자율주행기술이 교통류에 미치는 영향을 분석하기 위해서는 자율차와 비자율차 간의 상호작용을 분석하는 것이 중요한 이슈이다. 특히 자율주행기술을 활용한 유용한 서비스 중의 하나인 군집주행은 주변의 비자율 차량의 주행행태에 영향을 미칠 수 있다. 본 연구의 목적은 군집주행 환경에서 비자율차의 차로변경행태 분석하는 것이며, 3단계의 실험 및 조사를 수행하였다. 1단계 영상기반 인지특성 분석을 통해 군집주행 환경에서 어떠한 반응행태를 보일 것인지를 조사하였으며, 2단계 주행시뮬레이션 실험을 통해 비자율차의 차로변경행태를 분석하였다. 차로변경행태를 분석하기 위해 차로변경시간과 교통류의 안전성을 나타낼 수 있는 지표인 가속소음을 이용하였으며, 자율차의 시스템 보급률(Market Penetration Rate, MPR)과 피실험자 인적요소에 따른 비자율차의 주행행태 차이를 비교 분석하였다. 마지막 단계인 NASA-TLX(NASA Task Load Index)를 통해 비자율차 운전자의 작업부하를 평가하였다. 분석결과 군집차량군 주변의 비자율차 운전자는 심리적인 부담감을 느끼며, MPR이 증가할수록 차로변경시간이 길어지고 30-40대 운전자 또는 여성 운전자의 경우 안전성이 낮아지는 것으로 나타났다. 본 연구에서 도출된 결과는 자율차와 비자율차의 상호작용을 반영한 보다 현실성 높은 교통시뮬레이션 실험 시 기초자료로 활용될 수 있고, 이를 기반으로 자율협력주행 환경에서 적용 가능한 교통운영관리전략 수립을 효과적으로 지원할 것으로 기대된다.
자율주행기술이 교통류에 미치는 영향을 분석하기 위해서는 자율차와 비자율차 간의 상호작용을 분석하는 것이 중요한 이슈이다. 특히 자율주행기술을 활용한 유용한 서비스 중의 하나인 군집주행은 주변의 비자율 차량의 주행행태에 영향을 미칠 수 있다. 본 연구의 목적은 군집주행 환경에서 비자율차의 차로변경행태 분석하는 것이며, 3단계의 실험 및 조사를 수행하였다. 1단계 영상기반 인지특성 분석을 통해 군집주행 환경에서 어떠한 반응행태를 보일 것인지를 조사하였으며, 2단계 주행시뮬레이션 실험을 통해 비자율차의 차로변경행태를 분석하였다. 차로변경행태를 분석하기 위해 차로변경시간과 교통류의 안전성을 나타낼 수 있는 지표인 가속소음을 이용하였으며, 자율차의 시스템 보급률(Market Penetration Rate, MPR)과 피실험자 인적요소에 따른 비자율차의 주행행태 차이를 비교 분석하였다. 마지막 단계인 NASA-TLX(NASA Task Load Index)를 통해 비자율차 운전자의 작업부하를 평가하였다. 분석결과 군집차량군 주변의 비자율차 운전자는 심리적인 부담감을 느끼며, MPR이 증가할수록 차로변경시간이 길어지고 30-40대 운전자 또는 여성 운전자의 경우 안전성이 낮아지는 것으로 나타났다. 본 연구에서 도출된 결과는 자율차와 비자율차의 상호작용을 반영한 보다 현실성 높은 교통시뮬레이션 실험 시 기초자료로 활용될 수 있고, 이를 기반으로 자율협력주행 환경에서 적용 가능한 교통운영관리전략 수립을 효과적으로 지원할 것으로 기대된다.
Analysis of the interaction between the automated vehicles and manual vehicles is very important in analyzing the performance of automated cooperative driving environments. In particular, the automated vehicle platooning can affect the driving behavior of adjacent manual vehicles. The purpose of thi...
Analysis of the interaction between the automated vehicles and manual vehicles is very important in analyzing the performance of automated cooperative driving environments. In particular, the automated vehicle platooning can affect the driving behavior of adjacent manual vehicles. The purpose of this study is to analyze the lane change behavior of the manual vehicles in automated vehicle platonning environment and to conduct the experiment and questionnaire surveys in three stages. In the first stage, a video questionnaire survey was conducted, and responsive behaviors of manual vehicles were investigated. In second stage, the driving simulator experiments were conducted to investigate the lane change behaviors of in automated vehicle platonning environments. To analyze the lane change behavior of the manual vehicles, lane change durations and acceleration noise, which are indicators of traffic flow stability, were used. The driving behavior of manual vehicles were compared across different market penetration rates (MPR) of automated vehicles and human factors. Lastly, NASA-TLX (NASA Task Load Index) was used to evaluate the workload of the manual vehicle drivers. As a result of the analysis, it was identified that manual vehicle drivers had psychological burdens while driving in automated vehicle platonning environments. Lane change durations were longer when the MPR of the automated vehicles increased, and acceleration noise were increased in the case of 30-40 years old or female drivers. The results from this study can be used as a fundamental for more realistic traffic simulations reflecting the interaction between the automated vehicles and manual vehicles. It is also expected to effectively support the establishment of valuable transportation management strategy in automated vehicle environments.
Analysis of the interaction between the automated vehicles and manual vehicles is very important in analyzing the performance of automated cooperative driving environments. In particular, the automated vehicle platooning can affect the driving behavior of adjacent manual vehicles. The purpose of this study is to analyze the lane change behavior of the manual vehicles in automated vehicle platonning environment and to conduct the experiment and questionnaire surveys in three stages. In the first stage, a video questionnaire survey was conducted, and responsive behaviors of manual vehicles were investigated. In second stage, the driving simulator experiments were conducted to investigate the lane change behaviors of in automated vehicle platonning environments. To analyze the lane change behavior of the manual vehicles, lane change durations and acceleration noise, which are indicators of traffic flow stability, were used. The driving behavior of manual vehicles were compared across different market penetration rates (MPR) of automated vehicles and human factors. Lastly, NASA-TLX (NASA Task Load Index) was used to evaluate the workload of the manual vehicle drivers. As a result of the analysis, it was identified that manual vehicle drivers had psychological burdens while driving in automated vehicle platonning environments. Lane change durations were longer when the MPR of the automated vehicles increased, and acceleration noise were increased in the case of 30-40 years old or female drivers. The results from this study can be used as a fundamental for more realistic traffic simulations reflecting the interaction between the automated vehicles and manual vehicles. It is also expected to effectively support the establishment of valuable transportation management strategy in automated vehicle environments.
, 2015). 그러나 자율협력주행환경에서 비자율차의 주행행태를 분석한 연구는 미흡하였으며, 특히 횡방향 주행행태를 분석한 연구는 부재한 상황이다.
NASATLX에서 평가하는 6가지 주관적 요소는 무엇인가?
정신적 작업부하를 주관적으로 평가하는 도구로 NASA-TLX,SWAT(Subjective Workload Assessment Technique), Cooper-Harper Scale 등이 사용되며, 본 연구에서는 측정대상에 대한 높은 신뢰성과 항공교통부분에서 광범위하게 사용되고 있는 NASA-TLX를 이용하였다. NASATLX는 정신적 요구(mental demand), 신체적 요구(physical demand), 시간적 요구(temporal demand), 임무성취감(performance), 노력수준(effort), 좌절감(frustration)의 6가지 영역에 대한 주관적 요소를 평가하며, 가중치를 적용하여 작업부하 점수를 도출할 수 있다(Kim et al., 2010; Jeon et al.
NASA-TLX 설문조사란 무엇인가?
NASA-TLX 설문조사는 대형 시스템에서 작업수행시 요구되는 작업부하 평가를 위하여 미국 항공우주국에서 개발한 방법으로 본 연구에서는 군집주행 환경에서 운전자의 작업부하(Workload)를 평가하기 위한 목적으로 주행 시뮬레이션 실험 후 진행되었다. NASA-TLX는 Task에 대한 작업부하를 평가하기 위한 방법론으로 본 실험에서는 군집주행환경에서 차로변경 Task에 대한 피실험자의 작업부하를 평가하였다.
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