Algorithmic planning, simulation and validation of smart, shared parking services using a last mile hardware

Abstract

A major problem due to increased usage of vehicles is parking. In the work, we address the problem of parking by the use of a model called ’Smart Shared Private Parking’. In an urban area mixed with commercial and residential buildings, a household owner i.e. a resident keeps their parking lots not utilized during their office hours, long duration of shopping and vacations. An important question is how to make the residents provide their parking spaces. This can be made possible by hardware and efficient communication about the services offered. The work explains the conceptual deployment of such hardware and communication mechanism. This in turn helps to achieve the involvement of common residents to benefit from renting out their space and also help the drivers to utilize such services and reduce their expenses due to possibly competitive pricing scheme. For effective analysis of the model, we propose an infrastructure setup required to analyze various aspects of the model. To start with, the work highlights how a communication strategy could effectively reduce the number of times a vehicle is rerouted in search of a parking spot. Apart from reducing the commute time of a driver, this reduces the CO2 emissions. The beneficial aspects of the proposed solution for a vehicle (i.e. a car driver) are obtained by estimating and comparing vehicular emission in scenarios with and without such shared parking lots provisioned. The work proposed also highlights the beneficial aspects from a parking lot owner’s point of view. The first one among the beneficial aspects is how the parking lots are utilized in the time frame considered. This is achieved by comparing the utilization of commercial parking lots and shared parking lots with and without the proposed parking model in place. The next beneficial aspect is how the model helps the parking lot owners to earn money by lending their parking spaces. Finally, the work proposed presents a correlation analysis. This helps to conclude how the change in the number of such shared private parking lots affects the vehicles and the model itself through some metrics.