Abstract

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 TRANSIMS 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.

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