• International Journal of Computer Science & Network Security
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• v.23 no.11
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• pp.67-72
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• 2023

In the past decade, Autonomous Vehicle Systems (AVS) have advanced at an exponential rate, particularly due to improvements in artificial intelligence, which have had a significant impact on social as well as road safety and the future of transportation systems. The fusion of light detection and ranging (LiDAR) and camera data in real-time is known to be a crucial process in many applications, such as in autonomous driving, industrial automation and robotics. Especially in the case of autonomous vehicles, the efficient fusion of data from these two types of sensors is important to enabling the depth of objects as well as the classification of objects at short and long distances. This paper presents classification of objects using CNN based vision and Light Detection and Ranging (LIDAR) fusion in autonomous vehicles in the environment. This method is based on convolutional neural network (CNN) and image up sampling theory. By creating a point cloud of LIDAR data up sampling and converting into pixel-level depth information, depth information is connected with Red Green Blue data and fed into a deep CNN. The proposed method can obtain informative feature representation for object classification in autonomous vehicle environment using the integrated vision and LIDAR data. This method is adopted to guarantee both object classification accuracy and minimal loss. Experimental results show the effectiveness and efficiency of presented approach for objects classification.

• International Journal of Highway Engineering
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• v.9 no.4
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• pp.21-32
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• 2007

The linear traffic model(Vertical queueing model) that is adopted widely in traffic flow estimation assumes that all vehicles have the identical motion before joining a queue at the stop-line. Thus, a queue is supposed to form vertically not horizontally. Due to the simplicity of this model, the departure time of the leading vehicle is assumed to coincide with the start of effective green time. Thus, the delay estimates given by the Vertical queueing model is not always realistic. This paper explores a microscopic traffic model(a Kinematic Car-following model at Signalised intersections: a KCS traffic model) based on the one dimensional Kinematic equations in physics. A comparative evaluation in delay and sensitivity of delay difference between the KCS traffic model and the previously known Vertical queueing model is presented. The results show that the delay estimate in the Vertical queueing model is always greater than or equal to the KCS traffic model; however, the sensitivity of delay in the KCS traffic model is greater than the Vertical queueing model.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.22 no.1
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• pp.61-72
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• 2019

With the diversification of research using UAV(Unmanned Aerial Vehicle)s, the possibility of remote sensing research for urban green spaces is increasing. UAVs can be used as an investigation method to monitor the successful construction of the park and the planting of vegetation since its creation. This study was carried out to investigate UAVs utilization of urban green space monitoring in Dosol Square. It was photographed three times on May 21, July 13, and September 16, 2018 using DJI Phantom3 pro, Inspire2, and Parrot Sequoia multispectral camera. Orthographic images were overlaid on the planting plan of the site and the construction results were checked, the change of vitality of the plantation area was analyzed by NDVI(Normalized Difference Vegetation Index) and SAVI(Soil Adjusted Vegetation Index). As a result, it was confirmed that the UAVs are very effective for surveying the view of the urban green space after the construction and recording the results, which can be grasped quantitatively by overlaying the planting plan map. UAVs are more likely to be used in terms of monitoring vegetation vitality. It is interpreted that SAVI is better than NDVI in the green space just after composition. Chionanthus retusus and Pinus strobus were analyzed for their low level of vitality, and partially damaged and their vitality was lowered. In addition, there was difficulty in grass planting area and flower garden due to drainage and summer drought problems. In the future, it is expected that orthoimage and multispectral data using UAVs will be useful in the early vegetation monitoring and management field of urban green spaces.

• Journal of the Korean Institute of Intelligent Systems
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• v.11 no.5
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• pp.379-387
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• 2001

We proposed an enhanced extraction method of vehicle plate, in which both the brightness variation of gray and the Hue value of HSI color model were used. For the extraction of the vehicle plate from a vehicle image, first of all, candidate regions for the vehicle plate were extracted from the image by using the property of brightness variation of the image. A real place region was determined among candidate regions by the density of pixels with the Hue value of green and white. For- extracting the feature area containing characters from the extracted vehicle plate, we used the histogram-based approach of individual characters. And we proposed and applied for the recognition of characters the enhanced ART2 algorithm which support the dynamical establishment of the vigilance threshold with the genera]iced union operator of Yager. In addition, we propose an enhanced SOSL algorithm which is integrated both enhanced ART2 and supervised learning methods. The performance evaluation was performed using 100's real vehicle images and the evaluation results demonstrated that the extraction rates of tole proposed extraction method were improved, compared with that of previous methods based un brightness variation, RGB and HSI individually . Furthermore, the recognition rates of the proposed algorithms were improved much more than that of the conventional ART2 and BP algorithms.

• Journal of Korean Society of Transportation
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• v.31 no.6
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• pp.90-105
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• 2013

There are lots of variations on speed, acceleration and engine power during vehicle driving. It is well known that Green House Gas emissions by these dynamic driving properties are not precisely estimated by the average speed based emission estimation model which has been currently used in Korea. MOVES are selected as an appropriate transferable model among Micro-level emission estimation models. Based on MOVES, a novel emission estimation model can be used in Korea is developed. In this model, MOVES concept of emission estimation method and the MOVES method of estimating the Micro-level emission rate map is adopted. The results from the proposed model were compared with those from the average speed based emission model. The comparison results show the estimated base emission maps are good to be applied in Korea, but needed to be adjusted to consider the vehicle size differences between the two countries. Therefore, the factors for calibrating vehicle size difference were calculated and applied to acquired the micro-level emission maps for the Korean standard vehicle types.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.17 no.2
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• pp.113-127
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• 2018

This study develops a fusion priority signal control algorithm to pass without delay in emergency events. Fusion priority signal control is method combined center control with local control. The center control method applies signal times for each signalized intersection on the emergency vehicle's route when an emergency call is received. As signals are controlled before the emergency vehicle leaves for its destination, it is possible to clear the queues at each intersection more effectively. However, since the traffic information (speed, position) of the real-time emergency vehicle is not used, the intersection arrival time predicted by center control and actual arrival time of the emergency vehicle may be different from each other. In the case, it is possible to experience a delay caused by the signal. Local control method operate priority signal use the real-time information of EV, but there is a limitation that queue elimination time can not be reflected. In this study, fusion(center+local) control algorithm is proposed to compensate the disadvantages of center and local control also maximizing its advantages. Proposed algorithm is expected to decrease delay time of EV in emergency situation.

• Proceedings of the Korean Vacuum Society Conference
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• 2015.08a
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• pp.84.2-84.2
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• 2015

Growing market of electric vehicles such as hybrid, plug-in hybrid, and bare electric vehicles in the world is accelerating the significance of Li-ion batteries as a renewable green energy. According to such market flow, the developing components such as cathode, anode, electrolyte, and separator, composing the Li-ion batteries, is significantly important tasks for the commercialization. In particular, development of the cathode material having high capacity and stable thermal stability is essential for long-distance electric vehicle in the near future. Herein we introduce various applications of Li-ion batteries such as portable electronics, electric vehicles, and energy storage system, and also its research trend, in particular on the cathode materials.

• Transactions of the Korean Society of Automotive Engineers
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• v.20 no.6
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• pp.67-72
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• 2012

Novel Front End Module(FEM) with improved pedestrian protection is very important to reduce the severity of pedestrian injury. The FEM needs to have enough space from hood to absorb the energy from any pedestrian collision. In this study, the cooling performance of the FEM to cool the engine was investigated under 25% height reduction. The results indicated that the cooling performance analysis was about 86% level compared to that of the conventional FEM. Also, good qualitative agreement between CFD predictions and experimental measurements was found. This FEM needs the cooling performance enhancement for changed air flow path at the frontal part of vehicle. Therefore, we showed an improved performance using air guide setup and shape modification under the high load condition.

• Transactions of the Korean Society of Automotive Engineers
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• v.22 no.5
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• pp.29-34
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• 2014

Cooling the in-wheel motor in electric vehicles is critical to its performance and durability. In this study, thermal flow analysis was conducted by evaluating the thermal performance of two conventional cooling models for in-wheel motors under the continuous rating base speed condition. For conventional model #1, in which cooling oil was stagnant in the lower end of the motor, the maximum temperature of the coil was $221.7^{\circ}C$; for conventional model #2, in which cooling oil was circulated through the exit and entrance of the housing and jig, the maximum temperature of the coil was $155.4^{\circ}C$. Therefore, both models proved unsuitable for in-wheel motors since the motor control specifications limited the maximum temperature to $150^{\circ}C$.

• Transactions of the Korean Society of Automotive Engineers
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• v.21 no.4
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• pp.120-127
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• 2013

Hybrid electric vehicles have applied electric parts for saving fuel consumption and reducing levels of environmental pollution. Electrification of automobiles is indispensable for entering into global market because of enhanced environment restriction. ISG (Integrated Starter & Generator) system is one of main electric parts and can improve fuel efficiency more than other components by using Idle Stop & Go function and regenerative braking system. However, if ISG motor and inverter work under the continuously high load condition, it will make them the decrease of performance and durability. So the ISG motor and inverter need to properly design the cooling system of them. In this study, we suggested the enhancement points by modifying the thermal design of ISG motor and then confirmed the improvement of the cooling performance.