Effects of traffic speed level on frustration index in cellular automata traffic simulation

Traffic system shows a very complex and stochastic features, but it seems to be simulated successfully by cellular automata (CA) models. Various models have been developed in order to study and understand traffic behavior and network traffic situations. In this study, the relationship for speed and frustration index is simulated by CA under multi-class user traffic conditions. Acceleration rule, slow down probability, traffic density, maximal and minimal speeds are main effects, which determine driving behavior. According to the results, it is found that either the mixture of the average speed-frustration index or density-frustration index of multi-class traffic is the linear combination of users involving in traffic flow. Therefore, to gain a better understanding on multi-class user traffic is better to simulate it directly instead of estimating it by using the combination of each user.