Abstract
In an optimally integrated HMS (Human Machine Systems) human and machine understand each other to provide an optimum integration. This is one of the core principles which is applicable for the research frameworks in vehicle navigation domain for effectively conducting research for creating optimal guidance information for the human driver. Creation and integration of human cognitive models for navigation is necessary to follow this principle effectively. BeaCON: Behaviour-and Context-Based Optimal Navigation is an existing research framework in the car navigation domain, for conducting analysis for the research problem “Giving the driver adequate navigation information with minimal interruption”. Currently BeaCON does not use the human cognitive models for navigation for the creation of guidance information and because of that the integration with the human driver is not achieved to an optimum level. In this paper, we present enhancement of BeaCON by integrating behaviour and cognitive models of navigation. Understanding the human thoughts while driving enables BeaCON to have a granular analysis of user cognitive state while creating guidance information, which results further cognitive load reduction for navigation tasks by creating more effective guidance information.
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Balakrishna, A., Gross, T. (2021). What Humans Might Be Thinking While Driving: Behaviour and Cognitive Models for Navigation. In: Krömker, H. (eds) HCI in Mobility, Transport, and Automotive Systems. HCII 2021. Lecture Notes in Computer Science(), vol 12791. Springer, Cham. https://doi.org/10.1007/978-3-030-78358-7_25
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DOI: https://doi.org/10.1007/978-3-030-78358-7_25
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