Land travel has changed dramatically over the course of centuries. The car has become the favorite way of commuting. Increasingly, the road network is incapable of providing sufficient supply (capacity) for the demand (amount of cars) in rush hours resulting in congestion and delay, especially in dense urban areas such as the "Randstad". Congestion leads to significant societal and economic costs, directly because of the lost time and indirectly because congestion increases the unreliability of transport. For example, because of unreliable travel times, a driver plans to leave early. Without congestion, the result of demand and supply results in predictable traffic flows (in terms of travel time, costs, etc.) on the road network. A trip is said to be unreliable if the traffic flows exhibit conditions which were not expected by the traveller, which will often result in a negative experience with the traffic system for the traveller. Reliability thus depends on the expectations of the individual traveller and can be separated into variation and predictability. Large variation and low predictability lead to an unreliable situation. Drivers can deal with unreliability by changing their behaviour and choices, for example by choosing a different route or adapt their departure time. The reliability of a traffic system can be influenced by Advanced Traveller Information Systems (ATIS). ATIS aim at informing travellers about the current and future state of the transport system, such that the traveller can adjust the expectations or improve their experience with the traffic system. ATIS have been widely studied related to route choice, departure time choice and even mode choice or destination choice. However, most of this research is dedicated to information that targets at an optimal use of the network. Personalized traffic information takes into account the personal preferences, but also the context of the trip at hand. Especially this context can be of importance, as for a trip which is regularly made by a certain traveller the need for information is likely to be different than for a unique trip. In this thesis, the combination of non-recurrent traffic situations (as a combination of trip context and traffic flows in a road network) and traffic information is studied. This results in the following main objective: To gain more insight into the impact of traffic information on route choice behaviour in non-recurrent traffic situations