Final Activity Report Summary - MASCOT (Behavioural Modelling and Simulation of Congested Traffic) Microscopic traffic simulation, which captures traffic phenomena through detailed representation of individual drivers and their behaviour, is increasingly being recognised as an important tool for traffic analysis. Explicit and detailed modelling of the behaviour of individual drivers allows the simulation to be used to study not only traditional traffic engineering problems but also for intelligent Transportation Systems (ITS) applications and traffic impacts, such as safety analysis, energy consumption and air pollution. The fidelity of microscopic traffic simulation results heavily depends on the quality of the driving behaviour models it uses. However, there are significant gaps in the ability of current driving behaviour models to replicate the behaviour of real-world drivers. This project focuses on developing new driving behaviour models that facilitate development of microscopic simulators. In particular, new models were developed and estimated for some of the key driving behaviours, namely lane changing, gap acceptance and overtaking. Advances in modelling of lane changing behaviours were made in several directions: new models take into account persistence, anticipation and impatience on drivers' actions using advanced econometric methods. Furthermore, our results show that lane changes, which are often modelled as instantaneous events, take a significant time to be completed. Overtaking in two-lane roads is a behaviour that has important implications on traffic safety and performance. A model for the decisions drivers make whether to overtake or not was developed and estimated using data that was collected in a specialized driving simulator experiment. Factors affecting overtaking behaviour include the relations between the subject vehicle and its surroundings, as well as characteristics of the road facility and the driver himself.