Managed lanes represent various operational level traffic management strategies, such as high-occupancy vehicle lanes, truck lane restrictions, and dynamic lane assignments, all aimed at optimizing traffic flow and reducing traffic congestion within a specific time window. Traditionally, the effectiveness of these strategies has been evaluated using micro-simulation models, which typically relied on aggregated traffic parameters (e.g., traffic volume, speed) as performance measures. Past studies have often overlooked the calibration of driving behaviour parameters that significantly influence drivers’ car-following and lane-changing behaviours. This study introduces a virtual reality based micro-simulation interface that integrates the conventional micro-simulation model (PTV Vissim) with Unity’s game engine. This human-in-the-loop simulation enables users (e.g., drivers) to interact with Vissim-generated traffic in a virtual environment. By incorporating real-time human input, this approach allows for the calibration of driver behavioural parameters that extends the capabilities of conventional micro-simulation models. This study outlines the creation of a 3D road network, the development of a real-time data transmission mechanism between Vissim and Unity, and the design of intuitive user interface. This approach is applied to 12km section of Highway 401 in Durham Region, Ontario, Canada, to demonstrate its application. The developed interface allows for more realistic driving behaviour to be incorporated into the micro-simulation that can improve the evaluation of managed lane tactics. This approach provides more accurate and customised modelling outcomes that offer valuable insights for transportation planners and decision-makers to mitigate the risks associated with large-scale infrastructure investments.