Performance Evaluation of Road Traffic Control Using a Fuzzy Cellular Model
For traffic engineers, this offers a way to evaluate control performance under measurement uncertainty, but the contribution is incremental as it combines existing techniques (cellular automata and fuzzy logic).
The paper proposes a method for evaluating road traffic control performance using a fuzzy cellular model, enabling optimization of adaptive strategies. Experimental results show the method handles imprecise measurements and provides uncertainty quantification for control decisions.
In this paper a method is proposed for performance evaluation of road traffic control systems. The method is designed to be implemented in an on-line simulation environment, which enables optimisation of adaptive traffic control strategies. Performance measures are computed using a fuzzy cellular traffic model, formulated as a hybrid system combining cellular automata and fuzzy calculus. Experimental results show that the introduced method allows the performance to be evaluated using imprecise traffic measurements. Moreover, the fuzzy definitions of performance measures are convenient for uncertainty determination in traffic control decisions.