• Journal of the Economic Geographical Society of Korea
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• v.10 no.4
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• pp.427-443
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• 2007

The purpose of this study is to investigate spacio-temporal structures of traffic flows on the subway network in the Metropolitan Seoul, and the relationships between topological structures of traffic flows and land use patterns. In particular we analyze in the topological structures of traffic flows on the subway network in time dimension as well as in spatial dimension. For the purpose, this study utilizes data mining techniques to the one day T-card transaction data of the last four years, which has developed for exploring the characteristics of traffic flows from large scale trip-transaction databases. The topological structures of traffic flows on the subway network has changed considerably during the last four years. The volumes of traffic flows, the travel time and stops per trip have increased until 2006 and decreased again in 2007. The results are visualized by utilizing GIS and analyzed, and thus the spatial patterns of traffic flows are analyzed. The spatial distribution patterns of trip origins and destinations show substantial differences among time zones during a day. We analyze the relationships between traffic flows at subway stops and the geographical variables reflecting land use around them. We obtain 6 log-linear functions from stepwise multiple regression analysis. We test multicollinearity among the variables and autocollelation for the residuals.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.17 no.5
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• pp.14-28
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• 2018

Thanks to technical improvement on the vehicle to vehicle communication and the intelligent transportation system, gradual introduction of the autonomous vehicles is expected soon in the market. The study analyzes the autonomous vehicles' impacts on the network efficiencies. In order to measure the network efficiencies, the study applies the sequential procedures that combines the microscopic and macroscopic simulations. The microscopic simulation attends to the capacity changes due to the autonomous vehicles' proportions on the roadway while the macroscopic simulation utilizes the simulation results in order to identify the network-wide improvement. As expected, the autonomous vehicles efficiently utilizes the existing capacity of the roadway than the human driving does. Particularly, the maximum capacity improvements are expected by the 190.5% on the expressway. The significant capacity change is observed when the autonomous vehicles' proportions are about 80% or more. These improvements are translated into the macroscopic model, which also yields overall network efficiency improvement by the autonomous vehicles' penetration. However, the study identifies that the market debut of the autonomous vehicles does not promise the free flow condition, which implies the possible needs of the system optimal routing scheme for the era of the autonomous vehicles.