نویسندگان
چکیده
کلیدواژهها
عنوان مقاله [English]
نویسندگان [English]
This paper presents driving features and their influences on the vehicle’s fuel consumption and exhaust
emissions driving data gathering is performed in real traffic conditions in order to provide the velocity time
series. Advance Vehicle Locating (AVL) systems based on GPS technology are used for driving data collection.
Then 21 driving features are defined based on vehicle’s velocity time series. After the extraction of features
from the driving data, relation between the features is investigated in order to determine independent
features. The influence of the selected features on vehicle’s fuel consumption and pollutant emissions is then
studied using computer simulations. The Advisor software is utilized here for two types of vehicles, conventional
SAMAND and hybrid SAMAND (HEV), simulation results are compared with test results in some
cases. Finally the most effective driving features are determined by a total index and superior features are
identified and presented as the result of this study. These superior features can be used in traffic condition
clustering, driving cycle development, traffic condition clustering and intelligent HEV control.
کلیدواژهها [English]
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