Better Driving and Recall When In-car Information Presentation Uses Situationally-Aware Incremental Speech Output Generation

Abstract

It is established that driver distraction is the result of sharing cognitive resources between the primary task (driving) and any other secondary task. In the case of holding conversations, a human passenger who is aware of the driving conditions can choose to interrupt his speech in situations potentially requiring more attention from the driver, but in-car information systems typically do not exhibit such sensitivity. We have designed and tested such a system in a driving simulation environment. Unlike other systems, our system delivers information via speech (calendar entries with scheduled meetings) but is able to react to signals from the environment to interrupt when the driver needs to be fully attentive to the driving task and subsequently resume its delivery. Distraction is measured by a secondary short-term memory task. In both tasks, drivers perform significantly worse when the system does not adapt its speech, while they perform equally well to control conditions (no concurrent task) when the system intelligently interrupts and resumes.

A Multimodal In-Car Dialogue System That Tracks The Driver's Attention

“…Experiment 1 was performed in previous work presented in [14], but as the setup is a precursor, and the results are directly comparable to the work done Figure 4: Overview of our system: solid lines denote connections between hardware and software components, colours denote the workstations (in this case 4) that we used. Dashed lines denote network connections between components, arrows denote InstantIO connections, diamonds denote RSB connections.…”

“…Some stated that they would like to be able to control the system in some way (giving rise to Experiment 2). There were further results in Experiment 1 that are not of interest here and for which we refer the reader to [14].…”

A Interação Sonora Com Sistemas Embarcados Em Veículos

“…A proposta de Kennington et al, (2014) comparou duas interfaces de saída de voz e como elas afetam o desempenho das tarefas principal e secundária. Os autores propuseram uma interface adaptativa capaz de reconhecer os momentos nos quais o motorista precisa de mais atenção na via e capaz de interromper a saída de voz durante tal momento, com o objetivo de não distrair o condutor naquele período.…”

An Eye-Tracking Evaluation of Driver Distraction and Road Signs

“…OpenDS has been commonly used to measure drivers' reaction-times and behaviour (e.g., attention, workload) [30,38,61]. It has been used as an effective tool to measure the usability of different multi-modal interfaces [37,47], and to evaluate collaborative driving [7,46].…”

“…Kennington et al [36] developed a speech generation system which mimics human passenger conversations. The idea is for this system to recognize situations that require a driver's complete attention.…”