• Title/Summary/Keyword: 주행거리

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An Autonomous Driving System Based on Stereo-Vision and End-to-End Learning (스테레오 비전 및 End-to-End Learning 기반 자율주행 시스템)

  • Ye-Joong Yoon;Ji-Hwan Song;Hyeong-Seob Byeon;Bae-Seong Park;Jong-hyun Kim
    • Proceedings of the Korea Information Processing Society Conference
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    • 2023.11a
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    • pp.1171-1172
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    • 2023
  • 자율주행 기술에서 스테레오 비전과 End-to-End Driving은 많이 사용되는 기술이며 본 연구에서는 이를 신호등 인식과 주행에 적용하였다. 신호등 인식은 좌우 카메라로부터 적색 원을 인식한 후 스테레오 비전을 통해 신호등과의 거리를 추정한다. 주행 시스템은 End-to-End Learning 기반으로 이루어지며, 출력값인 가변저항을 조향각으로 변환하여 제어할 수 있다. 또한 감마 보정을 통한 데이터 증강을 통해 빛에 대해 민감하지 않게 모델을 학습하였다. 추후 신호등 인식 시 HSV 필터가 빛에 민감한 점과 주행 시 가변저항 값이 일정하지 않은 점이 해결된다면 더욱 안정적인 시스템을 구축할 수 있을 것으로 기대된다.

Methodology for Estimating Highway Traffic Performance Based on Origin/Destination Traffic Volume (기종점통행량(O/D) 기반의 고속도로 통행실적 산정 방법론 연구)

  • Howon Lee;Jungyeol Hong;Yoonhyuk Choi
    • The Journal of The Korea Institute of Intelligent Transport Systems
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    • v.23 no.2
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    • pp.119-131
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    • 2024
  • Understanding accurate traffic performance is crucial for ensuring efficient highway operation and providing a sustainable mobility environment. On the other hand, an immediate and precise estimation of highway traffic performance faces challenges because of infrastructure and technological constraints, data processing complexities, and limitations in using integrated big data. This paper introduces a framework for estimating traffic performance by analyzing real-time data sourced from toll collection systems and dedicated short-range communications used on highways. In particular, this study addresses the data errors arising from segmented information in data, influencing the individual travel trajectories of vehicles and establishing a more reliable Origin-Destination (OD) framework. The study revealed the necessity of trip linkage for accurate estimations when consecutive segments of individual vehicle travel within the OD occur within a 20-minute window. By linking these trip ODs, the daily average highway traffic performance for South Korea was estimated to be248,624 thousand vehicle kilometers per day. This value shows an increase of approximately 458 thousand vehicle kilometers per day compared to the 248,166 thousand vehicle kilometers per day reported in the highway operations manual. This outcome highlights the potential for supplementing previously omitted traffic performance data through the methodology proposed in this study.

Bird's-Eye View Service under Ubiquitous Transportation Sensor Network Environments (Ubiquitous Transportation Sensor Network에서 Bird's-Eye View 서비스)

  • Kim, Joohwan;Nam, Doohee;Baek, Sungjoon
    • The Journal of the Institute of Internet, Broadcasting and Communication
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    • v.13 no.2
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    • pp.225-231
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    • 2013
  • A bird's-eye view is an elevated view of an object from above, with a perspective as though the observer were a bird, often used in the making of blueprints, floor plans and maps. It can be used under severe weather conditions when visibility is poor. Under low visibility environments, drivers can communicate each other using V2V communication to get each vehicle's status to prevent collision and other accidents. Ubiquitous transportation sensor networks(u-TSN) and its application are emerging rapidly as an exciting new paradigm to provide reliable and comfortable transportatione services. The ever-growing u-TSN and its application will provide an intelligent and ubiquitous communication and network technology for traffic safety area.

Object detection and distance measurement system with sensor fusion (센서 융합을 통한 물체 거리 측정 및 인식 시스템)

  • Lee, Tae-Min;Kim, Jung-Hwan;Lim, Joonhong
    • Journal of IKEEE
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    • v.24 no.1
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    • pp.232-237
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    • 2020
  • In this paper, we propose an efficient sensor fusion method for autonomous vehicle recognition and distance measurement. Typical sensors used in autonomous vehicles are radar, lidar and camera. Among these, the lidar sensor is used to create a map around the vehicle. This has the disadvantage, however, of poor performance in weather conditions and the high cost of the sensor. In this paper, to compensate for these shortcomings, the distance is measured with a radar sensor that is relatively inexpensive and free of snow, rain and fog. The camera sensor with excellent object recognition rate is fused to measure object distance. The converged video is transmitted to a smartphone in real time through an IP server and can be used for an autonomous driving assistance system that determines the current vehicle situation from inside and outside.

A Study on Introducing Autonomous Public Transportation On-demand Service in Real Time Using Delphi Method (델파이 기법을 활용한 실시간 수요대응 자율주행 대중교통서비스 도입 방안 연구)

  • Joung, Junyoung;Shim, Sangwoo;Kim, Minseok
    • The Journal of The Korea Institute of Intelligent Transport Systems
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    • v.21 no.5
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    • pp.183-196
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    • 2022
  • Public transportation accessibility has been evaluated through minimum level of service for public transportation. However it is evaluated based operators rather than users. This study analyzed the users' accessibility(first-mile, last-mile) to public transportation using altteul transport card data. As a result of user's accessibility of public transportation, rural areas was lower than that in the urban areas. This study calssified type 1 and 2 based average approach time, and average approach time of Type 1 and 2 were more than average approach time of total area. We propsed an efficient introduction of autonomous public transportation on-demand service using delphi survey. As a result of delphi survey, experts agreed on 9 items regarding function, service item, route operation, approach distance, route mileage, punctuality.

Development of Longitudinal Algorithm to Improve Speed Control and Inter-vehicle Distance Control Acceptability (속도 제어와 차간거리 제어 수용성 개선을 위한 종방향 알고리즘 개발)

  • Kim, Jae-lee;Park, Man-bok
    • The Journal of The Korea Institute of Intelligent Transport Systems
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    • v.21 no.3
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    • pp.73-82
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    • 2022
  • Driver acceptance of autonomous driving is very important. The autonomous driving longitudinal controller, which is one of the factors affecting acceptability, consists of a high-level controller and a low-level controller. The host controller decides the cruise control and the space control according to the situation and creates the required target speed. The sub-controller performs control by creating an acceleration signal to follow the target speed. In this paper, we propose an algorithm to improve the inter-vehicle distance fluctuations that occur in the cruise control and space control switching problems in the host controller. The proposed method is to add an approach algorithm to the cruise control at the time of switching from cruise control to space control so that it is switched to space control at the correct switching distance. Through this, the error was improved from 12m error to 4m, and actual vehicle verification was performed.

Path Tracking Control of 6X6 Skid Steering Unmanned Ground Vehicle for Real Time Traversability (실시간 주행 안정성 분석을 위한 6X6 스키드 조향 무인 자율 주행 차량의 경로 추종 제어)

  • Hong, Hyosung;Han, Jong-Boo;Song, Hajun;Jung, Samuel;Kim, Sung-Soo;Yoo, Wan Suk;Won, Mooncheol;Joo, Sanghyun
    • Transactions of the Korean Society of Mechanical Engineers A
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    • v.41 no.7
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    • pp.599-605
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    • 2017
  • For an unmanned vehicle to be driven on the off-road terrain, it is necessary to consider the vehicle's stability. This paper suggests a path tracking controller for simulation of real-time vehicle stability analysis. The path tracking controller uses the preview distance to track the given trajectory. The disturbance moment is estimated using the yaw moment observer, and this information is used for compensation in the yaw moment control. On a curved path, the vehicle's desired velocity is determined from the curvature of the path. Because the vehicle is equipped with six independent motor driven wheels, the driving torques are distributed on all the wheels. The effectiveness of the path tracking controller is verified using ADAMS/MATLAB co-simulation.

A Moving Path Control of an Automatic Guided Vehicle Using Relative Distance Fingerprinting (상대거리 지문 정보를 이용한 무인이송차량의 주행 경로 제어)

  • Hong, Youn Sik;Kim, Da Jung;Hong, Sang Hyun
    • KIPS Transactions on Computer and Communication Systems
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    • v.2 no.10
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    • pp.427-436
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    • 2013
  • In this paper, a method of moving path control of an automatic guided vehicle in an indoor environment through recognition of marker images using vision sensors is presented. The existing AGV moving control system using infrared-ray sensors and landmarks have faced at two critical problems. Since there are many windows in a crematorium, they are going to let in too much sunlight in the main hall which is the moving area of AGVs. Sunlight affects the correct recognition of landmarks due to refraction and/or reflection of sunlight. The second one is that a crematorium has a narrow indoor environment compared to typical industrial fields. Particularly when an AVG changes its direction to enter the designated furnace the information provided by guided sensors cannot be utilized to estimate its location because the rotating space is too narrow to get them. To resolve the occurrences of such circumstances that cannot access sensing data in a WSN environment, a relative distance from marker to an AGV will be used as fingerprinting used for location estimation. Compared to the existing fingerprinting method which uses RSS, our proposed method may result in a higher reliable estimation of location. Our experimental results show that the proposed method proves the correctness and applicability. In addition, our proposed approach will be applied to the AGV system in the crematorium so that it can transport a dead body safely from the loading place to its rightful destination.

Lane Detection Algorithm with Bhattacharrya Distance (바타차야 거리를 이용한 차선 검출 알고리즘)

  • Han, Jae-Ho;Lee, Chul-Hee
    • Proceedings of the Korea Information Processing Society Conference
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    • 2017.11a
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    • pp.899-900
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    • 2017
  • 본 논문에서는 도로주행 영상 내에서 차선을 검출하는 알고리즘을 제안한다. 제안하는 알고리즘은 차량 내부 카메라로 촬영된 영상에 대하여 바타차야 거리를 이용해 차선 후보 영역을 검출한다. 검출된 영역에 대해 도로와 차선의 레퍼런스 RGB 값과의 바타차야 거리를 이용해 분류한 뒤, 차선이 갖는 특징을 모델링하여, 분류된 영역에서 차선으로 추정되는 영역만을 남긴다. 차선 영역 세그먼트의 흰 차선과 노란 차선의 클래스와의 유사도를 계산하여 검출된 차선정보를 제공한다.

Analysis of Car Following Model of Adaptive Cruise Controlled Vehicle Considering the Road Conditions According to Weather Circumstance (기상상황에 따른 노면상태를 고려한 첨단차량 추종거동 모형의 분석)

  • Kim, Tae-Uk;Bae, Sang-Hoon
    • The Journal of The Korea Institute of Intelligent Transport Systems
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    • v.12 no.3
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    • pp.53-64
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    • 2013
  • The car-following model is one of core models in Advanced Vehicle & Highway Systems (AVHS). The car-following model has been developed in aspects such as human factor and reduction error rates. However, the consideration of safety depending on weather condition has not been completed yet. In this paper, therefore, changes of driving condition for car-following due to different road condition were dealt with, and optimal safety distance corresponding to road condition such as dry, wet and snowy were computed. The GMIT(GM Model with Instantaneous T) model was picked over for simulation of adaptive cruise control applied the suggested optimal safety distance. As the results, the 1.7 times longer safety distance was required for wet road condition than dry road condition, and the 5.6 times longer safety distance was required for snowy road condition.