یک رویکرد مبتنی بر یادگیری ماشین در مورد قیمت گذاری پارکینگ هوشمند
Abstract
1- Introduction
2- Literature review
3- Problem formulation
4- The methodology
5- Results and discussions
6- Conclusion
References
Abstract
Now-a-days, with the ever increasing number of vehicles, getting parking space at right place and on time has become an inevitable necessity for all across the globe. In this context, finding an unoccupied parking slot by the interested vehicle owners with least overhead becomes an NP-Hard problem bounded by various constraints. In-advance availability of information regarding parking occupancy plays a major role in hassle free trip optimization for motorists. It also facilitates services-cum-profit management for the parking owners. It further helps in curbing congestion by reducing cruising time and hence, helps in controlling pollution of the smart cities. Thus, accurate and timely information regarding parking occupancy and availability has become the basic need in the evolution of the smart cities. Motivated by these facts, an occupancy-driven machine learning based on-street parking pricing scheme is proposed in this paper. The proposed scheme uses machine learning based approaches to predict occupancy of parking lots, which in turn is used to deduce occupancy driven prices for arriving vehicles. In order to train, test, and compare different machine learning models, on-street parking data of Seattle city has been used. To the best of our knowledge, this is the first time that parking occupancy prediction system is used to generate occupancy based parking prices for on-street parking system of the Seattle city. Results obtained using the proposed occupancy driven machine learning based on-street parking pricing scheme demonstrate its effectiveness over other existing state-of-the-art schemes.
Introduction
In most of the cities around the world, parking is considered to be a big problem because of many reasons, such as increase in population size, number and size of vehicles, limited parking spaces, traffic congestion on roads, locations of parking lots etc. With the rapid increase in the number of vehicles, getting and providing parking slots has become a challenge for the parkers and transport authorities/owners respectively. Usage of private vehicles over public transportation is always individual’s choice due to varying comfort levels, less travel time, and ease of travel etc. With increase in private vehicles, cruising time and congestion increases invariably. Most of the vehicles spent significant time on roads in searching parking spaces instead of commuting. This increases congestion on the roads. Situations get even worse during rush hours and near hot spots. This unnecessary congestion leads to overcrowding of vehicles, increase in carbon emissions, and raises various traffic management problems.