An extended macro model accounting for acceleration changes with memory and numerical tests

An extended macro model accounting for acceleration changes with memory and numerical tests
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扩展的宏观模型考虑了内存和数值测试的加速度变化

DOI:
10.1016/j.physa.2018.04.060
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发表时间:
2018-09
期刊:
Physica A: Statistical Mechanics and Its Applications
影响因子:
--
通讯作者:
Wang Jufeng
Wang Jufeng
中科院分区:
其他
文献类型:
--
作者:
Cheng Rongjun;Ge Hongxia;Sun Fengxin;Wang Jufeng

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考虑加速度随记忆变化的影响,提出了一种改进的连续介质交通流模型。应用线性稳定性理论,给出了新模型的线性稳定性条件。通过非线性分析,推导出描述中性线附近交通密度波传播行为的KdV-Burgers型方程。对扩展的交通流模型进行了数值模拟,探讨了加速度随记忆的变化对每辆车的速度、密度、油耗和尾气排放的影响。数值结果表明,加速度随记忆的变化对交通流的动态特性有显著的负面影响。此外,研究结果还验证了在小扰动的整个演化过程中,加速度随记忆变化的影响会恶化交通流的稳定性,增加汽车的总油耗和排放。
Considering effect of acceleration changes with memory, an improved continuum model of traffic flow is proposed in this paper. By applying the linear stability theory, we derived the new model’s linear stability condition. Through nonlinear analysis, the KdV–Burgers equation is derived to describe the propagating behavior of traffic density wave near the neutral stability line. Numerical simulation is carried out to study the extended traffic flow model, which explores how acceleration changes with memory affected each car’s velocity, density and fuel consumption and exhaust emissions. Numerical results demonstrate that acceleration changes with memory have significant negative effect on dynamic characteristic of traffic flow. Furthermore, research results verify that the effect of acceleration changes with memory will deteriorate the stability of traffic flow and increase cars’ total fuel consumptions and emissions during the whole evolution of small perturbation.
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发表时间: 2003-02
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