Obstacles located in an external environment of a vehicle can be classified. At least a portion of the external environment can be sensed using one or more sensors to acquire sensor data. An obstacle candidate can be identified based on the acquired sensor data. An occlusion status for the identified obstacle candidate can be determined. The occlusion status can be a ratio of acquired sensor data for the obstacle candidate that is occluded to all acquired sensor data for the obstacle candidate. A classification for the obstacle candidate can be determined based on the determined occlusion status. A driving maneuver for the vehicle can be determined at least partially based on the determined classification for the obstacle candidate. The vehicle can be caused to implement the determined driving maneuver. The vehicle can be an autonomous vehicle.

A method, arrangement and system are described for estimating one or more vehicle cornering stiffness parameters (c.sub.f, c.sub.r) in a linear vehicle operating region. The method includes reading sensor data representative of at least vehicle (1) longitudinal velocity (v.sub.x), vehicle lateral acceleration (a.sub.y), vehicle yaw rate (.sub.z) and vehicle steering angle (), determining from the read sensor data if the cornering stiffness parameters (c.sub.f, c.sub.r) are observable, and if so providing an estimate of the cornering stiffness parameters (c.sub.f, c.sub.r) using a bicycle model that includes a model of tire relaxation dynamics.

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 propulsion control system for a vehicle includes a first vehicle sensor, a second vehicle sensor, and a controller in electrical communication with the first vehicle sensor and the second vehicle sensor. The controller is programmed to determine a closed-loop noise level in a cabin of the vehicle using the first vehicle sensor. The controller is further programmed to determine an open-loop noise level in the cabin of the vehicle using the second vehicle sensor. The controller is further programmed to adjust a propulsion calibration value of the vehicle based at least in part on the closed-loop noise level and the open-loop noise level.

A vehicle control device is provided, which includes an engine, an engine control mechanism configured to control torque generated by the engine, and a processor configured to execute a vehicle attitude controlling module to perform a vehicle attitude control in which the engine control mechanism is controlled to reduce the torque so as to decelerate the vehicle, when a condition that the vehicle is traveling and a steering angle related value that is related to a steering angle of a steering device increases is satisfied, and a preventing module to prevent a combustion frequency of the engine per unit time from falling below a given value while the vehicle attitude controlling module executes the vehicle attitude control.

A method and system for applying vehicle settings to a vehicle that include storing at least one user settings profile on a plurality of components associated with the vehicle based on a computing device that is used to create or update the at least one user settings profile. The system and method also include determining if the at least one user settings profile has been updated since a last ignition cycle of the vehicle. The system and method further include selecting the at least one user settings profile to be applied to control a vehicle system of the vehicle from at least one component of the plurality of components based on if the at least one user settings profile has been updated since the last ignition cycle of the vehicle and on a connection of at least: a first portable device and a second portable device to the vehicle.

A vehicle control system includes a first error module that determines a first yaw error based on a difference between a yaw rate of the vehicle and a target yaw rate. A second error module determines a second yaw error based on the first yaw error and a target yaw error. A target yaw error module sets the target yaw error based on a skill level of a driver of the vehicle. An adjustment module selectively one of increases and decreases a target adjustment when the second yaw error is greater than a first predetermined threshold. An actuator control module, in response to the increase in the target adjustment, actuates a dynamics actuator of the vehicle.

A controller of a motor vehicle comprises a drive motor, wheels, braking devices for the wheels, said braking devices being separately controllable by the controller, an ambient sensor, a driving status sensor and a steering system. For increasing the driving stability, a steering angle is determinable by the controller from signals of the ambient sensor and of the driving status sensor, said steering angle providing a stable driving status in addition to a targeted braking of the wheels, and the steering angle is adjustable at the steering system in order to keep the motor vehicle on the paved road, in particular when driving along a curve, so that the motor vehicle remains on an intersecting plane of the possible dynamic vehicle area ahead with an actual road without skidding or colliding with other obstacles.

Systems and methods are provided for determining a road surface characteristic. In one implementation, a system includes at least one processing device programmed to receive, from at least one camera, at least two images representative of an environment of a vehicle; align at least a portion of the at least two images using estimated motion of the vehicle; provide, to a trained system configured to determine a characteristic of the road surface, at least the aligned portions of the at least two images; receive, from the trained system, the determined characteristic of the road surface; and provide, to a vehicle control system, based on at least the determined characteristic of the road surface, control information for changing at least one setting of the vehicle control system.

A tire longitudinal stiffness estimation system includes an electronic communication system disposed on a vehicle. A sensor is disposed on the vehicle in communication with the electronic communication system, and a processor is accessible through the electronic communication system. The sensor measures parameters associated with the vehicle and communicates data for the parameters to the processor. A mu slip curve generator receives the parameters to generate a mu slip curve in real time from the data. An extraction module extracts raw data from a linear portion of the mu slip curve. A denoising module de-noises the raw data from the mu slip curve by determining a vector for the raw data, an orientation of the vector, and a heading of the vector. The denoising module generates de-noised data, and a stiffness calculator receives the de-noised data and generates a longitudinal stiffness estimate for the tire.