  Ridepooling combines trips of multiple passengers in the same vehicle and may
thereby provide a more sustainable option than transport by private cars. The
efficiency and sustainability of ridepooling is typically quantified by key
performance indicators such as the average vehicle occupancy or the total
distance driven by all ridepooling vehicles relative to individual transport.
However, even if the average occupancy is high and rides are shared,
ridepooling services may increase the total distance driven due to additional
detours and deadheading. Moreover, these key performance indicators are
difficult to predict without large-scale simulations or actual ridepooling
operation. Here, we propose a dimensionless parameter to estimate the
sustainability of ridepooling by quantifying the load on a ridepooling service,
relating characteristic timescales of demand and supply. The load bounds the
relative distance driven and uniquely marks the break-even point above which
the total distance driven by all vehicles of a ridepooling service falls below
that of motorized individual transport. Detailed event-based simulations and a
comparison with empirical observations from a ridepooling pilot project in a
rural area of Germany validate the theoretical prediction. Importantly, the
load follows directly from a small set of aggregate parameters of the service
setting and is thus predictable a priori. The load may thus complement standard
key performance indicators and simplify planning, operation and evaluation of
ridepooling services.
