A Glimpse at the Future Technological Trends of Road Infrastructure: Textual Information-Based Data Retrieval

Abstract

Since the Fourth Industrial Revolution was announced in 2015, relevant key technologies have recently merged and have extensively affected our society. To provide empirical insights into the future and address expected issues in the context of transportation, this study seeks to investigate how future road infrastructure technology will shift. Going over the mainstream future road infrastructure inspired by the strategy implemented in the Korean New Deal 2.0, we extract central keywords explaining what specific technologies and political directions will prevail globally. In particular, a specific morphological analyzer, Mecab-Ko, which is suitable for Korean is selected after comparing a variety of packages. Then, a specific text mining approach is employed to collect textual online sources (news articles, research articles, and reports) written in Korean while most studies gather information written in English. Using the term frequency-inverse document frequency (TF-IDF), 11 keywords were extracted from unstructured textual online sources. Topic modelling with latent Dirichlet allocation (LDA) is subsequently performed to classify them into four groups: an unmanned payment system, intelligent road infrastructure, connected automated driving road, and eco-friendly road. Based on these findings, we can take a glimpse into how the future road infrastructure in Korea will be reshaped. Evidently, a digitalized road without a human component is around the corner. Fully automated systems will soon become available, and the keyword sustainability will continue to receive critical attention in the transportation sector.