sequence data and the predicted future driving data. This makes it possible to reduce the amount of computation while increasing the accuracy of the calculation.

[0037] While several embodiments of this disclosure have been described above with reference to the accompanying drawings, this disclosure is by no means limited to the embodiments described above. Those skilled in the art will understand that various modifications and changes can be made without departing from the scope defined by the claims. This disclosure is intended to encompass such modifications and changes insofar as they fall within the scope of the claims and their equivalents.

[0038] For example, in the above embodiment, the steering system 10 generates data about the curvature of the road based on stereo images, but it is not limited to this. Alternatively, for example, a locator device may be provided to generate data about the curvature of the road based on map data at the vehicle's position.

[0039] Furthermore, although the imaging device 11 in the above embodiment uses a stereo camera, it is not limited to this, and a monocular camera may be used instead. When using a monocular camera, a distance measuring device such as LiDAR (Light Detection and Ranging) may also be used.

[0040] The effects described herein are illustrative only, and the effects of this disclosure are not limited to those described herein. Therefore, other effects may be obtained with respect to this disclosure.

[0041] Furthermore, this disclosure may take the following forms:

[0042] (1) A steering control device comprising a control circuit capable of calculating a target steering angle of the vehicle based on driving data which includes a sequence of points indicating the position of the center of the road on which the vehicle is traveling, and data on a plurality of driving parameters including the driving speed of the vehicle, wherein the control circuit is capable of calculating a plurality of time intervals by dividing the distance between adjacent points among the plurality of points included in the sequence of points by the driving speed, predicting future driving data for each of the plurality of time intervals as they have sequentially elapsed based on the driving data using model predictive control, and calculating the target steering angle based on the sequence of points and the predicted future driving data. (2) The steering control device according to (1), wherein the plurality of driving parameters further include one or more of the following: the position of the vehicle with respect to the center of the road in the width direction of the road, the direction of travel of the vehicle with respect to the extension direction of the road, the steering angle of the vehicle, and the acceleration of the vehicle. (3) A vehicle comprising: an imaging device capable of generating an image by imaging the area in front of the vehicle; an image processing circuit capable of generating a sequence of points data indicating the position of the center of the road on which the vehicle is traveling based on the image; a steering device capable of steering the vehicle; and a control circuit capable of calculating a target steering angle of the vehicle based on the sequence of points data and driving data including data on a plurality of driving parameters including the vehicle's speed, and controlling the operation of the steering device based on the target steering angle, wherein the control circuit is capable of: calculating a plurality of time intervals by dividing the distance between adjacent points among the plurality of points included in the sequence of points data by the driving speed; predicting future driving data for each of the plurality of time intervals as they have sequentially elapsed based on the driving data using model predictive control; and calculating the target steering angle based on the sequence of points data and the predicted future driving data.

[0043] The control device 20 shown in Figure 1 can be implemented by a circuit including at least one semiconductor integrated circuit, such as at least one processor (e.g., a central processing unit (CPU)), at least one application-specific integrated circuit (ASIC) and / or at least one field-programmable gate array (FPGA). The at least one processor can be configured to perform all or some of the functions of the control device 20 shown in Figure 1 by reading instructions from at least one non-temporary, tangible computer-readable medium. Such a medium can take various forms, including, but is not limited to, various magnetic media such as hard disks, various optical media such as CDs or DVDs, and various semiconductor memories (i.e., semiconductor circuits) such as volatile or non-volatile memory. Volatile memory may include DRAM and SRAM. Non-volatile memory may include ROM and NVRAM. An ASIC is an integrated circuit (IC) specialized to perform all or some of the functions of the control device 20 shown in Figure 1. An FPGA is an integrated circuit designed to be configurable after manufacturing to perform all or some of the functions of the control device 20 shown in Figure 1.

Claims

1. A steering control device comprising a control circuit capable of calculating a target steering angle of a vehicle based on a sequence of points data indicating the center position of the road on which the vehicle is traveling, and driving data including data on multiple driving parameters including the vehicle's speed, wherein the control circuit is capable of calculating multiple time intervals by dividing the distance between adjacent points among the multiple points included in the sequence of points data by the driving speed, predicting future driving data for each of the multiple time intervals as they sequentially elapse based on the driving data using model predictive control, and calculating the target steering angle based on the sequence of points data and the predicted future driving data.

2. The steering control device according to claim 1, wherein the plurality of driving parameters further include one or more of the following: the position of the vehicle with respect to the center of the road in the width direction of the road, the direction of travel of the vehicle with respect to the extension direction of the road, the steering angle of the vehicle, and the acceleration of the vehicle.

3. A vehicle comprising: an imaging device capable of generating an image by imaging the area in front of the vehicle; an image processing circuit capable of generating a sequence of points indicating the position of the center of the road on which the vehicle is traveling based on the image; a steering device capable of steering the vehicle; and a control circuit capable of calculating a target steering angle of the vehicle based on the sequence of points and driving data including data on a plurality of driving parameters including the vehicle's speed, and controlling the operation of the steering device based on the target steering angle, wherein the control circuit is capable of: calculating a plurality of time intervals by dividing the distance between adjacent points among the plurality of points included in the sequence of points by the driving speed; predicting future driving data as the plurality of time intervals have sequentially elapsed based on the driving data using model predictive control; and calculating the target steering angle based on the sequence of points and the predicted future driving data.

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