Systems and methods use cameras to provide autonomous navigation features. In one implementation, a method for navigating a user vehicle may include acquiring, using at least one image capture device, a plurality of images of an area in a vicinity of the user vehicle; determining from the plurality of images a first lane constraint on a first side of the user vehicle and a second lane constraint on a second side of the user vehicle opposite to the first side of the user vehicle; enabling the user vehicle to pass a target vehicle if the target vehicle is determined to be in a lane different from the lane in which the user vehicle is traveling; and causing the user vehicle to abort the pass before completion of the pass, if the target vehicle is determined to be entering the lane in which the user vehicle is traveling.

Systems and methods use cameras to provide autonomous navigation features. In one implementation, a method for navigating a user vehicle may include acquiring, using at least one image capture device, a plurality of images of an area in a vicinity of the user vehicle; determining from the plurality of images a first lane constraint on a first side of the user vehicle and a second lane constraint on a second side of the user vehicle opposite to the first side of the user vehicle; enabling the user vehicle to pass a target vehicle if the target vehicle is determined to be in a lane different from the lane in which the user vehicle is traveling; and causing the user vehicle to abort the pass before completion of the pass, if the target vehicle is determined to be entering the lane in which the user vehicle is traveling.

Embodiments of the present disclosure relate generally to generating and utilizing three-dimensional terrain maps for vehicular control. Other embodiments may be described and/or claimed.

Embodiments of the present disclosure relate generally to generating and utilizing three-dimensional terrain maps for vehicular control. Other embodiments may be described and/or claimed.

A method includes receiving a first signal from a first button circuit in a first location indicating possible interaction with a corresponding interactable element by a user, and receiving sensed signal data from a first sensor circuit indicating changes in electrical properties of an electrode of the first sensor circuit The method includes determining whether the sensed signal data indicates detection of a first frequency identifying the first location based on receiving the first signal indicating the possible interaction with the corresponding interactable element. When the sensed signal data indicates detection of the first frequency identifying the first location, performance of a functionality associated with the corresponding interactable element is facilitated.

A method includes receiving a first signal from a first button circuit in a first location indicating possible interaction with a corresponding interactable element by a user, and receiving sensed signal data from a first sensor circuit indicating changes in electrical properties of an electrode of the first sensor circuit The method includes determining whether the sensed signal data indicates detection of a first frequency identifying the first location based on receiving the first signal indicating the possible interaction with the corresponding interactable element. When the sensed signal data indicates detection of the first frequency identifying the first location, performance of a functionality associated with the corresponding interactable element is facilitated.

A method for determining a friction coefficient for a contact between a tire of a vehicle and a roadway. The method includes processing sensor signals in order to generate processed sensor signals. The sensor signals represent state data that are read in at least by at least one detection device and that are correlatable with the friction coefficient. The processed sensor signals represent at least one preliminary friction coefficient. The method also includes ascertaining the friction coefficient using the processed sensor signals and a regression model.

A method for determining a friction coefficient for a contact between a tire of a vehicle and a roadway. The method includes processing sensor signals in order to generate processed sensor signals. The sensor signals represent state data that are read in at least by at least one detection device and that are correlatable with the friction coefficient. The processed sensor signals represent at least one preliminary friction coefficient. The method also includes ascertaining the friction coefficient using the processed sensor signals and a regression model.

The present invention relates to a method of cooperatively coordinating future driving maneuvers of a vehicle with fellow maneuvers of at least one fellow vehicle, wherein trajectories for the vehicle are rated with an effort value each, trajectories and fellow trajectories of the fellow vehicle are combined into tuples, the trajectory and the associated effort value of a collision-free tuple are selected as reference trajectory and reference effort value, trajectories with a lower effort value than the reference effort value are classified as demand trajectories, trajectories with higher effort value than the reference effort value are classified as alternative trajectories, and a data packet having a trajectory set consisting of the reference trajectory and the associated reference effort value as well as at least one trajectory from a group comprising the demand trajectories and the alternative trajectories as well as the respective effort values is transmitted to the fellow vehicle.

The present teaching relates to method, system, medium, and implementation of in-situ perception in an autonomous driving vehicle. A plurality of types of sensor data are acquired continuously via a plurality of types of sensors deployed on the vehicle, where the plurality of types of sensor data provide information about surrounding of the vehicle. One or more items surrounding the vehicle are tracked, based on some models, from a first of the plurality of types of sensor data from a first type of the plurality of types of sensors. A second of the plurality of types of sensor data are obtained from a second type of the plurality of sensors and are used to generate validation base data. Some of the one or more items are labeled, automatically, via validation base data to generate labeled at least some item, which is to be used to generate model updated information for updating the at least one model.