Ridesharing systems can significantly improve the efficiency of transportation systems by utilizing unused spaces in a vehicle while at the same time providing cheap, flexible and convenient commute options to urban passengers. Several studies have shown that ridesharing has the potential to reduce traffic congestion and pollution while increasing commuter flexibility. A few commercial ride sharing services already exist that provide on-demand rides to their customers. However, research shows that commercial ridesharing exacerbates the traffic congestion in urban areas by increasing traffic and dead-head miles. One alternative is carpool ridesharing where the drivers are regular commuters who pick up and deliver other commuters to their destination with the hope of recouping some of their travel costs at the price of increasing travel time.
A big obstacle in planning a carpool ridesharing system is the uncertainty that is inherent in the system. These uncertainties typically arise due to unknown road conditions that affect travel time and passenger or driver cancellations that result in uncertain demand and capacity of the system. Uncertainties also occur due to the passengers possibly having flexible pickup and drop-off locations. Although previous literature on ride-sharing systems have incorporated these sources of uncertainties individually, there is a lack of literature that focuses on all three sources of uncertainties together. Since these uncertainties are inherent to the system it is important to consider them in conjunction. The purpose of this research is to provide a ride-sharing planning scheme that will consider all three sources of uncertainties to provide a robust travel plan while at the same time reducing travel time for the commuters. This research will also focus on having common pickup and drop-off points for multiple passengers that will reduce detours and the use of HOV lanes which will reduce the total traveling time of the commuters.