System and method for identifying and alerting improper vehicle loading

Abstract

A method for identifying and alerting improper vehicle loading is provided. The method includes obtaining a camera image from at least one camera of a vehicle having a payload; performing image processing on the camera image through a processor of the carrying tool; determining a suspension deflection estimated value through a processor; determining, by a processor, a payload estimate and a payload center of gravity estimate using the suspension deflection estimate; if the payload estimate and the barycenter estimate indicate at least one of a payload imbalance or a payload exceeding a threshold, an alert is provided to a user of the vehicle based on the payload estimate and the barycenter estimate. The at least one camera comprises a front-view camera, a right-view camera and a left-view camera.

Description

Technical Field

[0001] This disclosure relates to a vehicle, and more specifically to a method for identifying and warning vehicle users of improper vehicle loading. Background Technology

[0002] Some vehicles are equipped with the capacity to carry payloads and other goods. However, some of these vehicles may be improperly loaded due to overloading or unbalanced payloads. Overloaded vehicles or vehicles with unbalanced payloads (i.e., improper center of gravity) may become unstable, difficult to control, and / or structurally damaged.

[0003] Therefore, while existing vehicles for carrying payloads can achieve their intended purpose, a new and improved vehicle is needed to help users avoid improper loading of payloads. Summary of the Invention

[0004] According to several aspects of this disclosure, a method for identifying and warning of improper vehicle loading is provided. The method includes acquiring camera images from at least one camera of a vehicle carrying a payload; performing image processing on the camera images via a processor of the vehicle; determining a suspension deflection estimate via the processor; determining a payload estimate and a payload center of gravity estimate via the processor using the suspension deflection estimate; and providing a warning to a user of the vehicle based on the payload estimate and the center of gravity estimate if the payload estimate and the center of gravity estimate indicate at least one of the following: payload imbalance or payload exceeding a threshold. The at least one camera includes a forward-facing camera, a right-facing camera, and a left-facing camera.

[0005] According to another aspect of this disclosure, obtaining a camera image includes at least one of the following: using inertial measurement unit (IMU) data to determine whether the vehicle is generally level or using the vehicle speed to determine whether the vehicle is parked, and if the vehicle is generally level and parked, initiating a processor to perform image processing.

[0006] According to another aspect of this disclosure, at least one camera includes a rearview camera and a central high-mounted brake light (CHMSL) camera.

[0007] According to another aspect of this disclosure, obtaining camera images includes obtaining camera images of at least one of the ground below or around the vehicle.

[0008] According to another aspect of this disclosure, determining the suspension deflection estimate includes using the height of at least one camera determined from the image processing steps performed.

[0009] According to another aspect of this disclosure, determining the suspension deflection estimate includes using known vehicle dimensions.

[0010] According to another aspect of this disclosure, determining the payload estimate and the payload center of gravity estimate includes using the vehicle suspension stiffness to calculate the payload estimate and the center of gravity estimate.

[0011] According to another aspect of this disclosure, providing a warning includes calculating a warning to the user using at least one of wheel load, payload weight, or estimated payload center of gravity.

[0012] According to another aspect of this disclosure, the estimated center of gravity of the payload includes both longitudinal and lateral positions.

[0013] According to another aspect of this disclosure, the method also includes calculating a recommended location for repositioning the payload to be provided to the user.

[0014] According to another aspect of this disclosure, the method also includes calculating a recommended payload reduction amount to provide to the user.

[0015] According to several aspects of this disclosure, a system is provided. The system includes one or more cameras for a vehicle having a payload, and the system is configured to acquire camera images below or around the vehicle, the one or more cameras including a front-side camera, a right-side camera, and a left-side camera; one or more human-machine interfaces (HMIs) disposed within the vehicle; and a controller for the vehicle. The controller includes a processor and is coupled to the one or more cameras and the one or more HMIs. The controller is configured to at least facilitate image processing of the camera images; determine a suspension deflection estimate by the processor; determine a payload estimate and a payload center of gravity estimate by the processor using the suspension deflection estimate; and provide a warning to a user of the vehicle based on the payload estimate and the payload center of gravity estimate if the payload estimate and the payload center of gravity estimate indicate at least one of the following: the payload is unbalanced within the vehicle or the payload exceeds a threshold.

[0016] According to another aspect of this disclosure, one or more cameras include a front-view camera, a rear-view camera, a right-view camera, a left-view camera, and a center high-mounted brake light (CHMSL) camera.

[0017] According to another aspect of this disclosure, the processor is configured to facilitate the acquisition of camera images using at least one of inertial measurement unit (IMU) data or vehicle speed, and the processor is configured to facilitate the determination, at least in part, based on the inertial measurement unit (IMU) data or vehicle speed, whether the vehicle is parked and generally horizontal, and if the vehicle is parked and generally horizontal, the processor is configured to facilitate the execution of image processing.

[0018] According to another aspect of this disclosure, determining the suspension deflection estimate includes using the height of at least one camera determined from the image processing steps performed.

[0019] According to another aspect of this disclosure, determining the payload estimate and the payload center of gravity estimate includes using the vehicle suspension stiffness to calculate the payload estimate and the center of gravity estimate.

[0020] According to another aspect of this disclosure, providing a warning includes calculating a warning to the user using at least one of wheel load, payload weight, or estimated payload center of gravity.

[0021] According to another aspect of this disclosure, the estimated center of gravity of the payload includes both longitudinal and lateral positions.

[0022] According to another aspect of this disclosure, providing a warning includes calculating at least one of a recommended location for repositioning the payload to be provided to the user or calculating a recommended payload reduction to be provided to the user.

[0023] According to several aspects of this disclosure, a vehicle is provided. The vehicle includes a fuselage, one or more cameras configured to acquire images of the area below and around the fuselage, and a processor coupled to the one or more cameras. The one or more cameras include a forward-facing camera, a right-side camera, and a left-side camera. The processor is configured to at least facilitate image processing of the camera images; determine a suspension deflection estimate by the processor; determine a payload estimate and a payload center of gravity estimate by the processor using the suspension deflection estimate; and provide a warning to a user of the vehicle based on the payload estimate and the payload center of gravity estimate if the payload estimate and the payload center of gravity estimate indicate at least one of the following: the payload is unbalanced within the vehicle or the payload exceeds a threshold.

[0024] The above-described features and advantages, as well as other features and advantages, of the currently disclosed systems and methods will become apparent when considered in conjunction with the accompanying drawings and the detailed description including the claims and examples. Attached Figure Description

[0025] This disclosure will be more fully understood through detailed description and accompanying drawings, in which:

[0026] Figure 1 A side perspective view of an exemplary vehicle is shown, the vehicle having a payload and a system according to this disclosure for identifying and warning of improper vehicle loading.

[0027] Figure 2 Based on this disclosure Figure 1 A schematic diagram of a system in a vehicle for identifying and warning of improper vehicle loading.

[0028] Figure 3 Based on this disclosure Figure 2 The flowchart shown illustrates the method used by the system to identify and warn of improper vehicle loading. Detailed Implementation

[0029] The following description is merely exemplary in nature and is not intended to limit this disclosure, its application, or its uses. Furthermore, it is not intended to be bound by any express or implied theory presented in the foregoing description, summary of the invention, or the following detailed description. It should be understood that throughout the drawings, corresponding reference numerals denote similar or corresponding parts and features.

[0030] Reference will now be made in detail to several examples of this disclosure illustrated in the accompanying drawings. Wherever possible, the same or similar reference numerals are used in the drawings and description to refer to the same or similar parts or steps. The drawings are simplified and not drawn to scale. The following description is merely exemplary in nature and is not intended to limit the disclosure, its application, or its uses.

[0031] Figure 1 A vehicle 10, a payload 12 contained within the vehicle 10, and a payload analysis system 14 are shown. The vehicle 10 is configured to carry the payload 12 when operated by a user. Generally, the vehicle 10 includes a car, and more preferably a pickup truck. However, the vehicle 10 can be any of a variety of different types of vehicles, such as sedans, vans, trucks, or sport utility vehicles (SUVs), and can 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 some examples, the vehicle 10 may also include motorcycles or other vehicles, such as aircraft, spacecraft, watercraft, etc., and / or one or more other types of mobile platforms (e.g., robots and / or other mobile platforms).

[0032] like Figure 1 As shown, the vehicle 10 includes a fuselage 16 disposed on a chassis 18. The fuselage 16 may include a vehicle floor 20 and may substantially surround other components of the vehicle 10. The vehicle 10 also includes a plurality of wheels 22 and a drive system (not shown) for the wheels 22 and the vehicle 10. Each wheel 22 is rotatably connected to the chassis 18 near a corresponding corner of the fuselage 16 to facilitate movement of the vehicle 10. In one embodiment, the vehicle 10 includes four wheels 22, although this may vary in other embodiments (e.g., for trucks and certain other vehicles).

[0033] like Figure 1As shown, the vehicle 10 includes at least one camera mounted on the fuselage 16. For example, the at least one camera includes a front-view camera 24, a rear-view camera 26, and / or multiple side-view cameras (e.g., a driver-side camera 28, a passenger-side camera 30, etc.). The front-view camera 24 is connected to the front of the vehicle 10 and configured to provide a clear view of the area surrounding the front of the vehicle 10. The rear-view camera 26 is connected to the rear of the fuselage 16 and configured to provide a clear view of the area surrounding the rear of the vehicle 10. The rear-view camera 26 can be multifunctional and can also be configured to assist a user in reversing the vehicle 10. The driver-side camera 28 can be mounted to the driver-side portion of the fuselage 16, for example, mounted on or integrated with the driver-side mirror. The passenger-side camera 30 can be mounted to the passenger-side portion of the fuselage 16, for example, mounted on or integrated with the passenger-side mirror. In some cases, the vehicle 10 may include a center high-mounted stop lamp (CHMSL) camera 32. CHSML camera 32 may include a camera integrated into a centrally mounted high-mounted brake light (or third brake light) and may provide a clear view of the floor of vehicle 10 and / or the area surrounding the rear of vehicle 10. Each camera may be configured with night vision, wide-angle view, wireless networking technology (e.g., built-in Wi-Fi and / or GPS functionality) and / or waterproofing.

[0034] Additionally, in various embodiments, the vehicle 10 may include one or more other sensors 34. For example, the other sensors 34 may include one or more inertial measurement unit (IMU) sensors that provide inertial measurement (IMU) data, detection sensors (e.g., other cameras, lidar, sonar, radar, etc.), and / or one or more other sensors configured to acquire sensor data about one or more other parameters relating to the vehicle 10, its operation, and / or the environment of the vehicle 10, such as the slope of the road and various parameters about the cameras (e.g., the camera's mounting location and orientation, such as the camera's pitch, roll and orientation, pixel size, number of pixels, and / or focal length).

[0035] Continue to refer to Figure 1The vehicle 10 also includes a human-machine interface (HMI) 36 disposed within the vehicle 10 for interaction with the operator of the vehicle 10. The HMI 36 communicates with the system 14. In several aspects, the HMI 36 includes one or more devices capable of interacting with the operator, such as screens disposed within the vehicle 10, such as instrument clusters, infotainment screens, head-up displays (HUDs), interior rearview screens, such as screen-enhanced rearview mirrors, sound transmission systems, speakers, microphones, etc. However, it should be understood that other HMIs 36 are also considered herein. For example, the HMI 36 may be a mobile device, such as a tablet computer, a mobile phone, a cellular phone communicating with an application (e.g., PAA 38), etc., and the HMI 36 may be provided by the operator and temporarily installed or disposed on internal passenger compartment components of the vehicle 10.

[0036] refer to Figure 2 A schematic diagram of a payload analysis system 14 is shown. The payload analysis system 14 is configured to identify and warn of improper vehicle loading. The payload analysis system 14 includes a controller 40 and interface circuitry 42.

[0037] Controller 40 is used to implement method 100 for identifying and warning of improper vehicle loading, as will be described below. In various embodiments, controller 40 (and in some embodiments, payload analysis system 14 itself) is disposed within and / or mounted to the fuselage 16 or chassis (not shown) of vehicle 10. In some embodiments, controller 40 and / or payload analysis system 14 and / or one or more of its components may be located outside fuselage 16, such as on a remote server, in the cloud, or on other devices that remotely perform image processing. It should be understood that controller 40 may otherwise differ from... Figure 1 The embodiments depicted herein. For example, controller 40 may be connected to one or more remote computer systems and / or other control systems, or may otherwise utilize one or more remote computer systems and / or other control systems, for example, as part of one or more of the vehicle 10 apparatus and system described above. Controller 40 includes at least one processor 44 and a non-transitory computer-readable storage device or memory 46.

[0038] Processor 44 performs the computational and control functions of controller 40 and may include any type of processor or multiple processors, a single integrated circuit such as a microprocessor, or any suitable number of integrated circuit devices and / or circuit boards that work together to perform the functions of the processing unit. During operation, it typically performs the processes described herein (e.g., Figure 3In method 100 shown, processor 44 executes one or more programs or application programs 48 contained in memory 46 and controls the general operation of controller 40 and the computer system of controller 40. Processor 44 may be a custom or commercially available processor, central processing unit (CPU), graphics processing unit (GPU), auxiliary processor among multiple processors associated with controller 40, semiconductor-based microprocessor (in the form of a microchip or chipset), macroprocessor, field-programmable gate array (FPGA), application-specific integrated circuit (ASIC), combination thereof, or generally a device for executing instructions.

[0039] Computer-readable storage device or memory 46 may include volatile and non-volatile storage devices such as read-only memory (ROM), random access memory (RAM), dynamic random access memory (DRAM) such as SDRAM, and keep-alive memory (KAM). KAM is persistent or non-volatile memory that can be used to store various operational variables when the processor 44 is powered off. Computer-readable storage device or memory 46 may be implemented using multiple storage devices such as PROM (programmable read-only memory), EPROM (electrical PROM), EEPROM (electrically erasable PROM), flash memory, or other electrical, magnetic, optical, or combined storage devices capable of storing data, some of which represents executable instructions used by the controller 40 to control the payload analysis system 14. In some examples, memory 46 is located on a computer chip and / or co-located on the same computer chip as the processor 44. In the illustrated embodiment, memory 46 stores programs and one or more stored values, including those for identifying and warning of improper loading of the vehicle 10 based on processing of sensor data obtained from cameras 24, 26, 28, and 30 and / or sensors 34.

[0040] Controller 40 also includes one or more applications 48. Applications 48 include software programs configured to perform specific functions or sets of functions. Applications 48 may include one or more computer programs, software components, instruction sets, processes, functions, objects, classes, instances, associated data, or adaptations thereof implemented as part of suitable computer-readable program code. Applications 48 may be stored within memory 46 or in additional or separate memory. Examples of applications 48 include audio or video streaming services, games, browsers, social media, suspension and engine control programs, fuselage control programs, advanced driver assistance system (ADAS) programs, etc. In a particular application 48 of this disclosure, system 14 includes a payload analysis application (PAA) 38.

[0041] For example, PAA 38, when combined with other vehicle control applications, can assist vehicle operators in loading payloads onto vehicle 10 by providing verbal (e.g., via vehicle speakers) or visual instructions (e.g., via HMI 36, etc.) to the operator. Verbal and / or visual assistance can be configured by the operator in HMI 36 or an onboard application (e.g., OnStar). More specifically, PAA 38 includes multiple subroutines or instructions stored in the memory 46 of controller 40 and executed by processor 44 while receiving data from sensors 34, such as vehicle cameras and / or IMUs, via interface circuitry 42. PAA 38 also includes multiple subroutines or instructions that enable data transfer from controller 40 to HMI 36.

[0042] The controller 40 may also consist of multiple controllers electrically connected to each other. The controller 40 may also include additional elements and / or modules, such as a real-time clock (RTC) module for measuring the elapsed time. In one exemplary embodiment, the controller 40 is powered by being connected to a battery or other power source.

[0043] The controller 40 communicates electrically with the interface circuit 42. In an exemplary embodiment, electrical communication is established using, for example, general purpose input / output (GPIO) pins, internal integrated circuit (I2C) bus, serial peripheral interface (SPI) bus, parallel communication bus, direct hardwired connection, fiber optic, infrared, and wireless bus technologies. It should be understood that various additional communication protocols used for communicating with the controller 40 are within the scope of this disclosure.

[0044] Interface circuitry 42 enables controller 40 to interact with cameras (e.g., front-view camera 24, rear-view camera 26, side-view cameras 28, 30 and / or CHSML camera 32) and / or HMI 36. Interface circuitry 42 allows communication, for example, from system drives and / or another computer system to the computer system of controller 40, and can be implemented using any suitable methods and means. In one embodiment, interface circuitry 42 acquires various data from sensor 34 and / or cameras, as well as other possible data sources. Interface circuitry 42 may include one or more network interfaces for communicating with other systems or components. Interface circuitry 42 may also include one or more network interfaces for communicating with technicians, and / or one or more storage interfaces for connecting to storage devices.

[0045] It should be understood that although this exemplary embodiment has been described in the context of a full-featured computer system, those skilled in the art will recognize that the mechanisms of this disclosure can be distributed as a program product having one or more types of non-transitory computer-readable signal-bearing media for storing the program and its instructions and for executing its distribution, such as a non-transitory computer-readable medium carrying the program and containing computer instructions stored therein, for causing a computer processor (e.g., processor 44) to execute and run the program. Such program products can take many forms, and this disclosure applies equally regardless of the specific type of computer-readable signal-bearing medium used for executing the distribution. Examples of signal-bearing media include recordable media such as floppy disks, hard disk drives, memory cards, and optical disks, and transmission media such as digital and analog communication links. It should be understood that cloud-based storage and / or other technologies may also be utilized in some embodiments. It should also be understood that the computer system of controller 40 may differ in other respects. Figure 2 The embodiments depicted, such as the computer system of controller 40, may be connected to or may otherwise utilize one or more remote computer systems and / or other control systems.

[0046] refer to Figure 3 The diagram illustrates a flowchart of method 100 according to PAA 38 of this disclosure. At block 102, the method begins when one or more specific conditions occur. Specific conditions may include manual initialization by an operator via HMI 36 or operation of a physical button located within the vehicle 10. In another example, the conditions may be met automatically by sensors 34 and / or cameras 24, 26, 28, 30, and 32.

[0047] Block 102 depicts acquiring camera images from at least one camera 24, 26, 28, 30, and 32 of a vehicle 10 having a payload 12. System 14 and interface circuitry 42 receive camera images from at least one camera 24, 26, 28, 30, and 32. This at least one camera includes a front-view camera 24, a rear-view camera 26, a right-view (or passenger-side) camera 30, and a left-view (or driver-side) camera 28. When in use, interface circuitry 42 can receive camera images from CHSML camera 32. Preferably, system 14 and interface circuitry 42 receive at least camera images from the front-view camera 24, the right-view camera 30, and the left-view camera 28 to estimate the vehicle's pitch and roll angles, thereby calculating the four suspension deflections. However, acquiring camera images from all cameras 24, 26, 28, 30, and 32 improves accuracy. In some cases, acquiring camera images may include using vehicle speed information to determine that vehicle 10 is stationary and generally horizontal (i.e., vehicle 10 is parked on a generally flat and level surface (within ±5°)). This speed information may be received from HMI 36 or vehicle 10 and / or, for example, an IMU sensor configured to measure the specific force, angular rate, and / or orientation of vehicle 10 (i.e., whether vehicle 10 is generally horizontal within ±5°). If vehicle 10 is on an uneven surface, subsequent payload estimates and payload center of gravity estimates may be inaccurate. When vehicle 10 is determined to be stationary and generally horizontal, system 14 and / or controller 40 may enable the steps of acquiring camera images in method 100 and block 102.

[0048] Box 104 depicts image processing performed on camera images via a controller 40 and processor 44 of the vehicle 10. Image processing may include image enhancement, image restoration, image compression, image segmentation, and / or object detection and classification of the camera images. Image processing may also include filtering, edge detection, and / or morphological processing of the camera images. Additionally, image processing may include determining the characteristics of each camera (e.g., the forward-facing camera H). f Rearview camera H r Right-view camera H sr Left-view camera H sl CHMSL camera H bThe height of each camera (e.g., [the image]). Determining the height of each camera may include, for example, using a depth-sensing camera that provides distance information for each pixel to calculate the ratio of the pixels to known measurements, thereby allowing accurate height estimation, and / or segmentation to estimate height based on the segmented portions. Furthermore, in some cases, performing image processing may include using machine learning and / or artificial intelligence (AI), such as training a convolutional neural network (CNN) or a four-stage developing network, to identify and estimate height based on the acquired camera images. It should be understood that processing camera images may include using other suitable techniques and / or algorithms.

[0049] For example, processor 44 can determine the height of each camera Z to obtain an estimate of the vehicle's vertical motion using the longitudinal position X, the known curb weight height Z0, and the estimated height Z from the camera images, and can use ΔZ to determine the pitch angle estimate θ. vc And roll angle estimation φ vc The pitch angle estimate can be determined using the following formula, where ΔZ is the estimated vertical motion of the vehicle, x is the horizontal distance (i.e., 10 units in front of the vehicle), and θ is the horizontal distance. vc It is the pitch angle, and ΔZ v It is an additional vertical displacement.

[0050] ΔZ=x tanθ vc +ΔZ v

[0051] The roll angle can be determined using the following formula, where φ vc It is the roll angle, ΔH s; The height difference ΔH is the height difference on the left side of the vehicle 10. sr It is the height difference on the right side of vehicle 10, D y It is the distance between two points that measure the height difference.

[0052]

[0053] Box 106 depicts the determination of suspension deflection estimates via processor 44. Suspension deflection estimation is an important aspect of vehicle dynamics and safety, involving measuring the degree of compression or extension of the suspension system under various loads and conditions (e.g., payload 12). In one example, processor 44 can use known vehicle dimensions and information received from self-processed camera images, such as camera height (H). f H r H sr H sl H bThe specific height of a portion of the vehicle 10 (e.g., front right, front left, rear right, rear left) or other parts thereof can be used to estimate suspension deflections (one or more) and forces. For example, the load estimate ΔF (or force from the effective load) for each wheel 22 of the vehicle 10 can be obtained by using the known vehicle suspension stiffness (K... fL K fR K rL and K rL and the estimated vehicle pitch angle θ vc Roll angle φ vc and vertical motion ΔZ v The following equation is used to determine the estimated left anterior load ΔF. fL Right anterior load estimate ΔF fR Left rear load estimate ΔF rL and right rear load estimate ΔF rR (or "wheel load"), where a is the distance between the front camera 24 and the position where the front wheel 22 of the vehicle 10 contacts the ground, and where L v It is the distance between wheels 22.

[0054]

[0055] Box 108 illustrates how the processor determines the payload estimate and payload center of gravity estimate by using suspension deflection estimates and load estimates for each wheel or section of the vehicle 10. For example, the processor 44 can determine the payload estimate F using the following formula. Load .

[0056] F Load =ΔF fL +ΔF fR +ΔF rL +ΔF rR

[0057] Additionally, processor 44 can use the following formula to determine the payload centroid (CG) estimate, where L x It is the longitudinal position of the center of gravity of the effective load and L y It is the lateral position of the center of gravity of the effective load.

[0058]

[0059] Box 110 depicts the load estimate F Load And center of gravity valuation L x L y Provide a warning to the user of vehicle 10 if the load estimate F Load And center of gravity valuation L x L yIf the payload 12 is found to be unbalanced or exceeds at least one of the thresholds, the vehicle 10 may be identified as a parked vehicle. For example, when the processor 44 and / or the controller 40 determines that the payload 12 is unbalanced and / or exceeds a threshold (e.g., a weight threshold, a balance threshold), the controller 40 and the interface circuitry 42 may send a warning to the HMI 36 and indicate to the user of the vehicle 10 (e.g., via text, verbally, etc.) that the payload 12 is unbalanced and / or exceeds the threshold.

[0060] Option box 112 depicts the calculation of a recommended location for repositioning the payload 12 to provide to the user of the vehicle 10. In some cases, the controller 40 may instruct the user of the vehicle 10 via the HMI 36 on a recommended location (e.g., lateral, longitudinal) for repositioning the payload 12 to safely balance the payload 12.

[0061] Option box 114 describes the calculation of a recommended payload reduction amount to provide to the user of vehicle 10. In some cases, controller 40 may instruct the user of vehicle 10 via HMI 36 to reduce the payload weight to a recommended amount to a predetermined safe weight.

[0062] The methods, systems, and vehicles disclosed herein include numerous advantages. These methods, systems, and vehicles are configured to identify and warn vehicle users of overloaded vehicles or vehicles with unbalanced loads (i.e., improper center of gravity). Operating overloaded and / or unbalanced vehicles can lead to vehicle instability, difficulty in vehicle control, and / or structural damage to the vehicle.

[0063] This description is merely illustrative in nature and is in no way intended to limit this disclosure, its application, or its use. The broad teachings of this disclosure can be implemented in many forms. Therefore, while this disclosure includes specific examples, its true scope should not be so limited, as other modifications will become apparent upon examination of the drawings, description, and appended claims.

Claims

1. A method for identifying and warning of improper vehicle loading, comprising: Acquire camera images from at least one camera of a vehicle with a payload, wherein the at least one camera includes a front-view camera, a right-view camera, and a left-view camera; The camera images are processed by the processor of the vehicle. The processor determines the estimated suspension deflection. The processor uses the suspension deflection estimate to determine the effective load estimate and the effective load center of gravity estimate; as well as If the payload estimate and center of gravity estimate indicate at least one of the following: the payload is unbalanced or the payload exceeds a threshold, a warning is issued to the user of the vehicle based on the payload estimate and the center of gravity estimate.

2. The method of claim 1, wherein obtaining a camera image comprises at least one of: using inertial measurement unit (IMU) data to determine whether the vehicle is generally level or using the vehicle speed to determine whether the vehicle is parked, and, if the vehicle is generally level and parked, initiating the processor to perform image processing.

3. The method according to claim 1, wherein the at least one camera includes a rearview camera and a central high-mounted brake light (CHMSL) camera.

4. The method of claim 1, wherein obtaining camera images includes obtaining camera images of at least one of the ground below or around the vehicle.

5. The method of claim 1, wherein determining the suspension deflection estimate includes using at least one camera height determined from the image processing step performed.

6. The method of claim 1, wherein determining the suspension deflection estimate includes using known vehicle dimensions.

7. The method of claim 1, wherein determining the payload estimate and the payload center of gravity estimate comprises using vehicle suspension stiffness to calculate the payload estimate and the center of gravity estimate.

8. The method of claim 1, wherein providing a warning comprises calculating a warning to the user using at least one of wheel load, payload weight, or estimated payload center of gravity.

9. The method of claim 8, wherein the estimated payload centroid includes a longitudinal position and a lateral position.

10. The method according to claim 1, further comprising: Calculate a recommended location for repositioning the payload to provide to the user.

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