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Two-Lane Traffic Flow Simulation Model via Cellular Automaton

机译:基于元胞自动机的两车道交通流仿真模型

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Road traffic microsimulations based on the individual motion of all the involved vehicles are now recognized as an important tool to describe, understand, and manage road traffic. Cellular automata (CA) are very efficient way to implement vehicle motion. CA is a methodology that uses a discrete space to represent the state of each element of a domain, and this state can be changed according to a transition rule. The well-known cellular automaton Nasch model with modified cell size and variable acceleration rate is extended to two-lane cellular automaton model for traffic flow. A set of state rules is applied to provide lane-changing maneuvers. S-t-s rule given in the BJH model which describes the behavior of jammed vehicle is implemented in the present model and effect of variability in traffic flow on lane-changing behavior is studied. Flow rate between the single-lane road and two-lane road where vehicles change the lane in order to avoid the collision is also compared under the influence of s-t-s rule and braking rule. Using results of numerical simulations, we analyzed the fundamental diagram of traffic flow and show that s-t-s probability has more effect than braking probability on lane-changing maneuver.
机译:基于所有参与车辆的个体运动的道路交通微观模拟现在被认为是描述,理解和管理道路交通的重要工具。元胞自动机(CA)是实现车辆运动的非常有效的方法。 CA是一种使用离散空间表示域中每个元素的状态的方法,可以根据转换规则更改此状态。具有更改的像元大小和可变加速率的著名的细胞自动机Nasch模型被扩展为两车道细胞自动机模型,用于交通流。应用了一组状态规则来提供变道演习。在本模型中,采用了描述拥堵车辆行为的BJH模型中给出的S-t-s规则,并研究了交通流量变化对变道行为的影响。在s-t-s规则和制动规则的影响下,还比较了车辆为了避免碰撞而改变车道的单车道和两车道之间的流量。利用数值模拟的结果,我们分析了交通流的基本图,并表明在换道操作中,s-t-s概率比制动概率具有更大的影响。

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