Journal of the Korea Academia-Industrial cooperation Society
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v.19
no.12
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pp.887-895
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2018
This paper presents a braking model that can be used to design the safety distance of a train control system and a train braking system to increase the volume of traffic. For the braking model, a train set (electric multiple unit composed 6 cars) was tested. The factors that can affect the braking characteristics include the friction coefficient, braking pressure, and regenerative braking. The braking pressure was classified into service and emergency braking and reflected the characteristics of the vehicle. The external force acting on the running railway car was tested in accordance with KS R 9217, and the running resistance of the train is presented in the form of a polynomial. The dynamic behavior of the train running on a straight flat line was simulated using UM 8.3. The results were validated with experimental data, and the results were reasonable. With the validated model, a stopping distance was determined according to the initial braking speed and compared with the deceleration braking model. In addition, a safety distance for the train control system could be changed according to the frictional coefficient limits. These results are expected to be useful for analyzing the dynamic behavior of trains, and for analyzing various railway environments and improving the braking performance.
KIPS Transactions on Computer and Communication Systems
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v.13
no.1
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pp.21-30
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2024
As the self-driving car market continues to grow, the need for charging infrastructure is growing. However, in the case of a wireless charging system, stability issues are being raised because it requires a large amount of power compared with conventional wired charging. SAE J2954 is a standard for building autonomous vehicle wireless charging infrastructure, and the standard defines a communication method between a vehicle and a power transmission system. SAE J2954 recommends using physical media such as Wi-Fi, Bluetooth, and UWB as a wireless charging communication method for autonomous vehicles to enable communication between the vehicle and the charging pad. In particular, UWB is a suitable solution for indoor and outdoor charging environments because it exhibits robust communication capabilities in indoor environments and is not sensitive to interference. In this standard, the process for building a wireless power transmission system is divided into several stages from the start to the completion of charging. In this study, UWB technology is used as a means of fine alignment, a process in the wireless power transmission system. To determine the applicability to an actual autonomous vehicle wireless power transmission system, experiments were conducted based on distance, and the distance information was collected from UWB. To improve the accuracy of the distance data obtained from UWB, we propose a Single Model and Multi Model that apply machine learning and deep learning techniques to the collected data through a three-step preprocessing process.
For the purpose of preciously describing real time traffic pattern in urban road network, dynamic network loading(DNL) models able to simulate traffic behavior are required. A number of different methods are available, including macroscopic, microscopic dynamic network models, as well as analytical model. Equivalency minimization problem and Variation inequality problem are the analytical models, which include explicit mathematical travel cost function for describing traffic behaviors on the network. While microscopic simulation models move vehicles according to behavioral car-following and cell-transmission. However, DNL models embedding such travel time function have some limitations ; analytical model has lacking of describing traffic characteristics such as relations between flow and speed, between speed and density Microscopic simulation models are the most detailed and realistic, but they are difficult to calibrate and may not be the most practical tools for large-scale networks. To cope with such problems, this paper develops a new DNL model appropriate for dynamic traffic assignment(DTA), The model is combined with vertical queue model representing vehicles as vertical queues at the end of links. In order to compare and to assess the model, we use a contrived example network. From the numerical results, we found that the DNL model presented in the paper were able to describe traffic characteristics with reasonable amount of computing time. The model also showed good relationship between travel time and traffic flow and expressed the feature of backward turn at near capacity.
The advent of 5G mobile communications, which is expected in 2020, will provide many services such as Internet of Things (IoT) and vehicle-to-infra/vehicle/nomadic (V2X) communication. There are many requirements to realizing these services: reduced latency, high data rate and reliability, and real-time service. In particular, a high level of reliability and delay sensitivity with an increased data rate are very important for M2M, IoT, and Factory 4.0. Around the world, 5G standardization organizations have considered these services and grouped them to finally derive the technical requirements and service scenarios. The first scenario is broadcast services that use a high data rate for multiple cases of sporting events or emergencies. The second scenario is as support for e-Health, car reliability, etc.; the third scenario is related to VR games with delay sensitivity and real-time techniques. Recently, these groups have been forming agreements on the requirements for such scenarios and the target level. Various techniques are being studied to satisfy such requirements and are being discussed in the context of software-defined networking (SDN) as the next-generation network architecture. SDN is being used to standardize ONF and basically refers to a structure that separates signals for the control plane from the packets for the data plane. One of the best examples for low latency and high reliability is an intelligent traffic system (ITS) using V2X. Because a car passes a small cell of the 5G network very rapidly, the messages to be delivered in the event of an emergency have to be transported in a very short time. This is a typical example requiring high delay sensitivity. 5G has to support a high reliability and delay sensitivity requirements for V2X in the field of traffic control. For these reasons, V2X is a major application of critical delay. V2X (vehicle-to-infra/vehicle/nomadic) represents all types of communication methods applicable to road and vehicles. It refers to a connected or networked vehicle. V2X can be divided into three kinds of communications. First is the communication between a vehicle and infrastructure (vehicle-to-infrastructure; V2I). Second is the communication between a vehicle and another vehicle (vehicle-to-vehicle; V2V). Third is the communication between a vehicle and mobile equipment (vehicle-to-nomadic devices; V2N). This will be added in the future in various fields. Because the SDN structure is under consideration as the next-generation network architecture, the SDN architecture is significant. However, the centralized architecture of SDN can be considered as an unfavorable structure for delay-sensitive services because a centralized architecture is needed to communicate with many nodes and provide processing power. Therefore, in the case of emergency V2X communications, delay-related control functions require a tree supporting structure. For such a scenario, the architecture of the network processing the vehicle information is a major variable affecting delay. Because it is difficult to meet the desired level of delay sensitivity with a typical fully centralized SDN structure, research on the optimal size of an SDN for processing information is needed. This study examined the SDN architecture considering the V2X emergency delay requirements of a 5G network in the worst-case scenario and performed a system-level simulation on the speed of the car, radius, and cell tier to derive a range of cells for information transfer in SDN network. In the simulation, because 5G provides a sufficiently high data rate, the information for neighboring vehicle support to the car was assumed to be without errors. Furthermore, the 5G small cell was assumed to have a cell radius of 50-100 m, and the maximum speed of the vehicle was considered to be 30-200 km/h in order to examine the network architecture to minimize the delay.
Traffic data by vehicle classification is difficult for mutual exchange of data due to the different vehicle classification from each other by the data sources; as a result, application of the data is very limited. In Particular. in case of TCS vehicle classification in national highways, passenger car, van and truck are mixed in one category and the practical usage is very low. The research standardize the vehicle classification to convert other data and develop the model which can estimate national highway traffic data by the standardized vehicle classification from the raw traffic data obtained at the highway tollgates. The tollgates are categorized into several groups by their features and the model estimates traffic data by the standardized vehicle classification by using the point estimation and bootstrap algorithm. The result indicates that both of the two methods above have the significant level. When considering the bias of the extreme value by the sample size, the bootstrap algorithm is more sophisticated. Using result of this study, we is expect the usage improvement of TCS data and more specific comparison between the freeway traffic investigation and link volume on freeway using the TCS data.
The Korea's automotive industry have been achieved a remarkable growth with various original models since the first original model ‘Pony’for the 25years. Most of the design works were depended upon the designers of the other countries on the early times, but now the design work gets to have the independency with our own technology and the automobile is now one of the major exporting goods of Korea to other countries. The basic design concept of the body shape can be considered into four types, and they have their own characteristics. The period of time for the original model developement of the Korean auto makers can be thought as four periods ; introducing period, settling period, developing period and matured period are them. The models that developed on each period reflects the characteristics of the times with designers, technology and market conditions. The basic design concepts of the Korean car body show the variety but the concepts have been intergrated into the two types as the time gose by. This tendency would comes form mainly technology, but the consumers characteristics of the market would also influence as much as the technological reason. It would become more important on developing the original model with the autonomy in design concept of the body through grasping the change of formal characteristics clearly on an automobile in the future.
Kim, Su jae;Choo, Sang ho;Kim, Ji yoon;Han, Jae yoon
The Journal of The Korea Institute of Intelligent Transport Systems
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v.17
no.1
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pp.55-70
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2018
Recently, as shared transportation services has expanded, integrated mobility services that link personal transportation and public transportation are paid attention. To do this, it is necessary to analyze trip mode chaining behavior. This study analyzed the characteristics of the trip mode chaining behavior using the 2010 travel diary survey in Seoul, and analyzed factors to affect mode choice of trip chaining through the multinomial logit model. The transportation means were classified into passenger cars, city buses, intercity buses, railways, taxis, and others, and 25 trip mode chaining types were identified. Among them, the trip share connected between city bus and railways was the highest. It was also found that the trip mode chaining occurred mainly at commuting and in the morning and afternoon peak. According to the model results, the mode choice of trip chaining is significantly influenced by individual attributes (sex and age), household attributes (car ownership and income), trip attributes (trip purpose, trip time and trip length), and arrival area attributes (number of subway lines and bus lines, ratio of commercial area, land use mix and central region).
Park, Kyung-Soon;Park, Jae-Seong;Ban, Keum-Ok;Kim, Kyoung-Oak
The Journal of the Korea Contents Association
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v.13
no.11
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pp.322-331
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2013
The purpose of the present study was to develop a convergent education contents for dementia prevention, operating on the web network applying modern information technology(IT). At the preparation stage, local and worldwide literatures related to dementia were analyzed followed by surveying industry demands, based on which the program was designed and developed. In the following enhancement stage, the program was modified as much as possible by advices obtained from experts in various fields. Development results of the present program are summarized as follows. Firstly, 645 intellect development model to prevent dementia was established through peer review and verification of convergent education theories by expert groups. This model was named as "Garisani" meaning "cognition capable of judging objects" in the Korean language. Secondly, 'Find a way' and 'Connect a line' modules were developed in the numeric field as well as 'Identify a letter(I, II)' modules, in the language field for web-based left brain training program. Thirdly, 'Find my car' and 'Vision training' modules in the attention field and 'Object inference' and 'Compare pictures' modules in the cognition field were developed for web-based right brain training program. Fourth, 'Pentomino' and 'BQmaze'(Brain Quotient and maze) modules in the space perception field and 'Visual training' in the memory field were developed for web-based left and right brains training. Fifth, all results were integrated leading to a 52 week Garisani convergent education program for dementia prevention.
Hwang, Jin Sang;Kim, Jae Koo;Yun, Hong Sik;Jung, Woon Chul
Journal of Korean Society for Geospatial Information Science
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v.23
no.2
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pp.97-104
/
2015
Due to the introduction of various IT devices, including the recently smartphones and the widespread use of the car navigation system to the location-based information service space has been increased. Spatial information users have been requiring higher levels of quality. In this paper, we study how to build accurate three-dimensional space information by integrating MMS(Moblie Mapping System) survey and airborne survey data. Thus, to analyze the tendency of deviation between the MMS survey and airborne survey data observed in the experimental region, the deviation tendency of the data, it was confirmed that was not consistent. Deviation correction model to select how to change the georeferencing information directly contained in the GPS/INS processing results for the determination, classifies the standard is a method for acquiring the correction reference point coordinates using the calibration model, and analyzed their advantages and disadvantages. With the information of the reference point obtained by airborne photograph of a project, using the method of correcting the MMS survey data. Not only clear the deviation existing between the MMS survey data, it was possible to confirm that the deviation exists between the airborne survey data and MMS survey data was also almost erased.
The purpose of this study is to verify how 7 sentiment domains extracted through sentiment analysis from social media have an influence on business performance. It consists of three phases. In phase I, we constructed the sentiment lexicon after crawling 45,447 pieces of VOC (Voice of the Customer) on 26 auto companies from the car community and extracting the POS information and built a seven-sensitive domains. In phase II, in order to retain the reliability of experimental data, we examined auto-correlation analysis and PCA. In phase III, we investigated how 7 domains impact on the market share of three major (GM, FCA, and VOLKSWAGEN) auto companies by using linear regression analysis. The findings from the auto-correlation analysis proved auto-correlation and the sequence of the sentiments, and the results from PCA reported the 7 sentiments connected with positivity, negativity and neutrality. As a result of linear regression analysis on model 1, we indentified that the sentimental factors have a significant influence on the actual market share. In particular, not only posotive and negative sentiment domains, but neutral sentiment had significantly impacted on auto market share. As we apply the availability of data to the market, and take advantage of auto-correlation of the market-related information and the sentiment, the findings will be a huge contribution to other researches on sentiment analysis as well as actual business performances in various ways.
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