  This paper presents a new ridesharing simulation platform that accounts for
dynamic driver supply and passenger demand, and complex interactions between
drivers and passengers. The proposed simulation platform explicitly considers
driver and passenger acceptance/rejection on the matching options, and
cancellation before/after being matched. New simulation events, procedures and
modules have been developed to handle these realistic interactions. The
capabilities of the simulation platform are illustrated using numerical
experiments. The experiments confirm the importance of considering supply and
demand interactions and provide new insights to ridesharing operations. Results
show that increase of driver supply does not always increase matching option
accept rate, and larger matching window could have negative impacts on overall
ridesharing success rate. These results emphasize the importance of a careful
planning of a ridesharing system.
