David Ulčák

The research in this article deals with verifying the deficit of parking spaces from model examples in the city of Ostrava, Czech Republic. Specifically, it deals with the possibilities of solving these deficits using automated parking systems. The main data collection took place between 2010 and 2019; later, supplemental lockdown data (up until May 2022) were obtained. The main objective of this article was to use data to determine the profitability and functionality of automated parking systems in mid-sized cities such as Ostrava. The RING system was chosen as a suitable model for the automated parking system. The data (using a least-squares approximation) were used via statistical methods to make predictions for future years, including the construction of confidence limits for a given significance level. Based on data from 2011–2019, we found that the RING system would be profitable with a probability of 92.45% in the following years. We compared these predictions with the actual data and made a new prediction.

The underlying cause of the problem with parking is the imbalance between demand and supply in key areas where demand for parking is high, but parking is limited due to excessive land prices. Newly-developed automated multi-storey parking facilities are able to automatically pick up and place cars on different storeys, with minimal requirements on space. In the paper we concentrate on Automated Parking Systems and their malfunction rate. Specifically, we analyzed two automated systems located in the Czech Republic, in the towns of Brno and Slaný. We employed time series and various testing hypotheses to compare the malfunction rate of the systems, and used information from practice. We conclude with an evaluation and a brief description of the optimization of systems and the use of innovative tools.