Properly estimating transit energy use is a critical element of transit system planning. Reasonable predictions of energy consumption are needed by transit agencies and stakeholders to select proper fleet, arrange vehicle operations, develop improvement plans, etc. However, the current models used to estimate transit energy use at the vehicle level are quite limited, in part because few models were specifically designed for transit systems. Current energy models may fail to capture some key operation elements such as stop frequency and passenger load (“over-simplify”), or asking for input or configuration information which is too difficult for most people to obtain (“over-specify”). In this project, the researcher classifies all the potential models used for estimating vehicle energy and develops a hybrid model to estimate transit vehicle energy consumption based on system knowledge and real-world observational data. The model is expected to take affordable and easy-to-collect vehicle specification and engine and on-road operation condition data as inputs, include vehicle registration data, GPS position and speed data, OBD engine parameter data, and road grade data from the USGS Digital Elevation Model (DEM). The proposed new vehicle emission modeling framework will be verified and calibrated using local transit data. Finally, the proposed modeling approach will be applied to improve current transit vehicle operation and reduce transit fuel use in the MARTA fleet. The new emission modeling approach is expected to better estimate energy consumption and emissions of transit vehicles, and provide more effective eco-transit approach for real-world transit operations.
