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The COVID-19 outbreak in 2020 has changed the way people travel due to its highly contagious nature. In this study, changes in the travel behavior of passengers due to COVID-19 in the first half of 2020 were examined. To determine whether COVID-19 has affected the use of transportation by passengers, paired t-tests were conducted between the passenger volume of private vehicles in Seoul prior to and after the pandemic. Additionally, the passenger occupancy rate of different modes of transportation during the similar time periods were compared and analyzed to identify the changes in monthly usage rate for each mode. In the case of private vehicles and public bicycles, the usage rates have recovered or increased when compared to those of before the pandemic. Conversely, bus and rail passenger service rates have decreased from the previous year before the pandemic. Furthermore, it is found that existing bus and rail users have switched to the private auto mode due to COVID-19. Based on the results, traffic patterns of travelers after the outbreak and implications responding to the pandemic are discussed.
Dong-Gyun Ku; Jung-Sik Um; Young-Ji Byon; Joo-Young Kim; Seung-Jae Lee. Changes in Passengers’ Travel Behavior Due to COVID-19. Sustainability 2021, 13, 7974 .
AMA StyleDong-Gyun Ku, Jung-Sik Um, Young-Ji Byon, Joo-Young Kim, Seung-Jae Lee. Changes in Passengers’ Travel Behavior Due to COVID-19. Sustainability. 2021; 13 (14):7974.
Chicago/Turabian StyleDong-Gyun Ku; Jung-Sik Um; Young-Ji Byon; Joo-Young Kim; Seung-Jae Lee. 2021. "Changes in Passengers’ Travel Behavior Due to COVID-19." Sustainability 13, no. 14: 7974.
The string stability of cooperative adaptive cruise control (CACC) platoons is largely affected by complex driving environment and abnormal driving behaviors. Fast and repetitive driving-state changes always occur during the period of changing driving states (such as leaving a platoon or lane-change), due to errors made in driver decisions or automatic driving system. This research proposes a framework which combines recognition of driving states with platoon operations and risk-prediction in order to reduce disturbance and unnecessary platoon operations resulting from driving-state jitters. First of all, long short-term memory (LSTM) neural networks were used in this research combined with a time-window in order to recognize driving states. Based on this research, the LSTM mode with an added time-window was found to be able to effectively reduce comparatively the jitters of recognition results. After that, an integrated mode which incorporates a recognition mode with danger probabilities was demonstrated to present better platoon operations. Monte Carlo simulation and importance sampling method will be given to predict platoons' and vehicles' trajectories and compute danger probabilities. In addition, an innovative strategy is implemented to identify an additional leader and execute a platoon splitting in order to improve driving smoothness, if a vehicle is recognized in an abnormal car-following state with a high danger-probability. In summary, this research has conducted extensive numerical tests to evaluate performances of the proposed system and the analysis results show that the proposed strategies will effectively increase smoothness and safety for a multi-platooning system.
Wei Hao; Li Liu; Xianfeng Yang; Yongfu Li; Young-Ji Byon. Reducing CACC Platoon Disturbances Caused by State Jitters by Combining Two Stages Driving State Recognition With Multiple Platoons' Strategies and Risk Prediction. IEEE Transactions on Intelligent Transportation Systems 2020, PP, 1 -11.
AMA StyleWei Hao, Li Liu, Xianfeng Yang, Yongfu Li, Young-Ji Byon. Reducing CACC Platoon Disturbances Caused by State Jitters by Combining Two Stages Driving State Recognition With Multiple Platoons' Strategies and Risk Prediction. IEEE Transactions on Intelligent Transportation Systems. 2020; PP (99):1-11.
Chicago/Turabian StyleWei Hao; Li Liu; Xianfeng Yang; Yongfu Li; Young-Ji Byon. 2020. "Reducing CACC Platoon Disturbances Caused by State Jitters by Combining Two Stages Driving State Recognition With Multiple Platoons' Strategies and Risk Prediction." IEEE Transactions on Intelligent Transportation Systems PP, no. 99: 1-11.
Mohammad Hadi Almasi; Yoonseok Oh; Ali Sadollah; Young-Ji Byon; Seungmo Kang. Urban transit network optimization under variable demand with single and multi-objective approaches using metaheuristics: The case of Daejeon, Korea. International Journal of Sustainable Transportation 2020, 15, 386 -406.
AMA StyleMohammad Hadi Almasi, Yoonseok Oh, Ali Sadollah, Young-Ji Byon, Seungmo Kang. Urban transit network optimization under variable demand with single and multi-objective approaches using metaheuristics: The case of Daejeon, Korea. International Journal of Sustainable Transportation. 2020; 15 (5):386-406.
Chicago/Turabian StyleMohammad Hadi Almasi; Yoonseok Oh; Ali Sadollah; Young-Ji Byon; Seungmo Kang. 2020. "Urban transit network optimization under variable demand with single and multi-objective approaches using metaheuristics: The case of Daejeon, Korea." International Journal of Sustainable Transportation 15, no. 5: 386-406.
Perimeter control is an emerging alternative for traffic signal control, which regulates the traffic flows on the periphery of a road network. Some model-based approaches have been suggested earlier for the optimization of perimeter control based on macroscopic fundamental diagrams (MFDs). However, there are several limitations when considering their application to a large-scale urban area because the model-based approaches may not be scalable to multiple regions and inappropriate for handling various effects caused by the shape change of MFDs. Therefore, we propose a model-free and data-driven approach that combines reinforcement learning (RL) with the macroscopic traffic simulation based on the recently developed network transmission model. First, we design four perimeter control models with different macroscopic traffic variables and parametrizations. Then, we validate the proposed models by evaluating their performances with the test demand scenarios at different levels. The validation results show that the model containing travel demand information adapts to a new demand scenario better than the model containing only density-related factors.
Jinwon Yoon; Sunghoon Kim; Young-Ji Byon; Hwasoo Yeo. Design of reinforcement learning for perimeter control using network transmission model based macroscopic traffic simulation. PLOS ONE 2020, 15, e0236655 .
AMA StyleJinwon Yoon, Sunghoon Kim, Young-Ji Byon, Hwasoo Yeo. Design of reinforcement learning for perimeter control using network transmission model based macroscopic traffic simulation. PLOS ONE. 2020; 15 (7):e0236655.
Chicago/Turabian StyleJinwon Yoon; Sunghoon Kim; Young-Ji Byon; Hwasoo Yeo. 2020. "Design of reinforcement learning for perimeter control using network transmission model based macroscopic traffic simulation." PLOS ONE 15, no. 7: e0236655.
This paper proposes a new enhanced method based on one-dimensional direct linear transformation for estimating vehicle movement states in video sequences. The proposed method utilizes a contoured structure of target vehicles, and the data collection procedure is found to be relatively stable and effective, providing a better applicability. The movements of vehicles in the video are captured by active calibration regions while the spatial consistency between the vehicle’s driving track and the calibration information are in sync. The vehicle movement states in the verification phase are estimated using the proposed method first, and then the estimated states are compared with the actual movement states recorded in the experimental test. The results show that, in the case of camera perspective of 90 degrees, in all driving states of low speed, high speed, or deceleration, the error between estimated speed and recorded speed is less than 1.5%, the error of accelerations is less than 7%, and the error of distances is less than 2%; similarly, in the case of camera perspective of 30 degrees, the errors of speeds, distances, and accelerations are less than 4%, 5%, and 10%, respectively. It is found that the proposed method is superior to other existing methods.
Hao Feng; Weiguo Shi; Feng Chen; Young-Ji Byon; Weiwei Heng; Shaoyou Pan. A Calculation Method for Vehicle Movement Reconstruction from Videos. Journal of Advanced Transportation 2020, 2020, 1 -13.
AMA StyleHao Feng, Weiguo Shi, Feng Chen, Young-Ji Byon, Weiwei Heng, Shaoyou Pan. A Calculation Method for Vehicle Movement Reconstruction from Videos. Journal of Advanced Transportation. 2020; 2020 ():1-13.
Chicago/Turabian StyleHao Feng; Weiguo Shi; Feng Chen; Young-Ji Byon; Weiwei Heng; Shaoyou Pan. 2020. "A Calculation Method for Vehicle Movement Reconstruction from Videos." Journal of Advanced Transportation 2020, no. : 1-13.
Dwell time is a critical factor in constructing and adjusting railway timetables for efficient and accurate operation of railways. This paper develops dwell time estimation models for a Shinbundang line (S line) in Seoul, South Korea using support vector regression (SVR), multiple linear regression (MLR), and random forest (RF) techniques utilizing archived real-time metro operation data along with smart card-based passenger information. In the first phase of this research, the collected data are processed to extract boarding and alighting passenger counts and observed dwell times of each train at all stations of the S line under the current operational environment. In the second phase, we develop SVR, MLR, and RF-based dwell time estimation models. It is found that the SVR-based model successfully estimates the dwell times within 10 s of differences for 84.4% of observed data. The results of this paper are especially beneficial for autonomous railway operations that need constructing and maintaining dynamic railway timetables that require reliable dwell time predictions in real-time.
Yoonseok Oh; Young-Ji Byon; Ji Young Song; Ho-Chan Kwak; Seungmo Kang. Dwell Time Estimation Using Real-Time Train Operation and Smart Card-Based Passenger Data: A Case Study in Seoul, South Korea. Applied Sciences 2020, 10, 476 .
AMA StyleYoonseok Oh, Young-Ji Byon, Ji Young Song, Ho-Chan Kwak, Seungmo Kang. Dwell Time Estimation Using Real-Time Train Operation and Smart Card-Based Passenger Data: A Case Study in Seoul, South Korea. Applied Sciences. 2020; 10 (2):476.
Chicago/Turabian StyleYoonseok Oh; Young-Ji Byon; Ji Young Song; Ho-Chan Kwak; Seungmo Kang. 2020. "Dwell Time Estimation Using Real-Time Train Operation and Smart Card-Based Passenger Data: A Case Study in Seoul, South Korea." Applied Sciences 10, no. 2: 476.
A database of three-component acceleration time series recorded at downhole arrays in earthen dam cores was published by the Japan Commission on Large Dams. This study reviews the acceleration time series in nine earthfill and rockfill dams in Japan. The apparent shear wave velocities between downhole sensors in each dam during strong shakes are determined by calculating the wave travel time between the recorded time series. Transient shear strains are calculated from the differences in the displacement time series between sensors through the double integration of filtered acceleration time series. The modulus reduction curves of the in situ core materials are constructed by combining the apparent shear wave velocities and shear strains. The modulus reduction data are then compared with empirical models. Observations show considerable uncertainties and dam-dependent characteristics in the extracted in situ shear modulus. Accordingly, this study proposes a methodology to update the empirical modulus reduction model for dam core materials on the basis of observed data on downhole time series.
Tadahiro Kishida; Dongsoon Park; Rita L. Sousa; Richard Armstrong; Young-Ji Byon. Modulus reductions of dam embankment materials based on downhole array time series. Earthquake Spectra 2019, 36, 400 -421.
AMA StyleTadahiro Kishida, Dongsoon Park, Rita L. Sousa, Richard Armstrong, Young-Ji Byon. Modulus reductions of dam embankment materials based on downhole array time series. Earthquake Spectra. 2019; 36 (1):400-421.
Chicago/Turabian StyleTadahiro Kishida; Dongsoon Park; Rita L. Sousa; Richard Armstrong; Young-Ji Byon. 2019. "Modulus reductions of dam embankment materials based on downhole array time series." Earthquake Spectra 36, no. 1: 400-421.
Missing value imputation approaches have been widely used to support and maintain the quality of traffic data. Although the spatiotemporal dependency-based approaches can improve the imputation performance for large and continuous missing patterns, additionally considering traffic states can lead to more reliable results. In order to improve the imputation performances further, a section-based approach is also needed. This study proposes a novel approach for identifying traffic-states of different spots of road sections that comprise, namely, a section-based traffic state (SBTS), and determining their spatiotemporal dependencies customized for each SBTS, for missing value imputations. A principal component analysis (PCA) was employed, and angles obtained from the first principal component were used to identify the SBTSs. The pre-processing was combined with a support vector machine for developing the imputation model. It was found that the segmentation of the SBTS using the angles and considering the spatiotemporal dependency for each state by the proposed approach outperformed other existing models.
Yoon-Young Choi; Heeseung Shon; Young-Ji Byon; Dong-Kyu Kim; Seungmo Kang. Enhanced Application of Principal Component Analysis in Machine Learning for Imputation of Missing Traffic Data. Applied Sciences 2019, 9, 2149 .
AMA StyleYoon-Young Choi, Heeseung Shon, Young-Ji Byon, Dong-Kyu Kim, Seungmo Kang. Enhanced Application of Principal Component Analysis in Machine Learning for Imputation of Missing Traffic Data. Applied Sciences. 2019; 9 (10):2149.
Chicago/Turabian StyleYoon-Young Choi; Heeseung Shon; Young-Ji Byon; Dong-Kyu Kim; Seungmo Kang. 2019. "Enhanced Application of Principal Component Analysis in Machine Learning for Imputation of Missing Traffic Data." Applied Sciences 9, no. 10: 2149.
Leadership development has become an import aspect of the UAE’s educational system. In recent years, UAE leaders have focused on the reform of higher education assessment, curriculum and administration with a view to encouraging Emirati students to contribute to the nation’s growth as national human capital, through leadership roles where they will be guided and educated driving the needs of the knowledge economy. In many courses, students are more knowledge recipients than producers; they are considered cognitively active whilst physically inactive where learning is considered a passive process. BUSS301, a third-year undergraduate course taught to engineering students has undergone major revisions influenced by student evaluations on application, relevance and assessment. The earlier syllabus entitled Corporate Leadership and Human Resource Management (more theoretical and examination driven) has evolved to a more recent Enquiry Based approach: Teaching and Learning Leadership by Simulation and Theory where students are driving their own learning through inquiry using a project-based learning (PBL) approach. Keywords: Project-based learning, engineering education, leadership, student-centred learning, constructivism, teambuilding, collaboration
Siobhan O’Sullivan; Chung-Suk Cho; Robert Pech; Young-Ji Byon. Leadership development of 21st century engineering millennial students in Khalifa University, United Arab Emirates; problem-based learning in action. New Trends and Issues Proceedings on Humanities and Social Sciences 2018, 5, 59 -70.
AMA StyleSiobhan O’Sullivan, Chung-Suk Cho, Robert Pech, Young-Ji Byon. Leadership development of 21st century engineering millennial students in Khalifa University, United Arab Emirates; problem-based learning in action. New Trends and Issues Proceedings on Humanities and Social Sciences. 2018; 5 (3):59-70.
Chicago/Turabian StyleSiobhan O’Sullivan; Chung-Suk Cho; Robert Pech; Young-Ji Byon. 2018. "Leadership development of 21st century engineering millennial students in Khalifa University, United Arab Emirates; problem-based learning in action." New Trends and Issues Proceedings on Humanities and Social Sciences 5, no. 3: 59-70.
For a particular section of a road network, there are multiple sources of quantitative and qualitative traffic information. Quantitative sensors are usually hardware-based, including loop detectors and GPS devices that produce numerical data. Qualitative sensors are usually processed data, including the traffic department’s websites and radio broadcasts that produce subjective categorical data based on hidden processes. Each sensor is characterized by a specific level of error and sampling frequency. It is a challenge to combine and utilize multiple sources of data for estimating real-time traffic conditions. By using Single-Constraint-At-A-Time (SCAAT) Kalman filters, this paper combines multiple data sources from a section of a highway. However, in real-life, true traffic conditions are unknown because all sensors have associated errors with them. A micro-simulation package is used in order to have access to the true traffic conditions of a simulated environment that has been calibrated for a particular road section in Toronto. Then, the performance of predictions made by the developed SCAAT filters are compared with the true traffic conditions under different sampling strategies with varying number of probes and varying sampling frequencies. SCAAT filters are found to be effective for fusing the data and estimating current traffic conditions.
Young-Ji Byon; Amer Shalaby; Baher Abdulhai; Chung-Suk Cho; Hwasoo Yeo; Samah El-Tantawy. Traffic Condition Monitoring with SCAAT Kalman Filter-based Data Fusion in Toronto, Canada. KSCE Journal of Civil Engineering 2018, 23, 810 -820.
AMA StyleYoung-Ji Byon, Amer Shalaby, Baher Abdulhai, Chung-Suk Cho, Hwasoo Yeo, Samah El-Tantawy. Traffic Condition Monitoring with SCAAT Kalman Filter-based Data Fusion in Toronto, Canada. KSCE Journal of Civil Engineering. 2018; 23 (2):810-820.
Chicago/Turabian StyleYoung-Ji Byon; Amer Shalaby; Baher Abdulhai; Chung-Suk Cho; Hwasoo Yeo; Samah El-Tantawy. 2018. "Traffic Condition Monitoring with SCAAT Kalman Filter-based Data Fusion in Toronto, Canada." KSCE Journal of Civil Engineering 23, no. 2: 810-820.
Ideal configuration or layout of highways should resemble the actual demands for the roads represented by Origin-Destination (OD) information. It would be beneficial if existing highways can be evaluated for their configurational fitness against the current demands, and newly planned highways can carefully be designed in terms of their layouts and topologies that would reflect the demands. Analysis techniques used for complex networks in the matured field of network theory can be applied for the highway layout health monitoring against the current OD information. This paper proposes a methodology of measuring the fitness of existing highways by comparing their structural configuration against conceptual OD networks using well-established techniques in network theory for complex networks. In the first phase, this paper conducts an empirical analysis and finds that both structural highway network and OD network follow the "power law" distribution as they are weighted by capacity and traffic volume respectively. It is also found that the power law coefficient of the OD network dynamically changes throughout the day and week. In the second phase, a noble methodology of weighting and measuring the health, of structural highway networks against OD networks by means of comparing their power law coefficients is proposed. It is found that the proposed method is effective at detecting deviations from ideal structural configurations associated with actual demands.
Sehyun Tak; Sunghoon Kim; Young-Ji Byon; Donghoun Lee; Hwasoo Yeo. Measuring health of highway network configuration against dynamic Origin-Destination demand network using weighted complex network analysis. PLOS ONE 2018, 13, e0206538 .
AMA StyleSehyun Tak, Sunghoon Kim, Young-Ji Byon, Donghoun Lee, Hwasoo Yeo. Measuring health of highway network configuration against dynamic Origin-Destination demand network using weighted complex network analysis. PLOS ONE. 2018; 13 (11):e0206538.
Chicago/Turabian StyleSehyun Tak; Sunghoon Kim; Young-Ji Byon; Donghoun Lee; Hwasoo Yeo. 2018. "Measuring health of highway network configuration against dynamic Origin-Destination demand network using weighted complex network analysis." PLOS ONE 13, no. 11: e0206538.
In urban areas, traffic signals cause unnecessary stops and delays to vehicles resulting in excessive energy consumptions and emissions. The eco-approach technology has been introduced to achieve environmentally friendly driving behaviors and to improve energy efficiencies with reduced rapid accelerations or decelerations. However, it is not clear how the behavior of drivers would change while following an eco-approaching vehicle. Especially in the mixed traffic, dynamics behind the interactions between the human-driven vehicle and connected automated vehicle (CAV) that perfectly achieve the ecoapproach, and the impacts on energy consumptions are not transparent. This research designs a driving simulation environment for the mixed traffic to assess the benefits of the eco-approach. In the experiments, a straight roadway with four signalized intersections equipped with communication devices is developed. An eco-guidance algorithm for human drivers and an eco-approach control algorithm of CAV with the I2V communication system are designed and compared, where each scenario is tested 50 times with a human driver using a driving simulator. The results indicate that both eco-guidance scenario and following CAV with the eco-approach scenario could reduce over 6% of fuel consumptions compared to the base-case scenario, which is normal-driving without guidance. This indicates the energy efficiency benefit of the ecoapproach of CAVs and its impact on surrounding vehicles in the mixed traffic.
Lian Cui; Huifu Jiang; B. Brian Park; Young-Ji Byon; Jia Hu. Impact of Automated Vehicle Eco-Approach on Human-Driven Vehicles. IEEE Access 2018, 6, 62128 -62135.
AMA StyleLian Cui, Huifu Jiang, B. Brian Park, Young-Ji Byon, Jia Hu. Impact of Automated Vehicle Eco-Approach on Human-Driven Vehicles. IEEE Access. 2018; 6 (99):62128-62135.
Chicago/Turabian StyleLian Cui; Huifu Jiang; B. Brian Park; Young-Ji Byon; Jia Hu. 2018. "Impact of Automated Vehicle Eco-Approach on Human-Driven Vehicles." IEEE Access 6, no. 99: 62128-62135.
While large construction sites have on-site loaders to handle heavy and large packages of bricks, small brick manufacturers employ a truck-mounted loader or sometimes deploy a loader truck to accompany normal brick delivery trucks to small construction sites lacking on-site loaders. It may be very challenging for small contractors to manage a sustainable delivery system that is both cost-effective and environmentally friendly. To address this issue, this paper proposes to solve a multi-trip vehicle loader routing problem by uniquely planning routes and schedules of several types of vehicles considering their synchronized operations at customer sites and multi trips. This paper also evaluates the sustainability of the developed model from both economic and environmental perspectives. Case studies based on small construction sites in the Middle East demonstrate applications of the proposed model to make the most economical plans for delivering bricks. Compared to the single-trip vehicle loader routing problem, the proposed model reduces, on average, 18.7% of the total delivery cost while increasing CO2 emission negligibly. The economic benefit is mainly achieved by reducing the required number of vehicles. Brick plant managers can use the proposed mathematical model to plan the most cost-effective delivery schedules sustainably while minimizing negative environmental effects.
Heungjo An; Young-Ji Byon; Chung-Suk Cho. Economic and Environmental Evaluation of a Brick Delivery System Based on Multi-Trip Vehicle Loader Routing Problem for Small Construction Sites. Sustainability 2018, 10, 1427 .
AMA StyleHeungjo An, Young-Ji Byon, Chung-Suk Cho. Economic and Environmental Evaluation of a Brick Delivery System Based on Multi-Trip Vehicle Loader Routing Problem for Small Construction Sites. Sustainability. 2018; 10 (5):1427.
Chicago/Turabian StyleHeungjo An; Young-Ji Byon; Chung-Suk Cho. 2018. "Economic and Environmental Evaluation of a Brick Delivery System Based on Multi-Trip Vehicle Loader Routing Problem for Small Construction Sites." Sustainability 10, no. 5: 1427.
In the majority of cases, the primary means of information input to operators in nuclear power plant (NPP) control rooms is through the visual channel. In this study, eye movement patterns of NPP operators are analyzed with eye-tracking data obtained from simulator-based experimental studies. Two eye-tracking measures of attentional-resource effectiveness in monitoring and detection tasks in NPPs that have been developed by the authors are introduced, and several applications with the two eye-tracking measures are discussed for use of the measures. The underlying principle of the measures is that information sources should be selectively attended according to their importance. One of the two measures is the fixation-to-importance ratio (FIR), which represents attentional resource (eye fixations) spent on an information source compared to the importance of the information source. The other measure is selective attention effectiveness (SAE), which incorporates the FIRs of all information sources. The FIR represents the effectiveness of an information source, whereas the SAE represents the overall effectiveness of all information sources. Frequency and duration of eye fixations of an operator on information sources are used as the attentional resource. Finally, insights on future applications of eye-tracking data coupled with other psychophysiological measurement techniques to nuclear human factors are addressed on the basis of advances of fourth industrial revolution technologies.
Jun Su Ha; Young-Ji Byon; Chung-Suk Cho; Poong Hyun Seong. Eye-Tracking Studies Based on Attentional-Resource Effectiveness and Insights into Future Research. Nuclear Technology 2018, 202, 237 -246.
AMA StyleJun Su Ha, Young-Ji Byon, Chung-Suk Cho, Poong Hyun Seong. Eye-Tracking Studies Based on Attentional-Resource Effectiveness and Insights into Future Research. Nuclear Technology. 2018; 202 (2-3):237-246.
Chicago/Turabian StyleJun Su Ha; Young-Ji Byon; Chung-Suk Cho; Poong Hyun Seong. 2018. "Eye-Tracking Studies Based on Attentional-Resource Effectiveness and Insights into Future Research." Nuclear Technology 202, no. 2-3: 237-246.
With recent aging demographic trends, the needs for enhancing geo-spatial analysis capabilities and monitoring the status of accessibilities of its citizens with healthcare services have increased. The accessibility to healthcare is determined not only by geographic distances to service locations, but also includes travel time, available modes of transportation, and departure time. Having access to the latest and accurate information regarding the healthcare accessibility allows the municipal government to plan for improvements, including expansion of healthcare infrastructure, effective labor distribution, alternative healthcare options for the regions with low accessibilities, and redesigning the public transportation routes and schedules. This paper proposes a new method named, Seoul Enhanced 2-Step Floating Catchment Area (SE2SFCA), which is customized for the city of Seoul, where population density is higher and the average distance between healthcare-service locations tends to be shorter than the typical North American or European cities. The proposed method of SE2SFCA is found to be realistic and effective in determining the weak accessibility regions. It resolves the over-estimation issues of the past, arising from the assignment of high healthcare accessibility for the regions with large hospitals and high density of population and hospitals.
Yeeun Kim; Young-Ji Byon; Hwasoo Yeo. Enhancing healthcare accessibility measurements using GIS: A case study in Seoul, Korea. PLOS ONE 2018, 13, e0193013 .
AMA StyleYeeun Kim, Young-Ji Byon, Hwasoo Yeo. Enhancing healthcare accessibility measurements using GIS: A case study in Seoul, Korea. PLOS ONE. 2018; 13 (2):e0193013.
Chicago/Turabian StyleYeeun Kim; Young-Ji Byon; Hwasoo Yeo. 2018. "Enhancing healthcare accessibility measurements using GIS: A case study in Seoul, Korea." PLOS ONE 13, no. 2: e0193013.
Traditionally, departments of transportation (DOTs) have dispatched probe vehicles with dedicated vehicles and drivers for monitoring traffic conditions. Emerging assisted GPS (AGPS) and accelerometer-equipped smartphones offer new sources of raw data that arise from voluntarily-traveling smartphone users provided that their modes of transportation can correctly be identified. By introducing additional raster map layers that indicate the availability of each mode, it is possible to enhance the accuracy of mode detection results. Even in its simplest form, an artificial neural network (ANN) excels at pattern recognition with a relatively short processing timeframe once it is properly trained, which is suitable for real-time mode identification purposes. Dubai is one of the major cities in the Middle East and offers unique environments, such as a high density of extremely high-rise buildings that may introduce multi-path errors with GPS signals. This paper develops real-time mode identification ANNs enhanced with proposed mode availability geographic information system (GIS) layers, firstly for a universal mode detection and, secondly for an auto mode detection for the particular intelligent transportation system (ITS) application of traffic monitoring, and compares the results with existing approaches. It is found that ANN-based real-time mode identification, enhanced by mode availability GIS layers, significantly outperforms the existing methods.
Young-Ji Byon; Jun Su Ha; Chung-Suk Cho; Tae-Yeon Kim; Chan Yeob Yeun. Real-Time Transportation Mode Identification Using Artificial Neural Networks Enhanced with Mode Availability Layers: A Case Study in Dubai. Applied Sciences 2017, 7, 923 .
AMA StyleYoung-Ji Byon, Jun Su Ha, Chung-Suk Cho, Tae-Yeon Kim, Chan Yeob Yeun. Real-Time Transportation Mode Identification Using Artificial Neural Networks Enhanced with Mode Availability Layers: A Case Study in Dubai. Applied Sciences. 2017; 7 (9):923.
Chicago/Turabian StyleYoung-Ji Byon; Jun Su Ha; Chung-Suk Cho; Tae-Yeon Kim; Chan Yeob Yeun. 2017. "Real-Time Transportation Mode Identification Using Artificial Neural Networks Enhanced with Mode Availability Layers: A Case Study in Dubai." Applied Sciences 7, no. 9: 923.
Emerging technologies provide a venue on which on-line traffic controls and management systems can be implemented. For such applications, having access to accurate predictions on travel-times are mandatory for their successful operations. Transportation engineers have developed numerous approaches including model-based approaches. The model-based approaches consider underlying traffic mechanisms and behaviors in developing the prediction procedures and they are logically intuitive unlike datadriven approaches. Because of this explanation power, the model-based approaches have been developed for the on-line control purposes. For departments of transportation (DOTs), it is still a challenge to choose a specific approach that meets their requirements. In efforts to develop a unique guideline for transportation engineers and decision makers when considering for implementing modelbased approaches for highways, this paper reviews model-based travel-time prediction approaches by classifying them into four categories according to the level of details involved in the model: Macroscopic, Mesoscopic, CA-based, and Microscopic. Then each method is evaluated from five main perspectives: Prediction range, Accuracy, Efficiency, Applicability, and Robustness. Finally, this paper concludes with evaluations of model-based approaches in general and discusses them in relation to data-driven approaches along with future research directions.
Simon Oh; Young-Ji Byon; Kitae Jang; Hwasoo Yeo. Short-term travel-time prediction on highway: A review on model-based approach. KSCE Journal of Civil Engineering 2017, 22, 298 -310.
AMA StyleSimon Oh, Young-Ji Byon, Kitae Jang, Hwasoo Yeo. Short-term travel-time prediction on highway: A review on model-based approach. KSCE Journal of Civil Engineering. 2017; 22 (1):298-310.
Chicago/Turabian StyleSimon Oh; Young-Ji Byon; Kitae Jang; Hwasoo Yeo. 2017. "Short-term travel-time prediction on highway: A review on model-based approach." KSCE Journal of Civil Engineering 22, no. 1: 298-310.
Leo G. Rebholz; Tae-Yeon Kim; Young-Ji Byon. On an accurate α model for coarse mesh turbulent channel flow simulation. Applied Mathematical Modelling 2017, 43, 139 -154.
AMA StyleLeo G. Rebholz, Tae-Yeon Kim, Young-Ji Byon. On an accurate α model for coarse mesh turbulent channel flow simulation. Applied Mathematical Modelling. 2017; 43 ():139-154.
Chicago/Turabian StyleLeo G. Rebholz; Tae-Yeon Kim; Young-Ji Byon. 2017. "On an accurate α model for coarse mesh turbulent channel flow simulation." Applied Mathematical Modelling 43, no. : 139-154.
Emerging GPS devices enable new data collection opportunities for transit performance monitoring. In addition to the fact that GPS devices can replace labor-intensive survey techniques, they also collect traffic information throughout transit routes that the traditional fixed loop detectors cannot. If public transit vehicles are equipped with GPS devices, it is possible to monitor the performance of public transit services throughout the routes and alert the associated authorities at significantly lower costs about potential problems for corrective actions to be taken. Transantiago, a major public transit service provider in Santiago, Chile, has recently installed GPS sensors on all its vehicles which provides an excellent venue on which an innovative transit monitoring methodology can be modeled and applied. This paper first conducts current-status analysis on distributions of headways throughout a route in Santiago by processing extensive raw GPS data from transit vehicles. Then, unique transit headway adherence indices are developed with respect to the expected passenger waiting time and are presented in forms of two-dimensional tempo-spatial graphs. The analysis of real-life data collected from bus GPS probes in Santiago, Chile indicates that GPS devices in transit buses can effectively provide the proposed performance measures throughout the route on a daily basis.
Young-Ji Byon; Cristián E. Cortés; Young-Seon Jeong; Francisco Javier Martínez; Marcela A. Munizaga; Mauricio Zúñiga. Bunching and Headway Adherence Approach to Public Transport with GPS. International Journal of Civil Engineering 2017, 16, 647 -658.
AMA StyleYoung-Ji Byon, Cristián E. Cortés, Young-Seon Jeong, Francisco Javier Martínez, Marcela A. Munizaga, Mauricio Zúñiga. Bunching and Headway Adherence Approach to Public Transport with GPS. International Journal of Civil Engineering. 2017; 16 (6):647-658.
Chicago/Turabian StyleYoung-Ji Byon; Cristián E. Cortés; Young-Seon Jeong; Francisco Javier Martínez; Marcela A. Munizaga; Mauricio Zúñiga. 2017. "Bunching and Headway Adherence Approach to Public Transport with GPS." International Journal of Civil Engineering 16, no. 6: 647-658.
Automatic Dependent Surveillance-Broadcast (ADS-B) is one of the key technologies for future “e-Enabled” aircrafts. ADS-B uses avionics in the e-Enabled aircrafts to broadcast essential flight data such as call sign, altitude, heading, and other extra positioning information. On the one hand, ADS-B brings significant benefits to the aviation industry, but, on the other hand, it could pose security concerns as channels between ground controllers and aircrafts for the ADS-B communication are not secured, and ADS-B messages could be captured by random individuals who own ADS-B receivers. In certain situations, ADS-B messages contain sensitive information, particularly when communications occur among mission-critical civil airplanes. These messages need to be protected from any interruption and eavesdropping. The challenge here is to construct an encryption scheme that is fast enough for very frequent encryption and that is flexible enough for effective key management. In this paper, we propose a Staged Identity-Based Encryption (SIBE) scheme, which modifies Boneh and Franklin's original IBE scheme to address those challenges, that is, to construct an efficient and functional encryption scheme for ADS-B system. Based on the proposed SIBE scheme, we provide a confidentiality framework for future e-Enabled aircraft with ADS-B capability.
Joonsang Baek; Eman Hableel; Young-Ji Byon; Duncan S. Wong; Kitae Jang; Hwasoo Yeo. How to Protect ADS-B: Confidentiality Framework and Efficient Realization Based on Staged Identity-Based Encryption. IEEE Transactions on Intelligent Transportation Systems 2016, 18, 690 -700.
AMA StyleJoonsang Baek, Eman Hableel, Young-Ji Byon, Duncan S. Wong, Kitae Jang, Hwasoo Yeo. How to Protect ADS-B: Confidentiality Framework and Efficient Realization Based on Staged Identity-Based Encryption. IEEE Transactions on Intelligent Transportation Systems. 2016; 18 (3):690-700.
Chicago/Turabian StyleJoonsang Baek; Eman Hableel; Young-Ji Byon; Duncan S. Wong; Kitae Jang; Hwasoo Yeo. 2016. "How to Protect ADS-B: Confidentiality Framework and Efficient Realization Based on Staged Identity-Based Encryption." IEEE Transactions on Intelligent Transportation Systems 18, no. 3: 690-700.