With advances in the technology applied to automated driving systems (ADSs), active efforts have been made to evaluate the safety of ADS in various complex situations using simulations. In accordance with these efforts, numerous institutions have developed single-scenario pools that reflect a variety of road and traffic characteristics and ADS performances. However, a single scenario has limitations in comprehensively evaluating the performance of complex ADS. Therefore, this study proposed a methodology that combines and transforms single scenarios into multiple scenarios. This aided in continuously evaluating the ADS performance over entire road segments and implemented this methodology in the simulations.

This study develops a methodology based on benefit-cost analysis for exclusive lane (i.e., high-occupancy vehicle lane) operation, in consideration of the advantages and disadvantages of the exclusive lane operation of zero emission vehicles, in order to estimate the feasibility of the zero emission vehicle exclusive lane operation and ultimately provide a recommendation to policymakers. While the major benefit of zero emission vehicles on an exclusive lane is travel time savings to all types of vehicles and the major cost of that is the increases of congestion and accident on an exclusive lane, the results show that the benefit in travel time savings was more significant compared to the cost in congestion and accident. This implies that the operation of zero emission vehicles exclusive lane is advantageous and can be an effective strategy for promoting eco-friendly vehicles to address environmental issues.

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.