Fuel economy is closely related to driving style, traffic situation, and urban geomorphic environment. In this study, the authors propose to compare fuel consumption based on normalised driving behaviour. A personalised driver model is established for each driver by using the locally designed neural network and the real‐world vehicle test data. Driving behaviour is normalised by employing the personalised model to conduct the speed‐following task as defined by standard driving cycle test. Based on the normalised driving behaviour, an aggressiveness index is used to quantitatively evaluate the driving style, and a fuel index is proposed to estimate the fuel consumption. A case study is conducted on the fuel consumption comparison in four major cities in China, namely, Beijing, Shanghai, Chongqing, and Nanjing. Computational results verify the effectiveness of the proposed scheme.
Comparing fuel consumption based on normalised driving behaviour: a case study on major cities in China
IET Intelligent Transport Systems ; 11 , 4 ; 189-195
2017-05-01
7 pages
Aufsatz (Zeitschrift)
Elektronische Ressource
Englisch
Nanjing , aggressiveness index , fuel index , urban geomorphic environment , fuel economy , vehicle test data , neural nets , traffic situation , energy consumption , behavioural sciences computing , Shanghai , driving style , Chongqing , China , Beijing , traffic engineering computing , standard driving cycle test , speed‐following task , locally designed neural network , personalised driver model , fuel consumption , normalised driving behaviour
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