Modeling and Verification of Eco-Driving Evaluation
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초록
Traditional ecological driving (Eco-Driving) evaluations often rely on mathematical models that predominantlyoffer subjective insights, which limits their application in real-world scenarios. This study develops a robust,data-driven Eco-Driving evaluation model by integrating dynamic and distributed multi-source data, includingvehicle performance, road conditions, and the driving environment. The model employs a combinationweighting method alongside K-means clustering to facilitate a nuanced comparative analysis of Eco-Drivingbehaviors across vehicles with identical energy consumption profiles. Extensive data validation confirms thatthe proposed model is capable of assessing Eco-Driving practices across diverse vehicles, roads, and environmentalconditions, thereby ensuring more objective, comprehensive, and equitable results.
Abstract
Traditional ecological driving (Eco-Driving) evaluations often rely on mathematical models that predominantlyoffer subjective insights, which limits their application in real-world scenarios. This study develops a robust,data-driven Eco-Driving evaluation model by integrating dynamic and distributed multi-source data, includingvehicle performance, road conditions, and the driving environment. The model employs a combinationweighting method alongside K-means clustering to facilitate a nuanced comparative analysis of Eco-Drivingbehaviors across vehicles with identical energy consumption profiles. Extensive data validation confirms thatthe proposed model is capable of assessing Eco-Driving practices across diverse vehicles, roads, and environmentalconditions, thereby ensuring more objective, comprehensive, and equitable results.
참고문헌 (15)
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