• ETRI Journal
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• 제45권6호
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• pp.1065-1078
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• 2023

In vehicular networks, diverse safety information can be shared among vehicles through internet connections. In vehicle-to-internet communications, vehicles on the road are wirelessly connected to different cloud networks, thereby accelerating safety information exchange. Onboard sensors acquire traffic-related information, and reliable intermediate nodes and network services, such as navigational facilities, allow to transmit safety information to distant target vehicles and stations. Using vehicle-to-network communications, we minimize delays and achieve high accuracy through consistent connectivity links. Our proposed approach uses intermediate nodes with two-hop separation to forward information. Target vehicle detection and routing of safety information are performed using machine learning algorithms. Compared with existing vehicle-to-internet solutions, our approach provides substantial improvements by reducing latency, packet drop, and overhead.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제14권5호
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• pp.2171-2185
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• 2020

In order to judge that whether the vehicles in different images which are captured by surveillance cameras represent the same vehicle or not, we proposed a novel vehicle face recognition algorithm based on improved Nonnegative Matrix Factorization (NMF), different from traditional vehicle recognition algorithms, there are fewer effective features in vehicle face image than in whole vehicle image in general, which brings certain difficulty to recognition. The innovations mainly include the following two aspects: 1) we proposed a novel idea that the vehicle type can be determined by a few key regions of the vehicle face such as logo, grille and so on; 2) Through adding weight, sparseness and classification property constraints to the NMF model, we can acquire the effective feature bases that represent the key regions of vehicle face image. Experimental results show that the proposed algorithm not only achieve a high correct recognition rate, but also has a strong robustness to some non-cooperative factors such as illumination variation.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제18권6호
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• pp.1462-1477
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• 2024

With the evolving complexity of connected vehicle features, the volume and diversity of data generated during driving continue to escalate. Enabling data sharing among interconnected vehicles holds promise for improving users' driving experiences and alleviating traffic congestion. Yet, the unintentional disclosure of users' private information through data sharing poses a risk, potentially compromising the interests of vehicle users and, in certain cases, endangering driving safety. Federated learning (FL) is a newly emerged distributed machine learning paradigm, which is expected to play a prominent role for privacy-preserving learning in autonomous vehicles. While FL holds significant potential to enhance the architecture of the Internet of Vehicles (IoV), the dynamic mobility of vehicles poses a considerable challenge to integrating FL with vehicular networks. In this paper, a novel clustered FL framework is proposed which is efficient for reducing communication and protecting data privacy. By assessing the similarity among feature vectors, vehicles are categorized into distinct clusters. An optimal vehicle is elected as the cluster head, which enhances the efficiency of personalized data processing and model training while reducing communication overhead. Simultaneously, the Local Differential Privacy (LDP) mechanism is incorporated during local training to safeguard vehicle privacy. The simulation results obtained from the 20newsgroups dataset and the MNIST dataset validate the effectiveness of the proposed scheme, indicating that the proposed scheme can ensure data privacy effectively while reducing communication overhead.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제5권5호
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• pp.874-887
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• 2011

Compared to nomadic and fixed relay stations, vehicle-mounted mobile relay stations show different characteristics caused by the time-variant topology, due to their mobility. Especially, a relay mounted in a vehicle is differentiated from nomadic or fixed relay by the restricted distance between the relay and associated mobile station and the variable density of relay deployment in a cell. In this paper, we identify the characteristics of vehicle-mounted mobile relay stations and provide some parameters that highly influence the performance of vehicle-mounted relay. Through simulation, we measure the effect of relay density, zone ratio, relay transmission power, and frame transmission mode on the performance of vehicle-mounted relay. The results show that the performance of vehicle-mounted relay is highly susceptible to the above vehicle-mounted relay-specific parameters.

• Journal of Information Processing Systems
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• 제19권5호
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• pp.663-672
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• 2023

Most vehicle detection methods have poor vehicle feature extraction performance at night, and their robustness is reduced; hence, this study proposes a night vehicle detection method based on style transfer image enhancement. First, a style transfer model is constructed using cycle generative adversarial networks (cycleGANs). The daytime data in the BDD100K dataset were converted into nighttime data to form a style dataset. The dataset was then divided using its labels. Finally, based on a YOLOv5s network, a nighttime vehicle image is detected for the reliable recognition of vehicle information in a complex environment. The experimental results of the proposed method based on the BDD100K dataset show that the transferred night vehicle images are clear and meet the requirements. The precision, recall, mAP@.5, and mAP@.5:.95 reached 0.696, 0.292, 0.761, and 0.454, respectively.

• 인터넷정보학회논문지
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• 제6권3호
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• pp.147-158
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• 2005

나날이 심각해지는 교통문제에서 차량에 대한 정보를 이용하여 교통흐름을 개선해 줄 뿐만 아니라, 교통위반 차량을 효율적으로 적발할 수 있다. 차량 번호판은 차량정보를 인식하는데 중요하게 사용될 수 있다. 본 논문에서는 이동식 형태인 차량에 탑재한 카메라를 이용하여 촬영한 영상에서 차량의 번호판을 인식하는 새로운 기법을 제안한다. 여러 단계의 영상처리 과정과 인식 과정을 거쳐서 실시간에 처리할 수 있는 시스템으로 일반 차량뿐 아니라 특장차에 대한 인식도 가능하게 한다. 제안한 기법을 이용한 실제적 환경에서의 영상과 인식에 대한 결과가 실험결과에서 보여진다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제13권4호
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• pp.1795-1811
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• 2019

In order to achieve rapid and accurate detection of vehicle objects in complex traffic conditions, we propose a novel vehicle detection method. Firstly, more contextual and small-object vehicle information can be obtained by our Joint Feature Network (JFN). Secondly, our Evolved Region Proposal Network (EPRN) generates initial anchor boxes by adding an improved version of the region proposal network in this network, and at the same time filters out a large number of false vehicle boxes by soft-Non Maximum Suppression (NMS). Then, our Mask Network (MaskN) generates an example that includes the vehicle occlusion, the generator and discriminator can learn from each other in order to further improve the vehicle object detection capability. Finally, these candidate vehicle detection boxes are optimized to obtain the final vehicle detection boxes by the Fine-Tuning Network(FTN). Through the evaluation experiment on the DETRAC benchmark dataset, we find that in terms of mAP, our method exceeds Faster-RCNN by 11.15%, YOLO by 11.88%, and EB by 1.64%. Besides, our algorithm also has achieved top2 comaring with MS-CNN, YOLO-v3, RefineNet, RetinaNet, Faster-rcnn, DSSD and YOLO-v2 of vehicle category in KITTI dataset.

• International Journal of Internet, Broadcasting and Communication
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• 제7권2호
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• pp.113-116
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• 2015

Generally, in the railway vehicle the driving force of gravity happens by the high-speed running and the repetitive impulse cause the degradation and the malfunction phenomenon shows differently because the durability of each component changes according to the internal and external causes. The maintenance of propulsion control device which is played the very important role as to the stable service of the railway vehicle is greatly important among them. Therefore maintenance training propulsion control device simulator is needed to maximize learning through repetition and improve the maintenance practical skills training. This paper designed the railway vehicle running device with a miniature for the railway vehicle maintenance training and developed a propulsion control device simulator equipped the imitation steering wheel.

• 대한기계학회:학술대회논문집
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• 대한기계학회 2003년도 춘계학술대회
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• pp.1205-1211
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• 2003

Having information is most important at the present age. Internet is main source of obtaining information and mobile telecommunication let people communicate each other without any time and space limitation. Recently, advanced technology in telecommunication makes two-way service possible. So, the mobile internet service combined internet with mobile telecommunication is widely and rapidly promoted. Therefore user can transmit and receive a lot of information without time and space restriction using various application technologies. This paper deals with machinery that makes human do office work conveniently in vehicle using mobile internet service. Namely, it tries to design mobile internet machinery combining of wireless payment, GPS module, mobile internet, and mobile office etc. And that can transmit and receive e-mail or documents etc. This machinery has various objects, and design process has complexity. To reduce trial error and processing complexity, Axiomatic Design Method is used to design the machinery.

• ETRI Journal
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• 제37권5호
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• pp.867-876
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• 2015

This paper proposes an efficient interference control scheme for vehicular moving networks. The features of the proposed scheme are as follows: radio resources are separated into two resource groups to avoid interference between the cellular and vehicle-to-vehicle (V2V) links; V2V links are able to share the same radio resources for an improvement in the resource efficiency; and vehicles can adaptively adjust their transmission power according to the interference among the V2V links (based on the distributed power control (DPC) scheme derived using the network utility maximization method). The DPC scheme, which is the main feature of the proposed scheme, can improve both the reliability and data rate of a V2V link. Simulation results show that the DPC scheme improves the average signal-to-interference-plus-noise ratio of V2V links by more than 4 dB, and the sum data rate of the V2V links by 15% and 137% compared with conventional schemes.