A new “Smart Parking” System Infrastructure and Implementation

Abstract

We propose a new “smart parking” system for an urban environment. The system assigns and reserves an optimal parking space for a driver based on the user's requirements that combine proximity to destination and parking cost, while also ensuring that the overall parking capacity is efficiently utilized. Our approach solves a Mixed Integer Linear Program (MILP) problem at each decision point in a time-driven sequence. The solution of each MILP is an optimal allocation based on current state information and subject to random events such as new user requests or parking spaces becoming available. The allocation is updated at the next decision point ensuring that there is no resource reservation conflict and that no user is ever assigned a resource with higher than the current cost function value. Implementation issues including parking detection, reservation guarantee and Vehicle-to-Infrastructure (V2I) or Infrastructure-to-Vehicle (I2V) communication are resolved in the paper. Our system can save driver time, fuel and expense, while reducing the traffic congestion and environment pollution. We also describe a deployment and testing pilot study of the system in a garage at Boston University.