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An Analysis on Impact Factors of Bus Fuel Consumption Based on Decision Tree Model

机译:基于决策树模型的公交车燃油消耗影响因素分析

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This paper focuses on exploring the most sensitive factors affecting bus fuel consumption quantitatively based on the CART (classification and regression tree) model. Firstly, the distribution of fuel consumption data is proved to agree with Gamma distribution after data processing, which introduces the threshold of high-level fuel consumption used in this research. Further analysis on the processed data shows that four factors of road feature like intersection density on the route and six driving behavior factors including rapid acceleration have significant impacts on fuel consumption. Then, the CART model is applied to three sub-datasets of different periods, and the outcomes show that fuel consumption is sensitive to the smoothness of driving during peak hours, the density of bus stops and the frequency of idling at off-peak times. Based on the CART model results, fuel-efficient strategies can be presented quantitatively from aspects of bus line planning, traffic management, and driving behavior training.
机译:本文重点研究基于CART(分类和回归树)模型定量地影响公交车燃油消耗的最敏感因素。首先,燃料消耗数据的分布被证明与数据处理后的伽马分布一致,这引入了本研究中使用的高级燃料消耗的阈值。对处理数据的进一步分析表明,道路特征中的四个因素(如路线上的交叉路口密度)和六个驾驶行为因素(包括快速加速)对油耗有重大影响。然后,将CART模型应用于不同时期的三个子数据集,结果表明,燃油消耗量对高峰时段的行驶平稳性,公交车站的密度和非高峰时段的怠速频率敏感。基于CART模型的结果,可以从公交线路规划,交通管理和驾驶行为培训等方面定量提出节油策略。

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