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Analysis of mixed traffic flow with human-driving and autonomous cars based on car-following model

机译:基于汽车跟踪模型的人力驾驶和自主汽车混合交通流量分析

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We investigated the mixed traffic flow with human-driving and autonomous cars. A new mathematical model with adjustable sensitivity and smooth factor was proposed to describe the autonomous car's moving behavior in which smooth factor is used to balance the front and back headway in a flow. A lemma and a theorem were proved to support the stability criteria in traffic flow. A series of simulations were carried out to analyze the mixed traffic flow. The fundamental diagrams were obtained from the numerical simulation results. The varying sensitivity and smooth factor of autonomous cars affect traffic flux, which exhibits opposite varying tendency with increasing parameters before and after the critical density. Moreover, the sensitivity of sensors and smooth factors play an important role in stabilizing the mixed traffic flow and suppressing the traffic jam. (C) 2017 Elsevier B.V. All rights reserved.
机译:我们调查了与人驾驶和自主汽车的混合交通流量。 提出了一种具有可调节灵敏度和平滑因子的新数学模型,以描述自动驾驶汽车的移动行为,其中使用平滑因子来平衡流动的前后前进。 证明了一种引理和定理,以支持交通流量的稳定标准。 进行了一系列模拟以分析混合交通流量。 基本图是从数值模拟结果获得的。 自主车的不同灵敏度和平滑因子影响交通助焊剂,其在临界密度前后增加参数具有相反的变化趋势。 此外,传感器和平滑因素的灵敏度在稳定混合交通流量和抑制交通堵塞方面发挥着重要作用。 (c)2017年Elsevier B.V.保留所有权利。

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