Interaction auto-labeling using spatial overlap of track footprints for mining interactions

Abstract

Apparatus and methods of the present disclosure provide a solution to quickly sort through and identify relevant data sets from large amounts of data collected by numerous vehicles. This process is a form of data mining where a processor executes instructions out of a memory to evaluate sensor data collected by vehicles over time. These vehicles may be driven by person's such that data collected by those sensors would be representative of how a person drives. After data has been acquired, it may be evaluated to identify portions of data where one vehicle encounters another vehicle along a roadway. Data may be classified as being associated with particular types of driving maneuvers and organized into data sets with labels consistent with the classification or driving maneuver. Classifications could correspond to different typed of driving maneuvers, 'turning left across traffic,' “all way stop,” “merging onto a highway,” or “lane change”.