Investigation of car park preference by intelligent system guidance

Abstract

In recent years, especially in developing countries, the number of vehicles has rapidly increased, leading to an increase in the demand for parking spaces. The most effective method to overcome this is to efficiently manage existing car parks. For this purpose, intelligent transportation system (ITS) applications have been used for facilities. In this study, the effect of guidance according to parking preferences on the utilisation of car parks with the support of an intelligent parking guidance system is examined. The preference and choice of car parks were modelled based on the observed data by developing a simulation program and testing the validity of the model. Subsequently, the effects of various parameters (e.g., parking fees, walking distance, and driving distance) on the selection of car parks, which have been ignored in the existing ITS, were included in the examination of the model. The results indicate that the driving distance and carbon dioxide emission, walking distance, and parking fees are reduced by 17, 14, and 1%, respectively. This study shows that system efficiency can be enhanced by considering additional car park preference parameters in intelligent parking system designs and management. © 2020 Elsevier Ltd