At large-scale events, the large inflow of visitors travelling by car often causes queues on the roads in the direct surroundings of the event. These queues can spill back to the main road network, where through traffic is driving as well: this through traffic will be hindered by the congestion, while those travellers don’t have the event venue as their destination. To prevent or at least reduce this unnecessary hindrance caused by car traffic at events, this Master thesis has researched control methodologies to optimise advice that is given to individual travellers using in-car systems. In individual traffic management (ITM), the event visitors will receive advice for their route and departure time choice. ITM can be used to optimise the decisions of the event visitors, to prevent queue spillback and other traffic issues at events. In this thesis, the design trade-offs for an ITM controller are identified: these trade-offs determine the actual design of an ITM controller aimed specifically at car traffic around large-scale events. Conceptually, the controller design is composed of a one-shot prediction model and mathematical optimisations of the individual route and departure time advice. These optimisations target a constrained system optimal traffic state in the network. Simulations of the designed controller show that ITM has potential to alleviate the congestion (and spillback) hindrance at large-scale events, by distributing event visitors over alternative routes and departure times. The benefits found in the simulations advocate the use of ITM at an event (or event-like conditions) in practice. Therefore, the application of the ITM controller design in practice is also discussed in this research. The discussion identifies the need to develop a (software) tool that is able to execute the controller’s actions in an offline or real-time manner. Furthermore, the possible barriers and opportunities for the implementation of ITM in the current and future traffic system are assessed.