• The Journal of Korean Institute of Communications and Information Sciences
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• v.38C no.3
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• pp.227-232
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• 2013

Due to the development of ITS technology, various services related to transportation under vehicular environments have been provided. Especially, as wireless communication technology, WAVE has been established as a standard for vehicle-to-vehicle communications. WAVE has fast connection and excellent mobility characteristics. A VSC-A project is conducting by global automotive OEMs in USDOT. This project introduces the advanced safety services with vehicle-to-vehicle communications. In this paper, we presented the scenario of a do not pass warning service, which prevents an accident during overtaking activity by using vehicle-to-vehicle communications. In addition, we analyzed network performance under WAVE. In conclusion, we introduced the simulation results. Finally, we summarized the communication range and delay values for consideration factors for a overtaking model.

• The KIPS Transactions:PartD
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• v.19D no.2
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• pp.127-132
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• 2012

In the Seoul metropolitan bus network, it may be necessary for a bus passenger to pick up a parcel, which has been purchased through e-commerce, at his or her convenient bus stop on the way to home or office. The flow-capturing location-allocation model can be applied to select pickup points for such bus stops so that they maximize the captured passenger flows, where each passenger flow represents an origin-destination (O-D) pair of a passenger trip. In this paper, we propose a fast heuristic algorithm to select pickup points using a large O-D matrix, which has been extracted from five million transportation card transactions. The experimental results demonstrate the bus stops chosen as pickup points in terms of passenger flow and capture ratio, and illustrate the spatial distribution of the top 20 pickup points on a map.

• Proceedings of the KOR-KST Conference
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• 2003.02a
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• pp.127-150
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• 2003

This research presents a novel application of static traffic assignment methods, but with a variable time value, for estimating the market share of a high-speed rail (HSR) in the NW-SE corridor of Korea which is currently served by the airline (AR), conventional rail (CR), and highway (HWY) modes. The proposed model employs the time-space network structure to capture the interrelations among all competing transportation modes, and to reflect their supply- and demand-sides constraints as well as interactions through properly formulated link-node structures. The embedded cost function for each network link offers the flexibility for incorporating all associated factors, such as travel time and fare, in the model computation, and enables the use of a distribution rather than a constant to represent the time-value variation among all transportation mode users. To realistically capture the tripmakers' value-of-time (VOT) along the target area, a novel method for VOT calibration has been developed with aggregate demand information and key system performance data from the target area. Under the assumption that intercity tripmakers often have nearly "perfect" travel information, one can solve the market share of each mode after operations of HSR for each O-D pair under the time-dependent demand with state-of-the-art traffic assignment. Aside from estimating new market share, this paper also investigated the impacts of HSR on other existing transportation modes.

• Journal of the Korean Society of Safety
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• v.38 no.4
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• pp.54-59
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• 2023

The relationship between near misses and major accidents can be confirmed using the ratios proposed by Heinrich and Bird. Systematic reviews of previous national and international studies did not reveal the assessment process used in near-miss management systems. In this study, a model was developed for assessing near misses and major factors were derived through case application. By reviewing national and international literature, 14 factors were selected for each dimension of the P2T (people, procedure, technology) model. To identify the causal relationship between accidents and these factors, a near-miss assessment model was developed using a Bayesian network. In addition, a sensitivity analysis was conducted to derive the major factors. To verify the validity of the model, near-miss data obtained from the ethylene production process were applied. As a result, "PE2 (education)," "PR1 (procedure)," and "TE1 (equipment and facility not installed)" were derived as the major factors causing near misses in this process. If actual workplace data are applied to the near-miss assessment model developed in this study, results that are unique to the workplace can be confirmed. In addition, scientific safety management is possible only when priority is given through sensitivity analysis.

• Journal of the Korea Convergence Society
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• v.13 no.1
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• pp.51-62
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• 2022

AI-based speed prediction studies have been conducted quite actively. However, while the importance of explainable AI is emerging, the study of interpreting and reasoning the AI-based speed predictions has not been carried out much. Therefore, in this paper, 'Explainable Deep Graph Neural Network (GNN)' is devised to analyze the speed prediction and assess the nearby road influence for reasoning the critical contributions to a given road situation. The model's output was explained by comparing the differences in output before and after masking the input values of the GNN model. Using TOPIS traffic speed data, we applied our GNN models for the major congested roads in Seoul. We verified our approach through a traffic flow simulation by adjusting the most influential nearby roads' speed and observing the congestion's relief on the road of interest accordingly. This is meaningful in that our approach can be applied to the transportation network and traffic flow can be improved by controlling specific nearby roads based on the inference results.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.17 no.5
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• pp.14-28
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• 2018

Thanks to technical improvement on the vehicle to vehicle communication and the intelligent transportation system, gradual introduction of the autonomous vehicles is expected soon in the market. The study analyzes the autonomous vehicles' impacts on the network efficiencies. In order to measure the network efficiencies, the study applies the sequential procedures that combines the microscopic and macroscopic simulations. The microscopic simulation attends to the capacity changes due to the autonomous vehicles' proportions on the roadway while the macroscopic simulation utilizes the simulation results in order to identify the network-wide improvement. As expected, the autonomous vehicles efficiently utilizes the existing capacity of the roadway than the human driving does. Particularly, the maximum capacity improvements are expected by the 190.5% on the expressway. The significant capacity change is observed when the autonomous vehicles' proportions are about 80% or more. These improvements are translated into the macroscopic model, which also yields overall network efficiency improvement by the autonomous vehicles' penetration. However, the study identifies that the market debut of the autonomous vehicles does not promise the free flow condition, which implies the possible needs of the system optimal routing scheme for the era of the autonomous vehicles.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.14 no.7
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• pp.3508-3517
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• 2013

District is not only a place that every urban activities are executing but also basic unit that are forming urban structure. Therefore this study tried to make land use-transportation model through analyzing $CO_2$ exhausting volumes by assuming 270 scenarios those are postulated various land use patterns and transport policies in District. As results, this study shows best District Unit Design technique is the policy that develop equally all blocks or only outer blocks and introduction of car free zone to inner 2 way streets. Most important policy in order to reduce $CO_2$ gas is to introduce Transportation Demand Management especially in case of hyper high density development. In case of low density development, policy of car free streets in 2 ways roads is efficiency for reducing $CO_2$ gas. And suggested land use-transportation model will be good for choosing alternatives those are able to reduce $CO_2$ in District Unit.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2006.11a
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• pp.599-617
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• 2006

A network model and a Genetic Algorithm(GA) is proposed to solve the simultaneous estimation of the trip distribution and traffic assignment from traffic counts in the congested networks in a logit-based Stochastic User Equilibrium (SUE). The model is formulated as a problem of minimizing the non-linear objective functions with the linear constraints. In the model, the flow-conservation constraints of the network are utilized to restrict the solution space and to force the link flows meet the traffic counts. The objective of the model is to minimize the discrepancies between the link flows satisfying the constraints of flow-conservation, trip production from origin, trip attraction to destination and traffic counts at observed links and the link flows estimated through the traffic assignment using the path flow estimator in the legit-based SUE. In the proposed GA, a chromosome is defined as a vector representing a set of Origin-Destination Matrix (ODM), link flows and travel-cost coefficient. Each chromosome is evaluated from the corresponding discrepancy, and the population of the chromosome is evolved by the concurrent simplex crossover and random mutation. To maintain the feasibility of solutions, a bounded vector shipment is applied during the crossover and mutation.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.40 no.2
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• pp.119-133
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• 2022

Due to the improvement of surveying, mapping and communication techniques, various apps for road direction guides and vehicle navigations have been developed. Although such a development has impacted on walking and driving, there is a limit to improving the daily convenience of the socially impaired people. This is mainly due to the fact that the software have been developed for normal pedestrians and drivers. Therefore, visually impaired people still have problems with the confusion of direction and/or non-provision of risk factors in walking. This study aimed to propose a scheme which constructs data for mobility-impaired or traffic-impaired people based on various geospatial information. The factors and components related to walking for the visually impaired are selected by geospatial data and a walking route guidance network that can be applied to a commercial software. As a result, it was confirmed that road direction guidance would be possible if additional contents, such as braille blocks (dotted/linear), sound signals, bus stops, and bollards are secured. In addition, an initial version of the application software was implemented based on the suggested data model and its usefulness was evaluated to a visually impaired person. To advance the stability of the service in walking for the visually impaired people, various geospatial data obtained by multiple institutes are necessary to be combined, and various sensors and voice technologies are required to be connected and utilized through ICT (Information and Communications Technologies) technology in near future.

• Journal of the Korean Institute of Intelligent Systems
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• v.5 no.4
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• pp.41-55
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• 1995

In this paper, an optimal idenfication method using fuzzy-neural networks is proposed for modeling of nonlinear complex systems. The proposed fuzzy-neural modeling implements system structure and parameter identification using the intelligent schemes together wlth optimization theory, linguistic fuzzy implication rules, and neural networks(NNs) from input and output data of processes. Inference type for this fuzzy-neural modeling is presented as simplified inference. To obtain optimal model, the learning rates and momentum coefficients of fuzzy-neural networks(FNNs) are tuned automatically using improved modified complex method and modified learning algorithm. For the purpose of its application to nonlinear processes, data for route choice of traffic problems and those for activateti sluge process of sewage treatment system are used for the purpose of evaluating the performance of the proposed fuzzy-neural network modeling. The results show that the proposed method can produce the intelligence model with higher accuracy than other works achieved previously.