Pooling in Ridesharing using Meeting Points

Ridesharing, a recent popular mode of transportation where two or more travelers following similar routes and schedules share a car to gain benefits in terms of monetary, comfort, door to door service etc. GPS technology, smartphones and ridesharing apps altogether have made it convenient and efficient for strangers to get matched in real-time for sharing a trip. In reality, this transportation mode is more of like on-demand taxi services. To attain more benefit in term of matching rate and distance savings, this paper introduces meeting point concept to motivate ride pooling or group sharing. To be more specific, meeting point is a common meet up point, to where riders might need to go by walking, from where driver can pick them up all at once given that riders and drivers meets time and distance feasibility. For this we propose time feasibility and distance feasibility conditions to find possible match lists. To find out the optimal match pairs or groups we introduce a mathematical optimization model that finds optimal groups on the fly. For implementing the whole framework, we take help of open source Python Programming language and Gurobi optimizer. We test our model with open source data sets of Chengdu city, China. The introduction of meeting points improves the matching rate and occupancy rate which implies meeting point opens the door for ride pooling with group matching.