Queueing Network Based Driver Model for Varying Levels of Information Processing
| العنوان: | Queueing Network Based Driver Model for Varying Levels of Information Processing |
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| المؤلفون: | Myung Hwan Yun, Ye Lim Rhie, Ji Hyoun Lim |
| المصدر: | IEEE Transactions on Human-Machine Systems. 49:508-517 |
| بيانات النشر: | Institute of Electrical and Electronics Engineers (IEEE), 2019. |
| سنة النشر: | 2019 |
| مصطلحات موضوعية: | Visual search, 050210 logistics & transportation, Computer Networks and Communications, Computer science, 05 social sciences, Information processing, Eye movement, Human Factors and Ergonomics, Advanced driver assistance systems, Cognition, Cognitive architecture, Computer Science Applications, Human-Computer Interaction, Artificial Intelligence, Control and Systems Engineering, Human–computer interaction, 0502 economics and business, Signal Processing, Task analysis, Eye tracking, 0501 psychology and cognitive sciences, 050107 human factors |
| الوصف: | With growing interest in the topic of smart computing and context-aware services, identifying driver's intention has become important in automotive industry. Among existing studies on driver assistance systems, few studies have used the concept of the levels of processing (LOP) to understand driver's information processing. This paper introduces experimental and computational studies that connect human behavior data to internal goal of a driver when an in-vehicle task involves visual search. In the case of consuming information displayed on a car instrument cluster, we considered two levels of information processing, perceptual and cognitive. Through an empirical study, we observed different human oculomotor behaviors that depend on the LOP by evaluating the reaction time (RT) and eye movement patterns. Further, we suggested different ways of information processing that can be represented as different routes in the underlying cognitive architecture of a queueing network. Simulation study demonstrated that trends in simulated oculomotor behavior were similar to those observed in the experiment, that is, RT at the cognitive LOP was shorter than that at the perceptual LOP, while eyes fixated for shorter duration and with lower frequency. In terms of application, this study reveals the possibility of using human-generated data for evaluating the innate purposes of drivers. Together with further development of sensors and invasive computing, the approach proposed in this paper could assist the realization of cognitive cars by understanding drivers’ intent using eye tracking technology. |
| تدمد: | 2168-2305 2168-2291 |
| DOI: | 10.1109/thms.2018.2874183 |
| URL الوصول: | https://explore.openaire.eu/search/publication?articleId=doi_________::65500b0ac735831daf40624c9a6dff8a https://doi.org/10.1109/thms.2018.2874183 |
| Rights: | CLOSED |
| رقم الانضمام: | edsair.doi...........65500b0ac735831daf40624c9a6dff8a |
| قاعدة البيانات: | OpenAIRE |
| تدمد: | 21682305 21682291 |
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| DOI: | 10.1109/thms.2018.2874183 |