摘要: |
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 research effort, the research team classifies all the potential models used for
estimating vehicle energy and will develop a hybrid model to estimate
transit vehicle energy consumption based on system knowledge and realworld 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. |