Abstract: A method for controlling automated vehicle acceleration and braking includes detecting, via at least one vehicle object sensor of a host vehicle, a closest-in-path (CIP) target vehicle ahead of the host vehicle, obtaining a path history of the CIP target vehicle, the path history including multiple historic positions of the CIP target vehicle at specified time intervals, obtaining a path history of the host vehicle, the path history of the host vehicle including multiple historic positions of the host vehicle at the specified time intervals, comparing the path history of the CIP target vehicle to the path history of the host vehicle to determine a divergence index, and in response to the divergence index being less than a specified divergence threshold, controlling automated acceleration and braking of the host vehicle based at least in part on tracked movement of the CIP target vehicle.

Abstract: A vehicle control system for driving behavior vehicle detection includes at least one vehicle object detector configured to detect motion of target vehicles within an object detection range of a host vehicle, a vehicle user interface configured to display a visual indication to a driver of the host vehicle, and a vehicle control module configured to obtain detected motion parameters of the one or more target vehicles via the at least one vehicle object detector, determine a hazard index for each of the one or more target vehicles, according to the detected motion parameters, and in response to the hazard index exceeding a specified threshold value for at least one of the one or more vehicles, update the vehicle user interface to provide a visual notification of identified driving behavior exceeding the specified threshold value for the at least one of the one or more target vehicles.

Abstract: Methods and systems for providing driving assistance in a vehicle. In one embodiment, a method includes: receiving, by a processor, vehicle data from a sensor system of the vehicle; determining, by a processor, a path of the vehicle based on the steering data; expanding, by the processor, the path of the vehicle to a path area based on probabilistic uncertainty bound prediction; determining, by the processor, a target object based on the path area and object data that identifies objects within the environment of the vehicle; and generating, by the processor, control signals to vehicle actuators to control the vehicle based on the target object.

Abstract: Vehicles and related systems and methods are provided for predicting a future maneuver expected to be executed by a driver. One method involves determining a combined probability for a potential maneuver based on constituent probabilities corresponding to different vehicle state variables, and environmental conditions using one or more tuning parameters specific to the respective combination of maneuver and vehicle state variable, determining an adjusted probability for the potential maneuver based at least in part on the combined probability and one or more contextual state variables corresponding to a current operating context for the vehicle, adapted to driver behavior and driving style, identifying the potential maneuver as an expected maneuver to be executed by a driver of the vehicle based on the adjusted probability, and automatically initiating one or more actions in a manner that is influenced by the expected maneuver.

Abstract: Methods and systems are provided that include one or more sensors configured to obtain sensor data pertaining to both a driver of a vehicle and an environment surrounding the vehicle; and a processor that is coupled to the one or more sensors and that is configured to at least facilitate determining, using the sensor data, when the driver is incapacitated; determining, using the sensor data, when a threat is detected for the vehicle; and taking action to avoid the threat when the driver is incapacitated and the threat is detected, via instructions provided by the processor.

Abstract: In accordance with an exemplary embodiment, methods and systems are provided for controlling steering of an autonomous vehicle. The method includes: operating, by a processor, the autonomous vehicle in a semi-automated mode; receiving, by the processor, driver input including a measured driver torque; receiving, by the processor, threat data; determining, by the processor, a steering command bias based on an impedance relation, impedance parameters, the measured driver torque, and the threat data; determining, by the processor, a reference angle based on the steering command bias and a desired angle; and generating, by the processor, control data to control the steering of the autonomous vehicle based on the reference angle.

Abstract: Automated driver assistance systems and methods for towing predict vehicle/trailer instabilities and adapt automated driving control to avoid them. A tow-vehicle includes a controller that, through an actuator system, controls speed and/or steering. A map system and/or a sensor system monitor a roadway on which the vehicle is travelling to identify a road profile located ahead of the vehicle over a prediction horizon. A projected trajectory for navigating the vehicle through the road profile over the prediction horizon and considering environmental conditions is determined. Before travel over the road profile, whether the projected trajectory through the road profile will result in exceeding a vehicle dynamic threshold is determined. When the projected trajectory will result in exceeding the vehicle dynamic threshold through the road profile, a control action is determined to prevent instability and optimize driver experience. The vehicle is operated through the road profile using the control action.

Abstract: Systems and methods for controlling a vehicle. The systems and methods receive static object detection data from a perception system. The static object detection data includes a first representation of a static object at a current time and a second representation of the static object at an earlier time.

Abstract: In accordance with an exemplary embodiment, methods and systems are provided for controlling steering of an autonomous vehicle. The method includes: operating, by a processor, the autonomous vehicle in a semi-automated mode; receiving, by the processor, driver input including a measured driver torque; receiving, by the processor, threat data; determining, by the processor, a steering command bias based on an impedance relation, impedance parameters, the measured driver torque, and the threat data; determining, by the processor, a reference angle based on the steering command bias and a desired angle; and generating, by the processor, control data to control the steering of the autonomous vehicle based on the reference angle.