• Proceedings of the Korean Association of Geographic Inforamtion Studies Conference
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• 2008.06a
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• pp.275-279
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• 2008

본 논문은 제주 택시 텔레매틱스 사업의 운영 결과 축적된 히스토리 정보를 기반으로 택시들의 운행기록을 분석하여 승객들이 택시를 찾는 지점을 분석하는 기법을 제시하고 이를 바탕으로 시간별 지역별 링크별 승차 패턴을 분석한다. 이를 위하여 택시의 상태도 천이에서 승차지점을 추출하였으며 해당 데이터를 데이터베이스 테이블에 저장하였다. 이후 승차지점들을 그루핑하여 승차 패턴의 추이를 발견하고 이에 대한 분석을 수행하였다. 이 분석 데이터는 택시들을 지역별 시간대별로 승객이 많이 찾는 위치로 이동시키고 택시의 공차 운행율을 감소시키는 배차 방식을 개발하여 택시의 영업 수익 증대와 승객의 택시 대기시간 감소를 기할 수 있다.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.16 no.4
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• pp.76-91
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• 2017

The Area of a domestic railway station is designed based on the 4-step traffic demand forecasting model with the average daily passenger count as one of its parameter. However, nowadays, due to increasing rate of railway station's function, the non-passengers are increasing. In order to consider those non-passengers who aren't using trains, assumed volume are added to the average daily passenger count of station to estimate the area, but the criteria being applied has no concrete basis. Therefore, this study aimed to recalculate the increasing non-passenger rate based on actual survey data of station users in any type of railway station to obtain the optimum area. Subsequently, the the design area was performed through pedestrian simulation. According to the result of the simulation, it was found that the total space of the exciting railway stations can be reduced up to 45% and will still satisfy the level of service(LOS) requirement.

• Journal of Energy Engineering
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• v.8 no.1
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• pp.1-6
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• 1999

사울 지역을 대상으로 TDM 수단의 도입 및 연비 향상대책 등에 의한 에너지절약 효과를 분석한 결과, 승용차의 경우 1) 함께타기 촉진에 의한 승차율이 2% 정도 향상될 경우 서울여객 소비의 3.3%(전국여객 소비의 1.0%), 2) 버스전용차개선제 등의 TDM 수단이 도입.시행에 따라 서울여객 소비의 2.6%(전국여객 소비의 0.8%), 3) 2000년까지 자동차 연비목표치가 달성되면 서울여객 소비의 3.2%(전국여객 소비의 0.9% 상당) 감소하는 등, 이들 모든 시책이 도입되는 경우 서울 여객 소비기준 약 9.1%의 에너지 절약 효과가 기대된다. 화물차의 경우에는 1) 공동배송에 의한 수송 효율화에 따라 적재율이 10% 향상되면 서울화물 소비의 8.9%(전국화물 소비의 1.6%), 2) 또 수송효율에 의한 실차율이 2% 향상되면 서울화물 소비의 1.8%(전국화물 소비의 0.3%), 3) 2000년까지 자동차 연비가 5% 향상되면 서울화물 소비의 1.4%(전국화물 소비의 0.4%) 감소하는 것을 합하면 약 12.1%의 에너지절약효과가 기대된다.

• Proceedings of the Korean Association of Geographic Inforamtion Studies Conference
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• 2008.10a
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• pp.195-199
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• 2008

본 논문은 택시들의 승차율을 높이고 승객들의 대기시간을 최소화하기 위하여 제주 택시들의 이동이력 데이터를 기반으로 하여 공차들을 승객을 만날 가능성이 많은 지역으로 배치하는 기법을 제시한다. 이동이력 데이터에 포함된 공차 보고와 승차 보고 수 사이의 스케일 차이를 극복하기 위하여 전체수와 영역내 합에 대한 비율로 정규화하는 방법을 설명하고 장단점을 분석한다. 또 시간대별, 요일별, 주간별 택시들의 승객 대기시간에 대한 통계 데이터에 기반하여 가장 수요와 공급이 적정하게 유지되는 시간구간을 발견하고 이 구간에 대한 택시 분포와 현재의 택시 분포의 차이에 의해 수요보다 공급이 많은 곳의 택시를 재배치한다.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.22 no.3
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• pp.131-146
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• 2023

Smart card data is widely used in the public transportation field. Despite the inevitability of various errors occur during the data collection and storage; however, smart card data errors have not been extensively studied. This paper investigates inherent errors in boarding and alighting station information in smart card data. A comparison smart card data and bus boarding and alighting survey data for the same time frame shows that boarding station names differ by 6.2% between the two data sets. This indicates that the error rate of smart card data is 6.2% in terms of boarding station information, given that bus boarding and alighting survey data can be considered as ground truth. This paper propose 6-step algorithm for correcting errors in smart card boarding station information, linking them to corresponding information in Bus Information System(BIS) Data. Comparing BIS data and bus boarding and alighting survey data for the same time frame reveals that boarding station names correspond by 98.3% between the two data sets, indicating that BIS data can be used as reliable reference for ground truth. To evaluate its performance, applying the 6-step algorithm proposed in this paper to smart card data set shows that the error rate of boarding station information is reduced from 6.2% to 1.0%, resulting in a 5.2%p improvement in the accuracy of smart card data. It is expected that the proposed algorithm will enhance the process of adjusting bus routes and making decisions related to public transportation infrastructure investments.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.39 no.3
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• pp.461-467
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• 2019

Advances in location-aware and IoT (Internet of Things) technology increase the rapid generation of massive movement data. Knowledge discovery from massive movement data helps us to understand the urban flow and traffic management. This paper proposes a method to analyze frequent origin-destination sequence patterns from irregular spatiotemporal taxi pick-up locations. The proposed method starts by conducting cluster analysis and then run a frequent sequence pattern analysis based on identified clusters as a base unit. The experimental data is Seoul taxi trajectory data between 7 a.m. and 9 a.m. during one week. The experimental results present that significant frequent sequence patterns occur within Gangnam. The significant frequent sequence patterns of different regions are identified between Gangnam and Seoul City Hall area. Further, this study uses administrative boundaries as a base unit. The results based on administrative boundaries fails to detect the frequent sequence patterns between different regions. The proposed method can be applied to decrease not only taxis' empty-loaded rate, but also improve urban flow management.

• Journal of the Korean Society for Railway
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• v.8 no.6 s.31
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• pp.507-512
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• 2005

Railroad transportation system has experienced major changes due to KTX introduction. Kyungbu corridor especially Seoul to Cheonan has line capacity problem and its solution has been a primary concern to researchers and policy decision makers. This study explored pattern of train operation between Seoul and Cheonan after the introduction of KTX in 2004. Both the number of trains and available seat capacity per day have increased but maximum number of trains per specific hour has not been changed much. Demand for train shows that if concentrated in a specific time, so number of trains during the peak hour should be increased. But, it is difficult ? 새 line capacity, so increasing seat capacity per train might be an option. An increase in an avaliable sear should be considered the characteristics of each train lines.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.11 no.2
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• pp.1-9
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• 2012

This study proposed a method to determine the number and location of bus information terminals (BIT), which is a device to provide passengers with bus arrival time at bus stops in a Bus Information System (BIS). In low-density area, it is not efficient to survey bus demands such as the number of passengers at all bus stops due to time and cost. This kind of a survey would, however, competently cover all bus stops if performed inside the bus. The number of riding-on and -off passengers is observed for every bus stop, and this data collection is repeated over all day. Data obtained from the survey are aggregated each bus stop. This study defines Utility Index (UI), an aggregate each bus stop. Bus stops are ranked according to UI and determined for a BIT within budget limitation. As a case study, a bus line in Jeju island, Korea, was dealt with. This case showed that the more aggregate the better data quality. This study is expected to contribute to solving a location problem of BITs in a BIS.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.20 no.5
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• pp.157-171
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• 2021

As smartphones spread and ICT technologies develop, taxi services have changed from hovering to platform-based calls and reservations. This has improved the mobility and accessibility of taxi users but caused problems, such as digital observing (no-responses to calls) for either short-distance services or services during the peak-demand periods. Digital Observing means ignoring and not accepting calls when they occur, which require improvement. Therefore, this study aims to derive measures to mitigate discrepancies in taxi supply and demand by adjusting the expected revenue of each taxi service using reinforcement learning based on the Taxi operation data. The results confirmed that the average complete response rate to calls would increase from 50.29% to 54.24% when incentives are applied, and an improvement of 5.86% can be achieved in short-distance sections of less than 5,000 won incentives. It is expected that the improvement will increase profitability for drivers, reduce the waiting time for passengers, and improve satisfaction with taxi services overall.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.35 no.3
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• pp.663-670
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• 2015

In most public transportation related master plans, decisions for investment priorities are initially made by facilities with lower installation rates or lower satisfaction (performance) levels. In general, the decisions are made without conducting importance factor analysis. In this study, a combined method of importance-performance analysis (IPA) model for bus users related in travel time is proposed by using Structural Equation Model (SEM). The results of the IPA for Metropolitan users show that the categories need improvement are number of bus stops, number of intersections, headways, waiting times for boarding and traffic signal operations in order. On the other hand, Non-Metropolitan uses show that the categories need improvement are traffic signal operations, waiting times for boarding, headways, bus exclusive lanes and number of intersections that is in reverse order to Metropolitan users.