Energy impact of different penetrations of connected and automated vehicles: a preliminary assessment

Jackeline Rios-Torres, Andreas A. Malikopoulos
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引用次数: 14

Abstract

Previous research reported in the literature has shown the benefits of traffic coordination to alleviate congestion, and reduce fuel consumption and emissions. However, there are still many remaining challenges that need to be addressed before a massive deployment of fully automated vehicles. This paper aims to investigate the energy impacts of different penetration rates of connected and automated vehicles (CAVs) and their interaction with human-driven vehicles. We develop a simulation framework for mixed traffic (CAVs interacting with human-driven vehicles) in merging roadways and analyze the energy impact of different penetration rates of CAVs on the energy consumption. The Gipps car following model is used along with heuristic controls to represent the driver decisions in a merging roadways traffic scenario. Using different penetration rates of CAVs, the simulation results indicated that for low penetration rates, the fuel consumption benefits are significant but the total travel time increases. The benefits in travel time are noticeable for higher penetration rates of CAVs.
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联网和自动驾驶汽车的不同渗透对能源的影响:初步评估
先前的文献研究表明,交通协调对缓解拥堵、减少燃料消耗和排放有好处。然而,在大规模部署全自动驾驶汽车之前,仍有许多挑战需要解决。本文旨在研究不同普及率的联网和自动驾驶汽车(cav)对能源的影响,以及它们与人类驾驶汽车的相互作用。本文开发了混合交通(自动驾驶汽车与人类驾驶汽车相互作用)合并道路的仿真框架,并分析了不同渗透率的自动驾驶汽车对能源消耗的影响。将Gipps汽车跟随模型与启发式控制一起用于表示合并道路交通场景中的驾驶员决策。在不同侵彻率下,仿真结果表明,低侵彻率下,整车油耗效益显著,但总行程时间增加。在行驶时间的好处是显而易见的更高的渗透率的自动驾驶汽车。
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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