The urban public transport system in Casablanca, one of the major Moroccan cities, offers different alternatives. But the system is not efficient enough. Transportation options are rather frustrating, time-consuming, and sometimes risky. Many residents experience long and expensive commutes in often uncomfortable and unsafe vehicles through heavy traffic. In such a context, simulation can help to support urban mobility decision-makers in the task of shaping transportation initiatives. In this paper, we focus on improving the urban mobility system using an agent-based model. It offers the ability to capture and reproduce the mobility behavior of commuters.