• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.20 no.2
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• pp.95-111
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• 2021

As the population decreases in an aging society, the average age of drivers increases. Accordingly, the elderly at high risk of being in an accident need autonomous-driving vehicles. In order to secure driving safety on the road, several technologies to respond to various obstacles are required in those vehicles. Among them, technology is required to recognize static obstacles, such as poor road conditions, as well as dynamic obstacles, such as vehicles, bicycles, and people, that may be encountered while driving. In this study, we propose a deep neural network algorithm capable of simultaneously detecting these two types of obstacle. For this algorithm, we used 1,418 road images and produced annotation data that marks seven categories of dynamic obstacles and labels images to indicate road damage. As a result of training, dynamic obstacles were detected with an average accuracy of 46.22%, and road surface damage was detected with a mean intersection over union of 74.71%. In addition, the average elapsed time required to process a single image is 89ms, and this algorithm is suitable for personal mobility vehicles that are slower than ordinary vehicles. In the future, it is expected that driving safety with personal mobility vehicles will be improved by utilizing technology that detects road obstacles.

• Journal of Korean Tunnelling and Underground Space Association
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• v.19 no.5
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• pp.813-827
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• 2017

Surveillance cameras installed in tunnels capture the various video frames effected by dynamic and variable factors. In addition, localizing and managing the cameras in tunnel is not affordable, and quality of capturing frame is effected by time. In this paper, we introduce a new method to detect and track the vehicles in tunnel by using surveillance cameras installed in a tunnel. It is difficult to detect the video frames directly from surveillance cameras due to the motion blur effect and blurring effect on lens by dirt. In order to overcome this difficulties, two new methods such as Differential Frame/Non-Maxima Suppression (DFNMS) and Haar Cascade Detector to track cars are proposed and investigated for their feasibilities. In the study, it was shown that high precision and recall values could be achieved by the two methods, which then be capable of providing practical data and key information to an automatic accident detection system in tunnels.

• Journal of Korean Society of Transportation
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• v.19 no.3
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• pp.101-113
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• 2001

Since late 1970s. one of the principal research areas in transportation problem is dynamic traffic assignment (DTA). Although many models have been developed regarding DTA, yet they have some limits of describing real traffic patterns. This reason comes from the fact that DTA model has the time varying constraints such as state equation, flow propagation constraint, first in first out(FIFO) rule and queuing evolution. Thus, DTA model should be designed to satisfy these constraints as well as dynamic route choice condition, dynamic user equilibrium. In this respect, link-based DTA models have difficulty in satisfying such constraints because they have to satisfy the constraints for each link, while path-based DTA models may easily satisfy them. In this paper we develop a path-based DTA model. The model includes point queue theory to describe the queue evolution and simulation loading method for depicting traffic patterns in more detail. From a numerical test, the model shows promising results.

• Journal of the Society of Disaster Information
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• v.17 no.3
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• pp.655-666
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• 2021

Purpose: This study is to develop a method for measuring dynamic speeding risks using vehicle trajectory big data and to demonstrate the feasibility of the devised speeding index. Method: The speed behaviors of vehicles were analysed in microscopic space and time using individual vehicle trajectories, and then the boundary condition of speeding (i.e., boundary speed) was determined from the standpoint of crash risk. A novel index for measuring the risk exposure of speeding was developed in microscopic space and time with the boundary speed. Result: A validation study was conducted with vehicle-GPS trajectory big data and ground-truth vehicle crash data. As a result of the analysis, it turned out that the index of speeding-risk exposure has a strong explanatory power (R²=0.7) for motorway traffic accidents. This directly indicates that speeding behaviors should be analysed at a microscopic spatiotemporal dimension. Conclusion: The spatial and temporal evolution of vehicle velocity is very variable. It is, hence, expected that the method presented in this study could be efficaciously employed to analyse the causal factors of traffic accidents and the crash risk exposure in microscopic space using mobility trajectory data.

• Journal of Korean Society of Transportation
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• v.20 no.5
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• pp.113-130
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• 2002

In this paper, we developed DNL(Dynamic Network Loading) model based on Moving cell theory to analyze the dynamic characteristics of traffic flow in congested network. In this paper vehicles entered into link at same interval would construct one cell, and the cells moved according to Cell following rule. In the past researches relating to DNL model a continuous single link is separated into two sections such as running section and queuing section to describe physical queue so that various dynamic states generated in real link are only simplified by running and queuing state. However, the approach has some difficulties in simulating various dynamic flow characteristics. To overcome these problems, we present Moving cell theory which is developed by combining Car following theory and Lagrangian method mainly using for the analysis of air pollutants dispersion. In Moving cell theory platoons are represented by cells and each cell is processed by Cell following theory. This type of simulation model is firstly presented by Cremer et al(1999). However they did not develop merging and diverging model because their model was applied to basic freeway section. Moreover they set the number of vehicles which can be included in one cell in one interval so this formulation cant apply to signalized intersection in urban network. To solve these difficulties we develop new approach using Moving cell theory and simulate traffic flow dynamics continuously by movement and state transition of the cells. The developed model are played on simple network including merging and diverging section and it shows improved abilities to describe flow dynamics comparing past DNL models.

• Journal of the Korea Society for Simulation
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• v.17 no.2
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• pp.91-103
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• 2008

In order to simulate the behavior of automated manufacturing systems, the performance of material handling systems should be measured dynamically. Multi-Agent technology could be well adapted for the development of simulator for distributed and intelligent manufacture systems. A multi-agent system is composed of one coordination agent and multiple application agents. Issues in AGVS simulator can be classified by the set-up and operating problems. Decisions on the number of vehicles, bi- or uni-directional guide-path, etc. are fallen into the set-up problem category, while deadlock tree algorithm and conflict resolution are in operating problem. In this paper, a multi-agent based deadlock-free simulator for automated guided vehicle system(AGVS) are proposed through the use of multi-agent technologies and the development of deadlock-free algorithm. In this AGVS simulator proposed, well-known Floyd algorithm is used to create AGVS Guide path, through which AGVS move. Also, AGVs avoid vehicle conflict and deadlock using check path algorithm. And Moving vehicle agents are operated in real-time control by coordination agent. AGV position is dynamically calculated based on the concept of rolling time horizon. Simulator receives and presents operating information of vehicle in AGVS Gaunt chart. The performance of the proposed algorithm and developed simulator based on multi-agent are validated through set of experiments.

• Journal of the Korean Geotechnical Society
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• v.31 no.9
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• pp.29-38
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• 2015

In this study, track dynamic interaction characteristics caused by the vehicle running through transitional section such as bridge abutments were studied using the finite element analysis program. The geometric condition of track was generated by trigonometric function and allowable maximum track irregularity is determined by KORAIL track maintenance criteria. The sub-infrastructure under rail fastener system was modelled by 3D solid elements. To reduce computational cost only half track line is numerically considered and the roller boundary condition was applied to each side of model. In this study, the vehicle-track dynamic interaction analysis was carried out for standard Korean transition section of concrete track and the dynamic behaviors were investigated. The dynamic characteristics considered are wheel load variation, vertical acceleration at body, and maximum Mises stress at each part of transitional section.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2010.05a
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• pp.761-764
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• 2010

Interest in vehicle infotainment system, that provides both entertainment of driving and information for safe and convenient driving, has been recently increased. MOST is defined as the network transmitting high-bandwidth infortainment data to vehicle, and it has been standardized as MOST150. In this research, dynamic behavior method that deals with roles and functions of each devices connected to MOST150 Network, and Power Management Method was studied. MOST Network consists of a master device, including function block 'NetworkMaster', and all other devices called slave devices. The purpose of this study is to apply the analysis of the methods of operating and power management based on condition of master device and slave devices on MOST150 network to the future development of MOST150 devices.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2014.10a
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• pp.624-627
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• 2014

In vehicular network, the basic goal is to provide vehicle safety service and commercial service such as ITS(Intelligent Transportation System) or video, etc on the road. And most research concentrated on transportation of safety message in congestion situation. It is important to allocate channel for safety message in congestion situation, but providing suitable service is also important problem in vehicular network. For this reason, IEEE 1609.4 allocate 4 multiple service channels (SCHs) for non-safety data transfer. But, in congestion situation with many vehicles, the contention for channel acquisition between services becomes more severe. So services are provided improperly because of lack of service channel. This paper suggests dynamic channel allocation algorithm. The proposed algorithm is that RSU(RaodSide Unit) maintain and manage the information about service and status of channels. On based of the SJF(Shortest Job First) scheduling using those information, RSU selects the most appropriate channel among the 4 SCHs allocated by IEEE 1609.4 in network congestion situation.

• Journal of Korean Society of Transportation
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• v.21 no.5
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• pp.19-29
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• 2003

The purpose of this study is to analyse the effect of the parking information on the waiting time using the simulation method. Stated Preference survey has been implemented to construct the parking lot choice model. A queue simulation is carried out to investigate the effect of various parking information on the waiting time. The results show that providing parking information is likely to increase the utilization of parking place and to decease the waiting time of individual vehicle. Furthermore, as the parking demand increases, the detailed and quantitative parking information such as "5 minutes delay" is more effective than qualitative parking information such as "available".