The present disclosure relates to a vehicle interface system for an autonomous vehicle, and more particularly, to an interface system and remote trailer vehicle maneuver system.
Operating a vehicle with a trailer in tow is very challenging for many drivers. This is particularly true for drivers that are unskilled at backing up vehicles with attached trailers, which may include those that drive with a trailer on an infrequent basis (e.g., have rented a trailer, use a personal trailer on an infrequent basis, etc.). Trailer backup assist systems for vehicles may include an onboard user interface that allows the user to steer a trailer towed by the vehicle through an automated steering controller that provides the steering motion that moves the trailer along a user-defined path curvature.
A system for configuring a trailer model for a trailer maneuvering is disclosed in U.S. Pat. No. 9,352,777, assigned to Ford Global Technologies, LLC (hereafter “the '777 Publication”). The system described in the '777 Publication includes a mobile device used to capture 3D trailer data to create a trailer profile to communicate to the trailer maneuvering system. The mobile device may also be used to capture dimensional data, such as the distance between a first reference point and a second reference point on the vehicle and trailer. A request may also be provided by the mobile device to take a photo of the trailer itself. It may be advantageous to further provide Autonomous Vehicle (AV) control integration and other intuitive features that utilize sensing capability of the mobile device to assess the environment, measure the boundaries of a parking space, and provide a user interface for input of a target position and orientation of the vehicle and trailer.
It is with respect to these and other considerations that the disclosure made herein is presented.
The detailed description is set forth with reference to the accompanying drawings. The use of the same reference numerals may indicate similar or identical items. Various embodiments may utilize elements and/or components other than those illustrated in the drawings, and some elements and/or components may not be present in various embodiments. Elements and/or components in the figures are not necessarily drawn to scale. Throughout this disclosure, depending on the context, singular and plural terminology may be used interchangeably.
The systems and methods disclosed herein are configured to improve a Remote Trailer Maneuvering (RTM) system through the use of a mobile device application or “app”. The RTM app prompts the user to take a photo of the target location for positioning the trailer. The mobile device processes the photo by identifying and characterizing environmental information for possible obstacles, such as walls, surrounding objects, etc. The RTM app may process the photo with steps that include overlaying overlay a representation of the trailer at a desired position using an Augmented Reality (AR) controller. When a boat is detected as the trailer payload, and the RTM system further identifies a boat ramp, the system calculates a travel distance to drive the trailer into the water for unloading the boat.
The RTM system may determine the distance using various methods, including determining a salinity level of the water, measuring relative distances between the vehicle, the trailer/trailer contents, the water, obstacles in the vicinity, and using other measurements. The RTM system may identify any obstructions that are predicted to prevent completion of the operation that results in the trailer ending at the target position, and output information and warnings to the user, prompt for information and user control feedback, and provide other information useful for completion of the trailer maneuvering operation.
Once the photo is processed, the RTM system on the mobile device sends control instructions to the RTM controller onboard the vehicle for validation and execution. The vehicle may send a responsive message to the mobile device indicating that the RTM system is ready to proceed with the maneuvering function.
Embodiments described in the present disclosure may allow a user to initiate an automated trailering maneuver operation and indicate the desired destination for the trailer without continuously providing tedious control inputs.
These and other advantages of the present disclosure are provided in greater detail herein.
The disclosure will be described more fully hereinafter with reference to the accompanying drawings, in which exemplary embodiments of the disclosure are shown, and not intended to be limiting.
The automotive computer 145 may be or include an electronic vehicle controller, having one or more processor(s) 150 and memory 155. The automotive computer 145 may, in some example embodiments, be disposed in communication with the mobile device 120, and one or more server(s) 170. The server(s) 170 may be part of a cloud-based computing infrastructure, and may be associated with and/or include a Telematics Service Delivery Network (SDN) that provides digital data services to the vehicle 105 and other vehicles (not shown in
Although illustrated as a car, the vehicle 105 may take the form of another passenger or commercial automobile such as, for example, a car, a truck, a sport utility, a crossover vehicle, a van, a minivan, a taxi, a bus, etc., and may be configured to include various types of automotive drive systems. Exemplary drive systems can include various types of internal combustion engine (ICE) powertrains having a gasoline, diesel, or natural gas-powered combustion engine with conventional drive components such as, a transmission, a drive shaft, a differential, etc. In another configuration, the vehicle 105 may be configured as an electric vehicle (EV). More particularly, the vehicle 105 may include a battery EV (BEV) drive system, or be configured as a hybrid EV (HEV) having an independent onboard power plant, a plug-in HEV (PHEV) that includes a HEV powertrain connectable to an external power source, and including a parallel or series hybrid powertrain having a combustion engine power plant and one or more EV drive systems. HEVs can include battery and/or super capacitor banks for power storage, flywheel power storage systems, or other power generation and storage infrastructure. The vehicle 105 may be further configured as a fuel cell vehicle (FCV) that converts liquid or solid fuel to usable power using a fuel cell, (e.g., a hydrogen fuel cell vehicle (HFCV) powertrain, etc.) and/or any combination of these drive systems and components.
Further, the vehicle 105 may be a manually driven vehicle, and/or be configured to operate in a fully autonomous (e.g., driverless) mode (e.g., level-5 autonomy) or in one or more partial autonomy modes. Examples of partial autonomy modes are widely understood in the art as autonomy Levels 1 through 5. An autonomous vehicle (AV) having Level 1 autonomy may generally include a single automated driver assistance feature, such as steering or acceleration assistance. Adaptive cruise control is one such example of a Level-1 autonomous system that includes aspects of both acceleration and steering. Level-2 autonomy in vehicles may provide partial automation of steering and acceleration functionality, where the automated system(s) are supervised by a human driver that performs non-automated operations such as braking and other controls. Level-3 autonomy in a vehicle can generally provide conditional automation and control of driving features. For example, Level-3 vehicle autonomy typically includes “environmental detection” capabilities, where the vehicle can make informed decisions independently from a present driver, such as accelerating past a slow-moving vehicle, while the present driver remains ready to retake control of the vehicle if the system is unable to execute the task. Level 4 autonomy includes vehicles having high levels of autonomy that can operate independently from a human driver, but still include human controls for override operation. Level-4 automation may also enable a self-driving mode to intervene responsive to a predefined conditional trigger, such as a road hazard or a system failure. Level 5 autonomy is associated with autonomous vehicle systems that require no human input for operation, and generally do not include human operational driving controls.
According to embodiments of the present disclosure, the RTM system 107 may be configured to operate with a vehicle having a Level-2 or Level-3 autonomous vehicle controller. An example AV controller 235 is described in greater detail with respect to
The mobile device 120 generally includes a memory 123 for storing program instructions associated with an application 135 that, when executed by a mobile device processor 121, performs aspects of the disclosed embodiments. The application (or “app”) 135 may be part of the RTM system 107, or may provide information to the RTM system 107 and/or receive information from the RTM system 107.
In some aspects, the mobile device 120 may communicate with the vehicle 105 through the one or more wireless channel(s) 130, which may be encrypted and established between the mobile device 120 and a Telematics Control Unit (TCU) 160. The mobile device 120 may communicate with the TCU 160 using a wireless transmitter associated with the TCU 160 on the vehicle 105. The transmitter may communicate with the mobile device 120 using a wireless communication network such as, for example, the one or more network(s) 125. The wireless channel(s) 130 are depicted in
The network(s) 125 illustrate an example of an example communication infrastructure in which the connected devices discussed in various embodiments of this disclosure may communicate. The network(s) 125 may be and/or include the Internet, a private network, public network or other configuration that operates using any one or more known communication protocols such as, for example, transmission control protocol/Internet protocol (TCP/IP), Bluetooth®, Wi-Fi based on the Institute of Electrical and Electronics Engineers (IEEE) standard 802.11, Ultra-Wide Band (UWB), and cellular technologies such as Time Division Multiple Access (TDMA), Code Division Multiple Access (CDMA), High Speed Packet Access (HSPDA), Long-Term Evolution (LTE), Global System for Mobile Communications (GSM), and Fifth Generation (5G), to name a few examples.
The automotive computer 145 may be installed in an engine compartment of the vehicle 105 (or elsewhere in the vehicle 105) and operate as a functional part of the RTM system 107, in accordance with the disclosure. The automotive computer 145 may include one or more processor(s) 150 and a computer-readable memory 155.
The one or more processor(s) 150 may be disposed in communication with one or more memory devices disposed in communication with the respective computing systems (e.g., the memory 155 and/or one or more external databases not shown in
The VCU 165 may coordinate the data between vehicle 105 systems, connected servers (e.g., the server(s) 170), and other vehicles (not shown in
The TCU 160 can be configured to provide vehicle connectivity to wireless computing systems onboard and offboard the vehicle 105, and may include a Navigation (NAV) receiver 188 for receiving and processing a GPS signal from the GPS 175, a Bluetooth® Low-Energy Module (BLEM) 195, a Wi-Fi transceiver, an Ultra-Wide Band (UWB) transceiver, and/or other wireless transceivers (not shown in
The BLEM 195 may establish wireless communication using Bluetooth® and Bluetooth Low-Energy® communication protocols by broadcasting and/or listening for broadcasts of small advertising packets, and establishing connections with responsive devices that are configured according to embodiments described herein. For example, the BLEM 195 may include Generic Attribute Profile (GATT) device connectivity for client devices that respond to or initiate GATT commands and requests, and connect directly with the mobile device 120.
The CAN bus 180 may be configured as a multi-master serial bus standard for connecting two or more of the ECUs 117 as nodes using a message-based protocol that can be configured and/or programmed to allow the ECUs 117 to communicate with each other. The CAN bus 180 may be or include a high speed CAN (which may have bit speeds up to 1 Mb/s on CAN, 5 Mb/s on CAN Flexible Data Rate (CAN FD)), and can include a low-speed or fault tolerant CAN (up to 125 Kbps), which may, in some configurations, use a linear bus configuration. In some aspects, the ECUs 117 may communicate with a host computer (e.g., the automotive computer 145, the RTM system 107, and/or the server(s) 170, etc.), and may also communicate with one another without the necessity of a host computer. The CAN bus 180 may connect the ECUs 117 with the automotive computer 145 such that the automotive computer 145 may retrieve information from, send information to, and otherwise interact with the ECUs 117 to perform steps described according to embodiments of the present disclosure. The CAN bus 180 may connect CAN bus nodes (e.g., the ECUs 117) to each other through a two-wire bus, which may be a twisted pair having a nominal characteristic impedance. The CAN bus 180 may also be accomplished using other communication protocol solutions, such as Media Oriented Systems Transport (MOST) or Ethernet. In other aspects, the CAN bus 180 may be a wireless intra-vehicle CAN bus.
The VCU 165 may control various loads directly via the CAN bus 180 communication or implement such control in conjunction with the BCM 193. The ECUs 117 described with respect to the VCU 165 are provided for exemplary purposes only, and are not intended to be limiting or exclusive. Control and/or communication with other control modules not shown in
In an example embodiment, the ECUs 117 may control aspects of vehicle operation and communication using inputs from human drivers, inputs from an autonomous vehicle controller, the RTM system 107, and/or via wireless signal inputs received via the wireless channel(s) 133 from other connected devices such as the mobile device 120, among others. The ECUs 117, when configured as nodes in the CAN bus 180, may each include a central processing unit (CPU), a CAN controller, and/or a transceiver (not shown in
The BCM 193 generally includes integration of sensors, vehicle performance indicators, and variable reactors associated with vehicle systems, and may include processor-based power distribution circuitry that can control functions associated with the vehicle body such as lights, windows, security, door locks and access control, and various comfort controls. The BCM 193 may also operate as a gateway for bus and network interfaces to interact with remote ECUs (not shown in
The BCM 193 may coordinate any one or more functions from a wide range of vehicle functionality, including energy management systems, alarms, vehicle immobilizers, driver and rider access authorization systems, Phone-as-a-Key (PaaK) systems, driver assistance systems, Autonomous Vehicle (AV) control systems, power windows, doors, actuators, and other functionality, etc. The BCM 193 may be configured for vehicle energy management, exterior lighting control, wiper functionality, power window and door functionality, heating ventilation and air conditioning systems, and driver integration systems. In other aspects, the BCM 193 may control auxiliary equipment functionality, and/or be responsible for integration of such functionality. In one aspect, a vehicle having a trailer control system may integrate the system using, at least in part, the BCM 193.
The computing system architecture of the automotive computer 145, VCU 165, and/or the RTM system 107 may omit certain computing modules. It should be readily understood that the computing environment depicted in
The user interface device 215 may be configured or programmed to present information to a user (e.g., the user 140 depicted with respect to
In some aspects of the present disclosure, the user interface device 215 may be and/or include the mobile device 120 as discussed with respect to
The NAV system 188 may be configured and/or programmed to determine a position of the vehicle 105, and the trailer 110. The NAV system 188 may include a Global Positioning System (GPS) receiver configured or programmed to triangulate the position of the vehicle 105 relative to satellites or terrestrial based transmitter towers associated with the GPS system 175 (as shown in
The TCU 160 generally includes wireless transmission and communication hardware that may be disposed in communication with one or more transceivers associated with telecommunications towers and other wireless telecommunications infrastructure (not shown in
In other aspects, the autonomous driving sensors 230 may utilize sensor data from the user interface device (configured as a mobile device or smartphone), in conjunction with the trailer and trailer payload dimension data from the trailer profile information, to determine dimension information associated with obstacles identified in the operating environment. Examples of such identification are described in greater detail with respect to the following figures.
The autonomous driving sensors 230 may include any number of devices configured or programmed to generate signals that help navigate the vehicle 105 while the vehicle 105 is operating in the autonomous (e.g., driverless) mode. Examples of autonomous driving sensors 230 may include a Radio Detection and Ranging (RADAR or “radar”) sensor configured for detection and localization of objects using radio waves, a Light Detecting and Ranging (LiDAR or “lidar”) sensor, a vision sensor system having trajectory, obstacle detection, object classification, augmented reality, and/or other capabilities, and/or the like. The autonomous driving sensors 230 may provide instrumentation data to the vehicle 105 to “see” the roadway and the vehicle surroundings, and/or negotiate various obstacles while the vehicle is operating in the autonomous mode as it performs the trailer maneuver assist operation.
The autonomous vehicle controller 235 may be configured or programmed to control one or more vehicle subsystems while the vehicle is operating in the autonomous mode. Examples of subsystems that may be controlled by the autonomous vehicle controller 235 may include one or more systems for controlling braking, ignition, steering, acceleration, transmission control, and/or other control mechanisms. The autonomous vehicle controller 235 may control the subsystems based, at least in part, on signals generated by the autonomous driving sensors 230, and the RTM system 107.
Conventional Trailer Backup Assist (PTBA) systems, such as the system described in the U.S. Pat. No. 9,352,777, may provide intuitive interfaces that allow a user to steer a trailer by providing an automated steering controller. In such systems, the PTBA system may provide the correct steering motion that moves the trailer along a desired path curvature, which may be indicated by a user of the device. Without the PTBA controller, it may be counter-intuitive for a customer to manually steer the vehicle in order to provide the correct inputs at the steering wheel to direct the trailer along a desired path curvature. In some aspects, the RTM system 107 may improve upon the current system by providing a way for a user 140 to specify the target location to which the vehicle and trailer is to be maneuvered. The user 140 may provide information to The RTM system 107, with which the system identifies the target parking spot for the trailer 110 (e.g., the target position 109), and forms a digital model indicative of a general layout of the trailer parking environment 100 (as depicted in
Once the user 140 has launched the app 135, and authenticated into an account that securely identifies the mobile device 120 and/or the app 135 with the vehicle 105 (not shown in
The app 135 may further include coaching instructions using one or more follow-up dialogue boxes, such as a follow-up instruction dialogue box 315. Accordingly, the user 140 may position the mobile device 120 based on the instructions 310, 315, and snap the image 305 using an image trigger 320 when the follow-up prompt (not shown in
The app 135 may determine the target position 109 using various dimensional orientation techniques that place a digital representation of the vehicle 105 and the trailer 110 in 3-dimensional (3D) space, such that the RTM system 107 can identify an appropriate path for the vehicle 105 and trailer 110 to take, and determine control instructions that avoid potential obstacles (e.g., the wooden pier 325). In order to avoid an obstacle, The RTM system 107 must characterize the visual representation of the pier from the dimensional orientation data as an obstacle using image recognition, identify the recognized object from the image 305 as an obstacle, and define relative boundaries of the obstacle(s), the vehicle 105, the trailer 110, and the target position 109 with respect to the vehicle and trailer dimensions, and plot one or more viable paths (not shown in
In one example embodiment, The RTM system 107 may determine reference points to determine vehicle, trailer/trailer payload, and obstacle boundaries. For example, the mobile device 120 may determine a dimension B, which represents a relative dimension between an edge of the vehicle 105 and an edge of the trailer 110. The RTM system 107 may determine an environmental dimension indicative of a distance between where the trailer currently is (a first trailer location) and a target position 109 (e.g., where the user 140 intends for the RTM system 107 to position the trailer 110) based, at least in part, on the trailer dimensions, the vehicle dimensions, obstacle dimensions, and other known information. For example, if the vehicle dimensions and the trailer dimensions are known values, the RTM system 107 may utilize the autonomous driving sensors 230 (e.g., a LiDAR sensor 505) to evaluate relative distances between the sensor(s) 505 (and by extension, vehicle portions), and the object(s) at issue. In the present example, the wooden pier 325 includes a boundary 510 representing the right side physical edge of the pier, plus a buffer, from the perspective of the photo, which may be the extent to which the vehicle 105 may operate without damage to itself or the wooden pier 325. The LiDAR sensor 505 may determine a distance (A) between the vehicle 105 and the boundary edge 510 of the pier. The RTM system 107 may also be aware of a relative dimension of an edge boundary 520 of the trailer 110, due to the known dimension 515 of the vehicle 105, the trailer 110, and the difference (B) between the two dimensions. In one aspect, The RTM system 107 may determine a distance between the outermost trailer edge 520 and the boundary 510 of the wooden pier (obstacle) 325 (the dimension represented as (C)) by the merits of known dimensions and the difference thereof. For example, the dimension (A) may be observed from sensor data (not shown in
The RTM system 107 may warn the user if there is an environmental condition such as obstruction(s) in the trailer maneuver path 640, or adjacent to the trailer maneuver path 640, that cannot be avoided to complete the maneuver. In another aspect, the RTM system 107 may provide a warning if the target position 109 is in a space that is tighter than the vehicle 105 and trailer 110 needs to fit. The RTM system 107 may then provide context appropriate feedback, such as generating and outputting a request that the user 140 either remove obstructions from the trailer maneuver path 640, or select a different location target position. The RTM system 107 may ask the user 140 to confirm when this condition has been corrected, by capturing another image of the location with the new target position 109 after correcting the condition. After the user provides the application 135 with image data, the RTM system 107 onboard the vehicle 105 may validate the image to determine that the image includes sufficient information to plot a trailer maneuver path. In one example embodiment, the RTM system 107 may send information 132 to the remote device 120 that includes, for example, a desired vehicle and trailer direction when the feature has completed, an estimated distance from a current location to the target location, graphic information indicative of obstacles and their location (e.g., dimension and location characteristics associated with potential obstacles such as trees, bushes, etc.), a location of the mobile device 120 relative to the vehicle 105, a location of the vehicle 105 and the trailer 110, and other possible information.
The RTM system 107 may identify obstacles (e.g., the wooden pier 325 and the second obstacle 625), identify borders associated with the obstacles, and navigate the trailer 110 to avoid the obstacles. For example, a second obstacle 625 may not be in the direct path of the trailer maneuver path 640, but be close enough to be identified and avoided while navigating the trailer 110. In another aspect, the sensor data 630 may continually look for and identify obstacles and relative distances between the trailer 110, the water 610, the water's edge 635, and other visually obtainable information needed to complete the trailer maneuver operation.
Responsive to generating the trailer maneuver path 640, based on the image 305 and possibly other information such as a trailer profile and a marine vehicle profile received from the server(s) 170 (as depicted in
According to an example embodiment, the application 135 may request for user input for approval to commence vehicle motion. In other aspects, the RTM system 107 may require a persistent user interaction to provide a vehicle motion command that maintains vehicle motion. The motion command may take a variety of forms, which can include, for example, a request for user input that traces a complex geometric shape on the mobile device 120 using the touchscreen, holding down one or more buttons, and/or providing an input sequence to mobile device 120 using some combination of touch inputs and button inputs, etc.
Referring first to
At step 715, the method may further include determining a target location for parking the trailer via an image of the trailer parking environment. This step may include determining a trailer dimension, determining an environmental dimension indicative of a distance between the trailer first location and the target location, determining a boundary using the image of the trailer parking environment, and positioning the target location at a distal end of the boundary, where the target location is represented as a rectangular shape having a distal target edge proximate to the distal end of the boundary.
In some aspects, the method may further include steps comprising receiving trailer/marine vehicle dimensional data corresponding to a kinematic model of the trailer/marine vehicle, identifying a first reference point and a second reference point in the image of the trailer parking environment to calculate a dimension of the kinematic model, determining, using the first reference point and the second reference point, a trailer dimension, and updating a trailer profile with the trailer/payload dimension.
At step 720, the method may further include generating a trailer maneuver path, based on the image, from a first trailer location to the target location. This step may include identifying, based on the image, an obstacle along the trailer maneuver path, generating a modified trailer maneuver path by modifying the trailer maneuver path to avoid the obstacle, determining that an obstruction intervenes the first trailer location and the target location, determining that the trailer maneuver path to the target location does not have an alternative route, and generating a message on the mobile device indicating an instruction to remove the obstacle.
Identifying the obstacle in the path may include steps such as receiving a trailer profile comprising a trailer dimension determining a dimension of the obstacle based on the trailer dimension, determining a first distance from the obstacle to the trailer, determining a second distance from the obstacle to the vehicle, and generating the modified trailer maneuver path based on the first distance and the second distance.
Generating the trailer maneuver path may alternatively include allowing the user to determine whether the obstacle is a true hazard or something that may be ignored. Accordingly, the method may include identifying, based on the image, an obstacle along the trailer maneuver path to the target location, then displaying a user-selectable option to ignore the obstacle. The method may further include receiving a user selection of the user-selectable option to ignore the obstacle, and generating the modified trailer maneuver path to the target location based on the user-selectable option.
In another example embodiment, the generating step can include identifying, based on the image, an obstacle along the trailer maneuver path to the target location, and displaying a user action message via the mobile device instructing a user action to remove the obstacle. Once the user has removed the obstacle, the user may provide an indication using the mobile device that the obstacle is removed and the procedure may be continued.
At step 725, the method may further include the step of sending a configuration message to the vehicle, the configuration message comprising instructions for causing an autonomous vehicle controller to maneuver the trailer to the target position based on the trailer maneuver path. Sending the configuration message to the vehicle, can include sending an instruction set for causing the autonomous vehicle controller to maneuver the trailer to the target position based on the modified trailer maneuver path. In some aspects, changing the trailer maneuver path can be performed using information that includes, for example, the dimension of the obstacle, and/or the first distance, and/or the second distance.
In the above disclosure, reference has been made to the accompanying drawings, which form a part hereof, which illustrate specific implementations in which the present disclosure may be practiced. It is understood that other implementations may be utilized, and structural changes may be made without departing from the scope of the present disclosure. References in the specification to “one embodiment,” “an embodiment,” “an example embodiment,” etc., indicate that the embodiment described may include a particular feature, structure, or characteristic, but every embodiment may not necessarily include the particular feature, structure, or characteristic. Moreover, such phrases are not necessarily referring to the same embodiment. Further, when a feature, structure, or characteristic is described in connection with an embodiment, one skilled in the art will recognize such feature, structure, or characteristic in connection with other embodiments whether or not explicitly described.
It should also be understood that the word “example” as used herein is intended to be non-exclusionary and non-limiting in nature. More particularly, the word “exemplary” as used herein indicates one among several examples, and it should be understood that no undue emphasis or preference is being directed to the particular example being described.
A computer-readable medium (also referred to as a processor-readable medium) includes any non-transitory (e.g., tangible) medium that participates in providing data (e.g., instructions) that may be read by a computer (e.g., by a processor of a computer). Such a medium may take many forms, including, but not limited to, non-volatile media and volatile media. Computing devices may include computer-executable instructions, where the instructions may be executable by one or more computing devices such as those listed above and stored on a computer-readable medium.
With regard to the processes, systems, methods, heuristics, etc. described herein, it should be understood that, although the steps of such processes, etc. have been described as occurring according to a certain ordered sequence, such processes could be practiced with the described steps performed in an order other than the order described herein. It further should be understood that certain steps could be performed simultaneously, that other steps could be added, or that certain steps described herein could be omitted. In other words, the descriptions of processes herein are provided for the purpose of illustrating various embodiments and should in no way be construed so as to limit the claims.
Accordingly, it is to be understood that the above description is intended to be illustrative and not restrictive. Many embodiments and applications other than the examples provided would be apparent upon reading the above description. The scope should be determined, not with reference to the above description, but should instead be determined with reference to the appended claims, along with the full scope of equivalents to which such claims are entitled. It is anticipated and intended that future developments will occur in the technologies discussed herein, and that the disclosed systems and methods will be incorporated into such future embodiments. In sum, it should be understood that the application is capable of modification and variation.
All terms used in the claims are intended to be given their ordinary meanings as understood by those knowledgeable in the technologies described herein unless an explicit indication to the contrary is made herein. In particular, use of the singular articles such as “a,” “the,” “said,” etc. should be read to recite one or more of the indicated elements unless a claim recites an explicit limitation to the contrary. Conditional language, such as, among others, “can,” “could,” “might,” or “may,” unless specifically stated otherwise, or otherwise understood within the context as used, is generally intended to convey that certain embodiments could include, while other embodiments may not include, certain features, elements, and/or steps. Thus, such conditional language is not generally intended to imply that features, elements, and/or steps are in any way required for one or more embodiments.
Number | Name | Date | Kind |
---|---|---|---|
8436902 | Kuehnle | May 2013 | B2 |
8665079 | Pawlicki | Mar 2014 | B2 |
8861791 | You | Oct 2014 | B2 |
9352777 | Lavoie | May 2016 | B2 |
9500497 | Lavoie | Nov 2016 | B2 |
9506774 | Shutko | Nov 2016 | B2 |
9536155 | Takemae | Jan 2017 | B2 |
9829883 | Lavoie | Nov 2017 | B1 |
9937953 | Lavoie | Apr 2018 | B2 |
9969428 | Hafner | May 2018 | B2 |
9981662 | Lavoie | May 2018 | B2 |
10126755 | Lavi | Nov 2018 | B1 |
10160274 | Gignac | Dec 2018 | B1 |
10214241 | Shepard | Feb 2019 | B2 |
10286950 | Lavoie | May 2019 | B2 |
10345822 | Parchami | Jul 2019 | B1 |
10730553 | Raad | Aug 2020 | B2 |
10773721 | Buss | Sep 2020 | B2 |
10800454 | Lavoie | Oct 2020 | B2 |
10814912 | Cotter | Oct 2020 | B2 |
11024051 | Gomezcaballero | Jun 2021 | B2 |
11027667 | Greenwood | Jun 2021 | B2 |
11034364 | Narang | Jun 2021 | B1 |
20060132295 | Gem | Jun 2006 | A1 |
20110184605 | Neff | Jul 2011 | A1 |
20120288154 | Shima | Nov 2012 | A1 |
20130151058 | Zagorski | Jun 2013 | A1 |
20140032049 | Moshchuk | Jan 2014 | A1 |
20140218522 | Lavoie | Aug 2014 | A1 |
20140249691 | Hafner | Sep 2014 | A1 |
20140358429 | Shutko | Dec 2014 | A1 |
20150120141 | Lavoie | Apr 2015 | A1 |
20170291603 | Nakamura | Oct 2017 | A1 |
20170329332 | Pilarski | Nov 2017 | A1 |
20180233034 | Tachibana | Aug 2018 | A1 |
20180267558 | Tiwari | Sep 2018 | A1 |
20190135291 | Sim | May 2019 | A1 |
20190202251 | Hall | Jul 2019 | A1 |
20190202451 | Hayamizu | Jul 2019 | A1 |
20190205024 | Lavoie | Jul 2019 | A1 |
20190210418 | Hall | Jul 2019 | A1 |
20190213290 | Delva | Jul 2019 | A1 |
20190276013 | Kim | Sep 2019 | A1 |
20190291730 | Kamiya | Sep 2019 | A1 |
20190294170 | Kazemi | Sep 2019 | A1 |
20190347498 | Herman | Nov 2019 | A1 |
20200062245 | Samotsvet | Feb 2020 | A1 |
20200064855 | Ji | Feb 2020 | A1 |
20200066147 | Vadillo | Feb 2020 | A1 |
20200086793 | Watanabe | Mar 2020 | A1 |
20200097001 | Lavoie | Mar 2020 | A1 |
20200110402 | Golgiri | Apr 2020 | A1 |
20200133259 | Van Wiemeersch | Apr 2020 | A1 |
20200150652 | Urano | May 2020 | A1 |
20200249684 | Onofrio | Aug 2020 | A1 |
20200257299 | Wang | Aug 2020 | A1 |
20200355823 | Tingley | Nov 2020 | A1 |
20210061270 | Parks | Mar 2021 | A1 |
20210082220 | Boerger | Mar 2021 | A1 |
20210107567 | Varunjikar | Apr 2021 | A1 |
20210129835 | Viehmann | May 2021 | A1 |
20210129865 | Jeong | May 2021 | A1 |
20210171136 | Kaiser | Jun 2021 | A1 |
20210190536 | Gil Casals | Jun 2021 | A1 |
20210197852 | Fairfield | Jul 2021 | A1 |
20210206389 | Kim | Jul 2021 | A1 |
20210229589 | Wright, III | Jul 2021 | A1 |
20210235019 | Tonkin | Jul 2021 | A1 |
20210237739 | Hayakawa | Aug 2021 | A1 |
20210269092 | Golgiri | Sep 2021 | A1 |
20210276588 | Kabzan | Sep 2021 | A1 |
20210309217 | Kim | Oct 2021 | A1 |
20220009522 | Zhang | Jan 2022 | A1 |
20220017079 | Kakeshita | Jan 2022 | A1 |
20220017080 | Moriya | Jan 2022 | A1 |
20220017081 | Yokoyama | Jan 2022 | A1 |
20220048499 | Yang | Feb 2022 | A1 |
20220063622 | Jumpertz | Mar 2022 | A1 |
20220063664 | Liu | Mar 2022 | A1 |
20220073095 | Seitz | Mar 2022 | A1 |
20220080977 | Ucar | Mar 2022 | A1 |
20220105931 | Motegi | Apr 2022 | A1 |
Number | Date | Country |
---|---|---|
102016224528 | Jun 2018 | DE |
Entry |
---|
“Trailering & Towing Technology in the Sierra—GMC Life,” Web page <https://www.gmc.com/gmc-life/truks/tailering-and-towing-technology-in-the-next-generation-2019-sierra.html>, 6 pages, retrieved from the internet on Oct. 26, 2020. |
Number | Date | Country | |
---|---|---|---|
20210229509 A1 | Jul 2021 | US |