Designing visual peripheral information system for fully automated driving /
Having a fully automated vehicle (AV), a human driver only decides on the final destination, and the AV will handle all the driving tasks and decisions. Therefore, human drivers have the freedom to follow their own preferred activities and become passengers or occupants. Engaging in non-driving rela...
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| Format: | Software eBook |
| Language: | English |
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2019.
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| 001 | 115475 | ||
| 003 | UTeM | ||
| 005 | 20191113104226.0 | ||
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| 008 | 191017t20192019ne ||||| |||| 00| | eng d | ||
| 999 | |c 115475 |d 115475 | ||
| 020 | |a 9789038648064 |q paperback |c gift | ||
| 040 | |a UTeM |b eng |c UTeM |e rda | ||
| 090 | 0 | 0 | |a TL152.8 |b .J83 2019 |
| 100 | 0 | |a Juffrizal Karjanto, |e author. |9 79296 | |
| 245 | 1 | 0 | |a Designing visual peripheral information system for fully automated driving / |c Juffrizal Karjanto. |
| 264 | 1 | |c 2019. | |
| 264 | 4 | |c ©2019 | |
| 300 | |a xvii, 203 pages : |b colour illustrations, charts, photographs ; |c 24 cm + |e 1 computer disc (12cm) | ||
| 336 | |a text |2 rdacontent | ||
| 336 | |a still image |2 rdacontent | ||
| 337 | |a unmediated |2 rdamedia | ||
| 338 | |a volume |2 rdacarrier | ||
| 347 | |a text file |b PDF |c 7.46 MB |2 rda | ||
| 500 | |a Accompanied by CD : CDR 19664. | ||
| 504 | |a Reference : pages 157-175. | ||
| 520 | |a Having a fully automated vehicle (AV), a human driver only decides on the final destination, and the AV will handle all the driving tasks and decisions. Therefore, human drivers have the freedom to follow their own preferred activities and become passengers or occupants. Engaging in non-driving related tasks (NRT) will make the occupants of the AV become unaware of the intentions of the vehicle with regards to navigation and unable to anticipate upcoming events. As most if not all of the attention will be channeled to the NRT, they will experience poor situation awareness. This scenario will make the occupants of the AV become unprepared for the forces generated from the horizontal accelerations (e.g., acceleration, braking, and cornering) and become more susceptible to the development of motion sickness. The primary motivation of this thesis is to study ways to enhance situation awareness and mitigate motion sickness from developing when the occupant of an AV is engaging in the NRT. In addition, the means to achieve these goals preferably will not interrupt the performance or the experience in engaging with the NRT. This steers the work into the direction of peripheral displays or peripheral information systems. The first part of the thesis aims at understanding the problems and opportunities that arise from the development of AVs. First, we formulate the interesting research questions that serve as the backbone of our research and also fulfill our ambitions as researchers. Then, we describe four key aspects that form the theoretical basis of the work presented in this thesis. We begin with the explanation of automation and its taxonomy levels. Next, we explain the development in regard to AVs and the kind of activities that are envisioned by both the future users and automakers of the AV. Then, we show that engaging NRT will lead to diminished situation awareness and increased susceptibility to motion sickness. Lastly, we describe peripheral vision and the potential of using peripheral information system in order to achieve the aforementioned goals. Since the driving style is an important determinant of the forces generated from the horizontal accelerations, a first step is to investigate the driving style of AVs. In the second part of the thesis, we present the development of driving styles of AV and the on-road AV simulator. For the development of the driving styles of AV, we present the study in three phases. First, we begin with the understanding of driving styles of human drivers and the associated personality traits. Then, we perform the classification of human drivers that was done based on the personality trait of sensation-seeking as a dimension. In the second phase, we propose three driving styles for an AV. Then, we perform a study with the proposed driving styles tested on a real road at three different points of interest with the assistance of a specially designed device. In the third phase, we present a study with the three proposed driving styles of an AV on human drivers who were first classified as either assertive or defensive drivers according to the sensation-seeking dimension. The proposed driving styles were then tested when leaving a junction, decelerating when approaching a junction, and undertaking a corner. In this study, we found that regardless of the type of driver, both of them prefer a more defensive driving style of an AV. For the development of on-road AV simulator, we establish the Mobility Lab (ML), an instrumented car that was developed to support research in AV. Within this chapter, we present the system architecture of ML and also a validation study which to validate the ability of ML in performing AV driving experience. Here, we show that our setup can produce highly consistency test rides that simulate the AV driving on the real road. In the third part of the thesis, we present two major studies that explore the possibilities of using prototypes of peripheral information system in enhancing the situation awareness and mitigate the development of motion sickness, especially when watching a video/movie and reading inside a moving AV. First, we explain the three main types of measurements that we applied in both of our studies. The measurements are ML-based measures, participant-based measures, and prototype-based measure. For the ML-based measures, three measurements of interests were the dominant frequency of motion, the dosage of induced motion sickness, and a subjective rating of the simulated AV test ride. For the participant-based measures, situation awareness and mental workload of the participant of the study were measured. The experienced motion sickness by the participant was also measured using both a self-rating questionnaire and a physiological measurement (heart rate variability (HRV)). In addition, user experience in interacting with the aforementioned prototypes was assessed as the prototype-based measure. In the first study (watching a video/movie in a moving AV), with the presence of our prototype, we found that situation awareness was quickly enhanced, but participants still experienced slight motion sickness. In the second study, a different prototype was developed to reduce the participant’s need to look outside while reading in a moving AV. We found that again situation awareness can be elevated, but the multi-movements presented in front of the participant might amplify the development of motion sickness. In the final part of the thesis, we conclude our contributions to the research area. First, from the second part of the study, we contribute to the development of a future driving style of the AV. We show that future AV users might want the vehicle to be driven in a more defensive manner compared to their own driving style. Next, we contribute the alternative way to perform AV-related studies rather than using the common fixed/moving based simulator. We propose the use of on-road AV simulator that provides richer and real experience hence providing natural reaction from the participants of the study. Our proposed prototypes contribute to the design considerations of future interfaces inside the interior of an AV. Our proposed prototypes may increase the situation awareness quickly in a more passive and unobtrusive way, but we believe active prevention may be required to mitigate the development of motion sickness completely. | ||
| 650 | 0 | |a Autonomous vehicles. |9 162673 | |
| 650 | 0 | |a Automobiles |x Automatic control. |9 23579 | |
| 650 | 0 | |a Motor vehicles |x Automatic control. |9 19096 | |
| 710 | 2 | |a Eindhoven University of Technology (TU/e), |e issuing body. |9 162233 | |
| 720 | |a Professor Dr. Matthias | ||
| 790 | |a Department of Industrial Design | ||
| 791 | |a Doctor of Philosophy in Industrial Design | ||
| 792 | |a 2019 | ||
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| 997 | |a GIFT | ||
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