SYSTEMS AND METHODS FOR ESTIMATING A TRAFFIC PATTERN FROM SPARSE DATA

Systems, methods, and other embodiments described relate to estimating a traffic pattern using learning models that process data from road sensors that are sparse. In one embodiment, a method includes forming multi-channel data from partial data and timing data about traffic on a road, the partial data acquired from road sensors. The method also includes generating an adjacency matrix from the partial data and geometry about the road. The method also includes training a graph model using temporal patterns for graph nodes from the multi-channel data and the adjacency matrix to complete the partial data and output a traffic pattern estimate.