A method to park a vehicle in a parking space using a parking assistant is provided. The course of a parking maneuver is dynamically adapted to boundaries of the parking space that are changed during the parking maneuver by determining whether and in which direction the boundaries of the parking space change during the parking maneuver. An originally determined first trajectory is replaced by a second trajectory that is adapted to changed boundaries of the parking space and along which the parking maneuver is continued.

The present invention relates to a method for collision avoidance for a host vehicle, the method comprising: detecting a target in the vicinity of the vehicle; determining that the host vehicle is travelling on a collision course with the target; detecting a user initiated steering action for steering the vehicle towards one side of the target; determining a degree of understeering of the host vehicle; when the degree of understeering exceeds a first understeering threshold, controlling a steering control system of the vehicle to counteract the user initiated steering action to thereby reduce the degree of understeering. The invention further relates to an evasive steering system.

An automatic steering control apparatus includes a target-path acquisition unit that acquires a target path that is to be a traveling path of the vehicle, a target-rudder-angle acquisition unit that acquires a target rudder angle that is to be a rudder angle in the vehicle, on the basis of the target path, a sideslip-angle estimation unit that estimates a sideslip angle in the vehicle that is traveling at the target rudder angle, on the basis of the target rudder angle and a vehicle condition of the vehicle, and an automatic steering control unit. The automatic steering control unit performs at least one of stopping of automatic steering control and controlling of a steering-quantity regulation gain for regulating the target rudder angle, when the estimated sideslip angle is equal to or greater than a predetermined value.

Systems and methods are provided for generating data indicative of a friction associated with a driving surface, and for using the friction data in association with one or more vehicles. In one example, a computing system can detect a stop associated with a vehicle and initiate a steering action of the vehicle during the stop. The steering action is associated with movement of at least one tire of the vehicle relative to a driving surface. The computing system can obtain operational data associated with the steering action during the stop of the vehicle. The computing system can determine a friction associated with the driving surface based at least in part on the operational data associated with the steering action. The computing system can generate data indicative of the friction associated with the driving surface.

A vehicle travel control apparatus includes an anomaly monitoring section for determining, through monitoring, whether or not a driver is in an anomalous state in which the driver has lost his or her ability to drive the vehicle, and a deceleration section for automatically stopping the vehicle by decelerating the vehicle after a final anomaly determined time which is a point in time when the anomaly monitoring section finally determines that the driver is in the anomalous state. The deceleration section prohibits deceleration of the vehicle in the case where the deceleration section determines that the vehicle is present in the deceleration prohibited section after the final anomaly determination time.

The subject disclosure relates to features that improve safety for autonomous vehicle (AV) maneuvers and in particular, that improve safety for parallel parking. A process of the disclosed technology includes steps for initiating a parking maneuver, navigating the AV into a parking location, and detecting a roadway grade with respect to a direction of the AV. In some aspects, the process can further include steps for automatically adjusting a wheel angle of the AV based on the roadway grade with respect to the direction of the AV. Systems and machine-readable media are also provided.

A vehicle is provided. The vehicle may include an engine that is configured to auto-stop and auto-start. The system may also include a controller programmed to power an electrical actuator coupled to a steering mechanism to synchronize a drive angle of the vehicle and a steering wheel angle of the vehicle, in response to a parameter indicative of a likelihood of a wheel slip event exceeding a threshold and the steering-wheel angle being greater than a predetermined threshold.

A lane keeping controller includes a first initial target steering angle calculator, a second initial target steering angle calculator, and a steering angle calculator. A first arithmetic unit of the first initial target steering angle calculator performs a first arithmetic operation to calculate a first initial target steering angle using a lane curvature so that a vehicle runs along the lane curvature. A second arithmetic unit of the second initial target steering angle calculator performs a second arithmetic operation to calculate a second initial target steering angle using a yaw angle deviation so that a yaw angle to lane agrees with a target yaw angle. During execution of override control, the lane curvature and the yaw angle deviation are not corrected and a target steering angle is made to be small in comparison with that during execution of normal lane keeping control.

The disclosure relates to assessing and responding to wheel slippage and estimating road friction for a road surface. For instance, a vehicle may be controlled in an autonomous driving mode in order to follow a trajectory. A wheel of the vehicle may be determined to be slipping such that the vehicle has limited steering control. In response to determining that the wheel is slipping, steering of one or more wheels may be controlled in order to orient the one or more wheels towards the trajectory in order to allow the vehicle to proceed towards the trajectory when the wheel is no longer slipping. In addition, the road friction may be estimated based on the determination that the wheel is slipping. The vehicle may be controlled in the autonomous driving mode based on the estimated road friction.

Automatic steering control is essential part for autonomous vehicle which controls the steering in various scenarios to achieve safe and comfortable driving. The present subject matter discloses a system and method for steering control during autonomous vehicle driving using neural networks. In an embodiment, a lane side offset, a radius of curvature and a speed of a vehicle are received. Further, an ideal steering angle required to keep the vehicle at a center of a lane is determined using the radius of curvature. Furthermore, an offset error is determined based on the lane side offset using a reference offset. In addition, a corrective steering angle is determined using the radius of curvature, speed of the vehicle and offset error. Also, a steering angle required to keep the vehicle at a center of a lane is computed using the ideal steering angle and the corrective steering angle.