• KIPS Transactions on Computer and Communication Systems
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• v.6 no.4
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• pp.189-196
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• 2017

BIS(Bus Information System) provides the different information related to buses including predictions of arriving times at stations. BIS have been deployed almost all cities in our country and played active roles to improve the convenience of public transportation systems. Moving average filters, Kalman filter and regression models have been representative in forecasting the arriving times of buses in current BIS. The accuracy in prediction of arriving times depends largely on the forecasting algorithms and traffic conditions considered when forecasting in BIS. In present BIS, the simple prediction algorithms are used only considering the passage times and distances between stations. The forecasting of arrivals, however, have been influenced by the traffic conditions such as traffic signals, traffic accidents and pedestrians ets., and missing data. To improve the accuracy of bus arriving estimates, there are big troubles in building models including the above problems. Hidden Markov Models have been effective algorithms considering various restrictions above. So, we have built the HMM forecasting models for bus arriving times in the current BIS. When building models, the data collected from Sunchean City at 2015 have been utilized. There are about 2298 stations and 217 routes in Suncheon city. The models are developed differently week days and weekend. And then the models are conformed with the data from different districts and times. We find that our HMM models can provide more accurate forecasting than other existing methods like moving average filters, Kalmam filters, or regression models. In this paper, we propose Hidden Markov Model to obtain more precise and accurate model better than Moving Average Filter, Kalman Filter and regression model. With the help of Hidden Markov Model, two different sections were used to find the pattern and verified using Bootstrap process.

• Spatial Information Research
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• v.19 no.4
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• pp.11-20
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• 2011

In accordance with low carbon and green growth paradigm, a subway is one of major public transit systems for resolving traffic congestion and decreasing traffic accidents. In addition, as subway networks expand, passengers' travel pattern in the subway network change and consequently affect the urban structure. Generally, new subway route has been planned and developed, mainly considering a travel demand forecast. However, it is desired to conduct an empirical analysis on the forecast model regarding change of travel accessibility and passenger demand pattern according to new subway line. Therefore, in this paper, an alternative method, developed based upon a spatial syntax model, is proposed for evaluating new subway route in terms of passenger's mobility and network accessibility. In a case study, we constructed subway network data, mainly targeting the no 9 subway line opened in 2009. With an axial-map analysis, we calculated spatial characteristics to describe topological movement interface. We then analyzed actual modal shift and change on demand of passengers through the number of subway passenger between subway stations and the number of passenger according to comparative bus line from Smart Card to validate suggested methods. Results show that the proposed method provides quantitative means of visualizing passenger flow in subway route planning and of analyzing the time-space characteristics of network. Also, it is expected that the proposed method can be utilized for predicting a passengers' pattern and its impact on public transportation.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.32 no.3D
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• pp.213-222
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• 2012

After enforcing 2007 semi-public management system of intra-city bus, Busan city has tried to promote the bus utilization through bus service improvements. As an effort for this, we attempted to clarify the main factors affecting to bus service satisfaction targeting intra-city bus users. In this study, 20 subcategories of intra-city bus service were assorted into 6 factors: Basic Service, Safe Driving, Route Information, Comfort, Cleanliness and Facilities, then the preference for each detailed bus service were analyzed. And the effects for bus service satisfaction were shown under the various conditions according to the general characteristics of intra-city bus users (gender, age), behavioral traffic characteristics (frequency of use, boarding time) and transportation environments (temperature, rainfall). These results would be important basic data for decision-making in bus policy for climate change and establishment of operating plan for bus utilization.

• Proceedings of the KOR-KST Conference
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• 1997.12a
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• pp.1-12
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• 1997

우리 나라 자동차운송산업에 존재하는 지입제(위탁관리제)는 과거부터 논란의 대상이 되어 왔다. 1950년대 말부터 시작된 육운 분야의 직영화 정책은 노선버스나 택시의 경우 비교적 성공적인 결과를 가져왔으나 화물자동차운송과 전세버스분야에서 만큼은 아직도 대다수 사업장에서 지입제가 관행화된 제도로 남아 있다. 지입제도는 비효율적이고 전근대적인 경영기법으로 인식되고 있으며 산업발전의 저해요인 보기도하고 불가피하다고 평가되기도 하였다. 본 논문에서는 지입제를 단순하게 비합리적인 제도라고 보기보다는 나름대로의 장점을 가지고 있어 합법적 또는 비합법적인 형태로 지금까지 유지되고 있다고 본다. 지입제는 정보가 비대칭적인 상황에서 기업조직을 통해 생산과 판매를 하기보다는 시장거래를 통한 계약을 통하여 운송서비스를 생산 및 판매를 함으로써 유인일치를 달성시킬 수 있다는 것을 보여주고 있다. 장거리를 운행하는 운송사업의 경우 사업자와 고용운전자는 노동성과에 대한 비대칭적인 정보를 가질 수밖에 없게 된다. 이는 대리문제를 야기시켜 기업조직에 의한 운송서비스의 공급은 생산비용을 상승시킨다. 반면 자동차운송서비스는 생산단위를 분리하기 위한 비용이 비교적 적어 독립적인 운영이 가능하다. 따라서 차량을 1대씩 분리하여 사업권을 시장거래하는 지입제를 운송사업자와 운전자는 선택하게 된다는 것이다.

• Proceedings of the KOR-KST Conference
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• 1997.12b
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• pp.1-14
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• 1997

우리나라 자동차운송산업에 존재하는 지입제(위탁관리제)는 과거부터 논란의 대상이 되어왔다. 1950년대 말부터 시작된 육문 분야의 직영화 정책은 노선버스나 택시의 경우 비교적 성공적인 결과를 가져왔으나 화물자동차운송과 전세버스분야에서 만큼은 아직도 대다수 사업장에서 지입제가 관행화된 제도로 남아 있다. 지입제도는 비효율적이고 전근대적인 경영기법으로 인식되고 있으며 산업발전의 저해요인 보기도하고 불가피하다고 평가되기도 하였다. 본 논문에서는 지입제를 단순하게 비합리적인 제도라고 보기보다는 나름대로의 장점을 가지고 있어 합법적 또는 비합법적인 형태로 지금까지 유지되고 있다고 본다. 지입제는 정보가 비대칭적인 상황에서 기업조직을 통해 생산과 판매를 하기보다는 시장거래를 통한 계약을 통하여 운송서비스를 생산 및 판매를 함으로써 유인일치를 달성시킬 수 있다는 것을 보여주고 있다. 장거리를 운행하는 운송사업의 경우 사업자와 고용운전자는 노동성과에 대한 비대칭적인 정보를 가질 수밖에 없게 된다. 이는 대리문제를 야기시켜 기업조직에 의한 운송서비스의 공급은 생산비용을 상승시킨다. 반면 자동차운송서비스는 생산단위를 분리하기 위한 비용이 비교적 적어 독립적운영이 가능하다. 따라서 차량을 1대씩 분리하여 사업권을 시장거래하는 지입제를 운송사업자와 운전자는 선택하게 된다는 것이다.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.28 no.5D
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• pp.587-595
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• 2008

Many studies on bus scheduling optimization have been done from the 1960s to recent years for establishing rational bus schedule plan that can improve convenience of bus passengers and minimize unnecessary runs. After 2000, as part of the Intelligent Transport Systems (ITS), the importance of the schedule management and providing schedule information through bus schedule optimization has become a big issue, and much research is being done to develop optimization models that will increase bus passenger convenience and, on the side of bus management, minimize unnecessary bus operation. The purpose of this study is to calculate the optimal bus frequency and create a timetable for each bus stop by applying DTR or DTRC model that use data for each bus stop and route segment. Model verification process was implemented using data collected from bus management system (BMS) and integrated transit-fare card system for bus route of Seoul's No. 472 line. In order to evaluate the reliability and uncertainty of optimal solution, sensitivity analysis was implemented for the various parameters and assumptions used in the bus scheduling model.

• 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.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.22 no.1
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• pp.52-64
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• 2023

This paper concentrated on estimating the travel time value of individual regional bus passengers in various in-vehicle crowding conditions. In the analysis model, the traffic-selection data of individual transportation passengers based on smart-card data were used. Variables which reflect the level of in-vehicle crowding and the variables of in-vehicle travel time that reflect the level of in-vehicle crowding were included in the model using Box-Cox transformation. The result of this paper indicates that the travel time value experienced by individual users would increase as the in-vehicle crowding level increases. The smart card data used in this paper is considered to have significant implications in terms of conducting more sophisticated and realistic qualitative research to reflect the values of variables for in-vehicle traffic hours and in-vehicle crowding levels, which previously had limitations in observation and quantification. It is expected that the effects of improvement measures for reducing congestion on regional buses can be considered quantitatively by applying the estimation results of crowding multiplier.

• Journal of the Korea Society of Computer and Information
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• v.26 no.6
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• pp.81-88
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• 2021

In this paper, we design and implement a bus information notification application based on the GPS sensor of a smartphone. This application provides the ability to check bus stops within a radius of 200m based on the current user's location using the smartphone's GPS sensor, Google Map, and open API. In addition, if you click the marker of the desired stop, you can see the name of the stop, and click the view arrival information button to check the detailed bus arrival information of the stop. In addition, it provides a function to check the location information of pharmacies, nonghyups, and post offices that sell public masks, the names of public mask stores, and mask inventory through the public mask store button. Each icon was used differently to make visual differences in order to easily indicate the difference between the times of public mask sales and bus stops. In addition, if you want to know the information of other bus stops and the route of the desired bus, not around the user's location, click the bus stop search button. Finally, after storing the destination stop or location, it implements a function that provides an alarm when it approaches the location.

• Journal of Advanced Navigation Technology
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• v.20 no.6
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• pp.588-594
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• 2016

As more populations are getting older, the number of vulnerable pedestrians is increasing, thereby social problems related to transportations also frequently occur in different areas and situations. Many of such problems come from bus drivers who may pass bus stops not recognizing passengers about to board. In this paper, we propose a new IoT bus notification system developed to avoid these situations. Our implementation aims to gain bus service routes using publicly opened data, notify passengers about bus stop locations using GPS information and finally deliver the positions of those passengers to the bus drivers so that they can hardly miss passengers who are willing to board on the right stop. By creating an application, it was conducted by means of a GPS to communicate the location of the vehicle by means of GPS and transfer data to the location of the vehicle. Experimental results show that it is possible to accurately determine the position of passengers even in a crowded race area. The average error distance is 31m, and if the data to be processed as error is excluded, it provides a high reliability as 19m.