Earticle

현재 IT기술과 자동차기술을 융합한 지능형 자동차에 대한 연구가 활발히 진행중에 있으며 많은 새로운 서비스 모델들이 개발중에 있다. 지능형자동차에 대한 개발이 활발하게 이루어지면서 무선 네트워크를 이용한 다양 한 서비스가 제공이 되고 있다. 이러한 지능형 자동차가 무선 네트워크를 이용한 서비스가 제동되면서 다양한 보안 위협 요소가 도출되고 있다. 본 논문에서는 지능형 자동차의 외부에서 네트워크에 침입하여 지능형자동차의 보안위 협 요소를 분석하고 지능형 자동차의 보안 솔루션의 인증 모델에 대한 기법을 제공하고자 한다. 인증 모델의 경우 신체의 고유성을 식별할 수 있는 생체인식을 이용한 인증기법을 제안한다.

Studies on the intelligent vehicles that are fused with IT and intelligent vehicle technologies are currently under active discussion. And many new service models for them are being developed. As intelligent vehicles are being actively developed, a variety of wireless services are support. As such intelligent vehicles use wireless network, they are exposed to the diverse sources of security risk. This paper aims to examine the factors to threaten intelligent vehicle, which are usually intruded through network system and propose the security solution using biometric authentication technique. The proposed security system employs biometric authentication technique model that can distinguish the physical characteristics of user.

IT와 융합한 지능형 자동차에 대한 연구가 현재 활발히 진행중이다. 안전한 지능형 자동차 서비스를 위해 다양한 통신 기술이 제공이 되고 있다. 지능형 자동차가 통신기술을 이용한 서비스가 제공되면서 다양한 보안위협 요소가 도출되고 있다. 지능형 자동차에서 보안 인증 솔루션을 위해서는 소유권, 지식, 생체정보를 포함하고 있어야 한다[6,7]. 본 논문에서는 지능형 자동차의 보안위협 요소를 분석하고 지능형 자동차의 보안 솔루션인 생체정보를 이용한 인증 기법을 제공한다. 기존의 지능형 자동차 인증보안 솔루션보다 높은 보안성을 갖는 구현의 문제점이 해결 되도록 사용자 생체인증기법을 제안한다.

Studies on the intelligent vehicles that are converged with IT and vehicular technologies are currently under active discussion. A variety of communication technologies for safety intelligent vehicle services are support. As such intelligent vehicles use communication technologies, they are exposed to the diverse factors of security threats. To conduct intelligent vehicle security authentication solutions, there are some factors that can be adopted ownership, knowledge and biometrics[6,7]. This paper proposes to analyze the factors to threaten intelligent vehicle, which are usually intruded through communication network system and the security solution using biometric authentication scheme. This study proposed above user's biometrics information-based authentication scheme that can solve the anticipated problems with an intelligent vehicle, which requires a higher level of security than existing authentication solution.

다양한 지능형 자동차의 통신 방법의 개발이 편안하고 안전한 정보를 전달해주고 있다. 하지만 이러한 통신 방법의 개발 또한 보안을 생각해야 한다. 지능형 자동차에서 사용될 내비게이션의 업데이트 또한 무선 업데이 트 방식을 사용하는데 현재 사용하고 있는 업데이트 방식은 신뢰할만한 보안 방식이 없는 실정이다. 자동차에 사용 되는 내비게이션 통신은 국가별로 다양한 방법으로 TTI 서비스를 제공하고 있으며, 우리나라의 경우에는 대부분 T-DMB를 이용하여 TPEG 방식으로 정보를 전송해주고 있다. 내비게이션 무선 업데이트에 대한 특성을 파악하고, 신뢰 할 수 있는 업데이트 정보 전송을 위해 공격 시나리오를 작성 한 뒤 그에 따른 보안 대책을 제안한다.

The development of communication method for a variety of intelligent automobiles are delivering comfortable and safe information. However the development of such communication method must also think about security. Even the update of navigation to be used for intelligent automobiles uses the wireless updating methods but the updating methods currently being used has no reliable security measures. The navigation communications used in the intelligent automobiles are being provided with TTI(Traffic and Travel Information) service using a variety of methods by the countries. In the case of Korea, most are based on T-DMB using the TPEG method for transmitting the information. By identifying the characteristics on the navigation wireless update, a security solution is proposed for delivering the reliable update information after creating the attack scenario.

정보통신기술 발전에 따라 많은 장치들간의 통신과 네트워킹의 수용이 이뤄지고 있다. 장치간의 통신을 위한 융합 사업이 빠르게 발전되어지고 있다. IT 융합 통신은 무선통신에서 차후 개척분야의 하나로 여겨지고 있다. 본 논문에서는 IT 융합 구조에서 M2M, 지능형 자동차, 스마트그리드, U-헬스케어에 대한 보안 위협요소를 분석하 였다. 임베디드 시스템 보안, 포렌식 보안, 사용자 인증과 키관리 기법에 대한 IT 융합 보안의 방향을 제안하였다.

As the developing of the information communication technology, more and more devices are with the capacity of communication and networking. The convergence businesses which communicate with the devices have been developing rapidly. The IT convergence communication is viewed as one of the next frontiers in wireless communications. In this paper, we analyze detailed security threats against M2M(Machine to Machine), intelligent vehicle, smart grid and u-Healthcare in IT convergence architecture. We proposed a direction of the IT convergence security that imbedded system security, forensic security, user authentication and key management scheme.

Localization modules play an important role in ensuring the secure operation of intelligent vehicles (IV) and accelerating the development of driving technologies. To safely drive an intelligent vehicle, an exact data registration is necessary. Map drift, scan-to-map alignment, high computational load, sensor noise, and calibration are the most prominent issues that cause poor localization performance for intelligent vehicles. Therefore, by presenting a digital twin-assisted data registration (DT-ADR) technique, this research attempts to mitigate that gap. The purpose of this study is to show how to implement the DT-ADR technique to help improve the existing light detection and ranging (LiDAR) data registration technique for more accurate vehicle localization and driving capabilities. We first investigate traditional data registration techniques that address the challenges for scan matching localization. We then present the proposed DT-ADR technique and discuss a pose selection technique. Next, we demonstrate an implementation of the proposed DT-ADR technique using AWSIM cosimulation, Autoware universe, and ROS2 virtual environments. To verify the effectiveness of the description of the localization approach, a case study is also conducted to analyze the pose estimation of IV. Lastly, an initial result is evaluated for the proposed DT-ADR technique, which reduces the orientation root mean squared error by an average compared to the existing LiDAR data registration technique based on normal distribution transforms. This work could be utilized as a testbed for future research that attempts to include advanced localization features for IV driving.

본 논문에서는 연구목적과 관련하여, 협업 지능형교통체계와 자율주행체계에 관심을 가지고 있으며, C-ITS 특성 가운데 핵심 전달 메시지인 CAM과 DENM 특성 분석, 또한 V2X 통신의 보안 특성과 함께 CAM 및 DENM 메시지의 보안 인증서 및 헤더 구조를 중심으로 분석에 초점을 맞추고 있다. 연구방법에 대해, 우리는 CAM 메시지 인 차량의 위치와 상태를 알리는 메시지를 분석하고, DENM 메시지인 차량 사고와 같은 이벤트를 알리는 메시지를 분석하고, 이를 지원하는 보안통신 특성을 분석한다. 차량통신에 사용하는 보안헤더와 인증서 형식과 함께, 차량용 서명된 인증서 검증 절차, 그리고 차량용PKI 특성을 얻었다. 아울러, V2X 보안통신을 위해 필요로 하는 보안 동기패 턴에 대한 특성과 전송능력에 대해서도 함께 유도할 수 있었다. 그러므로 본 논문은 C-ITS 환경에서 DENM 및 CAM을 전송하는 통신 서비스를 위한 보안 특성을 고려할 때 의미 있는 결과라 할 수 있다.

In this paper, we have interested in cooperative intelligent transport system and autonomous driving system, and focused on analysis of the characteristics of Cooperative Awareness Message (CAM) and Decentralized Environmental Notification Basis Service (DENM) message, which is key delivery message among cooperative intelligent transport system (C-ITS) characteristics for research objectivity. For research method, we also described V2X communication, and also analyzed the security certificate and header structure of CAM and DENM messages. We described CAM message, which is a message informing the position and status of the vehicle. And the DENM message is presented a message informing an event such as a vehicle accident, and analysis security communication, which is supported services. According to standard analysis result, 186 bits or 275 bits are used. In addition to the security header and the certificate format used for vehicle communication, we have gained the certificate verification procedure for vehicles and PKI characteristics for vehicles. Also We derived the characteristics and transmission capability of the security synchronization pattern required for V2X secure communication. Therefore when it is considered for communication service of DENM and CAM in the C-ITS environment, this paper may be meaningful result.

기존의 Greedy 경로 프로토콜은 일반적으로 차량 Ad-hoc 통신 (Vehicle Ad-hoc Networks) 에서 좋은 성능을 보인 다. 그러나 일시적으로 거리를 비게 만드는 교통신호가 존재하는 구간이나 분리된 도로가 합류하는 지점이 없는 도시의 도로에서 지형적인 영향으로 Greedy 라우팅 프로토콜은 잘못된 경로 라우팅 된 경우 불필요하게 경로가 길어지거나 라 우팅 실패가 많이 발생한다. 또한, 단순하게 목적지 노드와의 직선거리를 가지고 노드들의 우선순위를 부여하고 가장 낮 은 값을 가진 노드를 중계노드로 선택한다. 최근에 차랑 Ad-hoc 통신에서는 지리적인 환경의 특성 때문에 거리뿐만 아 니라 전달 방향도 중요한 요소 중에 하나이다. 그래서 본 논문은 개선된 프로토콜을 제안 하는데 하나의 노드가 패킷을 전달할 때 목적지 노드 까지를 지능적으로 거리 및 전달 방향성을 고려하여 다음 노드를 선정하고 교통 통신 상태를 지 능적 제어에 따라 보다 안정적인 경로 설정을 할 수 있게 하고 지형적 모델이 따라 자유롭게 변경이 가능 하게끔 관리 한다. 제안된 프로토콜 방법의 성능 분석은 두 가지의 이동모델을 적용한 네트워크 시뮬레이션을 통하여 검증하였고 대 부분의 경우 기존 프로토콜보다 좋은 성능을 보였다.

Greedy protocols show good performance in Vehicular Ad-hoc Networks (VANETs) environment in general. But they make longer routes causing by surroundings or turn out routing failures in some cases when there are many traffic signals which generate empty streets temporary, or there is no merge roads after a road divide into two roads. When a node selects the next node simply using the distance to the destination node, the longer route is made by traditional greedy protocols in some cases and sometimes the route ends up routing failure. Most of traditional greedy protocols just take into account the distance to the destination to select a next node. Each node needs to consider not only the distance to the destination node but also the direction to the destination while routing a packet because of geographical environment. The proposed routing scheme considers both of the distance and the direction for forwarding packets to make a stable route. And the protocol can configure as the surrounding environment. We evaluate the performance of the protocol using two mobility models and network simulations. Most of network performances are improved rather than in compared with traditional greedy protocols.

In the development of intelligent vehicles, path tracking of unmanned vehicle is a basis of autonomous driving and automatic navigation. It is very important to find the exact position of a vehicle for the path tracking, and it is possible to get the position information from GPS. However the information of GPS is not the current position but the past position because a vehicle is moving and GPS has a time delay. In this paper, therefore, the moving distance of a vehicle is estimated using a direction sensor and a velocity sensor to compensate the position error of GPS. In the steering control, optimal fuzzy rules for the path tracking can be found through the simulation of Simulink. Real driving experiments show the fuzzy rules are good for the steering control and the position error of GPS is well compensated by the proposed estimation method.

Recent technological advances made a vehicle more intelligent to increase safety and comfort. An intelligent vehicle provides drivers with safety warning information through audible sounds, visual displays, and tactile devices. However, elderly drivers have been known to decrease the physical and cognitive abilities such as muscular strength, hearing, eyesight, short term memory, and spatial perception. Therefore, possible age-related deficits should be considered to design an effective warning system. This paper aims to evaluate the impact of advancing age on response performance on audible safety warnings which are widely used for alerting driving hazards. In order to understand the effect of age-related hearing loss and movement slowing, three sound characteristics (frequency, intensity, and period) and three age groups (younger, middle, and older) are considered. Data was drawn from 38 drivers who drove a simulated rural road in a driving simulator. Experimental results show that age influences driver's response performance. In conclusion, the appropriate range of a warning sound is suggested.

Mostly a ride comfort and handling performance of vehicle is influenced by dynamic behavior control of vehicle. We are focusing on development of a semi-intelligent suspension system with continuously variable damper(HS-SH type). only using absolute velocity of sprung mass without using the relative velocity besides having lower system prices and a little energy requirement. In this paper, the system is realized in consideration to control strategy (sky-hook control, hybrid filter, etc.) and has been proved to have improvement of behavior control of vehicle by quarter car and Vehicle test, respectively.

대기환경 문제는 국민의 생활에 직접 관련이 있고, 국민들은 미세먼지와 관련하여 많은 우려를 하고 있다. 미세먼지 오염원 중에 가장 큰 비중을 차지하는 것이 자동차 배출가스이기 때문에, 정부에 서는 자동차 배출가스 등급제를 시행하여 대기환경을 개선하고자 노력하고 있다. 하지만, 자동차 정기 검사와 불법 및 부실검사소 단속은 사전예방이 어렵고 검사 및 단속 이후에 조치가 되는 한계점이 있 다. 본 연구에서는 지능정보기술을 활용하여 모든 대상을 검사 및 단속하지 않고도 사전 예측하여 선 제적인 정책수행이 가능한 방안을 제시한다. 또한, 이상징후의 즉각적인 파악을 통해 실시간적인 정책 수행이 가능하다. 딥러닝을 활용하면 분류되지 않은 특성에 대해서도 패턴인식을 통해 유사한 것들을 분류할 수 있게 되어 사전예측이 가능하다. 정책의 수행을 위한 구체적인 데이터 모델 및 알고리즘은 추가적인 연구가 필요하다. 향후 연구를 통해 실제 자동차 검사결과와 부실 및 불법 검사소 정보를 활 용하여 사전예측 모델을 만들어 시험하고 결과를 분석할 계획이다.

The air environment problem is directly related to the lives of the people, and the people are concerned about fine dust. Since automobile emissions account for the largest proportion of particulate matter pollutants, the government is trying to improve the air environment by implementing a rating system for automobile emissions. However, regular vehicle inspections and crackdowns at illegal and insolvent inspection centers are difficult to prevent in advance, and there are limitations in that measures are taken after inspections and crackdowns. This study proposes a plan that enables preemptive policy implementation by using intelligent information technology to predict in advance without inspecting and cracking down on all targets. In addition, real-time policy execution is possible through immediate identification of abnormal symptoms. Using deep learning, it is possible to classify similar things through pattern recognition even for unclassified features, allowing for advance prediction. Detailed data models and algorithms for policy implementation need additional research. Through future research, we plan to test and analyze the results by creating a predictive model using actual vehicle inspection results and information on insolvent and illegal inspection sites.

Vehicular Ad hoc Networks have attracted extensive attentions in recent years for their promises in improving safety and enabling other value-added services. Security and privacy are two integrated issues in the deployment of vehicular networks. Privacy-preserving authentication is a key technique in addressing these two issues. We propose a hash chain based authentication protocol that preserves the user privacy . We show that the our scheme can efficiently authenticate users. Name of Our protocol is

차량 간 통신 네트워크 환경에서 차량 간 혹은 차량 대 기지국 간 통신 시 다양한 통신에 방해가 되는 장애 요소가 발생하거나 존재할 수 있다. 다양한 장애 요인들로 인하여 차량의 고장이나 긴급상황이 발생할 경우 정보 전송과정에서 통신 네트워크의 포화상태나 과도한 경쟁으로 인한 패킷의 손실 및 지연이 발생하게 된다. 이러한 결과 인적, 물적 피해와 더불어 지속적인 통신시도로 차량의 전원고갈 문제가 발생할 수 있다. 따라서, 다양한 장애요인이 상존하는 도로 환경에서 종단간에 고속, 안정적일 뿐만 아니라 에너지 효율적인 프로토콜 개발이 요구된다. 본 논문에서는 IEEE 802.15.3 WPAN을 기반으로 차량간 통신 시스템에서 에너지 효율적인 긴급 메세지 전송을 위한 MAC 프로토콜을 제안한다. 시뮬레이션 및 분석을 통하여 본 논문에서 제안하는 방법이 패킷충돌 및 경쟁으로 발생하는 전송지연을 감소시켰으며, 에너지 효율적인 프로토콜임을 확인하였다.

Inter-vehicular communication suffers from a variety of the problem on the road, resulting in large delay in propagating emergency warning. An energy depletion as well as a transmission delay may induced by traffic accident. A transmission delay are caused by direct contention from nodes that can hear each other or indirect contention from nodes that can not hear each other, but simultaneously transmit to the same destination. A variety of works have been researched to solve the transmission delay and energy consumption problem in intelligent cars transportation systems. We consider a vehicle-to-vehicle communication protocol for disseminating an emergency information that include end-to-end and energy efficient transmission. In this paper, we propose A vehicle-to-vehicle communication protocol scheme for dissemination emergency information in intelligent cars communication based on IEEE 802.15.3 wireless personal area networks. Results from a simulation study reveal that our scheme can achieves low latency in delivering emergency warnings, and efficiency in consuming energy in stressful road scenarios.

This paper presents the design and experimental validation of an intelligent tire alignment and lifting control system for an under-vehicle autonomous parking robot. The proposed system enables the robot to autonomously enter beneath a vehicle, recognize tire positions using a LiDAR-based sensing module, and perform precise lifting through a fork-type mechanism. A YOLOv8 instance segmentation algorithm is employed to detect tire regions from LiDAR point cloud data and estimate their geometric centers. The detected tire positions are then matched with a vehicle database to determine the correct alignment for lifting. Experiments were conducted on three different vehicle types under various surface conditions. The results show that the proposed system achieved a tire recognition accuracy exceeding 95%, a lifting success rate of 100%, and an average lifting operation time of 12.3 seconds. These results demonstrate the reliability and practicality of the proposed method for real-world autonomous parking applications.

IoT의 핵심 요소 기술 중 하나인 Bluetooth를 전기차 무선 충전 시스템에 사용하는 경우가 늘어나면서 이에 대한 보안 문 제가 큰 이슈로 부각되고 있다. 무선 통신 기술인 Bluetooth에 보안을 강화하기 위한 다양한 기술적 노력이 있어 왔지만 여전 히 다양한 공격 방법이 존재한다. 본 논문은 Bluetooth 시스템을 대상으로 대표적인 2가지 공격 방법을 지능적으로 탐지하기 위해 잘 알려진 Hidden Markov Model을 이용한 지능형 Bluetooth 침입 탐지 시스템을 제안한다. 제안 방법은 탐지의 정확성 이외에 실시간 탐지가 가능하도록 Bluetooth 전송 계층 프로토코인 H4의 패킷 타입과 전송 방향을 조합하고 이들의 시간상의 전개를 특징으로 사용한다. 데이터 수집 환경을 구성하고 실험을 통해 얻은 데이터를 대상으로 개발한 시스템의 성능을 분석 한다.

With the increase in cases of using Bluetooth devices used in the electric vehicle charging systems, security issu es are also raised. Although various technical efforts have beed made to enhance security of bluetooth technology, v arious attack methods exist. In this paper, we propose an intelligent Bluetooth intrusion detection system based on a well-known machine learning method, Hidden Markov Model, for the purpose of detecting intelligently representativ e Bluetooth attack methods. The proposed approach combines packet types of H4, which is bluetooth transport layer protocol, and the transport directions of the packet firstly to represent the behavior of current traffic, and uses the t emporal deployment of these combined types as the final input features for detecting attacks in real time as well as accurate detection. We construct the experimental environment for the data acquisition and analysis the performance of the proposed system against obtained data set.

Most autonomous vehicles use GPS to determine vehicle location and heading. Using GPS for vehicle autonomous driving posts a few challenges. It does not look far ahead of the vehicle and requires frequent adjustment of vehicle heading. This results in an unstable control system and increases the chance of unstable driving behavior. Unlike this kind of passive or reactive control system, human drivers look far ahead of the road to determine the road curvature and actively adjust vehicle heading and turning angle in advance. Visual information is essential to enabling this kind of human-like driving behavior for autonomous vehicles and should be an important supplement to the GPS-based system, especially in GPS-denied environments. Road lanes are often curved, making vision-based detection of smooth and continuous curves in front of the vehicle a challenging task. Furthermore, commonly used computer vision algorithms such as edge detectors or Hough transform for line or curvature detection are not robust in changing lighting conditions. This paper presents a vision algorithm designed specifically for detecting and modeling road curvature for human-like active steering control and heading adjustment for autonomous vehicles. The proposed algorithm has been tested for paved and unpaved road conditions and shown very good results.

With the development of information technology, in particular, to improve the video and image processing technology, intelligent video surveillance system collected data can be used to extract the relevant information on the vehicle for life and related investigations provided for convenience. Since the acquisition by the light, angle, and the impact of weather, so that the video data is difficult to retrieve, for this problem, this paper presents a background model fusion method can effectively eliminate the adverse weather light and other factors. This algorithm can quickly and efficiently and with high accuracy to detect vehicle information.

The test platform plays an important role for the development of intelligent vehicles. In this work, we propose to design and build a miniature test model before building a real scene. The whole test system consists of the simulated traffic environment, the micro-intelligent vehicle and the visual information processing. Firstly, a micro- intelligent vehicle test platform applied to visual information perception is proposed. Secondly, some algorithms about traffic environmental element detection such as lane detection, traffic light and traffic signal recognition and obstacle detection are presented. The experiment validated the proposed approach. On the one hand, the main visual technologies of intelligent vehicles such as line detection, obstacle detection, and traffic signal recognition can be tested in this system; on the other hand, the test result can be used to evaluate and improve the design of the real test platform.

Vehicle intelligent position systems based on Received Signal Strength Indicator (RSSI) in WirelessSensor Networks (WSNs) areefficientlyutilized. The vehicle’s position accuracy is of great importance for transportation behaviors, such as dynamic vehicle routing problems and multiple pedestrian routing choice behaviors and so on. Therefore, a precise position and available optimization is necessary for total parameters of conventional RSSI model. In this papar, we investigate the experimental performance of translating the power measurements to corresponding distance between eachpair of nodes. The priori knowledge about the environment interference could impact the accuracy of vehicles’s position and the reliability of paremeters greatly. Based on the real-world outdoor experiments, we compares different regression analysis of the RSSI model, in order to establish a calibration scheme on RSSI model. Empirical experimentation shows that the average errors of RSSI model is able to decrease throughout therules of environmental factor n and shadowing factor ηrespectively. Moreover, the calculation complexity is reduced, as aninnovative approach. Since variation tendency of environmental factor n, shadowing factor η with distance and signal strength could be simulated respectively, RSSI model fulfills the precision of the vehicle intelligent position system.