In order to drive effectively, a driver must be aware of how they can expect
other vehicles' behaviour to be affected by their decisions, and also how they
are expected to behave by other drivers. One common family of methods for
addressing this problem of interaction are those based on Game Theory. Such
approaches often make assumptions about leaders and followers in an interaction
which can result in conflicts arising when vehicles do not agree on the
hierarchy, resulting in sub-optimal behaviour. In this work we define a
measurement for the incidence of conflicts, Area of Conflict (AoC), for a given
interactive decision-making model. Furthermore, we propose a novel
decision-making method that reduces this value compared to an existing approach
for incorporating altruistic behaviour. We verify our theoretical analysis
empirically using a simulated lane-change scenario.Comment: 8 pages, 5 figures, submitted to RSS 2020: Interaction and
Decision-Making in Autonomous-Driving Worksho
