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Yes / To understand the executive demands of the false-belief (FB) task relative to an alternative theory-of-mind (or mechanical causality) task, picture sequencing, the present study used path analyses. One hundred and sixty-six children between 3 and 6 years old completed the FB and picture-sequencing tasks, three executive function tasks (updating, inhibition, and shifting), and the receptive language test. The model with the best fit indicated that FB performance had a direct contribution from shifting of attention and inhibitory control, which was independent of the significant contribution made by picture sequencing. This model indicates that FB inference requires more executive processing than picture sequencing, which is used as an alternative task to measure theory of mind. Statement of contribution What is already known on this subject? The majority of researchers use the false-belief task to assess mentalizing ability in young children. Sources of information used in various different mentalizing tasks require different levels of cognitive demand. Many executive functions (EFs) are involved in children's judgements of false belief. What does this study add? A statistical model was created to compare processing requirements of false-belief and picture-sequencing tasks. The model supported the claim that the false-belief task involves considerably more than just mentalizing. Shifting the focus of attention was an EF that was found to be a key component of performance in the false-belief task. / Japanese Society for the Promotion of Science: KAKENHI Grant No. 16K04327.

Increasingly, many of today’s vehicles offer Society of Automotive Engineers (SAE) partially automated driving (PAD) and a limited number of SAE conditionally automated vehicles (CAD) are being developed. Vehicles with PAD systems support the driver through longitudinal and lateral control inputs. However, during PAD the driver must be prepared to take control of the vehicle at any time, requiring them to monitor the environment and PAD system. In contrast, during CAD the driver is not required to monitor the environment or system but must take control when prompted by the system. Given the ability of CAD vehicles to operate in PAD and manual driving, it is important to consider drivers’ mode awareness, that is, their ability to follow the state of the automated system and predict the implications of this status for vehicle control and monitoring responsibilities. In addition, since CAD does not require drivers to keep their visual or attentional resources on the driving task or environment, drivers are allowed to perform secondary tasks (i.e., non-driving related tasks (NDRTs)). Given that drivers will freely choose what types of tasks they do during CAD it is important to build an understanding of whether drivers will choose to engage in NDRTs in the CAD state, and drivers’ ability to perform NDRTs during CAD. To investigate driver’s mode awareness after transitions between modes, their willingness to engage in NDRTs, and their ability to perform scheduled smartphone NDRTs, an on-road experiment was conducted using the Wizard-of-Oz (WoZ) method to simulate a vehicle capable of Assisted Driving (similar to PAD) and Automated Driving (similar to CAD). A total of 36 drivers completed the on-road experiment, and experienced stable periods of manual driving, Assisted driving, and Automated driving, as well as transitions between these modes. After each transition, participants’ mode awareness was measured. Drivers’ performance of NDRTs and behavioral adaptation during Automated Driving was assessed by asking them to complete scheduled tasks on their smartphones. To measure driver willingness to engage in unscripted NDRTs during automated driving, participants were allowed to freely choose to engage in smartphone NDRTs between the scheduled tasks. It was hypothesized that drivers’ mode awareness of Assisted and Automated Driving and their willingness to engage and perform NDRTs during Automated Driving would increase with system exposure over the five planned activation periods of Automated Driving. Results from a mixed-model ANOVA showed that participants’ mode awareness of their role in Automated Driving statistically significantly increased from the first activation to the subsequent activations. There was no statistically significant effect of activation period on drivers’ willingness to engage in NDRTs, as measured by the mean percentage of time drivers chose to engage in NDRTs during Automated Driving, or driver’s ability to perform tasks, as measured by the mean task completion time of the experimenter administered smartphone NDRTs. The mean number of participants who chose to engage in an NDRT (73.8%) and the percentage of time spent on NDRTs per Automated Driving activation period (M=20.37%; SD=23.9), indicated that drivers were willing to engage in NDRTs during Automated Driving. In addition, drivers showed a high level of task performance, completing 95% of the scheduled NDRTs correctly. Altogether, these results suggest that drivers are willing to engage in and perform NDRTs during Automated Driving and that driver behavior during Automated Driving is consistent and stable during a two-hour exposure period. Finally, the findings indicate that requiring the participant to control the vehicle manually for a brief period prior to transitioning to a level of automation that allows the driver to take their visual and attentional resources away from the roadway environment results in statistically significantly less NDRT engagement compared to when participants transition directly to this level of automation. Overall, the findings from this study have methodological and potential system design implications that can help guide the future research on and design of automated driving systems. / M.S. / Increasingly, many of today’s vehicles offer automated driving technology (i.e., Assisted Driving) that support the driver through steering, braking, and accelerating the vehicle. However, during this level of automation the driver must be prepared to take control of the vehicle, requiring them to monitor the environment and the automated driving system. In addition, a limited number of vehicles offer automated driving technology (i.e., Automated Driving) that controls the vehicle and does not require the driver to monitor the environment or system, however, the driver must take control when prompted by the system. Vehicles capable of Automated Driving can also operate in Assisted and manual driving modes. Given the ability of Automated Driving vehicles to operate in Assisted and manual driving, it is important to consider driver’s ability to follow and predict the behavior of the automated system. In addition, since Automated Driving does not require drivers to keep their eyes or mind on driving or monitoring the road, drivers are allowed to perform secondary tasks. Since drivers are free to choose what types of tasks they do during Automated Driving, it is important to understand whether drivers will choose to engage in Secondary tasks, and their ability to perform these tasks during Automated Driving. To investigate driver’s mode awareness after transitions between modes, their willingness to engage in tasks, and their ability to perform scheduled smartphone tasks, an on-road experiment was conducted using the Wizard-of-Oz (WoZ) method. The WoZ method uses a concealed human to simulate an automated computer system, in this case an automated driving system. A total of 36 drivers completed the on-road experiment. The participants experienced periods of manual driving, Assisted driving, and Automated driving, as well as transitions between these modes. After each transition, participants’ knowledge of who/what was controlling the vehicle and the driver’s role in the current automated mode was measured. Drivers’ performance of tasks during Automated Driving was assessed by asking them to complete scheduled tasks on their smartphones. To measure driver willingness to engage in tasks during automated driving, participants were allowed to freely choose to engage in smartphone tasks between the scheduled tasks. It was hypothesized that drivers’ mode awareness of Assisted and Automated Driving and their willingness to engage and perform NDRTs during Automated Driving would increase with system exposure over the five planned activation periods of Automated Driving. Results showed that participants’ ability to identify their role in Automated Driving increased from the first time they experienced the system to the subsequent times. There was no change in drivers’ willingness to engage in tasks or drivers’ ability to perform tasks as they gained more experience with the Automated Driving system. However, the level of task engagement indicated that drivers were immediately willing to engage in tasks during Automated Driving. Drivers also showed a high-level of task performance. Taken together, these findings indicate that drivers are willing to engage in and perform non-driving related tasks during Automated Driving. These findings can help guide future research focused on automated systems and the design of automated driving systems.

京都大学 / 新制・課程博士 / 博士(工学) / 甲第25243号 / 工博第5202号 / 新制||工||1993(附属図書館) / 京都大学大学院工学研究科機械理工学専攻 / (主査)教授 小森 雅晴, 教授 細田 耕, 准教授 遠藤 孝浩, 教授 松野 文俊 / 学位規則第4条第1項該当 / Doctor of Agricultural Science / Kyoto University / DFAM

Real time systems have been a major area of study for many years. Advancements in electronics, computers, information technology and digital networks are fueling major changes in the area of real time systems. In this thesis, we look at some of the most commonly modeled real time task systems, such as the periodic task model, including more complex task models such as the sporadic task systems. Primary focus of researchers in these fields include how to guarantee hard real time requirement of any task specification, with the minimal utilization of available hardware resources. Advancement in technology has brought multi-cored architectures with shared memory and massively parallel computing devices within the reach of ordinary computer users. Hence, it makes sense to study existing and newer task models on a wide variety of hardware platforms. Periodic task model and systems with such task models have been designed and well understood. Newer models such as the sporadic task models have been proposed to capture a more larger variety of real time systems being designed and used. We focus on designing more efficient scheduling algorithms for the sporadic LL task model, and propose simpler proofs to some of the algorithms existing in current literature. This thesis also focuses on scheduling sporadic task systems, under both multiprocessor full-migration and multiprocessor partitioned scheme. We also provide approximation algorithms to efficiently determine feasibility of such task systems.

Pas de résumé / The thesis investigated the development of children’s global/local processing hierarchical patterns introduced by Navon (1977). The objectives were to understand more comprehensively the developmental characteristics of children’s perception through their global and local processing of hierarchical patterns, by considering the effects of age, stimuli properties, duration of exposure to the stimuli and gender in a perceptual task and a drawing task. These effects were tested in 3 different populations: typically developing children, children with mental retardation and early blind children. The results revealed that typically developing children attended to both the local and global level of processing but these modes of spatial information processing operated independently. In a first step, children before 4 years of age showed dominance of local processing and then a more global processing developed at 4 years of age, and at 5 years of age integrated responses began to emerge. Early blind children showed similar developmental characteristics, although there was a protracted period of local processing dominance. Indeed, these children mainly produced local responses at ages of between 6 and 10 years, and then developed more global responses at 11-12 years and continued to integrate the two levels of analysis at later ages. On the other hand, global dominance was shown in children with mental retardation and their development was affected more by mental age than by chronological age. Moreover, their responses were shown to be sensitive to the fact that meaningful object could be located at the local level, enhancing local processing in this case. These results need further confirmations as the studies of global/local processing in atypical children are not numerous. In particular, the effect of duration of exposure to the stimuli should be further analyzed, because this factor did not seem to have a great effect in our experiments while it seemed more powerful in other studies carried out with adults. Replication of the study with children with mental retardation appears also important to plan for future work, because we can have some doubt relatively the absence of modification through ages of the way these children perceive hierarchical patterns. Finally, defining more precisely what may underlie the gender differences seems also worth to explore since gender did not show a major effect in our results.

The thesis focuses on a new concept of cellular automata control based on instructions. The instruction can be understood as a rule that checks the states of cells in pre-defined areas in the cellular neighbourhood. If a given condition is satisfied, the state of the central cell is changed according to the definition of the instruction. Because it's possible to perform more instructions in one computational step, their sequence can be understood as a form of a short program. This concept can be extended with simple operations applied to the instruction's prescription during interpretation of the instructions - an example of such operation can be row shift or column shift. An advantage of the instruction-based approach lies in the search space reduction. In comparison with the table-based approach, it isn't necessary to search all the possible configurations of the cellular neighbouhood, but only several areas determined by the instructions. While the groups of the inspected cells in the cellular neighbourhood are designed manually on the basis of the analysis of the solved task, their sequence in the chromosome is optimized by genetic algorithm. The capability of the proposed method of cellular automata control is studied on these benchmark tasks - majority, synchronization, self-organization and the design of combinational circuits.

The aim of this study was to investigate the effect of irrelevant thoughts on golf performance.26 junior golfers participated in a repeated measures experiment where the effects ofirrelevant thoughts, through a working memory task, on golf performance was investigated.The participants got to hit 12 golf shots, 6 without working memory task and 6 with workingmemory task. A significant difference was found in both dependent variables lateral deviationand time. The participants had bigger lateral deviation and took longer time to complete theirshots when having a working memory task. The results from the study indicates thatirrelevant thoughts could impair junior golfers performance, although more research is neededon the subject for senior golfers. / Syftet med denna studie var att undersöka effekten av irrelevanta tankar på golfprestation. 26 juniorgolfare deltog i ett upprepat mätnings experiment där effekterna av irrelevanta tankar,genom ett arbetsminnestest, på golfprestation undersöktes. Deltagarna fick slå 12 golfslag, 6 utan arbetsminnestest och 6 med arbetsminnestest. En signifikant skillnad hittades i båda beroende variablerna spridning i sidled samt tid. Deltagarna hade större spridning och tog längre på sig att slå sina slag när de hade ett arbetsminnestest. Resultaten från studien indikerar att irrelevanta tankar kan försämra juniorgolfares prestation, däremot behövs vidareforskning kring ämnet för seniorgolfare.

Network on Chip (NoC) architectures provide scalable platforms for designing Systems on Chip (SoC) with large number of cores. Developing products and applications using an NoC architecture offers many challenges and opportunities. A tool which can map an application or a set of applications to a given NoC architecture will be essential. In this thesis we first survey current techniques and we present our proposals for mapping and scheduling of concurrent applications to NoCs with multithreaded processors as computational resources. NoC platforms are basically a special class of Multiprocessor Embedded Systems (MPES). Conventional MPES architectures are mostly bus-based and, thus, are exposed to potential difficulties regarding scalability and reusability. There has been a lot of research on MPES development including work on mapping and scheduling of applications. Many of these results can also be applied to NoC platforms. Mapping and scheduling are known to be computationally hard problems. A large range of exact and approximate optimization algorithms have been proposed for solving these problems. The methods include Branch-and–Bound (BB), constructive and transformative heuristics such as List Scheduling (LS), Genetic Algorithms (GA) and various types of Mathematical Programming algorithms. Concurrent applications are able to capture a typical embedded system which is multifunctional. Concurrent applications can be executed on an NoC which provides a large computational power with multiple on-chip computational resources. Improving the time performances of concurrent applications which are running on Network on Chip (NoC) architectures is mainly correlated with the ability of mapping and scheduling methodologies to exploit the Thread Level Parallelism (TLP) of concurrent applications through the available NoC parallelism. Matching the architectural parallelism to the application concurrency for obtaining good performance-cost tradeoffs is  another aspect of the problem. Multithreading is a technique for hiding long latencies of memory accesses, through the overlapped execution of several threads. Recently, Multi-Threaded Processors (MTPs) have been designed providing the architectural infrastructure to concurrently execute multiple threads at hardware level which, usually, results in a very low context switching overhead. Simultaneous Multi-Threaded Processors (SMTPs) are superscalar processor architectures which adaptively exploit the coarse grain and the fine grain parallelism of applications, by simultaneously executing instructions from several thread contexts. In this thesis we make a case for using SMTPs and MTPs as NoC resources and show that such a multiprocessor architecture provides better time performances than an NoC with solely General-purpose Processors (GP). We have developed a methodology for task mapping and scheduling to an NoC with mixed SMTP, MTP and GP resources, which aims to maximize the time performance of concurrent applications and to satisfy their soft deadlines. The developed methodology was evaluated on many configurations of NoC-based platforms with SMTP, MTP and GP resources. The experimental results demonstrate that the use of SMTPs and MTPs in NoC platforms can significantly speed-up applications.

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