• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.7
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• pp.3018-3040
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• 2018

The mobility model is one of the most important factors that impacts the evaluation of any transportation vehicular networking protocols via simulations. However, to obtain a realistic mobility model in the dynamic urban environment is a very challenging task. Several studies extract mobility models from large-scale real data sets (mostly taxi GPS data) in recent years, but they do not consider the statuses of taxi, which is an important factor affected taxi's mobility. In this paper, we discover three simple observations related to the taxi statuses via mining of real taxi trajectories: (1) the behavior of taxi will be influenced by the statuses, (2) the macroscopic movement is related with different geographic features in corresponding status, and (3) the taxi load/drop events are varied with time period. Based on these three observations, a novel taxi mobility model (T-START) is proposed with respect to taxi statuses, geographic region and time period. The simulation results illustrate that proposed mobility model has a good approximation with reality in trajectory samples and distribution of nodes in four typical time periods.

• Journal of the Korean Society for Aviation and Aeronautics
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• v.28 no.2
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• pp.29-35
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• 2020

In this paper, we established a prediction model of fuel consumption at the aircraft's taxi operation. To look for countermeasures to reduce fuel consumption and carbon emissions, Airbus A380's actual ground taxi data was used. As a result, the number of stops or turnings during the taxi operation was not related to fuel consumption. It was confirmed that the amount of fuel consumption in the taxi operation was the taxi time and the thrust change. It can be confirmed that ground control optimization, which is the result of close cooperation between the control organization and the airline, is absolutely necessary to reduce taxi time and minimize the occurrence of thrust change events.

• Journal of Korean Society of Transportation
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• v.3 no.1
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• pp.46-57
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• 1985

The objective of this paper is to derive a optimum distance and time taxi fare structure based on social costs. Social costs expressed in terms of congestion and vehicle operating costs were successfully internalized. Speed and volume data for three major arterials in Seoul CBD were used. Optimum congestion charge turned out to be 97.01 Won/Km which can be regarded as congestion tax in the context of Seoul CBD. This congestion tax can possibly be incorporated into time-based taxi fare structure. Congestion is likely to be reduced as a result of imposition of time-based taxi fare which reflects social costs.

• Journal of the Korean Society for Aviation and Aeronautics
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• v.26 no.2
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• pp.39-46
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• 2018

Departure Manager (DMAN) is a tool to optimize the departure sequence and to suggest appropriate take-off time and off-block time of each departure aircraft to the air traffic controllers. To that end, Variable Taxi Time (VTT), which is time duration of the aircraft from the stand to the runway, should be estimated. In this paper, a study for development of VTT prediction algorithm based on machine learning techniques is presented. The factors affecting aircraft taxi speeds were identified through the analysis of historical traffic data on the airport surface. The prediction model suggested in this study consists of several sub-models that reflect different types of surface maneuvers based on the analysis result. The prediction performance of the proposed method was evaluated using the actual operational data.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2018.10a
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• pp.590-592
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• 2018

Taxis that are illegally parked on the road to catch customer can cause traffic congestion and sometimes cause traffic accidents. Stop position of taxis is determined by the long term experience of taxi drivers. In this study, We provide information to taxi drivers and customer who visit in first time through finding stop position of taxis by time. To do this, we used the Internet of Vehicle (IoV) data collected from sensors installed in 40 taxis. Previous studies attempted by forming a cluster around a taxi. Since this method is centered on a taxi, the position of the cluster changes depending on the location of the taxi. In this study, we use a road segmentation algorithm to solve these problems. Unlike the previous studies, since the cluster is formed around the road, the position of the cluster is fixed and it is not affected by the number of taxis, so it is possible to grasp the stop position in real time. The road segmentation is made up of 30m units, and map the taxi location data divided into hourly, weekday, and weekend to the nearest point. As a result of the mapping, it was difficult to see a big difference in the time of week because there were few taxis to operate on weekends, but in case of weekdays, the difference of stop position between the commute time zone and the night time zone was confirmed. The results of this study suggest that it will be possible to propose the prevention of taxi illegally driving taxi and the location of the taxi stand.

• ETRI Journal
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• v.44 no.2
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• pp.220-231
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• 2022

Building smart transportation services in urban cities has become a worldwide problem owing to the rapidly increasing global population and the development of Internet-of-Things applications. Traffic congestion and environmental concerns can be alleviated by sharing mobility, which reduces the number of vehicles on the road network. The taxi-parcel sharing problem has been considered as an efficient planning model for people and goods flows. In this paper, we enhance the functionality of a current people-parcel taxi sharing model. The adapted model analyzes the historical request data and predicts the current service demands. We then propose two novel online routing algorithms that construct optimal routes in real-time. The objectives are to maximize (as far as possible) both the parcel delivery requests and ride requests while minimizing the idle time and travel distance of the taxis. The proposed online routing algorithms are evaluated on instances adapted from real Cabspotting datasets. After implementing our routing algorithms, the total idle travel distance per day was 9.64% to 12.76% lower than that of the existing taxi-parcel sharing method. Our online routing algorithms can be incorporated into an efficient smart shared taxi system.

• Journal of Platform Technology
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• v.6 no.1
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• pp.17-23
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• 2018

Taxi's queue for entering into taxi stand makes traffic jam and congestion around taxi stand. If we make that taxi waits in another place around taxi stand, and can approach to taxi stand when it gets in its turn, these traffic jam and congestion around taxi stand can be reduced. In this paper, we propose entry sequence operating system for taxi stand to reduce traffic jam and congestion around taxi stand. In this system, taxi driver can request his sequence number, and the system issues sequence number to driver. When it is time to approach to taxi stand due to issued sequence number, the proposed system notifies to taxi driver via taxi terminal. Taxi getting the proposed service can wait in another place around taxi stand, and can approach to taxi stand after receiving notify for approaching. Therefore, the proposed system in this paper can reduce traffic jam and congestion around taxi stand because it can reduce or get rid of taxi's queue around taxi stand. We implement the taxi stand approach sequence management system proposed in this paper for taxi stand installed in Chungju-Si, Chungbuk. We use Google Cloud service and Android platform for implementing.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.42 no.1
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• pp.57-65
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• 2022

Gyeongsangnam-do has been operating Bravo-taxi, a Gyeongnam-type DRT using taxi vehicles, since 2017 to guarantee the right of mobility for residents who live in areas lacking public transportation. This research investigated and analyzed changes in users' awareness over two years from beginning of Bravo-taxi operation in Gyeongsangnam-do, which started operating Bravo-taxis in 2017, targeting sites lacking public transportation. Through this study, the positive effects of taxi-type DRT were confirmed, such as improving the mobility of residents in areas underprivileged by public transportation, reducing required time for trips, and increasing preference for Bravo-taxis compared to existing buses. On the other hand, problems with the current Bravo-taxi system were also identified. In some areas, it was found that there were not enough coupons for Bravo-taxis, or in the case of Bravo-taxis operating at fixed times, the user's desired time and operating time did not match, resulting in lower satisfaction. The results of this research are expected to be utilized as basic data for service continuity of taxi-type DRT in operation by other local governments.

• International Journal of Highway Engineering
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• v.14 no.3
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• pp.163-171
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• 2012

Demand Responsive Transit (DRT) services are becoming necessary as part of not only alternative transportation means for elderly and mobility impaired passengers, but also sustainable and flexible transportation options in urban area due to the development of communication technologies and Location Based Services (LBS). It is difficult to investigate the system performance regarding vehicle operational schemes and vehicle routing algorithms due to the lack of commercial software to support door-to-door vehicle simulation for larger area. This study proposes a simulation framework to evaluate innovative and flexible transit systems focusing on various vehicle routing algorithms, which describes data-type requirements for simulating door-to-door service on demand. A simulation framework is applied to compare two vehicle dispatch algorithms, Nearest Vehicle Dispatch (NVD) and Insertion Heuristic (IH) for real-time shared-taxi service in Seoul. System productivity and efficiency of the shared-taxi service are investigated, comparing to the conventional taxi system.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.5D
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• pp.731-738
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• 2006

Facing congestion, people want to know traffic information about their routes, especially real-time link travel time (LTT). In this paper, as a sequel paper of the previous non-taxi based LTT generating study by Choi et al. (1998), taxi based GPS probes have been tried to produce LTT for urban arterials. Taxis in itself are good deployment mode of GPS probes although it by nature experiences boarding and alighting time noises which should be accounted. A heuristic real-time dynamic outlier filter algorithm for taxi GPS probe has been developed focusing on urban arterials. An actual traffic survey for dynamic link travel times has been conducted using license plate method for the test arterials of Seoul city transportation network. With the algorithm, it is estimated that 70% of outliers have been filtered and the relative error has been improved by 73.7%. The filtering algorithm developed here would be expected to be in use for other spatial sites with some calibration efforts. Some limitations and future research agenda have also been discussed.