• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.19 no.2
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• pp.18-35
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• 2020

Many human, roadway, and vehicle factors affect vehicle-pedestrian crashes. Especially, the roadway factors are easily defined and suitable for suggesting countermeasures. The characteristics of the road network are one of the roadway factors. The road network significantly influences behaviors and conflicts of drivers and pedestrians. A metropolitan city such as Seoul contains various types of road networks, and crash prevention strategy considering characteristics of the road network is required. In this study, we analyze the effects of road networks on vehicle-pedestrian crashes. In the study, high order road ratio, intersection ratio, high-low intersection ratio are considered as road network variables. Using Geographically Weighted Poisson Regression, crash frequencies in Dongs of Seoul are analyzed based on the road network variable as well as socioeconomic variables. As a result, Dongs are grouped by coefficient signs, and each group is suggested about improvement directions considering conflict situations.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.18 no.6
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• pp.110-123
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• 2019

Traffic data is the most basic element necessary for transportation planning and traffic system operation. Recently, a method of estimating traffic flow characteristics using distance to a leading vehicle measured by an ADAS camera has been attempted. This study investigated the feasibility of the ADAS vehicle reflecting the distance error of image-based vehicle identification technology as a means to estimate the traffic flow through the normalized root mean square error (NRMSE) based on the number of lanes, traffic demand, penetration rate of probe vehicle, and time-space estimation area by employing the microscopic simulation model, VISSIM. As a result, the estimate of low density traffic flow (i.e., LOS A, LOS B) is unreliable due to the limitation of the maximum identification distance of ADAS camera. Although the reliability of the estimates can be improved if multiple lanes, high traffic demands, and high penetration rates are implemented, artificially raising the penetration rates is unrealistic. Their reliability can be improved by extending the time dimension of the estimation area as well, but the most influential one is the driving behavior of the ADAS vehicle. In conclusion, although it is not possible to accurately estimate the traffic flow with the ADAS camera, its applicability will be expanded by improving its performance and functions.

• Journal of Korea Spatial Information System Society
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• v.10 no.3
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• pp.31-43
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• 2008

Travel time prediction is an indispensable to many advanced traveler information systems(ATIS) and intelligent transportation systems(ITS). In this paper we propose a method to predict travel time using $Na{\ddot{i}}ve$ Bayesian classification method which has exhibited high accuracy and processing speed when applied to classily large amounts of data. Our proposed prediction algorithm is also scalable to road networks with arbitrary travel routes. For a given route, we consider time-varying average segment velocity to perform more accuracy of travel time prediction. We compare the proposed method with the existing prediction algorithms like link-based prediction algorithm [1] and Micro T* algorithm [2]. It is shown from the performance comparison that the proposed predictor can reduce MARE (mean absolute relative error) significantly, compared with the existing predictors.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.11 no.4
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• pp.19-33
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• 2012

Ministry of Land, Transport and Maritime Affairs prepared the method to update traffic connection system by amending "National Transport System Efficiency Act(hereinafter Act)". The key is a development of Intermodal Transfer Center. The law and guideline related with Intermodal Transfer Center requires the installation and operation of transfer information guide facility to improve user's convenience. However, there are no sufficient studies that can be used as references for the method to construct transfer support information system related with user's preference. The study performed the research about user's service satisfaction in relation with transfer support information service, which was embodied in model operation process, on the basis of transfer support information system of Intermodal Transfer Center applied to Gimpo Airport. The analysis result about service preference, importance of each supplied information, service satisfaction and consideration for service embodiment can be used as a guideline to embody the user information service of Intermodal Transfer Center. In addition, through CVM, the study estimated and proposed the service valuation of smart intermodal transfer service that provides customized information to cope with user's situation and traffic means operation status among transfer support information service. It is determined that the study will measure the benefit of Intermodal Transfer Center user by using monetary value when smart intermodal transfer service is supplied and provide the ground to expand high-tech transfer information service with high usefulness and convenience.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.19 no.6
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• pp.208-221
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• 2020

The objective of this study is to estimate and analyze the traffic density of continuous flow using the trajectory of individual vehicles and the headway of sample probe vehicles-front vehicles obtained from ADAS (Advanced Driver Assitance System) installed in sample probe vehicles. In the past, traffic density of continuous traffic flow was mainly estimated by processing data such as traffic volume, speed, and share collected from Vehicle Detection System, or by counting the number of vehicles directly using video information such as CCTV. This method showed the limitation of spatial limitations in estimating traffic density, and low reliability of estimation in the event of traffic congestion. To overcome the limitations of prior research, In this study, individual vehicle trajectory data and vehicle headway information collected from ADAS are used to detect the space on the road and to estimate the spatiotemporal traffic density using the Generalized Density formula. As a result, an analysis of the accuracy of the traffic density estimates according to the sampling rate of ADAS vehicles showed that the expected sampling rate of 30% was approximately 90% consistent with the actual traffic density. This study contribute to efficient traffic operation management by estimating reliable traffic density in road situations where ADAS and autonomous vehicles are mixed.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.19 no.6
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• pp.144-151
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• 2020

The number of drones used in various fields expected to 50,000 commercial drones by 2026. is to purchase business liability insurance only for commercial drones, as the scope of use of drones expands, it necessary to improve the drone insurance system, which imposes legal obligations aircraft duties. In particular, due to the diversification of aircraft characteristics of drones, an insurance system according to the degree of risk is required. To this end, a survey on the current status of drone operation in Korea, a review of documents related to drone insurance at home and abroad, collection and analysis of drone-related data, insurance systems for each transportation method, and analysis of data on overseas drone insurance products. o derive an improvement plan for the drone insurance system for drone insurance by aircraft characteristics and operation missions, and establish insurance standards by aircraft characteristics and operation missions, derive implications through required insurance surveys by sector such as users, users, and insurance companies. Detailed insurance standards were established by calculating the degree of risk according to the physical characteristics of the aircraft, and the liability for damage according to the operation mission was specified.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.6 no.2
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• pp.480-497
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• 2012

As a new business concept, machine-to-machine (M2M) communications are born from original telemetry technology with the intrinsic features of automatic data transmissions and measurement from remote sources typically by cable or radio. M2M includes a number of technologies that need to be combined in a compatible manner to enable its deployment over a broad market of consumer electronics. In order to provide better understanding for this emerging concept, the correlations among M2M, wireless sensor networks, cyber-physical systems (CPS), and internet of things are first analyzed in this paper. Then, the basic M2M architecture is introduced and the key elements of the architecture are presented. Furthermore, the progress of global M2M standardization is reviewed, and some representative applications (i.e., smart home, smart grid and health care) are given to show that the M2M technologies are gradually utilized to benefit people's life. Finally, a novel M2M system integrating intelligent road with unmanned vehicle is proposed in the form of CPS, and an example of cyber-transportation systems for improving road safety and efficiency are introduced.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2010.05a
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• pp.927-930
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• 2010

Recently, continuous k-nearest neighbor query(CkNN) which is defined as a query to find the nearest points of interest to all the points on a given path is widely used in the LBS(Location Based Service) and ITS(Intelligent Transportation System) applications. It is necessary to acquire results quickly in the above applications and be applicable to spatial network databases. This paper proposes a new method to search nearest POIs(Point Of Interest) for moving query objects on the spatial networks. The method produces a set of split points and their corresponding k-POIs as results. There is no order between the POIs. The analysis show that the proposed method outperforms the existing methods.

• Journal of Korea Society of Digital Industry and Information Management
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• v.18 no.4
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• pp.23-30
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• 2022

Recently, traffic congestion and environmental pollution have occurred due to population concentration and vehicle increase in large cities. Various studies are being conducted to solve these problems. Most of the traffic congestion in cities is caused by traffic signals at intersections. This paper proposes a dynamic traffic light control (DTLC) scheme to support safe vehicle operation and smooth traffic flow using real-time traffic information based on VANET. DTLC receives instantaneous speed and directional information of each vehicle through road side units (RSUs) to obtain the density and average speed of vehicles for each direction. RSUs deliver this information to traffic light controllers (TLCs), which utilize it to dynamically control traffic lights at intersections. To demonstrate the validity of DTLC, simulations were performed on average driving speed and average waiting time using the ns-2 simulator. Simulation results show that DTLC can provide smooth traffic flow by increasing average driving speed at dense intersections and reducing average waiting time.

• Journal of Korea Society of Digital Industry and Information Management
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• v.18 no.4
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• pp.1-11
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• 2022

Recently, research on license plate recognition, which is a core technology of an intelligent transportation system(ITS), is being actively conducted. In this paper, we propose a method to extract numbers and characters from low-quality license plate images by applying the YOLOv4 algorithm. YOLOv4 is a one-stage object detection method using convolution neural network including BACKBONE, NECK, and HEAD parts. It is a method of detecting objects in real time rather than the previous two-stage object detection method such as the faster R-CNN. In this paper, we studied a method to directly extract number and character regions from low-quality license plate images without additional edge detection and image segmentation processes. In order to evaluate the performance of the proposed method we experimented with 500 license plate images. In this experiment, 350 images were used for training and the remaining 150 images were used for the testing process. Computer simulations show that the mean average precision of detecting number and character regions on vehicle license plates was about 93.8%.