Modeling and Verification of Eco-Driving Evaluation


Lin Liu, Nenglong Hu, Zhihu Peng, Shuxian Zhan, Jingting Gao, Hong Wang, Journal of Information Processing Systems Vol. 20, No. 3, pp. 296-306, Jun. 2024  

https://doi.org/10.3745/JIPS.04.0310
Keywords: Combination Weighting Method, data-driven, eco-driving, K-Means Clustering
Fulltext:

Abstract

Traditional ecological driving (Eco-Driving) evaluations often rely on mathematical models that predominantly offer 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, including vehicle performance, road conditions, and the driving environment. The model employs a combination weighting method alongside K-means clustering to facilitate a nuanced comparative analysis of Eco-Driving behaviors across vehicles with identical energy consumption profiles. Extensive data validation confirms that the proposed model is capable of assessing Eco-Driving practices across diverse vehicles, roads, and environmental conditions, thereby ensuring more objective, comprehensive, and equitable results.


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Cite this article
[APA Style]
Liu, L., Hu, N., Peng, Z., Zhan, S., Gao, J., & Wang, H. (2024). Modeling and Verification of Eco-Driving Evaluation. Journal of Information Processing Systems, 20(3), 296-306. DOI: 10.3745/JIPS.04.0310.

[IEEE Style]
L. Liu, N. Hu, Z. Peng, S. Zhan, J. Gao, H. Wang, "Modeling and Verification of Eco-Driving Evaluation," Journal of Information Processing Systems, vol. 20, no. 3, pp. 296-306, 2024. DOI: 10.3745/JIPS.04.0310.

[ACM Style]
Lin Liu, Nenglong Hu, Zhihu Peng, Shuxian Zhan, Jingting Gao, and Hong Wang. 2024. Modeling and Verification of Eco-Driving Evaluation. Journal of Information Processing Systems, 20, 3, (2024), 296-306. DOI: 10.3745/JIPS.04.0310.