TASeT: Improving the Efficiency of Electric Taxis with Transfer-Allowed Rideshare

We consider a promising application for electric taxis (eTaxis) in transportation cyberphysical systems. The new rideshare scheme introduced herein takes into consideration both the limited battery of eTaxis and the user requirements. In the proposed eTaxi-sharing system, a passenger may share a taxi with others to enjoy a reduced fare and can potentially transfer from one eTaxi to another before reaching her destination, as long as her total trip time is within the maximum she specifies to be tolerable. Transfers are restricted to only take place at the designated (safe and convenient) battery charging stations scattered around the city. When an eTaxi comes to a charging station to pick up/drop off a transfer passenger, the eTaxi's battery can be charged. In this paper, we address a new optimization problem called Transfer-Allowed Shared eTaxis (TASeT), whose goal is to schedule an eTaxis service and find optimal rideshare and transfer plans to maximize the system throughput in terms of the number of passengers served by the taxi service within a given time period. A mixed-integer programming (MIP) formulation is presented to solve TASeT, along with an efficient greedy heuristic. Aside from large-scale simulation, we also present a case study that utilizes real taxi traces collected from the city of Shanghai, China. Compared with the nontransferable taxi-sharing (NTT) case, our solution could improve the number of served passengers and shared travel distance by 22% and 37%, respectively, during rush hours.