Fuzzy cellular model for on-line traffic simulation
This work addresses the need for realistic on-line traffic simulation under uncertainty for traffic control applications, but the contribution is incremental as it applies fuzzy sets to an existing cellular automata framework.
The paper introduces a fuzzy cellular model for on-line traffic simulation that handles uncertainty in input data and results, modeling vehicles individually with fuzzy parameters. In a queue discharge simulation, the model's queue length changes were compared to the NaSch cellular automata model, showing its applicability for traffic control.
This paper introduces a fuzzy cellular model of road traffic that was intended for on-line applications in traffic control. The presented model uses fuzzy sets theory to deal with uncertainty of both input data and simulation results. Vehicles are modelled individually, thus various classes of them can be taken into consideration. In the proposed approach, all parameters of vehicles are described by means of fuzzy numbers. The model was implemented in a simulation of vehicles queue discharge process. Changes of the queue length were analysed in this experiment and compared to the results of NaSch cellular automata model.