The importance of traffic planning has, throughout the years, been in- creased, providing sustainable developments of traffic and infrastructural investments. The analysis of the current traffic situation and the evalua- tion of the effects of a future investment are crucial for the socio-economic benefits maintenance. These analyses and evaluations are most commonly done using traffic simulation models. One of the main traffic planning aims, nowadays, is to increase the number of public transport users against the number of private car users. This change in mode choice is called transition effect and could be beneficial both from an environmental and socio-economic perspective. This thesis aims to evaluate and improve the macroscopic traffic demand and transition model, used fot the city of Norrköping. Additionally, the thesis investigates if a general transition Logit model can be developed and which parameters are the most important to be included in a modal choice estimation. For the needs of this study, the traffic planning software Visum is used. The travel mode distribution is calculated by Logit models coded in Python-scripts integrated in Visum. Then, a traffic assignment is performed by Visum, computing new travel times as inputs to the Logit model and this iterative procedure continues until the system reaches an equilibrium. The thesis aims for a more reliable prediction of the transition effect by correcting the Python-scripts and estimating the parameters of the Logit model using data from surveys. The study shows that travel times is the most important factor for realistic results generation. However, the data used for the estimation of the Logit model parameters did not include sufficient information of travel times. The travel times had to be calculated, using two different methods, in order to be included in the estimation of new parameters. Although these methods could not provide any positive effects on the transition, they did prove the importance and significance travel time have when developing a traffic model. The result of the study invokes the importance to further develop the method of calculating travel times, when the input data is not sufficient, and shows that the travel time parameters are case specific.