Estimating the Benefits of Korea’s Intercity Rail Speed Increase Project: An Agent-Based Model Approach

Abstract

In the cost–benefit analysis of urban transportation investment, a logsum-based benefit calculation is widely used. However, it is rarely applied to inter-regional transportation. In this study, we applied a logsum-based approach to the calculation of benefits for high-speed projects for inter-regional railways in Korea’s long-term transportation plan. Moreover, we applied a behavioral model in which an agent travels beyond the zones assumed by an aggregate model. In the case of South Korea, such a model is important for determining transportation priorities: whether to specialize in mobility improvement by investing in a high-speed railway project, such as the 300 km/h Korea Train eXpress (KTX), or to improve existing facilities, such as by building a relatively slower railroad (150–250 km/h) to enhance existing mobility and accessibility. In this context, if a new, relatively slow railroad were constructed adjacent to a high-speed railroad, the benefits would be negligible since the reduction in travel time would not sufficiently reflect accessibility improvements. Therefore, this study proposes the use of aggregate and agent-based models to evaluate projects to improve intercity railway service and conduct a case study with the proposed new methodology. A logsum was selected to account for the benefits of passenger cars on semi-high-speed and high-speed railroads simultaneously since it has been widely used to estimate the benefits of new modes or relatively slow modes. To calculate the logsum, this study used input data from both the aggregate and individual agent-based models, and found that an analysis of the feasibility of inter-regional railroad investment was possible. Moreover, the agent-based model can also be applied to inter-regional analysis. The proposed methods are expected to enable a more comprehensive evaluation of the transport system. In the case of the agent-based model, it is suggested that further studies undertake more detailed scenario analysis and travel time estimation.

Effects of Exclusive Lanes for Autonomous Vehicles on Urban Expressways under Mixed Traffic of Autonomous and Human-Driven Vehicles

“…KTDB is a publicly available travel demand database that includes origin-destination (O-D) trip data and transportation networks to which travel demands can be assigned under various AV operating scenarios. It is commonly believed that KTDB is the most reliable transportation database in South Korea and numer-ous macroscopic transportation studies are conducted using its network and O-D trips [30]. Emme4 performs a static user equilibrium assignment of auto traffic [11,18,31].…”

“…The data were constructed based on the conditions of the year 2019. Each link in the road network data contains information on length, number of lanes, and capacity [30]. In addition, the link includes an associated volume delay function (VDF) that relates the travel time to the volume-to-capacity ratio [11].…”