Abstract: Aspects of the present application correspond to utilization of a combined set of inputs from simulation systems to generate or train machine learned algorithms for utilization in vehicles with vision system-only based processing. Aspects of the present application correspond to utilization of a set of inputs from sensors or sensing systems and simulation systems to create updated training sets for use in machine learning algorithms. The combined set of inputs includes a first set of data corresponding to vision system from a plurality of cameras configured in a vehicle. The combined set of inputs further includes a second set of data corresponding to simulated content systems that generate additional training set data including visual images and data labels to supplement the vision system data.

Abstract: Aspects of this technical solution can generate, according to one or more first environment metrics, a three-dimensional (3D) model including a first surface corresponding to one or more physical ways through a physical environment, the one or more first environment metrics indicative of boundaries of the one or more physical ways, generate, according to one or more second environment metrics, one or more geometric two-dimensional (2D) objects on the first surface, the second environment metrics indicative of the one or more physical ways, identify, according to one or more viewpoint metrics indicative of cameras of a physical object configured to move along the one or more physical ways, one or more viewpoints oriented to capture corresponding portions of the 3D model, and render, from the one or more corresponding portions of the 3D model, one or more 2D images each corresponding to respective ones of the viewpoints.

Abstract: Aspects of the present application correspond to utilization of a combined set of inputs from simulation systems to generate or train machine learned algorithms for utilization in vehicles with vision system-only based processing. Aspects of the present application correspond to utilization of a set of inputs from sensors or sensing systems and simulation systems to create updated training sets for use in machine learning algorithms. The combined set of inputs includes a first set of data corresponding to vision system from a plurality of cameras configured in a vehicle. The combined set of inputs further includes a second set of data corresponding to simulated content systems that generate additional training set data including visual images and data labels to supplement the vision system data.

Abstract: Aspects of the present application correspond to utilization of a combined set of inputs from simulation systems to generate or train machine learned algorithms for utilization in vehicles with vision system-only based processing. Aspects of the present application correspond to utilization of a set of inputs from sensors or sensing systems and simulation systems to create updated training sets for use in machine learning algorithms. The combined set of inputs includes a first set of data corresponding to vision system from a plurality of cameras configured in a vehicle. The combined set of inputs further includes a second set of data corresponding to simulated content systems that generate additional training set data including visual images and data labels to supplement the vision system data.