This dataset provides detailed information on the destination labels for the trip trajectory and charging of 65 Battery Electric Vehicles in California in the eVMT dataset. This dataset includes the Tesla Model S and Chevrolet Bolt only. Additionally, the repository contains a Python script that trains a deep-learning model to predict the driving behavior of the drivers in this dataset. The aim of this model is to forecast the charging needs of the drivers, so that they can align their charging needs with renewable energy resources availability. This way, the impact of fossil fuel resources in charging the vehicle can be decreased, and carbon emission per mile driven can be reduced.
