PATENT DOCUMENT

Publication Number: US-10583828-B1
Application Number: US-201615275153-A
Country: US
Kind Code: B1

Title: Position determination

Abstract:
Some embodiments provide an autonomous navigation system which autonomously parks a vehicle in a selected available parking space. The vehicle can be parked in a particular parking position in the parking space based on one or more factors. The particular parking position can be selected from a set of potential parking positions based on an aggregate intersection risk value associated with the particular parking position being less than at least one other potential parking position. The aggregate intersection risk value can be determined based on one or more of a proximity of one or more adjacent vehicles to the parking space, a door sweep volume of the one or more adjacent vehicles, body morphology of one or more present occupants of the vehicle, and predicted occupancy of the vehicle.

Claims:
What is claimed is: 
     
       1. An apparatus, comprising:
 an autonomous navigation system configured to be installed in an ego-vehicle and autonomously park the ego-vehicle in an environment in which the ego-vehicle is located, wherein the autonomous navigation system is configured to, in response to a command to park the ego-vehicle:
 select a particular parking position of the ego-vehicle within a detected available parking space, from a set of potential parking positions within the detected available parking space, based at least in part upon:
 a proximity of at least one door sweep volume of a door on a detected vehicle based at least in part upon recognition of a vehicle type associated with the detected vehicle according to one or more unique identifiers associated with the detected vehicle, wherein the detected vehicle is separate from the ego-vehicle and located proximate to the particular parking position selected by the ego-vehicle, and wherein the door sweep volume comprises a space through which the door is configured to sweep through the environment when the door is opened, or 
 a predicted occupancy of one or more portions of an interior of the ego-vehicle at a future time prior to the vehicle leaving the detected available parking space; and 
 
 generate a set of control commands which, when executed by one or more control elements installed in the ego-vehicle, cause the ego-vehicle to be navigated along a driving route which results in the ego-vehicle being positioned in the particular parking position in the detected available parking space. 
 
 
     
     
       2. The apparatus of  claim 1 , wherein:
 to select the particular parking position based at least in part upon a proximity of at least one door sweep volume of a door on a detected vehicle to the particular parking position, the autonomous navigation system is configured to:
 identify the door of the detected vehicle on a particular position on the detected vehicle; 
 determine the door sweep volume of the door on the detected vehicle; 
 assign a spacing weight value with the door sweep volume; 
 assign separate aggregate intersection risk values with each potential parking position of the set of potential parking positions, based at least in part upon, for each potential parking position, a determined proportion of the door sweep volume which overlaps the given potential parking position and the spacing weight value assigned to the door sweep volume; and 
 select, as the particular parking position of the ego-vehicle, a particular potential parking position, of the set of potential parking positions, associated with a minimum aggregate intersection risk value for the set of potential parking positions. 
 
 
     
     
       3. The apparatus of  claim 2 , wherein the autonomous navigation system is configured to:
 identify the door of the detected vehicle on a particular position on the detected vehicle, and determine the door sweep volume of the door, based at least in part upon recognition of the vehicle type associated with the detected vehicle. 
 
     
     
       4. The apparatus of  claim 3 , wherein the autonomous navigation system is configured to:
 associate the spacing weight value with one or more portions of the detected vehicle, based at least in part upon recognition of the vehicle type associated with the detected vehicle. 
 
     
     
       5. The apparatus of  claim 4 , wherein:
 recognition of the vehicle type associated with the detected vehicle is based at least in part upon at least one of:
 identifying the one or more unique identifiers associated with the detected vehicle, based on processing at least one sensor data representation, of the detected vehicle, generated by one or more sensor devices installed in the ego-vehicle; 
 determining a particular vehicle type associated with the identified one or more unique identifiers, wherein the particular vehicle type comprises one or more of a make, a model, a year, or any combination thereof, of the detected vehicle. 
 
 
     
     
       6. The apparatus of  claim 1 , wherein:
 the at least one detected vehicle comprises at least two separate vehicles presently located adjacent to the detected available parking space; and 
 to determine a particular parking position of the ego-vehicle within a detected available parking space, the autonomous navigation system is configured to:
 associate spacing weight values with the at least two separate vehicles; 
 for each separate potential parking position, of the set of potential parking positions within the detected available parking space, determine a separate aggregate intersection risk value associated with the given potential parking position, based at least in part upon, for each of the at least two separate vehicles, a proximity of the given potential parking position to the respective one of the at least two separate vehicles and the spacing weight value assigned to the respective one of the at least two separate vehicles; and 
 
 select, as the particular parking position of the ego-vehicle, a particular parking position of the set of potential parking positions associated with a minimum aggregate intersection risk value. 
 
     
     
       7. The apparatus of  claim 1 , wherein:
 at least one potential parking position, of the set of potential parking positions, comprises a particular orientation of the ego-vehicle relative to the detected available parking space. 
 
     
     
       8. The apparatus of  claim 1 , wherein:
 selection of a particular parking position of the ego-vehicle within a detected available parking space, from a set of potential parking positions of the ego-vehicle within the detected available parking space, is further based at least in part upon detection of one or more occupants in one or more particular portions of an interior of the ego-vehicle, the autonomous navigation system is configured to:
 for each occupant detected in the interior:
 identify a door of the ego-vehicle associated with the portion of the interior occupied by the given occupant; 
 determine a particular spacing weight value associated with the occupant based on one or more determined properties of the given occupant; and 
 assign the particular spacing weight value to a door sweep volume through which the identified door is configured to sweep through the environment when the identified door is opened; 
 
 for each potential parking position of the set of potential parking positions:
 determine a separate intersection risk value for each door sweep volume comprised in the given potential parking position, based at least in part upon the respective spacing weight value assigned to the respective door sweep volume and a proportion of the door sweep volume comprised in the given potential parking position which overlaps at least some of one or more objects located in the environment; and 
 determine an aggregate intersection risk value for the given potential parking position, based at least in part upon the separate intersection risk values determined for each door sweep volume comprised in the given potential parking position; and 
 
 selecting, as the particular parking position of the ego-vehicle, a particular parking position of the set of potential parking positions associated with a minimum aggregate intersection risk value. 
 
 
     
     
       9. The apparatus of  claim 8 , wherein:
 the autonomous navigation system is configured to, for at least one occupant detected in the interior, determine a particular spacing weight value associated with the occupant based on a determined body morphology of the at least one occupant. 
 
     
     
       10. The apparatus of  claim 9 , wherein:
 the autonomous navigation system is configured to determine a body morphology of the at least one occupant based on processing at least one sensor data representation, generated by at least one sensor device installed in the ego-vehicle, of at least a portion of the at least one occupant. 
 
     
     
       11. The apparatus of  claim 10 , wherein:
 the autonomous navigation system is configured to determine a body morphology of the at least one occupant based on monitoring one or more body motions of the at least one occupant prior to the at least one occupant entering the interior of the ego-vehicle. 
 
     
     
       12. The apparatus of  claim 9 , wherein:
 the autonomous navigation system is further configured to determine a particular spacing weight value associated with the occupant based on:
 associating the occupant with a particular user profile, based on processing at least one sensor data representation of at least a portion of the at least one occupant; and 
 identifying a spacing weight value associated with the particular user profile. 
 
 
     
     
       13. The apparatus of  claim 1 , wherein:
 the predicted occupancy of one or more portions of an interior of the ego-vehicle comprises a predicted occupancy of one or more particular portions of the interior by one or more occupants associated with one or more particular body morphologies. 
 
     
     
       14. The apparatus of  claim 13 , wherein:
 the autonomous navigation system is configured to determine the predicted occupancy of one or more particular portions of the interior by one or more occupants associated with one or more particular body morphologies based at least in part upon:
 determining a present position of the ego-vehicle in the environment; and 
 determining that a probability that the one or more occupants will board one or more particular portions of the ego-vehicle interior at the present location at least meets a probability threshold value, based on at least one historical record of ego-vehicle occupant additions associated with the present position. 
 
 
     
     
       15. The apparatus of  claim 13 , wherein:
 the autonomous navigation system is configured to determine the predicted occupancy of one or more particular portions of the interior by one or more occupants associated with one or more particular body morphologies based at least in part upon:
 determining a present local time; and 
 determining that a probability that the one or more occupants will board one or more particular portions of the ego-vehicle interior at the present local time at least meets a probability threshold value, based on at least one historical record of ego-vehicle occupant additions associated with the present local time. 
 
 
     
     
       16. The apparatus of  claim 13 , wherein:
 to select a particular parking position of the ego-vehicle within a detected available parking space, based at least in part upon a predicted occupancy of one or more portions of an interior of the ego-vehicle, the autonomous navigation system is configured to:
 for at least each predicted occupant of the interior:
 identify a door of the ego-vehicle associated with the portion of the interior predicted to be occupied by the given occupant; 
 determine a particular spacing weight value associated with the predicted occupant based on one or more particular body morphologies of the given occupant; and 
 associate the particular spacing weight value with a door sweep volume through which the identified door is configured to sweep through the environment when the identified door is opened; 
 
 for each potential parking position of the set of potential parking positions:
 determine a separate intersection risk value for each door sweep volume comprised in the given potential parking position, based at least in part upon the respective spacing weight value associated with the respective door sweep volume and a proportion of the door sweep volume comprised in the given potential parking position which overlaps at least some of one or more objects located in the environment; and 
 determine an aggregate intersection risk value for the given potential parking position, based at least in part upon the separate intersection risk values determined for each door sweep volume comprised in the given potential parking position; and 
 
 select, as the particular parking position of the ego-vehicle, a particular parking position of the set of potential parking positions associated with a minimum aggregate intersection risk value. 
 
 
     
     
       17. The apparatus of  claim 16 , wherein:
 at least one potential parking position, of the set of potential parking positions, comprises a particular orientation of the ego-vehicle relative to the detected available parking space. 
 
     
     
       18. A method, comprising:
 performing by an autonomous navigation system of an ego-vehicle, in response to a command to park the ego-vehicle:
 selecting a particular parking position of the ego-vehicle within a detected available parking space, from a set of potential parking positions within the detected available parking space, based at least in part upon:
 a proximity of at least one door sweep volume of a door on a detected vehicle based at least in part upon recognition of a vehicle type associated with the detected vehicle according to one or more unique identifiers associated with the detected vehicle, wherein the detected vehicle is being separate from the ego-vehicle and located proximate to the particular parking position selected by the ego-vehicle, wherein the door sweep volume comprises a space through which the door is configured to sweep through when the door is opened, or 
 a predicted occupancy of one or more portions of an interior of the ego-vehicle at a future time prior to the vehicle leaving the detected available parking space; and 
 
 generating a set of control commands which, when executed by one or more control elements installed in the ego-vehicle, cause the ego-vehicle to be navigated along a driving route which results in the ego-vehicle being positioned in the particular parking position in the detected available parking space. 
 
 
     
     
       19. The method of  claim 18 , wherein:
 selecting the particular parking position based at least in part upon a proximity of at least one door sweep volume of a door on a detected vehicle to the particular parking position, comprises:
 identifying the door of the detected vehicle on a particular position on the detected vehicle; 
 determining the door sweep volume of the door on the detected vehicle; 
 assigning a spacing weight value with the door sweep volume; 
 assigning separate aggregate intersection risk values with each potential parking position of the set of potential parking positions, based at least in part upon, for each potential parking position, a determined proportion of the door sweep volume which overlaps the given potential parking position and the spacing weight value assigned to the door sweep volume; and 
 selecting, as the particular parking position of the ego-vehicle, a particular potential parking position, of the set of potential parking positions, associated with a minimum aggregate intersection risk value for the set of potential parking positions. 
 
 
     
     
       20. A non-transitory computer readable medium storing program instructions that when executed by an autonomous navigation system of an ego-vehicle cause the autonomous navigation system to:
 select, in response to a command to park the ego-vehicle, a particular parking position of the ego-vehicle within a detected available parking space, from a set of potential parking positions within the detected available parking space, based at least in part upon:
 a proximity of at least one door sweep volume of a door on a detected vehicle based at least in part upon recognition of a vehicle type associated with the detected vehicle according to one or more unique identifiers associated with the detected vehicle, wherein the detected vehicle is being separate from the ego-vehicle and located proximate to the particular parking position selected by the ego-vehicle, wherein the door sweep volume comprises a space through which the door is configured to sweep through when the door is opened, or 
 a predicted occupancy of one or more portions of the interior of the ego-vehicle at a future time prior to the vehicle leaving the detected available parking space; and 
 
 generate a set of control commands which, when executed by one or more control elements installed in the ego-vehicle, cause the ego-vehicle to be navigated along a driving route which results in the ego-vehicle being positioned in the particular parking position in the detected available parking space.

Description:
This application claims benefit of priority of U.S. Provisional Application Ser. No. 62/232,814, filed Sep. 25, 2015, which is hereby incorporated by reference herein in its entirety. 
    
    
     BACKGROUND 
     Technical Field 
     This disclosure relates generally to autonomous navigation of a vehicle, and in particular to an autonomous navigation system which can be included in a vehicle and which navigates the vehicle in an environment which includes one or more vehicle parking spaces. 
     Description of the Related Art 
     The rise of interest in autonomous navigation of vehicles, including automobiles, has resulted in a desire to develop autonomous navigation systems which can autonomously navigate (i.e., autonomously “drive”) a vehicle through various routes, including one or more roads in a road network, such as contemporary roads, streets, highways, etc. 
     In some cases, autonomous navigation is enabled via an autonomous navigation system (ANS) which can process and respond to detection of various elements in an external environment, including static features (e.g., roadway lanes, road signs, etc.) and dynamic features (present locations of other vehicles in a roadway on which the route extends, present locations of pedestrians, present environmental conditions, roadway obstructions, etc.) along a route in real-time as they are encountered, thereby replicating the real-time processing and driving capabilities of a human being. 
     In some cases, an autonomous navigation system autonomously positions a vehicle in which the system is located, also referred to herein as the “ego-vehicle”, in a parking space, also referred to as “parking” the ego-vehicle, based on geometric considerations, including one or more of the size and dimensions of the ego-vehicle and the parking spot geometry. For example, the ego-vehicle can be parked in the parking space in a particular position, also referred to herein as the parking position of the ego-vehicle, where the parking position of the ego-vehicle relative to the parking space is determined based on one or more geometric features. For example, an autonomous navigation system navigating a vehicle can determine a parking position of the ego-vehicle within a given parking space based on centering a surface area overlay of the ego-vehicle on the driving surface, also referred to as the ego-vehicle “footprint”, a midpoint of the parking space, so that the ego-vehicle, when parked in the parking position, is centered within the parking space. 
     SUMMARY OF EMBODIMENTS 
     Some embodiments provide an autonomous navigation system which autonomously parks a vehicle in an environment in which the vehicle is located. The autonomous navigation system, in response to a command to park the vehicle, determines a particular parking position of the vehicle within a detected available parking space and generates a set of control commands which, when executed by one or more control elements installed in the vehicle, cause the vehicle to be navigated along a driving route which results in the vehicle being positioned in the particular parking position in the detected available parking space. The particular parking position is determined based at least in part upon a position of at least one at least one detected vehicle located proximate to the detected available parking space. 
     Some embodiments provide an autonomous navigation system which autonomously parks the vehicle in an environment in which the vehicle is located. The autonomous navigation system, in response to a command to park the vehicle, select a particular parking position of the vehicle within a detected available parking space, from a set of potential parking positions of the vehicle within the detected available parking space, based at least in part upon detection of one or more occupants in one or more particular portions of an interior of the vehicle; and generates a set of control commands which, when executed by one or more control elements installed in the vehicle, cause the vehicle to be navigated along a driving route which results in the vehicle being positioned in the particular parking position in the detected available parking space. 
     Some embodiments provide an autonomous navigation system which autonomously parks the vehicle in an environment in which the vehicle is located. The autonomous navigation system, in response to a command to park the vehicle, selects a particular parking position of the vehicle within a detected available parking space, from a set of potential parking positions of the vehicle within the detected available parking space, based at least in part upon a predicted occupancy of one or more portions of an interior of the vehicle; and generate a set of control commands which, when executed by one or more control elements installed in the vehicle, cause the vehicle to be navigated along a driving route which results in the vehicle being positioned in the particular parking position in the detected available parking space. 
    
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
         FIG. 1  illustrates a schematic block diagram of a vehicle which comprises an autonomous navigation system (ANS) which is configured to park the vehicle in a selected parking position in a selected parking space, according to some embodiments. 
         FIG. 2  illustrates an overhead view of an environment in which an ego-vehicle and parking spaces are located and where an ANS installed in the vehicle determines a particular parking position in a particular available parking space in which the vehicle can be parked, according to some embodiments. 
         FIG. 3A  illustrates an overhead view of an environment in which an ego-vehicle and parking spaces are located and where an ANS installed in the vehicle determines a particular parking position in a particular available parking space in which the vehicle can be parked, according to some embodiments. 
         FIG. 3B  illustrates an overhead view of an environment in which an ego-vehicle and parking spaces are located and where an ANS installed in the ego-vehicle determines a particular parking position in a particular available parking space  304  in which the ego-vehicle can be parked, according to some embodiments. 
         FIG. 3C  illustrates parking an ego-vehicle in a particular parking position in an identified available parking space, according to some embodiments. 
         FIG. 4A  illustrates an overhead view of an environment in which an ego-vehicle and parking spaces are located and where an ANS installed in the vehicle determines a particular parking position in a particular available parking space in which the vehicle can be parked, according to some embodiments. 
         FIG. 4B  illustrates an overhead view of an environment in which an ego-vehicle and parking spaces are located and where an ANS installed in the vehicle determines a particular parking position in a particular available parking space in which the vehicle can be parked, according to some embodiments. 
         FIG. 4C  illustrates parking an ego-vehicle in a particular parking position in an identified available parking space, according to some embodiments. 
         FIG. 5A  illustrates an overhead view of an environment in which an ego-vehicle and parking spaces are located and where an ANS installed in the vehicle determines a particular parking position in a particular available parking space in which the vehicle can be parked, according to some embodiments. 
         FIG. 5B  illustrates parking an ego-vehicle in a particular parking position in an identified available parking space, according to some embodiments. 
         FIG. 6  illustrates a computer system that may be configured to include or execute any or all of the embodiments described herein. 
     
    
    
     This specification includes references to “one embodiment” or “an embodiment.” The appearances of the phrases “in one embodiment” or “in an embodiment” do not necessarily refer to the same embodiment. Particular features, structures, or characteristics may be combined in any suitable manner consistent with this disclosure. 
     “Comprising.” This term is open-ended. As used in the appended claims, this term does not foreclose additional structure or steps. Consider a claim that recites: “An apparatus comprising one or more processor units. . . . ” Such a claim does not foreclose the apparatus from including additional components (e.g., a network interface unit, graphics circuitry, etc.). 
     “Configured To.” Various units, circuits, or other components may be described or claimed as “configured to” perform a task or tasks. In such contexts, “configured to” is used to connote structure by indicating that the units/circuits/components include structure (e.g., circuitry) that performs those task or tasks during operation. As such, the unit/circuit/component can be said to be configured to perform the task even when the specified unit/circuit/component is not currently operational (e.g., is not on). The units/circuits/components used with the “configured to” language include hardware—for example, circuits, memory storing program instructions executable to implement the operation, etc. Reciting that a unit/circuit/component is “configured to” perform one or more tasks is expressly intended not to invoke 35 U.S.C. § 112, sixth paragraph, for that unit/circuit/component. Additionally, “configured to” can include generic structure (e.g., generic circuitry) that is manipulated by software and/or firmware (e.g., an FPGA or a general-purpose processor executing software) to operate in manner that is capable of performing the task(s) at issue. “Configure to” may also include adapting a manufacturing process (e.g., a semiconductor fabrication facility) to fabricate devices (e.g., integrated circuits) that are adapted to implement or perform one or more tasks. 
     “First,” “Second,” etc. As used herein, these terms are used as labels for nouns that they precede, and do not imply any type of ordering (e.g., spatial, temporal, logical, etc.). For example, a buffer circuit may be described herein as performing write operations for “first” and “second” values. The terms “first” and “second” do not necessarily imply that the first value must be written before the second value. 
     “Based On.” As used herein, this term is used to describe one or more factors that affect a determination. This term does not foreclose additional factors that may affect a determination. That is, a determination may be solely based on those factors or based, at least in part, on those factors. Consider the phrase “determine A based on B.” While in this case, B is a factor that affects the determination of A, such a phrase does not foreclose the determination of A from also being based on C. In other instances, A may be determined based solely on B. 
     DETAILED DESCRIPTION 
     Some embodiments include one or more vehicles in which an autonomous navigation system (“ANS”) is included, where the ANS is configured to navigate the vehicle to a position within a space in the environment which is configured for vehicle parking. Such a space can be referred to herein as a parking space, and the position of the vehicle in the parking space to which the ANS navigates the vehicle can be referred to as a parking position. 
     In some embodiments, the ANS installed in a vehicle is configured to navigate the vehicle in which the ANS is installed, also referred to herein as the ego-vehicle, to a stop in a particular position within a parking space. The ANS can identify and select a particular parking space in the environment in which to stop the vehicle, also referred to herein as parking the vehicle. The ANS can further determine a particular parking position within the particular parking space to park the vehicle, and the ANS can navigate the vehicle to be parked in the particular parking position within the particular parking space. 
     A parking position can represent a portion of the parking space which can be at least partially occupied by the ego-vehicle. In some embodiments, the parking position is sized and shaped to at least partially correspond to the geometry of the ego-vehicle. For example, a parking position can include a surface area of a driving surface, including a surface area of a parking space, over which a vehicle is positioned when the vehicle is parked in the given parking position. Such a surface area can be referred to as a driving surface “footprint” of the ego-vehicle. In some embodiments, the parking position can include a particular volume space of the environment which can be occupied by the ego-vehicle when the ego-vehicle is parked in the given parking position. 
     In some embodiments, the parking position includes one or more of a particular portion of the environment through which a door included in the vehicle can sweep when the door is at least partially opened. The footprint of such a portion can be referred to as the door sweep area of the door, and the volume space of such a portion can be referred to as the door sweep volume of the door. As referred to herein, the door sweep area of a door and the door sweep volume of a door are referred to herein as the door sweep volume of the door. A parking position which includes one or more of a door sweep area, door sweep volume, etc. of a door included in the vehicle can include said one or more of a door sweep area, door sweep volume, etc. extending from a particular position at a boundary of the vehicle footprint, volume space, etc. which corresponds to a relative position of the door on the exterior of the ego-vehicle. 
     In some embodiments, a parking position includes a footprint area of a vehicle which is parked in a particular orientation within a parking space. For example, a parking position can include a footprint of a vehicle which is positioned with a front end of the vehicle pointing towards an exit of the parking space. Where the ANS installed in a vehicle navigates the vehicle to a parking position, in a parking space, where the parking position includes a particular orientation of the vehicle, the ANS can navigate the vehicle to be parked in the particular orientation in the parking position. 
     In some embodiments, the ANS autonomously navigates the vehicle along a driving route via generation of control commands associated with various control elements of the vehicle, where the control commands, when received at the associated control elements, cause the control elements to navigate the vehicle along the driving route. 
     In some embodiments, the ANS generates a driving route through an external environment based at least in part upon various objects included in the external environment. Such objects can include one or more static elements, including roadway features, including roadway lanes, curbs, etc., parking space features, including sparking space boundary markings, traffic signs and traffic signals, flora, artificial structures, inanimate objects, etc. Such objects can include one or more dynamic elements, including a time of day, local weather conditions, fauna, traffic participants, etc. in the external environment. Traffic participants can include vehicles, pedestrians, some combination thereof, etc. located in the external environment, including traffic participants located proximate to or in the roadway along which the vehicle is located. 
     As referred to herein, a “driving route” includes a pathway along which a vehicle is navigated. A driving route can extend from a starting location to another separate destination location, extend back to a destination location which is the same as the starting location, etc. A route can extend along one or more various portions of one or more various roadways. For example, a route between a home location and a work location can extend from a home driveway, through one or more residential streets, along one or more portions of one or more avenues, highways, toll ways, etc., and to one or more parking spaces in one or more parking areas. Such routes can be routes which a user repeatedly navigates over time, including multiple times in a given day (e.g., routes between home and work locations may be travelled at least once in a given day). 
     Reference will now be made in detail to embodiments, examples of which are illustrated in the accompanying drawings. In the following detailed description, numerous specific details are set forth in order to provide a thorough understanding of the present disclosure. However, it will be apparent to one of ordinary skill in the art that some embodiments may be practiced without these specific details. In other instances, well-known methods, procedures, components, circuits, and networks have not been described in detail so as not to unnecessarily obscure aspects of the embodiments. 
     It will also be understood that, although the terms first, second, etc. may be used herein to describe various elements, these elements should not be limited by these terms. These terms are only used to distinguish one element from another. For example, a first contact could be termed a second contact, and, similarly, a second contact could be termed a first contact, without departing from the intended scope. The first contact and the second contact are both contacts, but they are not the same contact. 
     The terminology used in the description herein is for the purpose of describing particular embodiments only and is not intended to be limiting. As used in the description and the appended claims, the singular forms “a”, “an” and “the” are intended to include the plural forms as well, unless the context clearly indicates otherwise. It will also be understood that the term “and/or” as used herein refers to and encompasses any and all possible combinations of one or more of the associated listed items. It will be further understood that the terms “includes,” “including,” “comprises,” and/or “comprising,” when used in this specification, specify the presence of stated features, integers, steps, operations, elements, and/or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and/or groups thereof. 
     As used herein, the term “if” may be construed to mean “when” or “upon” or “in response to determining” or “in response to detecting,” depending on the context. Similarly, the phrase “if it is determined” or “if [a stated condition or event] is detected” may be construed to mean “upon determining” or “in response to determining” or “upon detecting [the stated condition or event]” or “in response to detecting [the stated condition or event],” depending on the context. 
       FIG. 1  illustrates a schematic block diagram of a vehicle  100  which comprises an autonomous navigation system (ANS)  110  which is configured to park the vehicle  100  in a selected parking position in a selected parking space, according to some embodiments. Some or all of the ANS  110  illustrated in  FIG. 1 , including one or more of the modules  111 ,  112 ,  113 , etc., can be included in any of the embodiments of ANSs included in any of the embodiments herein. 
     Vehicle  100  includes an autonomous navigation system (“ANS”)  110 , a set of one or more sensor devices  116 , a set of one or more control elements  120 , and a set of one or more user interfaces  130 . 
     Sensor devices  116  can include one or more sensor devices which are configured to monitor one or more aspects of an external environment in which the vehicle is located. Monitoring an aspect of an external environment can include generating, at the sensor device, sensor data which includes information regarding the aspect of the external environment; such sensor data can be referred to as a sensor data representation of the aspect of the external environment. For example, a sensor device  116  can include one or more of a camera device which generates images of one or more portions of the external environment, a light beam scanning device which generates one or more point clouds of one or more portions of the external environments, a radar device which generates radar data associated with one or more portions of the external environment, etc. Aspects of an external environment which can be monitored include one or more objects included in the environment, where the one or more objects can include one or more static elements, dynamic elements, etc. For example, a sensor device  116  which includes a camera device can capture images of an external environment which includes images of static elements, including parking space boundary markers, roadway curbs, physical objects located adjacent to a parking space, inanimate obstacles in the roadway, etc., images of dynamic elements including traffic participants, fauna, ambient environment conditions, weather, etc. 
     Sensor devices  116  can include one or more sensor devices which are configured to monitor one or more aspects of the vehicle  100  interior. Such sensor devices can include camera devices configured to collect image data of one or more occupants in the vehicle interior, control element sensors which monitor operating states of various driving control elements  120  of the vehicle, some combination thereof, etc. One or more of sensor devices  116  can generate one or more sensor data representations of one or more portions of the vehicle interior, including one or more sensor data representations of at least some portion of one or more occupants in the one or more portions of the vehicle interior. Such sensor data representations generated by one or more sensor devices  116  can be communicated to ANS  110  and used by the ANS  110  to determine one or more of occupancy of one or more portions of the vehicle interior, quantity of occupants of the vehicle interior, body morphologies associated with one or more occupants of the vehicle interior, profiles associated with one or more occupants of the vehicle interior, personal data associated with one or more particular occupants of the vehicle interior, etc. 
     The control elements  120  included in vehicle  100  include various control elements, including actuators, motors, etc. which each control one or more components of the vehicle which cause the vehicle to be navigated through an external environment. For example, a control element  120  can include one or more of a braking assembly (also referred to herein interchangeably as a braking system) which applies braking pressure to one or more wheel assemblies of the vehicle to cause the vehicle to be decelerated, a throttle assembly which adjusts the acceleration of the vehicle  100  through an external environment, a steering assembly which adjusts one or more configurations of one or more wheel assemblies which causes the vehicle to be adjustably navigated in one or more various directions through the external environment, etc. A control element can execute one or more various adjustments to navigation of the vehicle based on receipt and execution of one or more various control commands at the control elements from one or more of a user interface  130 , the ANS  110 , etc. 
     The one or more interfaces  130  can include one or more user interfaces, also referred to herein interchangeably as input interfaces, including one or more driving control interfaces with which an occupant of the vehicle  100  can interact, such that the driving control interfaces generate control commands which cause one or more control elements  120  to adjustably navigate the vehicle  100 , based on one or more occupant interactions with one or more interfaces  130 . For example, one or more interfaces  130  can provide an interactive interface via which an occupant can provide a command, to the ANS  110 , to park the vehicle  100 . The parking command, in some embodiments, is independent of specifying a specific parking space in which to park the vehicle and comprises a command to the ANS to select a parking space and park the vehicle  100  in the selected parking space. The parking command can comprise a command to the ANS  110  to park the vehicle  100  in a parking space located within a certain proximity of the vehicle  100  in the environment. In some embodiments, where the ANS  110  navigates the vehicle  100  along a driving route, the driving route can include navigating the vehicle  100  to a parked position in a parking spot located within a certain proximity of a destination location of the driving route. As a result, the ANS  110  can, upon navigating to within a certain proximity of a destination location of the driving route, select a parking space located within a certain proximity of the destination location and park the vehicle  100  in the selected parking space as part of navigating the vehicle to the destination location. 
     In some embodiments, one or more input interfaces  130  included in the vehicle  100  provide one or more instances of information to occupants of the vehicle, including indications of whether the vehicle is being navigated via autonomous driving control of the vehicle  100  by ANS  110 , whether the vehicle is being navigated to a parking position based on execution of a parking command provided to the ANS  110 , whether the vehicle is being navigated to a parking position based on implementation of a driving route, some combination thereof, etc. 
     In some embodiments, vehicle  100  comprises one or more interfaces  130  which are configured to be communicatively coupled to one or more computer systems  190  which are separate from the vehicle  100 , including one or more user devices supporting one or more users, one or more remotely located computer systems, etc. Such users can include one or more occupants of the vehicle  100 , and the one or more computer systems  190  can include one or more user devices supporting the one or more occupants and located within an interior of the vehicle  100 . In some embodiments, the ANS  110  can communicate with the one or more computer systems  190  via the one or more interfaces  130  and can access information associated with one or more particular user profiles, including face recognition data, body morphology data, door spacing preference data, driving history data, personal schedule data, etc. 
     In some embodiments, one or more instances of personal data can be accessed by ANS  110 . For example, in some embodiments, ANS  110  can process sensor data, generated by one or more sensor devices  116 , and, based on personal data including facial recognition data, associated user device detection, etc., identify a particular occupant in the vehicle interior as being associated with a particular user profile. Users can benefit from use of personal data by the ANS. For example, the personal data can be used by the ANS  110  to park the vehicle  100  in a parking position which accommodates one or more of a body morphology of an occupant, spacing preferences of the occupant, predicted occupants determined based on a personal schedule of a detected occupant, etc. 
     Users can selectively block use of, or access to, personal data. A system incorporating some or all of the technologies described herein can include hardware and/or software that prevents or blocks access to such personal data. For example, the system can allow users to “opt in” or “opt out” of participation in the collection of personal data or portions of portions thereof. Also, users can select not to provide location information, or permit provision of general location information (e.g., a geographic region or zone), but not precise location information. 
     Entities responsible for the collection, analysis, disclosure, transfer, storage, or other use of such personal data should comply with established privacy policies and/or practices. Such entities should safeguard and secure access to such personal data and ensure that others with access to the personal data also comply. Such entities should implement privacy policies and practices that meet or exceed industry or governmental requirements for maintaining the privacy and security of personal data. For example, an entity should collect users&#39; personal data for legitimate and reasonable uses, and not share or sell the data outside of those legitimate uses. Such collection should occur only after receiving the users&#39; informed consent. Furthermore, third parties can evaluate these entities to certify their adherence to established privacy policies and practices. 
     ANS  110  includes various modules  111 ,  112 ,  113  which can be implemented by one or more computer systems. ANS  110  autonomously navigates vehicle  100  along one or more driving routes, based at least in part upon sensor data generated by one or more sensor devices  116 . 
     Driving control module  112  can determine a driving route which navigates the vehicle  100  to be parked in a particular parking position in a particular parking space based at least in part upon at least some sensor data generated by one or more sensor devices  116 , including position data indicating a geographic position of the vehicle  100  and a world model, stored in one or more memory storage devices included in the vehicle  100 , one or more remotely-located systems external to the vehicle  100 , etc. Module  112  can generate a driving route based at least in part upon sensor data representations, generated by one or more sensor devices  116 , of one or more parking spaces, objects located proximate to the parking space, etc. 
     In some embodiments, the module  112  generates one or more sets of control elements commands which are communicated to one or more control elements  120  in the vehicle  100  and cause the control elements  120  to navigate the vehicle  100  along a driving route. The module  112  can generate control commands based on a driving route, where the control commands, when executed by the control elements  120 , cause the vehicle  100  to be navigated along the driving route. Navigating the vehicle  100  along a driving route can include navigating the vehicle to be parked in a particular parking position, which can include being parked in a particular orientation, within a particular parking space located in the environment. 
     ANS  110 , in some embodiments, includes an environment monitoring module  113  which is configured to monitor one or more aspects of an external environment, including one or more objects of the environment, based on processing sensor data generated by one or more sensor devices  116 . The module  113  can, based on the processing, identify various static elements and dynamic elements in the external environment, including one or more parking spaces, one or more objects located proximate to the one or more parking spaces, etc. In some embodiments, the module  113  can, based on processing a sensor data representation of a vehicle located in the environment, implement recognition of one or more features of the vehicle, including a position of one or more doors of the vehicle, a vehicle type of the vehicle, an intersection risk value associated with the vehicle, etc. The intersection risk value can be determined based on the vehicle type. Module  113  can identify a position of one or more doors, a door sweep area, volume, etc. of the vehicle, a vehicle type of the vehicle, etc. based on identifying a unique identifier of the vehicle, including information located on a license plate, data generated by a signal generator device included in the vehicle, etc. The module  113  can identify various properties of the vehicle, including the vehicle type, based on communicating with a remote computer system  190  and accessing a database where the detected unique identifier can be correlated with a profile associated with the detected vehicle, where the profile can include information indicating the vehicle type. The module  113  can determine the vehicle type, which can include manufacturer, make, model, etc. based on processing a sensor data representation of the vehicle, accessing a database which indicates door positions, door sweep area, volume, etc., intersection risk value associated with the vehicle, etc. 
     ANS  110  can include an occupant monitoring module  111  which processes sensor data representations of one or more portions of the vehicle interior and monitors occupancy of the vehicle interior. The module  111  can identify one or more occupants located in one or more particular portions of the vehicle, determine that one or more occupants are associated with one or more user profiles, associated one or more occupants with one or more body morphologies, determine one or more spacing weight values associated with the one or more occupants, etc. 
       FIG. 2  illustrates an overhead view of an environment  200  in which an ego-vehicle  210  and parking spaces  202 - 206  are located and where an ANS  211  installed in the vehicle  210  determines a particular parking position  250  in a particular available parking space  204  in which the vehicle  210  can be parked, according to some embodiments. Vehicle  210  can include any of the embodiments of vehicles included herein, and ANS  211  can include any of the embodiments of ANSs included herein. 
     In some embodiments, an ANS installed in a vehicle is configured to determine a parking position in a parking space, and park  260  the ego-vehicle in the determined parking position, based at least in part upon one or more determine geometric features of the parking space. 
     As shown, vehicle  210  is located near a set of parking spaces  202 - 206 , and sensor devices  214 A-B installed in a front portion of the vehicle  210  are monitoring  215  a particular available parking space  204 . The available parking spot is identified by the ANS  211  based on processing sensor data generated by sensors  214 A-B and determining that spaces  202  and  206  are occupied by vehicles  230 ,  240 . ANS  211  determines various geometric properties of the parking space  204 , including a centerline  205 . 
     ANS  211 , in some embodiments, is configured to select a particular parking position in which to park the ego-vehicle  210  in the available parking space  204  based on the geometric features of the parking space  204 . As shown in  FIG. 2 , the particular parking position  250  shown in  FIG. 2  is aligned on the centerline of the space  204 . 
     In some embodiments, parking a vehicle in a parking position selected based on parking space geometric features can result in a risk of collision between at least some part of the vehicle and at least some part of another object located in the environment, including another vehicle. For example, as shown in the illustrated embodiment, vehicles  230  and  240  are parked in spaces  202  and  206 , where vehicle  230  includes doors  234 A-B and vehicle  240  includes door  244 . As shown, doors  234 A-B are associated with respective door sweep volumes  236 A-B and door  244  is associated with door sweep volume  246 . While parking  260  vehicle  210  in position  250  may not result in an overlap of the door sweep volume  246  with the vehicle, based at least in part upon vehicle  240  being parked offset  243  from the centerline  241  of space  206  away from space  204 , the footprint  253  portion of the parking position  250  overlaps  237 A-B with the door sweep volumes  234 A-B, thereby posing a risk that one or more of the doors  254 A-B of vehicle  230  can collide with vehicle  210  if vehicle  210  is parked in position  250 . Furthermore, the doors  218 A-D of vehicle are associated with door sweep volumes  219 A-D which correspond to portions  254 A-D of the parking position, and the portions  254 A, C overlap  255 A-B with the vehicle  230 , thereby posing a risk that one or more of the doors  218 A, C of the ego-vehicle  210  can collide with vehicle  230  if the ego-vehicle is parked in position  250 . 
       FIG. 3A  illustrates an overhead view of an environment  300  in which an ego-vehicle  310  and parking spaces  202 - 206  are located and where an ANS  311  installed in the vehicle  310  determines a particular parking position  350  in a particular available parking space  304  in which the vehicle  310  can be parked, according to some embodiments. Vehicle  310  can include any of the embodiments of vehicles included herein, and ANS  311  can include any of the embodiments of ANSs included herein. 
     In some embodiments, an ANS installed in a vehicle is configured to determine a parking position in a parking space, and park  460  the ego-vehicle in the determined parking position, based at least in part upon a position of one or more proximate objects located adjacent to the parking space, including one or more vehicles parked in one or more adjacent parking spaces. The ANS can assign intersection risk values to one or more portions of the detected vehicles, including one or more doors sweep volumes associated with one or more doors of the vehicles, and can determine, from a set of potential parking positions in a parking space, a particular parking position which minimizes the aggregate intersection risk value associated with the parking position. The aggregate intersection risk value can be based on various factors, including a proximity of one or more objects to the parking position, including one or more door sweep volumes of the one or more objects. 
     As shown in  FIG. 3A , the ANS  311  can select a parking position  350 , which includes a portion  353  corresponding to a footprint of the vehicle  310  and a set of portions  354 A-D corresponding to door sweep volumes  319 A-D of the doors  318 A-D of the vehicle  310 , based on a determination that the parking position  350  is associated with an aggregate intersection risk value which is less than at least one other potential parking position in the parking space  204 . An aggregate intersection risk value can be determined based on separate intersection risk values associated with separate portions  353 - 354  of the position  350 , including a sum of the separate values. A separate intersection value can be determined, for a given parking position portion, based on a proportion of overlap between the parking position portion and one or more particular portions of one or more other objects in the environment, including another vehicle in the environment, a door sweep volume of another vehicle, etc. The intersection risk value can be determined based at least in part upon a proportion of the overlap of the parking position portion with the other object and one or more weight values assigned to one or more of the parking position portion and the one or more other object. 
     As shown, the selected parking position  350  in  FIG. 3A  positions the ego-vehicle  310  in an offset  351  from the centerline  205  of the parking space, such that the vehicle  310 , when parked  360  in the position  350 , is positioned sufficiently distant from vehicles  230 ,  240  that overlap between the door sweep volumes  236 A-B,  246  of the respective doors  234 A-B,  244  of the vehicles  230 ,  240  is avoided. Similarly, the portions  354 A-D of the parking position  350  corresponding to the door sweep volumes  319 A-D of the doors  318 A-D of vehicle  310  do not overlap with any portion of vehicles  230 ,  240 , so that intersection between any portion of the vehicle  310  and vehicles  230 ,  240  is avoided when vehicle  310  is parked in position  350 . As a result, intersection risk values associated with the various portions  353 ,  354  of the position  350  can be null values, minimal values, etc. base on the absence of overlap. Because the aggregate intersection risk value associated with position  350  can be less than an aggregate intersection risk value associated with another potential parking position, including the parking position  250  illustrated in  FIG. 2  which includes overlap between portions of position  250  and portions of vehicle  230 , including the door sweep volumes  234 A-B of vehicle  230 , the ANS  311  can select position  350  instead of position  250  and can park  360  the vehicle  310  in position  350  in parking space  204 . 
       FIG. 3B  illustrates an overhead view of an environment  200  in which an ego-vehicle  310  and parking spaces  202 - 206  are located and where an ANS  311  installed in the vehicle  310  determines a particular parking position  350  in a particular available parking space  304  in which the vehicle  310  can be parked, according to some embodiments. Vehicle  310  can include any of the embodiments of vehicles included herein, and ANS  311  can include any of the embodiments of ANSs included herein. 
     In some embodiments, ANS  311  selects a particular parking position  350  which results in the vehicle  310  being positioned in parking space  204  such that the door sweep volume of one or more doors of one or more of the ego-vehicle  310  and an adjacent vehicle  230  overlap with one or more of the ego-vehicle  310  and the vehicle  230 , based on an intersection risk value assigned to one or more portions of the vehicle  230  being less than another intersection risk value assigned to one or more portions of another adjacent vehicle  240 . For example, ANS  211  may determine that a parking position  350  which results in vehicle  310  being positioned in an offset  351  from the centerline  205  away from the vehicle  240  results in a minimum aggregate intersection risk value, even though the door sweep volumes  236 A-B of vehicle  230  overlap  339 A-B with the vehicle  310  in the position  350 , based at least in part upon the vehicle  230  being associated with a reduced intersection risk value, relative to the vehicle  240 . The aggregate intersection risk value for position  350  can be based at least in part on an intersection risk value assigned to vehicle  240  and a proximity  349  of the position  350  to the vehicle  240 . The ANS  211  can determine an intersection risk value for one or more of the vehicles  230 ,  240  based at least in part upon determining a vehicle type of the one or more vehicles. In some embodiments, the parking position may be restricted to being at least a certain minimum spacing distance from a proximate environmental element, including a proximate parked vehicle. For example, ANS  311  can determine a position  350  which is associated with a minimum aggregate intersection risk value which also includes the position being spaced at least a minimum spacing distance from both vehicles  230 ,  240 , and cause vehicle  310  to be parked in the position  350 . As a result, the ANS  311  selects a parking position  350  which is spaced sufficiently distant from vehicles  230 ,  240  to provide at least a minimum protection against collision between two or more of vehicles  310 ,  230 ,  240 . Where the position  350  which is associated with a minimum intersection risk value and which is spaced at least the minimum spacing distance from both vehicle  230 ,  340  is associated with an intersection risk value which at least meets a threshold intersection risk value, the ANS  311  can refrain from parking the vehicle  310  in the space  204  and can cause the vehicle to navigate through the environment to locate another available parking space. 
       FIG. 3C  illustrates parking an ego-vehicle in a particular parking position in an identified available parking space, according to some embodiments. The parking can be implemented by one or more portions of any embodiment of ANS included in any embodiments herein. An ANS can be implemented by one or more computer systems. 
     At  372 , a parking command is received. The parking command can be received based on one or more of occupant interaction with one or more user interfaces included in one or more of the ego-vehicle, user interaction with one or more user interfaces included in a user device communicatively coupled to the ANS, navigation of the ego-vehicle along one or more portions of a driving route, etc. 
     At  374  and  376 , sensor data representations of one or more portions of the environment are processed and an unoccupied parking space, also referred to herein as an available parking space, is detected in the environment. Detection of an available parking space can also be referred to as identifying an available parking space. 
     At  380 , one or more objects located proximate to the available parking space are identified. Such object can include one or more vehicles located adjacent to the available parking space. Identifying a vehicle in the environment can include processing a sensor data representation of the vehicle, implementing recognition of one or more features of the vehicle, including a position of one or more doors of the vehicle, a vehicle type of the vehicle, an intersection risk value associated with the vehicle, etc. The intersection risk value can be determined based on the vehicle type. The identifying at  380  can include identifying a position of one or more doors, a door sweep area, volume, etc. of the vehicle, a vehicle type of the vehicle, etc. based on identifying a unique identifier of the vehicle, including information located on a license plate, data generated by a signal generator device included in the vehicle, etc. The identifying at  380  can include identifying various properties of the vehicle, including the vehicle type, based on communicating with a remote computer system and accessing a database where the detected unique identifier can be correlated with a profile associated with the detected vehicle, where the profile can include information indicating the vehicle type. The identifying at  380  can include determine the vehicle type of a vehicle identified adjacent to the available parking space, which can include manufacturer, make, model, etc. based on processing a sensor data representation of the vehicle, accessing a database which indicates door positions, door sweep area, volume, etc., intersection risk value associated with the vehicle, etc. 
     At  382 , a door sweep volume of one or more doors of a detected adjacent vehicle is determined and associated with the one or more doors. The determining can be based on identifying the vehicle at  380 . Associating the door sweep volume with the one or more doors can be based on determining a relative position of the one or more doors on the vehicle detected in the environment, based at least in part upon the identifying at  380 . 
     At  384 , an intersection weight value is assigned to one or more portions of the adjacent vehicle. The one or more portions can include a door sweep volume of one or more of the doors of the vehicle. The intersection weight value can be determined based on identifying the vehicle at  380  and can be based at least in part upon the vehicle type. 
     At  386 , a particular parking position of the ego-vehicle in the available parking space is determined. The parking position can be selected from a set of potential parking positions in the parking space. For each potential parking position of the set, an aggregate intersection risk value is determined, and the particular parking position which is selected is a potential parking position, of the set, which is associated with a minimum aggregate intersection risk value. The aggregate intersection risk value is determined based on a plurality of intersection risk values associated with separate portions of the potential parking position, where separate intersection risk values are determined for separate door sweep volumes included in the parking position, the vehicle volume included in the parking position, etc. In some embodiments, the aggregate intersection risk value is determined based on one or more intersection risk values associated with one or more separate portions, door sweep volumes, etc. of the one or more adjacent vehicles identified in the environment. For each portion of the potential parking position, portion of an adjacent vehicle, door sweep volume of an adjacent vehicle, a separate intersection risk value is determined based at least in part on a proportion of the portion, door sweep volume, etc. which overlaps one or more objects in the environment, including one or more structures, vehicles, etc. 
     At  388 , the ego-vehicle is caused to be parked in the selected particular parking position in the available parking space. Such causation can include generating a set of control commands which, when communicated to one or more control elements included in the ego-vehicle, are executed by the one or more control elements can cause the ego-vehicle to be navigated along a driving route which causes the vehicle to be parked in the particular parking position in the identified available parking space. 
     Where each of the potential parking positions in the set of potential parking positions is associated with an aggregate intersection risk value which at least meets a threshold intersection risk value, parking at the identified available parking space is aborted, and the vehicle can be commanded to be navigated along a driving route which enables additional portions of the environment to be monitored for one or more additional available parking spaces. Elements  374 - 388  can be implemented repeatedly until a at least one parking position in an available parking space is associated with an aggregate intersection risk value which is less than the threshold intersection risk value. 
       FIG. 4A  illustrates an overhead view of an environment  400  in which an ego-vehicle  410  and parking spaces  402 - 404  are located and where an ANS  411  installed in the vehicle  410  determines a particular parking position  450  in a particular available parking space  404  in which the vehicle  410  can be parked, according to some embodiments. Vehicle  410  can include any of the embodiments of vehicles included herein, and ANS  411  can include any of the embodiments of ANSs included herein. 
     In some embodiments, an ANS installed in a vehicle is configured to determine a parking position in a parking space, and park  460  the ego-vehicle in the determined parking position, based at least in part upon a body morphology of the occupants of the interior of the ego-vehicle. The ANS can select a parking position in the parking space which accommodates spacing needs of occupants of the vehicle based at least in part upon positioning the vehicle to provide sufficient space for one or more vehicle doors associated with portions of the vehicle interior predicted to be occupied by the occupants. The spacing needs of an occupant can be determined based at least in part upon a body morphology of the occupant. For example, an occupant associated with an elderly body morphology may require more space to exit the vehicle than an occupant associated with an adult body morphology, and the ANS can park the vehicle in a parking position which is selected to account for occupant body morphology. 
     As shown, vehicle  410  is located near a set of parking spaces  402 - 404 , and sensor devices  414 A-B installed in a rear portion of the vehicle  410  are monitoring  415  a particular available parking space  404 . ANS  411  determines various geometric properties of the parking space  404 , including a centerline  405 . ANS  411  can further determine that a side of the parking space  404  is bounded by a wall structure  406 . 
     ANS  411 , in some embodiments, is configured to select a particular parking position in which to park the ego-vehicle  410  in the parking space  404 . The particular parking position  450  shown in  FIG. 4  is offset  451  from the centerline of the space  404  and is oriented  452  away from an exit of the space  404 , so that parking  460  the ego-vehicle  410  in the position  450  includes orienting the ego-vehicle  410  so that the front end  412  of the ego-vehicle aligns with the orientation  452  of the position  450 . 
     In some embodiments, ANS  411  is configured to select a particular parking position  450  based on an occupancy of the vehicle  410 . The vehicle can determine a present occupancy of the vehicle, which can include determining that one or more occupants associated with one or more particular properties are occupying one or more particular portions of the vehicle interior, based on processing sensor data generate by one or more sensor devices included in the vehicle. The ANS can associate one or more occupants with one or more body morphologies based on monitoring the one or more occupants via processing sensor data. 
     As shown, vehicle  410  includes interior  416  which comprises separate particular portions  416 A-D, where each separate portion  416  is associated with a particular door  418  of the vehicle  410  and where each door  418 A-D is associated with a separate door sweep volume  419 A-D. Vehicle  410  includes a present occupant  417 A located in portion  416 A of the vehicle interior. The ANS  411  can associate the occupant  417  with a user profile based on sensor data representations of the occupant, generated by one or more sensor devices in the vehicle, sensor data representation data associated with the user profile, etc. In some embodiments, the ANS  411  can associate a particular one or more body morphologies with the occupant  417 A based on monitoring the occupant  417 A. In some embodiments, the ANS  411  is configured for associate one or more body morphologies with the occupant  417 A based on monitoring the occupant prior to the occupant entering the vehicle interior. For example, the ANS  411  can monitor the occupant as the occupant approaches the vehicle and can associate the occupant with a body morphology based on the monitoring. 
     As shown, the parking position  450  includes a portion  453  which correlates to a footprint of the vehicle  410  and portions  454 A-D which correlate to the door sweep volumes  419 A-D of the doors  418 A-D of the vehicle. Based on the occupant  417 A of the vehicle  410 , ANS  411  can associate, assign, etc. a particular spacing weight value with a particular door sweep volume  419 A of a door  418 A associated with the particular portion  416 A of the interior which the occupant  417 A occupies. The spacing weight value assigned to volume  419 A can be associated with one or more parameters of the occupant  417 A, including a body morphology of the occupant  417 A, a user profile of the occupant  417 A, some combination thereof, etc. 
     ANS  411  can determine an aggregate intersection risk value for the position  450  based on determining separate intersection risk values for the separate portions  453 ,  454 A-D of the position  450 . The aggregate intersection risk value can be a sum of the separate intersection risk values. Each separate intersection risk calculated for a separate portion  453 - 454  can be based on a spacing weight value assigned to the portion and a proportion of the portion which overlaps with one or more particular portions of the environment, including a portion of the environment which is external to the parking space  404 , an object located proximate to the parking space  404 , etc. For example, an intersection risk value calculated for portion  454 A can be a product of the spacing weight value assigned to volume  419 A and the proportion of overlap  456  of the portion  454 A with the wall structure  406  bounding the space. 
     As shown, the particular position  450  is positioned, offset  451  from the centerline  405  of the space, so that the portion  454 A corresponding to door volume  419 A projects into space  402  and is distal from wall  406 , relative to the footprint  453  portion. As a result, the intersection risk value computed for portion  454 A can be relatively low, as the portion  454 A does not overlap any objects in the environment. While portions  454 B-D overlap  456  wall  406 , the spacing weight value assigned to the portions  454 B-D can be less than the value assigned to portion  454 A, a null value, etc., as neither door  418 B-D corresponding to portions  454 B-D is associated with an occupied interior portion. As a result, the aggregate intersection risk value computed for position  450  can be less than other potential parking positions in the space  404 . 
       FIG. 4B  illustrates an overhead view of an environment  400  in which an ego-vehicle  410  and parking spaces  402 - 404  are located and where an ANS  411  installed in the vehicle  410  determines a particular parking position  450  in a particular available parking space  404  in which the vehicle  410  can be parked, according to some embodiments. Vehicle  410  can include any of the embodiments of vehicles included herein, and ANS  411  can include any of the embodiments of ANSs included herein. 
     In some embodiments, the ANS  411  is configured to select a parking position which is associated with a minimal aggregate intersection risk value, even though such a position can result in at least partial obstruction of door sweep volume for one or more occupants. For example, as shown in  FIG. 4B , where vehicle  410  includes occupants  417 A-B, D in vehicle interior portions  416 A-B, D, spacing weight values can be assigned to portions  454 A-B, D based on the body morphologies of the occupants. Where the body morphologies of occupants  417 B-D result in a greater spacing weight value being assigned to portions  454 B-D than portion  454 A, an aggregate intersection risk value determined for position  450  can be minimized where the position  450  is positioned and oriented in space  404  so that the proportion of overlap of portions  454 B-D is minimized, although at the expense of overlap  456  of portion  454 A. 
       FIG. 4C  illustrates parking an ego-vehicle in a particular parking position in an identified available parking space, according to some embodiments. The parking can be implemented by one or more portions of any embodiment of ANS included in any embodiments herein. An ANS can be implemented by one or more computer systems. 
     At  470 , an individual is detected approaching the ego-vehicle, based on processing sensor data generated by one or more sensor devices. At  472 , a particular body morphology is associated with the individual based on monitoring the individual. The association can be based on associating the individual with a particular user profile, based on facial recognition, monitoring body motions of the individual approaching the vehicle, identifying one or more mobility aids, including a wheelchair, cane, crutch, etc. being utilized by the individual, etc. 
     At  474 , subsequent to the individual occupying a particular portion of the vehicle interior, the particular portion is identified and associated with the occupant. At  476 , a spacing weight value associated with the occupant is assigned to a door sweep volume of a door associated with the interior portion. The value can be determined based on the occupant morphology. 
     At  478 , a parking command is received. The parking command can be received based on one or more of occupant interaction with one or more user interfaces included in one or more of the ego-vehicle, user interaction with one or more user interfaces included in a user device communicatively coupled to the ANS, navigation of the ego-vehicle along one or more portions of a driving route, etc. 
     At  480 , sensor data representations of one or more portions of the environment are processed and an unoccupied parking space, also referred to herein as an available parking space, is detected in the environment. 
     At  482 , one or more objects located proximate to the available parking space are identified. Such object can include one or more vehicles located adjacent to the available parking space, one or more objects which define one or more boundaries of the available parking space, including one or more wall structures, curb structures, etc. 
     At  484 , a particular parking position of the ego-vehicle in the available parking space is determined. The parking position can be selected from a set of potential parking positions in the parking space. For each potential parking position of the set, an aggregate intersection risk value is determined, and the particular parking position which is selected is a potential parking position, of the set, which is associated with a minimum aggregate intersection risk value. The aggregate intersection risk value is determined based on a plurality of intersection risk values associated with separate portions of the potential parking position, where separate intersection risk values are determined for separate door sweep volumes included in the parking position, the vehicle volume included in the parking position, etc. For each portion of the potential parking position, a separate intersection risk value is determined based at least in part on a proportion of the portion which overlaps one or more objects in the environment, including one or more structures, vehicles, etc. Where the portion of the potential parking position comprises a door sweep volume of a door included in the ego-vehicle, a separate intersection risk value is determined for the door sweep volume based at least in part upon a proportion of the portion which overlaps one or more objects in the environment and a space weight value assigned to the door sweep volume. 
     At  486 , the ego-vehicle is caused to be parked in the selected particular parking position in the available parking space. Such causation can include generating a set of control commands which, when communicated to one or more control elements included in the ego-vehicle, are executed by the one or more control elements can cause the ego-vehicle to be navigated along a driving route which causes the vehicle to be parked in the particular parking position in the identified available parking space. 
     Where each of the potential parking positions in the set of potential parking positions is associated with an aggregate intersection risk value which at least meets a threshold intersection risk value, parking at the identified available parking space is aborted, and the vehicle can be commanded to be navigated along a driving route which enables additional portions of the environment to be monitored for one or more additional available parking spaces. Elements  474 - 484  can be implemented repeatedly until a at least one parking position in an available parking space is associated with an aggregate intersection risk value which is less than the threshold intersection risk value. 
       FIG. 5A  illustrates an overhead view of an environment  500  in which an ego-vehicle  510  and parking spaces  502 - 504  are located and where an ANS  511  installed in the vehicle  510  determines a particular parking position  550  in a particular available parking space  504  in which the vehicle  510  can be parked, according to some embodiments. Vehicle  510  can include any of the embodiments of vehicles included herein, and ANS  511  can include any of the embodiments of ANSs included herein. 
     In some embodiments, an ANS installed in a vehicle is configured to determine a parking position in a parking space, and park the ego-vehicle in the determined parking position, based at least in part upon predicted occupancy of the interior of the ego-vehicle. Where the vehicle is predicted to receive one or more additional occupants prior to the vehicle leaving the parking space, the ANS can select a parking position in the parking space which accommodates the predicted occupants based at least in part upon positioning the vehicle to provide sufficient space for one or more vehicle doors associated with portions of the vehicle interior predicted to be occupied by the predicted occupants. 
     As shown, vehicle  510  is located near a set of parking spaces  502 - 504 , and sensor devices  514 A-B installed in a rear portion of the vehicle  510  are monitoring  515  a particular available parking space  504 . ANS  511  determines various geometric properties of the parking space  504 , including a centerline  505 . ANS  511  can further determine that a side of the parking space  504  is bounded by a wall structure  506 . 
     ANS  511 , in some embodiments, is configured to select a particular parking position in which to park the ego-vehicle  510  in the parking space  504 . The particular parking position  550  shown in  FIG. 5  is offset  551  from the centerline of the space  504  and is oriented  552  towards an exit of the space  504 , so that parking the ego-vehicle  510  in the position  550  includes orienting the ego-vehicle  510  so that the front end  512  of the ego-vehicle aligns with the orientation  552  of the position  550 . 
     In some embodiments, ANS  511  is configured to select a particular parking position  550  based on a predicted occupancy of the vehicle  510  at a future time prior to the vehicle leaving the parking space  504 . The vehicle can predict a particular occupancy, which can include predicting that a certain set of one or more occupants associated with one or more particular properties will occupy one or more particular portions of the vehicle interior, based on one or more of a present occupancy of the vehicle, a present location of the vehicle, a present time, some combination thereof, etc. For example, the ANS can access a historical record of occupant additions to the vehicle interior which associates the additions with one or more of a date, time of day, day of the week, location, present occupant prior to the occupant addition, etc. The historical record can include information associated with a user profile of a present occupant, including a personal schedule. 
     As shown, vehicle  510  includes interior  516  which comprises separate particular portions  516 A-D, where each separate portion  516  is associated with a particular door  518  of the vehicle  510  and where each door  518 A-D is associated with a separate door sweep volume  519 A-D. Vehicle  510  includes a present occupant  517 A located in portion  516 A of the vehicle interior. The ANS  511  can associate the occupant  517  with a user profile based on sensor data representations of the occupant, generated by one or more sensor devices in the vehicle, sensor data representation data associated with the user profile, etc. The ANS  511  can determine, based on one or more parameters, that a predicted occupancy of the vehicle  510  includes an occupant  517 D in portion  516 D of the vehicle interior  516 D. In some embodiments, the ANS  511  determines that the predicted occupant  517 D is associated with one or more particular body morphologies, door spacing preferences, user profiles, etc. The determination can be based on a historical record of occupant additions, where the record includes a historical record of body morphologies of occupants entering the vehicle at one or more various times, locations, etc. In some embodiments, the determination can be based on a determination that a probability that the one or more occupants will enter one or more particular portions of the vehicle interior at the parking space, prior to the vehicle leaving the parking space at a future time, etc. at least meets a probability threshold value. In some embodiments, the determination can be based on a determination that a probability that the one or more occupants will board one or more particular portions of the vehicle interior at the present local time at least meets a probability threshold value, based on at least one historical record of vehicle occupant additions associated with the present local time. 
     As shown, the parking position  550  includes a portion  553  which correlates to a footprint of the vehicle  510  and portions  554 A-D which correlate to the door sweep volumes  519 A-D of the doors  518 A-D of the vehicle. Based on the predicted occupant  517 D of the vehicle  510  prior to the vehicle leaving the parking space  504 , ANS  511  can associate, assign, etc. a particular spacing weight value with a particular door sweep volume  519 D of a door  518 D associated with the particular portion  516 D of the interior in which the occupant  517 D is predicted to occupy. The spacing weight value assigned to volume  519 D can be associated with one or more parameters of the occupant  517 D, including a body morphology of the predicted occupant  517 D, a user profile of the occupant  517 D, some combination thereof, etc. Similarly, a spacing weight value associated with occupant  517 A can be assigned to volume  519 A and thus the portion  554 A of the parking position  550  which corresponds to volume  519 A. 
     ANS  511  can determine an aggregate intersection risk value for the position  550  based on determining separate intersection risk values for the separate portions  553 ,  554 A-D of the position  550 . The aggregate intersection risk value can be a sum of the separate intersection risk values. Each separate intersection risk calculated for a separate portion  553 - 554  can be based on a spacing weight value assigned to the portion and a proportion of the portion which overlaps with one or more particular portions of the environment, including a portion of the environment which is external to the parking space  504 , an object located proximate to the parking space  504 , etc. For example, an intersection risk value calculated for portion  554 A can be a product of the spacing weight value assigned to volume  519 A and the proportion of overlap  556  of the portion  554 A with the wall structure  506  bounding the space. 
     As shown, the particular position  550  is oriented so that the portion  554 D corresponding to door volume  519 D projects into space  502  and is distal from wall  506 , relative to the footprint  553  portion. As a result, parking vehicle  510  in the position  550  results in door  518 D facing into space  502 . The position  550  can be selected based on a determination that the predicted morphology of occupant  517  requires more space to enter the vehicle, and thus is associated with a greater spacing weight value, than occupant  517 A. As a result, the selected position  553  enables the ego-vehicle  510  to be positioned to optimize available space for the predicted occupant  517 D to enter portion  516 D of the vehicle interior  516 , relative to occupant  517 A. The position  550  can be selected from a set of potential parking positions, where the aggregate intersection risk value of position  550  is less than the aggregate intersection risk values of other potential parking positions, which may receive higher intersection risk values as a result of including greater overlap of portion  554 D with other elements of the environment, including wall  506 . Based on selection of position  550 , the ANS  551  can navigate  560  the vehicle  510  to be parked in position  550  of space  504 . 
       FIG. 5B  illustrates parking an ego-vehicle in a particular parking position in an identified available parking space, according to some embodiments. The parking can be implemented by one or more portions of any embodiment of ANS included in any embodiments herein. An ANS can be implemented by one or more computer systems. 
     At  570 , a parking command is received. The parking command can be received based on one or more of occupant interaction with one or more user interfaces included in one or more of the ego-vehicle, user interaction with one or more user interfaces included in a user device communicatively coupled to the ANS, navigation of the ego-vehicle along one or more portions of a driving route, etc. 
     At  572  and  574 , sensor data representations of one or more portions of the environment are processed and an unoccupied parking space, also referred to herein as an available parking space, is detected in the environment. 
     At  576 , one or more objects located proximate to the available parking space are identified. Such object can include one or more vehicles located adjacent to the available parking space, one or more objects which define one or more boundaries of the available parking space, including one or more wall structures, curb structures, etc. 
     At  578 , a predicted occupancy of one or more positions of the vehicle interior is determined. Predicted occupancy can comprise a predicted occupancy of the vehicle at a future point in time at which the vehicle is navigated away from the parking space. Predicted occupancy can include predicted occupants in one or more particular portions of the vehicle interior, body morphology associated with one or more of the predicted occupants, user profiles associated with one or more of the predicted occupants, door spacing preferences associated with one or more of the predicted occupants, some combination thereof, etc. 
     At  580 , a separate spacing weight is assigned to a door sweep volume associated with each separate door of the vehicle. Each door can be associated with a particular portion of the vehicle interior, and a particular spacing weight can be assigned to a door sweep volume of a given door based on one or more properties of a predicted occupant of the particular portion of the vehicle interior associated with the given door, including one or more of body morphology, associated user profile, door spacing preference, etc. Where an occupant is detected as presently occupying a particular portion of the vehicle interior, a particular spacing weight value can be assigned to a door sweep volume of a door associated with the particular portion, based on one or more properties associated with the detected occupant. 
     At  582 , a particular parking position of the ego-vehicle in the available parking space is determined. The parking position can be selected from a set of potential parking positions in the parking space. For each potential parking position of the set, an aggregate intersection risk value is determined, and the particular parking position which is selected is a potential parking position, of the set, which is associated with a minimum aggregate intersection risk value. The aggregate intersection risk value is determined based on a plurality of intersection risk values associated with separate portions of the potential parking position, where separate intersection risk values are determined for separate door sweep volumes included in the parking position, the vehicle volume included in the parking position, etc. For each portion of the potential parking position, a separate intersection risk value is determined based at least in part on a proportion of the portion which overlaps one or more objects in the environment, including one or more structures, vehicles, etc. Where the portion of the potential parking position comprises a door sweep volume of a door included in the ego-vehicle, a separate intersection risk value is determined for the door sweep volume based at least in part upon a proportion of the portion which overlaps one or more objects in the environment and a space weight value assigned to the door sweep volume. 
     At  584 , the ego-vehicle is caused to be parked in the selected particular parking position in the available parking space. Such causation can include generating a set of control commands which, when communicated to one or more control elements included in the ego-vehicle, are executed by the one or more control elements can cause the ego-vehicle to be navigated along a driving route which causes the vehicle to be parked in the particular parking position in the identified available parking space. 
     Where each of the potential parking positions in the set of potential parking positions is associated with an aggregate intersection risk value which at least meets a threshold intersection risk value, parking at the identified available parking space is aborted, and the vehicle can be commanded to be navigated along a driving route which enables additional portions of the environment to be monitored for one or more additional available parking spaces. Elements  574 - 584  can be implemented repeatedly until a at least one parking position in an available parking space is associated with an aggregate intersection risk value which is less than the threshold intersection risk value. 
       FIG. 6  illustrates an example computer system  600  that may be configured to include or execute any or all of the embodiments described above. In different embodiments, computer system  600  may be any of various types of devices, including, but not limited to, a personal computer system, desktop computer, laptop, notebook, tablet, slate, pad, or netbook computer, cell phone, smartphone, PDA, portable media device, mainframe computer system, handheld computer, workstation, network computer, a camera or video camera, a set top box, a mobile device, a consumer device, video game console, handheld video game device, application server, storage device, a television, a video recording device, a peripheral device such as a switch, modem, router, or in general any type of computing or electronic device. 
     Various embodiments of an autonomous navigation system (ANS), as described herein, may be executed in one or more computer systems  600 , which may interact with various other devices. Note that any component, action, or functionality described above with respect to  FIGS. 1 through 5  may be implemented on one or more computers configured as computer system  600  of  FIG. 6 , according to various embodiments. In the illustrated embodiment, computer system  600  includes one or more processors  610  coupled to a system memory  620  via an input/output (I/O) interface  630 . Computer system  600  further includes a network interface  640  coupled to I/O interface  630 , and one or more input/output devices, which can include one or more user interface (also referred to as “input interface”) devices. In some cases, it is contemplated that embodiments may be implemented using a single instance of computer system  600 , while in other embodiments multiple such systems, or multiple nodes making up computer system  600 , may be configured to host different portions or instances of embodiments. For example, in one embodiment some elements may be implemented via one or more nodes of computer system  600  that are distinct from those nodes implementing other elements. 
     In various embodiments, computer system  600  may be a uniprocessor system including one processor  610 , or a multiprocessor system including several processors  610  (e.g., two, four, eight, or another suitable number). Processors  610  may be any suitable processor capable of executing instructions. For example, in various embodiments processors  610  may be general-purpose or embedded processors implementing any of a variety of instruction set architectures (ISAs), such as the x86, PowerPC, SPARC, or MIPS ISAs, or any other suitable ISA. In multiprocessor systems, each of processors  610  may commonly, but not necessarily, implement the same ISA. 
     System memory  620  may be configured to store program instructions, data, etc. accessible by processor  610 . In various embodiments, system memory  620  may be implemented using any suitable memory technology, such as static random access memory (SRAM), synchronous dynamic RAM (SDRAM), nonvolatile/Flash-type memory, or any other type of memory. In the illustrated embodiment, program instructions included in memory  620  may be configured to implement some or all of an ANS, incorporating any of the functionality described above. Additionally, existing control data of memory  620  may include any of the information or data structures described above. In some embodiments, program instructions and/or data may be received, sent or stored upon different types of computer-accessible media or on similar media separate from system memory  620  or computer system  600 . While computer system  600  is described as implementing the functionality of functional blocks of previous Figures, any of the functionality described herein may be implemented via such a computer system. 
     In one embodiment, I/O interface  630  may be configured to coordinate I/O traffic between processor  610 , system memory  620 , and any peripheral devices in the device, including network interface  640  or other peripheral interfaces, such as input/output devices  650 . In some embodiments, I/O interface  630  may perform any necessary protocol, timing or other data transformations to convert data signals from one component (e.g., system memory  620 ) into a format suitable for use by another component (e.g., processor  610 ). In some embodiments, I/O interface  630  may include support for devices attached through various types of peripheral buses, such as a variant of the Peripheral Component Interconnect (PCI) bus standard or the Universal Serial Bus (USB) standard, for example. In some embodiments, the function of I/O interface  630  may be split into two or more separate components, such as a north bridge and a south bridge, for example. Also, in some embodiments some or all of the functionality of I/O interface  630 , such as an interface to system memory  620 , may be incorporated directly into processor  610 . 
     Network interface  640  may be configured to allow data to be exchanged between computer system  600  and other devices attached to a network  685  (e.g., carrier or agent devices) or between nodes of computer system  600 . Network  685  may in various embodiments include one or more networks including but not limited to Local Area Networks (LANs) (e.g., an Ethernet or corporate network), Wide Area Networks (WANs) (e.g., the Internet), wireless data networks, some other electronic data network, or some combination thereof. In various embodiments, network interface  640  may support communication via wired or wireless general data networks, such as any suitable type of Ethernet network, for example; via telecommunications/telephony networks such as analog voice networks or digital fiber communications networks; via storage area networks such as Fibre Channel SANs, or via any other suitable type of network and/or protocol. 
     Input/output devices may, in some embodiments, include one or more display terminals, keyboards, keypads, touchpads, scanning devices, voice or optical recognition devices, or any other devices suitable for entering or accessing data by one or more computer systems  600 . Multiple input/output devices may be present in computer system  600  or may be distributed on various nodes of computer system  600 . In some embodiments, similar input/output devices may be separate from computer system  600  and may interact with one or more nodes of computer system  600  through a wired or wireless connection, such as over network interface  640 . 
     Memory  620  may include program instructions, which may be processor-executable to implement any element or action described above. In one embodiment, the program instructions may implement the methods described above. In other embodiments, different elements and data may be included. Note that data may include any data or information described above. 
     Those skilled in the art will appreciate that computer system  600  is merely illustrative and is not intended to limit the scope of embodiments. In particular, the computer system and devices may include any combination of hardware or software that can perform the indicated functions, including computers, network devices, Internet appliances, PDAs, wireless phones, pagers, etc. Computer system  600  may also be connected to other devices that are not illustrated, or instead may operate as a stand-alone system. In addition, the functionality provided by the illustrated components may in some embodiments be combined in fewer components or distributed in additional components. Similarly, in some embodiments, the functionality of some of the illustrated components may not be provided and/or other additional functionality may be available. 
     Those skilled in the art will also appreciate that, while various items are illustrated as being stored in memory or on storage while being used, these items or portions of them may be transferred between memory and other storage devices for purposes of memory management and data integrity. Alternatively, in other embodiments some or all of the software components may execute in memory on another device and communicate with the illustrated computer system via inter-computer communication. Some or all of the system components or data structures may also be stored (e.g., as instructions or structured data) on a computer-accessible medium or a portable article to be read by an appropriate drive, various examples of which are described above. In some embodiments, instructions stored on a computer-accessible medium separate from computer system  600  may be transmitted to computer system  600  via transmission media or signals such as electrical, electromagnetic, or digital signals, conveyed via a communication medium such as a network and/or a wireless link. Various embodiments may further include receiving, sending or storing instructions and/or data implemented in accordance with the foregoing description upon a computer-accessible medium. Generally speaking, a computer-accessible medium may include a non-transitory, computer-readable storage medium or memory medium such as magnetic or optical media, e.g., disk or DVD/CD-ROM, volatile or non-volatile media such as RAM (e.g. SDRAM, DDR, RDRAM, SRAM, etc.), ROM, etc. In some embodiments, a computer-accessible medium may include transmission media or signals such as electrical, electromagnetic, or digital signals, conveyed via a communication medium such as network and/or a wireless link. 
     The methods described herein may be implemented in software, hardware, or a combination thereof, in different embodiments. In addition, the order of the blocks of the methods may be changed, and various elements may be added, reordered, combined, omitted, modified, etc. Various modifications and changes may be made as would be obvious to a person skilled in the art having the benefit of this disclosure. The various embodiments described herein are meant to be illustrative and not limiting. Many variations, modifications, additions, and improvements are possible. Accordingly, plural instances may be provided for components described herein as a single instance. Boundaries between various components, operations and data stores are somewhat arbitrary, and particular operations are illustrated in the context of specific illustrative configurations. Other allocations of functionality are envisioned and may fall within the scope of claims that follow. Finally, structures and functionality presented as discrete components in the example configurations may be implemented as a combined structure or component. These and other variations, modifications, additions, and improvements may fall within the scope of embodiments as defined in the claims that follow.

Metadata:
Filing Date: 20160923
Publication Date: 20200310
Grant Date: 20200310
Priority Date: 20150925
Inventors: HAN, BYRON B.
GOLKO, ALBERT J.
ZADESKY, STEPHEN P.
Assignee: APPLE INC
CPC Classifications: [{"code": "F16H63/48", "inventive": true, "first": false, "tree": "[]"}, {"code": "B60T2201/10", "inventive": false, "first": false, "tree": "[]"}, {"code": "B60T7/22", "inventive": true, "first": false, "tree": "[]"}, {"code": "B62D15/0285", "inventive": true, "first": true, "tree": "[]"}, {"code": "G05D1/021", "inventive": true, "first": false, "tree": "[]"}, {"code": "G08G1/141", "inventive": true, "first": false, "tree": "[]"}, {"code": "B60W10/18", "inventive": false, "first": false, "tree": "[]"}, {"code": "B60W30/06", "inventive": true, "first": true, "tree": "[]"}, {"code": "G05B15/02", "inventive": false, "first": false, "tree": "[]"}, {"code": "G05D1/0297", "inventive": false, "first": false, "tree": "[]"}, {"code": "B62D15/0285", "inventive": false, "first": false, "tree": "[]"}, {"code": "E05B47/00", "inventive": false, "first": false, "tree": "[]"}, {"code": "B60W10/20", "inventive": false, "first": false, "tree": "[]"}, {"code": "B62D6/00", "inventive": false, "first": false, "tree": "[]"}, {"code": "B60W40/12", "inventive": true, "first": false, "tree": "[]"}, {"code": "B60T7/22", "inventive": false, "first": false, "tree": "[]"}, {"code": "E04H6/422", "inventive": false, "first": false, "tree": "[]"}, {"code": "F16H63/483", "inventive": false, "first": false, "tree": "[]"}, {"code": "G05B15/02", "inventive": false, "first": false, "tree": "[]"}, {"code": "B62D6/00", "inventive": false, "first": false, "tree": "[]"}, {"code": "E04H6/422", "inventive": false, "first": false, "tree": "[]"}, {"code": "G05D1/0297", "inventive": false, "first": false, "tree": "[]"}, {"code": "E05B47/00", "inventive": false, "first": false, "tree": "[]"}, {"code": "G05D1/021", "inventive": true, "first": false, "tree": "[]"}, {"code": "B60W10/18", "inventive": false, "first": false, "tree": "[]"}, {"code": "B60T7/22", "inventive": false, "first": false, "tree": "[]"}, {"code": "G08G1/141", "inventive": true, "first": false, "tree": "[]"}, {"code": "F16H63/483", "inventive": false, "first": false, "tree": "[]"}, {"code": "B60W30/06", "inventive": true, "first": true, "tree": "[]"}, {"code": "B60W10/20", "inventive": false, "first": false, "tree": "[]"}, {"code": "B62D15/0285", "inventive": false, "first": false, "tree": "[]"}, {"code": "B60W40/12", "inventive": true, "first": false, "tree": "[]"}, {"code": "G08G1/168", "inventive": true, "first": false, "tree": "[]"}, {"code": "E04H6/422", "inventive": false, "first": false, "tree": "[]"}]
Family ID: 69723642