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首页> 外文期刊>Simulation modelling practice and theory: International journal of the Federation of European Simulation Societies >A traffic cellular automata model based on road network grids and its spatial and temporal resolution's influences on simulation
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A traffic cellular automata model based on road network grids and its spatial and temporal resolution's influences on simulation

机译：基于路网网格的交通蜂窝自动机模型及其时空分辨率对仿真的影响

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Microscopic Traffic Simulation Model based on Cellular Automata (CA) has become more and more popular since it was firstly introduced by Creamer and Ludwig in 1986. Cellular automata are simpler to implement on computers, provide a simple physical picture of the system and can be easily modified to deal with different aspects of traffic. However, in a traditional traffic CA model, the spatial resolution of CA and temporal resolution of simulation are low. Take TRAN-SIMS for example. The size of cellular automata is 7.5 m and the time step equals 1 s. In such a case, if a vehicle drives at a speed of 4 cells per s, the speed difference between 95 km/h (3.5 × 7.5 m/s) and 121 km/h (4.4999 × 7.5 m/s) will not be distinguished by simulation models. And the temporal resolution of 1 s makes the system hard to model different drivers' reaction time, which plays a very important role in vehicular movement models. In this paper, a microscopic traffic cellular automata model based on road network grids is proposed to overcome the low spatial and temporal resolutions of traditional traffic CA models. In our model, spatial resolution can be changed by setting different grid size for lanes and intersections before or during simulation and temporal resolution can be defined according to simulation needs to model different drivers' reaction time, whereas the vehicular movement models are still traditional CA models. By doing so, the low spatial and temporal resolution of CA model can be overcome and the advantages of using CA to simulate traffic are preserved. The paper also presents analyses of the influences on simulation of different 1D lane grid size, 2D intersection grid size and different combinations of temporal resolution and mean drivers' reaction time. The analysis results prove the existence of spatial and temporal resolution thresholds in traffic CA models. They also reveal that the size of grids, the combinations of different temporal resolutions and mean drivers' reaction time do pose influences on the speed of vehicles and lane/intersection occupancy, but do not affect the volume of traffic greatly.
机译：自从Creamer和Ludwig于1986年首次提出以来，基于细胞自动机（CA）的微观交通模拟模型就变得越来越流行。细胞自动机更易于在计算机上实现，可以提供系统的简单物理图像，并且易于修改以处理流量的不同方面。但是，在传统的交通CA模型中，CA的空间分辨率和仿真的时间分辨率都较低。以TRAN-SIMS为例。细胞自动机的大小为7.5 m，时间步长等于1 s。在这种情况下，如果车辆以每秒4个格的速度行驶，则95 km / h（3.5×7.5 m / s）和121 km / h（4.4999×7.5 m / s）之间的速度差将不会通过仿真模型来区分。 1 s的时间分辨率使系统难以对不同驾驶员的反应时间进行建模，这在车辆运动模型中起着非常重要的作用。为了克服传统交通CA模型的时空分辨率低的缺点，提出了一种基于路网网格的微观交通蜂窝自动机模型。在我们的模型中，可以通过在仿真之前或仿真期间为车道和交叉路口设置不同的网格大小来更改空间分辨率，并且可以根据仿真需求为不同的驾驶员反应时间建模来定义时间分辨率，而车辆运动模型仍然是传统的CA模型。通过这样做，可以克服CA模型的低空间和时间分辨率，并保留了使用CA模拟交通的优势。本文还介绍了不同的一维车道网格尺寸，二维交叉口网格尺寸以及时间分辨率和平均驾驶员反应时间的不同组合对模拟的影响。分析结果证明了交通CA模型中存在时空分辨率阈值。他们还发现，网格的大小，不同的时间分辨率和平均驾驶员反应时间的组合确实会影响车辆的速度和车道/交叉口的占用，但不会对交通量产生很大影响。

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