  Lane merging is one of the critical tasks for self-driving cars, and how to
perform lane-merge maneuvers effectively and safely has become one of the
important standards in measuring the capability of autonomous driving systems.
However, due to the ambiguity in driving intentions and right-of-way issues,
the lane merging process in autonomous driving remains deficient in terms of
maintaining or ceding the right-of-way and attributing liability, which could
result in protracted durations for merging and problems such as trajectory
oscillation. Hence, we present a rule-compliance path planner (RCPP) for
lane-merge scenarios, which initially employs the extended
responsibility-sensitive safety (RSS) to elucidate the right-of-way, followed
by the potential field-based sigmoid planner for path generation. In the
simulation, we have validated the efficacy of the proposed algorithm. The
algorithm demonstrated superior performance over previous approaches in aspects
such as merging time (Saved 72.3%), path length (reduced 53.4%), and
eliminating the trajectory oscillation.
