Optimal Rebalancing With Waiting Time Constraints For A Fleet Of Connected Autonomous Taxi

A fleet of cooperative autonomous taxi is an emerging application of IoT in transportation industry. Unlike manned taxis that cruise on roads uncoordinated and often compete for passengers, autonomous vehicle can move cooperatively to transport passengers more efficiently. In this paper, we present a case study on an IoT application of new cooperative management technique for a fleet of autonomous taxi. In transportation network, optimal rebalancing allows sustainable flow of vehicle with a minimum number of vehicle to transport passengers flows in uneven directions. However, long waiting time to board a taxi during peak hours degrades quality of service. To tackle this issue, we extend recent advances in autonomous mobility-on-demand solution to incorporate waiting time policy. Specifically, we introduce stability and control of passenger's queues in the optimal rebalancing to confine the queues (thus waiting time in queues) to a specified range. We validate our new technique via data-driven simulations of a fleet of autonomous taxi by leveraging on Singapore's taxi dataset. Data-driven simulations demonstrate promising results of the new technique in ensuring efficient and low waiting time of taxi service for passengers.