Multistage Game Model Based Dynamic Pricing for Car Parking Slot to Control Congestion

Abstract

Car parking has become expensive both in terms of money and the time to search for a free parking slot, especially in metropolitan cities. The parking lots nearer to shopping complexes or corporate buildings often get occupied, leaving the farther parking lots empty and leading to traffic congestion near these already busy areas. With a dynamic pricing strategy, the prices of high-demand parking lots can be surged up during peak hours, deviating the traffic towards the unoccupied, cheaper parking lots. A dynamic pricing strategy for car parking slots helps in fairly distributing the traffic among all the parking lots and helps in increasing the revenue of the parking lot management as well. However, increasing the prices unconditionally will affect the drivers. In this paper, a game-theory-based dynamic pricing strategy is proposed that aims to optimize the benefits for both the car parking management and the drivers. The goal is to find the Nash equilibrium price for peak hours and off-peak hours where the car parking management’s revenue is maximized while the price paid by the drivers is minimized. Simulation results show that the proposed model manages to reduce the congestion at peak hours and the profits of parking lot owners are increased.