  Cities around the world vary in terms of their transportation networks and
travel demand patterns; these variations affect the viability of shared
mobility services. This study proposes metrics to quantify the shareability of
person-trips in a city, as a function of two inputs--the road network structure
and origin-destination (OD) travel demand. The study first conceptualizes a
fundamental shareability unit, 'flow overlap'. Flow overlap denotes, for a
person-trip traversing a given path, the weighted (by link distance) average
number of other trips sharing the links along the original person's path. The
study extends this concept to the network level and formulates the Maximum
Network Flow Overlap Problem (MNFLOP) to assign all OD trips to paths that
maximize network-wide flow overlap. The study utilizes the MNFLOP output to
calculate metrics of shareability at various levels of aggregation: person-trip
level, OD level, origin or destination level, network level, and link level.
The study applies the MNFLOP and associated shareability metrics to different
OD demand scenarios in the Sioux Falls network. The computational results
verify that (i) MNFLOP assigns person-trips to paths such that flow overlaps
significantly increase relative to shortest path assignment, (ii) MNFLOP and
its associated shareability metrics can meaningfully differentiate between
different OD trip matrices in terms of shareability, and (iii) an MNFLOP-based
metric can quantify demand dispersion--a metric of the directionality of
demand--in addition to the magnitude of demand, for trips originating or
terminating from a single node in the network. The paper also includes an
extensive discussion of potential future uses of the MNFLOP and its associated
shareability metrics.
