• Journal of the Korean Society for Railway
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• v.17 no.3
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• pp.210-215
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• 2014

Various methods have been developed in an effort to increase the scheduled speeds of the urban railways. Reducing the train dwell times by extending door widths is one such method. However, there is thus far no domestic model of boarding and alighting that is appropriate to lead to boarding and alighting time reductions if the door width is extended. Foreign models are not suitable because human behaviors, which are important factors when assessing boarding and alighting times, differ from country to country. In this study, a boarding and alighting model for domestic urban railways is proposed and related equations and parameters are derived from measured and experimental data. The model can be employed to assess time reductions in Korean railroad system if the door widths are extended.

• Smart Media Journal
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• v.11 no.3
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• pp.90-101
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• 2022

Buses are a popular means of transportation. As such, thorough preparation is needed for passenger safety management. However, the safety system is insufficient because there are accidents such as a death accident occurred when the bus departed without recognizing the elderly approaching to get on in 2018. There is a safety system that prevents pinching accidents through sensors on the back door stairs, but such a system does not prevent accidents that occur in the process of getting on and off like the above accident. If it is possible to predict the intention of bus passengers to get on and off, it will help to develop a safety system to prevent such accidents. However, studies predicting the intention of passengers to get on and off are insufficient. Therefore, in this paper, we propose a 1×1 CNN3D-based getting on and off intention prediction model using skeleton keypoints of passengers extracted from the camera image attached to the bus through UDP-Pose. The proposed model shows approximately 1~2% higher accuracy than the RNN and LSTM models in predicting passenger's getting on and off intentions.

• Smart Media Journal
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• v.12 no.11
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• pp.57-66
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• 2023

In this paper, we present a study on an AI-based system utilizing the CCTV system within city buses to predict the intentions of boarding and alighting passengers, with the aim of preventing accidents. The proposed system employs the YOLOv7 Pose model to detect passengers, while utilizing an LSTM model to predict intentions of tracked passengers. The system can be installed on the bus's CCTV terminals, allowing for real-time visual confirmation of passengers' intentions throughout driving. It also provides alerts to the driver, mitigating potential accidents during passenger transitions. Test results show accuracy rates of 0.81 for analyzing boarding intentions and 0.79 for predicting alighting intentions onboard. To ensure real-time performance, we verified that a minimum of 5 frames per second analysis is achievable in a GPU environment. his algorithm enhance the safety of passenger transitions during bus operations. In the future, with improved hardware specifications and abundant data collection, the system's expansion into various safety-related metrics is promising. This algorithm is anticipated to play a pivotal role in ensuring safety when autonomous driving becomes commercialized. Additionally, its applicability could extend to other modes of public transportation, such as subways and all forms of mass transit, contributing to the overall safety of public transportation systems.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.18 no.4
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• pp.13-18
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• 2018

In this study, we classify Seoul metro stations according to boarding and alighting patterns using machine earning technique. The target data is the number of boarding and alighting passengers per hour every day at 233 subway stations from 2008 to 2017 provided by the public data portal. Gaussian mixture model (GMM) and K-means clustering are used as machine learning techniques in order to classify subway stations. The distribution of the boarding time and the alighting time of the passengers can be modeled by the Gaussian mixture model. K-means clustering algorithm is used for unsupervised learning based on the data obtained by GMM modeling. As a result of the research, Seoul metro stations are classified into four groups according to boarding and alighting patterns. The results of this study can be utilized as a basic knowledge for analyzing the characteristics of Seoul subway stations and analyzing it economically, socially and culturally. The method of this research can be applied to public data and big data in areas requiring clustering.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.9
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• pp.133-140
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• 2016

The Ministry of Land, Infrastructure and Transport has introduced low-floor buses, which are convenient for passengers getting on and off the bus and for the handicapped. The standard bus model is 11 m long and uses compressed natural gas (CNG). However, this model has drawbacks in narrow rural road conditions such as those in farming and fishing villages and mountainous areas, as well as difficulty in refueling since CNG facilities are not readily available. In this study, running resistance values were obtained by coasting performance tests on actual roads using a Tata Daewoo LF-40 model with three different weight conditions: curb vehicle weight (CVW), half vehicle weight (HVW), and gross vehicle weight (GVW).The test methods include WHVC, NIER-06, and constant-speed driving at 60 km/h. These tests were used to measure the fuel economy of vehicles other than the target vehicles to obtain the combined fuel economy. The energy efficiency was highest in the case of CVW. In the WHVC mode, the fuel consumption rates of HVW and GVW were typically 3.5% and 12% higher than that of CVW, respectively. In constant-speed driving, the fuel efficiency of HVW was higher than that of CVW. Further research is required to analyze the exhaust gas data.

• Journal of Korean Society of Transportation
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• v.30 no.1
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• pp.149-159
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• 2012

The evaluation of public transit service quality is more complicated than evaluating other aspects of transportation service. Although various measures of effectiveness [MOEs] for transit service have been studied and applied, a more comprehensive and accurate MOE is still required. In the past, either data from user surveys or the experience of bus agency administrators and/or engineers used to measure the quality of service. However, recently, with reliable and accurate real time data from BMS(Bus Management System) and BIS(Bus Information System), more reliable and accurate MOEs are available. This study develops a service evaluation model from users' perspectives, which is based on user' cost models that consider passenger access time, riding time, waiting time, and discomfort due to in-vehicle overcrowding, violation of traffic laws, and accident rate. For validating proposed model, data from the BMS and transit-fare cards (T-Money Card) for Seoul's No. 472 main bus line were used. Models developed in this study provided reliable results.

• Archives of design research
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• v.17 no.3
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• pp.313-322
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• 2004

Product design has direct effects on sales, exciting consumer's interest in purchasing. With the draft bill of Road Traffic Law passing the National Assembly, drivers have been entirely prohibited by the law from using a cell phone while driving since June 30, 2001, As a result, the demand for and the sales of hands-free Kit products for vehicles have been skyrocketing, and more and more of them have been introduced in the market and competing each other in sales. In these situations, the study attempted to present a case study showing the whole process of product design by a small company, which intended to gain an advantage over the competitors in the sector of hands-free products for vehicles with differentiated design. The product whose design development process was presented in the study has many characteristics. Among them it is the most remarkable in removing the connection between the cell phone terminal and the stationary hands-free product. The study was aimed to increase the investment value of design by helping understand that the ultimate goal of technology is commercialization and that how great the role of design is from the beginning to the final stage of product development. It also emphasized the point that one of the goals of design development should lie in providing a more accurate perception of the importance of design to the industry, by establishing a design process throughout the whole stages of product development including initiation, designing and commercialization.