Analysis of City Bus Driving Cycle Features for the Purpose of Multidimensional Driving Cycle Synthesis

Driving cycles are typically used for estimation of vehicle fuel/energy consumption and CO₂ emissions. In most of applications only the vehicle velocity vs. time profile is considered as a driving cycle, while a road slope is typically omitted. Since the road slope significantly impacts the fuel consumption, it should be included into realistic driving cycles for hilly roads. As a part of wider research of multidimensional driving cycle synthesis, this paper focuses on analysis of a broad city bus driving cycle dataset recorded in the city of Dubrovnik. The analysis is aimed at revealing the impact of road slope on velocity and acceleration distributions, and clustering the recorded data into several groups reflecting various driving and traffic congestion characteristics. Finally, the Markov chain method is employed to synthesize 3D driving cycles for the selected data clusters, where the Markov chain states include vehicle velocity, vehicle acceleration, and road slope. The synthesized cycles are validated to ensure their representativeness in terms of faithful description of main features of the recorded driving cycles.