Apple Invents an Enhanced Automotive Passive Entry System without mentioning Autonomous Vehicles once
Today the US Patent & Trademark Office published a patent application from Apple that relates to an enhanced automotive passive entry system. The patent makes no mention that it applies to autonomous vehicles which is interesting. The system could use an iPhone, Apple Watch or other wearable device to lock and unlock vehicles doors, open the trunk, start the vehicle and may support an in-vehicle wireless charging system for Apple devices. Apple also notes that to authenticate the fob in relation to a vehicle, it will utilize encryption to foil hackers. Lastly, a unique aspect to the system is that it uses machine learning.
Apple's Patent Background
Modern cars allow entry using a key fob, and some cars allow starting by a button when the key fob is inside the car. Such operation is called passive entry and passive start, which use a position of the key fob to unlock the car, allow starting the car, and provide other functionality. The location of the key fob is determined using magnetic signals emitted from magnetic antennas in the car. The magnetic signals are measured by the key fob and sent to the car for determining a location of the key fob.
The key fob can be bulky and be an additional item that a user must carry. Further, the magnetic fields are short range, and current techniques are susceptible to hackers, which can allow a thief to access the car and potentially steal it. Apple's invention is to overcome these problems.
Invention: Enhanced Automotive Passive Entry
Apple's invention covers methods and devices for allowing a mobile device (e.g., a key fob or a consumer electronic device, such as an iPhone, Apple Watch or other wearable device) to interact with a vehicle such that a location of the mobile device can be determined by the vehicle, thereby enabling certain functionality of the vehicle.
According to one embodiment, the mobile device and the vehicle can include radiofrequency (RF) antenna(s) and magnetic antenna(s). The mobile device can measure signal properties of the RF signals and the magnetic signals from the vehicle that relate to a distance of the device's antenna from a vehicle antenna.
Examples of signal properties include a received signal strength indicator (RSSI) and a time-of-flight value (e.g., a round trip time, RTT). In some implementations, the magnetic antenna(s) can measure an RSSI of the magnetic signals, and the RF antenna(s) can measure a time-of-flight value. The various types of antennas can be used in combination or separately. For example, the RF antenna(s) can be used to determine changes in location of the mobile device far from the vehicle (e.g., to determine a user is approaching the vehicle), while the magnetic antenna(s) can be used to determine a location of the mobile device when the mobile device is near or inside the vehicle. Either the mobile device or the vehicle can determine the location.
The location can be provided to a control unit of the vehicle, thereby enabling the control unit to perform a prescribed operation of the vehicle, such as unlocking one or more doors or allowing use of a start button.
In some embodiments, magnetic charging coils can be reused as a magnetic antenna. In other embodiments, a near-field communications (NFC) antenna can be reused as a magnetic antenna for use in determining a location of the device. Such a reuse of one or both can avoid a need for dedicated magnetic antennas and providing for a smaller and less expensive mobile device. In other implementations, a vehicle can have three-dimensional magnetic antennas, thereby allowing the mobile device to have only one magnetic antenna.
According to another embodiment, signal values measured from one or more antennas (e.g., RF or magnetic) can be used with a machine learning model to classify a location of the mobile device as being within one of a set of regions.
The set of regions can include a first subset of one or more regions outside the vehicle and a second subset of one or more regions outside the vehicle. The machine learning model can be trained using various sets of signal values measured at locations across the plurality of regions. The particular region can be provided to a control unit of the vehicle, thereby enabling the control unit to perform a prescribed operation of the vehicle.
Apple's patent FIG. 1 below shows a vehicle with an LF location system; FIG. 2 shows the internals of a key fob.
Apple's patent FIG. 3 below shows the high-level system design for an LF passive entry/passive start automotive system; FIG. 7 shows a mobile device having components for data collection, processing, and transfer of measurements and ancillary data.
Apple's patent FIG. 9 below shows a region-based passive entry/passive start automotive system; FIG. 11 shows an implementation of the machine-learning model for identifying which region a mobile device is located relative to a vehicle.
Random Points in the Patent Application
Another improvement to user experience can be to detect the user's intent when approaching or leaving the automobile, e.g., the user approaching the automobile likely has the intent to unlock the vehicle if the vehicle is currently locked. Additionally, as the user approaches the automobile, the automobile can turn on the interior lights, enable the heating system, and unlock the doors or trunk, without requiring physical interaction and doing so securely. Such longer range intent can be achieved as the power of RF signals decays as l/r.sup.2. Another improvement can be to reduce the susceptibility of an LF magnetic man-in-the-middle attack.
Apple hints that antenna system in the vehicle may allow smartphones with charging coils, like the iPhone 8, iPhone X and beyond to be recharged. In addition, Apple notes that "additional coils can be added to the mobile device to provide full 3-D functionality, or the automobile's existing LF antennas can be augmented with additional antennas to generate magnetic fields in three orthogonal directions."
Further into the patent filing Apple notes that "In some embodiments, the mobile device can always be listening in a low-power mode (e.g., using BTLE) for signal in a particular band. If there is some level of signal in that band, the mobile device can wake up and analyze the signal. In some implementations, the detected signal can include an encrypted message and/or a random value that the mobile device is to encrypt. The mobile device can store an encryption key (symmetric or asymmetric) that can decrypt the encrypted message so as to confirm an expected value of the message, thereby authenticating the vehicle. The same or a different key can be used to encrypt the random value, which can be sent to the vehicle in order for the vehicle to authenticate the mobile device. This messaging can occur over RF (e.g., over 400-700 MHz)."
Lastly, the patent never mentions an autonomous vehicle even once. That could mean the system could be for licensing to automakers or that Apple is planning and designing vehicle systems beyond the autonomous vehicle market.
Apple's patent application 20180234797 was filed back in Q1 2018. Considering that this is a patent application, the timing of such a product to market is unknown at this time.
Some of the Inventors of this Invention
Xu Chen: Senior ASIC Design Engineer at Apple; Specialize in logic design for CPU and memory subsystem - Skilled in Machine Learning, including Computer Vision and Artificial Neural Network.
Robert Brumley: Wireless Technologies; Location/Motion Engineering Manager at Apple
William Bencze: Software Engineering Manager at Apple / Location Software Engineer Manager; Extensive technical expertise in satellite navigation and location systems, RF systems; his LinkedIn page says "We're Hiring!"
Rob Mayor: Director of Location Technologies at Apple
Brent Ledvina: Location Software Manager at Apple
Indranil Sen: Sr. Manager Wireless Design at Apple
Mohit Narang: Sr. Director - Wireless Design
Shang-Te Yang: Wireless Systems Engineer
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