Abstract: In exemplary embodiments, methods and systems are provided that include one or more sensors of a vehicle and a processor of the vehicle. The one or more sensors are configured to obtain sensor data as to operation of the vehicle. The processor is coupled to the one or more sensors, and is configured to at least facilitate inputting the sensor data into a grey-box model including a neural network model for the forces acting on the vehicle and a physics-based model for body motion of the vehicle; determining a trajectory of the vehicle, using the grey-box model; determining a control action for the vehicle, based on the grey-box model using the sensor data; and executing the control action for the vehicle, in accordance with instructions provided by the processor.

Abstract: An autonomous vehicle includes a system for operating the vehicle. A slip angle sensor measures a slip angle of a wheel of the autonomous vehicle. An accelerometer measures an acceleration of the autonomous vehicle. A steering actuator controls a steering angle of the autonomous vehicle. The processor determines a road friction coefficient of the at a selected prediction step, calculates a normal force for the autonomous vehicle from the acceleration, determines a wheel stiffness for the wheel for the normal force at the slip angle using the road friction coefficient based on a tire model for the wheel, calculates a steering command for the autonomous vehicle using a model predictive control having the wheel stiffness as input, and controls the steering actuator using the steering command to steer the autonomous vehicle.

Abstract: A system and method for generating combined lateral and longitudinal trajectories for vehicular collision avoidance. The system and method include determining, offline from a vehicle, a set of optimized trajectories for the vehicle in avoiding a potential collision with an obstacle, where the set of optimized trajectories include a combined set of lateral and longitudinal vehicular motions that are stored in a database within the vehicle. Within the vehicle, a state estimation of the vehicle is determined and includes fetching, based on the state estimation, within the vehicle, a trajectory from the set of optimized trajectories. Based on the selected trajectory, one or more actuators within the vehicle are engaged, where the one or more actuators generate a simultaneous lateral and longitudinal motion of the vehicle in avoidance of the potential collision with the obstacle.

Abstract: In exemplary embodiments, methods and systems are provided that include one or more sensors of a vehicle and a processor of the vehicle. The one or more sensors are configured to obtain sensor data as to operation of the vehicle. The processor is coupled to the one or more sensors, and is configured to at least facilitate inputting the sensor data into a grey-box model including a neural network model for the forces acting on the vehicle and a physics-based model for body motion of the vehicle; determining a trajectory of the vehicle, using the grey-box model; determining a control action for the vehicle, based on the grey-box model using the sensor data; and executing the control action for the vehicle, in accordance with instructions provided by the processor.

Abstract: A vehicle includes a system performing a method for controlling a vehicle. A first steering device generates a first steering force on the vehicle, and a second steering device generates a second steering force at the vehicle. A lateral control module sends a first steering command to the first steering device. An estimation module estimates an external lateral force applied to the vehicle based on the first steering command, a second steering command applied to the second steering device, and a state of the vehicle. A compensation module determines an adjusted value of the second steering command for generating a lateral motion at the vehicle to attenuate the external lateral force and operates the second steering device of the vehicle based on the adjusted value of the second steering command to generate the second steering force at the vehicle that attenuates the external lateral force.

Abstract: A robotic system for driving a vehicle to a destination is configured for placement inside the vehicle, and it utilizes an imaging system for acquiring image data of at least a part of the interior of the vehicle and image data of external surroundings of the vehicle, and a control system for processing the image data acquired by the imaging system. The control system is configured to identify in the image data of at least part of the interior of the vehicle image data of the vehicle state indicators, and determine therefrom at least vehicle status data. The control system is adapted to determine from the image data of external surroundings road status data, and analyze the vehicle status data and the road status data for generating control instructions for driving the vehicle along the road.