In-Car Media Search (original) (raw)

A comparison between spoken queries and menu-based interfaces for in-car digital music selection

2005

Abstract. Distracted driving is a significant issue for our society today, and yet information technologies, including growing digital music collections, continue to be introduced into the automobile. This paper describes work concerning methods designed to lessen cognitive load and distracting visual demands on drivers as they go about the task of searching for and listening to digital music.

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Visual and Cognitive Demands of Using In-Vehicle Infotainment Systems

2017

The features of vehicle-based infotainment technology have greatly expanded in recent years, opening up a new array of tasks accessible to motorists while driving. Many of these new functions are unrelated to driving. Examples include voice commands to send a text message, check social media or surf the web. Furthermore, many tasks distract motorists from driving by diverting their eyes and attention from the road and hands from the steering wheel. Yet, surprisingly, little is known about how these interactions may affect a driver’s performance when the demands are high.

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The Impact of an Adaptive User Interface on Reducing Driver Distraction

This paper discusses the impact of an adaptive prototype in-car communication system (ICCS), called MIMI (Multimodal Interface for Mobile Info-communication), on driver distraction. Existing ICCSs attempt to minimise the visual and manual distraction, but more research needs to be done to reduce cognitive distraction. MIMI was designed to address usability and safety issues with existing ICCSs. Few ICCSs available today consider the driver’s context in the design of the user interface. An adaptive user interface (AUI) was designed and integrated into a conventional dialogue system in order to prevent the driver from receiving calls and sending text messages under high distraction conditions. The current distraction level is detected by a neural network using the driving speed and steering wheel angle of the car as inputs. An adaptive version of MIMI was compared to a non-adaptive version in a user study conducted using a simple driving simulator. The results obtained showed that the adaptive version provided several usability and safety benefits, including reducing the cognitive load, and that the users preferred the adaptive version.

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Using Artificial Intelligence to Automatically Customize Modern Car Infotainment Systems

International Conference on Artificial Intelligence (ICAI), 2016

In the last decade the automotive industry added digital features to their new cars, including advanced interactive infotainment system. Drivers execute several secondary tasks simultaneously besides the essential driving tasks. More complex infotainment system needs more cognitive attention causing more driver distraction. A consensus from multiple driver distraction research is that multi-tasking causes impaired performance. Although drivers know that distraction is a major reason of car accidents, they continue doing distracting activities during driving. In this paper we introduce a customized user interface instead of a standard user interface to reduce response time and hence driver distraction. While it is hard to directly measure cognitive-related distraction, events that take longer response time by the driver indicate a higher cognitive load as the user needs more time to perceive, analyze and comprehend when compared to simple events. Our hypothesis is that a reduction in the driver's response time while using infotainment system can indicate a reduction in driver distraction

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In-Car Media Search (original) (raw)

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