Effective pedestrian facilities are essential for promoting walking and supporting urban mobility objectives for municipalities. Conventional pedestrian level-of-service (PLOS) assessments rely on density as an indicator but fail to account for movement restriction, such as “shoulder brushing” or “bumping others.” This study introduces an innovative approach to real-time PLOS estimation that captures density and accounts for restricted movement. The system development consists of three phases: Detection, PLOS Modeling, and Application. Initially, a virtual camera within a game engine (Unity) replicates a real-world detection system to capture the trajectory of pedestrians on a second-by-second basis. Next, a traffic micro-simulation (Vissim) models pedestrian movement, deriving mathematical indicators to quantify density and restricted movement. These indicators are computed in real-time, offering enhanced PLOS measurement. Finally, the model is tested through a case study with countermeasures proposed to improve PLOS. The pilot study conducted on York Lane at York University, Toronto, Ontario, evaluates one base scenario and five alternatives. Under similar conditions, removing static obstacles improved restricted movement by 10%, while eliminating dynamic obstacles yielded a 15% improvement in comparison to the base scenario. The real-time virtual PLOS estimation system offers urban planners an effective tool to minimize restricted movement and enhance pedestrian infrastructure.
