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Bridging system limits with human–machine-cooperation
Bridging system limits with human–machine-cooperation
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Bridging system limits with human–machine-cooperation
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Bridging system limits with human–machine-cooperation
Bridging system limits with human–machine-cooperation

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Bridging system limits with human–machine-cooperation
Bridging system limits with human–machine-cooperation
Journal Article

Bridging system limits with human–machine-cooperation

2024
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Overview
Highly automated vehicles are subject to high expectations, encompassing safety improvements, efficiency in traffic flow and overall higher comfort. However, it is still unclear to what extent automation will be able to meet these expectations. Failures in sensors or erroneous data processing might bring an automated drive to a sudden stop. In such situations, the user of the vehicle could cooperate with the automated vehicle, to bridge system limits and directly continue the drive. How this cooperation process should be implemented and how much the vehicle user wants to be involved in this process is examined. In this paper, we investigate four different cooperation strategies, ranging from low involvement of the user in the driving task (pressing a button to continue the drive) to high involvement (performing the entire driving task with steering wheel and pedals). Participants experienced these strategies in a driving simulator, in which they encountered five inner city traffic scenarios where the automation reached its limits. The cooperation strategies were evaluated along the dimensions comfort, discomfort, mental demand, usability, perceived safety, trust in automation, personal benefit, and personal preference. As a main result, strategies with less involvement show increases in comfort and personal benefit as well as decreases in discomfort and mental demand. Further, perceived safety was rated highly for all strategies. In traffic scenarios perceived as more unsafe, strategies with higher involvement are preferred. This paper offers insights into user involvement in cooperative human machine interfaces, potentially enhancing the application of automated driving in urban traffic.