  Nowadays, ridesharing becomes a popular commuting mode. Dynamically arriving
riders post their origins and destinations, then the platform assigns drivers
to serve them. In ridesharing, different groups of riders can be served by one
driver if their trips can share common routes. Recently, many ridesharing
companies (e.g., Didi and Uber) further propose a new mode, namely "ridesharing
with meeting points". Specifically, with a short walking distance but less
payment, riders can be picked up and dropped off around their origins and
destinations, respectively. In addition, meeting points enables more flexible
routing for drivers, which can potentially improve the global profit of the
system. In this paper, we first formally define the Meeting-Point-based Online
Ridesharing Problem (MORP). We prove that MORP is NP-hard and there is no
polynomial-time deterministic algorithm with a constant competitive ratio for
it. We notice that a structure of vertex set, $k$-skip cover, fits well to the
MORP. $k$-skip cover tends to find the vertices (meeting points) that are
convenient for riders and drivers to come and go. With meeting points, MORP
tends to serve more riders with these convenient vertices. Based on the idea,
we introduce a convenience-based meeting point candidates selection algorithm.
We further propose a hierarchical meeting-point oriented graph (HMPO graph),
which ranks vertices for assignment effectiveness and constructs $k$-skip cover
to accelerate the whole assignment process. Finally, we utilize the merits of
$k$-skip cover points for ridesharing and propose a novel algorithm, namely
SMDB, to solve MORP. Extensive experiments on real and synthetic datasets
validate the effectiveness and efficiency of our algorithms.
