Optimizing Parking Dynamics in Urban Areas: A Mathematical Model for Pune, Maharashtra

The absence of parking spaces and the resulting urban congestion are the two more significant problems in rapidly urbanizing places like Pune and Maharashtra. The current parking problems, which are brought on by the fast increase in the number of automobiles, result in heavy traffic, a shortage of space, and decreased mobility. This work proposes a mathematical approach to address these issues by combining adaptive parking capacity and dynamic pricing, which increases parking capacity while lowering traffic. In order to create a model that can decrease traffic and increase parking efficiency, real data was gathered from the busiest parts of the Pune region, including the study area, J.M. Road. According to the developed model, adaptive capacity can minimize congestion by up to 20% during peak hours, while dynamic pricing aids in supply and demand balance. Legislators and urban planners may find these findings helpful in creating more efficient parking structures that support enhanced mobility, smoother traffic flow, and sustainable urban growth. The suggested mathematical model updates Pune's parking infrastructure, which adds to the city's growing urbanization.