An Improved Ant Colony Optimization Based Parking Algorithm with Graph Coloring.

In an era which is going towards the spread of smart cities and intelligent transportation systems, vehicular ad hoc networks are an interesting framework to propose innovative solutions. One of the most tedious problems for drivers in a urban environment is the parking process. Indeed, drivers looking for an available parking slot keep being the main cause of traffic congestion, which also involves a high stress and air pollution level. In this work, we provide a smart parking solution, aiming at a higher context awareness for drivers, by relying on a well known optimization problem, the ant colony. By choosing an opportune criterion to update the pheromone, we push drivers to choose possibly uncrowded paths, ending up with a solution which guarantees a fair node distribution with respect to the available parking slots.