6,961 research outputs found

    Helping people help themselves - toward a theory of autonomy-compatible help

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    If development is seen basically as autonomous self-development, then there is a subtle paradox in the whole notion of development assistance: How can an outside party ("helper") assist those undertaking autonomous activities (the"doers") without overriding, or undercutting their autonomy? This conundrum is the challenge facing a theory of autonomy-compatible development assistance - that is, helping theory. Starting from a simple model of non-distortionary aid, the author explores several themes of a broader helping theory, and shows how these themes arise in the work of"gurus"in different fields - John Dewey in pedagogy and social philosophy, Douglas McGregor in management theory, Carl Rogers in psychotherapy, Soren Kierkegaard in spiritual counseling, Saul Alinsky in community organizing, Paulo Freire in community education, and Albert Hirschman, and E.F. Schumacher in economic development. That such diverse thinkers in such different fields, arrive at very similar conclusions, increases confidence in the common principles. The points of commonality are summarized as follows: 1) Help must start from the present situation of the doers. 2) Helpers must see the situation through the eyes of the doers. 3) Help cannot be imposed on the doers, as that directly violates their autonomy. 4) Nor can doers receive help as a benevolent gift, as that increases dependency. 5) Doers must be in the driver seat. One major application of helping theory is to the problems of knowledge-based development assistance. The standard approach is that the helper, a knowledge-based development agency, has the"answers", and disseminates them to the doers. This corresponds to the standard teacher-centered pedagogy. The alternative under helping theory is the learner-centered approach. The teacher plays the role of midwife, catalyst, and facilitator, building learning capacity in the learner-doers, so that they can learn from any source, including their own experience. Development assistance is further complicated by the local, or tacit nature of much relevant knowledge. A knowledge-based development agency might function better, not simply as a source of knowledge, but as a broker connecting those who face problems with those in similar situations, who have learned to address the problems. Changing to the approach of helping theory, entails changing the helping agency itself, transforming it into an organization that fosters learning internally, as well as externally - as in a university, where professors engage in learning, and foster learning in students, but the organization does not adopt official views on the complex questions of the day. This means fostering competition in the marketplace of ideas within the organization, and taking a more Socratic stance with clients, who will then have to take responsibility for, and have ownership of their decisions.Economic Theory&Research,Decentralization,Health Economics&Finance,Development Economics&Aid Effectiveness,Labor Policies,Health Monitoring&Evaluation,Educational Sciences,Economic Theory&Research,Health Economics&Finance,Development Economics&Aid Effectiveness

    A demonstration of motion base design alternatives for the National Advanced Driving Simulator

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    A demonstration of the capability of NASA's Vertical Motion Simulator to simulate two alternative motion base designs for the National Advanced Driving simulator (NADS) is reported. The VMS is located at ARC. The motion base conditions used in this demonstration were as follows: (1) a large translational motion base; and (2) a motion base design with limited translational capability. The latter had translational capability representative of a typical synergistic motion platform. These alternatives were selected to test the prediction that large amplitude translational motion would result in a lower incidence or severity of simulator induced sickness (SIS) than would a limited translational motion base. A total of 10 drivers performed two tasks, slaloms and quick-stops, using each of the motion bases. Physiological, objective, and subjective measures were collected. No reliable differences in SIS between the motion base conditions was found in this demonstration. However, in light of the cost considerations and engineering challenges associated with implementing a large translation motion base, performance of a formal study is recommended

    Behavioural compensation by drivers of a simulator when using a vision enhancement system

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    Technological progress is suggesting dramatic changes to the tasks of the driver, with the general aim of making driving environment safer. Before any of these technologies are implemented, empirical research is required to establish if these devices do, in fact, bring about the anticipated improvements. Initially, at least, simulated driving environments offer a means of conducting this research. The study reported here concentrates on the application of a vision enhancement (VE) system within the risk homeostasis paradigm. It was anticipated, in line with risk homeostasis theory, that drivers would compensate for the reduction in risk by increasing speed. The results support the hypothesis although, after a simulated failure of the VE system, drivers did reduce their speed due to reduced confidence in the reliability of the system

    The psychology of driving automation: A discussion with Professor Don Norman

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    Introducing automation into automobiles had inevitable consequences for the driver and driving. Systems that automate longitudinal and lateral vehicle control may reduce the workload of the driver. This raises questions of what the driver is able to do with this 'spare' attentional capacity. Research in our laboratory suggests that there is unlikely to be any spare capacity because the attentional resources are not 'fixed'. Rather, the resources are inextricably linked to task demand. This paper presents some of the arguments for considering the psychological aspects of the driver when designing automation into automobiles. The arguments are presented in a conversation format, based on discussions with Professor Don Norman. Extracts from relevant papers to support the arguments are presented

    Investigation of low-cost infrared sensing for intelligent deployment of occupant restraints

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    In automotive transport, airbags and seatbelts are effective at restraining the driver and passenger in the event of a crash, with statistics showing a dramatic reduction in the number of casualties from road crashes. However, statistics also show that a small number of these people have been injured or even killed from striking the airbag, and that the elderly and small children are especially at risk of airbag-related injury. This is the result of the fact that in-car restraint systems were designed for the average male at an average speed of 50 km/hr, and people outside these norms are at risk. Therefore one of the future safety goals of the car manufacturers is to deploy sensors that would gain more information about the driver or passenger of their cars in order to tailor the safety systems specifically for that person, and this is the goal of this project. This thesis describes a novel approach to occupant detection, position measurement and monitoring using a low-cost thermal imaging based system, which is a departure from traditional video camera-based systems, and at an affordable price. Experiments were carried out using a specially designed test rig and a car driving simulator with members of the public. Results have shown that the thermal imager can detect a human in a car cabin mock up and provide crucial real-time position data, which could be used to support intelligent restraint deployment. Other valuable information has been detected such as whether the driver is smoking, drinking a hot or cold drink, using a mobile phone, which can help to infer the level of driver attentiveness or engagement

    'ํƒ‘์Šน์ž'์˜ ๊ด€์ ์˜ ์‹œ๊ฐ„, ์œ„์น˜ ๊ธฐ๋ฐ˜ ์ฐจ๋Ÿ‰ ํด๋Ÿฌ์Šคํ„ฐ UI ๋””์ž์ธ ํ”„๋ ˆ์ž„ ์ œ์•ˆ ์—ฐ๊ตฌ

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    ํ•™์œ„๋…ผ๋ฌธ(์„์‚ฌ)--์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› :๋ฏธ์ˆ ๋Œ€ํ•™ ๋””์ž์ธํ•™๋ถ€ ๋””์ž์ธ์ „๊ณต,2019. 8. ์ •์˜์ฒ .One important design issue is the examination of how the user interface (UI) supports the new user role in future mobility. However, there are few design studies on the passengers cognitive needs and behavior in Autonomous Vehicles (AVs) based on empirical data. There is no doubt that autonomous mobility technologies are growing. The technology is already aiding the driving experience, and it will change the mobility culture and the transition of driver into passenger. This study is based on the premise that future AV is capable of performing all driving tasks. It proposes a set of passenger-centered automotive cluster UI designs for future mobility employing two factors: time and path. A set of empirical data is provided to understand the passengers perspective. In this study, a solid set of empirical data on the cognitive needs of passengers is collected. Human cognitive characteristics and driving tasks are investigated from various viewpoints to understand the passengers iii perspective. The cognitive relationship in the driving environment is analyzed through a literature review on situation awareness (SA) and structuring of the data flow framework. The framework is further explored by connecting the technological role transformation to the passenger. To construct the empirical database on the passenger, three sets of user tests and in-depth interviews were undertaken. The user tests were designed employing the Wizard of Oz method, and the results were summarized using descriptive and exploratory analysis. Based on these insights, a set of UI designs from the perspective of the passenger was proposed, and usability tests were conducted to verify its effectiveness and usability. The results of the tests demonstrate that a major percentage of the information request was related to time (current time and duration) and path (vehicle location and surroundings). Based on the data, a UI framework was built. Two usage scenarios were designed, time-full and time-less, for better in-situation comprehension. Time- and path-based UI were proposed to flow with the scenarios. A usability test was conducted, and a passengers cognitive framework was defined. There are two aspects to this study: the data flow frameworks of the driver/passenger, and the UI design proposal. Situational precision from the perspective of the driver was analyzed to understand the relationship between the user, the vehicle and the road conditions. Further, the cognitive framework of the passenger was proposed based on the data. This study provides a solid understanding of drivers emerging needs when they are relieved of the cognitive burden of driving tasks. The UI features for AV are introduced based on the empirical data and research related to the provision of better situation awareness, focusing on time and location. This study contributes to the extant literature by observing the iv perspective of passengers in Autonomous vehicles based on a qualitative study. The proposed UI design will be further explored as a communication method between the system and the passive user in future mobility.์‚ฌ์šฉ์ž ์ธํ„ฐํŽ˜์ด์Šค๊ฐ€ (UI) ๋ฏธ๋ž˜ ์ด๋™์„ฑ์—์„œ ์ƒˆ๋กœ์šด ์‚ฌ์šฉ์ž ์—ญํ• ์„ ์ง€์ง€ํ•˜๋Š” ๋””์ž์ธ ๋„์ถœ์€ ๋ฏธ๋ž˜ ์ด๋™์„ฑ ๋ถ„์•ผ์—์„œ ์ค‘์š”ํ•œ ๋””์ž์ธ ์ด์Šˆ์ด๋‹ค. ๊ทธ๋Ÿฌ๋‚˜ ์‚ฌ์šฉ์ž ์‹คํ—˜์— ๊ทผ๊ฑฐํ•˜์—ฌ ์ž์œจ์ฃผํ–‰์ฐจ๋Ÿ‰ (AV) ์˜ ํƒ‘์Šน์ž์ธ์ง€ ์š•๊ตฌ์™€ ํ–‰๋™์— ๋Œ€ํ•œ ๋””์ž์ธ ์—ฐ๊ตฌ๋Š” ๋ฏธ๋ฏธํ•˜๋‹ค. ์ž์œจ์ฃผํ–‰์ด ๊ธฐ์ˆ ์˜ ๋ฐœ์ „๊ณผ ๊ทธ ์˜์—ญ์€ ์ ์ฐจ ๋„“์–ด์ง€๊ณ  ์žˆ๋‹ค. ํ•ด๋‹น ๊ธฐ์ˆ ์€ ์ด๋ฏธ ์šด์ „ ํ™˜๊ฒฝ์— ์ ์šฉ๋˜๊ณ  ์žˆ์œผ๋ฉฐ, ์ด๋กœ ์ธํ•ด ๋ฏธ๋ž˜ ์ด๋™๋ฌธํ™”์—์„œ ์‚ฌ์šฉ์ž์˜ ์—ญํ• ์€ '์šด์ „์ž'์—์„œ 'ํƒ‘์Šน์ž'๋กœ ๋ณ€ํ™”ํ•œ๋‹ค. ๋ณธ ์—ฐ๊ตฌ๋Š” ๋ฏธ๋ž˜ ์ž์œจ์ฃผํ–‰์ฐจ๋Ÿ‰์ด ๋ชจ๋“  ์šด์ „ ์ƒํ™ฉ์— ๋Œ€์ฒ˜ํ•  ์ˆ˜ ์žˆ๋‹ค๋Š” ๊ฒƒ์„ ์ „์ œ๋กœ ํ•œ๋‹ค. ์‚ฌ์šฉ์ž ์‹คํ—˜์„ ํ†ตํ•ด ํƒ‘์Šน์ž์˜ ๊ด€์ ์— ๋Œ€ํ•œ ๋ถ„์„์„ ์ง„ํ–‰ํ•˜์˜€๊ณ , ์ด๋ฅผ ๊ธฐ๋ฐ˜์œผ๋กœ ๋ฏธ๋ž˜ ๋ชจ๋นŒ๋ฆฌํ‹ฐ ํ™˜๊ฒฝ์— ์ ์šฉ๋  ์‚ฌ์šฉ์ž ์ธํ„ฐํŽ˜์ด์Šค๋ฅผ ์ œ์•ˆํ•œ๋‹ค. ์ œ์•ˆ๋œ ๋””์ž์ธ์€ ์šด์ „์ž ์ค‘์‹ฌ์˜ ์ƒํ™ฉ์ธ์ง€์—์„œ ๋ฒ—์–ด๋‚˜ ํƒ‘์Šน์ž ์ค‘์‹ฌ ์ธ์ง€ ์ •๋ณด ์š”์†Œ๋ฅผ ๋ถ„์„ํ•˜์˜€๊ณ , ์‹œ๊ฐ„๊ณผ ๊ฒฝ๋กœ ๋‘ ๊ฐ€์ง€ ์š”์†Œ๋ฅผ ๊ฐ•์กฐํ•œ UI ๋ฅผ ์ œ์•ˆํ•œ๋‹ค. ๋ณธ ์—ฐ๊ตฌ์—์„œ ํƒ‘์Šน์ž์˜ ์ธ์ง€ ์ •๋ณด ์š”๊ตฌ์— ๋Œ€ํ•œ ์‹คํ—˜์  ๋ฐ์ดํ„ฐ๋ฅผ ์ˆ˜์ง‘ํ•˜์˜€๋‹ค. ํƒ‘์Šน์ž์˜ ๊ด€์ ์„ ์ดํ•ดํ•˜๊ธฐ ์œ„ํ•ด ๋‹ค์–‘ํ•œ ๊ด€์ ์—์„œ ์ธ๊ฐ„์˜ ์ธ์ง€์  ํŠน์„ฑ ๋ฐ ์šด์ „ ํƒœ์Šคํฌ๋ฅผ ๊ด€์ฐฐํ•˜์˜€๊ณ , ์ƒํ™ฉ์ธ์ง€ (SA) ์— ๊ด€ํ•œ ๋ฌธํ—Œ ์—ฐ๊ตฌ์™€ ๋ฐ์ดํ„ฐ ํ”„๋ ˆ์ž„์›Œํฌ ๊ตฌ์กฐํ™”๋ฅผ ํ†ตํ•ด ์šด์ „ ํ™˜๊ฒฝ์—์„œ ๋ฐœ์ƒํ•˜๋Š” ์ธ์ง€์  ์š”์†Œ ๊ด€๊ณ„๋ฅผ ๋ถ„์„ํ•˜์˜€๋‹ค. ์ œ์•ˆ๋œ ํ”„๋ ˆ์ž„์›Œํฌ๋Š” ๊ธฐ์ˆ  ๋ณ€ํ™”์— ๋”ฐ๋ผ ์šด์ „์ž๊ฐ€ ํƒ‘์Šน์ž๋กœ ๋ณ€ํ™”๋˜์—ˆ์„ ๋•Œ ์šด์ „ ํ™˜๊ฒฝ์—์„œ์˜ ๋ฐ์ดํ„ฐ ๊ด€๊ณ„ ๋ณ€ํ™”๋ฅผ ์‹œ๊ฐ์ ์œผ๋กœ ๊ตฌ์กฐํ™”ํ•˜์—ฌ ์‹ฌ์ธต์ ์œผ๋กœ ํƒ๊ตฌ๋˜์—ˆ๋‹ค. ํƒ‘์Šน์ž์˜ ์ธ์ง€ ๋‹ˆ์ฆˆ ๋Œ€ํ•œ ์‹คํ—˜์  ๋ฐ์ดํ„ฐ๋ฒ ์ด์Šค๋ฅผ ์ˆ˜์ง‘ํ•˜๊ธฐ ์œ„ํ•ด ์ด 3 ์„ธํŠธ์˜ ์œ ์ € ํ…Œ์ŠคํŠธ์™€ ์‹ฌ์ธต ์ธํ„ฐ๋ทฐ๊ฐ€ ์ˆ˜๋ฐ˜๋˜์—ˆ๋‹ค. ์œ ์ € ํ…Œ์ŠคํŠธ๋Š” Wizard of Oz ๋ฐฉ๋ฒ•์„ ์‚ฌ์šฉํ•˜์—ฌ ์„ค๊ณ„๋˜์—ˆ์œผ๋ฉฐ ์‹คํ—˜ ๊ฒฐ๊ณผ๋Š” ์งˆ์  ์—ฐ๊ตฌ๋ฐฉ๋ฒ•๋ก ์˜ ๋ถ„์„ ๋ฐฉ๋ฒ•์„ ํ†ตํ•ด ๋ถ„์„๋˜์—ˆ๋‹ค. ์‹คํ—˜์„ ํ†ตํ•ด ์–ป์€ ์ธ์‚ฌ์ดํŠธ๋ฅผ ๋ฐ”ํƒ•์œผ๋กœ ํƒ‘์Šน์ž ๊ด€์ ์—์„œ UI ๋””์ž์ธ์„ ์ œ์•ˆํ•˜๊ณ  ์‚ฌ์šฉ์„ฑ ํ…Œ์ŠคํŠธ๋ฅผ ํ†ตํ•ด ํšจ์œจ์„ฑ๊ณผ ์œ ์šฉ์„ฑ์„ 5 ์  ๋ฆฌ ์ปคํŠธ ์Šค์ผ€์ผ๋กœ์จ ๊ฒ€์ฆํ•˜์˜€๋‹ค. ์‹คํ—˜ ๊ฒฐ๊ณผ์— ๋”ฐ๋ฅด๋ฉด ํƒ‘์Šน์ž๊ฐ€ ์š”์ฒญํ•œ ์ธ์ง€ ์ •๋ณด๋Š” ์‹œ๊ฐ„ (ํ˜„์žฌ ์‹œ๊ฐ ๋ฐ ๊ธฐ๊ฐ„)๊ณผ ๊ฒฝ๋กœ (์ฐจ๋Ÿ‰ ์œ„์น˜ ๋ฐ ์ฃผ๋ณ€ ํ™˜๊ฒฝ)์— ์ง‘์ค‘๋œ ๊ฒƒ์„ ๊ด€์ฐฐํ•  ์ˆ˜ ์žˆ์—ˆ๋‹ค. ์ด์™€ ๊ฐ™์€ ๋ฐ์ดํ„ฐ๋ฅผ ๊ธฐ๋ฐ˜์œผ๋กœ UI ํ”„๋ ˆ์ž„์›Œํฌ๋ฅผ ๊ตฌ์„ฑํ•˜์˜€๋‹ค. ์ƒํ™ฉ ์†์˜ ์‚ฌ์šฉ๋ก€๋ฅผ ์ œ์‹œํ•˜๊ธฐ ์œ„ํ•˜์—ฌ๋„ ๊ฐ€์ง€ time-full ๊ณผ time-less ์˜ ์‚ฌ์šฉ ์‹œ๋‚˜๋ฆฌ์˜ค๋ฅผ ๊ตฌ์ถ•ํ•˜๊ณ , ์ œ์•ˆ๋œ ์‹œ๋‚˜๋ฆฌ์˜ค์— ๋”ฐ๋ผ ์‹œ๊ฐ„๊ณผ ์œ„์น˜์— ๊ธฐ๋ฐ˜ํ•œ UI ๋ฅผ ์ œ์•ˆํ•˜์˜€๋‹ค. ์ œ์•ˆ๋œ UI ์— ๋Œ€ํ•œ ์‚ฌ์šฉ์„ฑ ํ…Œ์ŠคํŠธ๋ฅผ ์ง„ํ–‰ํ•˜์˜€๊ณ , ํƒ‘์Šน์ž ๊ด€์ ์—์„œ์˜ ์šด์ „์ƒํ™ฉ ์ธ์ง€ ์›Œํฌ ํ”„๋ ˆ์ž„์„ ์™„์„ฑํ•˜์˜€๋‹ค. ๋ณธ ์—ฐ๊ตฌ์˜ ๊ฐ€์น˜๋Š” ๋‘ ๊ฐ€์ง€๋กœ ์ •๋ฆฌ๋  ์ˆ˜ ์žˆ๋‹ค. ํ•˜๋‚˜๋Š” ์šด์ „์ž / ํƒ‘์Šน์ž์˜ ๋ฐ์ดํ„ฐ ํ”Œ๋กœ์šฐ ํ”„๋ ˆ์ž„์›Œํฌ๋ฅผ ์ œ์•ˆํ•˜์˜€๋‹ค๋Š” ๊ฒƒ๊ณผ ๋‘ ๋ฒˆ์งธ๋Š” ํƒ‘์Šน์ž์˜ ๊ด€์ ์„ ์ง€์ง€ํ•˜๋Š” UI ๋””์ž์ธ ์ œ์•ˆ์— ์žˆ๋‹ค. ์šด์ „์ž์˜ ๊ด€์ ์—์„œ์˜ ์šด์ „ ์ƒํ™ฉ์„ ๋ถ„์„ํ•˜์—ฌ ์‚ฌ์šฉ์ž, ์ฐจ๋Ÿ‰, ๊ทธ๋ฆฌ๊ณ  ๋„๋กœ ์ƒํƒœ ๊ฐ„์˜ ๊ด€๊ณ„๋ฅผ ์‹œ๊ฐํ™”ํ•˜์˜€๊ณ , ์ด๋Š” ํƒ‘์Šน์ž์ธ์ง€ ํ”Œ๋กœ์šฐ ํ”„๋ ˆ์ž„์›Œํฌ๋ฅผ ์ œ์•ˆํ•˜๋Š”๋ฐ ๊ธฐ์กฐ์ ์ธ ํ‹€๋กœ์จ ์‚ฌ์šฉ๋˜์—ˆ๋‹ค. ๋ณธ ์—ฐ๊ตฌ๋Š” ์šด์ „ ํƒœ์Šคํฌ๋ฅผ ์ˆ˜ํ–‰ํ•˜๋Š” ๋ฐ์— ํ•„์š”ํ–ˆ๋˜ ์ธ์ง€ ๋ถ€๋‹ด์—์„œ ๋ฒ—์–ด๋‚ฌ์„ ๋•Œ์˜ ์šด์ „์ž๊ฐ€ ํ•„์š”๋กœ ํ•˜๋Š” ๋ณตํ•ฉ์ ์ธ ๋‹ˆ์ฆˆ์— ๋Œ€ํ•ด ๊ด€์ฐฐํ•˜๊ณ  ๋ฏธ๋ž˜ ๋ชจ๋นŒ๋ฆฌํ‹ฐ ํ™˜๊ฒฝ์— ์ ํ•ฉํ•œ UI ์˜ ๋””์ž์ธ ์š”์†Œ์— ๋Œ€ํ•œ ์—ฐ๊ตฌ๋…ผ๋ฌธ์ด๋‹ค. ๋ฏธ๋ž˜ ์ž์œจ์ฃผํ–‰์ฐจ๋Ÿ‰ ์•ˆ์˜ ์‚ฌ์šฉ์ž ์ธํ„ฐํŽ˜์ด์Šค๊ฐ€ ๊ฐ–์ถ”์–ด์•ผ ํ•˜๋Š” ์š”์†Œ๋ฅผ ์‹คํ—˜์  ๋ฐ์ดํ„ฐ์— ๊ทผ๊ฑฐํ•˜์—ฌ ์ œ์‹œํ•˜๋ฉฐ, ์‹œ๊ฐ„๊ณผ ๋ฃจํŠธ๋ฅผ ๊ฐ•์กฐํ•˜์—ฌ ํ–ฅ์ƒ๋œ ์ƒํ™ฉ ์ธ์ง€๋ฅผ ์ œ๊ณตํ•˜๋Š” ๋ฐฉ๋ฒ•์— ๋Œ€ํ•œ ์‹ฌ๋„์žˆ๋Š” ๊ด€์ฐฐ์„ ๊ธฐ๋กํ•œ๋‹ค. ๋ณธ ์—ฐ๊ตฌ๋Š” ์งˆ์  ์—ฐ๊ตฌ์— ๊ธฐ์ดˆํ•œ ์ž์œจ ์ฐจ๋Ÿ‰์˜ ํƒ‘์Šน์ž ๊ด€์ ์„ ๊ด€์ฐฐํ•จ์œผ๋กœ์จ ๊ธฐ์กด ์ž์œจ์ฃผํ–‰์ด ๋””์ž์ธ ์—ฐ๊ตฌ์— ๊ธฐ์—ฌํ•  ๊ฒƒ์ด๋‹ค. ์ œ์•ˆ๋œ UI ๋””์ž์ธ ๋ฏธ๋ž˜ ์ด๋™ ์„ฑ์•ˆ์—์„œ ์‹œ์Šคํ…œ๊ณผ ํƒ‘์Šน์ž ๊ฐ„์˜ ์ปค๋ฎค๋‹ˆ์ผ€์ด์…˜ ๋ฐฉ๋ฒ•์— ๋Œ€ํ•œ ์—ฐ๊ตฌ๋กœ์จ ๊ทธ ์˜์˜๊ฐ€ ์žˆ๋‹ค.ABSTRACT ...................................................................................................................... II CHAPTER 1. INTRODUCTION......................................................................................... ๏ผ‘ 1.1. BACKGROUND ..............................................................................................................๏ผ‘ 1.2. PURPOSE .....................................................................................................................๏ผ— 1.3. RESEARCH QUESTION.....................................................................................................๏ผ˜ CHAPTER 2. LITERATURE REVIEW ..............................................................................๏ผ‘๏ผ‘ 2.1. SITATION AWARENESS (SA) ........................................................................................๏ผ‘๏ผ‘ 2.2. HUMAN INFORMATION PROCESSING MODEL..................................................................๏ผ‘๏ผ• 2.3. DRIVING SITUATION AWARENESS AND PERSPECTIVE.........................................................๏ผ’๏ผ 2.4. DRIVING TASK AND SENSORY INTERACTION ....................................................................๏ผ’๏ผ’ CHAPTER 3. COGNITIVE NEEDS IN AUTONOMOUS.....................................................๏ผ’๏ผ— 3.1. DRIVING BEHAVIOR TRANSFORMATION AND CLUSTER UI..................................................๏ผ’๏ผ— 3.2. COGNITIVE FRAMEWORK TRANSFORMATION ..................................................................๏ผ“๏ผ“ CHAPTER 4. USER TESTS ............................................................................................๏ผ“๏ผ– 4.1. WIZARD OF OZ PROTOTYPING .....................................................................................๏ผ“๏ผ˜ 4.2. PILOT TEST 1............................................................................................................๏ผ”๏ผ 4.2.1. Experiment Design & Laboratory Setting.................................................๏ผ”๏ผ 4.2.2. Persona Scenario & Task Design ..............................................................๏ผ”๏ผ’ 4.2.3. Preparation of Driving situation...............................................................๏ผ”๏ผ• 4.2.4. Procedure.................................................................................................๏ผ”๏ผ— 4.2.5. Data Analysis & Insight............................................................................๏ผ”๏ผ˜ 4.3. PILOT TEST 2............................................................................................................๏ผ•๏ผ‘ 4.3.1. Amendment: Experiment Design & Laboratory Setting ...........................๏ผ•๏ผ’ 4.3.2. Amendment: Task Scenario & Command Cue..........................................๏ผ•๏ผ” 4.3.3. Amendment: Perform Role and preparation of driving situation ............๏ผ•๏ผ— 4.3.4. Amendment: Procedure ...........................................................................๏ผ•๏ผ™ 4.3.5. Data Analysis & Insight............................................................................๏ผ–๏ผ’ 4.4. MAIN TEST ..............................................................................................................๏ผ–๏ผ• 4.4.1. Experiment Design & Laboratory setting .................................................๏ผ–๏ผ– 4.4.2. Task Design ..............................................................................................๏ผ–๏ผ™ 4.4.3. Procedure.................................................................................................๏ผ—๏ผ‘ 4.4.4. Result Analysis & Insight..........................................................................๏ผ—๏ผ” CHAPTER 5. UI CONCEPT DEVELOPMENT...................................................................๏ผ˜๏ผ‘ 5.1. UI DESIGN METHOD..................................................................................................๏ผ˜๏ผ‘ 5.2. DESIGN PROPOSAL ....................................................................................................๏ผ˜๏ผ” 5.3. USER SCENARIOS ......................................................................................................๏ผ˜๏ผ– 5.3.1 Scenario 1. Time-less: Late for a morning meeting..................................๏ผ˜๏ผ– 5.3.2 Scenario 2.Time-full: Leisure driving on weekends ..................................๏ผ™๏ผ“ CHAPTER 6. USABILITY TEST ......................................................................................๏ผ™๏ผ˜ 6.1. USABILITY TEST GUIDE ...............................................................................................๏ผ™๏ผ˜ 6.2. ASSESSMENT USABILITY TEST ..................................................................................๏ผ‘๏ผ๏ผ 6.2.1 Test planning........................................................................................๏ผ‘๏ผ๏ผ 6.2.2 Laboratory setting................................................................................๏ผ‘๏ผ๏ผ’ 6.2.3 Test conduct and debriefing.................................................................๏ผ‘๏ผ๏ผ– 6.3. RESULT ANALYSIS ..................................................................................................๏ผ‘๏ผ๏ผ– CHAPTER 7. CONCLUSION......................................................................................๏ผ‘๏ผ๏ผ— APPENDIX 1...........................................................................................................๏ผ‘๏ผ‘๏ผ APPENDIX 2...........................................................................................................๏ผ‘๏ผ‘๏ผ‘ APPENDIX 3...........................................................................................................๏ผ‘๏ผ‘๏ผ“ APPENDIX 4...........................................................................................................๏ผ‘๏ผ’๏ผ‘ APPENDIX 5...........................................................................................................๏ผ‘๏ผ’๏ผ” APPENDIX 6...........................................................................................................๏ผ‘๏ผ’๏ผ˜ APPENDIX 7...........................................................................................................๏ผ‘๏ผ“๏ผ“ BIBLIOGRAPHY ......................................................................................................๏ผ‘๏ผ“๏ผ– ๊ตญ๋ฌธ ์ดˆ๋ก ............................................................................................................๏ผ‘๏ผ”๏ผ“Maste

    The use of visual cues for vehicle control and navigation

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    At least three levels of control are required to operate most vehicles: (1) inner-loop control to counteract the momentary effects of disturbances on vehicle position; (2) intermittent maneuvers to avoid obstacles, and (3) outer-loop control to maintain a planned route. Operators monitor dynamic optical relationships in their immediate surroundings to estimate momentary changes in forward, lateral, and vertical position, rates of change in speed and direction of motion, and distance from obstacles. The process of searching the external scene to find landmarks (for navigation) is intermittent and deliberate, while monitoring and responding to subtle changes in the visual scene (for vehicle control) is relatively continuous and 'automatic'. However, since operators may perform both tasks simultaneously, the dynamic optical cues available for a vehicle control task may be determined by the operator's direction of gaze for wayfinding. An attempt to relate the visual processes involved in vehicle control and wayfinding is presented. The frames of reference and information used by different operators (e.g., automobile drivers, airline pilots, and helicopter pilots) are reviewed with particular emphasis on the special problems encountered by helicopter pilots flying nap of the earth (NOE). The goal of this overview is to describe the context within which different vehicle control tasks are performed and to suggest ways in which the use of visual cues for geographical orientation might influence visually guided control activities

    Assessment of a human computer interface prototyping environment

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    A Human Computer Interface (HCI) prototyping environment with embedded evaluation capability has been successfully assessed which will be valuable in developing and refining HCI standards and evaluating program/project interface development, especially Space Station Freedom on-board displays for payload operations. The HCI prototyping environment is designed to include four components: (1) a HCI format development tool, (2) a test and evaluation simulator development tool, (3) a dynamic, interactive interface between the HCI prototype and simulator, and (4) an embedded evaluation capability to evaluate the adequacy of an HCI based on a user's performance

    An ergonomics design knowledge based expert system

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    The research scope and objectives are to investigate the use of 'geometric reasoning' using the knowledge based techniques established for expert systems. An Expert System is integrated within the SAMMIE (System for Aiding Man-Machine Interaction Evaluation) computer man modelling system and used for vehicle interior design. Vehicle design objectives are related to a rule base determined from national and international standards and legislation. Malaysia is now progressing towards becoming an Industrialised Country by the year 2020. In mid 1985 the Malaysian Motor Industry produced the Proton Saga which has since been exported to other countries. Although the Standards and Industrial Research Institute of Malaysia (SIRIM) is playing an important role in design activities and provision of standardisation information, some standards and legislation for vehicle interior design are not easily available. There is an important and urgent need for standards and legislation to facilitate vehicle design within Malaysia and Internationally. A literature survey on the relevance of ergonomics design to standards and legislation for vehicle interior design is presented. Knowledge and expertise required for the knowledge base were elicited from various resources; extracted from journals, research publications and standards reports from various international organisations. The SAMMIE system was used to develop a prototype design model for the vehicle interior and the KES expert systems hell was selected to develop the Ergonomics Design Knowledge Based Expert System (EDKBES). EDKBES has a modular structure for ease of software readability, editing and testing, and to readily facilitate further development. The knowledge base is divided into several sections related to the hierarchical structure of vehicle interior design

    Driver's field of view from large vehicles: phase 3 - report

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    In response to DETRโ€™s request to investigate ways and means of improving the driversโ€™ field of view from HGVโ€™s, coaches and buses, nine representative vehicles were evaluated using CAD man-modelling techniques. Evaluation was made against a benchmark field of view requirement which was developed by ICE Ergonomics and based upon the swept path envelopes of large vehicles whilst manoeuvring and on road layout and design considerations. Each vehicle was assessed using eye-points for the 5th %ile female and 95th %ile male driver. Where a driverโ€™s field of view fell significantly short of the benchmark requirement a number of improvement options were investigated. Predominantly, the options selected were those which were most cost-effective and entailed the use of additional and modified wide angle mirrors on both the near-side and off-side of the vehicle. When reversing, driverโ€™s visual coverage of the blind zone to the immediate rear was provided by a CCTV system. To ensure that the CAD modelled solutions did not have a detrimental effect on other aspects of the driving task, and before road trials were conducted on the public highway, a number of user tests were carried out under controlled experimental conditions. Results showed that the minimum radii of curvature, currently stipulated for rear view mirrors, could be reduced without causing significantly greater numbers of driver judgement errors compared with existing mirror specifications. Final verification of the field of view improvement specification proposed was achieved through road trials using drivers in modified large vehicles
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