<p>This study investigates the critical role of optimized parking model in improving traffic flow in Central Delhi and New Delhi, two of the most congested urban areas in India. By addressing key parking-related factors, the research explores how these factors exacerbate urban traffic flow. The study employs a comprehensive parking behavior survey of 3000 drivers. This study employs a Two-Phase Parking Choice Model (PCM) and statistical correlation to analyze parking behavior and its impact on traffic flow. Key findings reveal that the implementation of real-time parking guidance systems can significantly reduce average cruising times by 25%, mitigating congestion and enhancing road capacity. Furthermore, strategically designed off-street parking facilities decreased illegal parking by 20%, and shown to alleviate demand for on-street parking and curb illegal parking practices. Statistical analyses, including correlation and regression models, highlight the direct relationship between parking search times and the congestion index, with each additional minute of cruising time increasing congestion by approximately 3.2%. This study uniquely addresses the gap in context-specific research by tailoring PCM model to the distinct urban conditions of Central and New Delhi, providing scalable interventions for high-density urban environments. This research provides actionable insights for urban planners and policymakers, emphasizing the transformative potential of integrating smart parking technologies and tailored policy interventions to optimize traffic flow. The findings contribute to the broader discourse on sustainable urban transportation, offering scalable solutions for high-density urban areas globally.</p>