Abstract: A system and method for determining whether a driver of a host vehicle intends to make a left or right turn with a certain level of confidence. The method obtains a plurality of turning cues that identify external parameters around the host vehicle and/or define operating conditions of the host vehicle, and determines a confidence level that the host vehicle will make a left or right turn based on the turning cues, where determining the confidence level includes weighting each of the cues based on current vehicle operating conditions.

Abstract: An autonomous vehicle, a system and method of operating the autonomous vehicle. An environmental sensor obtains one or more parameters of external agents of the vehicle. A processor of the vehicle obtains a route having a destination at the autonomous vehicle, builds a Markov state model of the route that includes a plurality of states for the autonomous vehicle and one or more parameters of the external agents, generates a plurality of driving policies for navigating the route, selects a policy for navigating the route from the plurality of driving policies using a Markov Decision Process, and executes the selected policy at the autonomous vehicle to navigate the vehicle along the route towards the destination.

Abstract: Methods and systems are provided for processing attention data. In one embodiment, a method includes: receiving, by a processor, object data associated with at least one object of an exterior environment of the vehicle; receiving upcoming behavior data determined from a planned route of the vehicle; receiving gaze data sensed from an occupant of the vehicle; processing, by the processor, the object data, the upcoming behavior data, and the gaze data to determine an attention score associated with an attention of the occupant of the vehicle; and selectively generating, by the processor, signals to at least one of notify the occupant and control the vehicle based on the attention score.

Abstract: A method for controlling an operating vehicle includes: (a) determining, via a controller, a confidence level that the light of the other vehicle is ON based on images captured by a camera of the operating vehicle; and (b) controlling, via the controller, an alarm of the operating vehicle based on the confidence level that the light of the other vehicle is ON.

Abstract: The present application generally relates to a method and apparatus for generating an action policy for controlling an autonomous vehicle. In particular, the system performs a deep learning algorithm in order to determine the action policy and an automatically generated curriculum system to determine a number of increasingly difficult tasks in order to refine the action policy.

Abstract: Techniques for road scene primitive detection using a vehicle camera system are disclosed. In one example implementation, a computer-implemented method includes receiving, by a processing device having at least two parallel processing cores, at least one image from a camera associated with a vehicle on a road. The processing device generates a plurality of views from the at least one image that include a feature primitive. The feature primitive is indicative of a vehicle or other road scene entities of interest. Using each of the parallel processing cores, a set of primitives are identified from one or more of the plurality of views. The feature primitives are identified using one or more of machine learning and classic computer vision techniques. The processing device outputs, based on the plurality of views, result primitives based on the plurality of identified primitives from multiple views based on the plurality of identified entities.

Abstract: Methods and apparatus are provided for controlling an autonomous vehicle. A sensor fusion system with a sensor system for providing environment condition information and a convolutional neural network (CNN) is provided. The CNN includes a receiving interface configured to receive the environment condition information from the sensor system, a common convolutional layer configured to extract traffic information from the received environment condition information, and a plurality of fully connected layers configured to detect objects belonging to different object classes based on the extracted traffic information, wherein the object classes include at least one of a road feature class, a static object class, and a dynamic object class.

Abstract: Systems and method are provided for evaluating control features of an autonomous vehicle for development or validation purposes. A real-world sensor data set is generated by an autonomous vehicle having sensors. A sensing and perception module generates perturbations of the real-world sensor data set. A generator module generates a 3-dimensional object data set from the real-world sensor data set. A planning and behavior module generates perturbations of the 3-dimensional object data set. A testing module tests a control feature such as an algorithm or software using the 3-dimensional object data set. A control module executes command outputs from the control feature for evaluation.

Abstract: Technical solutions are described for controlling an automated driving system of a vehicle. An example method includes computing a complexity metric of an upcoming region along a route that the vehicle is traveling along. The method further includes, in response to the complexity metric being below a predetermined low-complexity threshold, determining a trajectory for the vehicle to travel in the upcoming region using a computing system of the vehicle. Further, the method includes in response to the complexity metric being above a predetermined high-complexity threshold, instructing an external computing system to determine the trajectory for the vehicle to travel in the upcoming region. If the trajectory cannot be determined by the external computing system a minimal risk condition maneuver of the vehicle is performed.

Abstract: An electric power system includes an energy recovery system that is operable to convert kinetic energy into electric energy at a first voltage. A primary energy storage device is electrically connected to the energy recovery system at the first voltage. A first voltage autonomous driving system load is disposed in a parallel circuit with the energy recovery system and the primary energy storage device. A bi-directional DC-DC converter is electrically connected to the energy recovery system and the primary energy storage device for converting the electric energy between the first voltage and a second voltage. A secondary energy storage device is electrically connected to the bi-directional DC-DC converter at the second voltage. A second voltage autonomous driving system load is disposed in a parallel circuit with the secondary energy storage device.

Abstract: A system and method for generating a range image using sparse depth data is disclosed. The method includes receiving, by a controller, image data of a scene. The image data includes a first set of pixels. The method also includes receiving, by the controller, a sparse depth data of the scene. The sparse depth data includes a second set of pixels, and the number of the second set of pixels is less than the number of first set of pixels. The method also includes combining the image data and the sparse depth data into a combined data. The method also includes generating a range image using the combined data.

Abstract: A vehicle, system and method of autonomous navigation of the vehicle. A reference trajectory for navigating a training traffic scenario along a road section is received at a processor of the vehicle. The processor determines a coefficient for a cost function associated with a candidate trajectory that simulates the reference trajectory. The determined coefficient is provided to a neural network to train the neural network. The trained neural network generates a navigation trajectory for navigating the vehicle using a cost coefficient determined by the neural network. The vehicle is navigated along the road section using the navigation trajectory.

Abstract: Technical solutions are described for vehicle collision prevention for a vehicle when the vehicle is in a parked condition. An example method includes performing a stationary safety monitoring when the vehicle is in parked condition. The stationary safety monitoring includes detecting presence of a moving object within a predetermined region from the vehicle. Further, the method includes, in response to detecting the moving object in the predetermined region initiating a notification for the moving object to prevent collision with the vehicle.

Abstract: Methods and systems are provided for determining a vehicle position. In one embodiment, a method includes: receiving, by a processor of a rover vehicle, vehicle position data from one or more parked vehicles; receiving, by the processor of the rover vehicle, global positioning system data from a GPS receiver of the rover vehicle; and processing, by the processor of the rover vehicle, the vehicle position data and the global position system data to determine a position of the rover vehicle.

Abstract: Systems and methods are provided for controlling a vehicle. Control signals are generated at a high-level controller based on one or more sources of input data, comprising at least one of: sensors that provide sensor output information, map data and goals. The high-level controller comprises first controller modules comprising: an input processing module, a projection module, a memories module, a world model module, and a decision processing module that comprises a control model executor module. The control signals are processed at a low-level controller to generate commands that control a plurality of vehicle actuators of the vehicle in accordance with the control signals to execute one or more scheduled actions to be performed to automate driving tasks.

Abstract: A vehicle, system and method of driving of an autonomous vehicle. The vehicle includes a camera for obtaining an image of a surrounding region of the vehicle, an actuation device for controlling a parameter of motion of the vehicle, and a processor. The processor selects a context region within the image, wherein the context region including a detection region therein. The processor further estimates a confidence level indicative of the presence of at least a portion of the target object in the detection region and a bounding box associated with the target object, determines a proposal region from the bounding box when the confidence level is greater than a selected threshold, determines a parameter of the target object within the proposal region, and controls the actuation device to alter a parameter of motion of the vehicle based on the parameter of the target object.

Abstract: Methods and apparatus are provided for cleaning a sensor lens cover for an optical vehicle sensor. The method includes monitoring the sensor lens cover for a contaminant obstructing at least a portion of the sensor lens cover and determining the presence of the commandant and a contaminant type using information provided by one or more vehicle sensors. A cleaning modality selected based the contaminant type is activated and it is determined whether the cleaning modality has removed the contaminant from the sensor lens cover.

Abstract: Systems and method are provided for controlling a vehicle.

Abstract: A vehicle, system and method of driving of an autonomous vehicle. The vehicle includes a camera for obtaining an image of a surrounding region of the vehicle, an actuation device for controlling a parameter of motion of the vehicle, and a processor. The processor selects a context region within the image, wherein the context region including a detection region therein. The processor further estimates a confidence level indicative of the presence of at least a portion of the target object in the detection region and a bounding box associated with the target object, determines a proposal region from the bounding box when the confidence level is greater than a selected threshold, determines a parameter of the target object within the proposal region, and controls the actuation device to alter a parameter of motion of the vehicle based on the parameter of the target object.

Abstract: A vehicle, system and method of operating the vehicle. In one exemplary embodiment, a method of operating an autonomous vehicle is disclosed. An environmental sensor obtains one or more parameters of external agents of the vehicle. A processor of the vehicle obtains a route having a destination at the autonomous vehicle, builds a Markov state model of the route that includes a plurality of states for the autonomous vehicle and one or more parameters of the external agents, generates a plurality of driving policies for navigating the route, selects a policy for navigating the route from the plurality of driving policies using a Markov Decision Process, and executes the selected policy at the autonomous vehicle to navigate the vehicle along the route towards the destination.