조건부 자율주행자동차 (Level 3)에서 차량 내 터치스크린 위치와 비운전 과업 난이도가 운전 성능, 시각 집중 패턴, 인지 부하에 미치는 영향에 대한 연구: 비운전 과업과 제어권 전환 과업 중심으로

학위논문(석사) -- 서울대학교대학원 : 공과대학 산업공학과, 2023. 2. 박우진.This thesis aimed to investigate the effects of non-driving related task (NDRT) in-vehicle touchscreen location and NDRT difficulty level on the driver's NDRT, take-over task performance, and subjective workload in a highly automated vehicle. Despite of the increasing use of in-vehicle touchscreen in the context of automated driving, little empirical evidence is available that investigates human interaction with in-vehicle touchscreen interface during automated driving. The three NDRT in-vehicle touchscreen and two difficulty levels of NDRT were employed. The dependent measures were the following: NDRT and take-over task performance, eye gaze behavior, and subjective workload. The study has found significant effects of NDRT in-vehicle touchscreen location on all the dependent measures. The results indicated that Upper Right was found to be the best NDRT touchscreen location in terms of take-over performance. However, regarding the NDRT performance, Lower Right was found to be the best NDRT touchscreen location. Moreover, it showed that as the difficulty level of NDRT increases, it impairs the drivers' performance of NDRT and subjective workload. When comparing the three different NDRT in-vehicle touchscreen locations, the NDRT in-vehicle touchscreen is located closer to the windscreen appears to be optimal in reacting to critical situations; however, it is also necessary to consider NDRT touchscreen location from the perspective of the drivers' non-driving activities, particularly in the context of highly automated vehicles where the drivers are expected to perform NDRT. The study findings may help to determine the placement of onboard NDRT touchscreen for the presentation of information related to non-driving activities in a highly automated vehicle.본 논문에서는 고도화된 자율주행자동차에서 비운전 과업과 제어권 전환 과업을 수행할 때 적절한 비운전 과업 터치스크린 위치와 비운전 과업 난이도에 대해 알아보고자 한다. 고도화된 자율주행자동차에서는 운전자가 운전이 아닌 비운전 과업을 주로 수행하게 된다. 특히, 운전자가 자동차 내의 터치스크린을 통해 비운전 과업을 주로 수행하는 환경을 고려하였을 때, 운전자가 차량 내 터치스크린을 통해 편안하게 비주행 과업을 수행하는 것은 중요하다. 더불어, 비운전 과업을 수행하면서 때때로 발생하게 될 제어권 전환에도 안전하게 제어권 전환 과업 수행해야 한다. 운전자의 안전과 편안함을 동시에 고려하는 적절한 비운전 과업 터치스크린 위치와 비운전 과업 난이도에 대해 연구한 기존 논문이 없는 바, 본 논문에서는 서로 다른 터치스크린 위치 3곳과 2가지의 비운전 과업 난이도에 대해 운전자의 비운전 과업 성능과 운전 성능을 비교한다. 이에 대한 결과로 본 논문에서는 비운전 과업과 제어권 전환 과업 각각에 대해 운전자의 인지적, 신체적 부하를 줄이면서 동시에 안전한 운전에 적절한 비운전 과업 터치스크린 위치와 비운전 과업 난이도에 대한 설계 가이드라인을 제공한다.Chapter 1 Introduction 1 1.1 Research Background 1 1.2 Literature Review 2 1.3 Research Objective and Questions 5 Chapter 2 Method 7 2.1 Participants 7 2.2 Apparatus 7 2.3 Experiment 11 2.4 Experimental variables 17 2.5 Statistical analysis 20 Chapter 3 Results 21 3.1 NDRT Performance measures 21 3.2 Eye gaze behavior measures (NDRT phase) 25 3.3 Subjective experience measures (NDRT phase) 28 3.4 Take-over task performance measures 37 3.5 Eye gaze behavior measures (take-over task phase) 40 3.6 Subjective experience measures (take-over task phase) 42 Chapter 4 Discussion 45 4.1 NDRT performance measures 45 4.2 Take-over performance measures 50 Chapter 5 Conclusion 53 5.1 Summary and Implications 53 5.2 Future Research Directions 54 Bibliography 57 국문초록 65석

Information requirements for future HMI in partially automated vehicles

Partially automated vehicles are increasing in prevalence and enable drivers to hand over physical control of the vehicle’s longitudinal and latitudinal control to the automated system. However, at this partial level of automation, drivers will still be required to continuously monitor the vehicle’s operation and take back control at any time from the system when required. The Society of Automotive Engineers (SAE) defines this as Level 2 automation and consequently a number of design implications arise. To support the driver in the monitoring task, Level 2 vehicles today present a variety of information about sensor readings and operational issues to keep the driver informed; so appropriate action can be taken when required. However, existing research has shown that current Level 2 HMIs increase the cognitive workload, leading to driver cognitive disengagement and hence increasing the risk to safety. However, despite this knowledge, these Level 2 systems are available on the road today and little is known about what information should be presented to drivers inside these systems. Hence, this doctorate aimed to deliver design recommendations on how HMIs can more appropriately support the driver in the use of a partially automated Level 2 (or higher) vehicle system. Four studies were designed and executed for this doctorate. Study 1 aimed to understand the information preferences for drivers in a Level 2 vehicle using semi-structured interviews. Participants were exposed to a 10 minute, Level 2 driving simulation. A total of 25 interviews were conducted for first study. Using thematic analysis, two categories of drivers: ‘High Information Preference’ (HIP) and ‘Low Information Preference’ (LIP) were developed. It was evident that the drivers' expectations of the partial automation capability differed, affecting their information preferences and highlighting the challenge of what information should be presented inside these vehicles. Importantly, by defining these differing preferences, HMI designers can be more informed to design effective HMI, regardless of the driver’s predisposition. Building on this, an Ideas Café public engagement event was designed for Study 2; implementing a novel methodology to understand factors of trust in automated vehicles. Qualitative data gathered from the 35 event attendees was analysed using thematic analysis. The results reaffirmed the importance of the information presented in automated vehicles. Based on these first two studies, it was evident that there was an opportunity to develop a more robust understanding of what information is required in a Level 2 vehicle. Information requirements were quantitatively investigated through two eye-tracking studies (Studies 3 and 4). Both used a novel three- or five-day longitudinal study design. A shortlist of nine types of information was developed based on the results from the first two studies, regulatory standards and collaborations with Jaguar Land Rover experts. This was the first shortlist of its kind for automated vehicles. These 9 information types were presented to participants and eye tracking was used to record their information usage during Level 2 driving. Study 3 involved 17 participants and displayed only steady state scenarios. Study 4 involved 27 participants and introduced handover and warning events. Across both studies, information usage changed significantly, highlighting the methodological importance of longitudinal testing over multiple exposures. Participants increased their usage of information confirming the vehicle’s current state technical competence. In comparison, usage decreased of future state information that could help predict the future actions of the vehicle. By characterising the change in information usage, HMI designers can now ensure important information is designed appropriately. Notably, the ‘Action Explanation’ information, that described what the vehicle was doing and why, was found to be consistently the most used information. To date, this type of information has not been observed on any existing Level 2 HMI. Results from all four studies was synthesised to develop novel design recommendations for the information required inside Level 2 vehicles, and how this should be adapted over time depending on the driver’s familiarity with the system and driving events. This doctorate has contributed novel design recommendations for Level 2 vehicles through an innovative methodological approach across four studies. These design recommendations can now be taken forward to design and test new HMIs that can create a better, safer experience for future automated vehicles