Estimating Revenues of Integrated Fare System for Seoul Metropolitan Public Transportation using Smartcard Data

Abstract

The Integrated Fare System for the Seoul Metropolitan Public Transportation Network) is one in which the metropolises of Seoul, Gyeonggi, Incheon, However the Smartcard data indicates the movement of passengers based on subway terminal IDs. Therefore, it is difficult to analyze the exact route of passengers in the presence of transfer stations. This unknown information in turn leads to the problem of fare calculation and revenue allocation by transportation agencies. In the case of the passenger's undetermined route, the fare is calculated by assuming that the fare is based on the minimum travel distance, not based on the actual route of the passenger. As these routes and fare routes appear as different results, the settlement between bus and subway is established on day-to-day settlement between operating agencies of the current metropolitan integrated fare system. However, settlement between subway operating agencies is carried out every to 5 years by establishing a model that estimates the actual travel route of passengers. Currently, the issue of settlement of subway transport agencies has become a very important role in the operation of transport agencies. Also, due to the agreement on transfer loss compensation between local governments, the situation of the dispute is expanding to a problem that is extended at the government level. This problem is expected to be exacerbated by the entry of new private transportation means such as GTX, light rail, and KTX, and regional expansion of the fare system. This study, estimate the fares charged to passengers as settlement fees, additional fees, separate fees, and independent fees by modeling the minimum time route search and minimum distance route search linking the departure and arrival terminal IDs of the Smartcard. In this case, the minimum time route was assumed to represent the actual movement of passengers and applied as a method for distribution of revenues by transport agencies along with separate fares from privately financed agencies. The minimum distance route was applied to simulate the added fare method currently applied in the subway. As a route search technique, the metropolitan subway was recognized as a network composed of terminal IDs, and Big Node was applied as a station name composed of a set of terminal IDs. Also, due to the need to consider transfers and multiple stages in the subway network, we proposed a method to ensure an optimal solution without network expansion by introducing link-label method. Theories and case studies that are used in the allocation of revenues of actual transportation organizations are presented.

스마트카드자료는 수도권 지하철의 승객의 이동을 단말기ID로 나타내기 때문에 환승역이 존재하는 상황에서 승객의 이동경로를 분석하기 어렵다. 따라서 지하철 승객의 이동은 요금산정 및 운송기관의 수입금배분과 관련되어 승객이동경로의 미확정문제가 확대되고 있는 실정이다. 본 연구는 스마트카드의 출발-도착 단말기ID를 연결하는 최소시간경로탐색과 최소거리경로타색을 시행하여 승객에게 부과되는 요금을 추가요금, 별도요금으로 추정하는 방안을 마련하였다. 이때 최소시간경로는 승객의 실제이동을 대변하는 것으로 가정하고 민자기관의 별도요금과 함께 운송기관의 수입금배분 방안으로 적용하였다. 최소거리경로는 현재 지하철에서 적용하는 추가요금부과방식을 모사하기 위하여 적용하였다. 경로탐색기법으로 수도권 지하철을 단말기ID로 구성된 네트워크로 인식하고 빅노드를\ 단말기ID 집합으로 구성된 역사명으로 적용하였다. 또한 빅도드로 구축된 지하철 네트워크가 환승과 다수단을 고려할 필요성으로 인하여 링크표지를 도입하여 네트워크확장없이 최적해를 보장하는 방안을 제안하였다. 탐색된 최소거리 및 시간경로를 통하여 요금을 산정하고 누락된 민자기관의 별도요금을 개선하며 무임승차에 대한 운송기관의 수입금 배분기여도를 산정하여 사례연구로서 제시하였다.