Agent Mobility Model based on Street Centrality

Current agent mobility models are based on random movement. This means that the probability that a particular agent will be at a particular place is the same over the whole network. In contrast, we are trying to simulate an agent movement that reflects more realistically the distribution of vehicles in an urban street network. This can be achieved by moving away from the problem of an equal probability to a more unequal probability that is based on betweenness centrality, such that agents have a definite preference to traveling on a particular path.