Analysis of Disengagements in Semi-Autonomous Vehicles: Drivers’ Takeover Performance and Operational Implications

This report analyzes the reactions of human drivers placed in simulated Autonomous Technology disengagement scenarios. The study was executed in a human-in-the-loop setting, within a high-fidelity integrated car simulator capable of handling both manual and autonomous driving. A population of 40 individuals was tested, with metrics for control takeover quantification given by: i) response times (considering inputs of steering, throttle, and braking); ii) vehicle drift from the lane centerline after takeover as well as overall (integral) drift over an S-turn curve compared to a baseline obtained in manual driving; and iii) accuracy metrics to quantify human factors associated with the simulation experiment. Independent variables considered for the study were the age of the driver, the speed at the time of disengagement, and the time at which the disengagement occurred (i.e., how long automation was engaged for). The study shows that changes in the vehicle speed significantly affect all the variables investigated, pointing to the importance of setting up thresholds for maximum operational speed of vehicles driven in autonomous mode when the human driver serves as back-up. The results shows that the establishment of an operational threshold could reduce the maximum drift and lead to better control during takeover, perhaps warranting a lower speed limit than conventional vehicles. With regards to the age variable, neither the response times analysis nor the drift analysis provide support for any claim to limit the age of drivers of semi-autonomous vehicles

차량용 헤드업 디스플레이 설계에 관한 인간공학 연구

학위논문 (박사) -- 서울대학교 대학원 : 공과대학 산업공학과, 2020. 8. 박우진.Head-up display (HUD) systems were introduced into the automobile industry as a means for improving driving safety. They superimpose safety-critical information on top of the drivers forward field of view and thereby help drivers keep their eyes forward while driving. Since the first introduction about three decades ago, automotive HUDs have been available in various commercial vehicles. Despite the long history and potential benefits of automotive HUDs, however, the design of useful automotive HUDs remains a challenging problem. In an effort to contribute to the design of useful automotive HUDs, this doctoral dissertation research conducted four studies. In Study 1, the functional requirements of automotive HUDs were investigated by reviewing the major automakers' automotive HUD products, academic research studies that proposed various automotive HUD functions, and previous research studies that surveyed drivers HUD information needs. The review results indicated that: 1) the existing commercial HUDs perform largely the same functions as the conventional in-vehicle displays, 2) past research studies proposed various HUD functions for improving driver situation awareness and driving safety, 3) autonomous driving and other new technologies are giving rise to new HUD information, and 4) little research is currently available on HUD users perceived information needs. Based on the review results, this study provides insights into the functional requirements of automotive HUDs and also suggests some future research directions for automotive HUD design. In Study 2, the interface design of automotive HUDs for communicating safety-related information was examined by reviewing the existing commercial HUDs and display concepts proposed by academic research studies. Each display was analyzed in terms of its functions, behaviors and structure. Also, related human factors display design principles, and, empirical findings on the effects of interface design decisions were reviewed when information was available. The results indicated that: 1) information characteristics suitable for the contact-analog and unregistered display formats, respectively, are still largely unknown, 2) new types of displays could be developed by combining or mixing existing displays or display elements at both the information and interface element levels, and 3) the human factors display principles need to be used properly according to the situation and only to the extent that the resulting display respects the limitations of the human information processing, and achieving balance among the principles is important to an effective design. On the basis of the review results, this review suggests design possibilities and future research directions on the interface design of safety-related automotive HUD systems. In Study 3, automotive HUD-based take-over request (TOR) displays were developed and evaluated in terms of drivers take-over performance and visual scanning behavior in a highly automated driving situation. Four different types of TOR displays were comparatively evaluated through a driving simulator study - they were: Baseline (an auditory beeping alert), Mini-map, Arrow, and Mini-map-and-Arrow. Baseline simply alerts an imminent take-over, and was always included when the other three displays were provided. Mini-map provides situational information. Arrow presents the action direction information for the take-over. Mini-map-and-Arrow provides the action direction together with the relevant situational information. This study also investigated the relationship between drivers initial trust in the TOR displays and take-over and visual scanning behavior. The results indicated that providing a combination of machine-made decision and situational information, such as Mini-map-and-Arrow, yielded the best results overall in the take-over scenario. Also, drivers initial trust in the TOR displays was found to have significant associations with the take-over and visual behavior of drivers. The higher trust group primarily relied on the proposed TOR displays, while the lower trust group tended to more check the situational information through the traditional displays, such as side-view or rear-view mirrors. In Study 4, the effect of interactive HUD imagery location on driving and secondary task performance, driver distraction, preference, and workload associated with use of scrolling list while driving were investigated. A total of nine HUD imagery locations of full-windshield were examined through a driving simulator study. The results indicated the HUD imagery location affected all the dependent measures, that is, driving and task performance, drivers visual distraction, preference and workload. Considering both objective and subjective evaluations, interactive HUDs should be placed near the driver's line of sight, especially near the left-bottom on the windshield.자동차 헤드업 디스플레이는 차내 디스플레이 중 하나로 운전자에게 필요한 정보를 전방에 표시함으로써, 운전자가 운전을 하는 동안 전방으로 시선을 유지할 수 있게 도와준다. 이를 통해 운전자의 주의 분산을 줄이고, 안전을 향상시키는데 도움이 될 수 있다. 자동차 헤드업 디스플레이 시스템은 약 30년 전 운전자의 안전을 향상시키기 위한 수단으로 자동차 산업에 처음 도입된 이래로 현재까지 다양한 상용차에서 사용되고 있다. 안전과 편의 측면에서 자동차 헤드업 디스플레이의 사용은 점점 더 증가할 것으로 예상된다. 그러나 이러한 자동차 헤드업 디스플레이의 잠재적 이점과 발전 가능성에도 불구하고, 유용한 자동차 헤드업 디스플레이를 설계하는 것은 여전히 어려운 문제이다. 이에 본 연구는 이러한 문제를 해결하고, 궁극적으로 유용한 자동차 헤드업 디스플레이 설계에 기여하고자 총 4가지 연구를 수행하였다. 첫 번째 연구는 자동차 헤드업 디스플레이의 기능 요구 사항과 관련된 것으로서, 헤드업 디스플레이 시스템을 통해 어떤 정보를 제공할 것인가에 대한 답을 구하고자 하였다. 이에 주요 자동차 제조업체들의 헤드업 디스플레이 제품들과, 자동차 헤드업 디스플레이의 다양한 기능들을 제안한 학술 연구, 그리고 운전자의 정보 요구 사항들을 체계적 문헌 고찰 방법론을 통해 포괄적으로 조사하였다. 자동차 헤드업 디스플레이의 기능적 요구 사항에 대하여 개발자, 연구자, 사용자 측면을 모두 고려한 통합된 지식을 전달하고, 이를 통해 자동차 헤드업 디스플레이의 기능 요구 사항에 대한 향후 연구 방향을 제시하였다. 두 번째 연구는 안전 관련 정보를 제공하는 자동차 헤드업 디스플레이의 인터페이스 설계와 관련된 것으로, 헤드업 디스플레이 시스템을 통해 안전 관련 정보를 어떻게 제공할 것인가에 대한 답을 구하고자 하였다. 실제 자동차들의 헤드업 디스플레이 시스템에서는 어떤 디스플레이 컨셉들이 사용되었는지, 그리고 학계에서 제안된 디스플레이 컨셉들에는 어떤 것들이 있는지 체계적 문헌 고찰 방법론을 통해 검토하였다. 검토된 결과는 각 디스플레이의 기능과 구조, 그리고 작동 방식에 따라 정리되었고, 관련된 인간공학적 디스플레이 설계 원칙과 실험적 연구 결과들을 함께 검토하였다. 검토된 결과를 바탕으로 안전 관련 정보를 제공하는 자동차 헤드업 디스플레이의 인터페이스 설계에 대한 향후 연구 방향을 제시하였다. 세 번째 연구는 자동차 헤드업 디스플레이 기반의 제어권 전환 관련 인터페이스 설계와 평가에 관한 것이다. 제어권 전환이란, 자율주행 상태에서 운전자가 직접 운전을 하는 수동 운전 상태로 전환이 되는 것을 의미한다. 따라서 갑작스런 제어권 전환 요청이 발생하는 경우, 운전자가 안전하게 대처하기 위해서는 빠른 상황 파악과 의사 결정이 필요하게 되고, 이를 효과적으로 도와주기 위한 인터페이스 설계에 대해 연구할 필요성이 있다. 이에 본 연구에서는 자동차 헤드업 디스플레이 기반의 총 4개의 제어권 전환 관련 디스플레이(기준 디스플레이, 미니맵 디스플레이, 화살표 디스플레이, 미니맵과 화살표 디스플레이)를 제안하였고, 제안된 디스플레이 대안들은 주행 시뮬레이터 실험을 통해 제어권 전환 수행 능력과 안구의 움직임 패턴, 그리고 사용자의 주관적 평가 측면에서 평가되었다. 또한 제안된 디스플레이 대안들에 대해 운전자들의 초기 신뢰도 값을 측정하여 각 디스플레이에 따른 운전자들의 평균 신뢰도 점수에 따라 제어권 전환 수행 능력과 안구의 움직임 패턴, 그리고 주관적 평가가 어떻게 달라지는지 분석하였다. 실험 결과, 제어권 전환 상황에서 자동화된 시스템이 제안하는 정보와 그와 관련된 주변 상황 정보를 함께 제시해 주는 디스플레이가 가장 좋은 결과를 보여주었다. 또한 각 디스플레이에 대한 운전자의 초기 신뢰도 점수는 디스플레이의 실제 사용 행태와 밀접한 관련이 있음을 알 수 있었다. 신뢰도 점수에 따라 신뢰도가 높은 그룹과 낮은 그룹으로 분류되었고, 신뢰도가 높은 그룹은 제안된 디스플레이들이 보여주는 정보를 주로 믿고 따르는 경향이 있었던 반면, 신뢰도가 낮은 그룹은 룸 미러나 사이드 미러를 통해 주변 상황 정보를 더 확인 하는 경향을 보였다. 네 번째 연구는 전면 유리창에서의 인터랙티브 헤드업 디스플레이의 최적 위치를 결정하는 것으로서 주행 시뮬레이터 실험을 통해 디스플레이의 위치에 따라 운전자의 주행 수행 능력, 인터랙티브 디스플레이 조작 관련 과업 수행 능력, 시각적 주의 분산, 선호도, 그리고 작업 부하가 평가되었다. 헤드업 디스플레이의 위치는 전면 유리창에서 일정한 간격으로 총 9개의 위치가 고려되었다. 본 연구에서 활용된 인터랙티브 디스플레이는 음악 선택을 위한 스크롤 방식의 단일 디스플레이였고, 운전대에 장착된 버튼을 통해 디스플레이를 조작하였다. 실험 결과, 인터랙티브 헤드업 디스플레이의 위치가 모든 평가 척도, 즉 주행 수행 능력, 디스플레이 조작 과업 수행 능력, 시각적 주의 분산, 선호도, 그리고 작업 부하에 영향을 미침을 알 수 있었다. 모든 평가 지표를 고려했을 때, 인터랙티브 헤드업 디스플레이의 위치는 운전자가 똑바로 전방을 바라볼 때의 시야 구간, 즉 전면 유리창에서의 왼쪽 아래 부근이 가장 최적인 것으로 나타났다.Abstract i Contents v List of Tables ix List of Figures x Chapter 1 Introduction 1 1.1 Research Background 1 1.2 Research Objectives and Questions 8 1.3 Structure of the Thesis 11 Chapter 2 Functional Requirements of Automotive Head-Up Displays: A Systematic Review of Literature from 1994 to Present 13 2.1 Introduction 13 2.2 Method 15 2.3 Results 17 2.3.1 Information Types Displayed by Existing Commercial Automotive HUD Systems 17 2.3.2 Information Types Previously Suggested for Automotive HUDs by Research Studies 28 2.3.3 Information Types Required by Drivers (users) for Automotive HUDs and Their Relative Importance 35 2.4 Discussion 39 2.4.1 Information Types Displayed by Existing Commercial Automotive HUD Systems 39 2.4.2 Information Types Previously Suggested for Automotive HUDs by Research Studies 44 2.4.3 Information Types Required by Drivers (users) for Automotive HUDs and Their Relative Importance 48 Chapter 3 A Literature Review on Interface Design of Automotive Head-Up Displays for Communicating Safety-Related Information 50 3.1 Introduction 50 3.2 Method 52 3.3 Results 55 3.3.1 Commercial Automotive HUDs Presenting Safety-Related Information 55 3.3.2 Safety-Related HUDs Proposed by Academic Research 58 3.4 Discussion 74 Chapter 4 Development and Evaluation of Automotive Head-Up Displays for Take-Over Requests (TORs) in Highly Automated Vehicles 78 4.1 Introduction 78 4.2 Method 82 4.2.1 Participants 82 4.2.2 Apparatus 82 4.2.3 Automotive HUD-based TOR Displays 83 4.2.4 Driving Scenario 86 4.2.5 Experimental Design and Procedure 87 4.2.6 Experiment Variables 88 4.2.7 Statistical Analyses 91 4.3 Results 93 4.3.1 Comparison of the Proposed TOR Displays 93 4.3.2 Characteristics of Drivers Initial Trust in the four TOR Displays 102 4.3.3 Relationship between Drivers Initial Trust and Take-over and Visual Behavior 104 4.4 Discussion 113 4.4.1 Comparison of the Proposed TOR Displays 113 4.4.2 Characteristics of Drivers Initial Trust in the four TOR Displays 116 4.4.3 Relationship between Drivers Initial Trust and Take-over and Visual Behavior 117 4.5 Conclusion 119 Chapter 5 Human Factors Evaluation of Display Locations of an Interactive Scrolling List in a Full-windshield Automotive Head-Up Display System 121 5.1 Introduction 121 5.2 Method 122 5.2.1 Participants 122 5.2.2 Apparatus 123 5.2.3 Experimental Tasks and Driving Scenario 123 5.2.4 Experiment Variables 124 5.2.5 Experimental Design and Procedure 126 5.2.6 Statistical Analyses 126 5.3 Results 127 5.4 Discussion 133 5.5 Conclusion 135 Chapter 6 Conclusion 137 6.1 Summary and Implications 137 6.2 Future Research Directions 139 Bibliography 143 Apeendix A. Display Layouts of Some Commercial HUD Systems Appendix B. Safety-related Displays Provided by the Existing Commercial HUD Systems Appendix C. Safety-related HUD displays Proposed by Academic Research 국문초록 187Docto

Is the driver ready to receive just car information in the windshield during manual and autonomous driving?

A automação está a mudar o mundo. Como na aeronáutica, as empresas da indústria automóvel estão atualmente a desenvolver veículos autónomos. No entanto a autonomia do veículo não é completa, necessitando por vezes das ações do condutor. A forma como é feita a transição entre condução manual e autónoma e como mostrar esta informação de transição para o condutor constitui um desafio para a ergonomia. Novos ecrãs estão a ser estudados para facilitar estas transições. Este estudo usou um simulador de condução para investigar, se a informação em realidade aumentada pode influenciar positivamente a experiência do condutor durante a condução manual e autónoma. Compararam-se duas formas de apresentar a comunicação ao condutor. Um “conceito AR” mostrou toda a informação no para-brisas para ser mais fácil o condutor aceder à informação. O “conceito IC” mostrou a informação que aparece atualmente nos carros, usando o painel de instrumentos e o e-HUD. Os resultados indicam que a experiência do utilizador (UX) é influenciada pelos conceitos, sendo que o “conceito AR” teve uma melhor UX em todos os estados de transição. Em termos de confiança, os resultados revelaram também valores mais elevado para o “conceito AR”. O tipo de conceito não influenciou nem o tempo nem o comportamento de retomar o controlo do carro. Em termos de situação consciente, o “conceito AR” deixa os condutores mais conscientes durante a disponibilidade e ativação da função. Este estudo traz implicações para as empresas que desenvolvem a próxima geração de ecrãs no mundo automóvel.Automation is changing the world. As in aviation, the car manufacturers are currently developing autonomous vehicles. However, the autonomy of that vehicles isn’t complete, still being needed in certain moments the driver on ride. The way how is done this transition between manual and autonomous driving and how show this information to the driver is a challenge for Ergonomics. New displays are being studied to facilitate these transitions. This study used a driving simulator to investigates, whether augmented reality information can positively influence the user experience during manual and autonomous driving. Therefore, we compared two ways of present the communicate to the driver. The “AR concept” displays all the information in windshield to be easier to the driver access to the information. The “IC concept” displays the information that appears nowadays in the cars, where they use the Instrument Cluster and the e-HUD to display information. Results indicate that the user experience (UX) is influence by concepts, where “AR concept” had better UX in all the states. In terms of confidence, the results revealed higher scores in “AR concept” too. The type of concept does not influence the takeover times or the behavior of take control. In terms of situational awareness (SA), “AR concept” leave the drivers more aware during availability and activation. This study provides implications for automotive companies developing the next generation of car displays

Entorno virtual para diseñar y validar futuras interfaces a bordo para vehículos autónomos

[EN] This thesis presents a novel synthetic environment for supporting advanced explorations of user interfaces and interaction modalities for future transport systems. The main goal of the work is the definition of novel interfaces solutions designed for increasing trust in self-driving vehicles. The basic idea is to provide insights to the passengers concerning the information available to the Artificial Intelligence (AI) modules on-board of the car, including the driving behaviour of the vehicle and its decision making. Most of currently existing academic and industrial testbeds and vehicular simulators are designed to reproduce with high fidelity the ergonomic aspects associated with the driving experience. However, they have very low degrees of realism for what concerns the digital components of the various traffic scenarios. These includes the visuals of the driving simulator and the behaviours of both other vehicles on the road and pedestrians. High visual testbed fidelity becomes an important pre-requisite for supporting the design and evaluation of future on-board interfaces. An innovative experimental testbed based on the hyper-realistic video game GTA V, has been developed to satisfy this need. To showcase its experimental flexibility, a set of selected user studies, presenting novel self-driving interfaces and associated user experience results, are described. These explore the capabilities of inducing trust in autonomous vehicles and explore Heads-Up Displays (HUDs), Augmented Reality (ARs) and directional audio solutions. The work includes three core phases focusing on the development of software for the testbed, the definition of relevant interfaces and experiments and focused testing with panels comprising different user demographics. Specific investigations will focus on the design and exploration of a set of alternative visual feedback mechanisms (adopting AR visualizations) to gather information about the surrounding environment and AI decision making. The performances of these will be assessed with real users in respect of their capability to foster trust in the vehicle and on the level of understandability of the provided signals. Moreover, additional accessory studies will focus on the exploration of different designs for triggering driving handover, i.e. the transfer vehicle control from AI to human drivers, which is a central problem in current embodiments of self-driving vehicles.[ES] Esta tesis presenta un nuevo entorno virtual para apoyar exploraciones avanzadas de interfaces de usuario y modalidades de interacción para sistemas de transporte futuros. El objetivo principal del trabajo es la definición de soluciones de Realidad Aumentada diseñadas para aumentar la confianza en los vehículos autónomos. La idea básica es proporcionar información a los pasajeros sobre la información disponible para los módulos de Inteligencia Artificial (AI) a bordo del automóvil, incluido el comportamiento de conducción del vehículo y su toma de decisiones. El trabajo incluye tres fases centrales que se centran en el desarrollo de software para el banco de pruebas, la definición de interfaces y experimentos relevantes y pruebas enfocadas con paneles que comprenden diferentes datos demográficos de los usuarios. El entorno de trabajo específico del banco de pruebas experimental se compone de: - GTA V como entorno de prueba debido a su escenario complejo y sus gráficos hiperrealistas. - Volante y pedales para una conducción activa. - DeepGTA como marco de autocontrol. - Tobii Eye Tracking como dispositivo de entrada para las intenciones de los usuarios. Las investigaciones específicas se centrarán en el diseño y la exploración de un conjunto de mecanismos alternativos de retroalimentación visual (adopción de visualizaciones de AR) para recopilar información sobre el medio ambiente circundante y la toma de decisiones de IA. El rendimiento de estos se evaluará con los usuarios reales con respecto a su capacidad para fomentar la confianza en el vehículo y en el nivel de comprensión de las señales proporcionadas. Además, los estudios complementarios adicionales se centrarán en la exploración de diferentes diseños para activar el traspaso de conducción, es decir, el control del vehículo de transferencia de AI a los conductores humanos, que es un problema central en las realizaciones actuales de vehículos autónomos.Mateu Gisbert, C. (2018). Novel synthetic environment to design and validate future onboard interfaces for self-driving vehicles. http://hdl.handle.net/10251/112327TFG

AutoDRIVE: A Comprehensive, Flexible and Integrated Cyber-Physical Ecosystem for Enhancing Autonomous Driving Research and Education

Prototyping and validating hardware-software components, sub-systems and systems within the intelligent transportation system-of-systems framework requires a modular yet flexible and open-access ecosystem. This work presents our attempt towards developing such a comprehensive research and education ecosystem, called AutoDRIVE, for synergistically prototyping, simulating and deploying cyber-physical solutions pertaining to autonomous driving as well as smart city management. AutoDRIVE features both software as well as hardware-in-the-loop testing interfaces with openly accessible scaled vehicle and infrastructure components. The ecosystem is compatible with a variety of development frameworks, and supports both single and multi-agent paradigms through local as well as distributed computing. Most critically, AutoDRIVE is intended to be modularly expandable to explore emergent technologies, and this work highlights various complementary features and capabilities of the proposed ecosystem by demonstrating four such deployment use-cases: (i) autonomous parking using probabilistic robotics approach for mapping, localization, path planning and control; (ii) behavioral cloning using computer vision and deep imitation learning; (iii) intersection traversal using vehicle-to-vehicle communication and deep reinforcement learning; and (iv) smart city management using vehicle-to-infrastructure communication and internet-of-things

From Manual Driving to Automated Driving: A Review of 10 Years of AutoUI

This paper gives an overview of the ten-year devel- opment of the papers presented at the International ACM Conference on Automotive User Interfaces and Interactive Vehicular Applications (AutoUI) from 2009 to 2018. We categorize the topics into two main groups, namely, manual driving-related research and automated driving-related re- search. Within manual driving, we mainly focus on studies on user interfaces (UIs), driver states, augmented reality and head-up displays, and methodology; Within automated driv- ing, we discuss topics, such as takeover, acceptance and trust, interacting with road users, UIs, and methodology. We also discuss the main challenges and future directions for AutoUI and offer a roadmap for the research in this area.https://deepblue.lib.umich.edu/bitstream/2027.42/153959/1/From Manual Driving to Automated Driving: A Review of 10 Years of AutoUI.pdfDescription of From Manual Driving to Automated Driving: A Review of 10 Years of AutoUI.pdf : Main articl

A Voice and Pointing Gesture Interaction System for Supporting Human Spontaneous Decisions in Autonomous Cars

Autonomous cars are expected to improve road safety, traffic and mobility. It is projected that in the next 20-30 years fully autonomous vehicles will be on the market. The advancement on the research and development of this technology will allow the disengagement of humans from the driving task, which will be responsibility of the vehicle intelligence. In this scenario new vehicle interior designs are proposed, enabling more flexible human vehicle interactions inside them. In addition, as some important stakeholders propose, control elements such as the steering wheel and accelerator and brake pedals may not be needed any longer. However, this user control disengagement is one of the main issues related with the user acceptance of this technology. Users do not seem to be comfortable with the idea of giving all the decision power to the vehicle. In addition, there can be location awareness situations where the user makes a spontaneous decision and requires some type of vehicle control. Such is the case of stopping at a particular point of interest or taking a detour in the pre-calculated autonomous route of the car. Vehicle manufacturers\u27 maintain the steering wheel as a control element, allowing the driver to take over the vehicle if needed or wanted. This causes a constraint in the previously mentioned human vehicle interaction flexibility. Thus, there is an unsolved dilemma between providing users enough control over the autonomous vehicle and route so they can make spontaneous decision, and interaction flexibility inside the car. This dissertation proposes the use of a voice and pointing gesture human vehicle interaction system to solve this dilemma. Voice and pointing gestures have been identified as natural interaction techniques to guide and command mobile robots, potentially providing the needed user control over the car. On the other hand, they can be executed anywhere inside the vehicle, enabling interaction flexibility. The objective of this dissertation is to provide a strategy to support this system. For this, a method based on pointing rays intersections for the computation of the point of interest (POI) that the user is pointing to is developed. Simulation results show that this POI computation method outperforms the traditional ray-casting based by 76.5% in cluttered environments and 36.25% in combined cluttered and non-cluttered scenarios. The whole system is developed and demonstrated using a robotics simulator framework. The simulations show how voice and pointing commands performed by the user update the predefined autonomous path, based on the recognized command semantics. In addition, a dialog feedback strategy is proposed to solve conflicting situations such as ambiguity in the POI identification. This additional step is able to solve all the previously mentioned POI computation inaccuracies. In addition, it allows the user to confirm, correct or reject the performed commands in case the system misunderstands them

Systematic Review of Driver Distraction in the Context of Advanced Driver Assistance Systems (ADAS) & Automated Driving Systems (ADS)

Advanced Vehicle Systems promise improved safety and comfort for drivers. Steady advancements in technology are resulting in increasing levels of vehicle automation capabilities, furthering safety benefits. In fact, some of these vehicle automation systems are already deployed and available, but with promised benefits, such systems can potentially change driving behaviors. There is evidence that drivers have increased secondary task engagements while driving with automated vehicle systems, but there is a need for a clearer scientific understanding of any potential correlations between the use of automated vehicle systems and potentially negative driver behaviors. Therefore, this thesis aims to understand the state of knowledge on automated vehicle systems and their possible impact on drivers’ distraction behaviors. I have conducted two systematic literature reviews to examine this question. This thesis reports these reviews and examines the effects of secondary task engagement on driving behaviors such as take-over times, visual attention, trust, and workload, and discusses the implications on driver safety

License to Supervise:Influence of Driving Automation on Driver Licensing

To use highly automated vehicles while a driver remains responsible for safe driving, places new – yet demanding, requirements on the human operator. This is because the automation creates a gap between drivers’ responsibility and the human capabilities to take responsibility, especially for unexpected or time-critical transitions of control. This gap is not being addressed by current practises of driver licensing. Based on literature review, this research collects drivers’ requirements to enable safe transitions in control attuned to human capabilities. This knowledge is intended to help system developers and authorities to identify the requirements on human operators to (re)take responsibility for safe driving after automation

Exploring safer visual feedback in human-machine handover in highly autonomous vehicles

Driving is becoming increasingly automated and the automated driving system is gradually replacing the driver, which will inevitably have a significant impact on the driving experience. This study investigates the design of a dashboard for the highly automated vehicle that would provide the driver with relevant information during the human-machine handover. After reviewing previous studies, analyzing the state-of-the-art and generating user scenarios, we developed design guidelines, prototypes and user experience videos. This video served as a "research instrument" to test with users and explore and learn about consequences and interpretations. The test results suggest that the mental workload paid by the user for the task shows a trend of reduction from level 3 to level 4. The reduced workload can ensure more effective alerts and alarms, which can potentially make driving safer. Regarding the implementation of the design, conclusions are mainly drawn on three aspects: the necessity to combine several modalities at automation level 4, the need to redefine the color of the assisting AR bars we designed due to the indistinguishability of the red and orange ones, and the disagreement on whether and how to display speed information at handover. The practice and application of our prototype in scenarios supports previous studies and provides a reliable, creative solution for other researchers and designers