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Two-layer pointer model of driving style depending on the driving environment

机译:取决于驾驶环境的驾驶风格的两层指针模型

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摘要

This paper deals with the task of modeling the driving style depending on the driving environment. The model of the driving style is represented as a two-layer mixture of normal components describing data with two pointers: outer and inner. The inner pointer indicates the actual driving environment categorized as "urban", "rural" and "highway". The outer pointer through the determined environment estimates the active driving style from a fuel economy point of view as "low consumption", "middle consumption" and "high consumption". All of these driving styles are assumed to exist within each driving environment due to the two-layer model. Parameters of the model and the driving style are estimated online, i.e., while driving using a recursive algorithm under the Bayesian methodology. The main contributions of the presented approach are: (i) the driving style recognition within each of urban, rural and highway environments as well as in the case of switching among them; (ii) the two-layer pointer, which allows us to incorporate the information from continuous data into the model; (iii) the potential use of the data-based model for other measurements using corresponding distributions. The approach was tested using real data. (C) 2019 Elsevier Ltd. All rights reserved.
机译:本文涉及根据驾驶环境对驾驶风格进行建模的任务。驾驶风格的模型表示为正常成分的两层混合,使用两个指针(外部和内部)描述数据。内部指针指示分类为“城市”,“农村”和“高速公路”的实际驾驶环境。通过所确定的环境的外部指针从燃料经济性的角度估计为“低消耗”,“中等消耗”和“高消耗”。由于两层模型,所有这些驾驶方式都假定存在于每个驾驶环境中。该模型的参数和驾驶风格是在线估算的,即在贝叶斯方法下使用递归算法进行驾驶时。所提出的方法的主要贡献是:(i)在城市,乡村和高速公路环境中以及在它们之间切换的情况下识别驾驶风格; (ii)两层指针,它使我们能够将来自连续数据的信息整合到模型中; (iii)使用基于数据的模型进行其他使用相应分布的测量的潜在用途。该方法已使用实际数据进行了测试。 (C)2019 Elsevier Ltd.保留所有权利。

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