Abstract: In a method and system for generating vehicle image data, and to improve the generation of vehicle image data, 2D object information having at least 2D object data and object location data of one or more objects, perspective vehicle image data, and vehicle image location data for at least a portion of said vehicle image data are obtained. The object location data is compared with said vehicle image location data; and in case said object location data corresponds to said image location data, said 2D object data is correlated with said perspective vehicle image data using the object location data and the vehicle image location data to obtain a segmented vehicle image dataset.

Abstract: In a method and system for generating vehicle image data, and to improve the generation of vehicle image data, 2D object information having at least 2D object data and object location data of one or more objects, perspective vehicle image data, and vehicle image location data for at least a portion of said vehicle image data are obtained. The object location data is compared with said vehicle image location data; and in case said object location data corresponds to said image location data, said 2D object data is correlated with said perspective vehicle image data using the object location data and the vehicle image location data to obtain a segmented vehicle image dataset.

Abstract: Systems, components, and methodologies are provided for improvements in operation of automotive vehicles by enabling monitoring analysis and reaction to subtle sources of information that aid in prediction and response of vehicle control systems across a range of automation levels. Such systems, components, and methodologies include wheel-turn detection equipment for detecting a wheel angle of another vehicle to trigger a vehicle control system to perform an operation based on the detected wheel angle of the other vehicle.

Abstract: Systems, components, and methodologies are provided for improvements in operation of automotive vehicles by enabling monitoring analysis and reaction to subtle sources of information that aid in prediction and response of vehicle control systems across a range of automation levels. Such systems, components, and methodologies include wheel-turn detection equipment for detecting a wheel angle of another vehicle to trigger a vehicle control system to perform an operation based on the detected wheel angle of the other vehicle.

Abstract: An on-board computing system for determining an opportune time to log data into a first memory. A sensor system collects data of a vehicle's environment. A controller of the on-board computing system logs the data to a first memory when it determines an opportune time to log data to the first memory. The controller holds data in a second memory if it determines it is not an opportune time to log data into the first memory. The controller resumes logging data to the first memory when an opportune time presents itself.

Abstract: An on-board computing system for determining an opportune time to log data into a first memory. A sensor system collects data of a vehicle's environment. A controller of the on-board computing system logs the data to a first memory when it determines an opportune time to log data to the first memory. The controller holds data in a second memory if it determines it is not an opportune time to log data into the first memory. The controller resumes logging data to the first memory when an opportune time presents itself.

Abstract: A system for identifying the status of a group of secondary vehicles. The system determines whether the group of secondary vehicles are parked or part of a traffic jam.

Abstract: A yield determination system for automatically collecting, determining, and labeling yield behaviors of vehicles during cooperative driving scenarios. The system includes sensors for detecting the start and stop of the scenario, a data recorder for automatically collecting the data, an annotation unit for automatically labeling features of interest about the vehicle and surrounding vehicles during the scenario. The labeled file may be automatically uploaded and processed to insert the labelled features into a learning model to predict vehicle behavior in cooperative driving scenarios.