Mobile device tethering for remote parking assist

Information

  • Patent Grant
  • 10747218
  • Patent Number
    10,747,218
  • Date Filed
    Friday, January 12, 2018
    7 years ago
  • Date Issued
    Tuesday, August 18, 2020
    4 years ago
Abstract
Method and apparatus are disclosed for mobile device tethering for remote parking assist. An example vehicle includes ultra-wide angle cameras and a processor coupled to memory. The processor generates an interface based on a location of the mobile device including an overhead representation of the vehicle generated using images from the cameras and representations of a position of a mobile device and a boundary around the vehicle. The processor also sends the interface to the mobile device, and when the mobile device is not within the boundary, prevents autonomous parking of the vehicle.
Description
TECHNICAL FIELD

The present disclosure generally relates to a remote assist park system in a vehicle and, more specifically, mobile device tethering for remote parking assist.


BACKGROUND

A remote parking assist (RePA) system is designed to autonomously park a vehicle provided that the user's remote device is within a specified distance of the vehicle. The RePA system is intended to used when the operator is outside the vehicle. The operator triggers the RePA system to park or un-park a vehicle into or out of a parking space using a remote device wirelessly communicating with the vehicle. Governments are developing regulations to require that control of RePA with the remote device shall only be allowed when the remote device is within a certain distance of the vehicle. For example, the proposed European regulation requires the remote device to be within 6 meters of the nearest point of the motor vehicle (see Economic Commission for Europe, Regulation No. 79) in order for the vehicle to autonomously park. As a result of these regulations, the operator may need to move as the vehicle moves when the path the vehicle is using to park moves the vehicle away from the operator. However, it can be difficult for the operator to judge the distance from the vehicle to know when their remote device is close enough to the vehicle.


SUMMARY

The appended claims define this application. The present disclosure summarizes aspects of the embodiments and should not be used to limit the claims. Other implementations are contemplated in accordance with the techniques described herein, as will be apparent to one having ordinary skill in the art upon examination of the following drawings and detailed description, and these implementations are intended to be within the scope of this application.


Example embodiments are disclosed for mobile device tethering for remote parking assist. An example vehicle includes ultra-wide angle cameras and a processor coupled to memory. The processor generates an interface based on a location of the mobile device including an overhead representation of the vehicle generated using images from the cameras and representations of a position of a mobile device and a boundary around the vehicle. The processor also sends the interface to the mobile device, and when the mobile device is not within the boundary, prevents autonomous parking of the vehicle.


An example method includes generating an interface based on a location of the mobile device including an overhead representation of the vehicle generated using images from ultra-wide angle cameras positions on the vehicle and representations of a position of a mobile device and a boundary around the vehicle. The example method also includes sending, via a wireless module, the interface to the mobile device. Additionally, the method includes, when the mobile device is not within the boundary, preventing autonomous parking of the vehicle.





BRIEF DESCRIPTION OF THE DRAWINGS

For a better understanding of the invention, reference may be made to embodiments shown in the following drawings. The components in the drawings are not necessarily to scale and related elements may be omitted, or in some instances proportions may have been exaggerated, so as to emphasize and clearly illustrate the novel features described herein. In addition, system components can be variously arranged, as known in the art. Further, in the drawings, like reference numerals designate corresponding parts throughout the several views.



FIG. 1 illustrates a vehicle and a mobile device operating in accordance with this disclosure.



FIG. 2 illustrates an interface on the mobile device.



FIGS. 3A, 3B, and 3C illustrate another interface on the mobile device of FIG. 1.



FIG. 4 illustrates another interface on the mobile device of FIG. 1.



FIG. 5 is a block diagram of electronic components of the vehicle of FIG. 1.



FIG. 6 is a flowchart of a method to assist an operator operating the remote park assist system of the vehicle of FIG. 1, which may be implemented by the electronic components of FIG. 5.





DETAILED DESCRIPTION OF EXAMPLE EMBODIMENTS

While the invention may be embodied in various forms, there are shown in the drawings, and will hereinafter be described, some exemplary and non-limiting embodiments, with the understanding that the present disclosure is to be considered an exemplification of the invention and is not intended to limit the invention to the specific embodiments illustrated.


Remote park assist (RePA) systems are designed to autonomously park and un-park vehicles when the operator is outside the vehicle. For example, RePA systems may be used when a parking spot is too narrow for the operator to open the door, or passengers to open their doors, when the vehicle is parked. RePA systems use range detection sensors (e.g., ultrasonic sensors, radar, LiDAR, cameras, etc.) to sense the environment around the parking spot and plan and execute a path into and out of the parking spot. In some examples, the RePA system is activated by the operator and scans for an available parking space. When a parking space is detected, the RePA system signals, via an interface (e.g., a center console display, etc.) for the operator to stop the vehicle near the detected parking spot. The operator then exits the vehicle. RePA systems are further activated via mobile devices (e.g., smartphone, smart watch, key fob, etc.) to complete the autonomous parking. In jurisdictions that require the mobile device to stay within a threshold distance of a vehicle, the RePA system tracks the location of the mobile device in relation to the location of the vehicle and determines whether the mobile device is within the threshold distance. When the mobile device is outside the threshold distance from the vehicle, the RePA system will not autonomously move the vehicle.


The RePA system of the vehicle tracks the location of a mobile device (e.g., a smart phone, a smart watch, a key fob, etc.) associated with the operator relative to the location of the vehicle. The RePA system may use various techniques to determine the location of the mobile device relative to the location of the vehicle, such as dead reckoning and signal triangulation. Mobile device dead reckoning uses the inertial sensors (e.g., accelerometers, gyroscopes, etc.) in the mobile device to determine the current location of the mobile device based on a previous location (sometimes referred to as a “fix”). As the mobile device moves, the RePA system tracks the movement by tracking the distance and direction the mobile device has traveled relative to the initial location. To perform mobile device dead reckoning, the RePA system determines the initial location by establishing the location of the mobile device in relation to the location of the vehicle. However, establishing that relationship can be difficult. Additionally, dead reckoning is subject to cumulative error. Over time and distance, the error becomes large enough causing the location calculations to not be accurate enough for the RePA system. As a result, from time-to-time (e.g., after a threshold time, after a threshold distance, etc.), the RePA system reestablishes an initial location of the mobile device. For example, when an operator leaves the vehicle and goes shopping, to perform mobile device dead reckoning, the RePA system needs to reestablish the location of the mobile device relative to the location of the vehicle because of the cumulative error. One localization technique is to use the signal strength(s) of signals between the antenna of the mobile device and antenna(s) of the vehicle. By using a measurement of the strength of the signals (e.g., a received signal strength indicator (RSSI), a transmission strength (RX) a received channel power indicator (RCPI), etc.), the RePA system can estimate a location of the mobile device. The accuracy of the estimation depends on several factors, such as how many signal strength measurements from different vehicle antennas are being used, the frequency of the signal, the distance between the antenna of the mobile device and the antenna(s) of the vehicle, and interference of the environment around the vehicle, etc. In addition to mobile device dead reckoning, the RePA system performs vehicular dead reckoning. Since the vehicle moves during a RePA event, the system must estimate the real-time location of the vehicle to properly compare it with the estimated location of the mobile device. For example, even if the mobile device is stationary during the RePA event, the distance between the mobile device and vehicle will change as a result of the movement of the vehicle. Vehicular dead reckoning can be performed using the transducers already resident to typical vehicles, such as the steering wheel angle sensor and rotary encoders that are used for odometry. The vehicle can also perform dead reckoning using similar methods to mobile device dead reckoning (e.g. accelerometers, gyroscopes, etc.), but the vehicle-specific hardware is likely to produce more accurate results. As discussed below, the RePA system of the present disclosure uses dead reckoning and localization, singly and in combination, with various techniques to overcome the errors in the location determination methods and determine whether the mobile device is within a threshold distance of the vehicle.


As discussed below, the RePA system of the vehicle communicatively couples to the mobile device and provides interface elements to an application executing on the mobile device. These interface elements facilitate informing the operator of the state of the RePA system, such as (a) a location of a virtual boundary that defines the maximum distance at which the RePA system may be operated, (b) the location of the mobile device relative to the vehicle and/or the virtual boundary, and/or (c) the planned travel path of the vehicle, etc. Additionally, the vehicle provides warnings and/or status indicators to facilitate informing the operator of whether the operator should change position relative to the vehicle so that the RePA system can still autonomously operate the vehicle. In some examples, the warnings and/or status indicators are text, visual (e.g., color changes, operative interface changes, etc.), audible, and/or haptic. For example, interface elements may be augmented to be green, yellow, or red depending on the relationship between the location of the mobile device and the virtual boundary. The mobile device displays the interface elements. In some examples, the RePA system also sends images from a 360 degree camera system to be displayed on the mobile device.



FIG. 1 illustrates a vehicle 100 and a mobile device 102 operating in accordance with this disclosure. The vehicle 100 may be a standard gasoline powered vehicle, a hybrid vehicle, an electric vehicle, a fuel cell vehicle, and/or any other mobility implement type of vehicle. The vehicle 100 includes parts related to mobility, such as a powertrain with an engine, a transmission, a suspension, a driveshaft, and/or wheels, etc. The vehicle 100 is a semi-autonomous vehicle (e.g., some routine motive functions, such as parking, are controlled by the vehicle 100), or an autonomous vehicle (e.g., motive functions are controlled by the vehicle 100 without direct driver input). In the illustrated example the vehicle 100 includes a camera module (CM) 104, a wireless module (WM) 106, and an autonomy unit 108.


The camera module 104 receives images from cameras 110a-110d to generate a 360 degree camera video image. The cameras 110a-110d are ultra-wide fish-eye cameras that capture images of the area around the vehicle 100. The cameras 110a-110d are located on each side of the vehicle 100. In the illustrated example, the cameras 110a-110d are located on the front of the vehicle 100 (e.g., near a badge of the vehicle 100), the rear of the vehicle 100, and on the side-view mirrors 112 of the vehicle 100. The camera module 104 receives images from the cameras 110a-110d and merges the images together with a representation of the vehicle 100 to form the video image to provide a simulated top-down view of the area adjacent to the vehicle 100.


The wireless module 106 is communicatively coupled (e.g., wired or wirelessly) to wireless nodes 114a-114h located at various locations of the vehicle 100. The wireless module 106 performs localization techniques (e.g., triangulation/trilateration, and/or dead reckoning, etc.) based on signal strength values (e.g., a received signal strength indicator (RSSI), a transmission strength (RX), a received channel power indicator (RCPI), etc.) received from the wireless nodes 114a-114h to determine the location of the mobile device 102 relative to the location of the vehicle 100. The wireless module 106 provides this localization data to other electronic control modules in the vehicle 100, such as the autonomy unit 108.


In the illustrated example, each of the wireless nodes 114a-114h is configured to communicatively couple to the mobile device 102 of the operator. Each of the wireless nodes 114a-114h includes hardware and firmware to establish a wireless connection with a key fob and/or a mobile device (e.g., the mobile device 102). For example, the wireless nodes 114a-114h are wireless personal area network (WPAN) modules that wirelessly communicate with key fob(s) and/or mobile device(s) (e.g., the mobile device 102) via short-range wireless communication protocol(s). In some examples, the wireless nodes 114a-114h implement the Bluetooth® and/or Bluetooth® Low Energy (BLE®) protocols. The Bluetooth® and BLE® protocols are set forth in Volume 6 of the Bluetooth® Specification 4.0 (and subsequent revisions) maintained by the Bluetooth® Special Interest Group. Additionally or alternatively, the wireless nodes 114a-114h are configured to wirelessly communicate via Wi-Fi®, Near Field Communication (NFC), UWB (Ultra-Wide Band), and/or any other short-range and/or local wireless communication protocol (e.g., IEEE 802.11 a/b/g/n/ac/p) that enables each of the wireless nodes 114a-114h to communicatively couple to the mobile device 102.


Some of the wireless nodes 114a-114f are exterior nodes. The exterior nodes are positioned and oriented to communicatively couple to and/or monitor communication of the mobile device 102 and/or a key fob when the mobile device 102 and/or the key fob is located outside of and/or within the cabin of the vehicle 100. For example, each of the wireless nodes 114a-114f is located near an exterior of the vehicle 100 and oriented in a direction away from the cabin to communicatively couple to the mobile device 102 when the mobile device 102 is outside of the cabin of the vehicle 100. Some of the wireless nodes 114g and 114h are interior nodes. The interior nodes are positioned and oriented to communicatively couple to and/or monitor communication of the mobile device 102 and/or a key fob when the mobile device 102 and/or the key fob is located within and/or outside of the cabin of the vehicle 100. For example, the one of the wireless nodes 114g may be located near and oriented toward a front portion of the cabin to communicatively couple to and/or monitor communication of the mobile device 102 and/or a key fob when the mobile device 102 and/or the key fob is located within the front portion of the cabin. Further, the wireless nodes 114h may be located near and oriented toward a rear portion of the cabin to communicatively couple to and/or monitor communication of the mobile device 102 and/or a key fob when the mobile device 102 and/or the key fob is located within the rear portion of the cabin.


The autonomy unit 108 communicates with various electronic control units (ECUs) (e.g., a powertrain control unit, a body control unit, a brake control unit, etc.) and/or various sensors (e.g., ultrasonic sensors, radar, LiDAR, cameras, etc.) to autonomously control motive functions of the vehicle 100. The autonomy unit 108 includes a RePA system that, when engaged, autonomously parks the vehicle 100 as long as the conditions are met for operation. One condition is that the mobile device 102 is to be within a virtual boundary 116 defined by a threshold distance from the surface of the vehicle 100. Another condition is that the autonomy unit 108 receives, via the wireless module 106, a continuous input signal from the mobile device 102 that is generated while the operator is providing an input into the mobile device 102. Examples of methods of monitoring continuous input from the mobile device 102 are described in U.S. patent application Ser. No. 15/711,741, entitled “Mobile Device Initiation of Vehicle Remote-Parking,” filed Sep. 21, 2017, and U.S. patent application Ser. No. 15/861,348, entitled “Mobile Device Interface for Trailer Backup-Assist,” filed Jan. 3, 2018, which are herein incorporated by reference in their entirety.


The autonomy unit 108 determines whether the mobile device 102 is within the virtual boundary 116 based on the localization data provided by the wireless module 106. In some examples, the autonomy unit 108 provides, via the body control module, visual indicators to inform the operator of the relationship between the location of the mobile device 102 and the location of the virtual boundary 116. For example, the autonomy unit may change the color, illumination pattern, and/or the brightness of lights of the vehicle 100. Examples of providing a visual indicator on the vehicle are described in U.S. patent application Ser. No. 15/860,242, entitled “Mobile Device Tethering for a Remote Parking Assist System of a Vehicle,” filed Jan. 2, 2018, which is herein incorporated by reference in its entirety.


In the illustrated example, the autonomy unit 108 includes an interface controller 118. The interface controller 118 controls which interface elements are displayed on the mobile device 102, the characteristics of the interface elements, and sends instructions to the mobile device 102 that causes the selected interface elements to appear on a display of the mobile device 102. The interface controller 118 receives the localization data via the wireless module 106, determines the relationship between the location of the mobile device 102 and the location of the virtual boundary 116, generates interface elements, and sends the interface elements to the mobile device 102 via the wireless module 106. The interface controller 118 determines the mobile device 102 is either (a) within the virtual boundary 116, (b) outside of the virtual boundary 116, or (c) within, but near, the virtual boundary 116. In some examples, the interface controller 118 also sends the 360 degree camera video image generated by the camera module 104. As used herein, near the virtual boundary 116 refers to a specific distance set by the interface controller 118 from an edge of the virtual boundary 116. For example, “being near the virtual boundary 116” may be 0.5 meters from the edge of the virtual boundary 116. As another example, “being near the virtual boundary 116” may be defined as being 90% of the threshold distance that establishes the virtual boundary 116 from the vehicle 100. In such an example, if the virtual boundary 116 is defined at 6 meters from the vehicle 100, being near the virtual boundary 116 may be when the mobile device 102 is between 5.4 meters to 6 meters from the vehicle 100. Example interface elements are described in connection with FIGS. 2, 3A, 3B, 3C, and 4 below. Additionally, in some examples, the interface controller 118 sends commands to the mobile device 102 to cause audible and/or haptic alerts to be presented the operator.


In some examples, the interface controller 118 sends instructions to the mobile device 102 to produce a haptic alert to the operator. The interface controller 118 provides a vibration pattern with a configurable pulse interval when (a) the operator is holding the mobile device, (b) the mobile device is within a threshold distance of the vehicle (e.g., 1.5 times the distance that defines the virtual boundary 116), (c) the operator is providing continuous input (e.g., the continuous input signal is being received from the mobile device 102), and/or the vehicle 100 is below a speed threshold (e.g., 3.2 kilometers per hour, etc.). In some examples, the pulse interval is a function of the distance of the mobile device 102 from the vehicle 100. For example, the interface controller 118 may cause the pulses to become more frequent as the mobile device 102 approaches the virtual boundary 116. In some examples, in response to the mobile device 102 transitioning to being outside the virtual boundary 116, the instructions from the interface controller 118 cause mobile device 102 to continuously vibrate. Alternatively, in some examples, the interface controller 118 sends the state of the vehicle 100 (e.g., speed, direction of travel, etc.) to the mobile device 102. In such examples, the mobile device 102 uses the state of the vehicle 100 to determine the audible, visual and/or haptic alerts and the intervals associated with the haptic alerts.


In some examples, the interface controller 118 sends instructions to the mobile device 102 to produce an audible alert to the operator. The interface controller 118 provides an audio signal with a configurable pitch and/or tone when (a) the operator is holding the mobile device, (b) the mobile device is within a threshold distance of the vehicle (e.g., 1.5 times the distance that defines the virtual boundary 116), (c) the operator is providing continuous input (e.g., the continuous input signal is being received from the mobile device 102), and/or the vehicle 100 is below a speed threshold (e.g., 3.2 kilometers per hour, etc.). In some examples, the pitch and/or tone is a function of the distance of the mobile device 102 from the vehicle 100. For example, the interface controller 118 may cause the pitch and/or tone to increase as the mobile device 102 approaches the virtual boundary 116. In some examples, in response to the mobile device 102 transitioning to being outside the virtual boundary 116, the instructions from the interface controller 118 cause mobile device 102 to provide the pitch and/or tone act a predefine interval.


The mobile device 102 includes hardware and software to communicatively couple to the wireless nodes 114a-114h of the vehicle 100, execute applications, and display an interface to the operator. The mobile device 102 provides input device(s) (e.g., a physical button, a virtual button via a touch screen, a motion track on the touch screen, etc.). Additionally, the mobile device 102 includes (i) inertial sensors to provide movement information of the mobile device 102, (ii) a speaker, headphone jack, and/or personal area network module coupleable to wireless headphones, and (iii) a vibration motor to provide haptic feedback to the operator.



FIG. 2 illustrates an example interface 200 on the mobile device 102. Based on the localization data provided by the wireless module 106, the interface controller 118 generates the interface 200 and sends the interface 200 to the mobile device 102. The interface controller 118 periodically generates (e.g., every 500 milliseconds, every second, etc.) the interface 200 and sends the updated interface 200 to the mobile device 102. In some examples, the interface controller 118 sends the interface 200 to be displayed on the mobile device 102 when (a) the mobile device 102 is a threshold distance from the vehicle 100 (e.g., halfway between the vehicle 100 and the virtual boundary 116, etc.), (b) the vehicle 100 is autonomously moving below a speed threshold, (c) the continuous input signal is not received from the mobile device 102, (d) when the vehicle 100 detects objects (e.g., via radar, LiDAR, ultra-sonic sensors, etc.) around the vehicle 100 that are within a threshold distance from the vehicle 100, (e) the interface controller 118 determines that the available display region of the mobile device 102 is large enough to accommodate the interface 200, and/or (f) the RePA system in engaged.


In the illustrated example, the interface 200 includes (a) a 360 degree image 202 generated by the camera module 104 with a representation 204 of the vehicle 100, (b) a representation 206 of the virtual boundary 116, (c) a representation 208 of the planned path that the vehicle will execute to autonomously park, (d) a representation 210 of a state of the lights of the vehicle 100, and (e) a representation 212 of the positions of the wheels of the vehicle 100. Additionally, in some examples, the interface 200 includes a representation 214 of the location of the mobile device 102 and/or a zone of probability (e.g., an area that represents probable locations of the mobile device 102 accounting for localization errors) as determined by the wireless module 106. In some examples, the interface 200 includes indications of the direction of travel of the vehicle 100, the angle of the road, and/or other elements to assist the operator interpret the orientation of the vehicle 100. In some examples, the representation 206 of the virtual boundary 116 is color coded to indicate whether the mobile device 102 (a) is outside the virtual boundary 116 (e.g. color coded red), (b) is inside the virtual boundary 116 but near (e.g., within 0.5 meters, etc.) the edge of the virtual boundary 116 (e.g., color coded yellow), or (c) is inside the virtual boundary 116 (e.g., color coded green). Alternatively or additionally, in some examples, the representation 206 of the virtual boundary 116 may be animated to indicate the relationship of the location of the mobile device 102 to the location of the vehicle 100.



FIGS. 3A, 3B, and 3C illustrate another interface 300 on the mobile device 192 of FIG. 1. In some examples, the interface controller 118 generates the interface 300, when, for example, the available display region of the mobile device 102 is not large enough to accommodate the interface 200 of FIG. 2. In the illustrated examples, the interface 300 includes (a) an motion track 302, (b) the representation 204 of the vehicle 100, (c) the representation 206 of the virtual boundary 116, (d) the representation 214 of the estimated location of the mobile device 102, and (e) a border indicator 304. The motion track 302 provides an input for the operator to trace with his or her finger via a touch screen of the mobile device 102 to initiate and terminate remote parking of a vehicle 100 and/or provide a continuous input signal. For example, the mobile device 102 sends the continuous input signal to the vehicle 100 as long as the operator is continually tracing a path defined by the motion track 302. In such a manner, the autonomy unit 108 causes the vehicle 100 to move during remote parking only when the user is moving his or her finger (e.g., thumb), conductive stylus, and/or prosthetic digit along the motion track 302. The motion track 302 may be any continuous shape (e.g., non-circular, non-elliptical, wavy, obtuse, etc.) that reflects a natural motion or hand-movement of the user to facilitate the user in easily tracing the motion track 302 that initiates remote parking of the vehicle 100. The border indicator 304 is a region following an edge 306 of the screen of the mobile device 102 that is a number of pixels (e.g., 10 pixels, 20 pixel) wide.


In the illustrated examples, the motion track 302, the border indicator 304, and/or an interior portion 308 defined by the representation 206 of the virtual boundary 116 are color coded to indicate the relationship of the location of the mobile device 102 to the location of the vehicle 100. The color coding facilitates the operator understanding whether the mobile device 102 is within the virtual boundary 116 with a glance of the screen. Alternatively or additionally, in some examples, the interface controller 118 causes the interface 300 to have other visual indicators, such as blinking or animation, to communicate the status to the RePA system. For example, when the vehicle 100 is in motion, the border indicator 304 may be animated to rotate in a direction indicative of the direction of travel (e.g., forward or reverse) of the vehicle 100. In FIG. 3A, the interface 300 depicts the representation 214 of the mobile device 102 within the representation 206 of the virtual boundary 116. In such an example, the motion track 302, the border indicator 304, and/or the interior portion 308 defined by the representation 206 of the virtual boundary 116 may be color coded green. In FIG. 3B, the interface 300 depicts the representation 214 of the mobile device 102 within the representation 206 of the virtual boundary 116 and near the edge of the virtual boundary 116. In such an example, the motion track 302, the border indicator 304, and/or the interior portion 308 defined by the representation 206 of the virtual boundary 116 may be color coded yellow. In FIG. 3C, the interface 300 depicts the representation 214 of the mobile device 102 outside the representation 206 of the virtual boundary 116. In such an example, the motion track 302, the border indicator 304, and/or the interior portion 308 defined by the representation 206 of the virtual boundary 116 may be color coded red.



FIG. 4 illustrates another interface 400 that the interface controller 118 may cause to be displayed on the mobile device 102 of FIG. 1. In the illustrated example, the interface 400 includes (a) the representation 204 of the vehicle 100, (b) the representation 206 of the virtual boundary 116, (c) the representation 214 of the estimated location of the mobile device 102, (d) the representation 208 of the planned path that the vehicle will execute to autonomously park, (e) a representation 402 of an estimated final location of the virtual boundary 116, (f) a representation 404 of an area in which the virtual boundary 116 will exist during the virtual parking maneuver, (g) representation(s) of objects near the path of the vehicle 100, and/or (h) a representation 406 of an estimated final location of the vehicle 100. In some examples, the interface 400 animates the representation 204 of the vehicle 100 to show movement along the path to the final location of the vehicle 100. Additionally, in some examples, the interface 400 includes the video images from the 360 degree camera system to show the area around the vehicle 100. In such examples, as the vehicle 100 moves, the video images from the 360 degree camera system shift on the interface 400 to provide a current view of the area around the vehicle 100 as the vehicle 100 moves.



FIG. 5 is a block diagram of electronic components 500 of the vehicle 100 of FIG. 1. In the illustrate example, the electronic components 500 include the camera module 104, the wireless module 106, the autonomy unit 108, the cameras 110a-110d, the wireless nodes 114a-114h, and a vehicle data bus 502.


In the illustrated example, the autonomy unit 108 includes a processor or controller 504 and memory 506. In the illustrated example, the autonomy unit 108 is structured to include interface controller 118. Alternatively, in some examples, the interface controller 118 is incorporated into another electronic control unit (ECU) with its own processor and memory. The processor or controller 504 may be any suitable processing device or set of processing devices such as, but not limited to: a microprocessor, a microcontroller-based platform, a suitable integrated circuit, one or more field programmable gate arrays (FPGAs), and/or one or more application-specific integrated circuits (ASICs). The memory 506 may be volatile memory (e.g., RAM, which can include non-volatile RAM, magnetic RAM, ferroelectric RAM, and any other suitable forms); non-volatile memory (e.g., disk memory, FLASH memory, EPROMs, EEPROMs, non-volatile solid-state memory, etc.), unalterable memory (e.g., EPROMs), read-only memory, and/or high-capacity storage devices (e.g., hard drives, solid state drives, etc). In some examples, the memory 506 includes multiple kinds of memory, particularly volatile memory and non-volatile memory.


The memory 506 is computer readable media on which one or more sets of instructions, such as the software for operating the methods of the present disclosure can be embedded. The instructions may embody one or more of the methods or logic as described herein. In a particular embodiment, the instructions may reside completely, or at least partially, within any one or more of the memory 506, the computer readable medium, and/or within the processor 504 during execution of the instructions.


The terms “non-transitory computer-readable medium” and “tangible computer-readable medium” should be understood to include a single medium or multiple media, such as a centralized or distributed database, and/or associated caches and servers that store one or more sets of instructions. The terms “non-transitory computer-readable medium” and “tangible computer-readable medium” also include any tangible medium that is capable of storing, encoding or carrying a set of instructions for execution by a processor or that cause a system to perform any one or more of the methods or operations disclosed herein. As used herein, the term “tangible computer readable medium” is expressly defined to include any type of computer readable storage device and/or storage disk and to exclude propagating signals.


The vehicle data bus 502 communicatively couples the camera module 104, the wireless module 106, and the autonomy unit 108. In some examples, the vehicle data bus 502 includes one or more data buses. The vehicle data bus 502 may be implemented in accordance with a controller area network (CAN) bus protocol as defined by International Standards Organization (ISO) 11898-1, a Media Oriented Systems Transport (MOST) bus protocol, a CAN flexible data (CAN-FD) bus protocol (ISO 11898-7) and/a K-line bus protocol (ISO 9141 and ISO 14230-1), and/or an Ethernet™ bus protocol IEEE 802.3 (2002 onwards), etc.



FIG. 6 is a flowchart of a method to assist an operator operating the remote park assist system of the vehicle 100 of FIG. 1, which may be implemented by the electronic components 500 of FIG. 5. Initially, at block 602, the interface controller 118 waits until the remote parking system is enabled. In some examples, the operator enables the remote parking system through an infotainment system (e.g., Sync® by Ford, etc.) on a center console display. For example, after stopping the vehicle 100 and before exiting the cabin of the vehicle 100, the operator may enable the remote parking assist system. Enabling the remote parking system causes the autonomy unit 108 to, for example, identify a potential parking spot and plan a path into the parking spot. At block 604, after the remote parking assist system has been enabled, the interface controller 118 tracks the location of the mobile device 102 using the localization data from the wireless module 106. At block 606, the camera module 104 generates the 360 degree composite image from the images received from the cameras 110a-110d. At block 608, the interface controller 118 generates an interface (e.g., the interface 200, 300, 400 of FIGS. 2, 3A, 3B, 3C, and 4 above, etc.) based on the location of mobile device 102 relative to the location of the vehicle 100. At block 610, the interface controller 118 sends instructions to the mobile device 102 that cause the mobile device 102 to display the interface generated at block 606.


At block 612, the interface controller 118 determines whether the mobile device 102 is within the virtual boundary 116 based on the localization data received at block 604. When the mobile device 102 is not within the virtual boundary 116, the method continues at block 614. Otherwise, when the mobile device 102 is with the virtual boundary 116, the method continues at block 618. At block 614, the interface controller 118 adjusts the interface for the mobile device 102 to indicate the state of the remote parking system. For example, the interface controller 118 may cause the border indicator 304 on the interface 300 to flash red. At block 616, the autonomy unit 108 prevents autonomous movement of the vehicle 100.


At block 618, the interface controller 118 determines whether the mobile device 102 is near (e.g., within 0.5 meters) the virtual boundary 116. When the mobile device 102 is near the virtual boundary 116, the method continues to block 620. Otherwise, when the mobile device 102 is not near the virtual boundary 116, the method continues to block 624. At block 620, the interface controller 118 adjusts the interface for the mobile device 102 to indicate the state of the remote parking system. For example, the interface controller 118 may cause the border indicator 304 on the interface 300 to turn yellow and generate a text-based warning. At block 622, the autonomy unit 108 allows autonomous movement of the vehicle 100.


At block 624, the interface controller 118 adjusts the interface for the mobile device 102 to indicate the state of the remote parking system. For example, the interface controller 118 may cause the border indicator 304 on the interface 300 to turn green. At block 626, the autonomy unit 108 allows autonomous movement of the vehicle 100.


The flowchart of FIG. 6 is representative of machine readable instructions stored in memory (such as the memory 506 of FIG. 5) that comprise one or more programs that, when executed by a processor (such as the processor 504 of FIG. 5), cause the vehicle 100 to implement the example interface controller 118 and/or, more generally, the example autonomy unit 108 of FIGS. 1 and 5. Further, although the example program(s) is/are described with reference to the flowchart illustrated in FIG. 6, many other methods of implementing the example interface controller 118 and/or, more generally, the example autonomy unit 108 may alternatively be used. For example, the order of execution of the blocks may be changed, and/or some of the blocks described may be changed, eliminated, or combined.


In this application, the use of the disjunctive is intended to include the conjunctive. The use of definite or indefinite articles is not intended to indicate cardinality. In particular, a reference to “the” object or “a” and “an” object is intended to denote also one of a possible plurality of such objects. Further, the conjunction “or” may be used to convey features that are simultaneously present instead of mutually exclusive alternatives. In other words, the conjunction “or” should be understood to include “and/or”. As used here, the terms “module” and “unit” refer to hardware with circuitry to provide communication, control and/or monitoring capabilities, often in conjunction with sensors. “Modules” and “units” may also include firmware that executes on the circuitry. The terms “includes,” “including,” and “include” are inclusive and have the same scope as “comprises,” “comprising,” and “comprise” respectively.


The above-described embodiments, and particularly any “preferred” embodiments, are possible examples of implementations and merely set forth for a clear understanding of the principles of the invention. Many variations and modifications may be made to the above-described embodiment(s) without substantially departing from the spirit and principles of the techniques described herein. All modifications are intended to be included herein within the scope of this disclosure and protected by the following claims.

Claims
  • 1. A vehicle comprising: ultra-wide angle cameras; anda processor coupled to memory to:generate an interface based on a location of a mobile device including an overhead representation of the vehicle generated using images from the cameras and representations of a position of the mobile device and a boundary around the vehicle;send the interface to the mobile device; andwhen the mobile device is not within the boundary, prevent autonomous parking of the vehicle.
  • 2. The vehicle of claim 1, wherein the interface includes a border indicator that is displayed around a perimeter of a display of the mobile device.
  • 3. The vehicle of claim 2, wherein the processor is to change characteristics of the border indicator based on the location of the mobile device compared to the location of the boundary.
  • 4. The vehicle of claim 2, wherein the processor is to animate the border indicator based on a direction of travel of the vehicle.
  • 5. The vehicle of claim 1, wherein the interface includes a representation of the vehicle, a planned path of the vehicle, and a representation of angles of tires of the vehicle.
  • 6. The vehicle of claim 1, wherein the interface includes a motion track.
  • 7. The vehicle of claim 6, wherein the processor is to change characteristics of the motion track based on the location of the mobile device compared to the location of the boundary.
  • 8. The vehicle of claim 7, wherein the characteristics include at least one of a color or a blinking pattern.
  • 9. The vehicle of claim 1, wherein the processor is to send instructions to the mobile device to cause the mobile device to vibrate.
  • 10. The vehicle of claim 9, wherein the instructions cause the mobile device to vibrate at an interval based on a distance of the mobile device from the vehicle.
  • 11. A method comprising: generating, with a processor, an interface based on a location of a mobile device including an overhead representation of a vehicle generated using images from ultra-wide angle cameras positions on the vehicle and representations of a position of the mobile device and a boundary around the vehicle;sending, via a wireless module, the interface to the mobile device; andwhen the mobile device is not within the boundary, preventing autonomous parking of the vehicle.
  • 12. The method of claim 11, wherein the interface includes a border indicator that is displayed around a perimeter of a display of the mobile device.
  • 13. The method of claim 12, including changing characteristics of the border indicator based on the location of the mobile device compared to the location of the boundary.
  • 14. The method of claim 12, including animating the border indicator based on a direction of travel of the vehicle.
  • 15. The method of claim 11, wherein the interface includes a representation of the vehicle, a planned path of the vehicle, and a representation of angles of tires of the vehicle.
  • 16. The method of claim 11, wherein the interface includes a motion track.
  • 17. The method of claim 16, including changing characteristics of the motion track based on the location of the mobile device compared to the location of the boundary.
  • 18. The method of claim 17, wherein the characteristics include at least one of a color or a blinking pattern.
  • 19. The method of claim 11, including sending instructions to the mobile device to cause the mobile device to vibrate.
  • 20. The method of claim 19, wherein the instructions cause the mobile device to vibrate at an interval based on a distance of the mobile device from the vehicle.
US Referenced Citations (354)
Number Name Date Kind
5959724 Izumi Sep 1999 A
6151539 Bergholz Nov 2000 A
6275754 Shimizu Aug 2001 B1
6356828 Shimizu Mar 2002 B1
6452617 Bates Sep 2002 B1
6476730 Kakinami Nov 2002 B2
6477260 Shimomura Nov 2002 B1
6657555 Shimizu Dec 2003 B2
6683539 Trajkovic Jan 2004 B2
6724322 Tang Apr 2004 B2
6744364 Wathen Jun 2004 B2
6768420 McCarthy Jul 2004 B2
6801855 Walters Oct 2004 B1
6850844 Walters Jan 2005 B1
6850148 Masudaya Feb 2005 B2
6927685 Wathen Aug 2005 B2
6997048 Komatsu Feb 2006 B2
7042332 Takamura May 2006 B2
7123167 Staniszewski Oct 2006 B2
7307655 Okamoto Dec 2007 B1
7663508 Teshima Feb 2010 B2
7737866 Wu Jun 2010 B2
7813844 Gensler Oct 2010 B2
7825828 Watanabe Nov 2010 B2
7834778 Browne Nov 2010 B2
7847709 McCall et al. Dec 2010 B2
7850078 Christenson Dec 2010 B2
7924483 Smith Apr 2011 B2
8035503 Partin Oct 2011 B2
8054169 Bettecken Nov 2011 B2
8098146 Petrucelli Jan 2012 B2
8126450 Howarter Feb 2012 B2
8164628 Stein Apr 2012 B2
8180524 Eguchi May 2012 B2
8180547 Prasad May 2012 B2
8224313 Howarter Jul 2012 B2
8229645 Lee Jul 2012 B2
8242884 Holcomb et al. Aug 2012 B2
8335598 Dickerhoof Dec 2012 B2
8401235 Lee Mar 2013 B2
8493236 Boehme Jul 2013 B2
8538408 Howarter Sep 2013 B2
8542130 Lavoie Sep 2013 B2
8552856 McRae Oct 2013 B2
8587681 Guidash Nov 2013 B2
8594616 Gusikhin Nov 2013 B2
8599043 Kadowaki Dec 2013 B2
8618945 Furuta Dec 2013 B2
8645015 Oetiker Feb 2014 B2
8655551 Danz Feb 2014 B2
8692773 You Apr 2014 B2
8706350 Talty Apr 2014 B2
8725315 Talty May 2014 B2
8742947 Nakazono Jun 2014 B2
8744684 Hong Jun 2014 B2
8780257 Gidon Jul 2014 B2
8787868 Leblanc Jul 2014 B2
8825262 Lee Sep 2014 B2
8933778 Birkel Jan 2015 B2
8957786 Stempnik Feb 2015 B2
8994548 Gaboury Mar 2015 B2
8995914 Nishidai Mar 2015 B2
9008860 Waldock Apr 2015 B2
9014920 Torres Apr 2015 B1
9078200 Wuergler Jul 2015 B2
9086879 Gautama Jul 2015 B2
9141503 Chen Sep 2015 B1
9147065 Lauer Sep 2015 B2
9154920 O'Brien Oct 2015 B2
9168955 Noh Oct 2015 B2
9193387 Auer Nov 2015 B2
9225531 Hachey Dec 2015 B2
9230439 Boulay Jan 2016 B2
9233710 Lavoie Jan 2016 B2
9273966 Bartels Mar 2016 B2
9275208 Protopapas Mar 2016 B2
9283960 Lavoie Mar 2016 B1
9286803 Tippelhofer Mar 2016 B2
9302675 Schilling Apr 2016 B2
9318022 Barth Apr 2016 B2
9379567 Kracker Jun 2016 B2
9381859 Nagata Jul 2016 B2
9429657 Sidhu Aug 2016 B2
9429947 Wengreen Aug 2016 B1
9454251 Guihot Sep 2016 B1
9469247 Juneja Oct 2016 B2
9493187 Pilutti Nov 2016 B2
9506774 Shutko Nov 2016 B2
9511799 Lavoie Dec 2016 B2
9522675 You Dec 2016 B1
9529519 Blumenberg Dec 2016 B2
9557741 Elie Jan 2017 B1
9563990 Khan Feb 2017 B2
9595145 Avery Mar 2017 B2
9598051 Okada Mar 2017 B2
9606241 Varoglu Mar 2017 B2
9616923 Lavoie Apr 2017 B2
9637117 Gusikhin May 2017 B1
9651655 Feldman May 2017 B2
9656690 Shen May 2017 B2
9666040 Flaherty et al. May 2017 B2
9688306 McClain Jun 2017 B2
9701280 Schussmann Jul 2017 B2
9712977 Tu Jul 2017 B2
9715816 Adler Jul 2017 B1
9725069 Krishnan Aug 2017 B2
9731714 Kiriya Aug 2017 B2
9731764 Baek Aug 2017 B2
9754173 Kim Sep 2017 B2
9809218 Elie Nov 2017 B2
9811085 Hayes Nov 2017 B1
9842444 Van Wiemeersch Dec 2017 B2
9845070 Petel Dec 2017 B2
9846431 Petel Dec 2017 B2
9914333 Shank Mar 2018 B2
9921743 Bryant Mar 2018 B2
9946255 Matters Apr 2018 B2
9959763 Miller May 2018 B2
9971130 Lin May 2018 B1
9975504 Dalke May 2018 B2
10019001 Dang Van Nhan Jul 2018 B2
10032276 Liu Jul 2018 B1
10040482 Jung Aug 2018 B1
10043076 Zhang Aug 2018 B1
10131347 Kim Nov 2018 B2
10192113 Liu Jan 2019 B1
10246055 Farges Apr 2019 B2
10268341 Kocienda Apr 2019 B2
10369988 Tseng Aug 2019 B2
20030060972 Kakinami Mar 2003 A1
20030098792 Edwards May 2003 A1
20030133027 Itoh Jul 2003 A1
20050030156 Alfonso Feb 2005 A1
20050068450 Steinberg Mar 2005 A1
20050099275 Kamdar May 2005 A1
20060010961 Gibson Jan 2006 A1
20060227010 Berstis Oct 2006 A1
20060235590 Bolourchi Oct 2006 A1
20070230944 Georgiev Oct 2007 A1
20080027591 Lenser Jan 2008 A1
20080154464 Sasajima Jun 2008 A1
20080154613 Haulick Jun 2008 A1
20080238643 Malen Oct 2008 A1
20080306683 Ando Dec 2008 A1
20090096753 Lim Apr 2009 A1
20090098907 Huntzicker Apr 2009 A1
20090115639 Proefke May 2009 A1
20090125181 Luke May 2009 A1
20090125311 Haulick May 2009 A1
20090128315 Griesser May 2009 A1
20090146813 Nuno Jun 2009 A1
20090174574 Endo Jul 2009 A1
20090241031 Gamaley Sep 2009 A1
20090289813 Kwiecinski Nov 2009 A1
20090309970 Ishii Dec 2009 A1
20090313095 Hurpin Dec 2009 A1
20100025942 Mangaroo Feb 2010 A1
20100061564 Clemow Mar 2010 A1
20100114471 Sugiyama May 2010 A1
20100114488 Khamharn May 2010 A1
20100136944 Taylor Jun 2010 A1
20100152972 Attard Jun 2010 A1
20100156672 Yoo Jun 2010 A1
20100245277 Nakao Sep 2010 A1
20100259420 Von Rehyer Oct 2010 A1
20110071725 Kleve Mar 2011 A1
20110082613 Oetiker Apr 2011 A1
20110190972 Timmons Aug 2011 A1
20110205088 Baker Aug 2011 A1
20110253463 Smith Oct 2011 A1
20110309922 Ghabra Dec 2011 A1
20120007741 Laffey Jan 2012 A1
20120072067 Jecker Mar 2012 A1
20120083960 Zhu Apr 2012 A1
20120173080 Cluff Jul 2012 A1
20120176332 Fujibayashi Jul 2012 A1
20120271500 Tsimhoni Oct 2012 A1
20120303258 Pampus Nov 2012 A1
20120323643 Volz Dec 2012 A1
20120323700 Aleksandrovich Dec 2012 A1
20130021171 Hsu Jan 2013 A1
20130024202 Harris Jan 2013 A1
20130043989 Niemz Feb 2013 A1
20130073119 Huger Mar 2013 A1
20130109342 Welch May 2013 A1
20130110342 Wuttke May 2013 A1
20130113936 Cohen May 2013 A1
20130124061 Khanafer May 2013 A1
20130145441 Mujumdar Jun 2013 A1
20130211623 Thompson Aug 2013 A1
20130231824 Wilson Sep 2013 A1
20130289825 Noh Oct 2013 A1
20130314502 Urbach Nov 2013 A1
20130317944 Huang Nov 2013 A1
20140052323 Reichel Feb 2014 A1
20140095994 Kim Apr 2014 A1
20140096051 Boblett Apr 2014 A1
20140121930 Allexi May 2014 A1
20140147032 Yous May 2014 A1
20140156107 Karasawa Jun 2014 A1
20140188339 Moon Jul 2014 A1
20140222252 Matters Aug 2014 A1
20140240502 Strauss Aug 2014 A1
20140282931 Protopapas Sep 2014 A1
20140297120 Cotgrove Oct 2014 A1
20140300504 Shaffer Oct 2014 A1
20140303839 Filev Oct 2014 A1
20140320318 Victor Oct 2014 A1
20140327736 DeJohn Nov 2014 A1
20140350804 Park Nov 2014 A1
20140350855 Vishnuvajhala Nov 2014 A1
20140365108 You Dec 2014 A1
20140365126 Vulcano Dec 2014 A1
20150022468 Cha Jan 2015 A1
20150039173 Beaurepaire Feb 2015 A1
20150039224 Tuukkanen Feb 2015 A1
20150045991 Schwitters et al. Feb 2015 A1
20150048927 Simmons Feb 2015 A1
20150066545 Kotecha Mar 2015 A1
20150077522 Suzuki Mar 2015 A1
20150088360 Bonnet Mar 2015 A1
20150091741 Stefik Apr 2015 A1
20150109116 Grimm Apr 2015 A1
20150116079 Mishra Apr 2015 A1
20150123818 Sellschopp May 2015 A1
20150127208 Jecker May 2015 A1
20150149265 Huntzicker May 2015 A1
20150151789 Lee Jun 2015 A1
20150153178 Koo Jun 2015 A1
20150161890 Huntzicker Jun 2015 A1
20150163649 Chen Jun 2015 A1
20150197278 Boos Jul 2015 A1
20150203111 Bonnet Jul 2015 A1
20150203156 Hafner Jul 2015 A1
20150210317 Hafner Jul 2015 A1
20150217693 Pliefke Aug 2015 A1
20150219464 Beaurepaire Aug 2015 A1
20150220791 Wu Aug 2015 A1
20150226146 Elwart Aug 2015 A1
20150274016 Kinoshita Oct 2015 A1
20150286340 Send Oct 2015 A1
20150329110 Stefan Nov 2015 A1
20150344028 Gieseke Dec 2015 A1
20150346727 Ramanujam Dec 2015 A1
20150360720 Li Dec 2015 A1
20150365401 Brown Dec 2015 A1
20150371541 Korman Dec 2015 A1
20150375741 Kiriya Dec 2015 A1
20150375742 Gebert Dec 2015 A1
20160012653 Soroka Jan 2016 A1
20160012726 Wang Jan 2016 A1
20160018821 Akita Jan 2016 A1
20160055749 Nicoll Feb 2016 A1
20160153778 Singh Feb 2016 A1
20160062354 Li Mar 2016 A1
20160068158 Elwart Mar 2016 A1
20160068187 Hata Mar 2016 A1
20160075369 Lavoie Mar 2016 A1
20160090055 Breed Mar 2016 A1
20160107689 Lee Apr 2016 A1
20160112846 Siswick Apr 2016 A1
20160114726 Nagata Apr 2016 A1
20160117926 Akavaram Apr 2016 A1
20160127664 Bruder May 2016 A1
20160139244 Holtman May 2016 A1
20160144857 Ohshima May 2016 A1
20160152263 Singh Jun 2016 A1
20160170494 Bonnet Jun 2016 A1
20160185389 Ishijima Jun 2016 A1
20160189435 Beaurepaire Jun 2016 A1
20160207528 Stefan Jul 2016 A1
20160224025 Petel Aug 2016 A1
20160229452 Lavoie Aug 2016 A1
20160236680 Lavoie Aug 2016 A1
20160249294 Lee Aug 2016 A1
20160257304 Lavoie Sep 2016 A1
20160272244 Imai Sep 2016 A1
20160282442 O'Mahony Sep 2016 A1
20160284217 Lee Sep 2016 A1
20160288657 Tokura Oct 2016 A1
20160300417 Hatton Oct 2016 A1
20160304087 Noh Oct 2016 A1
20160304088 Barth Oct 2016 A1
20160349362 Rohr Oct 2016 A1
20160321445 Turgeman Nov 2016 A1
20160321926 Mayer Nov 2016 A1
20160334797 Ross Nov 2016 A1
20160347280 Daman Dec 2016 A1
20160355125 Herbert Dec 2016 A1
20160357354 Chen Dec 2016 A1
20160358474 Uppal Dec 2016 A1
20160368489 Aich Dec 2016 A1
20160371607 Rosen Dec 2016 A1
20160371691 Kang Dec 2016 A1
20170001650 Park Jan 2017 A1
20170008563 Popken Jan 2017 A1
20170026198 Ochiai Jan 2017 A1
20170028985 Kiyokawa Feb 2017 A1
20170030722 Kojo Feb 2017 A1
20170032593 Patel Feb 2017 A1
20170072947 Lavoie Mar 2017 A1
20170073004 Shepard Mar 2017 A1
20170076603 Bostick Mar 2017 A1
20170097504 Takamatsu Apr 2017 A1
20170116790 Kusens Apr 2017 A1
20170123423 Sako May 2017 A1
20170129537 Kim May 2017 A1
20170129538 Stefan May 2017 A1
20170132482 Kim May 2017 A1
20170144654 Sham May 2017 A1
20170144656 Kim May 2017 A1
20170147995 Kalimi May 2017 A1
20170168479 Dang Jun 2017 A1
20170192428 Vogt Jul 2017 A1
20170200369 Miller Jul 2017 A1
20170203763 Yamada Jul 2017 A1
20170208438 Dickow Jul 2017 A1
20170297385 Kim Oct 2017 A1
20170297620 Lavoie Oct 2017 A1
20170301241 Urhahne Oct 2017 A1
20170308075 Whitaker Oct 2017 A1
20170336788 Iagnemma Nov 2017 A1
20170357317 Chaudhri Dec 2017 A1
20170371514 Cullin Dec 2017 A1
20180015878 McNew Jan 2018 A1
20180024559 Seo Jan 2018 A1
20180029591 Lavoie Feb 2018 A1
20180029641 Solar Feb 2018 A1
20180039264 Messner Feb 2018 A1
20180043884 Johnson Feb 2018 A1
20180056939 van Roermund Mar 2018 A1
20180056989 Donald Mar 2018 A1
20180082588 Hoffman, Jr. Mar 2018 A1
20180088330 Giannuzzi Mar 2018 A1
20180093663 Kim Apr 2018 A1
20180105165 Alarcon Apr 2018 A1
20180105167 Kim Apr 2018 A1
20180148094 Mukaiyama May 2018 A1
20180174460 Jung Jun 2018 A1
20180189971 Hildreth Jul 2018 A1
20180194344 Wang Jul 2018 A1
20180196963 Bandiwdekar Jul 2018 A1
20180224863 Fu Aug 2018 A1
20180236957 Min Aug 2018 A1
20180284802 Tsai Oct 2018 A1
20180286072 Tsai Oct 2018 A1
20180339654 Kim Nov 2018 A1
20180345851 Lavoie Dec 2018 A1
20180364731 Liu Dec 2018 A1
20190005445 Bahrainwala Jan 2019 A1
20190042003 Parazynski Feb 2019 A1
20190066503 Li Feb 2019 A1
20190103027 Wheeler Apr 2019 A1
20190137990 Golgiri May 2019 A1
Foreign Referenced Citations (101)
Number Date Country
101929921 Dec 2010 CN
103818204 May 2014 CN
104183153 Dec 2014 CN
104485013 Apr 2015 CN
104691544 Jun 2015 CN
103049159 Jul 2015 CN
105513412 Apr 2016 CN
105588563 May 2016 CN
105599703 May 2016 CN
105774691 Jul 2016 CN
106027749 Oct 2016 CN
205719000 Nov 2016 CN
106598630 Apr 2017 CN
106782572 May 2017 CN
106945662 Jul 2017 CN
104290751 Jan 2018 CN
3844340 Jul 1990 DE
19817142 Oct 1999 DE
19821163 Nov 1999 DE
102005006966 Sep 2005 DE
102006058213 Jul 2008 DE
102009051055 Jul 2010 DE
102016224529 Mar 2011 DE
102016226008 Mar 2011 DE
102010034129 Nov 2012 DE
102009060169 Jun 2013 DE
102011080148 Jul 2013 DE
102012200725 Sep 2013 DE
102009051055 Oct 2013 DE
102011122421 Jun 2014 DE
102012008858 Jun 2014 DE
102013016342 Jan 2015 DE
102013019904 Feb 2015 DE
102012215218 Apr 2015 DE
102012222972 May 2015 DE
102013004214 May 2015 DE
102013019771 Dec 2015 DE
102013213064 Feb 2016 DE
102014007915 Feb 2016 DE
102014011802 Feb 2016 DE
102014009077 Apr 2016 DE
102014226458 Jun 2016 DE
102014011864 Dec 2016 DE
102014015655 May 2017 DE
102014111570 Jun 2017 DE
102016214433 Jun 2017 DE
102015209976 Jul 2017 DE
102015221224 Dec 2017 DE
102016011916 Feb 2018 DE
102016125282 Jun 2018 DE
102016211021 Jun 2018 DE
2653367 Jun 2000 EP
2768718 Jun 2011 EP
2289768 Oct 2013 EP
2620351 Dec 2015 EP
2295281 Mar 2016 EP
2135788 Jun 2016 EP
3021798 Dec 2012 FR
2534471 Oct 2000 GB
2344481 Dec 2012 GB
2497836 Sep 2014 GB
2481324 Mar 2015 GB
2517835 May 2016 GB
2491720 Jul 2016 GB
5586450 May 2004 JP
5918683 Oct 2004 JP
2000293797 Jul 2005 JP
2004142543 Apr 2009 JP
2016119032 Apr 2009 JP
2018052188 Jan 2010 JP
2004287884 Jul 2014 JP
2005193742 Jul 2014 JP
2009090850 Jun 2016 JP
2014134082 Jul 2016 JP
2014125196 Apr 2018 JP
20130106005 Jun 2006 KR
20160039460 May 2008 KR
20160051993 Jan 2010 KR
101641267 Sep 2013 KR
20090040024 Apr 2016 KR
20100006714 May 2016 KR
WO 2010006981 Jan 2010 WO
WO 2017112444 Dec 2010 WO
WO 2017118510 Jun 2011 WO
WO 2006064544 Nov 2011 WO
WO 2017125514 Jan 2013 WO
WO 2008055567 Apr 2013 WO
WO 2011141096 Jul 2014 WO
WO 2013056959 May 2015 WO
WO 2013123813 Dec 2015 WO
WO 2014103492 Mar 2016 WO
WO 2015068032 Aug 2016 WO
WO 2015193058 Sep 2016 WO
WO 2016046269 Apr 2017 WO
WO 2016128200 May 2017 WO
WO 2016134822 Jun 2017 WO
WO 2017062448 Jun 2017 WO
WO 2017073159 Jun 2017 WO
WO 2017096307 Jun 2017 WO
WO 2017096728 Jul 2017 WO
WO 2017097942 Jul 2017 WO
Non-Patent Literature Citations (23)
Entry
US 9,772,406 B2, 09/2017, Liu (withdrawn)
Bill Howard, Bosch's View of the Future Car: Truly Keyless Entry, Haptic Feedback, Smart Parking, Cybersecurity, Jan. 9, 2017, 8 Pages.
Alberto Broggi and Elena Cardarelli, Vehicle Detection for Autonomous Parking Using a Soft-Cascade ADA Boost Classifier, Jun. 8, 2014.
Al-Sherbaz, Ali et al., Hybridisation of GNSS with other wireless/sensors technologies on board smartphones to offer seamless outdoors-indoors positioning for LBS applications, Apr. 2016, 3 pages.
Automatically Into the Parking Space—https://www.mercedes-benz.com/en/mercedes- benz/next/automation/automatically-into-the-parking-space/; Oct. 27, 2014.
ChargeItSpot Locations, Find a Phone Charging Station Near You, retrieved at https://chargeitspot.com/locations/ on Nov. 28, 2017.
Core System Requirements Specification (SyRS), Jun. 30, 2011, Research and Innovative Technology Administration.
DAIMLER AG, Remote Parking Pilot, Mar. 2016 (3 Pages).
Jingbin Liu, IParking: An Intelligent Indoor Location-Based Smartphone Parking Service, Oct. 31, 2012, 15 pages.
Land Rover develops a smartphone remote control for its SUVs, James Vincent, Jun. 18, 2015.
Land Rover, Land Rover Remote Control via Iphone RC Range Rover Sport Showcase—Autogeföhl, Retrieved from https://www.youtube.com/watch?v=4ZaaYNaEFio (at 43 seconds and 1 minute 42 seconds), Sep. 16, 2015.
Perpendicular Parking—https://prezi.com/toqmfyxriksl/perpendicular-parking/.
SafeCharge, Secure Cell Phone Charging Stations & Lockers, retrieved at https://www.thesafecharge.com on Nov. 28, 2017.
Search Report dated Jan. 19, 2018 for GB Patent Application No. 1711988.4 (3 pages).
Search Report dated Jul. 11, 2017 for GB Patent Application No. 1700447.4 (3 Pages).
Search Report dated May 21, 2018 for Great Britain Patent Application No. GB 1800277.4 (5 Pages).
Search Report dated Nov. 22, 2018 for GB Patent Application No. GB 1809829.3 (6 pages).
Search Report dated Nov. 27, 2018 for GB Patent Application No. GB 1809112.4 (3 pages).
Search Report dated Nov. 28, 2017, for GB Patent Application No. GB 1710916.6 (4 Pages).
Search Report dated Nov. 28, 2018 for GB Patent Application No. GB 1809842.6 (5 pages).
Search Report dated Oct. 10, 2018 for GB Patent Application No. 1806499.8 (4 pages).
Tesla Model S Owner's Manual v2018.44. Oct. 29, 2018.
Vehicle's Orientation Measurement Method by Single-Camera Image Using Known-Shaped Planar Object, Nozomu Araki, Takao Sato, Yasuo Konishi and Hiroyuki Ishigaki, 2010.
Related Publications (1)
Number Date Country
20190220001 A1 Jul 2019 US