Energy-Efficient Driving Model by Clustering of GPS Information

Michael Breuß (), Ali Sharifi Boroujerdi () and Ashkan Mansouri Yarahmadi ()
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Michael Breuß: BTU Cottbus-Senftenberg
Ali Sharifi Boroujerdi: Volkswagen Infotainment GmbH
Ashkan Mansouri Yarahmadi: BTU Cottbus-Senftenberg

Chapter Chapter 26 in Operations Research Proceedings 2022, 2023, pp 213-219 from Springer

Abstract: Abstract In this paper we propose a novel approach to distinguish the style of drivers with respect to their energy efficiency. A unique property of the proposed method is that it relies exclusively on Global Positioning System (GPS) data. This setting is highly robust and available in practice as these GPS logs can easily be obtained. To rely on positional data alone means that all possible derived features from it will be highly correlated, so we have to consider a single feature. Here, we propose to explore the use of acceleration differences of a movement. Our strategy relies on agglomerative hierarchical clustering. The approach can be easily implemented to perform fast, even on huge amount of real-world data logs.

Keywords: Energy efficiency; Driving style analysis; Clustering; GPS data (search for similar items in EconPapers)
Date: 2023
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DOI: 10.1007/978-3-031-24907-5_26

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