• IE interfaces
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• v.23 no.2
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• pp.139-146
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• 2010

In this paper, we present the study of a real passenger transportation system. Passenger transportation problem aims to transport passengers from bus stops to their destinations by a fleet of vehicles while satisfying various constraints such as vehicle capacity, maximum allowable riding time in a bus, and time windows at destinations. Our problem also has special issues such as mixed loading, consideration of afternoon problem together with morning problem, and transferring passengers between vehicles. Our solution approach consists of three serial procedures: bus route generation, bus scheduling, and post optimization. Efficient heuristic algorithms were developed and implemented for the procedures. The proposed solution approach has been successfully applied to several real world problem instances and could reduce about 10% to 15% of buses.

• Proceedings of the KSRS Conference
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• 2004.10a
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• pp.347-350
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• 2004

The objective of this study is to discuss the future trend of the community bus. In doing so, we have selected Nagasaki City of Japan. Geographic Information Systems (GIS) is used for selection of the routes. In the present study we are going to add new parameters and new selection method. As a result of the study, we have been able to identify some best possible and detailed routes for the community bus operation in Nagasaki City, which meets the requirement of the welfare community as well as general passengers.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.21 no.6
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• pp.70-86
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• 2022

An autonomous demand-responsive bus with mobility-on-demand service is an innovative transport compensating for the disadvantages of an autonomous bus and a demand-responsive bus with mobility-on-demand service. However, less attention has been paid to the quantitative impact assessment of the autonomous demand-responsive bus due to the technological complexity of the autonomous demand-responsive bus. This study simulates autonomous demand-responsive bus trips by reinforcement learning on a microscopic traffic simulation to quantify the impact of the autonomous demand-responsive bus. The Chungju campus of the Korea National University of Transportation is selected as a testbed. Simulation results show that the introduction of the autonomous demand-responsive bus can reduce the wait time of passengers, average control delay, and increase the traffic speed compared to the results with fixed route bus service. This study contributes to the quantitative evaluation of the autonomous demand-responsive bus.

• Journal of Korea Planning Association
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• v.54 no.4
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• pp.71-78
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• 2019

Due to the rapid pace of low fertility and aging of Korea, population decline is rapidly progressing in the outskirts of the province and county. Demand for public transport is decreasing due to suburban population declines, while local government funding for maintenance of the bus system is expected to increase gradually. The government and municipalities are promoting the introduction of Demand Responsive Transport (DRT) in order to reduce the burden of financial support for buses while enhancing mobility of the residents in vulnerable areas. However, most DRTs in Korea have been operated mainly in the areas that are not provided with public transportation services. Although DRT is able to reduce the financial burden of local governments, it is not easy to be introduced because of the objection of the existing bus users. In this study, 11 out of 61 towns with poor public transportation services in Gyeongsangnam-Do were selected for the introduction of DRT to replace bus services by using village characteristics. The results of this study are expected to be used as a basis for decision making to use DRT instead of bus service for the burden of bus financing for local governments.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.10a
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• pp.175-177
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• 2022

This paper introduces a system that assists the blind to move to their destination, and compares the performance of 3-types of deep learning network (DNN) used in the system. The system is made up with a smartphone application that finds route from current location to destination using GPS and navigation API and a bus station installation module that recognizes and informs the bus (type and number) being about the board at bus stop using 3-types of DNN and bus information API. To make the module recognize bus number to get on, We adopted faster-RCNN, YOLOv4, YOLOv5s and YOLOv5s showed best performance in accuracy and speed.

• Journal of Korean Society of Transportation
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• v.33 no.6
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• pp.543-553
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• 2015

This study analyzed that the impact of the bus use environment on users' stress in each step of bus use, from accessing to leaving to transfer, in the city of Daejeon. For this, we collected the stress data from 300 users using personal interviews at the bus stops and on-board bus. Also, we used factor analysis and structural equation model method for analysis of the impact of external and internal bus environments on stress of users. The results of this study showed that the highest stress impact factor was an onboard factor(${\beta}=.416$) including 'density and crowding', 'no seat to seat' and 'low ride comfort and safe'. The next stress impact factor was transfer factor including 'insufficient transfer information', 'lack of connectivity of bus and subway' and 'uncomfort transfer route'. From the above, we recommend that bus policies need to focus on not the supplier but users and also, this user based policy need to be more specified considering the characteristics of various users such as females, the elderly, irregular users, and so on.

• Journal of Korean Society of Rural Planning
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• v.22 no.4
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• pp.1-11
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• 2016

Public transportation is public service that is contributed to the convenience of the public. However, opportunity for public services in rural areas is weaker than the chance in urban areas. The purpose of this study is to evaluate accessibility of various public facilities using public transportation. To evaluate the accessibility, we calculate the various time from community center to the nearest bus stop, walking time, riding time in bus, and waiting time for transfer. The results of this study ares as follows; (1) Villages occupy 19.8% in rural areas that walking time from community center to the nearest bus stop takes over 10 minutes in integrated Chungju-si; (2) The average speed is 21.9 km/hr estimated to departure and arrival time of bus route; (3) The accessibility time from community center using the average bus speed takes 15.43 minutes to public facilities, 35.15 minutes to emergency center, 8.70 minutes to medical center, 9.70 minutes to elementary school, 16.26 minutes to middle school, and 22.61 minutes high school; (4) The transfer time of public transportation takes 13.46, 21.96, 10.48, 7.78, 11.11, 16.10 minutes to public facilities, emergency center, medical center, elementary school, middle school, and high school, respectively; (4) Traffic accessibility using bus vehicles in the East and South Chungju-si is lower than areas in the West and North Chungju-si. Some villages surrounding public offices (eup-myeon office) which have a high density of population, indicate a high traffic accessibility.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.4
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• pp.1376-1391
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• 2015

In bus delay-tolerant networks, the route of bus is determinate but its arrival time is indeterminate. However, most conventional approaches predict future contact without considering its uncertainty, which makes a limitation on routing performance. A novel approach is proposed by employing interval algebra to characterize the contact's uncertainty and time-varying nature. The contact is predicted by using the Bayesian estimation to achieve a better routing performance. Simulation results show that this approach achieves a good balance between delivery latency and delivery ratio.

• Journal of the military operations research society of Korea
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• v.13 no.1
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• pp.101-115
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• 1987

This paper presents an optimization based heuristic algorithm for a tour bus scheduling problem where buses consist of various kinds of sightseeing and commutation services. First, this algorithm transforms the prolem into a vehicle routing problem on whose nodes denote trips and arcs denote connections between trips. Second, a greedy heuritic routing technique is applied to find a good feasible bus-route set. Then the greedy feasible solution is improved by the simplex method using column generation technique. The algorithm provides a better near-optimal solution which gives much reductions in the total tour distance and the number of tour buses.

• International conference on construction engineering and project management
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• 2015.10a
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• pp.19-20
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• 2015

Since 2013, Seoul Metropolitan Government (SMG) has introduced big data initiatively in administration and put into practices in transportation, safety, welfare in order to overcome limited resources and conflicting interests. For establishing a new midnight bus service, SMG prepared optimized midnight bus routes by analyzing big data from mobile phone Call Data Record (CDR) through collaboration with a telecommunication company. Despite of limited budget and resources, newly identified routes can cover over 42% of the citizen with 9 routes and less than 1% of buses compare with day time operation. In addition to solve transportation problem, SMG utilizes big data to resolve location selection problem for choosing new facility locations such as life double cropping centers and senior citizen leisure centers. As results, SMG demonstrates big data as a good tool to make policies and to build smarter city by overcome space-time limitation of resources, mediation of conflicts, and maximizes benefit of the citizen.