• KSII Transactions on Internet and Information Systems (TIIS)
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• 제15권10호
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• pp.3858-3874
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• 2021

As an essential part of the urban transportation system, precise perception of the traffic flow parameters at the traffic signal intersection ensures traffic safety and fully improves the intersection's capacity. Traditional detection methods of road traffic flow parameter can be divided into the micro and the macro. The microscopic detection methods include geomagnetic induction coil technology, aerial detection technology based on the unmanned aerial vehicles (UAV) and camera video detection technology based on the fixed scene. The macroscopic detection methods include floating car data analysis technology. All the above methods have their advantages and disadvantages. Recently, indoor location methods based on wireless signals have attracted wide attention due to their applicability and low cost. This paper extends the wireless signal indoor location method to the outdoor intersection scene for traffic flow parameter estimation. In this paper, the detection scene is constructed at the intersection based on the received signal strength indication (RSSI) ranging technology extracted from the wireless signal. We extracted the RSSI data from the wireless signals sent to the road side unit (RSU) by the vehicle nodes, calibrated the RSSI ranging model, and finally obtained the traffic flow parameters of the intersection entrance road. We measured the average speed of traffic flow through multiple simulation experiments, the trajectory of traffic flow, and the spatiotemporal map at a single intersection inlet. Finally, we obtained the queue length of the inlet lane at the intersection. The simulation results of the experiment show that the RSSI ranging positioning method based on wireless signals can accurately estimate the traffic flow parameters at the intersection, which also provides a foundation for accurately estimating the traffic flow state in the future era of the Internet of Vehicles.

• 한국측량학회:학술대회논문집
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• 한국측량학회 2007년도 춘계학술발표회 논문집
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• pp.333-336
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• 2007

This paper is the environmental impact assessment of at road design in the light of the sense for the real from the virtual reality. For in this papers, This study developed 3D-model and virtual reality contents by suggesting the environmental impact assessment based on GIS in the road design. And, through this process, it's possible to visualize the environmental impact assessment by constructing the 3D-model and simulation. The 3D-model can be a method to show the road effectively by maximizing the road's shape visually after the construction. The main construction which composes polyhedron model that is generated from digital map and aerial photo is built by mapping the real texture, so the Sense for the Real was more heightened. Through this study, it must be made to shorten a long time exhausting period of conference and construct more real road after due scene consideration by specific and various low-cost strategy in the environmental impact assessment afterwards.

• 반도체디스플레이기술학회지
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• 제20권4호
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• pp.23-28
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• 2021

Augmented reality is a technique for combining virtual images into real life by showing information of virtual 3D objects on top of a real-world environment (Azuma et al., 2001). This study is an augmented reality-based educational content delivery device that receives user input that selects either a preset object or a photographed object for augmented reality-based training; It includes a three-dimensional design generation unit that generates a stereoscopic model of the augmented reality environment from an object, a three-dimensional view of the scene, a disassembly process of the developing road from a three-dimensional model, and a content control unit provided by the user terminal by generating educational content including a three-dimensional model, a scene chart, a scene, a decomposition process, and a coupling process to build a coupling process from the scene to the three-dimensional model in an augmented reality environment. The next study provides a variety of educational content so that children can use AR technology as well as shapes to improve learning effectiveness. We also believe that studies are needed to quantitatively measure the efficacy of which educational content is more effective when utilizing AR technology.

• 한국전기전자재료학회:학술대회논문집
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• 한국전기전자재료학회 2008년도 춘계학술대회 논문집 센서 박막재료연구회 및 광주 전남지부
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• pp.6-9
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• 2008

A 3D depth measurement system is proposed for mobile vehicles. Depth measurement system which is composed of a rotating mirror, a line laser and mono-camera is employed to detect depth, where the laser light is reflected by the mirror and projected to- the scene objects whose locations are to be determined. The obtained depth information is converted into an image. Such depth images of the road region represent even and plane while that of off-road region is irregular or textured. Road region is detected employing a simple spatial differentiation technique to detect the plain textured area. Identification results of the diverse situation of Non-linear trail are included in this paper.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2002년도 ICCAS
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• pp.98.3-98
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• 2002

Vision-based systems for finding road lanes have to operate robustly under a wide variety of environ-mental conditions including large amount of scene clutters. This paper presents a method for finding the lane boundaries by combining a local line extraction method and dynamic programming as a search tool. The line extractor obtains an initial position estimation of road lane boundaries from the noisy edge fragments. Dynamic programming then improves the initial approximation to an accurate configuration of lane boundaries. Input image frame is divided into a few sub-regions along the vertical direction. The local line extractor then performs to extract candidate lines of road lanes in the...

• 제어로봇시스템학회논문지
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• 제4권6호
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• pp.759-764
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• 1998

We propose a novel algorithm capable of recognizing the road lane by image processing. Considering the fact that the direction and location of road lane are maintained similarly in successive images we formulate a function to represent the property. However, as noises play the role of making a lot of similar patterns appear and disappear in the road image, keeping of robustness in the lane detection has been known a difficult work. To overcome this problem, we introduce the following three ideas: 1) design of a function based on an edge direction and magnitude, 2) construction of a recursive filter to estimate the function recursively for successive images, 3) principal axis-based line fitting. These concepts enhance the adaptability to cope with the random environment of traffic scene and eventually lead to the reliable detection of a road lane.

• 한국시뮬레이션학회:학술대회논문집
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• 한국시뮬레이션학회 1997년도 춘계 학술대회 발표집
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• pp.81-85
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• 1997

In a virtual environment, agents must demonstrate some degree of realism and interactivity. This paper discusses the algorithm that enables agents to navigate a virtual road network realistically and interactively. The road description files written in this language provide the information of road environments to the navigating agents and the scene visualizer. We call this navigating agent in the road an ambient car. The ambient cars must follow the traffic rules as human does. To do this, the ambient car should continuously check its circumstances, such as, the traffic lights, lanes, road signs, and other ambient cars. Because of the huge scale of road network and the large number of ambient cars, the algorithm considers only the area where the participant is currently located. By this locality, the performance of the whole system does not fluctuate much in different situations. The behavior of ambient cars according to the predefined rules may appear monotonous. We added probability distribution functions to introduce some randomness. We implemented the above idea on silicon Graphics Indigo 2 workstation. The ambient car exhibited its awareness of lanes, traffic lights, and other cars. The participants could hardly distinguish between a human-controlled car and computer-controlled ambient car generated by the algorithm.

• 한국전기전자재료학회:학술대회논문집
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• 한국전기전자재료학회 2007년도 하계학술대회 논문집 Vol.8
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• pp.517-518
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• 2007

A method to recognize unpaved road region using a 3D depth measurement system is proposed for mobile robots. For autonomous maneuvering of mobile robots, recognition of obstacles or recognition of road region is the essential task. In this paper, the 3D depth measurement system which is composed of a rotating mirror, a line laser and mono-camera is employed to detect depth, where the laser light is reflected by the mirror and projected to the scene objects whose locations are to be determined. The obtained depth information is converted into an image. Such depth images of the road region represent even and plane while that of off-road region is irregular or textured. Therefore, the problem falls into a texture identification problem. Road region is detected employing a simple spatial differentiation technique to detect the plain textured area. Identification results of the diverse situation of Nonlinear trail are included in this paper.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2000년도 추계종합학술대회 논문집(4)
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• pp.69-72
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• 2000

This study proposes a new calculation method for generating real nighttime lamp-lit images. In order to improve the color appearance in the prediction of a nighttime lamp-lighted scene, the lamp-lit image is synthesized based on spectral distribution using the estimated local spectral distribution of the headlamps and the surface reflectance of every object. The principal component analysis method is introduced to estimate the surface color of an object, and the local spectral distribution of the headlamps is calculated based on the illuminance data and spectral distribution of the illuminating headlamps. HID and halogen lamps are utilized to create beam patterns and captured road scenes are used as background images to simulate actual headlamp-lit images on a monitor. As a result, the reproduced images presented a color appearance that was very close to a real nighttime road image illuminated by single and multiple headlamps.

• 로봇학회논문지
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• 제12권3호
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• pp.249-257
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• 2017

This paper proposes a method to segment urban scenes semantically based on location prior information. Since major scene elements in urban environments such as roads, buildings, and vehicles are often located at specific locations, using the location prior information of these elements can improve the segmentation performance. The location priors are defined in special 2D coordinates, referred to as road-normal coordinates, which are perpendicular to the orientation of the road. With the help of depth information to each element, all the possible pixels in the image are projected into these coordinates and the learned prior information is applied to those pixels. The proposed location prior can be modeled by defining a unary potential of a conditional random field (CRF) as a sum of two sub-potentials: an appearance feature-based potential and a location potential. The proposed method was validated using publicly available KITTI dataset, which has urban images and corresponding 3D depth measurements.