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Situational influencing factors on understanding cooperative actions in automated driving
•Scope of action, situation’s criticality and the way an intention is signalled influence willingness to cooperate.•Significant interaction for situation’s criticality and the way the intention was signalled.•Reaction time was shorter if situation’s criticality increased.•Future cooperative vehicles...
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Published in: | Transportation research. Part F, Traffic psychology and behaviour Traffic psychology and behaviour, 2020-04, Vol.70, p.223-234 |
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Main Authors: | , , |
Format: | Article |
Language: | English |
Subjects: | |
Citations: | Items that this one cites Items that cite this one |
Online Access: | Get full text |
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Summary: | •Scope of action, situation’s criticality and the way an intention is signalled influence willingness to cooperate.•Significant interaction for situation’s criticality and the way the intention was signalled.•Reaction time was shorter if situation’s criticality increased.•Future cooperative vehicles have to clearly indicate their intentions.
Cooperative interacting vehicles are a promising approach in the context of automated driving. To ensure understanding and acceptance of such systems, the underlying mechanisms of human cooperation in the context of traffic must be understood. In a driving simulator study, we investigated how situational factors influence cooperative behaviour in a lane change situation on a two-lane German highway during automated driving in the left lane. When another car in the right lane was approaching a slower truck, participants (N = 32) were asked by an automated system to either accelerate, decelerate or maintain speed. The driver’s scope of action, the situation’s criticality for the lane-changing vehicle and the display of intention to change lanes were manipulated. A hierarchical multinomial logistic regression revealed that a wider scope of action, a higher situation’s criticality and signalling the intention to change lanes positively influenced cooperative behaviour by accelerating and decelerating. These results might be applied to design user-centred automated cooperatively interacting vehicles. |
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ISSN: | 1369-8478 1873-5517 |
DOI: | 10.1016/j.trf.2020.03.006 |