• 제목/요약/키워드: Intelligent vehicles

검색결과 770건 처리시간 0.029초

3D Global Dynamic Window Approach for Navigation of Autonomous Underwater Vehicles

  • Tusseyeva, Inara;Kim, Seong-Gon;Kim, Yong-Gi
    • International Journal of Fuzzy Logic and Intelligent Systems
    • /
    • 제13권2호
    • /
    • pp.91-99
    • /
    • 2013
  • An autonomous unmanned underwater vehicle is a type of marine self-propelled robot that executes some specific mission and returns to base on completion of the task. In order to successfully execute the requested operations, the vehicle must be guided by an effective navigation algorithm that enables it to avoid obstacles and follow the best path. Architectures and principles for intelligent dynamic systems are being developed, not only in the underwater arena but also in related areas where the work does not fully justify the name. The problem of increasing the capacity of systems management is highly relevant based on the development of new methods for dynamic analysis, pattern recognition, artificial intelligence, and adaptation. Among the large variety of navigation methods that presently exist, the dynamic window approach is worth noting. It was originally presented by Fox et al. and has been implemented in indoor office robots. In this paper, the dynamic window approach is applied to the marine world by developing and extending it to manipulate vehicles in 3D marine environments. This algorithm is provided to enable efficient avoidance of obstacles and attainment of targets. Experiments conducted using the algorithm in MATLAB indicate that it is an effective obstacle avoidance approach for marine vehicles.

장갑차량 공격용 지능형 포탄의 전시 소요량 산정 모형에 관한 연구 (Study of Estimation Model for Wartime Stockpile Requirement of Intelligent Ammunition against Enemy Armored Vehicles)

  • 조홍용;정병희
    • 한국국방경영분석학회지
    • /
    • 제34권2호
    • /
    • pp.143-162
    • /
    • 2008
  • 이 연구는 현재 개발이 진행 중인 장갑차량 상부 공격용 지능형 탄약을 포함한 155mm 포병 탄약의 전시소요량을 산정하는 방법론을 정립하려는 것이다. 종래의 워게임 시뮬레이션에 의한 방법에서는 장갑표적 공격용 무기체계별 기대점유비율이 지상군 및 공군간에 과도하게 차이가 발생하고 있다. 또한 상향식 소요산정방법은 최소소요량에 비하여 너무나 과도하게 산출하는 경향이 있으므로 이러한 점들을 보완하기 위하여 표적 수량에 따른 무기체계별 할당에 의한 하향식 모형을 구성한 것이다. 이모형이 워게임에 의한 상향식 소요산정보다는 더 믿을 만한 결과를 산출한다.

지능형 운행체를 위한 비전 센서 기반 자이로 드리프트 감소 (Vision-based Reduction of Gyro Drift for Intelligent Vehicles)

  • 경민기;당 코이 누엔;강태삼;민덕기;이정욱
    • 제어로봇시스템학회논문지
    • /
    • 제21권7호
    • /
    • pp.627-633
    • /
    • 2015
  • Accurate heading information is crucial for the navigation of intelligent vehicles. In outdoor environments, GPS is usually used for the navigation of vehicles. However, in GPS-denied environments such as dense building areas, tunnels, underground areas and indoor environments, non-GPS solutions are required. Yaw-rates from a single gyro sensor could be one of the solutions. In dealing with gyro sensors, the drift problem should be resolved. HDR (Heuristic Drift Reduction) can reduce the average heading error in straight line movement. However, it shows rather large errors in some moving environments, especially along curved lines. This paper presents a method called VDR (Vision-based Drift Reduction), a system which uses a low-cost vision sensor as compensation for HDR errors.

Block-VN: A Distributed Blockchain Based Vehicular Network Architecture in Smart City

  • Sharma, Pradip Kumar;Moon, Seo Yeon;Park, Jong Hyuk
    • Journal of Information Processing Systems
    • /
    • 제13권1호
    • /
    • pp.184-195
    • /
    • 2017
  • In recent decades, the ad hoc network for vehicles has been a core network technology to provide comfort and security to drivers in vehicle environments. However, emerging applications and services require major changes in underlying network models and computing that require new road network planning. Meanwhile, blockchain widely known as one of the disruptive technologies has emerged in recent years, is experiencing rapid development and has the potential to revolutionize intelligent transport systems. Blockchain can be used to build an intelligent, secure, distributed and autonomous transport system. It allows better utilization of the infrastructure and resources of intelligent transport systems, particularly effective for crowdsourcing technology. In this paper, we proposes a vehicle network architecture based on blockchain in the smart city (Block-VN). Block-VN is a reliable and secure architecture that operates in a distributed way to build the new distributed transport management system. We are considering a new network system of vehicles, Block-VN, above them. In addition, we examine how the network of vehicles evolves with paradigms focused on networking and vehicular information. Finally, we discuss service scenarios and design principles for Block-VN.

태양복사열 내부전도 성능향상을 위한 탄소 나노구조체 흑체코팅 열처리 효과연구 (Effect of Thermal Post-Treatment using the Black Body Networking of Carbon Nano Structure For Internal Conduction from Solar Radiation)

  • 김대원;장성민;이두희;박준이;김영배
    • 열처리공학회지
    • /
    • 제34권4호
    • /
    • pp.159-164
    • /
    • 2021
  • The Improvement of thermal performance using heat treatment of carbon nanotubes coated on the copper heat sink to take the radiation energy from solar ray for the energy harvesting in earth orbit. Using the additive coating of purified CNT for the increase of specific area and development of thermal conductive capacity, the performance of heat transfer is improved about 0.181 K/W while applying the power of 22 W under temperature of 3.98℃. Coating of purified CNT shows increase of area and volume of thermal layer however it led the partial thermal resistance.

An Intelligent Auto Parking System for Vehicles

  • Razinkova, Anastasia;Cho, Hyun-Chan;Jeon, Hong-Tae
    • International Journal of Fuzzy Logic and Intelligent Systems
    • /
    • 제12권3호
    • /
    • pp.226-231
    • /
    • 2012
  • Autoparking assistant systems are a new and very promising area in automotive systems engineering. Since the traffic in modern cities becomes more intense, it is getting harder for a driver. Those systems are necessary for an inexperienced one to find a proper parking slot, or to park in a narrow parking slot without damaging his car or the vehicles around. The implementation of autoparking assistant systems may reduce drivers' stress and make parking generally more comfortable. In addition, such system can be extremely useful for senior or disabled people or for drivers with reduced mobility. The implementation of autoparking assistant systems may increase the safety of the parking, and therefore the development of such systems is a highly-demanded task. We introduce an intelligent autoparking system that automatically generates trajectory for parking using a fuzzy logic. This paper consists of three parts. In first part we introduce trajectory generation method for parallel parking without collisions. Fuzzy-logic based trajectory generation algorithm is described in second part. Experimental results presented in the third part of the paper prove effectiveness of the proposed method.

A refinement and abstraction method of the SPZN formal model for intelligent networked vehicles systems

  • Yang Liu;Yingqi Fan;Ling Zhao;Bo Mi
    • KSII Transactions on Internet and Information Systems (TIIS)
    • /
    • 제18권1호
    • /
    • pp.64-88
    • /
    • 2024
  • Security and reliability are the utmost importance facts in intelligent networked vehicles. Stochastic Petri Net and Z (SPZN) as an excellent formal verification tool for modeling concurrent systems, can effectively handles concurrent operations within a system, establishes relationships among components, and conducts verification and reasoning to ensure the system's safety and reliability in practical applications. However, the application of a system with numerous nodes to Petri Net often leads to the issue of state explosion. To tackle these challenges, a refinement and abstraction method based on SPZN is proposed in this paper. This approach can not only refine and abstract the Stochastic Petri Net but also establish a corresponding relationship with the Z language. In determining the implementation rate of transitions in Stochastic Petri Net, we employ the interval average and weighted average method, which significantly reduces the time and space complexity compared to alternative techniques and is suitable for expert systems at various levels. This reduction facilitates subsequent comprehensive system analysis and module analysis. Furthermore, by analyzing the properties of Markov Chain isomorphism in the case study, recommendations for minimizing system risks in the application of intelligent parking within the intelligent networked vehicle system can be put forward.

Research on Information Providing Method for Intelligent Navigation System

  • Park, Hye-Sun;Kim, Kyong-Ho
    • 대한인간공학회지
    • /
    • 제31권5호
    • /
    • pp.657-670
    • /
    • 2012
  • Background: Today, numerous telematics technologies, i.e., technologies developed by integrating telecommunications with information processing, are applied in vehicles. One such developmental application of this technology to vehicles is to increase the safety or convenience of drivers by providing them with necessary information such as warnings and information on emergencies and traffic situations. However, under certain conditions, there is a high probability of traffic accidents if the driving workload is high. Nowadays, the navigation system is frequently used in the vehicles, this system provides various information including route to the driver. But, the existing navigation systems are not only considered a driver's reaction but also provide unilaterally to the information regardless of them. Such one-side information service type may miss important information to the driver. In addition, it sometimes interferes safety driving. Objective: To solve this problem, the intelligent navigation system needs to the providing way that it checks the driver's reactions after providing information. Namely, if the driver passes the information received from the navigation, then the intelligent system provides more loudly and more frequently. Method: Therefore, in this study we introduce the intelligent navigation system that it automatically controls modality type and its strength when the driver misses or overlooks the information for their safety and entertainment and we analyze the driver's cognitive responses about the modality type and its strength. Results: To evaluate the effectiveness of the proposed system, we analyzed the reaction time and driving workload for each type of the information, modality and its strength. Also we evaluated the users' subjective satisfaction and understanding based on a questionnaire.

Intelligent 3D Obstacles Recognition Technique Based on Support Vector Machines for Autonomous Underwater Vehicles

  • Mi, Zhen-Shu;Kim, Yong-Gi
    • International Journal of Fuzzy Logic and Intelligent Systems
    • /
    • 제9권3호
    • /
    • pp.213-218
    • /
    • 2009
  • This paper describes a classical algorithm carrying out dynamic 3D obstacle recognition for autonomous underwater vehicles (AUVs), Support Vector Machines (SVMs). SVM is an efficient algorithm that was developed for recognizing 3D object in recent years. A recognition system is designed using Support Vector Machines for applying the capabilities on appearance-based 3D obstacle recognition. All of the test data are taken from OpenGL Simulation. The OpenGL which draws dynamic obstacles environment is used to carry out the experiment for the situation of three-dimension. In order to verify the performance of proposed SVMs, it compares with Back-Propagation algorithm through OpenGL simulation in view of the obstacle recognition accuracy and the time efficiency.

자율주행차량 도입에 따른 교통 네트워크의 효율성 변화 분석연구 (Exploring the Impacts of Autonomous Vehicle Implementation through Microscopic and Macroscopic Approaches)

  • 육동형;이백진;박준태
    • 한국ITS학회 논문지
    • /
    • 제17권5호
    • /
    • pp.14-28
    • /
    • 2018
  • 차량 통신 및 지능형 교통 시스템의 기술 향상으로 인해 자율 차량이 시장에 서서히 도입될 것으로 예상된다. 본 연구는 자율주행차량이 네트워크 효율성에 미치는 영향을 분석한 것이다. 네트워크의 효율성을 측정하기 위해 이 연구에서는 미시적 및 거시적 시뮬레이션을 결합한 순차적 단계를 적용했다. 미시적 시뮬레이션은 도로에서 자율주행차량의 비율에 의한 용량 변화를 고려하는 반면, 거시적 시뮬레이션은 네트워크 전체의 개선을 식별하기 위해 시뮬레이션 결과를 이용한다. 예상대로, 자율주행차량은 인간의 운전보다 기존 도로 용량을 효율적으로 활용한다. 특히, 고속도로에서 최대 용량 개선은 190.5%로 예상된다. 상당한 용량의 변화는 자율주행차량의 비율이 약 80% 이상일 때 관찰된다. 이러한 개선 사항은 자율주행차량의 보급을 통해 전반적인 네트워크 효율성을 향상시킬 수 있는 거시적 모델로 변환된다. 그러나 본 연구는 자율 주행 차량의 시장 첫 출연이 자유로운 흐름 조건을 보장하지 않는 다는 것을 확인하며, 이는 자율주행차량 시대에 맞는 시스템 최적의 경로 체계의 가능한 필요성을 의미한다.