Green routing fuel saving opportunity assessment: A case study using large-scale real-world travel data

Lei Zhu, J. Holden, E. Wood, Jeffrey Gender
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引用次数: 14

Abstract

New technologies such as connected and automated vehicles have attracted more and more research attention for their potential to improve the energy efficiency and environmental impact of current transportation systems. Green routing is one such connected vehicle strategy under which drivers receive information about the most fuel-efficient route before departing for a given destination. This paper introduces an evaluation framework for estimating the benefits of green routing based on large-scale, real-world travel data. The framework has the capability to quantify fuel savings by estimating the fuel consumption on alternate routes that could be taken between two locations and comparing these to the estimated fuel consumption of the actual route taken. A route-based fuel consumption estimation model that considers road traffic conditions, functional class, and grade is proposed and used in the framework. A study using a large-scale, high-resolution data set from the California Household Travel Survey indicates that 31% of actual routes have fuel savings potential, and among these routes the cumulative fuel savings could reach 12%. Alternately calculating the potential fuel savings relative to the full set of actual routes (including those that already follow the greenest route recommendation), the potential savings relative to the overall estimated fuel consumption would be 4.5%. Notably, two thirds of the fuel savings occur on green routes that save both fuel and time relative to the original actual routes. The remaining third would be subject to weighing the potential fuel savings against required increases in travel time for the recommended green route.
绿色路线节油机会评估:使用大规模真实旅行数据的案例研究
互联和自动驾驶汽车等新技术因其提高当前交通系统的能源效率和环境影响的潜力而吸引了越来越多的研究关注。绿色路线就是这样一种联网车辆策略,在这种策略下,司机在出发前往给定目的地之前会收到最省油的路线信息。本文介绍了一个基于大规模真实出行数据的绿色路线效益评估框架。该框架能够通过估算两个地点之间可能采取的替代路线的燃料消耗,并将其与实际路线的估计燃料消耗进行比较,从而量化节省的燃料。提出了一种考虑道路交通状况、功能类别和等级的基于路线的油耗估计模型,并将其应用于框架中。一项利用加州家庭旅行调查的大规模高分辨率数据集进行的研究表明,31%的实际路线具有节省燃料的潜力,其中累计节省燃料的路线可达12%。或者计算相对于全套实际路线(包括那些已经遵循最环保路线建议的路线)的潜在燃料节省,相对于总体估计燃料消耗的潜在节省将是4.5%。值得注意的是,三分之二的燃油节约发生在绿色路线上,相对于原来的实际路线,绿色路线既节省了燃油,又节省了时间。剩下的三分之一将取决于权衡潜在的燃料节省和推荐的绿色路线所需增加的旅行时间。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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