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    ์ฐจ๋Ÿ‰์šฉ ํ—ค๋“œ์—… ๋””์Šคํ”Œ๋ ˆ์ด ์„ค๊ณ„์— ๊ด€ํ•œ ์ธ๊ฐ„๊ณตํ•™ ์—ฐ๊ตฌ

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    ํ•™์œ„๋…ผ๋ฌธ (๋ฐ•์‚ฌ) -- ์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› : ๊ณต๊ณผ๋Œ€ํ•™ ์‚ฐ์—…๊ณตํ•™๊ณผ, 2020. 8. ๋ฐ•์šฐ์ง„.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.์ž๋™์ฐจ ํ—ค๋“œ์—… ๋””์Šคํ”Œ๋ ˆ์ด๋Š” ์ฐจ๋‚ด ๋””์Šคํ”Œ๋ ˆ์ด ์ค‘ ํ•˜๋‚˜๋กœ ์šด์ „์ž์—๊ฒŒ ํ•„์š”ํ•œ ์ •๋ณด๋ฅผ ์ „๋ฐฉ์— ํ‘œ์‹œํ•จ์œผ๋กœ์จ, ์šด์ „์ž๊ฐ€ ์šด์ „์„ ํ•˜๋Š” ๋™์•ˆ ์ „๋ฐฉ์œผ๋กœ ์‹œ์„ ์„ ์œ ์ง€ํ•  ์ˆ˜ ์žˆ๊ฒŒ ๋„์™€์ค€๋‹ค. ์ด๋ฅผ ํ†ตํ•ด ์šด์ „์ž์˜ ์ฃผ์˜ ๋ถ„์‚ฐ์„ ์ค„์ด๊ณ , ์•ˆ์ „์„ ํ–ฅ์ƒ์‹œํ‚ค๋Š”๋ฐ ๋„์›€์ด ๋  ์ˆ˜ ์žˆ๋‹ค. ์ž๋™์ฐจ ํ—ค๋“œ์—… ๋””์Šคํ”Œ๋ ˆ์ด ์‹œ์Šคํ…œ์€ ์•ฝ 30๋…„ ์ „ ์šด์ „์ž์˜ ์•ˆ์ „์„ ํ–ฅ์ƒ์‹œํ‚ค๊ธฐ ์œ„ํ•œ ์ˆ˜๋‹จ์œผ๋กœ ์ž๋™์ฐจ ์‚ฐ์—…์— ์ฒ˜์Œ ๋„์ž…๋œ ์ด๋ž˜๋กœ ํ˜„์žฌ๊นŒ์ง€ ๋‹ค์–‘ํ•œ ์ƒ์šฉ์ฐจ์—์„œ ์‚ฌ์šฉ๋˜๊ณ  ์žˆ๋‹ค. ์•ˆ์ „๊ณผ ํŽธ์˜ ์ธก๋ฉด์—์„œ ์ž๋™์ฐจ ํ—ค๋“œ์—… ๋””์Šคํ”Œ๋ ˆ์ด์˜ ์‚ฌ์šฉ์€ ์ ์  ๋” ์ฆ๊ฐ€ํ•  ๊ฒƒ์œผ๋กœ ์˜ˆ์ƒ๋œ๋‹ค. ๊ทธ๋Ÿฌ๋‚˜ ์ด๋Ÿฌํ•œ ์ž๋™์ฐจ ํ—ค๋“œ์—… ๋””์Šคํ”Œ๋ ˆ์ด์˜ ์ž ์žฌ์  ์ด์ ๊ณผ ๋ฐœ์ „ ๊ฐ€๋Šฅ์„ฑ์—๋„ ๋ถˆ๊ตฌํ•˜๊ณ , ์œ ์šฉํ•œ ์ž๋™์ฐจ ํ—ค๋“œ์—… ๋””์Šคํ”Œ๋ ˆ์ด๋ฅผ ์„ค๊ณ„ํ•˜๋Š” ๊ฒƒ์€ ์—ฌ์ „ํžˆ ์–ด๋ ค์šด ๋ฌธ์ œ์ด๋‹ค. ์ด์— ๋ณธ ์—ฐ๊ตฌ๋Š” ์ด๋Ÿฌํ•œ ๋ฌธ์ œ๋ฅผ ํ•ด๊ฒฐํ•˜๊ณ , ๊ถ๊ทน์ ์œผ๋กœ ์œ ์šฉํ•œ ์ž๋™์ฐจ ํ—ค๋“œ์—… ๋””์Šคํ”Œ๋ ˆ์ด ์„ค๊ณ„์— ๊ธฐ์—ฌํ•˜๊ณ ์ž ์ด 4๊ฐ€์ง€ ์—ฐ๊ตฌ๋ฅผ ์ˆ˜ํ–‰ํ•˜์˜€๋‹ค. ์ฒซ ๋ฒˆ์งธ ์—ฐ๊ตฌ๋Š” ์ž๋™์ฐจ ํ—ค๋“œ์—… ๋””์Šคํ”Œ๋ ˆ์ด์˜ ๊ธฐ๋Šฅ ์š”๊ตฌ ์‚ฌํ•ญ๊ณผ ๊ด€๋ จ๋œ ๊ฒƒ์œผ๋กœ์„œ, ํ—ค๋“œ์—… ๋””์Šคํ”Œ๋ ˆ์ด ์‹œ์Šคํ…œ์„ ํ†ตํ•ด ์–ด๋–ค ์ •๋ณด๋ฅผ ์ œ๊ณตํ•  ๊ฒƒ์ธ๊ฐ€์— ๋Œ€ํ•œ ๋‹ต์„ ๊ตฌํ•˜๊ณ ์ž ํ•˜์˜€๋‹ค. ์ด์— ์ฃผ์š” ์ž๋™์ฐจ ์ œ์กฐ์—…์ฒด๋“ค์˜ ํ—ค๋“œ์—… ๋””์Šคํ”Œ๋ ˆ์ด ์ œํ’ˆ๋“ค๊ณผ, ์ž๋™์ฐจ ํ—ค๋“œ์—… ๋””์Šคํ”Œ๋ ˆ์ด์˜ ๋‹ค์–‘ํ•œ ๊ธฐ๋Šฅ๋“ค์„ ์ œ์•ˆํ•œ ํ•™์ˆ  ์—ฐ๊ตฌ, ๊ทธ๋ฆฌ๊ณ  ์šด์ „์ž์˜ ์ •๋ณด ์š”๊ตฌ ์‚ฌํ•ญ๋“ค์„ ์ฒด๊ณ„์  ๋ฌธํ—Œ ๊ณ ์ฐฐ ๋ฐฉ๋ฒ•๋ก ์„ ํ†ตํ•ด ํฌ๊ด„์ ์œผ๋กœ ์กฐ์‚ฌํ•˜์˜€๋‹ค. ์ž๋™์ฐจ ํ—ค๋“œ์—… ๋””์Šคํ”Œ๋ ˆ์ด์˜ ๊ธฐ๋Šฅ์  ์š”๊ตฌ ์‚ฌํ•ญ์— ๋Œ€ํ•˜์—ฌ ๊ฐœ๋ฐœ์ž, ์—ฐ๊ตฌ์ž, ์‚ฌ์šฉ์ž ์ธก๋ฉด์„ ๋ชจ๋‘ ๊ณ ๋ คํ•œ ํ†ตํ•ฉ๋œ ์ง€์‹์„ ์ „๋‹ฌํ•˜๊ณ , ์ด๋ฅผ ํ†ตํ•ด ์ž๋™์ฐจ ํ—ค๋“œ์—… ๋””์Šคํ”Œ๋ ˆ์ด์˜ ๊ธฐ๋Šฅ ์š”๊ตฌ ์‚ฌํ•ญ์— ๋Œ€ํ•œ ํ–ฅํ›„ ์—ฐ๊ตฌ ๋ฐฉํ–ฅ์„ ์ œ์‹œํ•˜์˜€๋‹ค. ๋‘ ๋ฒˆ์งธ ์—ฐ๊ตฌ๋Š” ์•ˆ์ „ ๊ด€๋ จ ์ •๋ณด๋ฅผ ์ œ๊ณตํ•˜๋Š” ์ž๋™์ฐจ ํ—ค๋“œ์—… ๋””์Šคํ”Œ๋ ˆ์ด์˜ ์ธํ„ฐํŽ˜์ด์Šค ์„ค๊ณ„์™€ ๊ด€๋ จ๋œ ๊ฒƒ์œผ๋กœ, ํ—ค๋“œ์—… ๋””์Šคํ”Œ๋ ˆ์ด ์‹œ์Šคํ…œ์„ ํ†ตํ•ด ์•ˆ์ „ ๊ด€๋ จ ์ •๋ณด๋ฅผ ์–ด๋–ป๊ฒŒ ์ œ๊ณตํ•  ๊ฒƒ์ธ๊ฐ€์— ๋Œ€ํ•œ ๋‹ต์„ ๊ตฌํ•˜๊ณ ์ž ํ•˜์˜€๋‹ค. ์‹ค์ œ ์ž๋™์ฐจ๋“ค์˜ ํ—ค๋“œ์—… ๋””์Šคํ”Œ๋ ˆ์ด ์‹œ์Šคํ…œ์—์„œ๋Š” ์–ด๋–ค ๋””์Šคํ”Œ๋ ˆ์ด ์ปจ์…‰๋“ค์ด ์‚ฌ์šฉ๋˜์—ˆ๋Š”์ง€, ๊ทธ๋ฆฌ๊ณ  ํ•™๊ณ„์—์„œ ์ œ์•ˆ๋œ ๋””์Šคํ”Œ๋ ˆ์ด ์ปจ์…‰๋“ค์—๋Š” ์–ด๋–ค ๊ฒƒ๋“ค์ด ์žˆ๋Š”์ง€ ์ฒด๊ณ„์  ๋ฌธํ—Œ ๊ณ ์ฐฐ ๋ฐฉ๋ฒ•๋ก ์„ ํ†ตํ•ด ๊ฒ€ํ† ํ•˜์˜€๋‹ค. ๊ฒ€ํ† ๋œ ๊ฒฐ๊ณผ๋Š” ๊ฐ ๋””์Šคํ”Œ๋ ˆ์ด์˜ ๊ธฐ๋Šฅ๊ณผ ๊ตฌ์กฐ, ๊ทธ๋ฆฌ๊ณ  ์ž‘๋™ ๋ฐฉ์‹์— ๋”ฐ๋ผ ์ •๋ฆฌ๋˜์—ˆ๊ณ , ๊ด€๋ จ๋œ ์ธ๊ฐ„๊ณตํ•™์  ๋””์Šคํ”Œ๋ ˆ์ด ์„ค๊ณ„ ์›์น™๊ณผ ์‹คํ—˜์  ์—ฐ๊ตฌ ๊ฒฐ๊ณผ๋“ค์„ ํ•จ๊ป˜ ๊ฒ€ํ† ํ•˜์˜€๋‹ค. ๊ฒ€ํ† ๋œ ๊ฒฐ๊ณผ๋ฅผ ๋ฐ”ํƒ•์œผ๋กœ ์•ˆ์ „ ๊ด€๋ จ ์ •๋ณด๋ฅผ ์ œ๊ณตํ•˜๋Š” ์ž๋™์ฐจ ํ—ค๋“œ์—… ๋””์Šคํ”Œ๋ ˆ์ด์˜ ์ธํ„ฐํŽ˜์ด์Šค ์„ค๊ณ„์— ๋Œ€ํ•œ ํ–ฅํ›„ ์—ฐ๊ตฌ ๋ฐฉํ–ฅ์„ ์ œ์‹œํ•˜์˜€๋‹ค. ์„ธ ๋ฒˆ์งธ ์—ฐ๊ตฌ๋Š” ์ž๋™์ฐจ ํ—ค๋“œ์—… ๋””์Šคํ”Œ๋ ˆ์ด ๊ธฐ๋ฐ˜์˜ ์ œ์–ด๊ถŒ ์ „ํ™˜ ๊ด€๋ จ ์ธํ„ฐํŽ˜์ด์Šค ์„ค๊ณ„์™€ ํ‰๊ฐ€์— ๊ด€ํ•œ ๊ฒƒ์ด๋‹ค. ์ œ์–ด๊ถŒ ์ „ํ™˜์ด๋ž€, ์ž์œจ์ฃผํ–‰ ์ƒํƒœ์—์„œ ์šด์ „์ž๊ฐ€ ์ง์ ‘ ์šด์ „์„ ํ•˜๋Š” ์ˆ˜๋™ ์šด์ „ ์ƒํƒœ๋กœ ์ „ํ™˜์ด ๋˜๋Š” ๊ฒƒ์„ ์˜๋ฏธํ•œ๋‹ค. ๋”ฐ๋ผ์„œ ๊ฐ‘์ž‘์Šค๋Ÿฐ ์ œ์–ด๊ถŒ ์ „ํ™˜ ์š”์ฒญ์ด ๋ฐœ์ƒํ•˜๋Š” ๊ฒฝ์šฐ, ์šด์ „์ž๊ฐ€ ์•ˆ์ „ํ•˜๊ฒŒ ๋Œ€์ฒ˜ํ•˜๊ธฐ ์œ„ํ•ด์„œ๋Š” ๋น ๋ฅธ ์ƒํ™ฉ ํŒŒ์•…๊ณผ ์˜์‚ฌ ๊ฒฐ์ •์ด ํ•„์š”ํ•˜๊ฒŒ ๋˜๊ณ , ์ด๋ฅผ ํšจ๊ณผ์ ์œผ๋กœ ๋„์™€์ฃผ๊ธฐ ์œ„ํ•œ ์ธํ„ฐํŽ˜์ด์Šค ์„ค๊ณ„์— ๋Œ€ํ•ด ์—ฐ๊ตฌํ•  ํ•„์š”์„ฑ์ด ์žˆ๋‹ค. ์ด์— ๋ณธ ์—ฐ๊ตฌ์—์„œ๋Š” ์ž๋™์ฐจ ํ—ค๋“œ์—… ๋””์Šคํ”Œ๋ ˆ์ด ๊ธฐ๋ฐ˜์˜ ์ด 4๊ฐœ์˜ ์ œ์–ด๊ถŒ ์ „ํ™˜ ๊ด€๋ จ ๋””์Šคํ”Œ๋ ˆ์ด(๊ธฐ์ค€ ๋””์Šคํ”Œ๋ ˆ์ด, ๋ฏธ๋‹ˆ๋งต ๋””์Šคํ”Œ๋ ˆ์ด, ํ™”์‚ดํ‘œ ๋””์Šคํ”Œ๋ ˆ์ด, ๋ฏธ๋‹ˆ๋งต๊ณผ ํ™”์‚ดํ‘œ ๋””์Šคํ”Œ๋ ˆ์ด)๋ฅผ ์ œ์•ˆํ•˜์˜€๊ณ , ์ œ์•ˆ๋œ ๋””์Šคํ”Œ๋ ˆ์ด ๋Œ€์•ˆ๋“ค์€ ์ฃผํ–‰ ์‹œ๋ฎฌ๋ ˆ์ดํ„ฐ ์‹คํ—˜์„ ํ†ตํ•ด ์ œ์–ด๊ถŒ ์ „ํ™˜ ์ˆ˜ํ–‰ ๋Šฅ๋ ฅ๊ณผ ์•ˆ๊ตฌ์˜ ์›€์ง์ž„ ํŒจํ„ด, ๊ทธ๋ฆฌ๊ณ  ์‚ฌ์šฉ์ž์˜ ์ฃผ๊ด€์  ํ‰๊ฐ€ ์ธก๋ฉด์—์„œ ํ‰๊ฐ€๋˜์—ˆ๋‹ค. ๋˜ํ•œ ์ œ์•ˆ๋œ ๋””์Šคํ”Œ๋ ˆ์ด ๋Œ€์•ˆ๋“ค์— ๋Œ€ํ•ด ์šด์ „์ž๋“ค์˜ ์ดˆ๊ธฐ ์‹ ๋ขฐ๋„ ๊ฐ’์„ ์ธก์ •ํ•˜์—ฌ ๊ฐ ๋””์Šคํ”Œ๋ ˆ์ด์— ๋”ฐ๋ฅธ ์šด์ „์ž๋“ค์˜ ํ‰๊ท  ์‹ ๋ขฐ๋„ ์ ์ˆ˜์— ๋”ฐ๋ผ ์ œ์–ด๊ถŒ ์ „ํ™˜ ์ˆ˜ํ–‰ ๋Šฅ๋ ฅ๊ณผ ์•ˆ๊ตฌ์˜ ์›€์ง์ž„ ํŒจํ„ด, ๊ทธ๋ฆฌ๊ณ  ์ฃผ๊ด€์  ํ‰๊ฐ€๊ฐ€ ์–ด๋–ป๊ฒŒ ๋‹ฌ๋ผ์ง€๋Š”์ง€ ๋ถ„์„ํ•˜์˜€๋‹ค. ์‹คํ—˜ ๊ฒฐ๊ณผ, ์ œ์–ด๊ถŒ ์ „ํ™˜ ์ƒํ™ฉ์—์„œ ์ž๋™ํ™”๋œ ์‹œ์Šคํ…œ์ด ์ œ์•ˆํ•˜๋Š” ์ •๋ณด์™€ ๊ทธ์™€ ๊ด€๋ จ๋œ ์ฃผ๋ณ€ ์ƒํ™ฉ ์ •๋ณด๋ฅผ ํ•จ๊ป˜ ์ œ์‹œํ•ด ์ฃผ๋Š” ๋””์Šคํ”Œ๋ ˆ์ด๊ฐ€ ๊ฐ€์žฅ ์ข‹์€ ๊ฒฐ๊ณผ๋ฅผ ๋ณด์—ฌ์ฃผ์—ˆ๋‹ค. ๋˜ํ•œ ๊ฐ ๋””์Šคํ”Œ๋ ˆ์ด์— ๋Œ€ํ•œ ์šด์ „์ž์˜ ์ดˆ๊ธฐ ์‹ ๋ขฐ๋„ ์ ์ˆ˜๋Š” ๋””์Šคํ”Œ๋ ˆ์ด์˜ ์‹ค์ œ ์‚ฌ์šฉ ํ–‰ํƒœ์™€ ๋ฐ€์ ‘ํ•œ ๊ด€๋ จ์ด ์žˆ์Œ์„ ์•Œ ์ˆ˜ ์žˆ์—ˆ๋‹ค. ์‹ ๋ขฐ๋„ ์ ์ˆ˜์— ๋”ฐ๋ผ ์‹ ๋ขฐ๋„๊ฐ€ ๋†’์€ ๊ทธ๋ฃน๊ณผ ๋‚ฎ์€ ๊ทธ๋ฃน์œผ๋กœ ๋ถ„๋ฅ˜๋˜์—ˆ๊ณ , ์‹ ๋ขฐ๋„๊ฐ€ ๋†’์€ ๊ทธ๋ฃน์€ ์ œ์•ˆ๋œ ๋””์Šคํ”Œ๋ ˆ์ด๋“ค์ด ๋ณด์—ฌ์ฃผ๋Š” ์ •๋ณด๋ฅผ ์ฃผ๋กœ ๋ฏฟ๊ณ  ๋”ฐ๋ฅด๋Š” ๊ฒฝํ–ฅ์ด ์žˆ์—ˆ๋˜ ๋ฐ˜๋ฉด, ์‹ ๋ขฐ๋„๊ฐ€ ๋‚ฎ์€ ๊ทธ๋ฃน์€ ๋ฃธ ๋ฏธ๋Ÿฌ๋‚˜ ์‚ฌ์ด๋“œ ๋ฏธ๋Ÿฌ๋ฅผ ํ†ตํ•ด ์ฃผ๋ณ€ ์ƒํ™ฉ ์ •๋ณด๋ฅผ ๋” ํ™•์ธ ํ•˜๋Š” ๊ฒฝํ–ฅ์„ ๋ณด์˜€๋‹ค. ๋„ค ๋ฒˆ์งธ ์—ฐ๊ตฌ๋Š” ์ „๋ฉด ์œ ๋ฆฌ์ฐฝ์—์„œ์˜ ์ธํ„ฐ๋ž™ํ‹ฐ๋ธŒ ํ—ค๋“œ์—… ๋””์Šคํ”Œ๋ ˆ์ด์˜ ์ตœ์  ์œ„์น˜๋ฅผ ๊ฒฐ์ •ํ•˜๋Š” ๊ฒƒ์œผ๋กœ์„œ ์ฃผํ–‰ ์‹œ๋ฎฌ๋ ˆ์ดํ„ฐ ์‹คํ—˜์„ ํ†ตํ•ด ๋””์Šคํ”Œ๋ ˆ์ด์˜ ์œ„์น˜์— ๋”ฐ๋ผ ์šด์ „์ž์˜ ์ฃผํ–‰ ์ˆ˜ํ–‰ ๋Šฅ๋ ฅ, ์ธํ„ฐ๋ž™ํ‹ฐ๋ธŒ ๋””์Šคํ”Œ๋ ˆ์ด ์กฐ์ž‘ ๊ด€๋ จ ๊ณผ์—… ์ˆ˜ํ–‰ ๋Šฅ๋ ฅ, ์‹œ๊ฐ์  ์ฃผ์˜ ๋ถ„์‚ฐ, ์„ ํ˜ธ๋„, ๊ทธ๋ฆฌ๊ณ  ์ž‘์—… ๋ถ€ํ•˜๊ฐ€ ํ‰๊ฐ€๋˜์—ˆ๋‹ค. ํ—ค๋“œ์—… ๋””์Šคํ”Œ๋ ˆ์ด์˜ ์œ„์น˜๋Š” ์ „๋ฉด ์œ ๋ฆฌ์ฐฝ์—์„œ ์ผ์ •ํ•œ ๊ฐ„๊ฒฉ์œผ๋กœ ์ด 9๊ฐœ์˜ ์œ„์น˜๊ฐ€ ๊ณ ๋ ค๋˜์—ˆ๋‹ค. ๋ณธ ์—ฐ๊ตฌ์—์„œ ํ™œ์šฉ๋œ ์ธํ„ฐ๋ž™ํ‹ฐ๋ธŒ ๋””์Šคํ”Œ๋ ˆ์ด๋Š” ์Œ์•… ์„ ํƒ์„ ์œ„ํ•œ ์Šคํฌ๋กค ๋ฐฉ์‹์˜ ๋‹จ์ผ ๋””์Šคํ”Œ๋ ˆ์ด์˜€๊ณ , ์šด์ „๋Œ€์— ์žฅ์ฐฉ๋œ ๋ฒ„ํŠผ์„ ํ†ตํ•ด ๋””์Šคํ”Œ๋ ˆ์ด๋ฅผ ์กฐ์ž‘ํ•˜์˜€๋‹ค. ์‹คํ—˜ ๊ฒฐ๊ณผ, ์ธํ„ฐ๋ž™ํ‹ฐ๋ธŒ ํ—ค๋“œ์—… ๋””์Šคํ”Œ๋ ˆ์ด์˜ ์œ„์น˜๊ฐ€ ๋ชจ๋“  ํ‰๊ฐ€ ์ฒ™๋„, ์ฆ‰ ์ฃผํ–‰ ์ˆ˜ํ–‰ ๋Šฅ๋ ฅ, ๋””์Šคํ”Œ๋ ˆ์ด ์กฐ์ž‘ ๊ณผ์—… ์ˆ˜ํ–‰ ๋Šฅ๋ ฅ, ์‹œ๊ฐ์  ์ฃผ์˜ ๋ถ„์‚ฐ, ์„ ํ˜ธ๋„, ๊ทธ๋ฆฌ๊ณ  ์ž‘์—… ๋ถ€ํ•˜์— ์˜ํ–ฅ์„ ๋ฏธ์นจ์„ ์•Œ ์ˆ˜ ์žˆ์—ˆ๋‹ค. ๋ชจ๋“  ํ‰๊ฐ€ ์ง€ํ‘œ๋ฅผ ๊ณ ๋ คํ–ˆ์„ ๋•Œ, ์ธํ„ฐ๋ž™ํ‹ฐ๋ธŒ ํ—ค๋“œ์—… ๋””์Šคํ”Œ๋ ˆ์ด์˜ ์œ„์น˜๋Š” ์šด์ „์ž๊ฐ€ ๋˜‘๋ฐ”๋กœ ์ „๋ฐฉ์„ ๋ฐ”๋ผ๋ณผ ๋•Œ์˜ ์‹œ์•ผ ๊ตฌ๊ฐ„, ์ฆ‰ ์ „๋ฉด ์œ ๋ฆฌ์ฐฝ์—์„œ์˜ ์™ผ์ชฝ ์•„๋ž˜ ๋ถ€๊ทผ์ด ๊ฐ€์žฅ ์ตœ์ ์ธ ๊ฒƒ์œผ๋กœ ๋‚˜ํƒ€๋‚ฌ๋‹ค.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 ๊ตญ๋ฌธ์ดˆ๋ก 187Docto

    Reaktion menschlicher (Mit-)Fahrer auf hochautomatisierte Fahrzeuge im Mischverkehr auf der Autobahn und im urbanen Raum

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    In the future, highly automated vehicles will be introduced in road traffic, first on highways, and later in urban areas. The introduction will result in a long transition phase with mixed traffic. This transition phase poses new challenges for humans as passengers inside highly automated vehicles and for humans as drivers interacting with these vehicles in mixed traffic. Thus far, human drivers lack experience with highly automated vehicles and driving in mixed traffic. In addition, it can be expected that highly automated vehicles will drive in a more rule-compliant and defensive way than human drivers. This may cause conflicts with human drivers in mixed traffic, and lead to passenger discomfort and perceived risk. This dissertation investigated how humans react to highly automated vehicles in mixed traffic, taking both inside perspective of passengers and the outside perspective of human drivers into account. To this end, four psychological experiments. From the outside perspective, this dissertation investigated human driversโ€™ first contact with highly automated vehicles in dyadic interactions on the highway (Study 1) and repeated contact on longer highway sections (Study 2). Results showed that human drivers rate the rule-compliant automated driving behavior as pleasant and safe in dyadic interactions. However, human drivers feel slowed down by preceding highly automated vehicles on longer stretches of highway, which can be a potential hazard. Furthermore, an external labelling of highly automated vehicles may be recommendable in the long run. From the inside perspective of passengers, this dissertation investigated urban mixed traffic interactions with cyclists and pedestrians in longitudinal traffic (Study 3) and at a junction (Study 4). Results show that passengers do not accept any risk during highly automated driving and passengers want an early behavioral reaction of the highly automated vehicle to vulnerable road users in the driving environment. Across the four studies, the present dissertation shows that highly automated vehicles drive noticeably differently, which both passengers and manual drivers can perceive. However, highly automated driving behavior is perceived as unpleasant at maximum, but not as dangerous. When designing highly automated driving functions, both driver and passenger preferences should be considered equally. Future studies should examine the preferences of human road users regarding automated driving behavior.In Zukunft werden hochautomatisierte Fahrzeuge im StraรŸenverkehr eingefรผhrt, zunรคchst auf der Autobahn, und spรคter auch im urbanen Raum. Die Einfรผhrung dieser Technologie resultiert in einer langen รœbergangsphase mit Mischverkehr. Dieser รœbergang stellt Menschen als Passagiere und Fahrer vor neue Herausforderungen. Bislang fehlt Fahrern die Erfahrung mit hochautomatisierten Fahrzeugen und dem Fahren im Mischverkehr. Zudem ist zu erwarten, dass sich hochautomatisierte Fahrzeuge regelkonformer und defensiver fahren als menschliche Fahrer. Das kรถnnte zu Konflikten mit anderen Verkehrsteilnehmern, und zu Diskomfort und Risikoerleben beim Passagier fรผhren. Diese Dissertation untersuchte mithilfe von psychologischen Experimenten wie menschliche Fahrer auf hochautomatisierte Systeme aus der Passagiersicht und aus der AuรŸensicht als manuelle Fahrer im Mischverkehr reagieren. Ein weiteres Ziel war es zu verstehen, wie hochautomatisierte Fahrzeuge fahren sollen, damit sich Passagiere sicher fรผhlen. Aus der AuรŸensicht menschlicher Fahrer untersuchte diese Dissertation den Erstkontakt mit hochautomatisierten Fahrzeugen in dyadischen Interaktionen (Studie 1) und im wiederholten Kontakt (Studie 2) auf lรคngeren Autobahnabschnitten. Die Ergebnisse zeigen, dass Fahrer das regelkonforme hochautomatisierte Fahrverhalten in dyadischen Interaktionen als angenehm und sicher bewerten. Allerdings fรผhlen sich Fahrer auf lรคngeren Strecken ausgebremst, wodurch ein Gefahrenpotenzial entsteht kann. Weiterhin ist eine AuรŸenkennzeichnung auf lรคngere Sicht zu empfehlen. Aus der Passagiersicht untersuchte diese Dissertation urbane Mischverkehrsinteraktion im longitudinalen Verkehr (Studie 3) und an einer Einmรผndung (Studie 4). Die Ergebnisse zeigen, dass Passagiere keinerlei Risiko eingehen wollen und sich eine frรผhzeitige Verhaltensreaktion des hochautomatisierten Fahrzeugs auf schwรคchere Verkehrsteilnehmer in die Fahrumgebung wรผnschen. Studienรผbergreifend zeigt sich, dass hochautomatisierte Fahrzeuge merklich anders fahren, was Passagiere als auch fรผr manuelle Fahrer wahrnehmen kรถnnen. Automatisiertes Fahrverhalten wird aber maximal als unangenehm, nicht als gefรคhrlich bewertet. Bei der technischen Auslegung automatisierter Fahrfunktionen sollten die Prรคferenzen von Fahrern und Passagieren gleichermaรŸen berรผcksichtigt werden. Zukรผnftige Studien sollten die Prรคferenzen anderer menschlicher Verkehrsteilnehmer im Hinblick auf das Verhalten automatisierter Fahrzeuge weiter untersuchen

    Ehmi: Review and guidelines for deployment on autonomous vehicles

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    Human-machine interaction is an active area of research due to the rapid development of autonomous systems and the need for communication. This review provides further insight into the specific issue of the information flow between pedestrians and automated vehicles by evaluating recent advances in external human-machine interfaces (eHMI), which enable the transmission of state and intent information from the vehicle to the rest of the traffic participants. Recent developments will be explored and studies analyzing their effectiveness based on pedestrian feedback data will be presented and contextualized. As a result, we aim to draw a broad perspective on the current status and recent techniques for eHMI and some guidelines that will encourage future research and development of these systems

    Take It to the Curb: Scalable Communication Between Autonomous Cars and Vulnerable Road Users Through Curbstone Displays

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    Automated driving will require new approaches to the communication between vehicles and vulnerable road users (VRUs) such as pedestrians, e.g., through external human-machine interfaces (eHMIs). However, the majority of eHMI concepts are neither scalable (i.e., take into account complex traffic scenarios with multiple vehicles and VRUs), nor do they optimize traffic flow. Speculating on the upgrade of traffic infrastructure in the automated city, we propose Smart Curbs, a scalable communication concept integrated into the curbstone. Using a combination of immersive and non-immersive prototypes, we evaluated the suitability of our concept for complex urban environments in a user study (N = 18). Comparing the approach to a projection-based eHMI, our findings reveal that Smart Curbs are safer to use, as our participants spent less time on the road when crossing. Based on our findings, we discuss the potential of Smart Curbs to mitigate the scalability problem in AV-pedestrian communication and simultaneously enhance traffic flow

    Efficient Paradigm to Measure Street-Crossing Onset Time of Pedestrians in Video-Based Interactions with Vehicles

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    With self-driving vehicles (SDVs), pedestrians can no longer rely on a human driver. Previous research suggests that pedestrians may benefit from an external Humanโ€“Machine Interface (eHMI) displaying information to surrounding traffic participants. This paper introduces a natural methodology to compare eHMI concepts from a pedestrianโ€™s viewpoint. To measure eHMI effects on traffic flow, previous video-based studies instructed participants to indicate their crossing decision with interfering data collection devices, such as pressing a button or slider. We developed a quantifiable concept that allows participants to naturally step off a sidewalk to cross the street. Hidden force-sensitive resistor sensors recorded their crossing onset time (COT) in response to real-life videos of approaching vehicles in an immersive crosswalk simulation environment. We validated our method with an initial study of N = 34 pedestrians by showing (1) that it is able to detect significant eHMI effects on COT as well as subjective measures of perceived safety and user experience. The approach is further validated by (2) replicating the findings of a test track study and (3) participantsโ€™ reports that it felt natural to take a step forward to indicate their street crossing decision. We discuss the benefits and limitations of our method with regard to related approaches. Document type: Articl

    Willingness to Use Overhead Bridge Facilities Based on Theory of Planned Behavior

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    Overhead Bridge is the most vital crossing facilities for pedestrian to cross the busy road. This bridge is most important to implement the way to prevent the incident and to create awareness for the pedestrian to take a safety crossing behavior in order to avoid the accident crashes. The objective of this study is to estimate the frequency of overhead bridge usage and the relationship between characteristics and attitude among pedestrian. In understanding this output, Theory of Planned Behavior turned into used in the study to decide whether the characteristics and attitude affect the behavior of pedestrian that concerning the accident. This study was conducted at overhead bridges which located between Ayer Hitam to Batu Pahat. The sample for this study consists of 200 respondents. Set questionnaires which contain 30 items of questions were used to collect the data. The data were analysis using descriptive analysis, correlation analysis and regression analysis. Data was analyzed using SPSS.    There were 86 males and 114 females are evaluated the questionnaires. There were 157 respondents are who below 30 years and younger people. Correlation for all the factors of TPB are shows positive linear relationship. Attitude and Perceived Behavior Control show a significant to predict intention. Intention also showed strong relationship to the behavior. Lastly, Perceived Behavior Control showed strong relationship to the behavior. Attitude and Perceived Behavior Control may be having an impact on pedestrian to willing used overhead bridge and prevent pedestriansรขโ‚ฌโ„ข accidents and fatalities

    The role of route familiarity in traffic participantsโ€™ behaviour and transport psychology research:A systematic review

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    Studies of how transport behaviour (e.g., driving, cycling, and walking) is affected by practice and familiarity are not commonplace, in spite of the fact that much of our travel takes place on familiar, well-practiced routes. In other areas, it is well-established that repetition affects cognition, particularly memory and attention. The goals of the current systematic literature review were 1) to explore how researchers have described and examined the effects of peopleโ€™s familiarity with routes and road types, and 2) to obtain a better insight into the cognitive processes, and behaviour that occur in familiar road environments. The systematic review was conducted based on the principles described in the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA). Scopusโ€™ database was searched systematically using predefined search combinations which involved (1) the transport modes of driving, cycling, and walking; (2) research methods that typically involve route- or situation-familiar participants (e.g., naturalistic studies, observational studies and field operational tests); and (3) various words associated with route familiarity (e.g., familiar, everyday, and commute). Ninety-four studies met all inclusion criteria. Results were analysed in terms of the cognitive and behavioural changes associated with familiarity, as reported in the studies. Route familiarity was typically reported to reduce the amount of cognitive control used to process the immediate environment and to increase mind wandering, compared to unfamiliar situations. Familiarity also increased recall accuracy and opportunities for self-regulatory behaviour, and decreased task difficulty. Familiarity appears to have large effects on how people attend to and process the environment. Given the proportion of time people spend travelling in familiar situations, this low attention, high familiarity state should be considered the default mode and as a more integral context for experimental, naturalistic and observational research in transport psychology
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