• Journal of the Korea Institute of Information and Communication Engineering
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• v.18 no.8
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• pp.1885-1894
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• 2014

There are various high-performance algorithms in the area of the existing VDSs (vehicle detection systems). However, they requires a large amount of computational time-complexity and their systems generally are very expensive and consumes high-power. This paper proposes real-time traffic information detection algorithm that can be applied to low-cost, low-power, and open development platform such as Android. This algorithm uses a vehicle's sub-shadow to set ROI(region of interest) and to count vehicles using a location of the sub-shadow and the vehicle. The proposed algorithm is able to count the vehicles per each roads and each directions separately. The experiment result show that the detection rate for going-up vehicles is 94.1% and that for going-down vehicles is 97.1%. These results are close to or surpasses 95%, the detection rate of commercial loop detectors.

• Journal of the Korea Convergence Society
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• v.10 no.11
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• pp.95-100
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• 2019

In this paper, autonomous vehicles of service with existing vehicle accident for the prevention of the vehicle communication technology, self-driving techniques, brakes automatic control technology, artificial intelligence technologies such as well and developed the vehicle accident this occur to death or has been techniques, can prepare various safety cases intended to minimize the injury. In this paper, it is a study to secure safety in autonomous vehicles. This is determined according to spatial factors such as chip signals for general low-power short-range wireless communication and micro road AI. On the other hand, in this paper, the safety of boarding is improved by checking the signal from the electronic chip, up to "recognition of the emotion from residence time in the sensing area" to the biological electronic chip. As a result of demonstrating the reliability of the world countries the world, inducing safety autonomous system of all passengers in terms of safety. Unmanned autonomous vehicle riding and commercialization will lead to AI systems and biochips (Verification), linked IoT on the road in the near future, and the safety technology reliability of the world will be highlighted.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.9
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• pp.1166-1175
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• 2021

We investigate the current situation and development trend of domestic smart city and emergency vehicle priority signal control system analyzing the existing effectiveness of 1) emergency vehicle priority signal control system and 2) control emergency vehicle priority signal, based on domestic and foreign prior research for signal control system security. The effectiveness of time reduction was analyzed through actual application and test operation to emergency vehicles after establishing the system. In addition, for security management and stable service of real-time signal system control we propose improvement for the technical control items of the ISMS-P certification system to secure golden time to protect citizens' precious lives and property in case of emergency by classifying and mapping the existing ISMS-P certification system and the Korea Internet & Security Agency's cyber security guide according to the items of security threats.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.19 no.3
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• pp.105-114
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• 2019

As the Industrial Revolution progressed, Big Data technologies were used to develop a system that instantly identified the consequences of older vehicles using mobile devices. First, data from the vehicle was collected using the OBD2 sensor, and the data collected was stored in the raspberry pie, giving it the same situation that the raspberry pie was driving. In the event that vehicle data is generated, the data is collected in real time, stored in multiple nodes, and visualized and printed based on the processed, refined, processed and processed data. We can use Big Data in this process and quickly process vehicle data to identify it effectively through mobile devices.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.4
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• pp.467-473
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• 2020

Recently, the number of traffic accidents has also increased with the increase in the penetration rate of cars in Korea. In particular, not only inter-vehicle accidents but also human accidents near crosswalks are increasing, so that more attention to traffic safety around crosswalks are required. In this paper, we propose a system for predicting the safety level around the crosswalk by recognizing an approaching vehicle and estimating the speed of the vehicle using NVIDIA Jetson Nano-class edge devices. To this end, various machine learning models are trained with the information obtained from deep learning-based vehicle detection to predict the degree of risk according to the speed of an approaching vehicle. Finally, based on experiments using actual driving images and web simulation, the performance and the feasibility of the proposed system are validated.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.12
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• pp.1794-1799
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• 2022

Recently, the increasing number of overloaded vehicles on the road poses a risk to traffic safety, such as falling objects, road damage, and chain collisions due to the abnormal weight distribution, and can cause great damage once an accident occurs. therefore we propose to build an object detection-based AI model to identify overloaded vehicles that cause such social problems. In addition, we present a simple yet effective method to construct an object detection model for the large-scale vehicle images. In particular, we utilize the large-scale of vehicle image sets provided by open AI-Hub, which include the overloaded vehicles. We inspected the specific features of sizes of vehicles and types of image sources, and pre-processed these images to train a deep learning-based object detection model. Also, we propose an integrated system for tracking the detected vehicles. Finally, we demonstrated that the detection performance of the overloaded vehicle was improved by about 23% compared to the one using raw data.

• Information and Communications Magazine
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• v.33 no.4
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• pp.27-33
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• 2016

자율 주행(스마트) 자동차는 첨단 IT기술을 이용하여 사람의 개입을 줄여서 운행하는 자동차를 말한다. 자율 주행(스마트) 자동차는 자율적으로 차량 주변 환경 및 상황을 판단하여 정해진 목적지까지 안전하게 이동하는 차량을 의미한다. 자율 주행(스마트) 자동차는 주행 안전성과 운전자의 편의성을 향상시키기 위한 연구 형태로 주로 이루어지고 있다. 자율 주행(스마트) 자동차 기술은 자율 주행의 정도를 적용하여 단계별로 개발이 진행될 것으로 보인다. 자율 주행 자동차 기술은 인간 세상에 또 다른 변혁을 몰고 오고 있다. 자율 주행 자동차와 관련한 기술은 첨단 IT기술을 기계 자동차에 접목하는 것인데, 적용하는 IT 기술은 HW, SW기술로 나눌 수 있다. IT HW 기술로는 환경 인식에 필요한 HW, 위치 인식 HW, 판단/제어를 위한 여러가지 센서 HW 등이 있다. IT SW 기술로는 IT HW를 구동하기 위한 실시간 OS, IT HW 전장장치를 구동할 수 있는 여러가지 SW 관련 기술, 자율 주행을 위한 경로 알고리즘 등이 있다. 본 고에서는 자율 주행 자동차에 적용되는 IT SW 기술 중심으로 살펴본다.

• Proceedings of the Korea Information Processing Society Conference
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• 2017.11a
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• pp.126-127
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• 2017

사물인터넷 산업이 발전함으로써 차량 간의 통신이 주목 받고 있다. 네트워크 연결이 빈번하게 끊어지는 자동차 사이에서 무선으로 통신을 하기 위한 네트워킹에 대해 알아본다. 이를 위하여 차량이 노드 역할을 하는 VANET 환경에서 CCN을 적용하여 Data Packet 수를 살펴보았다.

• Proceedings of the Korea Multimedia Society Conference
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• 2012.05a
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• pp.234-235
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• 2012

본 논문에서는 개미 집단 최적화(Ant Colony Optimization, ACO) 알고리즘을 적용한 감속률에 따른 동적 상황인식 경로 선정 방법을 제안한다. 최근 ITS(Intelligent Transportation Systems)의 개발과 함께 차량용 내비게이션의 실시간 교통 정보를 이용하는 수요가 급증하면서, 경로탐색의 중요성이 더욱 가속화되고 있다. 현재 차량용 내비게이션은 멀티미디어 및 정보통신 기술의 결합과 함께 다양한 기능 및 정보를 사용자에게 제공하고 있으며, 이러한 경로탐색 알고리즘은 교통시스템, 통신 네트워크, 운송 시스템 등 다양한 분야에 적용되고 있다. 본 논문에서는 감속률에 따른 동적 상황인식 경로 선정 방법을 제안함으로써, 최단 시간 및 최소 비용의 정보를 제공해 줄 뿐만 아니라 교통정체로 인한 사회적 비용 감소의 효과를 가져다 줄 것으로 기대한다.

• Electronics and Telecommunications Trends
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• v.26 no.6
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• pp.47-57
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• 2011

DARPA 무인차 대회 우승과 구글 자율주행 자동차로 유명한 세바스찬 스런 스탠포드대 교수는 18살이 되던 해에 가장 친한 친구를 교통사고로 잃었고, 그것을 계기로 계기로 무인차 개발에 나서게 되었다고 한다. 현재 대부분의 교통사고는 운전자의 과실로 발생하며, 기계의 보조나 자동제어가 있다면 대부분 예방할 수 있다. 또한 자동으로 차선을 유지하고 차간거리를 유지하게 해준다면 도로의 교통 수용량을 2배 내지 3배로 높일 수 있으며, 도로에서 보내는 시간과 연료를 절약할 수 있다. 현재 지능형 자동차 및 도로 인프라 기술은 이러한 운전자의 안전성, 편의성, 교통 효율성, 에너지 절약을 달성하기 위한 자동차와 인프라 간의 협력형 ITS(C-ITS: cooperative ITS) 방향으로 기술개발이 이루어지고 있으며, 본 고에서는 이와 관련된 차량 자동유도 요소 기술 및 동향에 대해서 살펴본다.