• Title/Summary/Keyword: Autonomous Driving Simulator

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Effects of Agent Interaction on Driver Experience in a Semi-autonomous Driving Experience Context - With a Focus on the Effect of Self-Efficacy and Agent Embodiment - (부분자율주행 체험환경에서 에이전트 인터랙션 방식이 운전자 경험에 미치는 영향 - 자기효능감과 에이전트 체화 효과를 중심으로 -)

  • Lee, Jeongmyeong;Joo, Hyehwa;Choi, Junho
    • The Journal of the Convergence on Culture Technology
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    • v.5 no.1
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    • pp.361-369
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    • 2019
  • With the commercialization of the ADAS functions, the need for the experience of the autonomous driving system is increasing, and the role of the artificial intelligence agent is attracting attention. This study is an autonomous driving experience experiment that verifies the effect of self-efficacy and agent embodiment. Through a simulator experiment, we measured the effect of existence of self-efficacy and agent embodiment on social presence, perceived risk, and perceived ease of use. Results show that self-efficacy had a positive effect on social presence and perceived risk, and agent embodiment negatively affected perceived ease of use. Based on the results of the study, we proposed guidelines for agent design that can increase the acceptance of the semi-autonomous driving system.

Driving behavior Analysis to Verify the Criteria of a Driver Monitoring System in a Conditional Autonomous Vehicle - Part II - (부분 자율주행자동차의 운전자 모니터링 시스템 안전기준 검증을 위한 운전 행동 분석 -2부-)

  • Son, Joonwoo;Park, Myoungouk
    • Journal of Auto-vehicle Safety Association
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    • v.13 no.1
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    • pp.45-50
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    • 2021
  • This study aimed to verify the criteria of the driver monitoring systems proposed by UNECE ACSF informal working group and the ministry of land, infrastructure, and transport of South Korea using driving behavior data. In order to verify the criteria, we investigated the safety regulations of driver monitoring systems in a conditional autonomous vehicle and found that the driver monitoring measures were related to eye blinks times, head movements, and eye closed duration. Thus, we took two different experimental data including real-world driving and simulator-based drowsy driving behaviors in previous studies. The real-world driving data were used for analyzing blink times and head movement intervals, and the drowsiness data were used for eye closed duration. In the drowsy driving study, 10 drivers drove approximately 37 km of a monotonous highway (about 22 min) twice. The results suggested that the appropriate duration of eyes continuously closed was 4 seconds. The results from real-world driving data were presented in the other paper - part 1.

Driving behavior Analysis to Verify the Criteria of a Driver Monitoring System in a Conditional Autonomous Vehicle - Part I - (부분 자율주행자동차의 운전자 모니터링 시스템 안전기준 검증을 위한 운전 행동 분석 -1부-)

  • Son, Joonwoo;Park, Myoungouk
    • Journal of Auto-vehicle Safety Association
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    • v.13 no.1
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    • pp.38-44
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    • 2021
  • This study aimed to verify the criteria of the driver monitoring systems proposed by UNECE ACSF informal working group and the ministry of land, infrastructure, and transport of South Korea using driving behavior data. In order to verify the criteria, we investigated the safety regulations of driver monitoring systems in a conditional autonomous vehicle and found that the driver monitoring measures were related to eye blinks times, head movements, and eye closed duration. Thus, we took two different experimental data including real-world driving and simulator-based drowsy driving behaviors in previous studies. The real-world driving data were used for analyzing blink times and head movement intervals, and the drowsiness data were used for eye closed duration. In the real-world driving study, 52 drivers drove approximately 11.0 km of rural road (about 20 min), 7.9 km of urban road (about 25 min), and 20.8 km of highway (about 20 min). The results suggested that the appropriate number of blinks during the last 60 seconds was 4 times, and the head movement interval was 35 seconds. The results from drowsy driving data will be presented in another paper - part 2.

Development of Throttle and Brake Controller for Autonomous Vehicle Simulation Environment (자율주행 시뮬레이션 환경을 위한 차량 구동 및 제동 제어기 개발)

  • Kwak, Jisub;Yi, Kyongsu
    • Journal of Auto-vehicle Safety Association
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    • v.14 no.1
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    • pp.39-44
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    • 2022
  • This paper presents a development of throttle and brake controller for autonomous vehicle simulation environment. Most of 3D simulator control autonomous vehicle by throttle and brake command. Therefore additional longitudinal controller is required to calculate pedal input from desired acceleration. The controller consists of two parts, feedback controller and feedforward controller. The feedback controller is designed to compensate error between the actual acceleration and desired acceleration calculated from autonomous driving algorithm. The feedforward controller is designed for fast response and the output is determined by the actual vehicle speed and desired acceleration. To verify the performance of the controller, simulations were conducted for various scenarios, and it was confirmed that the controller can successfully follow the target acceleration.

The Effect of Autonomous Driving Vehicle Positive Notification on Situation Awareness and Take-over Performance (자율주행 차량의 안전한 상태 알림이 제어권 전환 시 상황 인식과 운전 수행에 미치는 영향)

  • Ji, JaeYeong;Kim, JayHee;Han, KwangHee
    • The Journal of the Convergence on Culture Technology
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    • v.7 no.4
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    • pp.641-652
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    • 2021
  • Drivers have willing to do secondary tasks in situations deemed safe autonomous driving. I studied that positive notifications for secure areas could improve situation awareness and driving performance after TOR(Take over request) in autonomous driving. Comparing TOR alert only and monitoring alert conditions, participants in the positive notification condition showed higher situation awareness and driving performance. Also, in emotional assessment, the positive notification condition showed higher positive evaluation than other conditions. Due to Covid-19, I designed experiments separate online with driving videos in experiment 1 and offline using a driving simulator in experiment 2. This study has implications that presented a different perspective on autonomous driving notification design.

Technology Acceptance Modeling based on User Experience for Autonomous Vehicles

  • Cho, Yujun;Park, Jaekyu;Park, Sungjun;Jung, Eui S.
    • Journal of the Ergonomics Society of Korea
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    • v.36 no.2
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    • pp.87-108
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    • 2017
  • Objective: The purpose of this study was to precede the acceptance study based on automation steps and user experience that was lacked in the past study on the core technology of autonomous vehicle, ADAS. The first objective was to construct the acceptance model of ADAS technology that is the core technology, and draw factors that affect behavioral intention through user experience-based evaluation by applying driving simulator. The second one was to see the change of factors on automation step of autonomous vehicle through the UX/UA score. Background: The number of vehicles with the introduction of ADAS is increasing, and it caused change of interaction between vehicle and driver as automation is being developed on the particular drive factor. For this reason, it is becoming important to study the technology acceptance on how driver can actively accept giving up some parts of automated drive operation and handing over the authority to vehicle. Method: We organized the study model and items through literature investigation and the scenario according to the 4 stages of automation of autonomous vehicle, and preceded acceptance assessment using driving simulator. Total 68 men and woman were participated in this experiment. Results: We drew results of Performance Expectancy (PE), Social Influence (SI), Perceived Safety (PS), Anxiety (AX), Trust (T) and Affective Satisfaction (AS) as the factors that affect Behavioral Intention (BI). Also the drawn factors shows that UX/UA score has a significant difference statistically according to the automation steps of autonomous vehicle, and UX/UA tends to move up until the stage 2 of automation, and at stage 3 it goes down to the lowest level, and it increases a little or stays steady at stage 4. Conclusion and Application: First, we presented the acceptance model of ADAS that is the core technology of autonomous vehicle, and it could be the basis of the future acceptance study of the ADAS technology as it verifies through user experience-based assessment using driving simulator. Second, it could be helpful to the appropriate ADAS development in the future as drawing the change of factors and predicting the acceptance level according to the automation stages of autonomous vehicle through UX/UA score, and it could also grasp and avoid the problem that affect the acceptance level. It is possible to use these study results as tools to test validity of function before ADAS offering company launches the products. Also it will help to prevent the problems that could be caused when applying the autonomous vehicle technology, and to establish technology that is easily acceptable for drivers, so it will improve safety and convenience of drivers.

Preference of Center Information Display Size and Location-based on Autonomous Driving Level (자율주행 단계별 센터페시아 디스플레이 크기 및 위치에 대한 선호도)

  • Kwon, Ju Yeong;Jeong, So Yon;Ju, Da Young
    • Journal of the HCI Society of Korea
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    • v.14 no.1
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    • pp.45-52
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    • 2019
  • As the requirement of the in vehicle infotainment service increases, the role of the in vehicle display is also expected to rise. Particularly, center information display(CID) is expected to be actively utilized, and since the size and position of the display is anticipated to change, it is necessary to research based on the users' perspective. However, there are limited research studies that investigated the user's consciousness on the size and position of autonomous vehicle display. Herein, the purpose of this study is to identify and present the preference of the center information display's size and position on each levels of driving automation. For this, an experiment on the driving simulator was conducted using the think-aloud method. As a result, it was found that the horizontal display(12.5inch) on the top position was the most preferred in the second level of the driving automation. On level three, the participants significantly preferred the vertical display(17inches) compared to the second level. This study is significant since it conducted an empirical study which examines the user' preference of CID using a driving simulator for the autonomous vehicle.

Study on Map Building Performance Using OSM in Virtual Environment for Application to Self-Driving Vehicle (가상환경에서 OSM을 활용한 자율주행 실증 맵 성능 연구)

  • MinHyeok Baek;Jinu Pahk;JungSeok Shim;SeongJeong Park;YongSeob Lim;GyeungHo Choi
    • Journal of Auto-vehicle Safety Association
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    • v.15 no.2
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    • pp.42-48
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    • 2023
  • In recent years, automated vehicles have garnered attention in the multidisciplinary research field, promising increased safety on the road and new opportunities for passengers. High-Definition (HD) maps have been in development for many years as they offer roadmaps with inch-perfect accuracy and high environmental fidelity, containing precise information about pedestrian crossings, traffic lights/signs, barriers, and more. Demonstrating autonomous driving requires verification of driving on actual roads, but this can be challenging, time-consuming, and costly. To overcome these obstacles, creating HD maps of real roads in a simulation and conducting virtual driving has become an alternative solution. However, existing HD maps using high-precision data are expensive and time-consuming to build, which limits their verification in various environments and on different roads. Thus, it is challenging to demonstrate autonomous driving on anything other than extremely limited roads and environments. In this paper, we propose a new and simple method for implementing HD maps that are more accessible for autonomous driving demonstrations. Our HD map combines the CARLA simulator and OpenStreetMap (OSM) data, which are both open-source, allowing for the creation of HD maps containing high-accuracy road information globally with minimal dependence. Our results show that our easily accessible HD map has an accuracy of 98.28% for longitudinal length on straight roads and 98.42% on curved roads. Moreover, the accuracy for the lateral direction for the road width represented 100% compared to the manual method reflected with the exact road data. The proposed method can contribute to the advancement of autonomous driving and enable its demonstration in diverse environments and on various roads.

Interactive ADAS development and verification framework based on 3D car simulator (3D 자동차 시뮬레이터 기반 상호작용형 ADAS 개발 및 검증 프레임워크)

  • Cho, Deun-Sol;Jung, Sei-Youl;Kim, Hyeong-Su;Lee, Seung-gi;Kim, Won-Tae
    • Journal of IKEEE
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    • v.22 no.4
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    • pp.970-977
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    • 2018
  • The autonomous vehicle is based on an advanced driver assistance system (ADAS) consisting of a sensor that collects information about the surrounding environment and a control module that determines the measured data. As interest in autonomous navigation technology grows recently, an easy development framework for ADAS beginners and learners is needed. However, existing development and verification methods are based on high performance vehicle simulator, which has drawbacks such as complexity of verification method and high cost. Also, most of the schemes do not provide the sensing data required by the ADAS directly from the simulator, which limits verification reliability. In this paper, we present an interactive ADAS development and verification framework using a 3D vehicle simulator that overcomes the problems of existing methods. ADAS with image recognition based artificial intelligence was implemented as a virtual sensor in a 3D car simulator, and autonomous driving verification was performed in real scenarios.

Analysis of the Influence of Road·Traffic Conditions and Weather on the Take-over of a Conditional Autonomous Vehicle (도로·교통 조건 및 기상 상황이 부분 자율주행자동차의 제어권전환에 미치는 영향 분석)

  • Park, Sungho;Yun, YongWon;Ko, Hangeom;Jeong, Harim;Yun, Ilsoo
    • The Journal of The Korea Institute of Intelligent Transport Systems
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    • v.19 no.6
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    • pp.235-249
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    • 2020
  • The Ministry of Land, Infrastructure and Transport established safety standards for Level 3 autonomous vehicles for the first time in the world in December 2019, and specified the safety standards for conditional autonomous driving systems. Accordingly, it is necessary to analyze the influence of various driving environments on take-over. In this study, using a driving simulator, we investigated how traffic conditions and weather conditions affect take-over time and stabilization time. The experimental procedure was conducted in the order of preliminary training, practice driving, and test driving, and the test driving was conducted by dividing into a traffic density and geometry experiment and a weather environment experiment. As a result of the experiment, it was analyzed that the traffic volume and weather environment did not affect the take-over time and take-over stabilization time, and only the curve radius affects take-over stabilization time.