Determining classification(s) for object(s) in an environment of autonomous vehicle, and controlling the vehicle based on the determined classification(s). For example, autonomous steering, acceleration, and/or deceleration of the vehicle can be controlled based on determined pose(s) and/or classification(s) for objects in the environment. The control can be based on the pose(s) and/or classification(s) directly, and/or based on movement parameter(s), for the object(s), determined based on the pose(s) and/or classification(s). In many implementations, pose(s) and/or classification(s) of environmental object(s) are determined based on data from a phase coherent Light Detection and Ranging (LIDAR) component of the vehicle, such as a phase coherent LIDAR monopulse component and/or a frequency-modulated continuous wave (FMCW) LIDAR component.

An exemplary method for detecting a rough road includes the steps of providing a vehicle sensor, the vehicle sensor configured to measure a steering torque of a vehicle, receiving a steering torque data signal from the vehicle sensor, generating a road condition data signal from the steering torque data signal, evaluating the road condition data signal over a specified time interval, comparing the road condition data signal with one or more thresholds, and determining whether rough road conditions exist based on the comparison of the road condition data signal with the one or more thresholds over the specified time interval.

The present disclosure is related to hybrid vehicles. The teachings thereof may be embodied in vehicles as well as operation schemes meant to increase energy efficiency, such as a method comprising: detecting multiple consumption parameters of the hybrid vehicle; determining a future state of charge of a traction battery of the vehicle by mapping the consumption parameters onto a state-of-charge value, wherein the mapping includes classifying the multiple consumption parameters according to trainable class boundaries; training the class boundaries based at least in part on the detected consumption parameters and an associated measured state of charge; and adjusting an operating parameter of a traction power component of the hybrid vehicle according to the determined future state of charge.

Determining classification(s) for object(s) in an environment of autonomous vehicle, and controlling the vehicle based on the determined classification(s). For example, autonomous steering, acceleration, and/or deceleration of the vehicle can be controlled based on determined pose(s) and/or classification(s) for objects in the environment. The control can be based on the pose(s) and/or classification(s) directly, and/or based on movement parameter(s), for the object(s), determined based on the pose(s) and/or classification(s). In many implementations, pose(s) and/or classification(s) of environmental object(s) are determined based on data from a phase coherent Light Detection and Ranging (LIDAR) component of the vehicle, such as a phase coherent LIDAR monopulse component and/or a frequency-modulated continuous wave (FMCW) LIDAR component.

A method performed by a computing device for controlling an automated guided vehicle according to an embodiment of the present disclosure includes obtaining information on a movable area including nodes arranged in a grid pattern, obtaining information on a moving path connecting a source node and a destination node existing in the movable area, wherein the moving path includes a plurality of moving nodes, and reserving at least some of the moving nodes located between a current node and the destination node by using information on the current node occupied by an automated guided vehicle according to movement of the automated guided vehicle.

A method and system for applying vehicle settings to a vehicle. The method and system include receiving a device identification (ID) from at least one of: a first portable device and a second portable device. The method and system additionally include identifying a user settings profile that is associated to the device ID. The method and system also include determining if the user settings profile has been updated since a last ignition cycle of the vehicle. The method and system further include applying the user settings profile to control a vehicle system, wherein the user settings profile is retrieved from at least one of: a central user settings data repository, a telematics unit of the vehicle, and a head unit of the vehicle.

A method for the delayed parking optimization of an autonomous vehicle includes activating a delayed parking optimization mode in a vehicle and, during the delayed parking optimization mode, detecting a presence of one or more passengers in the vehicle. On condition that no further passengers are detected in the vehicle, a delay period is initiated subsequent to which the vehicle engages the transmission of the vehicle from park to reverse, applies power to cause the vehicle to back out of the parking spot onto the roadway, engages the transmission into drive, applies power and manages steering and braking of the vehicle in order to navigate the vehicle forward on the roadway beyond the parking spot, engages the transmission into reverse, applies power and manages steering of the vehicle to cause the vehicle to back into the parking spot and engages the transmission of the vehicle into park.

The present disclosure is related to hybrid vehicles. The teachings thereof may be embodied in vehicles as well as operation schemes meant to increase energy efficiency, such as a method comprising: detecting multiple consumption parameters of the hybrid vehicle; determining a future state of charge of a traction battery of the vehicle by mapping the consumption parameters onto a state-of-charge value, wherein the mapping includes classifying the multiple consumption parameters according to trainable class boundaries; training the class boundaries based at least in part on the detected consumption parameters and an associated measured state of charge; and adjusting an operating parameter of a traction power component of the hybrid vehicle according to the determined future state of charge.

Steering a vehicle may include applying a net brake-steering force to a steered wheel sufficient to affect a steering moment upon the steered wheel sufficient to move the steered wheel away from a zero steering angle, and resisting movement of the steered wheel back toward the zero steering angle.

The system disclosed herein is for communication between a first electric vehicle and a second electric vehicle following the first electric vehicle on a route. The system includes a controller communicatively coupled to a battery associated with the second electric vehicle. The controller is configured to acquire a set of operating parameters associated with the first electric vehicle from the first electric vehicle and generate an adjustment command configured to adjust a component operating parameter of at least one component of the second electric vehicle based on the set of operating parameters. The set of operating parameters includes charge station data indicating whether a charge station along the route is unavailable for use.