This study developed a dynamic traffic control formulation designated as Dynamic Intersection Signal Control Optimisation (DISCO). DISCO considers the entire Fundamental Diagram, which is essential for controlling congested and transient traffic. As a dynamic model, DISCO works with time-variant traffic patterns and derives dynamic adaptive timing plans. In this thesis, we added some new features to DISCO and applied them to two congested spots in Hong Kong, and then validated DISCO with the site measurements. Our results showed that DISCO's delay estimates compared well with site measurements. This established DISCO as a reasonable traffic-modelling platform. We also compared two solution methods: Steepest descent (SD) and genetic algorithm (GA). Although the delay results showed that GA out-performed SD for all the scenarios tested, SD could further reduce the solution time by as much as 98% with a reasonable improvement from the Webster formula. DISCO shows promising results as a new approach for demand-responsive traffic control.