Apple Wins Two Project Titan Patents covering the Control of Vehicle Tractive Forces & Radar that Captures 4D-Info
The U.S. Patent and Trademark Office granted Apple 59 newly granted patents today. In this report we cover two of Apple's latest Project Titan patents covering road stability and a next-gen dual-radar system that will assist in the aesthetics of an autonomous or semi autonomous vehicle while providing high resolution and highly accurate 4D information of tracked objects.
Road Friction Coefficient Estimation System
Apple notes in their patent background that advanced driver assistance systems (ADAS) are sub-systems to automate, adapt, and enhance a vehicle's control system for better driving. Generally, the ADAS system relies on inputs from multiple data sources located onboard a vehicle to alert or enable safeguards that aid in controlling the vehicle.
A valuable parameter for ADAS and autonomous vehicular operation is road friction, which may influence following distance, vehicle speed, and driver intervention time and distance.
Wheel slip, which is a function of road friction, is a vehicular dynamic that can be used to estimate road friction and control vehicle tractive forces. However, estimating road friction in this manner may necessitate an excitation on the vehicle, such as engagement of the brakes. This type of road friction estimation generally cannot estimate road friction on the road ahead of the vehicle's current position, or may not provide a reliable estimate during straight-line driving, when no excitation is present.
Apple's invention covers a method that may include the operations of receiving lateral force measurements from a first device connection to a first vehicle as the first device is in communication with a road surface, estimating road friction coefficients of the road surface based at least on the received lateral force measurements, and collecting a first set of road surface characteristics sensor measurements from a first set of sensors of the first vehicle.
The method may also include the operations of combining the estimated road friction coefficients and the collected first set of road surface characteristics sensor measurements to generate a training data set associated with operation of the first vehicle, deriving a regression function from the training data set, wherein the regression function predicts real-time road friction coefficients of the road surface, and storing the regression function in a remote server in communication with the first vehicle through a communication network.
Aspects of invention involve systems, methods, devices and the like for obtaining real-time friction coefficient estimations of a road surface.
In one embodiment, a regression function is learned using a training data set which correlates input data measurements arriving from onboard system sensors and estimated road-friction coefficients for that input data measurement arriving from an extension system. The learned regression function can be used to predict real-time road friction coefficients.
The road friction estimate can be associated with specific regions around the vehicle, enabling prediction of road friction of the road ahead of a vehicle. In one embodiment, the onboard system sensors may be light detection and ranging (LIDAR) sensors, radio detection and ranging (RADAR) sensors, cameras and the like, located on a system like a vehicle that can be used to capture the road surface characteristics.
The extension system can be a trailer or other device equipped with components that measure a lateral force on the wheels of the extension system for use in obtaining the coefficient estimates of the extension system.
Apple's patent FIG. 2 below is a diagram illustrating a system with onboard sensors and other data sources used for automatic road friction coefficient estimation; FIG. 3A is a flowchart of a method for defining a regression function that can be used for computing real-time road friction coefficients; FIG. 4 is a functional block diagram of an electronic system including operational units arranged to perform various operations of the presently disclosed technology.
For more details on Apple's granted patent number 10,442,439 click here.
Radar System including Dual Receive Array
Apple's second Project Titan patent granted under number 10,446,938 relates to a radar system that may include (1) a transmit antenna array to emit a radar beam toward a selected portion of a field of view, as well (2) as a vertical receive antenna array and a horizontal receive antenna array.
Apple's patent FIG. 1 is a block diagram of an example radar system employing dual receive arrays to provide azimuth and elevation information. When operated as described, the new radar system may generate four-dimensional (4D) information to facilitate high resolution, high accuracy detection and tracking of potential objects or targets.
Apple's patent FIG. 7 above is a block diagram of an example multiple-radar system employing the example radar system of FIG. 1 to facilitate multiple fields of view.
One of the benefits of this next-gen radar system for autonomous or semi-autonomous vehicles is that some of the key hardware could be positioned behind a fascia (car dashboard) or fiberglass bumper or fender of a vehicle, to essentially hide the radome to improve the overall aesthetics of the vehicle.
For more details, check out the patent here.
About Making Comments on our Site: Patently Apple reserves the right to post, dismiss or edit any comments.