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This work compared the Micro-trips, Markov-chains and the MWD-CP methods in their ability of constructing driving cycles (DCs) that represent local driving patterns. For this purpose, we used a database made of 138 time series of speed obtained monitoring during two months a fleet of 15 transit buses operating on roads with different levels of service, traffic and road grades, under normal conditions of use. Then, we used 16 characteristic parameters, such as mean speed or positive kinetic energy, to describe the driving pattern of the buses’ drivers monitored. Subsequently, we implemented three of the most widely used methods to construct DCs using this common database as input data. Finally, we evaluated the degree of representativeness of the local driving pattern contained in each of the obtained DCs. Toward that end we defined that a DC represents a driving pattern when its characteristic parameters are equal to the characteristic parameter of the driving pattern. Therefore, we used as criteria of representativeness the relative differences between paired characteristic parameters, and observed that the MWD-CP method produced the DC that best represents the driving pattern in the region where the buses were monitored, followed by the DC produced by the Micro-trips method.
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