Patent ID: 12254702

The appended drawings are not necessarily to scale and may present a somewhat simplified representation of various preferred features of the present disclosure as disclosed herein, including, for example, specific dimensions, orientations, locations, and shapes. Details associated with such features will be determined in part by the particular intended application and use environment.

DETAILED DESCRIPTION

The present disclosure is susceptible of embodiments in many different forms. Representative examples of the disclosure are shown in the drawings and described herein in detail as non-limiting examples of the disclosed principles. To that end, elements and limitations described in the Abstract, Introduction, Summary, and Detailed Description sections, but not explicitly set forth in the claims, should not be incorporated into the claims, singly or collectively, by implication, inference, or otherwise.

For purposes of the present description, unless specifically disclaimed, use of the singular includes the plural and vice versa, the terms “and” and “or” shall be both conjunctive and disjunctive, and the words “including”, “containing”, “comprising”, “having”, and the like shall mean “including without limitation”. Moreover, words of approximation such as “about”, “almost”, “substantially”, “generally”, “approximately”, etc., may be used herein in the sense of “at, near, or nearly at”, or “within 0-5% of”, or “within acceptable manufacturing tolerances”, or logical combinations thereof. As used herein, a component that is “configured to” perform a specified function is capable of performing the specified function without alteration, rather than merely having potential to perform the specified function after further modification. In other words, the described hardware, when expressly configured to perform the specified function, is specifically selected, created, implemented, utilized, programmed, and/or designed for the purpose of performing the specified function.

Referring to the drawings, the left most digit of a reference number identifies the drawing in which the reference number first appears (e.g., a reference number ‘310’ indicates that the element so numbered is first labeled or first appears inFIG.3). Additionally, elements which have the same reference number, followed by a different letter of the alphabet or other distinctive marking (e.g., an apostrophe), indicate elements which may be the same in structure, operation, or form but may be identified as being in different locations in space or recurring at different points in time (e.g., reference numbers “110a” and “110b” may indicate two different input devices which may be functionally the same, but may be located at different points in a simulation arena).

Vehicles have become computationally advanced and equipped with multiple microcontrollers, sensors, processors, and control systems, including for example, autonomous vehicle and advanced driver assistance systems (AV/ADAS) such as adaptive cruise control, automated parking, automatic brake hold, automatic braking, evasive steering assist, lane keeping assist, adaptive headlights, backup assist, blind spot detection, cross traffic alert, local hazard alert, and rear automatic braking may depend on information obtained from cameras and sensors on a vehicle. Such systems may also provide a wealth of information of the vehicle, including, for example, location, automatic assistance sensors, occupancy data, motion sensors, to name a few. These systems may also provide detailed data as to the operation and location of a vehicle. Such information may be combined with remote databases, for example at cloud-based operation, to share data with other vehicles to augment map overlays from third party providers.

FIG.1is an illustration of an urban environment100, according to an embodiment of the present disclosure. Urban environment100may include a vehicle110with a multitude of obstacles. Obstacles may include a fire hydrant120, a restricted parking zone125in front of the fire hydrant120, a first tree130and a second tree135, a curb140of a first height, and a curb150of a second height.

An occupant in vehicle110may wish to park and depart, or egress, or pick up a person from vehicle110. However, if vehicle110stops, or parks, and if a vehicle door is attempted to open near an obstacle, such as fire hydrant120, first tree130, or second tree135, there may be a possibility of an impact between the vehicle door and the obstacle. Further, if vehicle110attempts to park in a restricted parking zone125, possibly without realizing, then the vehicle110may be subject to a ticket or fine.

In another embodiment, if vehicle110stops in front of curb140of a first height, where the first height may be high enough that if a vehicle door of vehicle110may be opened then it may scrape and cause an impact between the vehicle door and curb140. Whereas if vehicle110stops in front of curb150of a second height, where the second height may be less than the first height, if a vehicle door of vehicle110may be opened then it may have enough clearance such that there is no impact between the vehicle door and curb150.

FIG.2Ais an illustration of a vehicle door and its associated swing path200, according to an embodiment of the present disclosure. Vehicle door210is depicted on a displacement chart illustrating its swing path. For example, vehicle door210may include a set of door locations220of the vehicle door210, which given that the physical configuration of the vehicle door210may be determined and its one or more pivot points may also be determined, by the use of geometric analysis a set of swing paths225representing the location of the door locations220may be calculated as the vehicle door210is swung open. Area230may represent the position of door locations220when the vehicle door210is opened to its fullest. Thus, as will be discussed, if an obstacle is present in the area of swing paths225, then a possible collision zone may be predicted for each of the door locations220.

FIG.2Billustrates examples of factors200′ associated with possible geometric calculations of swing paths, according to an embodiment of the present disclosure. Factors200′ may include vehicle240and its associated physical characteristics. For example, depending on the model of vehicle240, vehicle240may have different weights, dimensions, number of doors, etc., of which may impact the dynamics associated with its doors. Further factors that may influence the swing paths of a vehicle door of vehicle240may include a bank angle250that may represent the angle of inclination between a horizontal plane245and road plane255. Also, given the suspension, weight, and physical characteristics of vehicle240, roll angle260may represent the angle of inclination between the horizontal plane245and vehicle plane265, where roll angle260may be greater than bank angle250.

Given the bank angle250and roll angle260in conjunction with the physical characteristics of vehicle240, including a lower door length, a clearance distance270may be calculated and compared to a curb height275to determine the possibility of a potential collision between a door of vehicle240and a curb height275.

FIG.3is a flowchart of a method300for detecting obstruction and potential collision detection between a vehicle door and an obstacle, according to an embodiment of the present disclosure. Method300may be depicted as a collisions detection portion310and an obstructions portion312. Collisions detection portion310may include sensors315and controllers (not shown but may be used to process output from the sensors315that may also be contained within other modules referenced inFIG.3), obstacle detection320, potential collision detection325, outside rearview mirror (OSRVM) prediction330and surround view overlay335. Sensors315may include a variety of sensor types including laser, ultrasonic, and cameras. Data from sensors315may be passed to obstacle detection320that may be used to analyze motion from the sensors of a vehicle door and based upon the vehicle's physical characteristics and characteristics of the obstacle may determine that an obstacle may be in the swing path of one or more of the vehicle's doors.

Potential collision detection325may determine, based on input data, a potential of a collision. Potential collision detection325may perform a geometric analysis as discussed inFIGS.2A and2B, based on data associated with a vehicle's orientation and dimension, including data from a neighboring vehicle, including a prediction of a swing path of its OSRVM, to determine a potential collision. Data from potential collision detection325may be forwarded to a surround view overlay335that may warn of potential collisions and may also display such warnings in conjunction with the location of a vehicle door at its one or more detent angles.

Data from potential collision detection325may also be passed to the cloud map360and collision report355of the obstructions portion312.

Obstructions portion312may include cameras and encoders340, in addition to sensors315. Cameras and encoders340may include side cameras and sensors that may detect side door and back door, e.g., hatch or sportback, positions and motion. Door data345may include positions and motion for the doors of a vehicle including door positions through the use of door encoders and through the use of image analysis. Image analysis may include the use of tracking pixel position to determine position and velocity from the cameras and encoders340.

Impact severity estimation350may, based on door data345and other characteristics, for example the weight and velocity of a particular door, estimate a severity of an impact between a vehicle door and an obstacle.

Collision report355, based on received information from potential collision detection325and impact severity estimation350may provide collision, or near miss type information to fleet operations and insurance companies. Such information may also be sent to cloud map360, which may combine with additional information from potential collision detection325to generate a database of map curb compatible streets and map parking restrictions and information. Such information may then be sent to map view overly365for display to vehicle occupants.

FIG.4is a detailed flowchart of a method400for determining potential collision detection between a vehicle door and an obstacle, according to an embodiment of the present disclosure. Method400includes sensors, for example as discussed with sensors315, method400may include multiple sensors, for example LiDAR402, an underbody camera404, an ultrasonic sensor406and an exterior camera408that may be located within a vehicle, such as vehicle110. The vehicle may have one or more of these type of sensors, or other types not specifically listed, as sensors402,404,406, and408are illustrative and not meant to be limiting. Data from the sensors is sent to obstacle detection410, which as discussed inFIG.3, may also include processors, microcontrollers, or other dedicated circuitry to process output from the sensors. Obstacle detection410may detect obstacles such as curbs, trees, fire hydrants, or other objects. In addition, obstacle detection410may also detect other vehicles, for example if vehicle110pulls into a parking lot, obstacle detection unit may identify neighboring vehicles that may be parked on either side of vehicle110, in front of vehicle110, or behind vehicle110.

Obstacle detection410may then generate sets of data that may later be used as an input to potential collision detection. Such data may include obstacle dimensions412, for example the height and width and depth of an obstacle. The data may also include neighbor vehicle type414, for example, the neighbor vehicle is an SUV, truck, sedan, or motorcycle. In addition, the data may include a neighbor vehicle direction416, for example is the neighboring vehicle facing vehicle110, alongside of vehicle110, or pointing away from vehicle110.

Data from obstacle dimensions412, neighbor vehicle type414, and neighbor vehicle direction416may then be sent to OSRVM prediction415. OSRVM prediction415, based on its input data, may perform an analysis to predict the likelihood of an OSRVM of the neighboring vehicle, which typically is the obstacle that projects the furthest from a vehicle, may impact the vehicle110.

Potential collision detection420may receive data regarding a neighboring vehicle from OSRVM prediction415combined with data from obstacle detection410and compare such data with data regarding vehicle110, such as vehicle orientation417and vehicle dimensions419. Then, utilizing a set of mathematical calculations, potential collision detection420may perform a geometric analysis between an obstacle, e.g., the neighboring vehicle and vehicle110.

Potential collision detection420may pass its analysis to surround view overlay425in which surround view overlay425may warn the occupants of vehicle110of potential collisions and display such information as will be discussed in further detail inFIGS.5A,5B, andFIG.6. In addition, potential collision detection420may pass its analysis to a collision report step870as will be discussed inFIG.8. Potential collision detection420may also determine if the obstacle is a curb, at potential collision with curb430, if there is a potential collision. If a collision is predicted to not occur the flowchart is directed back to obstacle detection410to continue monitoring. If, however, a collision with a curb is predicted, then such a prediction is passed to cloud map440. Cloud map440, with input from the sensors at curb color435, determines whether the curb area may be a restricted parking or stopping zone.

Cloud map440may also receive input from the collision with a curb in step880that indicates a collision between a curb and a vehicle, for example vehicle110, has occurred. Cloud map may then compile a map curb with compatible streets for various type of vehicles in addition to parking restrictions and information gathered by the sensors. Map view overlay450may then process information from cloud map440to display curb compatible streets and also display parking restrictions and restrictions as will be discussed inFIG.7. Map view overlay450may also display, to vehicle occupants, graphics illustrating the status/position of doors in relation to detected obstacles.

FIGS.5A,5B, and5Cillustrate scenarios of possible displays of vehicle door position detents and possible collision zones, according to an embodiment of the present disclosure. As discussed, map view overlay450may display graphics illustrating the status/position of doors in relation to detected obstacles.

FIG.5Aillustrates indent door positions of vehicle505at first detent positions515,525,535, and545and second indent door positions at510,520,530, and540, where the second indent door positions illustrate the furthest the doors may be capable of swinging. Further, the dashed lines indicate a possible collision warning. Therefore, inFIG.5Billustrates a display warning to the occupants that there are possible collisions of the doors at the second detent positions,510′,520′,530′, and540′.FIG.5Cillustrates a display warning to the occupants that there are possible collisions of the left-hand doors at both the first and second detent positions,510′,515′,520′, and525′ while the right-hand doors are clear to open fully.

FIG.6illustrates a possible display of a collision zone with a neighboring vehicle, according to an embodiment of the present disclosure.FIG.6illustrates vehicle610alongside neighboring vehicle620. First indent position640, shown as a solid line, may indicate that no collisions are being predicted if the door is swung out to the first ident position. However, the second indent position630indicated, by the dashed line, predicts a possible collision between the vehicle door and neighboring vehicle620. Swing path650illustrates the arc path of the outer edge of the vehicle door with a collision zone660showing a possible impact zone of the vehicle door with neighboring vehicle620.

FIG.7illustrates an urban environment with a variety of parking obstacles, according to an embodiment of the present disclosure.FIG.7relates to the flow chart inFIG.4, specifically to potential collision detection420, potential collision with curb430, curb color435, cloud map440, and map view overlay450.

FIG.7highlights various parking scenarios, for example area710and area715shows that there are no parking restrictions and may also display these areas with a certain color. Area720and area730illustrate that parking is available, but with a restricted time frame, e.g., 7 am-8 pm. And area725may illustrate a restricted parking zone, here being a fire hydrant. Further, as discussed inFIG.4, curb color435, using a sensor, may determine a restricted parking zone by the color of a curb. For example, area725may include a curb color of red thereby indicating a no parking zone. In addition,FIG.7illustrates the use of icons in a display to convey a parking status, for example, the fire hydrant, the parking zone times, and a vehicle icon. In addition, as discussed inFIG.1andFIG.2, curb compatibility, or curb height as compared to a swing path of a door may also be indicated.

FIG.8illustrates a detail flowchart of a method800for estimating door impact severity, according to an embodiment of the present disclosure.FIG.8may be directed to a front door of a vehicle but may also be directed to another door of the vehicle using the same or similar approach. Method800may utilize side cameras that may be integrated into an OSRVM or otherwise located on an outside of a vehicle, for example vehicle110. At step810the side cameras may be activated. At step820, the side cameras may detect that the front door has been opened. At step830the side cameras of step810may detect motion in the front door due to motion being detected in one or more of the cameras. Further, in step840by tracking pixels in an image captured by the one or more cameras a velocity of the door may be computed. At step850the sensors, such as the LiDAR402, the underbody camera404, the ultrasonic sensor406or the exterior camera408, or even the side cameras, may have detected an obstacle. And, since, at step830and step840, the position and velocity of the door may be calculated, an angle of the door opening may also be calculated and compared to a threshold. At which point, if the position and velocity, or change in velocity, of the door are determined to be greater that a threshold value then it may be determined that there will be an impact between the front door and the obstacle. At step860given that an impact likelihood has been established and given that a weight of the door at step863may be determined, an estimation of the severity of the front door with the obstacle may be estimated.

If at step850the position and velocity, or change in velocity, may be less than the threshold, then method800is returned to step830to continue to determine a position of the front door.

If, at step820, it is determined that the front door has not been opened at step822, a determination may be made that a rear door may have been opened and motion may be detected. At step825the rear door position and velocity may be estimated where such estimation may be accomplished through the use of rear cameras or other types of position encoders. At step827the position and velocity, or change in velocity, may be calculated and a determination may be made that the rear door may be near a detected obstacle. If the position and velocity, or change in velocity, exceed a certain threshold then step827may determine that there may be an impact between the rear door and the obstacle. At step865, given that a weight of the rear door may be determined from step863, an estimation of a severity of the rear door impact with the obstacle may be made at step865.

At step820if a determination is made that the front door, either on the driver or passenger side, has not been opened, but at step837through the use of a door encoder may sense that another door has been opened. At step835the position and velocity, or change in velocity, may be calculated and a determination may be made that the rear door may be near a detected obstacle. If the position and velocity, or change in velocity, exceed a certain threshold then step835made determine that there may be an impact between the door and the obstacle. At step867, given that a weight of the rear door may be determined from step863, an estimation of a severity of the rear door impact with the obstacle may be made at step867.

At step870a collision report may be generated based on an impact of the front doors, back doors, or other doors and from the potential collision detection420fromFIG.4. Further, at step880, if the obstacle was a curb, then the method may continue to the cloud map440discussed inFIG.4. If at step880, the obstacle was not a curb, the method may continue to step820such that ongoing monitoring with the side cameras may continue.

FIG.9illustrates a vehicle to cloud communication environment900, according to an embodiment of the present disclosure. Environment900may include multiple vehicles, for example vehicle910and vehicle920. Vehicle910may communicate, using a vehicular communication device, not shown, through cloud940to vehicle920. Vehicle910may include sensors and processors, or microcontrollers, as discussed inFIG.3that may be configured to detect obstacles and predict potential collisions. Thus, vehicle910may transfer such information to a vehicle920that may not be equipped to sense and predict such potential collisions. Such peer-to-peer vehicular communications may enable vehicle910to share pertinent information with other vehicles of a similar body style and clearances.

Vehicle910may also communicate through cloud940to server930, such as a back-office system. For example, server930may belong to a fleet owner in which vehicle910and vehicle920may be owned by the fleet owner. Vehicle910and vehicle920may then be programmed to upload information through cloud940that may be of interest to the fleet owner. For example, if vehicle910senses an obstacle and predicts a potential collision then such information, possibly including the location of vehicle910may be communicated through cloud940to server930of the fleet owner. Further, if vehicle910detects a collision, for example from another vehicle or from a collision with a curb, that information may also be conveyed to the fleet owner.

A fleet owner, through server930may also communicate back to vehicle910and vehicle920through cloud940, for example with information collected from other vehicles and shared through a cloud map, such as cloud map360and a map view overlay, for example map view overlay365.

FIG.10shows an exemplary embodiment of a method1000for surround view egress assistance, according to an embodiment of the present disclosure. Method1000begins at step1005with a detecting, by a sensor in a vehicle, an obstacle in a swing path of a vehicle door. As discussed, an obstacle may be many different objects. InFIG.1obstacles includes may be a first tree130or a second tree135. Obstacles may also be a curb of a street such as a curb140of a first height and a curb150of a second height, or even an object such as a fire hydrant120. Obstacle may also be other vehicles, such as vehicle620. Sensors in a vehicle may detect these obstacles. Sensors such as sensors315, may include technologies such as a LiDAR402, an underbody camera404, an ultrasonic sensor406, and an exterior camera408, or even a side camera in step810.

At step1010a location of the OSRVM of a neighboring vehicle may be determined. The OSVRM of a vehicle may be the portion of a vehicle that protrudes from the body of the vehicle more than other portions of the vehicle. As such, at step1010the location of an OSRVM of a neighboring vehicle may be determined and used to predict or estimate one or more collision zones between the OSRVM and the vehicle.

At step1015the method may include predicting, based on a geometrical analysis, one or more potential collision zones between the obstacle and the vehicle door. For example, as discussed inFIG.2A, the physical characteristics of vehicle door210are known. Its weight, dimensions, shape, and pivot points may be determined for any particular model and make of a vehicle. Therefore, a swing path, for each point of the vehicle door210may be geometrically calculated. Once the swing paths, such as swing paths225may be determined, it may be possible to predict the likelihood of a collision between the vehicle door and an obstacle.

Further, a collision zone, such as collision zone660, may be displayed to occupants in the vehicle. Also, depending on the shape of the vehicle door and the shape of the obstacle, the collision zone660may include multiple points on both the obstacle and the vehicle door.

At step1020, once an obstacle may be detected and based on a geometrical analysis, a predicting of one or more potential collision zones may have occurred, then based on data from an inertial measurement unit, a severity of an impact of the vehicle door with the obstacle may be estimated. Further, in place of an inertial measurement unit, data may be received from a vehicle telemetry unit that may include a velocity of the vehicle door, a weight of the vehicle door, and a position of the vehicle door, and from which a severity of an impact may also be estimated.

At step1025the predicting of step1015may also take into account the position and tilt of the vehicle, for example as shown inFIG.2Bdue to a bank and roll angle of the vehicle, e.g., bank angle250and roll angle260. For example, if the bank angle250and roll angle260are great enough, it may be calculated that a vehicle door may impact a curb, where if the bank angle250and roll angle260were zero, e.g., no vehicle tilt, that the vehicle door may miss impacting the curb when opened.

At step1030, sensors, such as the sensors discussed in step1005, may detect a color and height of an adjacent curb.FIG.7illustrated some possible curb scenarios, for example area725may be designated as a restricted parking zone and painted red as an indication to motorists that the area725does not allow for parking. Or area720and area730may be designated as parking with restrictions such as during certain hours of the day. This availability information may be conveyed by a particular color of the curb or stored and accessed through the cloud, for example through the cloud map440. Such information may then be conveyed to vehicle occupants through a visual or audible interface, for example through map view overlay450.

At step1035, an actual strike between the vehicle door and an obstacle may be detected. Such detection may utilize the sensors previously discussed or may also include motion or vibration sensors. The strike between the vehicle door and an obstacle may be caused by movement of the vehicle door or may also include a strike from a neighboring vehicle or object without movement of the vehicle door.

At step1040, as discussed above, a severity of an impact of the vehicle door with the obstacle may be based on data from an inertial measurement unit, where that data may include a velocity of the vehicle door, a weight of the vehicle door, and a position of the vehicle door.

At step1045data that is captured or calculated in the vehicle may be passed up to a cloud storage system. In addition, data that is stored in the cloud storage system may be accessed and downloaded to the vehicle or to a different vehicle or a vehicle owner, for example a fleet owner. Thus, step1045includes accessing, using a communication device, a cloud storage system configured to store information comprising a door collision, a parking restriction, and a curb compatibility wherein an owner may be notified of the presence of information, and wherein an additional vehicle may also have access to the information. As discussed with collision report355such data may also be sent to cloud map360, which may combine with additional information from potential collision detection325to generate a database of map curb compatible streets and map paring restrictions and information. Further, such information may also be sent to map view overly365for display to vehicle occupants.

At step1050, a position of the door may be determined in a number of ways. One such method is to use an outside camera, for example a camera mounted in an OSRVM, to determine its position based on the camera image motion. For example, as discussed inFIG.8, at step830, the side cameras of step810may detect motion in the front door due to motion being detected in one or more of the cameras. Further, in step840by tracking pixels in an image captured by the one or more cameras a velocity of the door may be computed.

Method1000may then end.

The description and abstract sections may set forth one or more embodiments of the present disclosure as contemplated by the inventor(s), and thus, are not intended to limit the present disclosure and the appended claims.

Embodiments of the present disclosure have been described above with the aid of functional building blocks illustrating the implementation of specified functions and relationships thereof. The boundaries of these functional building blocks have been arbitrarily defined herein for the convenience of the description. Alternate boundaries may be defined so long as the specified functions and relationships thereof may be appropriately performed.

The foregoing description of the specific embodiments will so fully reveal the general nature of the disclosure that others can, by applying knowledge within the skill of the art, readily modify and/or adapt for various applications such specific embodiments, without undue experimentation, without departing from the general concept of the present disclosure. Therefore, such adaptations and modifications are intended to be within the meaning and range of equivalents of the disclosed embodiments, based on the teaching and guidance presented herein. It is to be understood that the phraseology or terminology herein is for the purpose of description and not of limitation, such that the terminology or phraseology of the present specification is to be interpreted by the skilled artisan in light of the teachings and guidance.

The breadth and scope of the present disclosure should not be limited by any of the above-described exemplary embodiments.

Exemplary embodiments of the present disclosure have been presented. The disclosure is not limited to these examples. These examples are presented herein for purposes of illustration, and not limitation. Alternatives (including equivalents, extensions, variations, deviations, etc., of those described herein) will be apparent to persons skilled in the relevant art(s) based on the teachings contained herein. Such alternatives fall within the scope and spirit of the disclosure.