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Analysis of three independent real-world driving studies: A data driven and expert analysis approach to determining parameters affecting fuel economy

Title
Analysis of three independent real-world driving studies: A data driven and expert analysis approach to determining parameters affecting fuel economy
Authors
Birrell, S[Birrell, Stewart]Taylor, J[Taylor, James]McGordon, A[McGordon, Andrew]Son, J[Son, Joonwoo]Jennings, P[Jennings, Paul]
DGIST Authors
Son, J[Son, Joonwoo]
Issue Date
2014-12
Citation
Transportation Research Part D: Transport and Environment, 33, 74-86
Type
Article
Article Type
Article
Keywords
AccelerationData-Driven AnalysisData DrivenData SetDriver BehaviourEnergy EfficiencyExpert AnalysisFuel ConsumptionFuel EconomyReal-World DrivingReal-World DrivingsStatistical AnalysisStatistical MethodsTravel Behavior
ISSN
1361-9209
Abstract
It is well established that individual variations in driving style have a significant impact on vehicle energy efficiency. The literature shows certain parameters have been linked to good fuel economy, specifically acceleration, throttle use, number of stop/starts and gear change behaviours. The primary aim of this study was to examine what driving parameters are specifically related to good fuel economy using a non-homogeneous extended data set of vehicles and drivers over real-world driving scenarios spanning two countries. The analysis presented in this paper shows how three completely independent studies looking at the same factor (i.e., the influence of driver behaviour on fuel efficiency) can be evaluated, and, despite their notable differences in location, environment, route, vehicle and drivers, can be compared on broadly similar terms. The data from the three studies were analysed in two ways; firstly, using expert analysis and the second a purely data driven approach. The various models and experts concurred that a combination of at least one factor from the each of the categories of vehicle speed, engine speed, acceleration and throttle position were required to accurately predict the impact on fuel economy. The identification of standard deviation of speed as the primary contributing factor to fuel economy, as identified by both the expert and data driven analysis, is also an important finding. Finally, this study has illustrated how various seemingly independent studies can be brought together, analysed as a whole and meaningful conclusions extracted from the combined data set. © 2014 Elsevier Ltd.
URI
http://hdl.handle.net/20.500.11750/2635
DOI
10.1016/j.trd.2014.08.021
Publisher
Elsevier Ltd
Related Researcher
Files:
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Collection:
Companion Diagnostics and Medical Technology Research Group1. Journal Articles


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