Stuck in a lot of new features - schedule, nearest stop, block id, bus count, destination, direction, and refined how it collects training data. This brought the mean squared error from 3,000,000 to 1,644 in one case which means it was estimating the arrival time roughly under a minute on average.
The weather feature is done on the training side and just needs implemented on the front end side. Also the project now utilizes GTFS data. Next is to begin running everything on a public server and test and debug live issues.