• Title/Summary/Keyword: Driving environment

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Development of Advanced FMTC Virtual Driving Environment for Autonomous Driving System Development (자율주행시스템 개발을 위한 FMTC 가상주행환경 고도화 개발)

  • Beenhui, Lee;Kwanhoe, Huh;Hyojin, Lee;Jangu, Lee;Jongmin, Yoon;Seongwoo, Cho
    • Journal of Auto-vehicle Safety Association
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    • v.14 no.4
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    • pp.60-69
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    • 2022
  • Recently, the importance of simulation validation in a virtual environment for autonomous driving system validation is increasing. At the same time, interest in the advancement of the virtual driving environment is also increasing. To develop autonomous driving technology, a simulation environment similar to the real-world environment is needed. For this reason, not only the road model is configured in the virtual driving environment, but also the driving environment configuration that includes the surrounding environments -traffic, object, etc- is necessary. In this article, FMTC, which is a test bed for autonomous vehicles, is implemented in a virtual environment and advanced to form a virtual driving environment similar to that of real FMTC. In addition, the similarity of the virtual driving environment is verified through comparative analysis with the real FMTC.

Development of Autonomous Driving System Verification Environment through Advancement of K-City Virtual Driving Environment (K-City 가상주행환경 고도화를 통한 자율주행시스템 검증 환경 구축)

  • Beenhui Lee;Kwanhoe Huh;Jangu Lee;Namwoo Kim;Jongmin Yoon;Seonwoo Cho
    • Journal of Auto-vehicle Safety Association
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    • v.15 no.1
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    • pp.16-26
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    • 2023
  • Recently, the importance of simulation in a virtual driving environment as well as real road-based tests for autonomous vehicle testing is increasing. Real road tests are being actively conducted at K-City, an autonomous driving test bed located at the Korea Automobile Safety Test & Research Institute of the Transportation Safety Authority. In addition, the need to advance the K-City virtual driving environment and build a virtual environment similar to the autonomous driving system test environment in real road tests is increasing. In this study, for K-City of Korea Automobile Safety Test & Research Institute, using detailed drawings and actual field data, K-City virtual driving environment was advanced, and similarity verification was verified through comparative analysis with actual K-City.

Multi-Vehicle Environment Simulation Tool to Develop and Evaluate Automated Driving Systems in Motorway (고속도로에서의 자율주행 알고리즘 개발 및 평가를 위한 다차량 시뮬레이션 환경 개발)

  • Lee, Hojoon;Jeong, Yonghwan;Min, Kyongchan;Lee, Myungsu;Shin, Jae Kon;Yi, Kyongsu
    • Journal of Auto-vehicle Safety Association
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    • v.8 no.4
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    • pp.31-37
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    • 2016
  • Since real road experiments have many restrictions, a multi-vehicle traffic simulator can be an effective tool to develop and evaluate fully automated driving systems. This paper presents multi-vehicle environment simulation tool to develop and evaluate motorway automated driving systems. The proposed simulation tool consists of following two main parts: surrounding vehicle model and environment sensor model. The surrounding vehicle model is designed to quickly generate rational complex traffic situations of motorway. The environment sensor model depicts uncertainty of environment sensor. As a result, various traffic situations with uncertainty of environment sensor can be proposed by the multi-vehicle environment simulation tool. An application to automated driving system has been conducted. A lane changing algorithm is evaluated by performance indexes from the multi-vehicle environment simulation tool.

Development of Simulation Environment for Autonomous Driving Algorithm Validation based on ROS (ROS 기반 자율주행 알고리즘 성능 검증을 위한 시뮬레이션 환경 개발)

  • Kwak, Jisub;Yi, Kyongsu
    • Journal of Auto-vehicle Safety Association
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    • v.14 no.1
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    • pp.20-25
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    • 2022
  • This paper presents a development of simulation environment for validation of autonomous driving (AD) algorithm based on Robot Operating System (ROS). ROS is one of the commonly-used frameworks utilized to control autonomous vehicles. For the evaluation of AD algorithm, a 3D autonomous driving simulator has been developed based on LGSVL. Two additional sensors are implemented in the simulation vehicle. First, Lidar sensor is mounted on the ego vehicle for real-time driving environment perception. Second, GPS sensor is equipped to estimate ego vehicle's position. With the vehicle sensor configuration in the simulation, the AD algorithm can predict the local environment and determine control commands with motion planning. The simulation environment has been evaluated with lane changing and keeping scenarios. The simulation results show that the proposed 3D simulator can successfully imitate the operation of a real-world vehicle.

Development of Vehicle Environment for Real-time Driving Behavior Monitoring System (실시간 운전 특성 모니터링 시스템을 위한 차량 환경 개발)

  • Kim, Man-Ho;Son, Joon-Woo;Lee, Yong-Tae;Shin, Sung-Heon
    • Journal of the Ergonomics Society of Korea
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    • v.29 no.1
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    • pp.17-24
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    • 2010
  • There has been recent interest in intelligent vehicle technologies, such as advanced driver assistance systems (ADASs) or in-vehicle information systems (IVISs) that offer a significant enhancement of safety and convenience to drivers and passengers. However, unsuitable design of HMI (Human Machine Interface) must increase driver distraction and workload, which in turn increase the chance of traffic accidents. Distraction in particular often occurs under a heavy driving workload due to multitasking with various electronic devices like a cell phone or a navigation system while driving. According to the 2005 road traffic accidents in Korea report published by the ROad Traffic Authority (ROTA), more than 60% of the traffic accidents are related to driver error caused by distraction. This paper suggests the structure of vehicle environment for real-time driving behavior monitoring system while driving which is can be used the driver workload management systems (DWMS). On-road experiment results showed the feasibility of the suggested vehicle environment for driving behavior monitoring system.

Independent Object based Situation Awareness for Autonomous Driving in On-Road Environment (도로 환경에서 자율주행을 위한 독립 관찰자 기반 주행 상황 인지 방법)

  • Noh, Samyeul;Han, Woo-Yong
    • Journal of Institute of Control, Robotics and Systems
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    • v.21 no.2
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    • pp.87-94
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    • 2015
  • This paper proposes a situation awareness method based on data fusion and independent objects for autonomous driving in on-road environment. The proposed method, designed to achieve an accurate analysis of driving situations in on-road environment, executes preprocessing tasks that include coordinate transformations, data filtering, and data fusion and independent object based situation assessment to evaluate the collision risks of driving situations and calculate a desired velocity. The method was implemented in an open-source robot operating system called ROS and tested on a closed road with other vehicles. It performed successfully in several scenarios similar to a real road environment.

Effects of Driving Environment on Driver's Posture (주행중 운전자세 측정을 통한 주행조건 영향 분석)

  • Kim, Taeil;Choi, Kwangsoo;Jung, Eui S.;Park, Sungjoon;Choi, Jaeho
    • Journal of Korean Institute of Industrial Engineers
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    • v.29 no.4
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    • pp.271-282
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    • 2003
  • Automotive occupant packaging has been a part of main ergonomics interests, especially, in terms of driver's posture. Previous research on driver's posture has mainly focused on the initial optimal posture for driving sedans. However, customer preferences on cars are shifting from sedans to RV and automobile manufacturing companies seek to understand temporal changes in drivers' posture according to driving environment. So the main aim of this study was to develop a driver's posture measurement system during driving and investigate casual changes due to duration, car type, traffic flow. Four male drivers participated in the experiments during one week. It was shown that considerable changes in their postures were caused with respect to driving environment, which implies that not only static optimal postures but their dynamic changes should be taken into consideration for proper design and evaluation of interior packaging. The research is expected to help packaging designers understand human drivers so as to improve their comfort.

Construction of Roads for Vehicle Simulator Using GIS Map (GIS 데이터를 이용한 차량 시뮬레이터용 도로 구축에 관한 연구)

  • 임형은;성원석;황원걸;주승원
    • Journal of the Korean Society for Precision Engineering
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    • v.21 no.4
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    • pp.88-94
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    • 2004
  • Recently, vehicle simulators are widely used to evaluate driver's responses and driver assistance systems. It needs much effort to construct the virtual driving environment for a vehicle simulator. In this study, it is described how to make effectively the roads and the driving environment for a vehicle simulator. The GIS (Geographic Information System) is used to construct the roads and the environment effectively. Because the GIS is the integrated system of geographical data, it contains useful data to make virtual driving environment. First, the outline and centerline of roads is abstracted from the GIS. From the road outline, the road width is calculated. Using the centerline, the grid model of roads is constructed. The final graphic model of roads is constructed by mapping road image to the grid model according to the number of lanes and the kind of surface. Data of buildings from the GIS are abstracted. Each shape and height of buildings is determined according to kind of buildings, the final graphic model of buildings is constructed. Then, the graphic model of roadside tree is also constructed. Finally, the driving environment for driving simulator is constructed by converting the three graphic models with the graphic format of Direct-X and by joining the three graphic models.

Modeling of Roads for Vehicle Simulator Using GIS Map Data

  • Im Hyung-Eun;Sung Won-Suk;Hwang Won-Gul;Ichiro Kageyama
    • International Journal of Precision Engineering and Manufacturing
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    • v.6 no.4
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    • pp.3-7
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    • 2005
  • Recently, vehicle simulators are widely used to evaluate driver s responses and driver assistance systems. It needs much effort to construct the virtual driving environment for a vehicle simulator. In this study, it is described how to make effectively the roads and the driving environment for a vehicle simulator. GIS (Geographic Information System) is used to construct the roads and the environment effectively. Because the GIS is the integrated system of geographical data, it contains useful data to make virtual driving environment. First, boundaries and centerlines of roads are extracted from the GIS. From boundaries, the road width is calculated. Using centerlines, mesh models of roads are constructed. The final graphic model of roads is constructed by mapping road images to those mesh models considering the number of lanes and the kind of surface. Data of buildings from the GIS are extracted. Each shape and height of building is determined considering the kind of building to construct the final graphic model of buildings. Then, the graphic model of roadside trees is constructed to decide their locations. Finally, the driving environment for driving simulator is constructed by converting the three graphic models with the graphic format of Direct-X and by joining the three graphic models.

Driver Characteristics and Workload according to Changing Driving Environment and Types of Steering Wheel (도로 주행환경 변화와 핸들종류에 따른 운전자 부하 및 행동특성)

  • Jeon, Yong-Wook;Daimon, Tatsuru
    • Journal of the Ergonomics Society of Korea
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    • v.28 no.2
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    • pp.9-16
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    • 2009
  • The aim of this study was to evaluate the effects of the driving performance and workload according to changing driving environment and types of steering wheel. Twelve drivers who participated in this study consisted of two groups; six Japanese as the left-lane drivers who was accustomed to driving on left-hand side of the road, and six Europeans, Americans, and Korean as the right-lane drivers who was accustomed to driving on right-hand side of the road. They were asked to operate a driving simulator while using two different types of steering wheel (for the left-hand side driving and the right-hand side driving). During the experiment, a range of data were measured including driving performance, mental workload, and eye movements which were recorded in order to identify the amount of time looking towards the in-vehicle route guidance. Results indicated that the use of the steering wheel by parallel moving led to increase high attentional demand and worse glance behavior to traffic signs for the left-lane drivers. In the case of the right-lane drivers, the effects by changing driving direction were more effective than the types of steering wheel due to their habit or traits.