This paper presents an economical Level of Service (LOS) estimation model using GPS data in mixed traffic conditions. It focuses on defining clusters based on Highway Capacity Manual (HCM) categories of motorized LOS for practical application. The study aims to enhance the representation of mixed traffic conditions utilizing Sri Lanka as a case study, especially for the prevalent LOS D and E categories observed on two-lane roads in the Indian sub-continent. Data collection spans across Sri Lanka to ensure the generation of more representative values for the defined clusters. The study employs image processing models for video analysis along with GPS data and utilizes unsupervised clustering to define clusters corresponding to HCM definitions. The proposed methodology and model aim to improve LOS representation, considering the Indian sub-continent’s unique road network and predominant traffic scenarios. The research findings produce a table containing parameters similar to HCM 15–2 (Motorized LOS parameters for 2-lane roads) but in a practical sense instead of a planning tool. The model developed in this study has the potential for practical applications in traffic management, infrastructure planning, and policy-making, leading to more effective and efficient transportation systems in the region.