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A peer to peer ridesharing system connects drivers who are using theirpersonal vehicles to conduct their daily activities with passengers who arelooking for rides. A well-designed and properly implemented ridesharing systemcan bring about social benefits, such as alleviating congestion and its adverseenvironmental impacts, as well as personal benefits in terms of shorter traveltimes and or financial savings for the individuals involved. In this paper, thegoal is to study the impact of availability of carpool lanes and trafficconditions on ridesharing demand using an agent based simulation model. Agentswill be given the option to use their personal vehicles, or participate in aridesharing system. An exact many to many ride matching algorithm, where eachdriver can pick up and drop off multiple passengers and each passenger cancomplete his or her trip by transferring between multiple vehicle, is used tomatch drivers with passengers. The proposed approach is implemented in AnyLogicABS software with a real travel data set of Los Angeles, California. Theresults of this research will shed light on the types of urban settings thatwill be more recipient towards ridesharing services.

Impact of Traffic Conditions and Carpool Lane Availability on Peer to Peer Ridesharing Demand