# Sustainable Parking Space Management Using Machine Learning and Swarm Theory--The SPARK System
## 2 Literature Review  
### Parking Spaces: A Growing Urban Challenge  
The main issue addressed in this study is the escalating problem of vehicle congestion and the shortage of parking spaces in large cities and densely populated urban areas. The problem of insufficient parking spaces in these areas has become increasingly critical due to rapid urbanization, rising vehicle ownership, and limited land availability. This shortage exacerbates several significant global problems:  
* Increasing pollution: fuel is wasted as drivers search for available parking spots, contributing to higher emissions. This also applies to other environmental pollutants related to vehicle usage. * Growing congestion: illegal parking practices further clog streets, exacerbating traffic congestion. * Time consumption: drivers spend excessive time looking for parking spaces, leading to frustration and reduced productivity. * Business losses: the lack of adequate parking spaces can deter customers, resulting in economic losses for local businesses. Due to this fact, many studies have been conducted to describe and try to find solutions for this growing problem that every human is affected by. In the literature review, two main approaches to this topic can be found. The first involves designing parking spaces in city areas or increasing the efficiency of finding parking spaces. In the study, 'Modelling of the Movement of Designed Vehicles on Parking Space for Designing Parking' [10], the authors claim that the pace of addressing the lack of parking spaces is several times slower than the rate of transport growth among citizens. Consequently, the authors aim to determine the optimal size of parking spaces for designing parking areas, which are an integral part of the road infrastructure. A study on Banja Luka's city center in Bosnia and Herzegovina highlights the problem caused by infrastructure expansion, resulting in the loss of 442 public parking spaces. The proposed solution involves converting certain streets into new street parking spaces, adding 220 spots to alleviate the deficit [11]. In Paris, a policy to curb the influx of high-emission vehicles through escalated parking fees for non-residents aims to reduce urban pollution and encourage sustainable urban mobility, contributing to a healthier urban environment [12]. Meanwhile, a study in China proposes a tiered pricing strategy for Park and Ride facilities based on subway ride distances, promoting efficient use of parking resources and reducing congestion [13]. Additionally, the development of a Vehicle Parking Management System (VPMS) demonstrates how smart city solutions can enhance urban mobility and reduce environmental impacts [14]. These studies collectively emphasize the need for innovative policies and technological advancements to address parking shortages and promote sustainable urban development. In line with these findings, the study by [PERSON] and [PERSON] [15] addresses the urban parking challenges in Hangzhou, China, due to increasing vehicle numbers. It identifies key issues such as parking shortages, inefficient car park usage, and inadequate management structures. The authors propose solutions including enhanced urban parking planning, better management mechanisms, and increased involvement of social forces in car park development and management. One approach to mitigating vehicle congestion is the implementation of a solution called SlotFinder. SlotFinder is an innovative car parking system designed to tackle the issue of parking shortages in densely populated urban areas. By leveraging advanced spatio-temporal analysis and machine learning techniques, SlotFinder aims to optimize the utilization of available parking spaces, thereby reducing the time and fuel wasted in searching for vacant spots. The system collects data from various locations and employs sophisticated algorithms to predict parking availability, significantly enhancing overall urban traffic management and efficiency.