Ridesharing with Passenger Transfers

— Recently, ridesharing mobile applications, which dynamically match passengers to drivers, have begun to gain popularity. These services have the potential to fill empty seats in cars, reduce emissions and enable more efficient transportation. Ridesharing services become even more practical as robotic cars become available to do all the driving. In this work, we propose rideshare services which transfer passengers between multiple drivers. By planning for transfers, we can increase the availability and range of the rideshare service, and also reduce the total vehicular miles travelled by the network. We propose three heuristic algorithms to schedule rideshare routes with transfers. Each gives a tradeoff in terms of effectiveness and computational cost. We demonstrate these tradeoffs, both in simulation and on data from taxi passengers in San Francisco. We demonstrate scenarios where transferring passengers can provide a significant advantage.