  A peer to peer ridesharing system connects drivers who are using their
personal vehicles to conduct their daily activities with passengers who are
looking for rides. A well-designed and properly implemented ridesharing system
can bring about social benefits, such as alleviating congestion and its adverse
environmental impacts, as well as personal benefits in terms of shorter travel
times and or financial savings for the individuals involved. In this paper, the
goal is to study the impact of availability of carpool lanes and traffic
conditions on ridesharing demand using an agent based simulation model. Agents
will be given the option to use their personal vehicles, or participate in a
ridesharing system. An exact many to many ride matching algorithm, where each
driver can pick up and drop off multiple passengers and each passenger can
complete his or her trip by transferring between multiple vehicle, is used to
match drivers with passengers. The proposed approach is implemented in AnyLogic
ABS software with a real travel data set of Los Angeles, California. The
results of this research will shed light on the types of urban settings that
will be more recipient towards ridesharing services.
