  Rideshare is one way to share mobility in transportation without increasing
traffic demand, where travel mobility and usage of vehicle capacity can be
improved. However, current literature on rideshare has allowed only one-modal
trips and may be limited in the matching efficiency, especially when there is a
large gap between the supply and demand of mobility. Therefore, the objectives
of this paper are first to develop a multi-modal matching framework of shared
mobility with public transportation to maximize the performance of a rideshare
system, and second to evaluate the effect of the public transportation and of
the schedule flexibility on the matching efficiency. To fulfill the first
objective, a multi-modal matching framework is developed to allow rideshare
with both private and public vehicles with detailed design of detour, using
Genetic Algorithm. Also for the second objective, the effects of public
transportation and schedule flexibility are evaluated with a simplified network
of Sioux Falls. The results show that public transportation helps the match
rate slightly at a low supply of private vehicle, but this must be evaluated
for practical implementation as different cities may bring different results.
Also, a larger schedule flexibility helps greatly in increasing match rate even
at a lower supply level. As well, the planning subject of time schedule is
benefited more with larger schedule flexibility, in this paper the drivers, on
the matching efficiency. Moreover, a rideshare system with private vehicles
outperforms a public transportation system, possibly due to the rigid route of
public transportation that takes no detour burden. This confirms the need for a
flexible design of sharing mobility, as can be fulfilled with the multi-modal
matching framework developed in this research.
