• Title/Summary/Keyword: Driving environments

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Real-Time Eye Tracking Using IR Stereo Camera for Indoor and Outdoor Environments

  • Lim, Sungsoo;Lee, Daeho
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.11 no.8
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    • pp.3965-3983
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    • 2017
  • We propose a novel eye tracking method that can estimate 3D world coordinates using an infrared (IR) stereo camera for indoor and outdoor environments. This method first detects dark evidences such as eyes, eyebrows and mouths by fast multi-level thresholding. Among these evidences, eye pair evidences are detected by evidential reasoning and geometrical rules. For robust accuracy, two classifiers based on multiple layer perceptron (MLP) using gradient local binary patterns (GLBPs) verify whether the detected evidences are real eye pairs or not. Finally, the 3D world coordinates of detected eyes are calculated by region-based stereo matching. Compared with other eye detection methods, the proposed method can detect the eyes of people wearing sunglasses due to the use of the IR spectrum. Especially, when people are in dark environments such as driving at nighttime, driving in an indoor carpark, or passing through a tunnel, human eyes can be robustly detected because we use active IR illuminators. In the experimental results, it is shown that the proposed method can detect eye pairs with high performance in real-time under variable illumination conditions. Therefore, the proposed method can contribute to human-computer interactions (HCIs) and intelligent transportation systems (ITSs) applications such as gaze tracking, windshield head-up display and drowsiness detection.

Mobile Robot Driving using Moving Window

  • Choi, Sung-Yug;Kang, Jin-Gu;Hur, Hwa-Ra;Ju, Jin-Hwa
    • 제어로봇시스템학회:학술대회논문집
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    • 2003.10a
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    • pp.758-761
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    • 2003
  • This paper introduces a method that can detect obstacles and corridor environments from the images captured by a CCD camera in an automobile or mobile robot is proposed. Processing the input dynamic images in real time requires high performance hardware as well as efficient software. In order to relieve these requirements for detecting the useful information from the images in real time, a "Moving Window" scheme is proposed. Therefore, detecting the useful information, it becomes possible to search the obstacles within the driving corridor of an automobile or mobile robot. The feasibility of the proposed algorithm is demonstrated through the simulated experiments of the corridor driving.

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Development of the Driving Simulator of High Speed Train based on the Concurrent Engineering Design Environment (동시공학설계환경에서의 고속철도 주행시뮬레이터 개발)

  • Jun, Hyun-Kyu;Park, Sung-Hyuk;Kwak, Young-Kyu
    • Proceedings of the KSME Conference
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    • 2004.11a
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    • pp.1001-1006
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    • 2004
  • The concurrent engineering technologies have been broadly used in the field of the design, testing, manufacturing and maintenance works to reduce development time and costs. For this purpose, many design environments with the product data management system, the virtual engineering system and web database system are developed. In this research, we developed the driving simulator of the KTX(Korea Train Express) as a basic study for building the concurrent engineering design environment of rolling stock. The virtual track was developed from the Seoul to the Busan and the Daejeon to Mockpo to generate immersible driving environment. Also, fault generation systems were developed to educate drivers of the KTX. We expect to reduce the time and costs of newly developed rolling stock using the design environment developed in the research.

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The Design and Implementation of Driver Safety Assist System by Analysis of Driving Behavior Data (운전자 운전행동 분석을 통한 안전운전 지원시스템 설계 및 구현)

  • Ko, Jae-Jin;Choi, Ki-Ho
    • Journal of Advanced Navigation Technology
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    • v.17 no.2
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    • pp.165-170
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    • 2013
  • In this paper, we propose the information acquisition and analysis system for a vehicle driver in order to provide the safe driving environments. We first define the list of reckless driving behaviors and propose the recognition system, which recognizes the reckless behaviors, by using the acquired information. The collaboration among the information acquisition, the analysis, and the behavior comparison modules increases the accuracy of the recognition rate. Our system alarms to a vehicle driver in order to notify the potential to confront the dangerous situation due to the abnormal or reckless driving behaviors.

Improvement of Dynamic Performance of Vehicle Simulator Using Human Sensibility Ergonomics (감성공학 기법을 이용한 차량 시뮬레이터의 동적 성능 향상에 대한 연구)

  • Lee, Sang-Chul;Um, Sung-Sook;Son, Kwon;Choi, Kyung-Hyun
    • 제어로봇시스템학회:학술대회논문집
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    • 2000.10a
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    • pp.312-312
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    • 2000
  • Human sensibility ergonomics is applied to evaluation of dynamic performance of a vehicle driving simulator. Vehicle, driving environment, and human perception models are constructed and integrated. Driving simulations are carried out based on these models. This study defines a set verbal expressions collected and investigates which are the most appropriate for describing the fidelity of translational and angular accelerations of the driving simulator. An statistical analysis is uscd to find correlation between the ergonomic sensibility and the cut-off frequency of the washout algorithm. This study suggests a methodology to obtain an ergonomic database which can be used for the performance evaluation of dynamic environments.

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Analysis of Deep Learning-Based Lane Detection Models for Autonomous Driving (자율 주행을 위한 심층 학습 기반 차선 인식 모델 분석)

  • Hyunjong Lee;Euihyun Yoon;Jungmin Ha;Jaekoo Lee
    • IEMEK Journal of Embedded Systems and Applications
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    • v.18 no.5
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    • pp.225-231
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    • 2023
  • With the recent surge in the autonomous driving market, the significance of lane detection technology has escalated. Lane detection plays a pivotal role in autonomous driving systems by identifying lanes to ensure safe vehicle operation. Traditional lane detection models rely on engineers manually extracting lane features from predefined environments. However, real-world road conditions present diverse challenges, hampering the engineers' ability to extract adaptable lane features, resulting in limited performance. Consequently, recent research has focused on developing deep learning based lane detection models to extract lane features directly from data. In this paper, we classify lane detection models into four categories: cluster-based, curve-based, information propagation-based, and anchor-based methods. We conduct an extensive analysis of the strengths and weaknesses of each approach, evaluate the model's performance on an embedded board, and assess their practicality and effectiveness. Based on our findings, we propose future research directions and potential enhancements.

Development of a Control System for E-Bike Based on IOT (IOT 기반의 전기 자전거 제어 시스템 개발)

  • Park, Jong-Jin;Cho, Bum-Dong
    • The Transactions of The Korean Institute of Electrical Engineers
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    • v.65 no.1
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    • pp.150-157
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    • 2016
  • In this paper, a control system for E-bike based on IOT was developed, which collects and monitors information of states of E-bike and surrounding environments from several sensors and control devices in E-bike, and informs the possible dangers to rider when riding the E-bike. Developed electronic control system can manage battery efficiently, obtain battery's remaining power in real-time and provide possible riding distance to rider. It makes possible for rider to schedule near optimal riding route in terms of battery usage and respond quickly to battery discharge. Results of applying developed system to E-bike show that according to driving-mode, possible driving distance can be calculated efficiently and using user application App, real-time driver position marking and driving route searching functions lead to energy efficient E-bike driving. Later we will endeavor to integrate BMS, ECU, smart-phone and PC(server) to provide stable driving system based on various driving information of E-bike.

A Study on Independent Steering & Driving Control Algorithm for 6WS/6WD Vehicle (6WS/6WD 차량의 독립조향 및 구동 제어알고리즘에 관한 연구)

  • Kim, Chang-Jun;Han, Chang-Soo
    • Journal of Institute of Control, Robotics and Systems
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    • v.17 no.4
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    • pp.313-320
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    • 2011
  • Multi-axle driving vehicles that are used in special environments require high driving performance, steering performance, and stability. Among these vehicles, 6WS/6WD vehicles with middle wheels have structural safety by distributing the load and reducing the pitch angle during rapid acceleration and braking. 6WS/6WD vehicles are favored for military use in off road operations because of their high maneuverability and mobility on extreme terrains and obstacles. 6WD vehicles that using in-wheel motor can generate the independent wheel torque without other mechanical parts. Conventional vehicles, however, cannot generate an opposite driving force at each side wheel. Using an independent steering and driving system, six-wheel vehicles can show better performance than conventional vehicles. Using of independent steering and driving system, the 6 wheel vehicle can improve a performance better than conventional vehicle. This vehicle enhances the maneuverability under low speed and the stability at high speed. This paper describes an independent 6WS/6WD vehicle, consists of three parts; Vehicle Model, Control Algorithm for 6WS/6WD and Simulation. First, vehicle model is application of TruckSim software for 6WS and 6WD. Second, control algorithm describes the optimum tire force distribution method in view of energy saving. Last is simulation and verification.

A Study on V2X Modeling for Virtual Testing of ADS Based on MIL Simulation (MILS 기반 ADS 기능 검증을 위한 V2X 모델링에 관한 연구)

  • Seong-Geun Shin;Jong-Ki Park;Chang-Soo Woo;Chang-Min Ye;Hyuck-Kee Lee
    • Journal of Auto-vehicle Safety Association
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    • v.15 no.3
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    • pp.34-42
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    • 2023
  • Simulation-based virtual testing is known to be a major requirement for verifying the safety of autonomous driving functions. However, in the simulation environment, there is a difficulty in that all driving environments related to the autonomous driving system must be realistically modeled. In particular, C-ITS (Cooperative-Intelligent Transport Systems) is essential for urban autonomous driving of Lv.4, but the approach to modeling for C-ITS service in the MILS (Model in the Loop Simulation) environment is not yet clear. Therefore, this paper aims to deal with V2X (Vehicle to Everything) modeling methods to effectively apply C-ITS-based autonomous cooperative driving services in the MILS environment. First, major C-ITS services and use cases for autonomous cooperative driving are analyzed, and a modeling method of V2X signals for C-ITS service simulation is proposed. Based on the modeled V2X messages, the validity of the proposed approach is reviewed through simulations on the C-ITS service use case.

Comparison on the Driver Characteristics and Subjective Workload according to the Road Direction Change using Driving Simulator (도로주행방향 변화에 따른 운전 특성 및 주관적 부하의 운전 시뮬레이터 기반 비교 평가)

  • Jeon, Yong-Wook;Daimon, Tatsuru;Kawashima, Hironao;Kwon, Kyu-Sik
    • Journal of Korean Society of Industrial and Systems Engineering
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    • v.32 no.1
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    • pp.26-33
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    • 2009
  • The directions of the road are divided into two, the right-hand side and left-hand side of the road, by the convention and specific native method in the world. This paper deals with the characteristics and behaviors of drivers who are accustomed to driving on right-hand side of the road, drive with a handle on the left-hand side, and comparing with left-hand side drivers. The driver's eye movements were measured by eye camera and questionnaires were used for measuring subjective evaluation such as driving mental workload. The experimental results indicated even if the experts who had much experience on right-hand side driving, they had lower driving skill than novice driver, accustomed to driving on left-hand side. In terms of mental workload, MCH rating scale and MNASA-TLX, the right-hand side drivers were in lower stress condition than the left-hand side drivers because of having much driving experience. However, they conducted a few mistakes by confusing the position of turn signal and windshield wiper because of their driving habit or traits and it lead to operation mistakes. These results can be applied effectively to develop the driving support information with changed environments.