• Title/Summary/Keyword: Driving environment identification

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IMAGE PROCESSING TECHNIQUES FOR LANE-RELATED INFORMATION EXTRACTION AND MULTI-VEHICLE DETECTION IN INTELLIGENT HIGHWAY VEHICLES

  • Wu, Y.J.;Lian, F.L.;Huang, C.P.;Chang, T.H.
    • International Journal of Automotive Technology
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    • v.8 no.4
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    • pp.513-520
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    • 2007
  • In this paper, we propose an approach to identify the driving environment for intelligent highway vehicles by means of image processing and computer vision techniques. The proposed approach mainly consists of two consecutive computational steps. The first step is the lane marking detection, which is used to identify the location of the host vehicle and road geometry. In this step, related standard image processing techniques are adapted for lane-related information. In the second step, by using the output from the first step, a four-stage algorithm for vehicle detection is proposed to provide information on the relative position and speed between the host vehicle and each preceding vehicle. The proposed approach has been validated in several real-world scenarios. Herein, experimental results indicate low false alarm and low false dismissal and have demonstrated the robustness of the proposed detection approach.

Study on the Modelling of Algal Dynamics in Lake Paldang Using Artificial Neural Networks (인공신경망을 이용한 팔당호의 조류발생 모델 연구)

  • Park, Hae-Kyung;Kim, Eun-Kyoung
    • Journal of Korean Society on Water Environment
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    • v.29 no.1
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    • pp.19-28
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    • 2013
  • Artificial neural networks were used for time series modelling of algal dynamics of whole year and by season at the Paldang dam station (confluence area). The modelling was based on comprehensive weekly water quality data from 1997 to 2004 at the Paldang dam station. The results of validation of seasonal models showed that the timing and magnitude of the observed chlorophyll a concentration was predicted better, compared with the ANN model for whole year. Internal weightings of the inputs in trained neural networks were obtained by sensitivity analysis for identification of the primary driving mechanisms in the system dynamics. pH, COD, TP determined most the dynamics of chlorophyll a, although these inputs were not the real driving variable for algal growth. Short-term prediction models that perform one or two weeks ahead predictions of chlorophyll a concentration were designed for the application of Harmful Algal Alert System in Lake Paldang. Short-term-ahead ANN models showed the possibilities of application of Harmful Algal Alert System after increasing ANN model's performance.

Area Identification for Road Design (도로 설계 지역 구분)

  • Kim, Yong Seok
    • International Journal of Highway Engineering
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    • v.16 no.6
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    • pp.181-189
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    • 2014
  • PURPOSES : Ambiguous decision on whether rural or urban area for road design can increase the construction cost and restrict the land use of surrounding area. However, administrative classification on rural and urban area is not directly related to road design because of this classification is not based on the engineering viewpoint, so method which can explain the road design context is required. METHODS : Method which enables to identify the area for road design is suggested based on the deceleration expected to be experienced by drivers who use the road section concerned. Deceleration rate corresponding to the area such as rural or urban suggested in Road Design Guideline is used as the criteria to identify the area by comparing this value with the estimated deceleration rate at the road section concerned. Speed profile method is utilized to derive the deceleration rate, and speed estimation way for reflecting both road geometry and intersection is suggested using stopping sight distance concept. RESULTS : The procedure of the method application is suggested, and the design example utilizing the method is provided. CONCLUSIONS : The method is expected to be used to identify the area for road design with engineering viewpoint, and design consistency among the roads with similar driving environment can be made.

Noise Source Identification of the Design Elements of the Driving Gear for the Urban Railway (도시철도용 구동기어의 설계 요소에 대한 소음 기여도 분석)

  • Kim, Kinam;Lee, Hyuncheol;Sun, Chanwoong;Lee, Sungwook
    • Transactions of the Korean Society for Noise and Vibration Engineering
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    • v.25 no.7
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    • pp.470-480
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    • 2015
  • As the railway noise guideline of the Ministry of Environment after 2017 is strictly enforced, the noise level at stationary condition of urban railway is demanding the reduction about 2 dB(A). And the noise level at running condition is reduced by 6 dB(A) at 80 km/h. Therefore, the devices that causes noise shall arrange for the improvement plan of noise reduction for each device. In this paper, we carried out a technical review of the driving gear used to drive the vehicle from a variety of noise-induced equipment of a urban railway. Analyze the causes of the current noise levels and noise cause about the driving gear used in current urban railway and this study analyzes the noise level and noise cause the drive gear being used in the current urban railway. Finally, in this paper proposes a scheme for reducing the noise that can be designed to reduce the noise with considering the noise cause analysis.

Fuzzy Cntrol for Otimal Navigation of A Mobile Robot

  • Hwang, Hee-Soo;Joo, Young-Hoon;Woo, Kwang-Bang
    • 제어로봇시스템학회:학술대회논문집
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    • 1992.10b
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    • pp.473-478
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    • 1992
  • This paper aims to investigate the navigation control of a mobile robot in a confined environment. Steering angle becomes control variable which is computed from the fuzzy control rules. The identification method proposed in this paper presents the fuzzy control rules obtained through modelling of. the driving actions of human operator. The feasibility of the proposed method is evaluated through the application of the identified fuzzy controls rules to the navigation control of a mobile robot which follows the center of a corridor.

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Autonomous Vehicles as Safety and Security Agents in Real-Life Environments

  • Al-Absi, Ahmed Abdulhakim
    • International journal of advanced smart convergence
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    • v.11 no.2
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    • pp.7-12
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    • 2022
  • Safety and security are the topmost priority in every environment. With the aid of Artificial Intelligence (AI), many objects are becoming more intelligent, conscious, and curious of their surroundings. The recent scientific breakthroughs in autonomous vehicular designs and development; powered by AI, network of sensors and the rapid increase of Internet of Things (IoTs) could be utilized in maintaining safety and security in our environments. AI based on deep learning architectures and models, such as Deep Neural Networks (DNNs), is being applied worldwide in the automotive design fields like computer vision, natural language processing, sensor fusion, object recognition and autonomous driving projects. These features are well known for their identification, detective and tracking abilities. With the embedment of sensors, cameras, GPS, RADAR, LIDAR, and on-board computers in many of these autonomous vehicles being developed, these vehicles can properly map their positions and proximity to everything around them. In this paper, we explored in detail several ways in which these enormous features embedded in these autonomous vehicles, such as the network of sensors fusion, computer vision and natural image processing, natural language processing, and activity aware capabilities of these automobiles, could be tapped and utilized in safeguarding our lives and environment.

The Control System Modeling and Experiment for the Tele-operated Unmanned Vehicle

  • Duk sun Yun;Lee, Woon-Sung;Kim, Jung-Ha
    • Journal of Mechanical Science and Technology
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    • v.16 no.10
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    • pp.1253-1263
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    • 2002
  • The control system design and modeling of an unmanned vehicle by means of a new concept for better performance through a tole-operation system is suggested by sensor fusion. But, the control of a real vehicle is very difficult, because the system identification of the vehicle is hard to find the unknown factors and the disturbances of the experimental environment. For the longitudinal and lateral controls, the traction system and steering system models are set up and a tuning method to find the gain of the controller by experiments is presented. In this research, mechanical and electronic parts are implemented to operate the unmanned vehicle and data reconstruction method of information about the environment data coming from several sensors is presented by data plot for the vehicle navigation. This paper focuses on the integration of tole-operated unmanned vehicle. This vehicle mainly controlled lateral and longitudinal directions with actuators for controlling vehicle movement and sensors for the closed-loop controlled system.

Robot Driving System and Sensors Implementation for a Mobile Robot Capable of Tracking a Moving Target (이동물체 추적 가능한 이동형 로봇구동 시스템 설계 및 센서 구현)

  • Myeong, Ho Jun;Kim, Dong Hwan
    • Journal of the Korean Society of Manufacturing Technology Engineers
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    • v.22 no.3_1spc
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    • pp.607-614
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    • 2013
  • This paper proposes a robot driving system and sensor implementation for use with an education robot. This robot has multiple functions and was designed so that children could use it with interest and ease. The robot recognizes the location of a user and follows that user at a specific distance when the robot and user communicate with each other. In this work, the robot was designed and manufactured to evaluate its performance. In addition, an embedded board was installed with the purpose of communicating with a smart phone, and a camera mounted on the robot allowed it to monitor the environment. To allow the robot to follow a moving user, a set of sensors combined with an RF module and ultrasonic sensors were adopted to measure the distance between the user and the robot. With the help of this ultrasonic sensors arrangement, the location of the user couldbe identified in all directions, which allowed the robot to follow the moving user at the desired distance. Experiments were carried out to see how well the user's location could be recognized and to investigate how accurately the robot trackedthe user, which eventually yielded a satisfactory performance.

Fast algorithm for Traffic Sign Recognition (고속 교통표시판 인식 알고리즘)

  • Dajun, Ding;Lee, Chanho
    • Journal of IKEEE
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    • v.16 no.4
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    • pp.356-363
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    • 2012
  • Information technology improves convenience, safety, and performance of automobiles. Recently, a lot of algorithms are studied to provide safety and environment information for driving, and traffic sign recognition is one of them. It can provide important information for safety driving. In this paper, we propose a method for traffic sign detection and identification concentrating on reducing the computation time. First, potential traffic signs are segmented by color threshold, and a polygon approximation algorithm is used to detect appropriate polygons. The potential signs are compared with the template signs in the database using SURF and ORB feature matching method.

Implementation of Vehicle Location Identification and Image Verification System in Port (항만내 차량 위치인식 및 영상 확인 시스템 구현)

  • Lee, Ki-Wook
    • Journal of the Korea Society of Computer and Information
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    • v.14 no.12
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    • pp.201-208
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    • 2009
  • As the ubiquitous environment is created, the latest ports introduce U-Port services in managing ports generally and embody container's location identification system, port terminal management system, and advanced information exchange system etc. In particular, the location identification system for freight cars and containers provide in real time the information on the location and condition for them, and enables them to cope with an efficient vehicle operation management and its related problems immediately. However, such a system is insufficient in effectively handling with the troubles in a large-scale port including freight car's disorderly driving, parking, stop, theft, damage, accident, trespassing and controlling. In order to solve these problems, this study structures the vehicle positioning system and the image verification system unsing high resolution image compression and AVE/H.264 store and transmission technology, able to mark and identify the vehicle location on the digital map while a freight car has stayed in a port since the entry of an automatic gate, or able to identify the place of accident through image remotely.