The increasing demand for efficient and resilient transportation systems in the face of climate change necessitates innovative solutions for parking management. Dynamic pricing, also known as demand-based pricing, is a pricing strategy that adjusts prices in real-time based on demand and supply. This approach has been widely adopted in various industries, including airlines, hotels, and ride-sharing services. In recent years, there has been a growing interest in applying dynamic pricing to parking management. This paper proposes a dynamic pricing algorithm for private parking lots that utilizes real-time data on parking occupancy and traffic conditions within a 500-m radius to optimize parking revenue, minimize congestion, and encourage alternative transportation modes. The algorithm employs a dynamic pricing mechanism that adjusts parking rates in real-time based on occupancy data. This approach ensures optimal utilization of parking spaces, minimizing congestion and maximizing revenue generation. Additionally, the algorithm considers traffic conditions in the immediate vicinity, enabling a responsive and adaptable pricing strategy that aligns with the broader objectives of sustainable urban transportation. By aligning parking pricing with dynamic demand factors, this algorithm contributes to a more efficient, resilient, and environmentally responsible urban transportation system.