交通流时空模式、相变和演化的元胞自动机模型
Cellular automaton model simulating spatiotemporal patterns, phase transitions and evolution concavity in traffic flow
摘要：
本文首先证明了一个最近的模型（Tian et al.，传输Res. B 71，138-157，2015）不能很好地复制交通流中的演化曲线，即车辆的标准偏差沿着队列以凹形/线性方式增加。在此基础上，通过引入安全车速、随机概率的逻辑斯蒂函数和低速车辆的小随机减速度，提出了一种改进模型。仿真结果表明，改进模型能较好地再现交通流的亚稳态、时空模式、相变行为和交通振荡的演化规律。验证结果表明，由浮动车数据得到的交通速度经验时间序列也能很好地拟合。
英文摘要：
This paper firstly show that a recent model (Tian et al., Transpn. Res. B 71, 138-157, 2015) is not able to well replicate the evolution concavity in traffic flow, i.e. the standard deviation of vehicles increases in a concave/linear way along the platoon. Then we propose an improved model by introducing the safe speed, the logistic function of the randomization probability, and small randomization deceleration for low-speed vehicles into the model. Simulations show that the improved model can well reproduce the metastable states, the spatiotemporal patterns, the phase transition behaviors of traffic flow, and the evolution concavity of traffic oscillations. Validating results show that the empirical time series of traffic speed obtained from Floating Car Data can be well simulated as well.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
