This document describes road modeling with ensemble Gaussian processes. A road is modeled at a first time using at least one Gaussian process regression (GPR). A kernel function is determined based on a sample set of detections received from one or more vehicle systems. Based on the kernel function, a respective mean lateral position associated with a particular longitudinal position is determined for each GPR of the at least one GPR. The respective mean lateral position for each of the at least one GPR is aggregated to determine a combined lateral position associated with the particular longitudinal position. A road model is then output including the combined lateral position associated with the particular longitudinal position. In this way, a robust and computationally efficient road model may be determined to aid in vehicle safety and performance.