Trip assignment is still a modelling and prediction challenge. For aggregate analyses, it may suffice to use traditional trip assignment approaches. However, investigations of drivers’ choices with respect to network infrastructure changes require disaggregate and behavioural approaches. It is often crucial to investigate the effects of critical infrastructure elements in the network on drivers’ route choice behaviour. The case of Montreal is of particular interest because the city, an island, is completely separated from the rest of the region by two important rivers. Consequently, drivers have to select one of the available bridges to reach their destination. A large-scale travel survey conducted in Montreal in 2008 is used for empirical investigations. It is a one-day trip diary of approximately 4% of the city’s population and includes the bridge chosen in the itinerary for car driver trips. An advanced discrete choice model that jointly models choice set formation and final choice is then formulated and estimated using the observed trips. The empirical model correctly identifies the effects of travel time interacting with time of day and destination trip purpose. Empirical results show that age, gender and household auto ownership explain the variation of scale parameters of route/bridge choice. A discussion of the model’s performance is provided along with further result analysis and perspectives for further work.