Methods and systems for estimating vehicle load and trailer drawbar load based on camera images

Abstract

Methods and systems are provided for a vehicle towing a trailer. In one embodiment, a method comprises: receiving image data from one or more image sensors of the vehicle using a processor; determining a change in vehicle height based on the image data using the processor; determining a vehicle load and / or a trailer drawbar load based on the change in vehicle height using the processor; and generating notification data and / or control data using the processor to control the vehicle based on the vehicle load and / or the trailer drawbar load.

Description

introduction

[0001] The technical field relates generally to vehicles and, more particularly, to methods and systems for determining vehicle load and trailer drawbar load values ​​associated with a trailer coupled to the vehicle and for controlling the vehicle based on the determined values.

[0002] Trailer tongue load is a measure of the load the trailer tongue exerts on a vehicle's trailer hitch. Vehicle load is a measure of the vehicle's payload. If either load is too high, vehicle performance may be suboptimal. For example, trailer sway and / or vehicle instability may occur. Most vehicles are not equipped with sensors to directly record load values. Adding additional sensors to directly record load values ​​increases vehicle complexity.

[0003] DE 10 2023 119 679 A1 describes methods and systems comprising one or more underbody cameras and a processor for a vehicle. The underbody cameras are configured to capture camera images from beneath the vehicle. The processor is coupled to the one or more underbody cameras and configured to enable at least the following: performing image processing on the camera images; and determining a ride height, a measure of the vehicle's weight, or both, based on the camera images from the one or more underbody cameras and their processing by the processor.

[0004] US 2016 / 0 305 814 A1 describes an intelligent communication device that estimates the weight of a motor vehicle, including the front and rear wheel assemblies, after the vehicle has been loaded.A method includes identifying the vehicle in the intelligent communication device, using a camera of the intelligent communication device to capture and process a photograph of at least one wheel, wherein at least one point of the vehicle is lowered together with a suspension of the wheel of the vehicle when loading the vehicle, determining a distance of the wheel assembly relative to the photographed wheel, calculating a load value on the wheel assembly of the photographed wheel and a load value on the opposite wheel assembly as a function of the respective distances of these wheel assemblies to determine a total load value, and using the intelligent communication device to inform a user of a loading condition of the vehicle.

[0005] EP 3 137 859 B1 describes a method for determining the mass of a vehicle whose wheels are mounted in wheel arches using a smartphone.

[0006] It is desirable to provide methods and systems for determining load values ​​related to the trailer tongue load and the vehicle load without adding additional load sensors. Furthermore, it is desirable to improve vehicle performance based on the determined load values. Other desirable features and characteristics of the present invention will become apparent from the following detailed description and the appended claims, considered in conjunction with the accompanying drawings and this background introduction. Description

[0007] Methods and systems are provided for a vehicle configured to tow a trailer. According to the invention, a method comprises: receiving, by a processor, image data from one or more image sensors of the vehicle; determining, by the processor, a change in vehicle height based on the image data; determining, by the processor, a vehicle load and / or a trailer tongue load based on the change in vehicle height; determining a road grade angle from global positioning data and scaling, by the processor, the vehicle load and / or the trailer tongue load based on the road grade angle; and generating, by the processor, notification data and / or control data to control the vehicle based on the vehicle load and / or the trailer tongue load.

[0008] In various embodiments, the method comprises determining a front wheel or axle position and a rear wheel or axle position from the image data, and wherein determining the change in vehicle height is based on the front wheel or axle position and the rear wheel or axle position.

[0009] In various embodiments, the method includes evaluating a speed of the vehicle and enabling determining the change in vehicle height based on the evaluation.

[0010] In various embodiments, the method includes evaluating the state of the image sensor and enabling the change in vehicle height to be determined based on the evaluation.

[0011] In various embodiments, the method comprises evaluating a visibility of a front wheel or axle position and a rear wheel or axle position from the image data; and enabling determining the change in vehicle height based on the evaluation.

[0012] In various embodiments, the method includes determining whether a road grade angle can be determined, and if the road grade angle cannot be determined, the notification data includes congestion information.

[0013] In various embodiments, the method includes determining a road grade angle from the image data and scaling, by means of the processor, the vehicle load and / or the trailer tongue load based on the road grade angle.

[0014] In various embodiments, the method comprises determining a first pixel count between a first point and a second point in a first image of the image data in which the vehicle is unloaded; determining a second pixel count between a third point and a fourth point in a second image of the image data in which the vehicle is loaded; and converting the first and second pixel counts into a metric height, and wherein determining the change in vehicle height is based on the converted metric heights.

[0015] In various embodiments, the method includes wherein the first point and the third point are connected to a body of the vehicle, and wherein the second point and the fourth point are connected to a tire or an axle of the vehicle.

[0016] According to the invention, a system comprises: a non-transitory computer-readable medium configured to store suspension parameters; and a computer system onboard the vehicle. The computer system is configured to: receive image data from one or more image sensors of the vehicle; determine a change in vehicle height based on the image data; determine a vehicle load and / or a trailer tongue load based on the change in vehicle height; determine a road grade angle from global positioning data and scale the vehicle load and / or the trailer tongue load based on the road grade angle; and generate notification data and / or control data to control the vehicle based on the vehicle load and / or the trailer tongue load.

[0017] In various embodiments, the computer system is further configured to determine a front wheel or axle position and a rear wheel or axle position from the image data, and wherein it determines the change in vehicle height based on the front wheel or axle position and the rear wheel or axle position.

[0018] In various embodiments, the computer system is further configured to evaluate a speed of the vehicle and enables determining the change in vehicle height based on the evaluation.

[0019] In various embodiments, the computer system is further configured to evaluate the state of the image sensor and enable determining the change in vehicle height based on the evaluation.

[0020] In various embodiments, the computer system is further configured to evaluate visibility of a front wheel or axle position and the rear wheel or axle position from the image data; and to enable determining the change in vehicle height based on the evaluation.

[0021] In various embodiments, the computer system is further configured to determine whether a road grade angle can be determined, and if the road grade angle cannot be determined, the notification data includes overload information.

[0022] In various embodiments, the computer system is further configured to determine a first pixel count between a first point and a second point in a first image of the image data in which the vehicle is unloaded; determine a second pixel count between a third point and a fourth point in a second image of the image data in which the vehicle is loaded; and convert the first and second pixel counts to a metric height and determine the change in vehicle height based on the converted metric heights.

[0023] In various embodiments, the first point and the third point are connected to a body of the vehicle, and the second point and the fourth point are connected to a tire or an axle of the vehicle.

[0024] In one example, a vehicle comprises: at least one camera configured to capture a side view of the vehicle; and a computer system configured, via a processor, to: receive image data from one or more image sensors of the vehicle; determine a change in vehicle height based on the image data; determine a vehicle load and / or a trailer tongue load based on the change in vehicle height; and generate notification data and / or control data to control the vehicle based on the vehicle load and / or the trailer tongue load. Description of the drawings

[0025] The present disclosure will now be described in conjunction with the following drawings, wherein like numerals indicate like elements and wherein: Fig. 1 is a functional block diagram of a vehicle including a system for determining the load value according to various embodiments; Fig. 2 a data flow diagram showing elements of the vehicle’s load value determination system from Fig. 1 according to various embodiments; Fig. 3 and Fig. 4 are illustrations of the parameters calculated by the load value determination system; and Fig. 5 is a flowchart illustrating a process for determining load values ​​as performed by the load value determination system of the vehicle of the Fig. 1 and Fig. 2 is carried out according to exemplary embodiments. Detailed description

[0026] The following detailed description is merely exemplary and is not intended to limit the application and uses. Furthermore, there is no intention to be bound by any express or implied theories presented in the foregoing technical field, background, brief summary, or the following detailed description. As used herein, the term module refers to any hardware, software, firmware, electronic control component, processing logic, and / or processor device, alone or in any combination, including, but not limited to: application-specific integrated circuits (ASICs), an electronic circuit, a processor (collectively, dedicated, or as a group), and memory executing one or more software or firmware programs, combinational logic circuitry, and / or other suitable components that provide the described functionality.

[0027] Embodiments of the present disclosure may be described herein in terms of functional and / or logical block components and various processing steps. Such block components may be implemented by any number of hardware, software, and / or firmware components configured to perform the specified functions. For example, an embodiment of the present disclosure may utilize various integrated circuit components, such as memory elements, digital signal processing elements, logic elements, lookup tables, or the like, that can perform a variety of functions under the control of one or more microprocessors or other controllers.Furthermore, those skilled in the art will recognize that embodiments of the present disclosure may be used in connection with any number of systems and that the systems described herein are merely exemplary embodiments of the present disclosure.

[0028] For the sake of brevity, conventional techniques related to signal processing, data transmission, signaling, control, and other functional aspects of the systems (and the individual operating components of the systems) are not described in detail here. Furthermore, the connecting lines depicted in the various figures are intended to represent exemplary functional relationships and / or physical couplings between the various elements. It should be noted that many alternative or additional functional relationships or physical connections may be present in an embodiment of the present disclosure.

[0029] Referring to Fig. 1, a load rating system, generally shown at 100, is connected to a vehicle 10 in accordance with various embodiments. Generally, the load rating system 100 estimates load values, such as the vehicle load and / or the trailer tongue load, while the vehicle 10 is towing a trailer 12. As explained in more detail below, the load rating system 100 determines the values ​​based on an analysis of image data provided by a camera capturing side view images of the vehicle 10.

[0030] As in Fig. 1, the vehicle 10 includes an automobile configured to tow the trailer 12. The vehicle 10 may be any number of different types of motor vehicles, such as a sedan, a station wagon, a truck (as shown), or a sport utility vehicle (SUV), and may be two-wheel drive (2WD) (i.e., rear-wheel drive or front-wheel drive), four-wheel drive (4WD), or all-wheel drive (AWD), and / or various other types of vehicles in certain embodiments. In various embodiments, the vehicle 10 may also include other types of mobile platforms and is not limited to an automobile. In various embodiments, the trailer 12 may be any type of towable application having one or more wheels and is not limited to any particular embodiment.

[0031] The vehicle 10 is configured to be coupled and connected to the trailer 12 via a coupling device 11 and is configured to pull the trailer 12. In various embodiments, the coupling device 11 includes a coupling mechanism having a ball connected to a tongue of the trailer 12. When coupled to the vehicle 10, the tongue exerts a load on the coupling mechanism and thus on the vehicle 10. This load exerted on the trailer tongue is referred to as the trailer tongue load. The load transferred to the vehicle by the trailer 12 and other payload in the vehicle 10 is referred to as the vehicle load.

[0032] As in Fig. 1, the example vehicle 10 generally includes a chassis 13, a body 14, front wheels 16, rear wheels 18, and a suspension system 19. The body 14 is disposed on the chassis 13 and substantially encloses components of the vehicle 10. The body 14 and the chassis 13 may together form a frame. The wheels 16-18 are each rotatably connected to the chassis 13 via the axles 17 (front and rear) of the suspension system 19 near a corresponding corner of the body 14. In various embodiments, the wheels 16-18 include tires connected to rims. The vehicle 10 further includes a drive system 20, a transmission system 22, a steering system 24, a braking system 26, a sensor system 28, an actuator system 30, at least one data storage device 32, at least one controller 34, and a display system 35. In various embodiments, the drive system 20 may include an internal combustion engine, an electric machine, such as a traction motor, and / or a fuel cell drive system. The transmission system 22 is configured to transfer the power of the drive system 20 to the vehicle wheels 16-18 according to selectable gear ratios. According to various embodiments, the transmission system 22 may include a continuously variable automatic transmission, a continuously variable transmission, or another suitable transmission. The braking system 26 is configured to apply braking torque to the vehicle wheels 16-18.The braking system 26 may, in various embodiments, include friction brakes, cable brakes, a regenerative braking system such as an electric machine, and / or other suitable braking systems. The steering system 24 influences a position of the vehicle wheels 16-18. Although a steering wheel is shown for illustrative purposes, the steering system 24 may not include a steering wheel in some embodiments contemplated by the present disclosure.

[0033] The sensor system 28 includes one or more sensing devices 40a-40n that sense observable conditions of the external and / or internal environment of the vehicle 10 and / or the components of the vehicle 10 itself. The sensor devices 40a-40n may include, but are not limited to, radars, lidars, global positioning systems, optical cameras, thermal cameras, ultrasonic sensors, inertial measurement units, pressure sensors, position sensors, displacement sensors, speed sensors, and / or other sensors. In various embodiments, one or more of the sensing devices 40a-40n include one or more side-view cameras configured to capture a side-view image of the vehicle 10. In various embodiments, the side-view camera is integrated into the vehicle 10, for example, as part of a side-view mirror.In various other embodiments, the side camera is an auxiliary camera (i.e., configured on a remote vehicle 10 or a remote device, such as a user device) that transmits data associated with the captured images to the vehicle 10.

[0034] The actuator system 30 includes one or more actuator devices 42a-42n that control one or more vehicle functions, such as, but not limited to, the drive system 20, the transmission system 22, the steering system 24, and the braking system 26. In various embodiments, the vehicle features may also include interior and / or exterior features of the vehicle, such as doors, a trunk, and cabin features such as air, music, lighting, etc. (unnumbered).

[0035] Data storage 32 stores data used to control vehicle 10. In various embodiments, data storage device 32 stores defined values ​​for performing load value determination and controlling vehicle 10. As can be appreciated, data storage device 32 may be part of controller 34, separate from controller 34, or part of controller 34 and part of a separate system.

[0036] The controller 34 includes at least one processor 44, a communications bus 45, and a computer-readable storage device or medium 46. The processor 44 may be any custom or off-the-shelf processor, a central processing unit (CPU), a graphics processing unit (GPU), an auxiliary processor among multiple processors connected to the controller 34, a semiconductor-based microprocessor (in the form of a microchip or chipset), a macroprocessor, any combination thereof, or generally any device for executing instructions. The computer-readable storage devices or media 46 may include volatile and non-volatile memory, for example, read-only memory (ROM), random access memory (RAM), and keep-alive memory (KAM). KAM is persistent or non-volatile memory that can be used to store various operating variables while the processor 44 is powered off.Computer-readable storage device(s) 46 may be implemented using any number of known storage devices such as PROMs (Programmable Read-Only Memory), EPROMs (Electrical PROMs), EEPROMs (Electrically Erasable PROMs), flash memory, or other electrical, magnetic, optical, or combination storage devices capable of storing data, some of which may be executable instructions used by controller 34 in controlling vehicle 10. Bus 45 is used to communicate programs, data, status, and other information or signals between the various components of the vehicle and / or trailer. Bus 45 may be any suitable physical or logical means for interconnecting computer systems and components. These include, but are not limited to, direct, hard-wired connections, fiber optic, infrared, and wireless bus technologies.

[0037] The instructions may include one or more separate programs, each containing an ordered list of executable instructions for implementing logical functions. When executed by processor 44, the instructions receive and process signals from sensor system 28, perform logic, calculations, methods, and / or algorithms to automatically control the components of vehicle 10, and generate control signals for actuator system 30 to automatically control the components of vehicle 10 based on the logic, calculations, methods, and / or algorithms. Although in Fig. 1 only one controller 34 is shown, embodiments of the vehicle 10 may include any number of controllers 34 that communicate and cooperate via any suitable communication medium or combination of communication media to process the sensor signals, perform logic, calculations, methods and / or algorithms, and generate control signals to automatically control features of the vehicle 10.

[0038] In various embodiments, one or more instructions of controller 34 are included in load value determination system 100 that, when executed by processor 44, receive data from sensor system 28 and process the received data to extract points that identify deflections of vehicle 10. The instructions use the extracted points to estimate the trailer tongue load and the vehicle load. The instructions further process the sensor data to determine a road grade angle and adjust the trailer tongue load and vehicle load estimates based on the road grade angle, if available. The instructions are further configured to control vehicle 10 based on the determined load values.

[0039] As can be seen, the control 34 can be different from the Fig. 1. For example, the controller 34 may be coupled to or otherwise utilize one or more remote computer systems and / or other control systems, for example, as part of one or more of the vehicle devices and systems mentioned above.While this exemplary embodiment is described in the context of a fully functional computer system, those skilled in the art will recognize that the mechanisms of the present disclosure may be distributed as a program product having one or more types of non-transitory, computer-readable, signal-bearing media used to store the program and its instructions and to facilitate its distribution, such as a non-transitory, computer-readable medium carrying the program and having computer instructions stored therein for causing a computer processor (such as processor 44) to perform and execute the program. Such a program product may take a variety of forms, and the present disclosure applies equally regardless of the particular type of computer-readable, signal-bearing media used to facilitate distribution.Examples of signal-carrying media include writable media such as floppy disks, hard disks, memory cards, and optical disks, as well as transmission media such as digital and analog communication links. In certain embodiments, cloud-based storage and / or other technologies may also be used. It will also be appreciated that the computer system of the controller 34 may otherwise differ from the system illustrated in FIG. Fig. 1, for example, in that the computer system of the controller 34 may be coupled to or otherwise utilize one or more remote computer systems and / or other control systems.

[0040] With reference to Fig. 2 and with continued reference to Fig. 1 illustrates a data flow diagram of elements of the load value determination system 100 of Fig. 1 in accordance with various embodiments. As can be appreciated, various embodiments of the load value determination system 100 according to the present disclosure may include any number of modules embedded within the controller 34, which may be combined and / or further subdivided to implement the systems and methods described herein in a similar manner. Furthermore, inputs to the load value determination system 100 may be received from the sensor system 28, from other control modules (not shown) connected to the vehicle 10 and / or the trailer 12, and / or from other sub-modules (not shown) within the controller 34 of Fig. 1. In various embodiments, the load value determination system 100 includes an enabling module 202, a vehicle height determination module 204, a load determination module 206, a road grade angle determination module 208, a notification module 210, and a parameter data store 212.

[0041] The parameter data store 212 stores suspension parameters 214 and vehicle and / or camera parameters 216 used in determining the load values, as explained in more detail below. As can be appreciated, the parameters may be predefined during manufacturing and / or adjusted based on user input provided by a user configuring the system 100.

[0042] In various embodiments, the enabling module 202 receives as input image data 218, sensor state data 220, and vehicle speed data 222. In various embodiments, the image data 218 includes a left side view image and / or a right side view image of the vehicle 10 captured by the camera (either integrated with the vehicle 10 or as a separate camera) configured to capture side view images of the vehicle 10. The enabling module 202 evaluates the received data 218-222 based on the defined enabling conditions to enable or disable the load value determination. For example, the enabling module 202 sets the enabling data 224 to a value indicating enabling or disabling based on the evaluation.

[0043] For example, the enabling module 202 evaluates the image data 218 to determine whether both axles or wheels (front and rear), or one axle or wheel (front or rear) and a partial wheel, are visible in the image. If both axles or wheels, or one axle or wheel and a partial wheel, are visible in the image, the enabling module 202 sets the enabling data 224 to enabled. If both axles or wheels, or one partial wheel, are not visible in the image, the enabling module 202 sets the enabling data 224 to disabled.

[0044] In another example, the enabling module 202 evaluates the vehicle speed data 222 to determine whether the vehicle 10 is stationary. If the vehicle 10 is stationary, the enabling module 202 sets the enabling data 224 to enabled. If the vehicle 10 is not stationary, the enabling module 202 sets the enabling data 224 to disabled.

[0045] In another example, the enabling module 202 evaluates the sensor status data 220 to determine whether the sensing device, for example, the camera, is healthy. If the camera is healthy, the enabling module 202 sets the enabling data 224 to "enabled." If the camera is not healthy, the enabling module 202 sets the enabling data 224 to "disabled."

[0046] As can be appreciated, any combination of the described enabling conditions may be used to enable load value determination in various embodiments, as the disclosure is not limited to the present examples.

[0047] The vehicle height determination module 204 receives as input the enable data 224, the image data 218, and the vehicle / camera parameter data 216. If the enable data 224 indicates that the feature is enabled, the vehicle height determination module 204 processes the image data 218 to determine and analyze a frame height of the vehicle 10. For example, the vehicle height determination module 204 preprocesses the image data 218 to enhance the contrast of the image, such as using a histogram stretching technique or another method, and then performs edge detection on the enhanced image data to generate edge data indicating the edges of the detected objects within the image.

[0048] From the edge data, the vehicle height determination module 204 extracts points from the defined edges in the image and uses the points to calculate the vehicle height. In various embodiments, the vehicle height determination module 204 extracts points associated with the vehicle body by comparing the image to a template image that defines the edge of the body. For example, through the comparison, the vehicle height determination module 204 identifies a top center point of each wheel well associated with the wheels 16-18 or with another body component and extracts the associated points from the image.

[0049] In another example, if the clearance data 224 indicates that both axles or wheels are visible, the vehicle height determination module 204 extracts points associated with the center of each wheel (e.g., the point associated with the axle) by fitting an ellipsoidal element to elements in the image to identify the wheels or rims. Once the wheels or rims are identified, the vehicle height determination module 204 identifies the centers of the fitted ellipsoidal elements as the wheel center and extracts the corresponding points in the image.

[0050] In another example, if the clearance data 224 indicates that one or more of the axles or wheels are not fully visible, the vehicle height determination module 204 extracts points associated with the location where the tire contacts the ground by identifying a line with a certain predefined width in a specific area of ​​the image where the tire would be expected to be visible.

[0051] The vehicle height determination module 204 then calculates a vehicle height by determining the difference between a position of the extracted vehicle body point and the tire center point or the tire bottom point for both the front and rear wheels, and generates it based on the vehicle height data 226. In various embodiments, the difference may be calculated, for example, based on counting the number of pixels between the identified points in the image and converting the count into the lengths L1 and L2.

[0052] As in Fig. 3, the following relationships can be used to calculate the vehicle height at the front and rear wheels: β1=sin((x1−x0)2+(y1−y0)2f), β2=sin((x2−x0)2+(y2−y0)2f), L1=Dsin(β1)sin(180−β1−α), L2=Dsin(β2)sin(180−β2−α)and ΔL=L2−L1

[0053] Where f represents the focal length of the camera, x0, y0 represents the location of the extracted image point in image space, x1, y1 represents the observations in the image space of the tire (the central axis or the point where the tire meets the road) at time t1, and x2, y2 represents observations in the image space of the tire at time t2.Where α represents the angle of intersection in object space of the focal ray of the camera with the vertical line through the axis point of the vehicle (along which the vehicle moves up and down), as calculated from the extrinsic parameters of the camera and the vehicle dimensions, D represents the three-dimensional distance in object space between the camera location and the vertical line through the axis point of the vehicle (along which the vehicle moves up and down), calculated from the extrinsic parameters of the camera and the vehicle dimensions, β1 represents the angle between the main ray and the image ray to the tire point in image space at time t1, β1 represents the angle between the main ray and the image ray to the tire point in image space at time t2.And where L1 represents the vehicle height in object space at time t1 (for example, a standard height when the vehicle is unloaded), L2 represents the vehicle height in object space at time t1, and ΔL represents the change in vehicle height in object space between times t1 and t2.

[0054] Back to Fig. 2: In various embodiments, the load determination module 206 receives as input the vehicle height data 226, the suspension parameter data 214, and the vehicle and / or camera parameter data 216. The load determination module 206 converts the vehicle height data 226 into force values ​​based on the suspension parameter data 214. For example, a calibration, a lookup table, or a real-time function may be used to estimate the force values, where the values ​​are defined based on characteristics of the suspension system, derived through data acquisition, or calculated / estimated through simulation.

[0055] Thereafter, the load determination module 206 determines the vehicle load and the trailer tongue load based on the force values ​​and the vehicle parameter data 216 and generates vehicle load data 228 and trailer tongue load data 230 based thereon. As shown in Fig. 4, the following relationships can be used to determine the load values: Ft=−lcΔFf and Fload=ΔFr+ΔFf(1+lc), where F t stands for the load on the trailer drawbar, F f stands for the load on the front axle, F r stands for the load on the rear axle, F load is the load on the vehicle, l is the distance between the front axle and the rear axle of the vehicle 10, and c is the distance between the rear axle and the tongue of the trailer when coupled to the tow bar.

[0056] In various embodiments, the load values ​​for the left side of the vehicle 10 (i.e., the driver side) and the right side (i.e., the passenger side) of the vehicle 10 may be determined depending on the received images. Back to Fig. 2: In various embodiments, the road grade angle determination module 208 receives GPS data 232 and / or image data 218 as input. The road grade angle determination module 208 determines the road grade angle from the GPS data 232 and / or image data 218 and generates road grade angle data 234 therefrom. For example, if GPS data 232 is available, the grade angle is determined from the last recorded position difference (e.g., from a global navigation satellite system (GNSS)).

[0057] If GPS data 232 is unavailable, image data 218 is examined for external line features. For example, the direction of vertical lines and optionally horizontal lines of buildings, polls, street signs, etc. is extracted. The road grade angle determination module 208 determines the road grade from the vector intersection of the extracted lines. As can be appreciated, a combination of GPS data 232 and image data 218 may be used to determine the road grade angle. A combination of these methods or other methods may be used in various embodiments, as the disclosure is not limited to the present example.

[0058] In various embodiments, the reporting module 210 receives as input the road grade angle data 234, the vehicle load data 228, and the trailer tongue load data 230. The notification module 210 evaluates the data and generates notification data 236 and / or control data 238 based thereon. For example, if the grade angle data 234 is available, notification data 236 is generated that includes the current increase or value of the vehicle load and the trailer tongue load. If the vehicle load or the trailer tongue load is greater than a maximum load, notification data 236 is generated to indicate an overload condition. In another example, if the grade angle data 234 is not available and the vehicle load is greater than the maximum load, notification data 236 is generated to indicate an overload condition.

[0059] In various embodiments, the trailer tongue load data 230, the vehicle load data 228, and / or any overload conditions may also be provided as control data 238 to the control system or other vehicle systems for use in automatically controlling the vehicle 10 and / or for display purposes. The load values ​​may be provided, for example, as a load value in Newtons, as a percentage load of a maximum load, or as an image or display representing the load value and / or the percentage load.

[0060] With reference to Fig. 5 and with continued reference to the Fig. 1-2, a flowchart illustrates a method 500 for determining load values ​​and controlling a vehicle 10 based on those values ​​in accordance with exemplary embodiments. As will be appreciated in view of the disclosure, the order of operations within the method 500 is not limited to the order in Fig. 5, but may be performed in one or more varying orders, as applicable and consistent with the present disclosure. In various embodiments, method 500 may be scheduled to execute based on one or more predetermined events and / or may be executed continuously during operation of vehicle 10.

[0061] In one example, method 500 may begin at 502. Enabling conditions are evaluated at 503. For example, the image data is evaluated to determine if both axles and / or wheels (front and rear) are at least partially visible in the image at 504. If both axles and / or wheels are not at least partially visible in the image at 504, the feature is disabled and method 500 may end at 538. If both axles and / or wheels are at least partially visible in the image at 504, the vehicle speed data is evaluated to determine if vehicle 10 is stationary at 506. If vehicle 10 is not stationary at 506, the feature is disabled and method 500 may end at 538.

[0062] If the vehicle 10 is stationary at 506, the camera status data is evaluated to determine whether the camera is OK at 508. If the camera is not OK at 508, the function is deactivated and the method 500 can be terminated at 538. If the camera is OK at 508, the method 500 continues processing the image data to determine the load values ​​at 509.

[0063] For example, the image data is preprocessed at 510 to determine the edge data. Points are extracted from the edge data at 511, and the height of the vehicle frame at the front wheel and / or rear wheel is calculated based on a pixel count at 512. The vehicle frame heights are then used to determine a height change at each wheel from a standard height at 514. The force on the front wheel and the force on the rear wheel are determined based on the respective height change at 516, and the vehicle load and trailer tongue load are determined based on the front axle force and rear axle force, as well as the vehicle parameters, at 518.

[0064] It is then determined whether the road's inclination angle affects the load determination at 519. For example, it is determined at 520 whether GPS is available. If GPS data is available at 520, the road's inclination angle is determined at 522 from the last recorded difference in GNSS. If GPS data is not available at 520, it is determined whether the image data for external line features can be processed at 524. If line features can be extracted at 524, the direction of the vertical lines and optionally the horizontal lines of buildings, polls, street signs, etc. are extracted at 526, and the road inclination angle is determined from the vector intersection of the extracted lines.

[0065] Next, notification data and / or control data are generated at 527, depending on whether the road grade angle was detected. For example, if the road grade data is available at 528, the load values ​​are adjusted to the road grade angle at 530, and notification data is generated that includes the actual increase or value of the vehicle load and the trailer tongue load at 532. Method 500 may then end at 538.

[0066] In another example, if the road angle data is unavailable at 528 and the vehicle load is greater than a maximum load at 534, notification data is generated to indicate an overload condition at 536. Thereafter, the method 500 may exit at 538. As can be appreciated, the overload condition may also be generated regardless of when the road angle data is available in various embodiments, although the flow is not shown.

[0067] Although at least one exemplary embodiment has been presented in the foregoing detailed description, it should be understood that numerous variations exist. It should also be appreciated that the exemplary embodiment or exemplary embodiments are merely examples and are not intended to limit the scope, applicability, or configuration of the disclosure in any way. Rather, the foregoing detailed description is intended to provide one skilled in the art with a convenient guide for implementing the exemplary embodiment or exemplary embodiments. It should be understood that various changes in the function and arrangement of elements may be made without departing from the scope of the disclosure as set forth in the appended claims and their legal equivalents.

Claims

[1] A method for a vehicle (10) configured to tow a trailer (12), comprising: Receiving, by means of a processor (44), image data (218) from one or more image sensors of the vehicle (10); Determining, by means of the processor (44), a change in vehicle height based on the image data (218); Determining, by means of the processor (44), a vehicle load and / or a trailer drawbar load based on the change in vehicle height; Determining a road gradient from global positioning data and scaling, by means of the processor (44), the vehicle load and / or the trailer tongue load based on the road gradient; and Generating, by means of the processor (44), notification data (236) and / or control data (238) to control the vehicle (10) based on the vehicle load and / or the trailer tongue load. [2] The method of claim 1, further comprising determining, by the processor (44), a front wheel or axle position and a rear wheel or axle position from the image data (218), and wherein determining the change in vehicle height is based on the front wheel or axle position and the rear wheel or axle position. [3] The method of claim 1, further comprising evaluating a speed of the vehicle (10) and enabling determining the change in vehicle height based on the evaluation. [4] The method of claim 1, further comprising evaluating a visibility of a front wheel or axle position and a rear wheel or axle position from the image data (218); and enabling the change in vehicle height to be determined based on the evaluation. [5] The method of claim 1, further comprising determining whether a road grade angle can be determined, and if the road grade angle cannot be determined, the notification data (236) comprises overload information. [6] The method of claim 1, further comprising determining a road grade angle from the image data (218) and scaling, by means of the processor (44), the vehicle load and / or the trailer tongue load based on the road grade angle. [7] The method of claim 1, further comprising determining a first pixel count between a first point and a second point in a first image of the image data (218) in which the vehicle (10) is unloaded; determining a second pixel count between a third point and a fourth point in a second image of the image data (218) in which the vehicle (10) is loaded; and converting the first and second pixel counts to a metric height, and wherein determining the change in vehicle height is based on the converted metric heights. [8] The method of claim 7, wherein the first point and the third point are connected to a body (14) of the vehicle (10), and wherein the second point and the fourth point are connected to a tire or an axle (17) of the vehicle (10). [9] A system for a vehicle (10) configured to tow a trailer (12), comprising: a non-transitory computer-readable medium (46) configured to store suspension parameters; and a computer system on board the vehicle (10) configured, by means of a processor (44): receive image data (218) from one or more image sensors of the vehicle (10); determine a change in vehicle height based on the image data (218); to determine a vehicle load and / or a trailer drawbar load based on the change in vehicle height; determine a road gradient from global positioning data and scale the vehicle load and / or trailer tongue load based on the road gradient; and to generate notification data (236) and / or control data (238) to control the vehicle (10) based on the vehicle load and / or the trailer drawbar load.

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