A new Project Titan Patent from Apple covers an Autonomous Navigation System that includes an ‘Intention Recognition’ Module

Last Thursday the US Patent & Trademark Office published a patent application from Apple that relates to an autonomous navigation system of a vehicle which includes various dynamic elements, based on predicting trajectories of the vehicle and real-world dynamic elements based on recognizing contextual cues using a new “intention recognition’ module.

Apple notes that 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, autonomous navigation includes navigating a vehicle in response to detection of one or more traffic participants in the environment through which the vehicle is being navigated. For example, where another vehicle is detected ahead of the navigated vehicle and is determined to be moving slower than the navigated vehicle, such that the navigated vehicle is approaching the other vehicle, the navigated vehicle can be slowed or stopped to prevent the vehicle paths intersecting. In another example, where a pedestrian is identified near an edge of the roadway along which the vehicle is being navigated, the vehicle can be slowed or stopped in response to detection of the pedestrian.

In some cases, 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 cases, the ANS generates a driving route through an external environment based at least in part upon various static elements and dynamic elements included in the external environment. Static elements can include roadway features, including roadway lanes, curbs, etc., traffic signs and traffic signals, flora, artificial structures, inanimate objects, etc. Dynamic elements can include 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.

In some cases, the ANS generates a driving route based on various detected static elements and dynamic elements in the external environment, where the driving route includes a route, via which the vehicle can be navigated through the external environment, which avoids intersection of the vehicle with one or more static elements, dynamic elements, etc. located in the external environment.

For example, a driving route through an external environment can include a route which avoids intersection with a static obstacle in the roadway along which the vehicle is being navigated, a traffic participant which includes another vehicle navigating along the roadway in an opposite direction of travel relative to the vehicle, etc.

In some cases, the ANS, to generate a driving route which avoids intersection of the vehicle with various dynamic elements in an external environment, generates predicted trajectories of one or more dynamic elements, including traffic participants, through at least a portion of the external environment.

Apple’s patent FIG. 1 below illustrates a schematic block diagram of a vehicle which comprises an autonomous navigation system (ANS); FIG. 3 illustrates an overhead view of an environment in which multiple dynamic elements are located, including a vehicle which is autonomously navigated through the environment and includes a set of sensors which can generate sensor data associated with the dynamic elements and an autonomous navigation system which can determine a particular predicted trajectory of a dynamic element based on contextual cues identified in the sensor data.

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Apple’s patent FIG. 6 below illustrates autonomously navigating a vehicle through an external environment based on a predicted trajectory of a dynamic element in the external environment, according to some embodiments. The generating 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.

Apple’s patent application 20200302194 that was published last Thursday by the U.S. Patent Office was filed back in June 11, 2020. Considering that this is a patent application, the timing of such a product to market is unknown at this time. Review our Project Titan Archives to find additional patents on this subject matter.

Article Source: https://www.patentlyapple.com/patently-apple/2020/09/a-new-project-titan-patent-from-apple-covers-an-autonomous-navigation-system-that-includes-an-intention-recognition-module.html